RiceCAP Cumulative Project Report - University of …...RiceCAP Cumulative Project Report January 12, 2009 San Diego, CA Applied Plant Genomics Coordinated Agricultural Project A coordinated

RiceCAP CumulativeProject Report

January 12, 2009San Diego, CA

Applied Plant GenomicsCoordinated Agricultural Project

A coordinated research,education, and extension project

for the application of genomic discoveriesto improve rice in the United States

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TABLE OF CONTENTS

1. RICECAP PRINCIPAL INVESTIGATORS AND INSTITUTIONS . . . . . . . . . . . . 1

2. MEETING AGENDA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

3. RICECAP EXECUTIVE SUMMARY (January 2009)Jim Correll-University of Arkansas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

4. RICECAP ON THE WEB . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

5. OBJECTIVE TEAMS - PRINCIPAL INVESTIGATORS AND COOPERATORS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

6. OBJECTIVE 1 - BREEDING EFFORTA. Introduction (Anna McClung, USDA-ARS, DBNRRC) . . . . . . . . . . . . . . . . . . . . 16B. Overview of project results

1. Sheath Blighta) SB1 (Robert Fjellstrom, USDA-ARS, DBNRRC)

(1) Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17(2) Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17(3) Genotyping . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18(4) QTL Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18(5) Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18(6) Deliverables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18(7) Future . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

b) SB2 (Jim Oard, LSU AgCenter)(1) Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18(2) Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19(3) Genotyping . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19(4) QTL Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19(5) Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20(6) Deliverables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20(7) Future . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

c) SB4 (Shannon Pinson, USDA-ARS Rice Research Unit)(1) Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21(2) Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22(3) Genotyping . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22(4) QTL Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22(5) Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22(6) Deliverables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23(7) Future . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

d) SB5 (Yulin Jia, USDA-ARS, DBNRRC)(1) Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24(2) Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24(3) Genotyping . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

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(4) QTL Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25(5) Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25(6) Deliverables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26(7) Future . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28

e) SB6 (Steve Brooks, USDA-ARS, DBNRRC)(1) Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28(2) Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28(3) Genotyping . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29(4) QTL Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29(5) Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29(6) Deliverables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29(7) Future . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

f) Wild (Georgia Eizenga, USDA-ARS, DBNRRC)(1) Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29(2) Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30(3) Genotyping . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31(4) QTL Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31(5) Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31(6) Deliverables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32(7) Future . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32

g) Synthesis (Yulin Jia, USDA-ARS, DBNRRC) . . . . . . . . . . . . . . . . . . 322. Milling Yield

a) MY1 (Anna McClung, USDA-ARS, DBNRRC)(1) Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34(2) Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34(3) Genotyping . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34(4) QTL Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34(5) Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34(6) Deliverables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35(7) Future . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

b) MY2 (Clare Nelson, Kansas State University)(1) Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35(2) Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35(3) Genotyping . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35(4) QTL Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36(5) Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38(6) Deliverables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38(7) Future . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38

c) MY3 (Farman Jodari, California Cooperative Rice Research Foundation)(1) Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39(2) Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39(3) Genotyping . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39(4) QTL Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40(5) Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40(6) Deliverables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40(7) Future . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40

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d) Synthesis (Clare Nelson, Kansas State University) . . . . . . . . . . . . . . . 41(1) Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41(2) Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41(3) Genotyping . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41(4) QTL Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41(5) Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42(6) Deliverables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42(7) Future . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42

3. Association Mapping (Brian Scheffler, USDA-ARS MSA GenomicsLaboratory)

a) Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42b) Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43c) Genotyping . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43d) Association Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43e) Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43f) Deliverables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43g) Future . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43

4. Germplasm (Anna McClung, USDA-ARS, DBNRRC) . . . . . . . . . . . . . . . . 445. Markers (Robert Fellstrom-USDA-ARS, DBNRRC, Brian

Scheffler-USDA-ARS MSA Genomics Laboratory, & Anna McClung,USDA-ARS, DBNRRC) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44

7. OBJECTIVE 2 - CANDIDATE GENES EFFORTA. Introduction (Yinong & Guo-Liang) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46B. Overview of Project Results (Yinong Yang-Pennsylvania State University,

Guo-liang Wang-Ohio State University, Jan Leach-Colorado State University, & Pam Ronald-University of California-Davis)

1. RL-SAGE and microarray analysis of the rice transcriptome after Rhizoctonia solani infection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46

2. Identification of milling yield related genes in the developing rice seeds using massively parallel signature sequencing . . . . . . . . . . . . . 47

3. Functional validation of candidate genes associated with sheathblight resistance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48

a) OsGLP genes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48b) OxOXO genes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49c) OsCHI genes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49d) JAmyb . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49e) OxEIN2, OsCOI1 and OxMPK5 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49f) OxGBP and OsGST . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49g) Other transgenic lines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49

4. Sheath blight disease assay and real-time PCR quantification . . . . . . . . . . . 495. Initiation of transcriptome and secretome analyses of R. solani . . . . . . . . . 406. OryzaSNP project . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50

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8. BIOINFORMATICSA. Overview (Clare Nelson, Kansas State University) . . . . . . . . . . . . . . . . . . . . . . . . 51B. Data Center (Clare Nelson, Kansas State University) . . . . . . . . . . . . . . . . . . . . . . 51C. Organization (Clare Nelson, Kansas State University) . . . . . . . . . . . . . . . . . . . . . 51D. Protected Data (Clare Nelson, Kansas State University) . . . . . . . . . . . . . . . . . . . . 51E. Reference Maps (Clare Nelson, Kansas State University) . . . . . . . . . . . . . . . . . . 52F. QTL Analysis (Clare Nelson, Kansas State University) . . . . . . . . . . . . . . . . . . . . 53G. QTL-Mapping Software (Clare Nelson, Kansas State University) . . . . . . . . . . . . 53H. Data Use (Clare Nelson, Kansas State University) . . . . . . . . . . . . . . . . . . . . . . . . 53

9. OBJECTIVE 3 - TECHNICAL TRAINING EFFORTJim Correll-University of Arkansas, Peggy G. Lemaux-University of

California-Berkeley, & Rick Cartwright-University of Arkansas CooperativeExtension Service

A. Technical Training Workshops . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 541. RiceCAP Marker Assisted Breeding Workshop . . . . . . . . . . . . . . . . . . . . . . 542. RiceCAP Virus-Induced Gene Silencing and Stable RNAi Workshop . . . . 543. RiceCAP DNA Marker Workshop . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54

B. Other Workshops . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54C. Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55

RiceCAP Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55

10. OBJECTIVE 4 - OUTREACH / EXTENSION EFFORTPeggy G. Lemaux-University of California-Berkeley, & Rick Cartwright-University

of Arkansas Cooperative Extension ServiceA. Benchmarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61B. Accomplishments on each benchmark in Years 1 through 4 . . . . . . . . . . . . . . . . . 61C. Integration with other CAP projects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81D. Funded personnel involved . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82E. Deliverables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82

11. COLLABORATIVE EFFORTS AS A RESULT OF RICECAPGeorgia Eizenga, USDA-ARS, DBNRRC

A. New Collaborations Amongst RiceCAP Participants . . . . . . . . . . . . . . . . . . . . . . 83B. External Interactions and Funding Efforts Related to RiceCAP . . . . . . . . . . . . . . 84

12. NEW TECHNOLOGIES PURSUED AS A RESULT OF RICECAPBrian Scheffler-USDA-ARS MSA Genomics Laboratory . . . . . . . . . . . . . . . . . . 85

13. PUBLICATIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90

14. ABSTRACTS AND SCIENTIFIC PRESENTATIONS . . . . . . . . . . . . . . . . . . . . . . 95

15. PERSONNEL . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103

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1. RICECAP PRINCIPAL INVESTIGATORS AND INSTITUTIONS

Donn Beighley Southeast Missouri State UniversitySteve Brooks USDA-ARS, Dale Bumpers National Rice Research CenterRick Cartwright Arkansas Cooperative Extension ServiceFernando Correa RiceTec (formerly of CIAT, Colombia, South America)Jim Correll University of ArkansasGeorgia Eizenga USDA-ARS Dale Bumpers National Rice Research CenterRobert Fjellstrom USDA-ARS Dale Bumpers National Rice Research CenterScot Hulbert Washington State UniversityYulin Jia USDA-ARS Dale Bumpers National Rice Research CenterFarman Jodari California Cooperative Rice Research FoundationDwight Kanter MSU Delta Research and Extension Center, Stoneville, MSKen Korth University of ArkansasJan Leach Colorado State UniversityPeggy Lemaux University of California-BerkeleySally Leong USDA-ARS, CCRU, Madison, WIAnna McClung USDA-ARS, Dale Bumpers National Rice Research CenterKaren Moldenhauer University of Arkansas Rice Research & Extension CenterClare Nelson Kansas State UniversityHenry Nguyen University of Missouri-ColumbiaJim Oard LSU AgCenterShannon Pinson USDA-ARS Rice Research UnitPam Ronald University of California-DavisBrian Scheffler USDA-ARS MSA Genomics LaboratoryHerry Utomo LSU Rice Research StationGuo-Liang Wang Ohio State UniversityYinong Yang Pennsylvania State University

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2. MEETING AGENDA

The RiceCAP meeting format will be similar to last year’s and will consist of an overview of theproject followed by presentations for each of the 4 objectives and the bioinformatics effort of theRiceCAP Project by the objective team leaders. In the interest of time, the format has beenconsolidated to cover the project details by the objective team leaders rather than have all of thePI’s give individual presentations.

Monday, January 12, 2009

USDA/CSREES - RiceCAP Annual Meeting to the Advisory BoardsPresentations: 8:00 am – 1:00 pmBoard Meeting: 2:00 pm – 4:30 pmBoard Reports to the RiceCAP group: 5:00 – 6:00Location: The Town & Country Resort Hotel; San Diego, CARoom: Windsor Rose

7:00am – 7:45am COFFEE AND SNACKS7:30am – 8:00am Load PowerPoint Presentations!8:00am – 8:30am Jim Correll, Project Director, University of Arkansas

Welcome and Introduction: Meeting itinerary, project final stages,project progress and completion, budget completion, and RiceCAP II

Objective Reports9:00am – 9:40am Anna McClung, USDA-ARS, Beaumont, TX

Jim Oard, Louisiana State UniversityObjective 1: Project progress overview and project completion,update, past, present and future deliverables

9:40am – 10:20am Yinong Yang, Pennsylvania State UniversityObjective 2: Project progress overview and project completion,update, past, present and future deliverables

10:20am – 10:40am COFFEE BREAK

10:40am – 11:10am Clare Nelson, Kansas State UniversityBioinformatics: Project progress overview and project completion,update, past, present and future deliverables

11:10am – 11:30am Jim Correll, Project Director, University of ArkansasObjective 3: Educational Workshops for RiceCAP

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11:30am – 12:00pm Rick Cartwright, U of A-Cooperative Extension ServicePeggy Lemaux, University of California-BerkeleyObjective 4: Outreach project progress overview and projectcompletion, update, past, present and future deliverables

12:00pm – 1:00pm Jim Correll, Project Director, University of ArkansasGeneral Discussion / Questions

1:00pm BREAK

2:00pm – 4:00pm Advisory Board Meeting4:30pm – 5:00pm Board Discussion with Jim Correll5:00pm – 6:00pm Board Reports to RiceCAP PIs

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3. RICECAP EXECUTIVE SUMMARY (January 2009)

In 2003, US rice breeders met with industry stakeholders and developed a prioritized list ofresearchable issues that could be addressed using a genomics approach. From that discussion themain objectives of this project were developed and two traits that have major impact on farmersand processors were identified. The general scientific objectives of the RiceCAP projectincluded developing genetic markers that are closely linked to QTL-controlling milling qualityand resistance to sheath blight disease, and to transfer marker-assisted selection (MAS)technology to US rice breeding programs.

In January 2005, the RiceCAP project was initiated with the overarching goal to fosterresearch cooperation among the majority of the public and private rice breeders and the riceresearchers and molecular biologists in the United States to accomplish the scientific objectives.The project objectives have focused on two economically important traits to the U.S. riceindustry: milling yield and sheath blight disease resistance. Two additional objectives involveda training and educational effort to broaden the technical expertise among US students andtechnical staff working on rice, and an extension and outreach effort to communicate the benefitsof biotechnology and genomics to the broader rice community.

RiceCAP was a multi-state multi-institutional effort administered through the University ofArkansas Agricultural Experiment Station. Over the past four years, the PI's involved inRiceCAP have communicated the project progress through refereed publications and bookchapters, scientific abstracts and presentations, and annual Advisory Board meetings. Additionaldeliverables have included the development of rice germplasm within the various mappingpopulations, molecular markers added to the various rice genome maps available on theRiceCAP website, technical training of rice personnel in the US, and the communication ofbiotechnology efforts to the general rice community. The following report is a detailed outline ofthe project progress and documentation of the resultant deliverables over the past four years. Theproject will be completed in August 2009.

The two major scientific objectives being addressed as part of the RiceCAP effort were: (1)identify and use candidate genes and other molecular markers linked to quantitative trait lociwhich control milling quality and resistance to sheath blight disease, and (2) validate thefunction of candidate genes associated with milling quality and sheath blight resistance.

Significant progress has been made in molecular genetic studies of rice sheath blightresistance (SB). These accomplishments include improved phenotyping methods, improvedgenetic stocks that contain major SB-QTL, identification of resistant wild rice relatives, and highdensity genetic maps showing major and minor effect of SB-QTLs integrated with expressionprofiles, and robust mapping populations derived from rice cultivars adapted to the US.

Accurate phenotyping for sheath blight resistance, caused by Rhizoctonia solani, was oneof the major constraints for genetic studies on this complex quantitative trait, and advances inthis area occurred with the development of a standardized greenhouse screening technique. Animproved and standardized greenhouse "micro-chamber" method was developed and allowed foraccurate phenotyping for sheath blight resistance in just 7 days so that the phenotypicmeasurement for mapping is independent of height, plant architecture, and heading duration thatare known to confound prior QTL mapping projects. Successful utilization and adaptation of thismethod has accelerated overall progress on the identification of novel resistant resources fromwild relatives of rice and confirmation of engineered resistance for determination of thefunctional contribution of candidate genes. In collaboration with CIAT, this phenotyping method

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was ultimately transferred to CIAT in Colombia and several National Rice Research Programs inother Latin American countries for the evaluation of sheath blight as well as other rice diseases.The major breakthrough of the sheath blight mapping effort is the identification and confirmationof a SB-QTL with major effect. The major effect QTL, qSB9-2, at the bottom of chromosome 9,contributes more than 20% of the measured (phenotypic) disease severity. This QTL has beenidentified in four mapping populations, SB1, SB2, SB4, and SB5, across all tested environments,including the use of the micro-chamber phenotyping method. The major qSB9-2 QTL maps to asimilar location seen to harbor SB-QTLs in studies involving indica/japonica crosses (TAG.1995, 91: 382-388; Crop Sci. 2005, 45: 503-510) and a tropical japonica intercross (in RiceCAPSB1; Sharma et al. in press, Crop Sci. 2009). Confirmation of qSB9-2 is a significantadvancement in the quest for genetic resistance to sheath blight disease. Identification of 400highly and differentially expressed rice genes from the cultivar Jasmine 85 in response to theearly infection by R. solani by DNA microarray and SAGE has provided a critical platform forfine mapping. Some of these highly and differentially expressed genes have been mapped atqSB9-2 and at other minor effect QTLs. Within SB4, an additional mapping population, markersaturation (cM distances < 0.5) was achieved in the region of qSB9-2 and 47 progeny linescontaining new recombination points within this region have been identified to supportcontinued efforts to fine map this QTL. Additional molecular markers are being developed fromcandidate genes to delineate the physical location. Nevertheless, molecular markers RM245 andRM215 associated with qSB9-2 can now be used to monitor the introgression of qSB9-2 fromthe rice cultivar Jasmine 85 into elite breeding lines for pyramiding genetic resistance to thesheath blight pathogen. New recombination around a second SB-QTL, qSB12-1, on chromosome12 has also been identified in 35 progeny lines from SB4 to support fine mapping of this QTL.Other minor effect QTLs identified on other chromosomes can now be monitored. Together,these confirmed and newly identified SB-QTL present an excellent opportunity for determiningthe contribution of individual QTL to sheath blight resistance and validation of candidate genesusing tools developed by the team members in objective 2.

Absence of germplasm with complete resistance to the sheath blight pathogen in cultivatedrice worldwide has made wild relatives of rice (Oryza species) an attractive alternative toidentify novel sources of genetic resistance. The major accomplishment in this aspect is theidentification of seven moderately resistant accessions of Oryza species. These newly identifiedwild rice relatives may contain novel SB-QTLs. Research is underway to identify these novelSB-QTLs and incorporate them into rice varieties adapted to the US. Because the infectionprocess of R. solani is complex, little is known about the effect of the fungal extracts includingthe host specific toxin to the host plant. Another important accomplishment is the isolation oftoxin that induces robust phenotypic responses on the leaves of rice cultivars. Purified toxin hasbeen used to determine genetic factors that contribute to the sheath blight resistance.

Considerable effort should be directed toward fine mapping and ultimately cloning qSB9-2for a better understanding of the molecular mechanisms of sheath blight resistance. Futureresearch should utilize the numerous improved genetic stocks in combination with robustmolecular markers, such as RM215 and RM245, for marker assisted introgression to capture afavorable plant architecture based on tiller angle, plant height and heading duration to reachmaximum yield potential. Effort should be expended to continue identification and stacking ofnew resistance sources from wild species into diverse elite lines for the development of bothconventional and novel methods to manage the sheath blight disease in rice.

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Three mapping populations have been developed by RiceCAP for QTL analysis ofhead-rice yield (HRY) and related grain-quality traits. All of these materials are U.S. cultivars orbreeding lines, with crosses selected for divergent HRY between parents and similarity of otherkernel dimension and quality characteristics to minimize confounding with HRY variation.

Standard QTL analyses applied to MY1 and MY2 showed putative HRY QTLs, butexpressed in not all environments (location-year combinations). In particular, in MY2 all fourQTLs expressed in Louisiana appear to be identical with heading-date QTLs, so that inLouisiana, but not in Arkansas, earliness QTL alleles (3 Cypress, one LaGrue) confer higherHRY. A more elaborate analysis of MY2 incorporating weather covariates such as temperatureand humidity during selected grain-filling stages for each RIL, harvest moisture content, percentchalky kernels, and percent green kernels supports a mechanism of avoidance of high nightimetemperatures during the hard-dough stage. Harvest moisture did not affect HRY when theweather covariates were in the model, suggesting that the effect on milling yield had alreadybeen exerted at the time of harvest. For MY1, QTL analysis suggests at least two other QTLs,one associated with early heading in Louisiana. However, no Cypress QTLs are common tothese two Cypress crosses. Preliminary QTL analysis of MY3 based on one year of fieldevaluation and 95 SSRs shows no association of HRY QTLs with heading-date QTLs, consistentwith observation that in California different environmental factors affect HRY than in thesouthern rice-growing regions.

Our analyses provide up to five QTLs that together account partially for the HRYsuperiority of Cypress over two other parents in certain growing environments. After sufficientvalidation, the linked markers could be used for combination of the QTL alleles (three fromCypress, one each from LaGrue and RT0034) to develop cultivars with higher and more stablehead-rice yield. It must be emphasized that the most plausible of these QTLs affect HRY onlyindirectly, via advancing heading date (in Louisiana) or delaying harvest date (in Arkansas). Wehave not identified a QTL for HRY per se. We suggest that this will require a largermulti-environment study or an assay under controlled conditions that duplicate theenvironmental stresses that expose differential HRY performance.

In addition to focusing on the two recalcitrant traits milling yield and sheath blightresistance, there were other challenges that were addressed in the RiceCAP project. US breedersutilize a very narrow gene pool that traces to fewer than 40 introductions that serve as the basisfor almost all cultivars developed. Rather than using more diverse germplasm in this project, itwas decided to use elite breeding materials that are important to US varietal developmentprograms. Within the US germplasm base, there were only a few sources possessing high millingquality or clear resistance to sheath blight disease that could be used. In addition, in order tomake significant accomplishments within the 5 years of the grant, mapping populations werechosen that had already been initiated by breeders and were not developed specifically for thisproject. Due to the complexity of these two traits, it was clear that new methods for phenotypingwould have to be developed that were more accurate and could be used to screen a large numberof progeny in mapping populations. Ultimately the goal was not only to map genes for millingquality and sheath blight resistance but also to develop improved germplasm that could be usedby breeders and to facilitate the adoption of MAS technology by the US breeding community.

To complement the effort of Objective 1 of RiceCAP, the Objective 2 team has focused onvalidating the function of rice candidate genes associated with sheath blight resistance andmilling quality. Both genome-wide expression profiling and targeted approaches have been takento identify candidate genes related to sheath blight resistance and milling yield. Massively

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parallel signature sequencing (MPSS) has been conducted to identify rice genes that weredifferentially expressed in high- and low-milling yield cultivars during the grain filling. RobustLongSAGE and microarray analyses were used to identify differentially expressed rice genesfollowing Rhizoctonia solani infection. Defense-related genes were also identified based onprotein--protein interactions, defense pathway analysis, database and literature searches. Manyof these candidate genes have been mapped in rice chromosomes for their association withsheath blight resistance and milling yield QTLs. Using RNA interference, transgeneover-expression and mutant analysis, about two dozens of the targeted candidate genes havebeen functionally characterized for their positive or negative role in regulating sheath blightresistance. To understand the rice-fungus interaction, transcriptome and secretome analyses of R.solani were conducted to identify fungal genes and protein effectors that are important for thefungal pathogenesis. We also developed vectors and protocols for virus-induced gene silencing,RNAi, protoplast manipulation and efficient rice transformation that contribute to the ricebiotechnology toolbox.

Two additional RiceCAP objectives included: (Objective 3) Develop technical trainingprograms and resources to ensure implementation of molecular marker and gene validationtechnologies to solve rice problems; and (4) Provide educational opportunities for students andconsumers emphasizing the potential of genomic research for improving the abundance andquality of rice.

A series of highly popular and well-attended workshops on the use of DNA-basedtechnologies were conducted over the course of the RiceCAP effort. These workshops included awide range of undergraduate and graduate students, post-doctoral research associates, andtechnical staff focused on the molecular breeding efforts of rice in the US.

The team, led by Drs. Lemaux and Cartwright also have conducted a highly professionaleffort on the extension and outreach component of RiceCAP over the course of the project. Theywere tasked with developing educational materials on RiceCAP, recruiting RiceCAP researchersto give presentations in rice-producing states, giving presentations to rice milling and marketingindustry groups, reviewing lay-language summaries of research progress reports, and developingand implementing evaluation tools. These activities and the resultant impact of the wide range ofefforts conducted on extension and outreach efforts are documented in the report and on theRiceCAP website.

The deliverables to the rice research community, breeders, and stakeholders encompasspublications, germplasm, molecular markers, bioinformatics, training, and collaboration and aresummarized below:

Publication deliverables: There have been 28 publications and 35 pending publications asa direct result of the RiceCAP effort. The publications include the acknowledgment language‘The work was supported by the USDA Cooperative State Research, Education and ExtensionService - National Research Initiative - Applied Plant Genomics Program entitled “RiceCAP: Acoordinated research, education, and extension project for the application of genomic discoveriesto improve rice in the United States” (USDA/CSREES grant 2004-35317-14867).’

Germplasm: Key germplasm has already been transferred to US rice breeders from theRiceCAP project. Five sheath blight resistant lines derived from SB5 have been incorporatedinto breeding programs in AR, LA, and CA. Three TIL lines developed from SB4 and whichpossess novel sheath blight resistance introgressions have been released to the public. The SB2population has been registered and is available for public distribution through the Genetic StockOryza Resource center (GSOR) located at the USDA-ARS Dale Bumpers Rice Research and

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Extension Center located in Stuttgart, AR. Plans are under way to make the MY1, MY2, MY3,SB4, and SB5 populations available in 2009 through GSOR also. Germplasm lines developedfrom introgressions from wild species will be made available in 2010. Likewise any linesidentified in the other mapping populations that could be used directly by breeders will be madeavailable.

As part of an association mapping effort on US rice germplasm, purified seed of 400+ ricegenotypes has been deposited with the GSOR center and will be made available to the researchcommunity as genotyping of these lines is being completed.

Molecular markers: Molecular data on 896 SSRs screened using the RiceCAP parentallines were made available to all RiceCAP collaborators via the RiceCAP website. Sufficient SSRcoverage is present for all three milling yield and all four sheath blight RiceCAP mappingpopulations. Due to the common use of many of these parental lines (and other cultivars that arehighly related to them) many of these markers will be useful in US breeding programs.

In part due to the RiceCAP project, all US public rice breeding programs are now usingmolecular markers in their variety development programs. Markers are being used to evaluatebreeding materials for several grain quality traits and major blast resistance genes.

In addition to using these markers to make early generation selections and verify thepresence of genes in advanced breeding lines, they are also being used for quality control in F1'sand during the purification process of new releases. As a next step, a set of 15 SSR markers thatare linked to various economically important traits have been developed so that they can beefficiently evaluated on breeding lines through multiplexing. This will decrease the cost ofgenotyping tremendously and is yet another step in transferring marker technology to breeders.Previously, the rice community did not have interaction with the USDA-ARS Mid-South AreaGenomics Laboratory in Stoneville, MS, which has tremendous genomics capabilities. As aresult of RiceCAP, the MSA Genomics lab is now a key component to the milling, sheath blight,breeding, and association mapping studies fundamental to the project. Using high throughputtechnology, this lab has genotyped the MY2, MY3, and SB2 populations, each containing 325 ormore lines. This partnership with the MSA Genomics lab led to extension of MAS to thebreeding programs in MS and MO and to the development of a grant proposal to identify novelblast resistance genes led by Scheffler and researchers at ARS Stuttgart and Beaumont, andUniversity of Arkansas that has been funded by the US Rice Foundation. This project will leadto more markers and novel genetic resources for use by the US breeding community.

LaGrue and Cypress (MY2 parents), well known for high yield and milling quality, arebeing fully sequenced using Solexa technology through a contract with National Center forGenome Resources (NM). The information will be shared and eventually used in thedevelopment of a US cultivar SNP chip. Approximately 2.3 X genome coverage of LaGrue andCypress will be generated and made public, and published (by G. May, R. Fjellstrom and B.Scheffler; Anticipated date: April 2009).

Affymetrix microarrays were used to identify 4582 unique candidate SFP markers betweenCypress and LaGrue, the parents of the MY2 mapping population. These markers are foundthroughout the rice genome and a validation survey of 78 candidate SFPs showed that 77 of themcorrectly identified a true polymorphism (98.7% accuracy). Twenty candidate SFPs on 8chromosomes (1, 5, 6, 7, 8, 10, 11, 12), which have relatively large gaps (>20 cM) between SSRmarkers in the MY2 and SB2 mapping populations, are being evaluated to increase markersaturation, and as a result, improve QTL mapping efforts.

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Partnering with Dr. Susan McCouch (Cornell Univ.) has resulted in access to SNPtechnology for evaluating over 400 cultivars that are representative of the US gene pool. Thisproject will provide yet another set of informative markers to the US breeding community to usein varietal development programs.

Bioinformatics: The bioinformatics component of RiceCAP is divided into severalcomponents. The Data Center is the part of the RiceCAP WWW site devoted to maintaining dataand posting analytical results, and is hosted on a University of Arkansas computer, with secureaccess for data transfer by the bioinformatics group. The Data Center is divided into sections onprotected data, rice reference maps, and QTL analysis. The protected section contains theoriginal microarray, SAGE, and MPSS data; Affymetrix GeneChip SFP data, SSR selectionscreening results, marker genotyping and trait phenotyping results on four populations, and theresults of analyses conducted by the group including prepared files for QTL-analysis programs.The map reference section relies on the CMap application for drawing genetic and physicalcomparative maps on WWW pages. A “Reference maps” link opens an interface page allowingthe user to view, on a standard rice reference map, all the polymorphic SSRs identified in allRiceCAP crosses. The main feature, however, is a master map incorporating all rice genesidentified from literature and Gramene searches and RiceCAP SAGE, MPSS, expression array,SFP genotyping chip, candidate-gene-knockout, and proteomics experiments, as well as priorsheath-blight QTL-mapping results. The QTL analyses section provides links to graphical outputfrom QTL mapping in the RiceCAP crosses analyzed to date by the group. QTL-mappingsoftware also was developed and included in the data center and has been downloaded more than700 times. Provision should be made for transfer of map and QTL data to Gramene aroundmid-2009.

Training: The objective of the technical training portion of the RiceCAP effort was todevelop educational programs and resources to ensure implementation of molecular marker andgene validation technologies to solve rice problems.

As part of the technical training aspect of RiceCAP, four highly popular workshops,entitled “Markers unleashed: An overview of DNA marker technology as it applies to riceimprovement”, “RiceCAP virus-induced gene silencing and stable RNAi workshop”, “TheRiceCAP DNA Marker Workshop: Markers, Mapping, and Beyond” and “Lab Encounters inPlant Genomics” were held. The workshops were attended by 25-100 participants from 14 U.S.institutions representing the major public and private rice breeding and research programs in theU.S. The Lab Encounters workshop was for science and agriculture teachers of grades 5-12 tointroduce methods and applications of genomic plant research, especially as they apply to theRiceCAP project.

Overall, RiceCAP has created training opportunities through workshops for 25 graduatestudents, 15 undergraduate students, 19 postdoctoral research associates, and 41 technicalpersonnel or through direct support for 9 graduate students, 7 undergraduate students, 14postdocs, and 34 technical personnel.

The list of undergraduate and graduate students, technical personnel, and post-doctoralresearch associates that were directly supported by RiceCAP over the life of the grant, and theircontributions are listed on the RiceCAP website.

Collaborations: A wide range of collaborations have been initiated as a result of theRiceCAP effort. These collaborations have included a number of state and federally fundedefforts that have strongly leveraged RiceCAP support. The collaborative efforts have included 12of the RiceCAP scientists and are detailed within the report. Perhaps the collaboration having the

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most impact was for Objective 1 - Molecular Marker component where interaction began withDr. Brian Scheffler, with whom there had been no interaction between the rice community andthe USDA-ARS Mid-South Area Genomics Laboratory before RiceCAP. Through MississippiState rice breeder Dr. Dwight Kanter, Dr. Scheffler who had limited experience in rice research,was brought into the RiceCAP project, along with the tremendous genomics capabilities of hislab. As a result, the MSA Genomics lab is now a key component to the milling, sheath blight,breeding and association mapping studies fundamental to the project. Also, Dr. Scheffler hastaken the lead in having the MY2 parents LaGrue and Cypress re-sequenced by the NationalCenter for Genome Resources, Santa Fe, New Mexico, using the Solexa technology. BeyondRiceCAP, the MSA Genomics Laboratory has completed the sequencing various rice accessionsfor blast alleles for Dr. Yulin Jia.

In the area of bioinformatics, RiceCAP brought the U.S. rice researchers together with Dr.Clare Nelson who has been able to update the “QGene” software so that it will analyze datasetsover several different environments. Several new options for looking at trait data and analyzingQTLs have been added to QGene as plug-ins. QGene is one of two software programs availablefor mapping QTLs in advanced-backcross populations. This analysis is necessary for the threepopulations with the SB resistant wild Oryza species developed by Dr. Georgia Eizenga as partof RiceCAP.

Dr. Peggy Lemaux is part of the Objective 4 team for RiceCAP. Also, she is an Extensionand Education PI for Barley CAP and serves on the Advisory Board for Education and Extensionfor WheatCAP and Conifer CAP, thus she reviews efforts in all these CAPs. RiceCAP hasbenefited from this involvement but, more importantly for the CAPs, the work with RiceCAP hasallowed Lemaux to provide insights to the other CAPs on approaches and efforts that havesucceeded and those that failed. This is noted in section C. Integration with other CAP projectsin Objective 4 relating to “Extension and Outreach”.

Another aspect of RiceCAP was the collaborations outside of RiceCAP participants thatdeveloped and the additional funding that was applied for and obtained based on the resultsobtained with RiceCAP funding. A summary of these interactions and grants is listed below.

Dr. Jan Leach obtained funding from USDA-CSREES-NRI to re-sequence 20 diverse ricevarieties from worldwide sources including two US varieties, Cypress (southern US variety) andM202 (California variety) along with colleagues C. Robin Buell and Hei Leung. The grant wasentitled “Sequencing multiple and diverse rice varieties to allow connection of whole-genomevariation with phenotype” and provided valuable SNP information for the US rice communityfor other projects.

RiceCAP provided a forum for Drs. Rod Wing and Dave Kudrna (Univ. Arizona) to reporttheir findings regarding the relationship between the various wild Oryza species accessionsbased on the DNA sequencing work conducted as part of the NSF-funded “Oryza MapAlignment Project (OMAP)” and establish a relationship with the U.S. rice breeding community. In addition four accessions representing O. barthii, O. glaberrima, O. nivara, and O. rufipogon,which were part of the OMAP sequencing effort were included in the sheath blight screening testconducted by Dr. Georgia Eizenga.

RiceCAP graduate students and postdocs supported by RiceCAP obtained additionalUSDA-NRI-CSREES funding to attend the International Rice Genetics Symposium and the International Rice Functional Genomics Symposium during the RiceCAP effort.

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RICECAP ON THE WEB

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4. RICECAP ON THE WEB

The RiceCAP web site, www.ricecap.uark.edu, was established • to promote RiceCAP-funded genomics research, • to act as a communication tool between participating scientists, • to provide education and outreach to the rice industry (e.g., breeders,

farmers, producers),• to provide education and outreach to teachers, students, and all others with

an interest in the grant's goals and rice genomics in general. As part of the dissemination of research between participating scientists, the RiceCAP web sitealso acts as a (restricted) gateway to the sharing of research data that the grant has generated(this is discussed in detail in section 8, Bioinformatics).The website has been continually updated with calendar events, publications (e.g., posters,newsletters, reports), videos, fact sheets, directory, relevant links, research/data analyses, andother related items. A web site restructure was implemented in May 2007 to provide a moreintuitive organization and ease of navigation; the current web site structure is represented below:

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OBJECTIVE TEAMS AND REPORTS

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5. OBJECTIVE TEAMS - PRINCIPAL INVESTIGATORS AND COOPERATORS

Objective 1 Identify and use candidate genes and other molecular markers linked toquantitative trait loci which control milling quality and resistance to sheathblight disease.

Anna McClung, USDA-ARS DBNRRC (AR) & Rice Research Unit (TX)Jim Oard, Louisiana State UniversityBob Fjellstrom, USDA-ARS, Dale Bumpers National Rice Research CenterYulin Jia, USDA-ARS, Dale Bumpers National Rice Research CenterSally Leong, USDA-ARS, CCRU, WisconsinSteve Linscombe, LSU Ag Center, Rice Research StationKaren Moldenhauer, University of Arkansas Rice Research & Extension CntrHenry Nguyen, University of MissouriShannon Pinson, USDA-ARS Rice Research UnitHerry Utomo, Louisiana State UniversityFarman Jodari, California Cooperative Rice Research FoundationFernando Correa, RiceTec (formerly of CIAT; Cali, Colombia; So. America)Brian Scheffler, USDA-ARS MSA Genomics LaboratoryDonn Beighley, Southeast Missouri State UniversityDwight Kanter, Delta Research and Extension Center; Stoneville, MSSteve Brooks, USDA-ARS, Dale Bumpers National Rice Research CenterGeorgia Eizenga, USDA-ARS, Dale Bumpers National Rice Research CenterNeil Rutger, Chief Scientist Retired, USDA DBNRRC

Objective 2 Validate the function of candidate genes associated with sheath blight resistanceand milling quality

Yinong Yang, Pennsylvania State UniversityPamela Ronald, University of California at DavisGuo-liang Wang, Ohio State UniversityJan Leach, Colorado State University

Bioinformatics: Receive, organize, and archive RiceCAP project data; provide bioinformaticservices and analyses including backup and final review for all mapping andQTL studies

Clare Nelson, Kansas State University

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Objective 3 Technical Training

Anna McClung, USDA-ARS DBNRRC (AR) & Rice Research Unit (TX)Jim Correll, University of Arkansas, FayettevilleJim Oard, Louisiana State UniversityKen Korth, University of Arkansas, Fayetteville

Objective 4 Outreach

Rick Cartwright, University of Arkansas Cooperative Extension ServicePeggy Lemaux, University of California at BerkeleyKen Korth, University of Arkansas, FayettevilleSally Leong, USDA-ARS, CCRU, WisconsinBarbara Alonso, University of California at BerkeleyAnna McClung, USDA-ARS DBNRRC (AR) & Rice Research Unit (TX)Karen Moldenhauer, University of Arkansas Rice Research & Extension CntrChris Greer, University of California at DavisNathan Buehring, Mississippi State UniversityJanice Stephens, Colorado State University

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6. OBJECTIVE 1 - BREEDING EFFORT

A. Introduction Rice production in the US has proven to be very efficient with annual yield increases

averaging 1.2%. These high yields have resulted in steady increases in production thoughacreage has decreased to levels of 20 years ago. This yield increase has been partially due tothe development of cultivars and hybrids with high yield potential. Although the US hashistorically been the leader in producing high quality rice that commands a premium in theworld market, many other countries have greatly improved the quality of rice that theyexport, thus making the marketplace much more competitive. Thus, in spite of a veryefficient rice production system in the US, growers are losing market-share due to greatercompetition on price and quality. The US must maintain its long-time leadership inproducing high quality rice at reasonable prices to sustain domestic rice production. USproducers need rice cultivars that have improved quality and disease resistance, lower inputcosts, and production strategies that meet societal demands for protecting the environment.To improve production efficiency while maintaining high quality, there is a need to minimizelosses due to diseases and pests, and to improve traits critical to processing, such as millingquality. Many production traits, such as improved milling quality and yield, and durabledisease resistance, are complex traits governed by quantitative trait loci (QTL). AlthoughQTL underlie these desirable traits, their incorporation into crop plants such as rice is limitedby the low predictive value of genetic markers for phenotypic performance. This is caused bya variety of factors, including recombination between target traits and markers, lowexpression of certain genes, and strong genotype-by-environment interaction. However, withthe completion of the rice genome sequence in 2005, the rice research community was wellpositioned to utilize genomic information to solve practical problems important to the USrice industry, farmers, and consumers.

In 2003, US rice breeders met with industry representatives and developed a prioritizedlist of researchable issues that could be addressed using genomics. From that discussion themain objectives of this project were developed and two traits that have major impact onfarmers and processors were identified. The objectives of the RiceCAP project includeddeveloping genetic markers that are closely linked to QTL controlling milling quality andresistance to sheath blight disease, and transferring marker assisted selection (MAS)technology to US rice breeding programs.

Milling quality is a complex trait known to be affected by kernel shape, chalkiness, grainhardness and susceptibility to fissuring. It varies greatly depending on the cultivar andenvironmental conditions during grain fill, ripening, harvest, and post-harvest handling.Selection for milling quality in early breeding generations is difficult because of geneticsegregation, sensitivity of the trait to the environment, and the amount of seed required formilling evaluations. Moreover, because of stringent industry requirements for grain shapeparameters in short, medium, and long grain market classes, US rice breeders are primarilyinterested in identifying genes and markers for milling yield QTL other than thosecontrolling grain shape. Development of molecular markers linked to milling quality geneswould provide needed assistance to breeders in their attempt to improve head rice yields innew cultivars.

Sheath blight, caused by Rhizoctonia solani, is one of the most common and devastatingrice diseases in the world. In the US, yield losses of 50% can occur from this disease with

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additional losses in crop value coming from decreased milling quality. Fungicides thatcontrol the disease are available, but field scouting, proper timing of application, and aerialapplication of chemicals increase production costs. Sheath blight resistance, or tolerance, is acomplex quantitative trait controlled by multiple genes located on different chromosomes forwhich some QTL have been identified. Overall plant architecture also influences diseasedevelopment as taller cultivars generally are more tolerant to sheath blight than semi-dwarfcultivars. Cultivars with high levels of resistance have yet to be developed partly due tohighly variable screening methods and the lack of highly effective sources of resistance.

In addition to focusing on these two recalcitrant traits, there were other challenges thatwere addressed in the RiceCAP project. US breeders utilize a very narrow gene pool thattraces to fewer than 40 introductions that serve as the basis for almost all cultivars developed.Rather than using more diverse germplasm in this project, it was decided to use elitebreeding materials that are important to US varietal development programs. Within the USgermplasm base, there were only a few sources possessing high milling quality or clearresistance to sheath blight disease that could be used. In addition, in order to make significantaccomplishments within the 5 years of the grant, mapping populations were chosen that hadalready been initiated by breeders and were not developed specifically for this project. Dueto the complexity of these two traits, it was clear that new methods for phenotyping wouldhave to be developed that were more accurate and could be used to screen a large number ofprogeny in mapping populations. Ultimately the goal was to not only map genes for millingquality and sheath blight resistance but to also developed improved germplasm that could beused by breeders and to facilitate the adoption of MAS technology by the US breedingcommunity.

The following information details the efforts that were conducted in Objective 1 - toidentify and use candidate genes and other molecular markers linked to quantitative trait lociwhich control milling quality and resistance to sheath blight disease. Efforts were conductedon five sheath blight (SB) mapping populations (SB1, SB2, SB4, SB5, and SB6 and threemilling yield (MY) populations (MY1, MY2, and MY3). In addition, new projects wereinitiated during the effort to examine sheath blight resistance in wild relatives of rice andidentify and characterize the genetics of a toxin (SB6) produced by the sheath blightpathogen that is involved in disease development.

B. Overview of project results 1. Sheath Blight

a) SB1 (1) Description: The SB1 mapping population was comprised of 279 F2:F3progeny lines derived from a cross between Rosemont, a very early maturingsemi-dwarf tropical long grain cultivar that is very susceptible to sheath blightdisease, and Pecos, an early maturing medium height (tall) medium grain cultivarthat historically shows high tolerance to sheath blight. (2) Approach: The mapping population was evaluated for two years, tworeplications per year, to measure sheath blight field resistance. Plots wereinoculated with the sheath blight pathogen and grown under sprinkler irrigation tofavor disease development. Disease ratings were recorded 30 days after headingfor each line, rated on a scale of 0-9, as well as mature plant height and days to50% heading.

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(3) Genotyping: From an available pool of 638 polymorphic SSR markers, 149SSRs were selected for genotyping. Marker coverage was fairly completethroughout the rice genome, except for regions on chromosomes 1, 5, and 7,where no polymorphic markers could be identified.(4) QTL Analysis: Four significant QTLs for sheath blight resistance weremapped. The most significant SB-QTL, accounting for approximately 36% of theSB severity, mapped to the large (bottom) arm of chromosome 1, peaking at thesd-1 locus, which controls semi-dwarf plant height. The remaining threeSB-QTLs, located on chromosomes 2, 3, and 9, showed minor effects, eachaccounting for 5 to 7% of the disease rating, but were consistently detected acrossyears and replications. The most significant QTL for plant height peaked at thesd-1 locus on rice chromosome 1, accounting for nearly 89% of the plant heightvariation.(5) Conclusions: Results demonstrated that sheath blight resistance is correlatedwith plant height, a point of dispute in previous SB mapping reports. SignificantQTLs controlling sheath blight resistance independent of plant height wereidentified although minor in effect. Each of these minor QTLs were found inlocations where other SB-QTLs have been mapped, with the most significantQTL mapping to a region of chromosome 9 harboring SB-QTLs detected in threeother RiceCAP SB populations (SB2, SB4, and SB5).(6) Deliverables: This research resulted in a publication entitled “Geneticmapping of sheath blight resistance QTLs within tropical Japonica rice cultivars”,authored by Sharma A, McClung AM, Pinson SRM, Kepiro JL, Shank AR,Tabien RE, and Fjellstrom R, which has been accepted for publication in CropScience.(7) Future: SB-QTLs on chromosomes 2, 3, and 9 are being confirmed in F3:F4progeny lines that are independently segregating for markers at only one of theseQTL regions while being fixed for markers at the (two other) alternative QTLregions and the sd-1 locus. Some 300 progeny have been evaluated in aninoculated nursery in 2008. Data will be used to determine the effect of eachindividual SB-QTL.

b) SB2 (1) Description: The variety Cocodrie was used as the susceptible female parentwhile the tolerant MCR10277 was used as the male. Cocodrie is a popularsemi-dwarf, long grain susceptible variety in the southern U.S. (averaging a highdisease rating of 7.8 on a scale of 0-9). Its disease response was similar underboth AR and LA conditions. Mean plant height of 94 cm and 83 days to headingfor Cocodrie in Louisiana were typical for a southern long-grain variety. Cocodriewas 3 cm taller in AR vs. LA and 3 days earlier to head under AR conditions.

MCR10277 is a line developed by M.C. Rush that displayed significantlygreater tolerance to sheath blight across years and locations (mean = 3.7; range =2.7-5.0) as compared to Cocodrie (mean =7.7; range = 7.2 - 8.0). Average plantheight of the tolerant line in Louisiana was 5 cm shorter than Cocodrie while daysto heading of MCR10277 were 7 days later than the susceptible parent.MCR10277 in AR was also 7 days later in heading than Cocodrie, but reached the

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same height of 97 cm. The population comprised 325 double haploid lines thathad been developed using anther culture.(2) Approach: The field design in LA and AR was a RCBD with threereplications. Each plot was a single row that measured 2 meters in length.Standard agronomic practices for maximum plant growth, weed control and insectpests were carried out according to recommended practices at each site. SB2 plotsin LA were planted in April of each year and May of each year in AR. Plantswere inoculated with R. solani using standard practices at the late tillering stage ateach site. At the milk stage of seed maturity, entries were rated for tolerancebased on the 0-9 rating scale.

At CIAT (Cali, Colombia), screening of DH lines was carried out in a mistchamber where plants at mid to late tillering were inoculated and scored aspercentage of plant area affected. Evaluation of DH lines were also conducted inAR with micro-chambers (coke bottle) at the 3-4 leaf seedling stage and scoredwith the 0-9 scale. SB2 phenotypic data obtained in Louisiana and Arkansas weresimilar across years for the three traits that were measured. For example, meansheath blight ratings were correlated (r = 0.74, p < 0.001) and remarkably similarfor Louisiana (5.4±1.2) and Arkansas (5.7±1.1). Similarly, the range of sheathblight ratings was extensive and nearly identical for Louisiana (2.7-8.0) andArkansas (2.7-8.9). Days to 50% heading were not statistically different and werecorrelated across years and locations (LA = 87.5±3.6; AR = 81.9±3.7; r = 0.72, p< 0.001). Both locations showed similar ranges for heading date (LA = 79-99; AR= 74-93). Arkansas produced a greater range in plant height vs. Louisiana (LA =74-106; AR = 77-118), although family mean values were correlated (r = 0.78, p< 0.001) and not statistically different (LA = 89.8±5.6; AR = 97.1±7.4). Sheathblight ratings were negatively correlated, although only to a moderate degree,with heading date for both Louisiana (r = -0.44, p < 0.001) and Arkansas (r =-0.46, p < 0.001). Plant height showed weak negative-association sheath blightvalues (LA = -0.19, p = 0.004; AR = -0.24, p < 0.001). ANOVA of sheath blightratings showed that location, year, and location x year were significant sources ofvariation, but these effects were not significant for plant height or days toheading. (3) Genotyping: A total of 297 SSR markers were found to be polymorphicbetween Cocodrie and MCR10277 from a set of 1025 markers that were scored.Of these, 129 markers were scored for the 325 SB2 DH lines and used in the QTLanalysis (see below). The distribution of polymorphic markers acrosschromosomes varied considerably with a low of 2 on chromosome 6 and a high of14 on chromosome 2. A majority of the chromosomes (67%) showed fewer than10 polymorphic markers, indicating that large regions of the map were notinterrogated. Some extreme deviations from expected 1:1 segregation of markergenotypes were observed that may be due to generation or handling of SB2doubled haploid (DH) lines.(4) QTL Analysis: Sheath-blight-resistance QTL analyses with the MIM methodwere conducted in C. Nelson's lab at Kansas State University for each year (2005- LA only, 2006, 2007) and location (LA, AR), along with experiments conductedin the CIAT-greenhouse, and AR microchamber. A total of 8 QTLs were detected

20

across chromosomes 2, 3, 5, 6, 8, 9, and 12. The majority of QTLs produced arange of low to high LOD scores (2-14) whose effects were correspondinglysmall to moderate (R2 = 0.03 to 0.18). Six QTLs were detected in a minimum of 4of the experiments, and three regions on chromosomes 2, 8, and 9 were found inall field environments. In contrast, QTLs on chromosomes 3 and 12 were foundonly in AR. A region near the top of chromosome 5 was detected both in the SB2and SB5 (Lemont x J85) populations. The QTL in SB2 with the largest effectacross all experiments was detected at the bottom of chromosome 9 (LOD =4.5-29.5; R2 = 0.06-0.34). This region was also detected in SB1, SB4 and SB5and should be a focus for fine mapping and sequencing efforts. (5) Conclusions: The SB2 QTL on chromosome 2 mapped within a regionpreviously reported for sheath blight resistance (MGG. 2001. 265:302-310; TAG.1995. 91:382-388) including an EST encoding stromal ascorbate peroxidase(SAP), reported to be associated with fungal infection (Planta. 2005.2:192-200)and antioxidant metabolism (Plant J. 2002. 29: 192-202). The QTL at the bottomof chromosome 8 also mapped within a previously reported QTL (Crop Sci. 2005.45:503-510). The “major” QTL at the bottom of chromosome 9 mapped withinother reported QTLs (TAG. 1995. 91:382-388; Crop Sci. 2005. 45:503-510).RiceCAP microarray and SAGE data have identified candidate genes within theQTLs on chromosomes 2 and 9 that can be evaluated with fine mapping/cloningexperiments described below. In summary, the SB2 population has proven to be avaluable resource to identify candidate regions for future mapped-based cloningand MAS breeding efforts for sheath blight resistance. (6) Deliverables: The SB2 mapping population consists of 325 DH lines that havebeen registered (Chu et al. 2006. Crop Science 46:1416) and are available to thepublic through the Genetic Stocks Oryza Collection (GSOR) in Stuttgart, AR. Atotal of 8 candidate QTL markers have been identified for future basic researchand applied MAS efforts. Results from the SB2 mapping research efforts will besubmitted for publication in 2009 and will be posted online for public viewing atthe RiceCAP website. (7) Future: Fine mapping of sheath blight QTLs–The standard approach to finemapping of QTL regions on chromosomes 2, 8, and 9 would require developmentand phenotyping of thousands of additional DH / RILs that would take anadditional four or more years to complete. One alternative approach would be tocombine lines already developed and phenotyped from both SB2 and SB5 for anoverall population size ~ 500 individuals. (Other SB populations could also beincluded). An association mapping approach(s) would be used to fine mappre-selected QTLs on chromosomes 2, 8, and 9. SSRs from RiceCAP and SNPmarkers from McCouch NSF Project would be used to create a SNP/SSRdatabase for the 500 lines. In addition to whole-genome coverage, selected QTLson chromosomes 2, 8, and 9 would be saturated with SSR and SNP markers.Expected outcome in ~ two years would be a large marker database for finemapping and identification of candidate regions and/or genes suitable forsequencing and validation in SB2, SB5, and other populations.

21

c) SB4 (1) Description: A set of over 300 backcrossed TeQing-into-Lemont introgressionlines (TILs) were obtained from IRRI, and developed through RiceCAP effortinto a gene-mapping population. A subset of 123 TILs were subsequently selectedfor public release after characterization with 167 SSR markers (Figure 1). The123 TILs were selected based on their containing a predominantly Lemont geneticbackground (TILs range from 65 to 99% Lemont alleles; average = 88.6%).TeQing alleles for each of the SSR loci were backcrossed into two or more TILs.This internal replication makes the TILs ideal for verifying the phenotypic effectsassociated with the introgressed genetic regions. The TILs were created to serveas a companion population to the Lemont/TeQing RIL mapping population. Seed

Figure 1. A new rice gene-mapping population developed by RiceCAP cooperators. The 123 TeQing-into-Lemont introgression lines (TILs) are arranged vertically in order of their chromosome segment substitutions with red indicating where TeQing alleles were found, blue showing Lemont alleles. The TILs contained 73 to 95% Lemont alleles. TILs having more than one key introgression are listed more than once. Orange shaded probe names along the top indicate chromosomal regions initially reported to contain a sheath blight resistance QTL, with darker shading correlating with estimated QTL peaks.

22

of the TILs was increased and will soon be made publicly available via GSOR. (2) Approach: Our goal was to fine-map one or more QTLs associated withsheath blight resistance. We started with 18 previously reported QTLs (Figure 1),8 of which were validated by identification in more than one randomlysegregating population (Li et al., 1995; Pinson et al., 2005). Randomlysegregating populations are suited for QTL discovery, but their random geneticbackgrounds make it difficult to map the QTLs precisely, especially when asmany as 18 loci of individually small effect are involved. We elected to pursuefine-mapping within the TILs, where the standard Lemont-type geneticbackground would allow us to better determine presence or absence of a QTLbased on small phenotypic change. After further evaluation of the TILs, as well asresults from SB1, we decided to first focus the fine mapping efforts on qSB9-2and qSB12-1. (3) Genotyping: The TILs were characterized for 167 SSR loci selected torepresent the entire rice genome with =20 cM gaps between marker loci.Additional SSRs were evaluated in selected TILs to saturate the regions aroundthe targeted qSB9-2 and qSB12-1 QTLs. Marker evaluations were collaborativebetween USDA-RRU in TX, and USDA-DBNRRC in AR.(4) QTL Analysis: The TILs did not prove to be as genetically ‘clean’ asanticipated, but contained 5 or more introgressions in each TIL. In order to moredirectly observe the effect of one specific QTL introgression, we againbackcrossed selected TIL(s) with Lemont, and identified among the F2 progenylines those containing single-QTL introgressions for further study. Selected TILshaving homozygous F2:3 plants are being grown in 2008-09 in Puerto Rico toproduce sufficient pure-breeding seed for replicated field-plot evaluations in2009. However, we have identified other of the original TILs (not backcrossedagain) with chromosomal breakage points around the 11 cM qSB12-1 QTL region(Pinson et al., 2005) that have allowed us to more accurately place this QTLbetween the blast resistance gene, Pita and RM277 (Table 1). The qSB9-2 locuswas similarly found to most likely lie in the right-hand half of its original 13 cMQTL region, while a gene for spreading culms (or widely angled tillers) wasnewly discovered and mapped to the left-hand portion of the QTL region. Thesaturated marker data around qSB9-2 and qSB12-1 also allowed us to identify F2scontaining newly generated recombination around the targeted QTLs, which willallow further dissection of the QTL regions. To date, we have identified 47 F2progeny containing new recombination within the original 13 cM qSB9-2 region,and 12 new recombinants in the original 11 cM qSB12-1 region. (5) Conclusions: The qSB12-1 QTL which had been identified in early-generationmaterials (Li et al., 1995), but was not validated in the subsequent LQ-RIL study(Pinson et al., 2005), was validated as a SBR QTL near OSM89.

The effects of qSB9-2 and qSB12-1 were found large enough to be detectableusing both replicated field plots and micro-chamber methods. This is not true forall the SBR QTLs.

23

Table 1. Phenotypic response of seven TILs selected as containing qSB12-1 but no other introgressions with significant impact on sheath blight resistance shows that the SBR locus most likely lies between Pita and RM277. This places the QTL into a 7 cM or 5 Mbp region, smaller than the 11 cM, 7 Mbp QTL region originally reported for qSB12-1 by Pinson et al., 2005.

RM

5568

RM

3483

RM

247

RM

6998

RM

2778

2

OSM

89

Pita

RM

2798

2

RM

277

RM

3448

RM

309

Moderately Resistant TILs

381.13 383.13 615 642 649

Susceptible TILs 385 569

qSB9-2 and qSB12-1 have been more finely mapped. Table 1 shows thereduction of the qSB12-1 region from 11 to 7 cM. The qSB9-2 region, which wasfound to have a large phenotypic effect in SB5, has been reduced from 13 cM to 7cM.

A TeQing gene for spreading culms (Spr), also called open tillers, wasdiscovered and putatively mapped between RM3808 and RM215 on chromosome9, within the qSB9-2 region. The literature contains two reports of an opentillering gene in this region. Because increased airflow from the spreading culmscan discourage fungal growth, further clarification of the relationship between theSpr and SBR loci on the end of chromosome 9 should be pursued.(6) Deliverables:

(i) The TILs provide rice researchers with a unique population for efficientlyvalidating QTLs, and evaluating their value in a US-adapted geneticbackground. The TILs can also support de novo QTL mapping in as few as125 lines. Seed and SSR data will be disseminated via GSOR. Citation: Pinson, S.R., Liu, G., Jia, M.H., Jia, Y., Fjellstrom, R.G., Sharma, A., Tabien,R.E., Li, Z. 2008. “Registration of a rice gene mapping population consistingof TeQing-into-Lemont (TIL) backcross introgression lines”. To be submittedto Journal of Plant Registrations.(ii) TILs have been developed containing qSB9-2 and qSB12-1 individuallyand in combination but possessing fewer other background introgressions. (iii) TILs are being developed that contain new genetic recombination inqSB9-2 and qSB12-1 which will support even finer mapping of these QTLs.

(7) Future: (i) Evaluate the “cleaner TILs” in inoculated field and micro-chamber studiesduring 2009 to clarify the breeding value of these SBR QTLs. Publish QTL

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breeding value studies. Citation: Wang, Y., Pinson, S.R.M., Fjellstrom, R.G.,and Jia, Y. “Isolation of Two Rice Sheath Blight Resistance QTLs asMendelian Factors and Development of Molecular Tags to Support MAS”. To be submitted to Journal of Plant Registrations.(ii) Self the F2s found to have new recombination in and around the targetedQTLs, molecularly identify homozogous progeny, increase seed, and evaluatephenotypes. Publish more accurate estimates of the QTL locations. (iii) The TILs provided a solid basis for obtaining grant funds to study thegenetic control of rice tillering patterns, and grain elemental content(nutritional value). This population is also key to a research proposal underdevelopment to verify QTLs for resistance to rice Bacterial Panicle Blight.

d) SB5 (1) Description: The ‘SB5' population is derived from a cross of ‘Lemont’ with‘Jasmine 85’, and was developed using single seed descent in a greenhouse inStuttgart, Arkansas. Jasmine 85, a midseason aromatic long-grain indica cultivardeveloped at the International Rice Research Institute, Philippines is adapted tothe southern US and has good tolerance to rice sheath blight (SB) disease.Lemont, an early maturing, semi-dwarf tropical japonica cultivar commerciallygrown in the southern US from 1980's to 1990's, is highly susceptible to SB. Asubset of 256 F5 RILs of Lemont/Jasmine 85 (LJRILs) was selected withconfounding factors, plant height, plant type (tiller angle) and heading durationremoved, and was genotyped using SSR markers. A total of 602 F9-10 randomLJRILs are available for release to the scientific community.

Sheath blight disease ratings for Lemont were mean=8; range= 7-9 and forJasmine 85 were mean=2.5; range= 1-4 in Arkansas fields from 2005 to 2008. The days to 50% heading were 97.0 for Lemont and 111.0 days for Jasmine 85 infield tests in AR in 2008, and ranged 90.0 to 122.0 days for the 256 LJRILpopulation with an average of 97.3 days. Plant heights for Lemont and Jasmine 85were 93.5 cm and 110.8 cm, respectively, while the 256 LJRIL population, rangedfrom 81.5 cm to 125.5 cm with an average of 105.0 cm.(2) Approach: The disease reaction of 250 LJRILs to SB resistance wasphenotyped in a greenhouse using the recently developed micro-chamber(MCCM) and mist chamber (MCM) methods. The isolate Tol 2399-1 from thepathogen Rhizoctonia solani AG I-1A was used to culture inoculum on potatodextrose agar (PDA) medium. Mycelial discs at the diameter of 7 mm wereexcised and used to inoculate the 3-week-old rice seedlings (4-leaf stage) inplastic pots for the MCCM and 50 days old plants for the MCM. A colonized discwas placed at the base of a rice seedling (MCCM) or adult plant (MCM). Afterinoculation, the rice plants in a pot were covered with a 3L clear plastic bottle,forming high humidity in the MCCM, or kept inside a plastic walking mistchamber for the MCM method using humidifiers to provide high humidityconditions. The inoculated plants were kept at 24-28°C, and evaluated at 8-10days after inoculation. The sheath blight severity on test plants was measured asthe percentage of the diseased plant area affected (DPAA). There were 3 LJRILper pot and 3 plants per RIL in the MCCM and 5 plants per RIL per pot for theMCM. Each plant represented a replication. Each RIL was replicated 3 times and

25

each test was repeated 4 times. All the pots were arranged in a completelyrandomized design. Lemont and Jasmine 85 served as susceptible and resistantchecks, respectively. The field evaluation was performed in Beaumont, TX andStuttgart, AR with 2-4 replications bordered with Cocodrie and local isolates wereused for inoculation.

The mean disease ratings of Lemont and Jasmine 85 transformed to a scale of1-9 were 8.3 and 4.6 using MCCM, and 6.5 and 4.2 using MCM, respectively. Inthe field tests in 2008 the mean SB ratings of Lemont and Jasmine were of 9.0and 3.0 in AR, and 6.5 and 2.3 in TX, respectively. There was a high correlationfor the disease ratings between MCCM and MCM (r=0.53) and between AR fieldand TX field (r=0.62).(3) Genotyping: A subset of 256 LJRILs was genotyped using 199 SSR markers.The rates of successful amplification per locus/LJRIL were 93.0-100.0%. A SSRmap was constructed using 256 LJRILs and 199 SSR markers, representing a totalof 1684.2 cM of genetic distance at an average of 8.5 cM per marker. Sevenmarkers (3.5%) on chromosomes 3, 4 and 12 favored Lemont allele; 40 markers(20.1%) on chromosomes 1, 3, 7, 9 and 10 favored Jasmine 85 allele. Three(1.2%) and 30 (11.8%) LJRILs skewed toward Lemont and Jasmine 85,respectively. As expected from F5 progeny, the average frequencies of overallgenome heterozygosity and non-parental alleles per LJRIL were 9.5% (0-44.2%)and 0.4‰ (0-2.6%), respectively. Fifty-two (20.3%) LJRILs remainedheterozygous at =25 SSR loci.(4) QTL Analysis: MCCM and MCM, the two greenhouse evaluation methods forsheath blight resistance confirmed previously identified SB-QTL and detectednew SB-QTL. A total of 11 SB-QTLs were identified on chromosomes 1, 2, 3, 5,6 and 9 using MCCM and MCM (Fig.1). qSB1 and qSB9-2 were identified byboth MCCM and MCM. The major SB-QTL qSB9-2 that co-segregated withRM245 on chromosome 9 contributed 24.3% of total phenotypic variation usingMCCM and 27.2% using MCM. Four SB-QTLs or SB-QTL regions onchromosomes 2, 3 and 9 were confirmed with the previously reported SB-QTL,and five additional new SB-QTLs on chromosomes 1, 5, 6 and 9 were found. TenF5 LJ RILs segregating at qSB9-2 were identified and seeds are being advancedin a greenhouse for fine mapping. (5) Conclusions: Mapping and confirmation of a major SB-QTL is an importantstep for MAS in breeding for SB resistance. The major SB-QTL qSB9-2 mappedon chromosome 9 in SB5 was previously reported (TAG. 1995, 91: 382-388; CropSci. 2005, 45: 503-510) and can now be used with confidence in present breedingprograms for improving sheath blight resistance in US rice culitivars. MarkersRM215 and RM245 identified in combination with MCCM and MCM methodsare excellent tools for accelerating MAS for improving RSB resistance. Tensegregating F5 LJ QTLs at qSB9-2 were also identified for fine mapping.

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(6) Deliverables: (i) A total of 602 F9-10 random LJRILs are available for release to thescientific community through the GSOR center in Stuttgart, AR(http://www.ars.usda.gov/Main/docs.htm?docid=8318). (ii) The SSR marker RM245 co-segregating with the major SB-QTL qSB9-2can be used for breeding selection of SB resistant lines.(iii) SB resistant RILs RIL#47, #62, #101, #103 and #168 were transferred torice breeding programs in Arkansas, Louisiana, and California and areavailable to the entire rice community.(iv) Standardized-highly efficient and reliable method for evaluating sheathblight resistance using micro-chamber in greenhouse.(v) Expression profiles of 22,000 genes from Jasmine 85 to Rhizoctoniasolani at different time points after infection will be released to publicgenebank.(vi) Rice populations with potentially increased SB tolerance derived fromtriple crosses between Jasmine 85 and other sources of tolerance to SB weredeveloped at CIAT and are available to the rice community in the US throughthis project.

AP2882

RM428RM1167RM220RM1RM283RM5359RM490RM259

RM580RM312

RM449

RM3341

RM5RM488

RM246RM443RM403RM128

RM5501

RM1361

RM104

qSB1

qSB1

CHR1RM109

RM279

RM423RM555

RM71RM6911RM452RM424

RM561RM341RM475RM5427

RM3730RM263RM526

RM221

RM530RM112

RM250

RM166

RM208RM498

qSB2-1qSB2-2

CHR2RM22RM231

RM489

RM545RM517OSR13

RM7RM232RM251RM282

RM338

MRG6395MRG4864RM156RM16RM5626

RM426RM55RM15824

RM293RM468RM422RM143RM514RM442RM85

qSB3-1

qSB3-2qS

B3-3

CHR3RM507RM5796RM413RM13

RM7349RM437

RM289RM169RM509

RM164

RM459RM161RM5401

RM421

RM26RM87

qSB5-1

qSB5-2

CHR5RM133RM435RM190RM587RM510RM225

RM253

RM136RM3431RM3183RM541RM7193

RM454RM162

RM5371

RM340

RM103

qSB6-1

CHR6RM316

RM219AP5593RM296RM105

RM409

RM434

RM257

RM108RM107

RM215

RM245

qSB9-1qSB9-2

qSB9-2

CHR905101520253035404550556065707580859095100105110115120125130135140145150155160165170175180185190195200

Fig.1 Chromosomal locations of the SB-QTL mapped using micro-chamber method (solid boxes) and mist chamber method (hollow boxes) identified in SB5.

27

(vii) Publications published or being prepared:1. Jia, Y., Correa-Victoria, F., McClung, A., Zhu, L., Liu, G., Wamishe,

Y., Xie, J., Marchetti, M.A., Pinson, S.R.M., Rutger, J.N., Correll, J.C. 2006. Rapid determination of rice cultivar responses to the sheathblight pathogen Rhizoctonia solani using a micro-chamber screeningmethod. Plant Disease, 91:485-489.

2. Venu, R.C., Jia Y, Gowda, M., Jia, M.H., Jantasuriyarat, C., Stahlberg,E., Li, H., Rhineheart, A., Boddhireddy, P., Singh, P., Rutger, N.,Kudrna, D., Wing, R., Nelson, J.C., and Wang, G-L. 2007. RL-SAGEand microarray analysis of the rice transcriptome after Rhizoctoniasolani infection. Molecular Genetics and Genomics. 278:421-431.

3. Gowda, M., Venu, R.C., Jia, Y., Stahlberg, E., Pampanwar, V.,Soderlund, C., and Wang, G-L. 2007. Use of robust-long serialanalysis of gene expression to identify novel fungal and plant genesinvolved in host-pathogen interactions. In “Methods in MolecularBiology: Plant-Pathogen Interactions” Vol. 354:131-44. Ed. P.Ronald, Humana Press.

4. Pinson, S.R.M., Oard, J.H., Groth, D., Miller, R., Marchetti, M.A.,Shank, A. R., Jia, M.H., Jia, Y., Fjellstrom, R.G., and Li, Z. 2008.Registration of TIL:455, TIL:514, and TIL:642, Three RiceGermplasm Lines Containing Introgressed Sheath Blight ResistanceAlleles. Journal of Plant Registrations 2(3):251-254.

5. Jia, Y., Liu, G., Zhou, E., Lee, S., Dai, Y., and Singh, P. Ricediseases: Interactions of rice with pathogens. In “Rice”, Edited by PaulCounce , Blackwell Publishing (Apr 2008).

6. Groth, D., Oard, J., Zhang, W., Linscombe, S., Moldenhauer, K.,McClung, A., Jia, Y., Correa, F., Liu, G., Fjellstrom, R., Scheffler, B.,Dinu, Nelson, J.C., Lacaze, X., Correll, J.C., Utomo, H., Rutger, N.,and Leong, S. Identification of SBR QTL in SB2. Theoretical andApplied Genetics (Feb 2009).

7. Jia, Y., Liu, G, McClung, A., and Rutger, N. Registration of arecombinant inbred line population of the cross of Lemont X Jasmine85. Journal of Plant Registration (December 2009).

8. Liu, G., Jia, Y., Correa-Victoria, F., McClung, A., and Correll, J.C.Mapping Quantitative Trait Loci Responsible for Resistance to RiceSheath Blight Disease Using a Recombinant Inbred Line Population inGreenhouse (Submission to Phytopathology: December 2008)

9. Jia, Y., Liu, G., Correa-Victoria, F., McClung, A., and Correll, J.C.Registration of LJRIL#51, #67, #103, #158 and #186, five ricegermplasm line containing sheath blight resistance alleles (plan tosubmit to Journal of Plant Registration, March 2009).

10. Jia, Y. Compare and contrast of genetic resistance to the rice blast andsheath blight diseases. Invited review article for Journal of Frontier ofAgriculture in China (plan to submit Feb 2009).

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(7) Future: (i) A subset of 256 LJRILs will be further phenotyped for the SB resistancein the fields of Arkansas, Texas and Louisiana in 2009 for identifying andvalidating SB-QTL mapped. (ii) Ten best LJRILs were selected for further evaluation for their potential tobe advanced to pre-breeding lines in cooperation with Dr. KarenMoldenhauer.(iii) A subset of 227 LJRILs will be used to map the genetic factors thatcontrol color in milled rice in cooperation with Dr. Ming Chen.(iv) Extremely resistant and susceptible LJRILs will be phenotyped for silicafor two years for mapping genetic factors that are associated with diseaseresistance in cooperation with Dr. Rolfe Bryant.(v) Ten segregating F5 LJ RILs will be advanced to F6, and 4 F5 LJRILscontaining qSB9-2 will be backcrossed to Lemont for fine mapping and willbe crossed to three elite rice cultivars for the US rice breeding programs andthree IRRI cultivars for developing pre-breeding lines for targeted riceproduction areas in the world. (vi) A subset of 256 LJRILs will be used to map blast resistance genes. (vii) A subset of 256 LJRILS will be used to facilitate the mapping of sheathblight resistance factors in response to toxin in cooperation with Dr. SteveBrooks.

e) SB6 (1) Description: Rhizoctonia solani is a necrotrophic fungal pathogen knownto produce a phytotoxin in several important host-pathogen systems. In therice-sheath blight pathosystem R. solani produced a genotype specific toxin,where host sensitivity to the toxin (tissue necrosis) was correlated withsusceptibility to sheath blight disease (S.A. Brooks, 2007). Using a F2population derived from a cross between rice cultivars ‘Cypress’ (verysusceptible to disease and toxin sensitive) and ‘Jasmine 85’ (moderatelyresistant to disease and toxin insensitive), inheritance of toxin sensitivity(tissue necrosis) was determined to be controlled by two genes. To confirmthis result the clonally propagated F1 was backcrossed to Jasmine 85 toproduce a population of 44 BC1F1s that displayed the same phenotypes in a1:1:1:1 segregation ratio as expected, thus confirming the result in the F2population. The SB6 population (BC1F2) was derived by selfing a selectedBC1F1, resulting in a population of 92 individuals that segregated 3:1, asexpected for a single toxin sensitivity gene. (The details of this cross aredescribed in Brooks (2007), and below. In short, the backcross approach wasused to confirm that two genes controlled the toxin necrosis phenotype, andsplit the genes apart into populations that each segregated for a single gene.SB6 is one population where precise phenotyping can be performed forhigh-resolution mapping and map-based cloning.)(2) Approach: The SB6 population was phenotyped by infiltration of riceleaves with the R. solani phytotoxin using the method described by Brooks(2007). A minimum of three reps per line were used to phenotype the

29

population. The results fit the expected 3:1 segregation ratio using achi-square goodness-of-fit test.(3) Genotyping: 276 SSR markers were tested for polymorphism between theparents (CPRS, Jasm85) and heterozygosity in the BC1F1. The entire SB6population are full sibs derived from a single BC1F1, so 50% of the genome isfixed for the recurrent parent. Therefore, many SSR markers that werepolymorphic between the parents were not useful, because they resided inregions that were fixed for the recurrent parent. Of the total number of SSRs,70 were mapped on the population as the initial linkage analysis. (4) QTL Analysis: The 70 SSR markers were not sufficient to detect linkagewith the toxin necrosis phenotype. Large gaps in chromosome coverage stillexists and require further marker development and saturation.(5) Conclusions: The basic genetics used in the development of the SB6population have discovered the basis for inheritance of toxin-induced necrosisin rice. Although further molecular mapping is needed to detect linkage withthe gene of interest, the population segregates clearly for the phenotype in aMendelian fashion, and will be a powerful tool for map-based cloning of thisgene.(6) Deliverables: The phytotoxin screening method was developed as a toolfor improved precision of phenotyping a component of the rice-sheath blightpathosystem. This method allows dissection of a complex trait intocomponents inherited in a Mendelian fashion. The method, combined with theSB6 population, has provided the means to initiate a map-based cloningstrategy for genes involved in tolerance to this important disease.(7) Future: The preliminary work funded by RiceCAP on the sheath blightphytotoxin, has provided the basis to secure $100,000 of additional fundingfrom the USDA to continue the mapping and map-based cloning effort. Apost-doc will begin in April of 2009 to continue this project. In addition, theparents (including the BC1F1) are being submitted to Susan McCouch's labfor SNP analysis with 1348 SNPs on the Illumina array. This will provide theresolution necessary to detect useful markers in regions that currently have nomarker coverage. In addition, we will be phenotyping the SB5 (LMNT/Jasm85) population and using the existing genotypic data as a backup for theinitial linkage mapping.

f) Wild Relatives of Rice(1) Description: Sixty-seven Oryza spp. accessions were evaluated for sheathblight resistance using the micro-chamber, detached-leaf, and toothpick methods.Overall, seven accessions were highly tolerant to SB: O. nivara (IRGC100898,IRGC104443, IRGC104705), O. nivara/O. sativa (IRGC100943), O. barthii(IRGC100223), O. officinalis (IRGC105979), and O. meridionalis(IRGC105306). To identify the SB-QTL, three mapping populations weredeveloped from crosses between three accessions and susceptible US ricecultivars. These populations were Bengal by O. nivara (IRGC100898), Bengal xO. nivara (IRGC104705), and Lemont x O. meridionalis (IRGC105306). Allpopulations were developed using the advanced backcross method, which

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involves crossing the F1 hybrid to the cultivated rice parent two times andobtaining self seed (BC2F2) progeny.

For the Bengal/O. nivara (IRGC100898) population, 900 BC2F1 progenywere produced from 44 fertile BC1F1 plants, grown in the greenhouse to produceBC2F2 progeny, and 279 BC2F2 progeny (4-10 plants per BC1F1 plant) wereselected for SB inoculation and developing the mapping population. For theBengal/O. nivara (IRGC104705) population, 845 BC2F1 progeny were producedfrom 39 fertile BC1F1 plants, grown in the greenhouse to produce BC2F2progeny, and 279 BC2F2 progeny (4-10 plants per BC1F1 plant) were selectedfor SB inoculation and developing the mapping population. For the Lemont/O.meridionalis (IRGC 105306) population, approx. 800 BC2F1 progeny wereproduced from 30 fertile BC1F1 plants. This population will be advanced to theBC2F2 generation in the greenhouse this winter (Dec. 2008 - March 2009)following the methods described for the other two populations. (2) Approach: Both Bengal/O. nivara populations, composed of 279 plants, wereevaluated for SB reaction, days-to-heading, and plant height in the greenhouse. Three replications were planted using a randomized complete block designconsidering four plants in a pot as a replication. The control varieties, Lemont,Cocodrie, Ahrent, Bengal, Jasmine85, and TeQing, were included in the test. Approximately four weeks after planting, the seedlings were inoculated with apotato dextrose agar plug infiltrated with Rhizoctonia solani mycelia and coveredwith a micro-chamber (2-liter soft drink bottle) to create a high humidityenvironment. The plants were rated visually for reaction to SB 7-10 days later ona 0 (no disease) to 9 (entire culm has lesion) scale, and the lesion and culm lengthwere measured to calculate the disease index. Plants were grown to maturity andrated for days-to-heading and plant height. For the Bengal/O. nivara (IRGC100898) population, the greenhouse screening was repeated in fall 2008. Fourreplications of the Bengal/O. nivara (IRGC 104705) were grown in fall 2008(Oct.-Dec. 2008) using a randomized complete block design considering fourplants in a pot as a replication, and rated for SB. The standard control varietiesmentioned above were included in the test. The BC2F3 seeds produced after theplants were rated for reaction to SB were bulked by families to have enough seedfor distribution.

During summer 2008 (May-Oct.) the two Bengal/O. nivara populations werescreened in the field using a randomized complete block design with tworeplications. Each replication had nine plants per row and 14 ranges eachcontaining 20 progeny rows, four rows of four different control cultivars, and 24Bengal rows as a border. Four of the control cultivars Lemont, Cocodrie, Ahrent,Bengal, Jasmine85, and TeQing were planted in each range. Seven seed of eachprogeny line were planted in a row with a Bengal plant at the beginning and endof the row as a border. All plants were space planted in a row with approximately9 in. between the plants and 9 in. between the rows. The plants were inoculated atthe internode elongation stage of development with a mixture of R. solani myceliagrowing on a media prepared with crushed corn and ryegrass seed mixture. Theprogeny rows were rated for SB reaction approximately six weeks afterinoculation on a 0 (no disease) to 9 (nearly dead) scale. Data on days to heading,

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plant height, panicle type and plant type also were collected. Single panicles wereharvested from one replication of each population to have additional seed forfuture studies.

The Lemont/O. meridionalis population will be screened for reaction to SB inthe field during summer 2009 (May-Sept.) and in the greenhouse spring 2009following the methods described above.(3) Genotyping: Initially, a parental marker survey of 282 SSRs was conductedon the three parental accessions: Bengal, O. nivara (IRGC 100898) and O. nivara(IRGC 104705). Subsequently, the Bengal/O. nivara (IRGC 100898) populationwas genotyped with 130 polymorphic SSR markers distributed about every 10 to12 cM. Preference was given to polymorphic markers located in the region ofpreviously identified SB-QTL. The genotyping of the Bengal/O. nivara (IRGC104705) population with 120 polymorphic SSRs will be completed in the spring2009 after the evaluation of the Bengal/O. nivara (IRGC 100898) population iscompleted. For the Lemont/O. meridionalis population, the O. meridionalis parentwill need to be genotyped with SSR markers before the polymorphic SSRs can beselected. If the technology is in place, this population may be genotyped with theSNP markers based on the parental genotypes identified with Illumina's GoldenGate technology as described in the association mapping section of this report. (4) QTL Analysis: The linkage map for the Bengal/O. nivara (IRGC100898)population was constructed using the JoinMap 4.0.6 software. The SB-QTL wereidentified using QGene 4.2 software with both the CIM and MIM methods. Threenew SB-QTL, attributed to the O. nivara parent, were identified on chr. 2, 10 and11 with the QTL on chr. 2 being identified by both the micro-chamber and fieldevaluations. The LOD scores ranged from 2.7-3.3 for these novel QTLs. Inaddition, SB-QTL on chr. 2, 3, 6, 7 and 9, with LOD scores ranging from 2.4-5.2,previously identified in other RiceCAP populations, were confirmed by thispopulation and attributed to either the O. nivara or Bengal parent. The QTLs onchr. 6 were identified by both the micro-chamber and field evaluations. Also,QTLs for plant height (PH), heading date (HD) and plant type (PT) wereidentified with major QTLs on chr. 6 for HD, chr. 1 and 11 for PH, and chr. 9 forPT. The QTL analysis of the Bengal/O. nivara (IRGC 104705) population willbegin once the SB ratings from the microchamber method are complete. The QTLanalysis of the Bengal/O. nivara (IRGC 104705) population will begin once theSB ratings from the microchamber method are completed in late December. QTLanalysis of this population may confirm the newly identified QTLs in previouslydescribed Bengal/O. nivara (IRGC 100898)population.(5) Conclusions: New sources of resistance to sheath blight disease wereidentified in newly introduced wild relatives of rice. Three different mappingpopulations were developed using three wild Oryza accessions as parents. QTLanalysis of the Bengal/O. nivara (IRGC100898) population revealed three novelSB-QTL associated with the O. nivara parent with one identified by both themicro-chamber and field methods. In addition, seven SB-QTLs identified in otherstudies were confirmed in this study. Ultimately, germplasm lines possessingthese novel genes will be developed.

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(6) Deliverables: The screening of the collection of Oryza species for sheathblight resistance was reported in Plant Disease (Prasad and Eizenga, 2008). Apublication describing the QTL analysis of the Bengal/O. nivara (IRGC 100898)population is being prepared (Prasad, Eizenga, Nelson 2009) and will bepresented at the Plant and Animal Genome XVII Conference in San Diego, CA,10-14 January 2009.

We anticipate both the Bengal/O. nivara (IRGC 104705) and Lemont/O.meridionalis populations will follow a similar method of data analysis andpublication. All three populations will be available to the public through theGenetic Stocks-Oryza center at Stuttgart. (7) Future: The lines in the populations that showed the most resistance to SB inthe micro-chamber and field study will be backcrossed to the recurrent parent,re-evaluated for SB resistance and released to the rice breeding community as SBresistant germplasm.

The cumulative training efforts for objective 1f included 2 high schoolstudents (Owen, Floyd), 1 undergraduate student (Jackson), 1 post-doc (Prasad)and 1 technican (Ho).

g) Synthesis: Significant progress has been made in molecular genetic studies ofrice sheath blight resistance (SB). These accomplishments include improvedphenotyping methods, improved genetic stocks that contain major SB-QTL,identification of resistant rice wild relatives, and high density genetic maps showingmajor and minor effect SB-QTLs integrated with expression profiles, and robustmapping populations derived from rice cultivars adapted to the US.

Accurate phenotyping was one of the major constraints for genetic studies on thiscomplex quantitative trait, and advances in this area occurred with the developmentof a standardized greenhouse screening technique. The improved greenhouse methodknown as the “micro-chamber method” measures in a very short period of just 7 daysthe disease reaction of 3- to 4-leaf seedlings so that the phenotypic measurement formapping is independent of height, plant architecture, and heading duration that areknown to confound prior QTL mapping projects. Successful utilization andadaptation of this method has accelerated overall progress on the identification ofnovel resistant resources from wild relatives of rice and confirmation of engineeredresistance for determination of the functional contribution of candidate genes. Incollaboration with CIAT, this phenotyping method was ultimately transferred toCIAT in Colombia and several National Rice Research Programs in other LatinAmerican countries for the evaluation of sheath blight as well as other rice diseases.

The major breakthrough of the sheath blight mapping effort is the identificationand confirmation of a SB-QTL with major effect. The major effect QTL, qSB9-2, atthe bottom of chromosome 9, contributes more than 20% of the measured(phenotypic) disease severity. This QTL has been identified in four mappingpopulations, SB1, SB2, SB4, and SB5, across all tested environments, including theuse of the micro-chamber phenotyping method. The major qSB9-2 QTL maps to asimilar location seen to harbor SB-QTLs in studies involving indica/japonica crosses(TAG. 1995, 91: 382-388; Crop Sci. 2005, 45: 503-510) and a tropical japonicaintercross (in RiceCAP SB1; Sharma et al. in press, Crop Sci. 2009). Confirmation ofqSB9-2 is a significant advancement in the quest for genetic resistance to sheath

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blight disease. Identification of 400 highly and differentially expressed rice genesfrom the cultivar Jasmine 85 in response to the early infection by R. solani by DNAmicroarray and SAGE has provided a critical platform for fine mapping. Some ofthese highly and differentially expressed genes have been mapped at qSB9-2 and atother minor effect QTLs. Within SB4, an additional mapping population, markersaturation (cM distances < 0.5) was achieved in the region of qSB9-2 and 47 progenylines containing new recombination points within this region have been identified tosupport continued efforts to fine map this QTL. Additional molecular markers arebeing developed from candidate genes to delineate the physical location. Nevertheless, molecular markers RM245 and RM215 associated with qSB9-2 cannow be used to monitor the introgression of qSB9-2 from the rice cultivar Jasmine 85into elite breeding lines for pyramiding genetic resistance to the sheath blightpathogen. New recombination around a second SB-QTL, qSB12-1, on chromosome12 has also been identified in 35 progeny lines from SB4 to support fine mapping ofthis QTL. Other minor effect QTLs identified on other chromosomes can now bemonitored. Together, these confirmed and newly identified SB-QTL present anexcellent opportunity for the determining the contribution of individual QTL tosheath blight resistance and validation of candidate genes using tools developed bythe team members in objective 2.

Absence of germplasm with complete resistance to the sheath blight pathogen incultivated rice worldwide has made wild relatives of rice (Oryza species) an attractivealternative to identify novel sources of genetic resistance. The major accomplishmentin this aspect is the identification of seven moderately resistant accessions of Oryzaspecies: O. barthii (IRGC100223), O. meridionalis (IRGC105306), O. nivara(IRGC104705, IRGC100898 and IRGC104443), and O. officinalis (IRGC105979).These newly identified rice wild relatives may contain novel SB-QTLs. Research isunderway to identify these novel SB-QTLs and incorporate them into rice varietiesadapted to the US. Because the infection process of Rhizotonia solani is complex,little is known about the effect of the fungal extracts including the host specific toxinto the host plant. Another important accomplishment is the isolation of toxin thatinduces robust phenotypic responses on the leaves of rice cultivars. Purified toxin hasbeen used to determine genetic factors that contribute to the sheath blight resistance.

Considerable effort should be directed toward fine mapping and ultimatelycloning qSB9-2 for a better understanding of the molecular mechanisms of sheathblight resistance. Future research should utilize the numerous improved geneticstocks in combination with robust molecular markers, such as RM215 and RM245,for marker assisted introgression to capture a favorable plant architecture based ontiller angle, plant height and heading duration to reach maximum yield potential.Effort should be expended to continue identification and stacking of new resistancesources from wild species into diverse elite lines for the development of bothconventional and novel methods to manage the sheath blight disease in rice.

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2. Milling Yielda) MY1

(1) Description: Some 500 F11 random lines from the MY1 RT0034/Cypresspopulation were provided to the RiceCAP project by RiceTec, Inc., Alvin, TX.Cypress (PI 561734) is a long-grain, early-maturing semidwarf japonica varietywith outstanding milling yield. RT0034 is a long-grain breeding line fromRiceTec, Inc. (Alvin, TX) derived from an indica/japonica cross, and has highyield potential but poor milling quality. Based upon molecular marker analysis,129 F12 lines were evaluated during 2005 at Beaumont, Crowley, and Stuttgart.This population was chosen because of the divergence in milling yield and highdegree of polymorphism.(2) Approach: The study was conducted as a randomized block design with tworeplications. Repeated controls included the parents (RT0034 and Cypress) andother check varieties. Field studies were planted relatively late to subject thepopulation to greater environmental stress during grainfill and help differentiatethe RILs for milling quality. Fungicides were applied in a preventative fashion;however brown spot disease (Bipolaris oryzae), though it is rarely a problem insouthern germplasm, was significant at Beaumont. Data were collectedthroughout the season on plant stand, days to heading, tillering, plant height, anddisease incidence. Plots were harvested as they reached maturity, grain moisturewas recorded, samples were dried to 12% moisture and then sealed in plastic bagsuntil milling.(3) Genotyping: Parents were surveyed with a set of 630 SSR. Of these, 434 werepolymorphic and 152 were selected to be evenly spaced intervals (5 to 10-cM)along the reference map. The ratio of homozygous genotypes for RT0034 andCypress was 12319:6562 indicating that the population was skewed towardsRT0034 alleles.(4) QTL Analysis: QTLs for head-rice yield were not expressed consistently inthe two growing locations. Joint analyses showed one potential QTL for head riceyield on chromosome 9, with the favorable allele contributed by Cypress. Acluster of apparent QTLs for head-rice yield were identified on chromosome 8and were associated with grain maturity.(5) Conclusions: Six QTL for whole grain milling yield were identified onchromosomes 5, 6, 8, 9, and 10. The QTL with the largest LOD score was locatedon chr 9 and was associated with Pre-broken. The QTL located at chr 5 pos 3 andchr 8 pos 18 appeared to be independent of other traits. Milling yield was poorlycorrelated across the two locations as would be expected in a quantitativelyinherited trait that is susceptible to environmental fluctuations. However,Prebroken% was highly correlated with whole milling yield at both locations(r>0.75) suggesting it could be used as a predictor of quality prior to conductingthe labor intensive process of milling. Although there was significant variation forgrain dimension traits in this long grain x long grain cross, the traits were verystable across locations indicating that these can easily be selected for. Some 25QTL were identified on chromosome 8 that are components of rice grain quality.Although significant QTL were identified for milling yield and itssub-components, allelic distortion that was observed in favor of the RT0034

35

parent and the relatively small population size may have obscured the detection ofother QTL for milling quality.(6) Deliverables: A publication was drafted and submitted to a journal and is stillunder review.(7) Future: The population was observed to segregate for brown spotsusceptibility. A greenhouse screening method was developed for brown spotresistance will be used to evaluate MY1 progeny lines that exhibited extremedifferences in susceptibility under field conditions. It is possible that MY1 may beuseful in identifying QTL for resistance to this disease.

b) MY2 (1) Description: The MY2 population of 298 F6 recombinant-inbred lines (RILs)was developed from a cross of two long-grain US rice cultivars with high grainyield potential. Cypress shows generally high whole milling or head-rice yield(HRY), while LaGrue shows high HRY only in favorable environments, asindicated in Table 1.

(2) Approach: About 500 F4 lines were advanced in Crowley, LA and Beaumont,TX and DNA from about 300 F5 progeny was evaluated by K. Moldenhauer inStuttgart, AR with five SSR markers to test for segregation anomalies indicatingselfs and outcrosses. Only 1% of the progeny were outcrosses. Progeny wereincreased at two locations in 2005, but the planting in Beaumont was lost as aresult of hurricane Rita. F6 progeny were harvested by S. Linscombe at Crowleyand 325 F6 were planted in summer 2006 and 2007 at Crowley and Stuttgart inreplicated trials.(3) Genotyping and genetic-map construction: The Fjellstrom lab at Beaumontgenotyped the 325 lines for selected SSRs, numbering 107 after quality control.Of these lines, 16 were found to be Cypress selfs, 6 to carry too many nonparentalalleles, and 5 to be highly heterozygous, reducing the mapping population to 298RILs.

Table 1. Comparison of MY2 parents grown in Crowley, LA and Stuttgart, AR in 2005. (A. McClung)

Arkansas LouisianaLGRU CPRS LGRU CPRSMEAN SD MEAN SD MEAN SD MEAN SD

% Whole 59 4.2 57 6.5 51 6.8 65 3.3% Total 69 2.9 68 1.8 68 2.9 71 1.9% Pre-broken 27 7 26 9.9 43 5.5 18 5.3% Green 1.08 0.35 1.38 0.3 3.57 1.4 1.87 0.7% Chalk 3.82 0.8 2.82 0.8 6.92 1.08 3.6 0.5Length 7.13 0.07 7.15 0.31 7.31 0.03 7.12 0.07Width 2.13 0.04 2.12 0.03 2.15 0.01 2.16 0.03% Induced Fissure 13.96 4.76 22.22 8.68 35.43 3.97 19.05 4.771000 Kernel Weight 19.22 1.24 18.45 1.08 20.66 0.61 18.88 0.65

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The genetic map assembled with CarthaGene software is shown in Figure 1.Markers found to be unlinked, but assigned to chromosomes based on referencerice maps are shown in expected order but separated by 50-cM distances (see forexample chromosomes 4 and 10). The irregular marker coverage reflects thedifficulty of finding polymorphic, high-quality SSRs in many regions.

Overall marker segregation was 41:40:15:4 (Cypress CC: LaGrue LL:heterozygote LC: missing data), giving an excess of heterozygosity correspondingmore closely to an F4 than to the F6 generation. The distribution of segregation ofindividual markers is shown in Figure 2. Regions of distortion appear onchromosomes 2, 9, and 11.

(4) QTL analysis(i) Conventional QTL analysis: Conventional QTL analysis of HRY usingmultiple interval mapping (MIM) revealed several putative QTLs, none ofwhich were expressed in both AR and LA, though several in both years at oneof the locations. The strongest candidates are shown in Figure 3.

In the plot it is seen that the most reproducible effects appear onchromosomes 1 and 9 for AR and chromosomes 8 and 10 for LA, and that atall but the chromosome-8 putative QTL the HRY-increasing allele is that ofCypress, as would be expected. When the QTL profile for days to heading issuperimposed on the HRY profile it is seen that the QTLs lying onchromosomes, 2, 7, 8, and 10 and observed only in Louisiana coincide withearliness QTLs. This indicates that early heading increased HRY in Louisianabut not in Arkansas. Application of a more elaborate mapping approach basedon incorporating weather records for key stages of grain filling suggested thatearly heading allowed avoidance of high nighttime temperatures at the

Figure 2. Marker genotype segregation in Cypress x LaGrue rice F6 RILs. Vertical axis represents proportion of total nonmissing genotypes accounted for by the homozygous (LL and CC) and heterozygous (LC) genotypes shown in the legend.

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Figure 1. Genetic map of Cypress x LaGrue cross, constructed from 298 rice RILs.

Figure 3. QTL profiles of head-rice yield and heading date in 298 Cypress x LaGrue RILs. Only chromosomes with LOD peaks exceeding a nominal 0.05 acceptance threshold of 3.35 are shown. Lower plot shows magnitude and direction of additive QTL effects.

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hard-dough stage of kernel development. Because these temperatures aresome 10/ lower in Arkansas, this mechanism would not operate there,explaining why these earliness/HRY QTLs were not detected there. Thepractical implication of this finding is that early heading is advantageous inLouisiana for Cypress and presumably other cultivars with Cypress'smilling-quality genetic background.

HRY QTLs on chromosomes 1 and 9, with HRY advantages of around 1%contributed by the Cypress parent, were identified only in Arkansas. TheCypress genotype at the chromosome-1 QTL also lengthens the grain-fillingperiod (time between heading and harvest) by about two days, apparentlyresulting in superior milling yield in that environment.

(5) Conclusions: QTLs for earliness explain about a third of milling-yieldvariation in Louisiana in the Cypress x LaGrue cross. Application oflocation-specific weather records to multi-environment QTL analysis points atlate grain-filling stages as being most sensitive to environmental stress. Despitethe large size of this population, we have identified no environmentally stableQTLs that would account for Cypress's reputed HRY stability. It should beemphasized that the genetic map coverage has large gaps, so that important QTLscould have been missed.(6) Deliverables: Our analysis provides up to 5 QTLs that together accountpartially for the superiority of Cypress in certain growing environments. Thoughthey are subject to validation and are almost certainly phenology QTLs ratherthant QTLs for HYR per se, the QTL-linked markers could be used forcombination of the QTL alleles (four from Cypress, one from LaGrue) to developcultivars with higher and more stable head-rice yield.(7) Future: While the RIL population and its experimental management seem tobe of good quality, the genetic marker map shows very uneven coverage. Inconsequence, we cannot tell how many QTLs have been missed by eitherconventional or covariate QTL analysis, so do not know the full potential of ourstatistical approach. We recommend

(i) Fuller coverage of the map by means of additional genotyping, perhapswith SNPs. No additional phenotypic data are needed with this, although athird year of field and laboratory data would add much power to the QTLanalysis.(ii) Addition to the model of spatial covariates based on field planting layoutto reduce variation due to field trends.(iii) Application of an environmental-covariate model to the MY1 data(already begun) for support of the MY2 results based partly on the commonparent Cypress, and to the MY3 data for perspective based on consideration ofthe quite different California weather conditions.(iv) Conduct of a historical study based on rice Uniform Regional Nurserytrials with associated weather records and collection of genotyping data for aset of reference cultivars chosen with careful attention to their pedigreerelationships. The approach would employ single-marker association testsrather than an interval-mapping method, and require sufficiently densegenotyping (at least 20 well-distributed markers per chromosome).

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c) MY3 (1) Description: MY3 milling yield population is derived from a cross betweenL-204 and a California breeding line, 01Y110. L-204 is a long grain Californiacultivar with consistently high milling yields of 65%, whereas the advancedbreeding line 01Y110 has high yield potential, but consistently low millingquality, averaging 57%. Differences in the agronomic characteristics between thetwo parents are relatively small. Grains of L-204 are larger than 01Y110 (Table1).However, no obvious grain abnormalities such as grain curvature and excessivechalkiness are apparent in the two parents which could explain these largedifferences in milling quality. It is likely that having fewer possible factorsaffecting milling in this population may provide a better contrast for detectinguseful markers for milling per se. Amylose content differs between the twoparents with L-204 having intermediate amylose (23%) content, while 01Y110contains high amylose (25%). The purpose for evaluating this cross was toidentify and validate markers for milling yield in a temperate Japonica cross, adifferent gene pool than MY1 or MY2. The MY3 population (L-204/01Y110)was advanced through selfing in the summer and winter nurseries at Biggs, CAand Hawaii. Plants were bagged to minimize out crossing and 232 F7 RIL wereproduced for planting in 2007.(2) Approach: F7 panicle rows were planted in randomized complete blockdesign with two replications at Biggs, CA in May, 2007. Each block contained232 RILs, four rows of the parents L-204 and 01Y110, and one row of L-206 as acheck. Experimental units were 4' rows with 18" row spacing. Rows wereharvested as close as possible to the optimum moisture content of 17%. Data wascollected on agronomic traits, hourly relative humidity and temperature, andharvest moisture. Milling yield was determined using standard McGill No-2 mill.Field fissuring was determined from sub-samples that were used in milling yielddetermination. For fissuring susceptibility evaluation, a specialized hydrationchamber was developed to rehydrate dry rough rice samples for a sufficientperiod of time that would induce up to 95% fissuring in the most susceptible line.All 3 milling populations of MY1, MY2, and MY3 were phenotyped for fissuringresistance using the same fissure induction system. Other variable that weremeasured included grain dimension, percent chalky and immature kernels, RVApaste viscosity curve, and the waxy marker RM190. The study was repeated in2008 and is expected to be completed by March 2009. An additional, planting wasmade two weeks later, which can serve as a third environment.(3) Genotyping: Leaf tissue samples of the population and parents grown in thegreenhouse facility at Biggs, CA were sent to the USDA molecular genetics lab inBeaumont, TX for DNA extraction. DNA extracts were then sent to the genomicslab at USDA-MSA in Stoneville, MS for genotyping. Ninety nine SSR markersfound to be polymorphic between L-204 and 01Y110 parents at USDA Beaumontfacility were used for genotyping analysis. At the present time, marker analysis isongoing, with 96 markers already having been scored. An additional 30 to 50 SSRor SNP markers are scheduled to be scored for this population, to provide a totalof 120 to 150 markers used for mapping QTLs for milling yield and milling-related traits.

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Head Rice(HR) Field Fissuring(FF) Total Fissuring(TF) GrainNAME H2O min max ave min max ave min max ave Length Width 1000KWMY3Pop.

17.4 42.8 67.7 59.5 0.0 37.2 5.1 8.7 98.9 56.5 7.80 2.42 22.36

L204 16.1 62.6 66.8 64.4 0.0 7.8 3.2 23.8 80.6 52.9 7.84 2.47 22.901Y110 17.0 56.4 59.1 57.7 0.0 7.1 3.2 26.4 62.6 44.8 7.25 2.38 19.8

MY3 Correlations w/o ImDam > 12% HR x FF 0.62HR x TF 0.13HR x H2O 0.18HR x ImDam 0.20H2O x FF 0.13H2O x TF 0.34

(4) QTL Analysis: Pending(5) Conclusions: Although only a limited amount of data has been analyzed sofar, there are some common trends that have been observed in other milling yieldpopulations. The correlations above indicate that field fissuring (FF) hasmoderately strong correlation with head rice yield. This association has beennoted in other mapping populations.(6) Deliverables: A fissuring resistance screening system have been developed atRES Biggs, CA that allows screening of a large number of breeding lines.Approximately 5000 samples have been screened thus far for fissuring resistancein the three RiceCAP milling populations. Additionally, a new study wasconducted in conjunction with the RiceCAP project that has demonstrated thatlevel of fissuring resistance of a genotype can be influenced by the environment. (7) Future: The phenotypic and genotypic assessment of the MY3 population isexpected to be completed by early 2009. Results will be compared with those

0

2 0

4 0

6 0

8 0

10 0

12 0

2 6 10 14 18 2 2 2 6 3 0 3 4 3 8 4 2 4 6 50 54 58 6 2 6 6 70 74 78 8 2 8 6 9 0 9 4 9 8

% F issur ing

F ield F issur ing ( F F ) L2 0 4 =3 .2 %, 0 1Y 110 =3 .2

Ind uced F issuring ( T F ) L2 0 4 =52 .9 %,0 1Y 110 =4 4 8 %

02 0

4 06 0

8 010 0

4 4 4 6 4 8 5 0 5 2 5 4 5 6 5 8 6 0 6 2 6 4 6 6 6 8

% Head R ice ( HR )

Head R ice: L2 0 4 =6 4 .4 %,0 1Y 110 =57.7%

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from MY1 and MY2 to validate previous findings as well as identify new QTL.Ultimately the mapping population will be made available to the public and anyspecific RIL lines possessing unique combinations of alleles for milling QTL canbe provided to breeders to incorporate into their programs.

d) Synthesis (1) Description: Three mapping populations have been developed by RiceCAPfor QTL analysis of head-rice yield (HRY) and related grain-quality traits. All ofthese materials are US cultivars or breeding lines, with crosses selected fordivergent HRY between parents (in the table, the higher-HRY parent is shownfirst in each pair) and similarity of other kernel dimension and qualitycharacteristics to minimize confounding with HRY variation.

Name Cross Description Phenotyping GenotypingMY1 Cypress x RT0034 129 F7 RILs AR, LA 2005 152 SSRsMY2 Cypress x LaGrue 298 F7 RILs AR, LA 2006–07 107 SSRsMY3 L-204 x 01Y110 232 F7 RILs CA 2007–08 120–150 SSRs (pending)

(2) Approach: During phenotypic evaluation, hourly weather data were recordedat all locations for all populations. All RILs were scored for standard agronomictraits as well as grain quality traits. For fissuring susceptibility evaluation aspecialized hydration chamber was developed to rehydrate dry rough rice samplesfor a period of time sufficient to induce 95% fissuring in the most susceptible line.This method was used for efficient screening of 5000 samples from the threeRiceCAP populations.(3) Genotyping: Polymorphic markers were identified by screening of all parents(Fjellstrom, Beaumont TX) for sets of SSRs recommended by the Nelson lab forsuitable spacing on the reference rice genetic map. Markers were found for someremaining gaps (regions of low polymorphism) but many gaps remained,especially in MY2. These are undesirable because QTLs in these regions goundetected in subsequent analyses. (4) QTL analysis: Standard QTL analyses applied to MY1 and MY2 showedputative HRY QTLs, but expressed in not all environments (location-yearcombinations). In particular, in MY2 all four QTLs expressed in Louisiana appearto be identical with heading-date QTLs, so that in Louisiana, but not in Arkansas,earliness QTL alleles (3 Cypress, one LaGrue) confer higher HRY. A moreelaborate analysis incorporating weather covariates such as temperature andhumidity during selected grain-filling stages for each RIL, harvest moisturecontent, percent chalky kernels, and percent green kernels supports a mechanismof avoidance of high nighttime temperatures during the hard-dough stage. Harvestmoisture did not affect HRY when the weather covariates were in the model,suggesting that the effect on milling yield had already been exerted at the time ofharvest. For MY1 QTL analysis suggests at least two other QTLs, one associatedwith early heading in Louisiana. However, no Cypress QTLs are common to thesetwo Cypress crosses. Preliminary QTL analysis of MY3 based on one year offield evaluation and 95 SSRs shows no association of HRY QTLs with

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heading-date QTLs, consistent with observation that in California differentenvironmental factors affect HRY than in the southern rice-growing regions.(5) Conclusions: Application of location-specific weather records tomultienvironment QTL analysis improves the reliability of identification of QTLswith strong environmental interactions. We have identified five QTLs in the MY2population that together explain about 35% of milling-yield variation and twopossible QTLs in MY1. It must be emphasized that the most plausible of theseQTLs affect HRY only indirectly, via advancing heading date (in Louisiana) ordelaying harvest date (in Arkansas). We have not identified a QTL for HRY perse. We suggest that this will require a larger multi-environment study or an assayunder controlled conditions that duplicate the environmental stresses that exposedifferential HRY performance.(6) Deliverables: Our analyses provide up to five QTLs that together accountpartially for the HRY superiority of Cypress over two other parents in certaingrowing environments. After sufficient validation, the linked markers could beused for combination of the QTL alleles (three from Cypress, one each fromLaGrue and RT0034) to develop cultivars with higher and more stable head-riceyield.

A new fissuring-resistance screening system developed at RES Biggs, CAallows screening of a large number of breeding lines.(7) Future: Small population size (MY1), anomalous genetic segregation, anduneven marker coverage of the genome have interfered with QTL discovery, butthe latter two are “occupational hazards” in the QTL-mapping business. The MY3QTL analysis will provide information bearing on California growing conditions,where variation in humidity near harvest maturity may be more relevant to HRYthan nighttime temperatures.

Efforts should be made to fill in the MY2 marker coverage, perhaps withSNPs rather than SSRs.

The application of weather data to QTL analysis of the highlyenvironmentally-sensitive HRY trait suggests the initiation of historicalassociation-mapping studies exploiting detailed weather and agronomic recordsfrom uniform regional nursery trials combined with high-throughput retrospectivegenotyping of selected rice breeding lines and cultivars tested in those trials.

Because in our RiceCAP materials, HRY QTLs from opposite parents showedcontrasting responses to environmental effects such as nighttime temperature atlate grain-filling stages, there is hope that combining these QTLs in a singlegenetic background would confer stability of HRY in diverse growingenvironments.

3. Association Mapping a) Description: This project is structured to determine genetic diversity present inUS historic rice germplasm and elite rice breeding materials from each of the publicsector rice breeding programs in the United States. The knowledge of haplotypeblocks which have become fixed through selection in each state's rice breedingprogram may offer potential for increasing diversity by introducing new genes intothese areas of the genome or, conversely genomic tools to keep valuable linkageblocks together. The association mapping component of this study will identify

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markers associated with genes for important yield-components enabling rice breedersto more efficiently develop of new higher yielding rice varieties.

Seed from 472 rice entries (consisting of 131 historic U.S. rice accessionsspanning the years from 1900–2000, and 341 elite breeding lines selected from theUniform Regional Rice Nursery (URRN)) were purified by single-seed-descent tocreate the population for this study. US historic germplasm was obtained frompurified seed supplied by Dr. Neil Rutger, USDA-ARS, Stuttgart, AR (retired).Approximately 30 diverse pedigrees from each state's breeding program that werepart of the URRN in 2004, 2005, and 2006 were chosen for evaluation.b) Approach: Five seed of each entry were planted in the greenhouse in 2006 and arepresentative plant was selected for seed increase. Each entry was planted in thefield at Stoneville, MS in 2007 for seed increase and leaf tissue collection. In 2008,the population was planted in a randomized complete block design with 2 replicationsin AR, LA and MS. Two repeated checks were included in the planting to occur oncein each of four blocks of 118 entries to facilitate statistical analysis of field variationeffects. Phenotypic data on seven yield-component traits were collected from 2representative plants for each experimental unit. Data were collected on heading,height, maturity, productive tiller number, panicle length, seed/panicle, seed weightand biomass production.c) Genotyping: The genotypic analysis of the population by itself will provide usefulinformation to the rice breeding community about the population structure, diversity,and linkage disequilibrium present in the historic US rice pedigree and in each state'srice breeding program. This information on US rice germplasm will also complementthe NSF-Transgressive Variation study being performed by Dr. Susan McCouch atCornell University and Dr. Georgia Eizenga, USDA-ARS, Stuttgart, AR, on apopulation consisting of worldwide rice germplasm and present an opportunity forcomparison of U.S. and world rice germplasm. Dr. McCouch offered their IlluminaGoldengate 1536 SNP assay for the analysis. The SNPs were selected from thePerlegen dataset which included 20 diverse landraces representing all 5subpopulations of Oryza and resulted in over 1200 scoreable SNPs in this population.In addition, all RiceCAP parents were included in the SNP analysis and may identifynew markers that are useful in areas of the genome that appear to be monomorphicwith our current set of SSR markers.d) Association Analysis: Preliminary analysis indicates the set of 1536 SNPs maynot provide enough polymorphic information for association mapping and that agreater number of SNPs may need to be evaluated. This is likely due to the fact thatthe SNPs were selected to identify polymorphisms in international germplasm whichis much more diverse than the US germplasm that is predominant in this chosen set ofmaterials.e) Conclusions: Phenotypic data collection will be completed in early 2009 at whichtime association analysis using the SNP data will be conducted. At that point it willbe determined if additional marker analysis will be necessary.f) Deliverables:

(1) This project serves as the basis for Ph.D research project being conducted byMr. Walter Solomon and thus will result in increased expertise in translationalgenomics for the research community.

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(2) Pure seed of the 400+ genotypes has been deposited with the GSOR centerand will be made available to the research community.(3) Publications:

(i) Anticipated refereed publication: Solomon, W., Scheffler, B., McClung,A., Kanter, D., Oard, J., Zhang, W., Fjellstrom, R., Nelson, J.C., and Rutger,N. Association mapping of US germplasm pool. Crop Sci (Jun 2009).(ii) Abstracts/Presentations: Solomon, W., Oard, J., McClung, A., Wright M., Zhao, K., Reynolds, A., Bustamante, C., McCouch, S., Scheffler, B.E.Analysis of the RiceCAP germplasm panel for SNP diversity, populationstructure and seven yield-component traits of rice. Plant and Animal GenomeConference 2009. San Diego, CA 01-10-15, 2009.

g) Future: As a result of our interaction with Susan McCouch and her NSFfunded project, a new 1536 SNP chip is being developed that will be better suitedfor use with US breeding material which is predominantly tropical japonica andhas a narrow germplasm base. This chip will be useful in identify linkage blocksunique to US elite breeding lines that can be further evaluated in recombinationstudies to determine if these superior allelic combinations that are a result of yearsof breeding improvement or if they are genetic bottlenecks that are limiting thepotential of US cultivars. Ultimately, utilization of the 40,000 Affymetrix SNPchip that is under development may be necessary to address these and otherfine-mapping questions.

4. Germplasm: Key germplasm has already been transferred to US rice breeders fromthe RiceCAP project. Five sheath blight resistant lines derived from SB5 have beenincorporated into breeding programs in AR, LA, and CA. Three TIL lines developedfrom SB4 and which possess novel sheath blight resistance introgressions have beenreleased to the public. The SB2 population has been registered and is available for publicdistribution through the Genetic Stock Oryzae Resource center (GSOR) (located at theUSDA/CSREES Dale Bumpers Rice Research and Extension Center located in Stuttgart,AR. Plans are underway to make the MY1, MY2, MY3, SB4, and SB5 populationsavailable in 2009 through GSOR also. Germplasm lines developed from introgressionsfrom wild species will be made available in 2010. Likewise any lines identified in theother mapping populations that could be used directly by breeders will be made available.5. Markers: Molecular data on 896 SSRs screened using the RiceCAP parental lineswas made available to all RiceCAP collaborators via the RiceCAP website. SufficientSSR coverage is present for all three milling yield and all four sheath blight RiceCAPmapping populations. Due to the common use of many of these parental lines (and othercultivars that are highly related to them) many of these markers will be useful in USbreeding programs.

In part due to the RiceCAP project, all US public rice breeding programs are nowusing molecular markers in their variety development programs. Markers are being usedto evaluate breeding materials for several grain quality traits and major blast resistancegenes.

In addition to using these markers to make early generation selections and verify thepresence of genes in advanced breeding lines, they are also being used for quality controlin F1's and during the purification process of new releases. As a next step, a set of 15SSR markers that are linked to various economically important traits have been

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developed so that they can be efficiently evaluated on breeding lines throughmultiplexing. This will decrease the cost of genotyping tremendously and is yet anotherstep in transferring marker technology to breeders.

Previously, the rice community did not have interaction with the USDA-ARSMid-South Area Genomics Laboratory in Stoneville, MS, which has tremendousgenomics capabilities. As a result of RiceCAP, the MSA Genomics lab is now a keycomponent to the milling, sheath blight, breeding, and association mapping studiesfundamental to the project. Using high throughput technology, this lab has genotyped theMY2, MY3, and SB2 populations, each containing 325 or more lines. This partnershipwith the MSA Genomics lab led to extension of MAS to the breeding programs in MSand MO and to the development of a grant proposal to identify novel blast resistancegenes led by Scheffler and researchers at ARS Stuttgart and Beaumont, and University ofArkansas that has been funded by the US Rice Foundation. This project will lead to moremarkers and novel genetic resources for use by the US breeding community.

LaGrue and Cypress (MY2 parents), well known for high yield and milling quality,are being fully sequenced using Solexa technology through a contract with NationalCenter for Genome Resources (NM). The information will be shared and eventually usedin the development of a US cultivar SNP chip. ~2.3 X genome coverage of LaGrue andCypress will be generated and made public, and published (by G. May, R. Fjellstrom andB. Scheffler; Anticipated date: April 2009).

Affymetrix microarrays were used to identify 4582 unique candidate SFP markersbetween Cypress and LaGrue, the parents of the MY2 mapping population. Thesemarkers are found throughout the rice genome and a validation survey of 78 candidateSFPs showed that 77 of them correctly identified a true polymorphism (98.7% accuracy).Twenty candidate SFPs on 8 chromosomes (1, 5, 6, 7, 8, 10, 11, 12), which haverelatively large gaps (>20 cM) between SSR markers in the MY2 and SB2 mappingpopulations, are being evaluated to increase marker saturation, and as a result, improveQTL mapping efforts.

Partnering with Dr. Susan McCouch (Cornell Univ.) has resulted in access to SNPtechnology for evaluating over 400 cultivars that are representative of the US gene pool.This project will provide yet another set of informative markers to the US breedingcommunity to use in varietal development programs.

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7. OBJECTIVE 2 - GENE FUNCTION EFFORT

A. Introduction: To complement the effort of Objective 1 of RiceCAP, the Objective 2team has focused on validating the function of rice candidate genes associated with sheathblight resistance and milling quality. Both genome-wide expression profiling and targetedapproaches have been taken to identify candidate genes related to sheath blight resistanceand milling yield. Massively parallel signature sequencing (MPSS) has been conducted toidentify rice genes that were differentially expressed in high- and low-milling yield cultivarsduring the grain filling. Robust long SAGE and microarray analyses were used to identifydifferentially expressed rice genes following the Rhizoctonia solani infection.Defense-related genes were also identified based on protein-protein interactions, defensepathway analysis, database and literature searches. Many of these candidate genes have beenmapped onto rice chromosomes for their association with sheath blight resistance and millingyield QTLs. Using RNA interference, transgene overexpression and mutant analysis, abouttwo dozen of the targeted candidate genes have been functionally characterized for theirpositive or negative role in regulating sheath blight resistance. While our main objective is toidentify and validate candidate genes associated with sheath blight resistance and millingquality, we also conducted the OryzaSNP study and initiated transcriptome and secretomeanalyses of R. solani to identify fungal genes and protein effectors that are important forpathogenesis. We also developed vectors and protocols for virus-induced gene silencing,RNAi, protoplast manipulation and efficient rice transformation that contribute to the ricebiotechnology toolbox. Furthermore, additional funding was obtained that should leveragethe existing RiceCAP effort and further benefit the US rice community.

B. Overview of Project Results1. RL-SAGE and microarray analysis of the rice transcriptome after Rhizoctoniasolani infection: Sheath blight disease, caused by the pathogenic fungus Rhizoctoniasolani, is one of the most prevalent rice diseases, causing severe damage to rice yieldsworldwide. Because of its semi-saprophytic nature, R. solani has a wide host range andthe pathogenicity mechanisms are largely uncharacterized. No rice germplasm has beenidentified that is highly resistant to the pathogen. It is generally believed that resistance toR. solani is a typical quantitative trait controlled by polygenes and that only partiallyresistant or tolerant varieties exist in the worldwide collection of rice germplasm. Toelucidate the molecular basis of rice defense to the pathogen, Robust-Long SAGE(RL-SAGE) techniques were employed to profile the defense transcriptome of R.solani-infected rice plants. The US rice cultivar Jasmine 85 was used in the study since itis known for its relatively high level of resistance to R. solani under field conditions.RNA isolated from R. solani-infected and uninfected leaves of Jasmine 85 was used forthe construction of two RL-SAGE libraries. A total of 3,456 and 3,264 clones randomlypicked from the control and inoculated libraries, respectively, were sequenced. From theraw sequence reads, 90,230 and 78,218 individual tags were isolated from the control andinoculated libraries, respectively. RL-SAGE sequence analysis identified 20,233 and24,049 distinct tags from the control and inoculated libraries, respectively. Nearly half ofthe significant tags (>2 copies) from both libraries matched TIGR annotated genes andKOME full-length cDNAs. Among them, 42% represented sense and 7% antisensetranscripts, respectively. Interestingly, 60% of the library-specific (>10 copies) and

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differentially expressed (>4.0 fold change) tags were novel transcripts matching genomicsequence but not annotated genes. To compare RL-SAGE with microarray analysis, thesame RNA samples used for RL-SAGE analysis were used for microarray hybridizations.Interestingly, about 70% of the genes identified in the SAGE libraries showed similarexpression patterns (up or down-regulated) in the microarray data obtained from threebiological replications. Many genes specifically induced or suppressed in the infectedleaves were identified. Most of them are defense and cell-death related genes. About 8%of the tags from the control and inoculated libraries represented antisense transcripts ofannotated genes. A total of 422 genes that produced antisense transcripts were specific tothe inoculated library. Some of them encode proteins containing NB-ARC, zinc finger orkinase domain and other defense-related motifs. Many annotated genes contain bothsense and antisense transcripts in the control (558 genes) and inoculated (525 genes)libraries. Many pathogenicity-related genes generated both sense and antisensetranscripts and were present only in the inoculated library. To investigate the relationshipbetween the identified candidate genes and known sheath blight QTLs, highly inducedand suppressed candidate genes were chosen for mapping in the rice genome. Mappinganalysis revealed that some candidate RL-SAGE tags and microarray genes were locatedin known sheath blight QTL regions. The expression of ten differentially expressedRL-SAGE tags was confirmed with RT-PCR. The defense genes associated withresistance to R. solani identified in this study are useful genomic materials for furtherelucidation of the molecular basis of the defense response to R. solani and fine mappingof target sheath blight QTLs. Detailed results can be found in the paper published inMolecular Genetics and Genomics, 2007. 278:421-431.2. Identification of milling yield related genes in the developing rice seeds usingmassively parallel signature sequencing: Milling yield is an important aspect of ricegrain quality and directly affects the economic return of rice farmers.

It is known that milling yield is a quantitative trait and influenced by environmentalfactors. Measuring the trait is time-consuming and difficult. In US rice breedingprograms, improving milling yield has been one of the major goals in the last decade.However, no significant improvement of milling yield in new rice cultivars has beenachieved because no DNA markers have been identified that are linked to the complextrait. To identify the genes involved in milling yield, a deep transcriptional analysis ofdeveloping seeds was performed using massively parallel signature sequencing (MPSS).Three rice cultivars with various levels of milling yield were selected in the study. TheUS cultivar Cypress is known for its high milling yield whereas the other US cultivarLaGrue is known for its low milling yield. The japonica cultivar Nipponbare has mediummilling yield and its genome has been completely sequenced. Plants of the three cultivarswere grown in the growth chamber until flowering. Three MPSS libraries wereconstructed using RNA isolated from 6-day-old developing seeds of the plants. About 1.0to 1.2 million sequence reads were obtained from the three libraries. The distinct tags are12,600, 18,297 and 16,499 in Cypress, LaGrue and Nipponbare, respectively. About 85%and 90% of the significant and reliable signatures from the libraries matched the indicaand japonica genomes, respectively. A total of 157, 176, and 186 genes were obtainedthat had 1000-10,000 transcripts per million (TPM) in the Cypress, LaGrue, andNipponbare libraries, respectively. Since transcription factors (TFs) play a major roleduring seed development, TFs specifically expressed in Cypress (65) and LaGrue (134)

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were identified. Conserved cis regulatory elements among the upregulated genes inCypress were identified. Many key grain quality genes belonging to starch metabolism,aspartate amino acids metabolism, storage proteins, seed maturation, seed specificexpression and seed allegens had undergone alternate splicing, produced antisensetranscripts or highly induced/ suppressed in different grain quality libraries. Further, atime course study of genes belonging to starch metabolism like ADP glucosepyrophosphorylase and granule bound starch synthase showed higher expression in highmilling Cypress compared to low milling LaGrue in early stages of seed development asevaluated by RT-PCR. To confirm the MPSS results, the same RNA samples of Cypress,LaGrue, and Nipponbare using for the MPSS library construction were used for makingthree SBS libraries. The libraries were sequenced using Solexa's Genome Analyzer.About 2.0 to 3.0 million sequence reads were obtained from these libraries. Bioinformaticanalysis is being performed to obtain the expression profile of each cultivar during earlyseed development and compare the results with those from the MPSS libraries. Once a setof candidate genes are determined from both datasets, mapping analysis will be carriedout to check if these genes are co-localized with milling yield QTLs obtained from theCypress x LaGrue recombinant inbred population. Our comprehensive and deep surveyof the developing seed transcriptome in three rice cultivars using both high through-putsequencing MPSS and SBS technologies provides a rich genomic resource of millingyield and grain quality associated genes for the community. Candidate genes for millingyield may be useful markers for molecular breeding in rice. Further functional analysis ofthese genes will provide new insights into the regulation of the genes in differentbiochemical pathways controlling milling yield and other quality traits in rice. 3. Functional validation of candidate genes associated with sheath blightresistance: About 40 candidate genes were selected based on differential geneexpression, protein-protein interaction, defense pathway analysis and/or previous QTLstudies. RNAi and/or overexpression constructs were made in Leach (GLPs, OXOs, PR1,chitinases and 14-3-3 genes), Ronald (Xa21 R protein interactors such as Xb10, Xb11,Xb11i, Xb15, Xb24, Xb25, and PR10a; NH1 and activation tagging lines), Yang (AOS1,AOC1, JAMyb, Myc2, COI1, EIN2, EIL1, MPKs and Nramps) and Wang (G-boxbinding protein, GST, inner evelope membrane protein, ribosomal S10) labs. Manytransgenic rice lines (T0, T1 and T2 generations) have been generated and analyzed forsheath blight resistance.

a) OsGLP genes. A cluster of 12 germin-like protein (OsGLP) gene membersco-localizes with a major effect blast resistance QTL on chromosome 8. A highlyonserved portion of the OsGLP coding region was used as an RNA interference(RNAi) trigger to silence a few to all expressed chr 8 OsGLP family members.Challenge with R. solani (causal agent of sheath blight disease) revealed that as morechr 8 OsGLP genes were suppressed, disease susceptibility of the plants increased. Ofthe 12 chr 8 OsGLP, one clustered subfamily (OsGER4) contributed most toresistance; this same subfamily contributed most to resistance to the rice blastpathogen. Our work suggests that resistance provided by the chr 8 QTL, whichcontains the OsGLP cluster, is broad-spectrum. b) OsOXO genes. A cluster of four putative oxalate oxidase (OsOXO) genemembers co-localizes with a moderate effect blast resistance QTL on chr 3. A highlyconserved portion of the OsOXO coding region was used as an RNAi trigger to

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silence all expressed chr 3 OsOXO members. Only one of the OsOXO genes,OsOXO4, is expressed during disease or defense responses. Challenge with R. solanirevealed that as silencing of the OsOXO4 gene expression increased, sheath blightdisease increased. Preliminary results (phenotyping done; testing for silencingunderway) indicate that the resistance contributed by OsOXO4 may be broadspectrum as well, because in the same T2 family exhibited enhanced susceptibility torice blast disease (M. oryzae) and bacterial blight (X. oryzae pv. oryzae). Theseresults are consistent with the hypothesis that the chr 3 QTL which contains theOsOXO4 gene contributes to broad spectrum disease resistance.c) OsCHI genes. A single chitinase (OsChi2) gene co-localizes with a minor effectblast resistance QTL on chr 2. Because the OsChi2 is associated with a minor effectQTL, we have increased the number of plants screened for disease response andgenotyping. Plants in populations from T0 through T2 lines show enhancedsusceptibility to R. solani. Our goal for the next year is to determine the relationshipof phenotype with silencing.d) JAmyb. Cell death-associated genes such as JAmyb were analyzed for potentialrole in sheath blight resistance. Using the coke bottle method, we found that inducibleoverexpression of cell-death associated JAmyb enhanced host susceptibility to thesheath blight pathogen.e) OsEIN2, OsCOI1 and OsMPK5. Rice transgenic lines defective in SA, JA, ETand/or MAP kinase signal pathways have been tested using detached leaf assay, cokebottle method and/or inoculation of adult rice plants with the fungal mycelial balls.Detached leaf assay showed that suppression of OsCOI1 enhanced diseasesusceptibility to sheath blight pathogen. Adult plant test demonstrated that OsEIN2positively regulate sheath blight resistance while OsMPK5 negatively modulate thesheath blight resistance. The same set of transgenic rice lines were also tested usingthe coke bottle method. However, the results from the coke bottle experiments usingthe two-week old seedling tests are not consistent with the previous tests usingtwo-month old plants. Further testing are required to clearly establish their role insheath blight resistance.f) OsGBP and OsGST. Inoculation tests with the R. solani strain Fleet -B2 usingthe micro chamber method showed that suppression of OsGBP resulted in enhancedresistance while suppression of OsGST led to increased susceptibility to sheath blightpathogen. Inoculation with T3 and T4 plants are being conducted in our lab and inDr. Jan Leach's lab at Colorado State University.g) Other transgenic lines: Transgenic lines produced in Ronald's lab has beenevaluated for sheath blight resistance. A number of lines were shown to conferslightly enhanced resistance to sheath blight.

4. Sheath blight disease assay and real-time PCR quantification: To facilitate sheathblight disease assay, a new method is developed using two-month old adult plants forbetter inoculation and evaluation of sheath blight disease in greenhouse. In addition, apair of specific primers was designed for real-time PCR detection and quantification of R.solani anastomosis group (AG) 1-IA isolates that infect rice. A statistically significantdifference in disease lesion length was observed between Nipponbare (susceptiblecultivar) and Jasmine 85 (moderately resistant cultivar). The real-time PCR

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quantification of R. solani DNA from infected leaves of Nipponbare and Jasmine 85 wasin agreement with the results obtained by lesion length measurements.5. Initiation of transcriptome and secretome analyses of R. solani: To understand therice-fungus interaction, transcriptome and secretome analyses of R. solani wereconducted to identify fungal genes and protein effectors that are important for the fungalpathogenesis. Total RNAs were extracted from R. solani mycelia grown in minimal vs.rich media. cDNA libraries were made for transcriptome sequencing using 454 approach.In addition, secreted proteins were collected from R. solani cultural filtrates andseparated using 2D PAGE. A total of about 130 protein spot samples were analyzed bymass spectrometry. Many of these secreted proteins may play an important role in thefungal pathogenesis.6. OryzaSNP project: Leach's group used resequencing microarrays to interrogate 100Mb of the unique fraction of the reference genome for 20 diverse varieties and landracesthat capture the impressive genotypic and phenotypic diversity of domesticated rice(www.oryzaSNP.org). Included in that set are two varieties recommended by theRiceCAP group, M202 and Cypress. We submitted (11/21/08) a manuscript thatdescribes the distribution of 160,000 non-redundant single nucleotide polymorphisms(SNPs) and which lead to linkage disequilibrium estimates of 200 to 500 kb for the indicaand japonica subgroups, respectively. Most interesting are the introgression patterns ofshared SNPs (performed by Keyan Zhao, Cornell) which revealed the breeding historyand relationships among the 20 varieties. For example, some introgressed regions areassociated with agronomic traits that mark major milestones in rice improvement such asthe semi-dwarf gene Sd1 important in the Green Revolution. The comprehensive SNPdata provides a foundation for deep exploration of rice diversity and gene-traitrelationships, and their use for future rice improvement.

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8. BIOINFORMATICS

A. Overview: The bioinformatics objective was added as a requirement by the proposalreview panel at the inception of the RiceCAP project. Clare Nelson (Kansas State University)was invited to join as bioinformatics PI and executive-committee member and provided withfunding for a postdoc and Ph.D. student. While the group's initial effort was toward settingup a relational database with WWW interface and query capability, meetings and conferencecalls with the other PIs beginning during the first year eventually established that this wasnot wanted within RiceCAP. The services considered most useful were data cleaning andanalysis of several kinds as well as creation of genetic and physical maps of rice, showinggenes and markers placed as part of the RiceCAP work.

This early change of focus reflected a recurring question: how should the RiceCAPbioinformatics group both serve the research needs of the RiceCAP participants and fulfil theobligation of the project to the broader scientific community? External reviewers focusing onthe second goal observed that the bioinformatics effort had not created a WWW database, butwere not aware of the amount of data processing and analysis that the small group could beexpected to handle in addition to managing this resource. Plans for data persistence after theend of RiceCAP also came under question.

The role of the bioinformatics group was resolved at a meeting at Stuttgart in September2006 in which several external reviewers with bioinformatics expertise (Kevin Childs, TIGR; William Beavis, NCGR; Peter Bradbury, USDA-ARS/Cornell University; Mauricio LaRota,Oregon State University; and Kathy Yeater, USDA-ARS) provided a critique of the effortand a list of recommendations. The consensus was that the group's primary client in the shortterm was properly RiceCAP researchers, and that delivery of project results to the broadercommunity, though essential, was only a longer-term goal. Dr. Nelson entered an informalunderstanding with Susan McCouch (Cornell), a principal of the Gramene database, that thisdatabase would incorporate RiceCAP results at any time, though work would be needed atboth donor and recipient end to prepare and document the data.

The bioinformatics component also included training. Dr. Nelson taught sessions at eachof the RiceCAP marker workshops in Stuttgart, AR and Ardmore, OK, dealing withmapping, QTL mapping, and databases. A mini-tutorial on creating comparative maps inGramene was conducted by WebEx connection with RiceCAP participants in early 2007.

Although a wide range of personnel (RiceCAP PIs, technical staff, students, etc.) havebeen trained indirectly in bioinformatics as a result of RiceCAP, three Ph.D. students (Guo,Boddhireddy, Joehanes) and three postdocs (Liu, Sun, and Lacaze) have been trained in thebioinformatics group as a direct result of partial or full support from RiceCAP.

B. Data Center: The Data Center is the part of the RiceCAP WWW site devoted tomaintaining data and posting analytical results, and is hosted on a University of Arkansascomputer, with secure access for data transfer by the bioinformatics group.

C. Organization: The Data Center is divided into six sections. Three of these, Public dataand Submit data, and People, have little content, leaving the following three:

D. Protected data: This page is reached via password distributed to RiceCAP participants.It contains hyperlinks to downloadable files representing almost all the original data supplied

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to the Bioinformatics group: microarray, SAGE, and MPSS data; Affymetrix GeneChip SFPdata, SSR selection screening results, marker genotyping and trait phenotyping results onthree populations, and the results of analyses conducted by the group including prepared filesfor QTL-analysis programs. Miscellaneous other files include presentations and submittedMSS.

E. Reference maps: The CMap application for drawing genetic and physical comparativemaps on WWW pages was installed on a KSU local host rather than on the UArk host, butthe interface is seamless. The “Reference maps” link opens an interface page allowing theuser to view, on a standard rice reference map, all the polymorphic SSRs identified in allRiceCAP crosses (figure at top right), as well as all of those actually genotyped in thepopulations. The main feature, however, is a master map incorporating candidate genes forsheath-blight response identified from literature and Gramene searches and RiceCAP SAGE,MPSS, expression array, SFP genotyping chip, candidate-gene-knockout, and proteomicsexperiments, as well as prior sheath-blight QTL-mapping results. A detail from this map isillustrated at right.

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F. QTL analyses: This section provides links to graphical output from QTLmapping in theRiceCAP crosses (MY1, MY2, MY3, and SB2) analyzed to date by the group. A samplepanel is shown below.

G. QTL-mapping software: Though software was not among the planned RiceCAPdeliverables, a talented Ph.D. student supported from RiceCAP bioinformatics funding, RobyJoehanes, has rewritten a popular QTL-mapping program, adding powerful statistical andvisualization features that have been very useful for analysis and display of RiceCAP data. Alink to the public distribution page of QGene 4.0 may be found in the Data Center:http://coding.plantpath.ksu.edu/qgene/

H. Data use: Data use from the Data Center (by RiceCAP participants, since access is stillpassword-protected) has not been formally tracked. Some of the QTL plots have appeared inRiceCAP posters and other reports and the master reference map described above has beenused in a published article. The QGene software referred to above has been downloaded >600 times, including by some RiceCAP participants.

Provision should be made for transfer of map and QTL data to Gramene aroundmid-2009.

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9. OBJECTIVE 3 - TECHNICAL TRAINING EFFORT

The objective of the technical training portion of the RiceCAP effort was to developtechnical training programs and resources to ensure implementation of molecular marker andgene validation technologies to solve rice problems.

A. Technical Training Workshops Conducted under this Objective for participants inRiceCAP:

1. RiceCAP Marker Assisted Breeding Workshop. “Markers Unleashed, AnOverview of DNA Marker Technology as it Applies to Rice Improvement.” DaleBumpers National Rice Research Center, June 14-16, 2005. Attendance: 150.2. RiceCAP Virus-Induced Gene Silencing and Stable RNAi Workshop. TheSamuel Roberts Noble Foundation, Inc., October 31-November 5, 2005. Attendance: 25.3. RiceCAP DNA Marker Workshop. “Markers, Mapping and Beyond.” The SamuelRoberts Noble Foundation, Inc., June 4-10, 2006. Attendance: 75.

Evaluation of workshops are in Section 9.c.

B. Other Workshops Conducted under this Objective for Outreach/Extension TargetAudiences:

1. Ken Korth. Laboratory Encounters in Plant Genomics. Arkansas AgriculturalExtension Lab, June 27-28, 2006.

From June 25 to 26, 2006, Ken Korth, in collaboration with Janice Stevens and PeggyLemaux, conducted a workshop in Lonoke, AR to introduce high school science andagriculture teachers to rice genomic-research tools. All supplies and equipment needed toconduct exercises were provided to participants to isolate plant DNA and analyze DNAvia electrophoresis. A rice dwarf mutant deficient in gibberellin synthesis will be used todemonstrate principles of plant hormones and mutation. An exercise was provided on CDto demonstrate computer-based gene analysis and the teachers were introduced toRiceCAP, its goals, and how the principles covered in the workshop were being appliedin the RiceCAP project.2. Janice Stephens and Jan Leach. Classroom Activities in Plant Biotechnology. 2005 -2007.

A related outreach effort was conducted by Janice Stephens at Colorado StateUniversity, entitled “Classroom Activities in Plant Biotechnology”(http://lamar.colostate.edu/~jsteph). This introduced K-12 students to basic concepts inbiotechnology and included teacher training. Exercises focused on applied rice genomicsand featured DNA extraction, gel electrophoresis, restriction enzyme digestions,transformation and plant tissue culture. Two teacher training sessions were conductedand 525 students (grades 1-12) were taught at five different locations. RiceCAPinformation was presented in June 2005 during the Math, Science and Technology Daysevent at Colorado State University to 4th-6th grade children from local schools, includingHispanic and minority students, trying to interest them in science at an early age.Stephens and her group also participated in this event in late 2007, educating 410elementary students, their teachers and parents about DNA and plant genomics. Theseactivities were summarized in the online RiceCAP newsletter posted on the RiceCAP

55

website at: http://www.uark.edu/ua/ricecap/Communication/newsletters/RiceCAPv4n1_Sep07.pdf

The activities were also adapted for use by Jan Stephens and Jan Leach for use by theAmerican Phytopathological Society Education Center under K-12 Teacher Resources asfollows:http://www.apsnet.org/education/K12PlantPathways/TeachersGuide/Activities/PlantBiotechnology/default.htm

Classroom Activities in Plant Biotechnology by Janice Stephens and Jan Leach.Activities to introduce elementary and high school students to the basics of plantbiotechnology. It includes several classroom experiments that can be modified to suit theages of the students. Some units require students to research and write their own opinionson the use, risks, and benefits of plant biotechnology in today's world as well as theimpact of changing climate on food production regions of the world.

DNA extraction Gel electrophoresis of dyes Restriction enzyme analysis - methylene blue stain Transformation of E. coli using green fluorescent protein Plant tissue culture in the classroom Polymerase chain reaction Effect of environment on plant growth Research suggestion

C. Evaluation:The training workshops (for RiceCAP personnel) and other aspects of Objective 3 relatedto the application of rice genomics to applied rice breeding programs were assessed byDr. Karen Ballard, evaluation specialist with the Cooperative Extension Service,University of Arkansas Division of Agriculture, Little Rock, AR. Her report follows.

RiceCAP Evaluation SummaryKaren Ballard, PhD. Cooperative Extension Service, University of Arkansas Division ofAgriculture, November 13, 2008:

1. Description of program/project: The RiceCAP project is a multi-institution andmulti-state program with a strong research component as well as teaching andextension efforts to fully engage the rice community on the potential benefits of theoverall effort. The project will advance the utility of the biotechnology informationavailable for rice, train traditional rice breeders in the usefulness of biotechnologybased tools, and educate a broader audience on the merits of such an approach toimprove rice cultivars.2. Evaluation questions: Within the framework of summative evaluation, keyevaluation questions included:

a) Did the project meet the RiceCAP educational objectives? b) Did the educational program increase the acceptance of molecular breedingtools? (Impact on participants) c) Were there indicators of value and merit (impact) related to continuingeducation of industry personnel?

56

Evaluation design, methods, and data collection--Summative evaluation of theExtension/Outreach component of RiceCAP focused on measuring theachievement of outputs and outcomes. Project activity records documented thescope of the outreach and educational activities. An evaluation questionnaire forassessing impact of RiceCAP presentations was developed by Drs. Cartwright,Karen Ballard, and Rich Poling of the University of Arkansas Division ofAgriculture Cooperative Extension Service. The instrument collected descriptivedata on participant demographics, and a retrospective post/pre assessment, a briefsurvey on germane RiceCAP related issues, and an open-ended processimprovement question. This questionnaire was used at several grower meetingsand other events and the data is presented in Section 10.B.i.

A second instrument was developed for breeders and technicians. Methodsused for data collection included individual qualitative interviews and aweb-based survey. The survey was designed to measure breeder/technicianknowledge, attitudes, and practice adoption related to applied rice genomics andthe molecular biology in rice breeding. This survey also sought to assess theimpact of RiceCAP's educational outreach on breeder and technician practice.Both instruments were evaluated for both face and content validity utilizingexpert review.

Qualitative interviews were conducted at the annual rice breeder's conferencein Memphis, TN on February 14, 2007. Nine breeders and one breedingtechnician were interviewed. The web-based survey was completed in October of2008 by one rice breeder, three breeding technicians, and two persons whoclassified themselves as “other.”

Summary of main findings--The Breeder and Technician survey producedboth quantitative and qualitative results. Respondents completing the interviewand survey were from Arkansas, California, Louisiana, Mississippi, Missouri, andTexas.

Demographic characteristics of respondents included:

Age18-40 41-60 61+

2 11 2

GenderFemale Male

5 10

Reported practice adoption included:

Q - Do you use molecular methods in your program?Yes No12 3

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Q - D you use marker assisted selection in your lab?Yes No13 1

Qualitative comments: In collaboration with another lab; are trying toget a lap up and going; use results of affiliated lab, collaborative labprovides data on markers, etc.

Q - Are you developing genetically engineered varieties?Yes No

8 7

Qualitative comments: We were, haven’t done in last couple of years;have, quit in 2001; working on molecution - no DNA transfer fromone species to another.

Q - Have you made any changes in your lab, or affiliations over thepast 2 years that have allowed you to use new/additional molecularmethods/tools?

Yes No10 3

Qualitative comments: Several comments regarding purchase of newequipment; expanding equipment for gene typing; modification ofmethods to better support breeding process; simplified process;collection in field; hired post-doc; single nucleotide polymorphismallows us to perform recombinants in a mapping project. Newer fastermethods; focused more on molecular aspect trade-off of resourcecommitments; incorporated marker results on rice quality in selectiontools; incorporating marker results on rice quality in selection tools;and expanded affiliation by meeting people in RiceCAP.

Breeder attitudes and opinions included:

Q - Do you believe that molecular breeding tools result in bettervarieties?

Yes No Not Yet, in the future12 1 2

Q - Will molecular breeding tools result in faster release of varieties?Yes No14 1

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Q - Will molecular breeding tools result in a more efficient breedingprogram?

Yes No15 0

Q - Do you believe that molecular breeding tools are too expensive forpractical use?

Yes No5 9

Q - Do you believe that molecular methods are too cumbersome anddifficult for practical use in breeding?

Yes No5 9

Qualitative comments: Yes and No. Would take about $100,000(without personnel) to set-up lab. At least $30,000 + benefits. Aspeople work with technology changes have been made in the lastcouple of years that has streamlined process! More people come intopicture and are finding there is more flexibility in procedures to makesimpler.

Q - Do you have concerns about applied rice genomics in yourbreeding program?

Yes No3 12

Evaluation of RiceCAP effectiveness:

Q - Has the RiceCAP Project been of value to you and your program?Yes No14 1

Qualitative comments: Did not help start, helped make us moreefficient. Helped method of identification, training; contact with otherscientists and labs; screening techniques for sheath blight. Possiblecollaborations have helped; goals for getting technology to breeders. Itopens doors.

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Q - Is the RiceCAP Project moving in the right direction for yourneeds?

Yes No14

Qualitative comments: You have to educate people and get theminvolved if they are going to use it. Concentrate on genes that arerealistic. If we can get the markers we are attempting to find it willcertainly be a benefit. Thrilled by having markers milling yield. Veryvaluable and positive project. In general, RiceCAP has been acourageous effort by organizers. Despite difficulties, it has been asteep learning process for everyone involved. Highest quality ofscience must be utmost importance.

Implications of findings--Two areas of qualitative feedback thatwarrant consideration include the considerable range and reportedinadequacy of staff knowledge and proficiency in molecular breedingtechniques, and the identification of primary roadblocks to the use ofmolecular breeding tools.

When asked to rank the adequacy of staff training on a scale of1-10, with one being inadequate to 10 being totally proficient, therewas a significant range of responses. The mean response on thistraining adequacy scale was 4.75. The descriptions provided rangedfrom “No training” (of staff) to 10 years experience. One respondentnoted, “Have seen a lot of improvement in last two years . . . still needto learn more.” In general, there was a consensus of opinion thattraining needs are significant, and despite improvements, trainingremains a developmental and basic need to support breeding efforts.

Current and future training needs identified through the survey byrespondents included:

(i) “The art of doing plant breeding”. Classroom training ontechniques and application to breeding programs(ii) Practicum in lab for 1-2 weeks, hands on training for staff frompeople who do this (trouble-shooting, PAGE procedure). Trying toadapt this procedure but did not have professional to come on siteand this has been a bottle-neck and has dragged on for years(iii) Basic principles of mendelian genetics and functionalgenomics(iv) Ability to find data that is already out there and use it toprevent redundancy(v) Molecular genetic staff need to be part of the breeding team sothat all team members can better understand priorities, timing, andways to effectively communicate (vi) Analysis and interpretation of data. (Not trying to make fieldpeople lab people). Need people in the middle to do datatranslation.

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(vii) New breeders need training on how to sample tissue and howto handle samples (field people need to understand quality control)(viii) Standardized protocol for molecular procedures that areefficient and can be incorporated into breeding programs(ix) Bio Informatics(x) Improved marker development(xi) Therapies for format for development, techniques for profiling(Messenger RNA) and gene identification(xii) More training on the background knowledge of polymorphousand implications for problems(xiii) Periodic workshops once to 2x a year related to newdevelopments; need interaction between disciplines for update onrecent developments/advances

Identified roadblocks to the use of molecular breeding tools included:i) Expense - Initial cost of getting lab space, purchase and settingup equipment/tools/technology, and staffing labs ii) Low staffing levels - not enough people/time to run theprogramsiii) Recruitment and retention problems due to low salary andbenefit packageiv) Lack of useful markers (only two markers that are useful andwe are using themv) The marker is limited to certain gene/traitsvi) Every time you add a new objective/procedure you have to addmore personnel and it encumbers more record-keeping -Something has got to give!vii) Information roadblocks - internally. viii) There are natural/built in barriers between breeder andmolecular biologist to understand each other. Barriers might be,don't understand any way of applied breeding. Breeders don't knowmuch about molecular procedures. ix) Trust issues . . . Goal of project to bridge with breeder/biologistwill take time. x) Effective communication skills.xi) Efficient generation, processing and utilization of theinformation. As more marker data and types of marker databecome available it will be more and more difficult to effectivelyus the data. We need easy to use software tools that can helpsummarize and visualize the data so that breeders can make quickdecisions like they do with the phenotypic data

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10. OBJECTIVE 4 - OUTREACH / EXTENSION EFFORT

The objective of the extension and outreach portion of the RiceCAP effort was to developoutreach materials to be used in educational and extension efforts that communicate thepromise of molecular markers and gene validation technologies in solving rice problems.

A. Benchmarks1. Develop educational materials.2. Recruit RiceCAP researchers to give presentations in rice-producing states.3. Give presentations to rice milling and marketing industry.4. Review lay language summaries of research progress reports.5. Develop and implement evaluations tools.

B. Accomplishments on each benchmark in Years 1 through 41. Develop educational materials.

a) Logo--A logo for RiceCAP was developed featuring rice panicles. The logo wasused, along with the CSREES logo, on all education extension and outreach materialsfor RiceCAP, including PowerPoint presentations.b) Brochure --A tri-fold brochure was created to present the mainobjectives of RiceCAP and was designed for the general audience.Participants in and general goals of the project were on the outside ofthe brochure. The inside of the brochure defined some general termsassociated with the project, including DNA, gene, genomics andmarker. Information on the approaches being used to achieve the twogoals of RiceCAP, sheath blight resistance and improved millingquality, were also described. There was also a description of howmarkers aid breeding efforts and how researchers determine genefunction. All descriptions were presented in layman's terms to make iteasy for the general audience to understand. The brochure was usedon its own and in conjunction with PowerPoint presentations and the posters (seebelow). The text was prepared by Peggy G. Lemaux and Barbara Alonso (UCBerkeley), and Rick Cartwright, Jim Correll and Ken Korth (University of Arkansas).The brochure was the first educational tool developed for RiceCAP. The first printingof the brochure (5000 copies) was disseminated via numerous channels (see Table A).A revised and updated second version of the brochure was completed in 2006 and5000 copies of that version were printed and disseminated.c) Fact Sheets--Informational two-page fact sheets weredeemed to be effective informational tools for the RiceCAPtarget audiences. A fact sheet template for RiceCAP wasdeveloped by Lemaux and Alonso and was provided for otherRiceCAP participants to suggest or author fact sheets onappropriate topics. This was to be accomplished by submittingideas to the Outreach team.

The following fact sheets were developed, placed on theRiceCAP website and used at educational venues.

Lemaux, P.G. November 2006. ABCs of Rice Genomics.

62

Lemaux, P.G. July 2007. LL601 Rice, What Is It & What Does It Mean? (courtesyof the University of California, Division of Agriculture and Natural ResourcesStatewide Biotechnology Workgroup, available at http://ucbiotech.org; July2007). (Seehttp://www.uark.edu/ua/ricecap/Communication/newsletters/RiceCAPv3n9_Jul07.pdf).

Correa-Victoria, F. 2007. The Rice Tarsonemid Mite (courtesy of CIAT;Columbia, South America); this related fact sheet was written to cover a newrice pest.

Lemaux, P.G. January 2008. Using Genetics, Genomics, and Breeding to ImproveRice.

d) Posters--After the brochure was created in 2005 a RiceCAP poster was created toreflect the information contained in the poster. This contained sections describing theparticipants, the goals of the project and some of the basic information needed tounderstand the technologies that were being used for the project. The RiceCAP posterwas modified for different venues and to update information with the progress fromRiceCAP researchers. Posters were made available for download on the RiceCAPwebsite. In 2006 a modularized poster with room for 5 or 6 modules was created withan array of modules from which to choose in order to customize the RiceCAPmessage for specific audiences. This also facilitated updating the poster to reflectRiceCAP success. Modularized and flip-chart posters (see below) were also createdand made available for use by RiceCAP participants. In total, the RiceCAP poster,modularized RiceCAP poster and flip-chart were used at > 150 meetings and viewedby > 10,000 individuals.

Lemaux, P.G. and Alonso, B. 2007. Updated RiceCAP poster. The originalRiceCAP poster was updated with information that was generated by RiceCAPefforts. http://www.uark.edu/ua/ricecap/Outreach/downloads/poster_Jan8.pdf. K.Korth laminated four copies of this poster in early 2008 and distributed them todifferent educational cooperators: Anna McClung (TX); Don Groth (LA); RickCartwright (AR); and Chris Greer (CA).

Lemaux, P.G. et al. 2007. Revised poster for PAG/NRI Meeting.http://www.uark.edu/ua/ricecap/Outreach/downloads/PAG_NRI_poster.jpg

Laminated, informational flip chart was created, based on content of the RiceCAPbrochure and a similar educational tool used by Wheat CAP. It was designed to beupdated with information generated by RiceCAP efforts and was modifiable to fit theneeds of particular audiences. This was used at numerous field events (Table A).e) Other Educational Resources--A variety of other educational materials werecreated to be used in extension efforts. They were made available for use on theRiceCAP website and RiceCAP members were encourage to utilize them in theireducational efforts.

(i) Critical to extension and education activities was the RiceCAP website. In2007 the website was reorganized by Terri Phelan to improve ease of useespecially for extension and education materialshttp://www.uark.edu/ua/ricecap/index.html.(ii) A newsletter was initiated in 2005 to disseminate information among allRiceCAP participants and the public in general. The newsletter is distributed

63

electronically to a listserve of rice breeders, producers, scientists, and others, andis also available on the RiceCAP web site athttp://www.ricecap.uark.edu/newsletters.htm. The newsletter includes (but is notlimited to) synopses of news stories, research updates, calendar of meetingsrelevant to RiceCAP, and reports of outreach and education efforts.(iii) Standardized RiceCAP PowerPoint templates were provided on the Outreachpage of the website http://www.ricecap.uark.edu/Outreach/downloads/Blue%20template.ppt.(iv) RiceCAP post-it pads (image at right) were created that included the logo andURL of the RiceCAP website. A total of 1330 brochures and 320 post-it padswere sent out to numerous stakeholders and end users. They were alsodisseminated to groups at the Rice Research and Extension Center in StuttgartAR.

(v) RiceCAP grain pen (image below), containing twelve differentvarieties of rice, was created to emphasize rice diversity. It featuredthe RiceCAP logo and URL on the barrel and was distributed tocooperators in rice production states to increase awareness ofRiceCAP.

64

(vi) Related video featuring the challenges of rice production was produced byLemaux and associates at University of California. Lemaux, P.G. 2007: Cornucopia's Challenge;http://www.ricecap.uark.edu/outreach_downloads.htm#Cornucopia_Video has a

link to the video's host site http://ucbiotech.org (under Resources > Outreach &Extension > Videos) (Seehttp://www.ricecap.uark.edu/Communication/newsletters/RiceCAPv4n3_Dec07.pdf ).(vii) Lemaux, P.G. and Alonso, B. 2007. Modular Display: Plant Diversity: TheFoundation of Tomorrow's Foods that features rice and technologies like markerassisted selection that is used to improve rice. Made available for educationalpurposes through UC Berkeley, [email protected]. (viii) A short podcast was developed in 2008 by the RiceCAP outreach team, ledby Sally Leong and including Ken Korth, Rick Cartwright, Barbara ALonso andPeggy Lemaux, that describes the RiceCAP project and was used for growers,industry members, legislators and the general public. Both audio-only and videoversions are available for download on the RiceCAP website. It was evaluatedusing a digital display at a Barley CAP Extension Team Meeting in June 2008 inGolden Colorado; it received high marks, 3.6 and 3.7 out of 4, when asked if thedisplay was inviting to look at and easy to understand, respectively.

f) Review of Extension and Education Materials--An Educational Materials Reviewsubcommittee with four members was charged with supplying rapid and standardizedfeedback for RiceCAP participants preparing extension or education publications.RiceCAP-related educational materials were submitted to committee chair, KenKorth, University of Arkansas, who led the review with committee members, AnnaMcClung, USDA-ARS, Stuttgart AR, Nathan Buehring, Mississippi State UniversityExtension and Chris Greer, University of California Cooperative Extension. g) Encourage RiceCAP researchers to give presentations, especially inrice-producing states--A travel fund for outreach and extension was created toencourage individuals to participate in outreach efforts and educate their audiencesabout RiceCAP goals and the importance of rice research. Individuals requested up to$750 to attend a meeting where they were required to give a talk, present a poster orhand out brochures. Individuals receiving travel funds were also required to obtainfeedback from their audience using the evaluation tool. There was limited use of thisresource by RiceCAP researchers.

The Liberty Link controversy impacted public education efforts in rice greatlyduring 2007 and continues to cause problems. Many in the rice industry would simplyrather not hear about any biotechnology in rice until this controversy is completelysettled. Recent events such as the lifting of rice testing by the European Union andthe success of the U.S. cleanup effort should help.

Table A lists known presentations at local, state or regional meetings from 2004to 2008.

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Table A.2004 Events

Date EventPoint

Person Outcome SummaryNumber ofAttendees

08/2004 InternationalCollaboration toTackle Sheath Blightin Texas Rice

McClung RiceCAP newsletterdistributed

2400 riceproduction,research, andindustryrepresentatives

11/2004 RiceTec BoardMeeting, Houston,TX

Rutger

12/2004 USA RiceFederation. RiceOutlook Con., NewOrleans, LA

Rutger

12/2004 RiceCAP PressReleaseAnnouncement,Little Rock, AR

Correll

2005 Events

Date EventPoint


01/2006 Plant and AnimalGenome Conference,San Diego, CA

02/2005 Texas Rice ResearchFoundation

McClung

3/2005 USDA-ARS inBeaumont PlaysMajor Role in NewRiceCAP GenomicsProject in RiceProduction Update,Texas A&M CountyExtension Newsletter

McClung

03/2005 Rice BreedersMeeting, Stoneville,MS

Correll

04/2005 AR Rice Researchand PromotionBoard, Little Rock,AR

Correll

05/2005 Rice ProcessingIndustry Alliance,Fayetteville, AR

Correll

66

2005 Events

Date EventPoint


06/2005 Beaumont and EagleLake field days

McClung,Pinson,andFjellstrom

Presented RiceCAPposter developed byoutreach committee

06/2005 RiceCAP MASWorkshop, Stuttgart,AR

Correll

06/2005 AR Rice Researchand PromotionBoard, Stuttgart, AR

Correll

07/2005 Beaumont, TX fieldday

Pinson,andFjellstrom

Provided oralpresentations aboutobjectives and progressto date on RiceCAPproject

7/19/05 Rice IPM CountyAgent Training

Cartwright Poster and comments onRiceCAP at in-servicerice training

31 county agentsfrom all major ricecounties inArkansas (2minority)

7/26/05 Mississippi County,AR Field Day

Cartwright Poster and comments onRiceCAP

22 rice growers andother productionpersonnel (1minority)

7/29/05 Craighead County,AR Crops Field Day


101 rice growersand others (8minority)

8/2/05 Rice VerificationProgram Tour – NEArkansas


52 tour participants

8/3/05 Northeast ArkansasRice Field Day,Poinsett andsurrounding counties


204 rice growers,consultants andother productionpersonnel (11minority)

8/10/05 Rice Field Day, RiceResearch andExtension Center,Arkansas County


Approximately 700rice field dayattendees (approx33 minority)

8/11/05 Clay County CropsField Day


78 growers andother attendees (4minority)

8/12/05 Jackson County RiceField Day


61 attendees (7minority)

67

2005 Events

Date EventPoint


8/15/05 Randolph CountyCrops Tour



8/16/05 Pine TreeExperiment StationField Day, Colt, AR

Cartwright Poster on RiceCAP Approximately 125attendees (14minority)

8/17/05 Cache River ValleySeeds Field Day,Cash, AR



8/19/05 Agro-Tech CropsDay, Farm ServiceLLC and LawrenceCounty Extension,Hoxie, AR



8/26/05 White County RiceDay, Griffithville,AR



9/28/05 IPM Retreat,Stuttgart, AR

Cartwright Comments on RiceCAP 20 county agents

10/18/05 Arkansas RiceResearch andPromotion BoardMeeting, Little Rock,AR

Cartwright Comments on RiceCAPto ARRPB Boardmembers

10/25/05 Annual RiceTECConference, LittleRock, AR

Cartwright Comments to RiceTECpersonnel aboutRiceCAP

10/2005 Virus Induced GeneSilencing Workshop,Samuel RobertsNoble Foundation,Ardmore, OK

11/2005 5th International RiceGeneticsSymposium, Manila,Philippines

12/4 –5/2005

USA Rice OutlookConference, Austin,TX

McClungand Greer

Poster and PowerPointcomments

563 OutlookConferenceattendees

68

2006 Events

Date EventPoint

Person Outcome SummaryNumber ofattendees

01/2006 Plant and AnimalGenome XIVConference, SanDiego, CA

Correll

1/5/06 Lawrence/RandolphCounty Expo,Walnut Ridge, AR

Cartwright Poster and PowerPointcomments on RiceCAP


1/9/06 Lonoke CountyCrops Meeting,Lonoke, AR



1/10/06 Mississippi CountyRice Meeting,Keiser, AR



1/11/06 Jackson County RiceMeeting, Newport,AR



1/11/06 IndependenceCountyRice/SoybeanMeeting, Oil Trough,AR


26 attendees

1/12/06 Prairie County RiceMeeting, Hazen, AR



1/12/06 Monroe CountyRice/SoybeanMeeting, Clarendon,AR



1/13/06 Crittenden CountyCrops Meeting,Earle, AR



1/17/06 Craighead CountyCrops Meeting,Jonesboro, AR



1/18/06 Poinsett CountyRice/SoybeanMeeting, Weiner, AR



1/23/06 Woodruff CountyRice/SoybeanMeeting, McCrory,AR

Cartwright PowerPoint Commentson RiceCAP


1/30-2/2/06

Arkansas CropManagementConference, LittleRock, AR

Cartwright Informal discussion ofRiceCAP with selectedrice consultants


69

2006 Events

Date EventPoint


2/7/06 Arkansas CountyRice Meeting,DeWitt, AR



2/8/06 Mississippi CropCollege, Starkville,MS

Cartwright PowerPoint commentson RiceCAP to 60Mississippi rice industrypersonnel andconsultants

(2 minority)

2/9/06 Jefferson CountyRice/SoybeanMeeting, Pine Bluff,AR



2/9/06 Desha CountyRice/SoybeanMeeting, Dumas, AR

Cartwright PowerPoint commentsabout RiceCAP


2/14/06 Chicot/AshleyCountyRice/SoybeanMeeting, LakeVillage, AR

Cartwright PowerPoint commentson RiceCAP


2/15/06 ASU Plant PathologyClass, Jonesboro, AR

Cartwright Guest Lecture on ricepathology andproduction – commentsand question/answers onRiceCAP

16 undergraduatestudents (3minority)

2/16/06 Arkansas CountyRice SoybeanMeeting, Stuttgart,AR



2/17/06 Lawrence CountyRice Meeting, Hoxie,AR



02/26-3/2/2006

RTWG Meeting, TheWoodlands, TX

Cartwright, Lemaux,Correll,Vance

Presented RiceCAPposter

370 attendees

05/2006 UA Rice ProcessingProgram's IndustryAlliance,Fayetteville, AR

McCaskill,McClung

Distributed RiceCAPbrochures and notepads,PowerPoint presentationon goals andachievements

40 attendees

06/2006 RiceCAP DNAMarker Workshop

R. Nelson

70

2006 Events

Date EventPoint


06/2006 LaboratoryEncounters in PlantGenomicsWorkshop, 5th –12th grade Teachersof Science andAgriculture,Sponsored by theUSDA RiceCoordinatedAgriculture Program(RiceCAP), June 27-28, 2006 Lonoke,Arkansas

Korth

06/26-30/06

Rice GenomeAnnotationWorkshop, TIGR,Rockville, MD

06/28-07/02/06

17th InternationalConference onArabidopsisResearch, Madison,WI

6/29/06 LSU AgCenter RiceResearch StationField Day

Linscombe RiceCAP poster 400 attendees

6/29/06 Eagle Lake RiceField Day

McClung RiceCAP poster 300 attendees

7/11/06 Vermilion ParishLSU AgCenter Rice& Model FarmerField Day, Klondike,LA

7/11/06 Main Rice Tec FieldDay, Alvin, TX

7/11/06 Southwest LA FieldTour

7/13/06 Beaumont Rice FieldDay

McClung RiceCAP poster 275 attendees

7/20/06 Delta Research &Extension Center

8/3/06 SEREC Crops FieldDay, Rohwer, AR

71

2006 Events

Date EventPoint


08/05-09/06

Plant Biology,American Society ofPlant Biologists(ASPB) andCanadian Society ofPlant Physiologists(CSPP), Boston, MA

Korth

8/9/06 RREC Field Day,Stuttgart, AR

Cartwright RiceCAP poster 400 attendees

8/16/06 Cache River ValleySeed Field Day,Cash, AR

8/23/06 MO Rice Farm FieldDay, Glennonville,MO

8/30/06 CA Rice Field Day,Biggs, CA

Greer RiceCAP poster 350 attendees

8/31/06 Delta Center FieldDay, Portageville,MO

10/10-14/06

Plant GenomicsEuropean Meetings5, Venice, Italy

11/12-16/06

International AnnualMeeting, AmericanSociety Agronomy(ASA), Crop ScienceSociety of America(CSSA), Soil ScienceSociety of America(SSSA),Indianapolis, IA

12/3-6/06 Rice OutlookConference, LasVegas, NV

McClung PowerPoint researchupdate

450 attendees

2007 Events

Date Event and State AttendeesPointPerson

Were BreedersInvolved?

Methods andMaterials

2/07 Cotton/RiceConservationTillageConference,Houston TX

72

2007 Events




1/8/07 Prairie CountyRice Meeting,Hazen, AR

130 Cartwright No PowerPoint andbrochures

1/9/07 CraigheadCounty RiceMeeting,Jonesboro, AR

80 Cartwright No PowerPoint andposter andbrochures

1/10/07 Jackson CountyRice Meeting,Newport, AR


1/11/07 Poinsett CountyRice Meeting,Weiner, AR


1/16/07 CrittendenCounty RiceMeeting, Earle,AR


1/17/07 MississippiCounty RiceMeeting, Keiser,AR


1/19/07 Greene CountyRice Meeting,Paragould, AR

50 Cartwright Yes PowerPoint andbrochures

1/19/07 Clay CountyRice Meeting,Corning, AR

120 Cartwright Yes PowerPoint andposter andbrochures

1/26/07 WoodruffCounty RiceMeeting,McCrory, AR


2/9/07 Lee CountyCrops Meeting,Marianna, AR


2/13/07 Arkansas RiceConference,Wynne AR

200 Cartwright Yes Poster

2/14/07 Rice BreedersMeeting,Memphis TN

15 Cartwright Yes Survey by K.Ballard

2/20/07 Arkansas CountyRice Meeting,DeWitt, AR


73

2007 Events




2/21/07 Rice ProductionCourse, CrossCounty, Wynne,AR

25 Cartwright Yes PowerPoint

2/22/07 Lawrence CountyRice Meeting


3/6/07 AR River ValleyCrops Meeting,Morrilton, AR

40 Cartwright No PowerPoint

4/9-10/ 07 MarkerDiscussionRoundtable

18 Cartwright Yes Sponsored byRiceCAP

6/13/07 NE LouisianaResearch StationField Day, St.Joseph, LA

75 Cartwright Yes RiceCAP posterdisplayed

6/21/07 RiceTec AlvinTexas Field Day,Alvin, TX


6/26/07 33rd Eagle LakeField Day, EagleLake, TX


6/28/07 LSU RiceResearch StationField Day,Crowley, LA


7/5/07 Rice IPMMeeting,Newport, AR

21 Cartwright No Discussion andflipchart

7/5/07 Rice IPMMeeting,Jonesboro, AR

18 Cartwright No Discussion andflipchart

7/12/07 Rice Field Day,Prairie County,AR

53 Cartwright Yes Oral presentation

7/12/07 60th BeaumontField Day,Beaumont, TX


7/19/07 Rice IPMMeeting, DesArc,AR

31 Cartwright No Oral presentationand discussion

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2007 Events




7/19/07 Mississippi StateUniversity, DeltaResearch andExtension CenterField Day,Stoneville, MS


8/2/07 University ofArkansasSoutheastArkansas CropsField Day,Rowher, AR.

270 Cartwright Yes

8/3/07 NortheastArkansas CropsField Day,Waldenburg, AR.

235 Cartwright Yes

8/6/07 Rice In-ServiceTraining forArkansas CountyAgents

37 Cartwright No County ExtensionAgents fromArkansas riceproductioncounties,RiceCAP updateand explanation

8/7/07 Rice FieldTraining for RiceConsultants

28Cartwright

No Rice Consultantsfrom Arkansas,RiceCAP updateand question/answer session

8/8/07 University ofArkansas RiceField Day, RiceResearch AndExtensionCenter, nearStuttgart, AR.

400Cartwright

Yes RiceCAPresearch updatepresented andposter displayed

8/9/07 RiceTec HybridRice Field Day,North ofHarrisburg, ARon Hwy 1.

250

Cartwright

Yes RiceCAP posterdisplayed

8/10/07 Crops Field Day,Clay County, AR

150Cartwright

Yes Rice growers,consultants,industry –RiceCAP oralpresentation

75

2007 Events




8/14/07 Crop Field Day,LawrenceCounty, AR

70Cartwright

No Rice growers,consultants,industrypersonnel –RiceCAP oralpresentation

8/15/07 Rice andSoybean FieldTour, CacheRiver ValleySeed CompanyField Day, Cash,AR

200

Cartwright

Yes Rice growers,consultants, seedand cropprotectionindustrypersonnel –RiceCAP oralpresentations

8/22/07 Missouri RiceResearch FieldDay, MissouriRice ResearchFarm nearGlennonville,MO.


8/29/07 Rice ExperimentStation FieldDay, Biggs, CA


12/3-5/07 Rice OutlookConference,Orlando, FL

300 Cartwright,McClung

Yes RiceCAP posterdisplayed,PowerPointresearch update

2008 Events




1/13-14/08 National FarmBureauConvention, NewOrleans, LA

4500 + Cartwright Yes Farmers,politicians,industrypersonnel –RiceCAP oralpresentation,brochures, posterdisplayed

1/16/08 Rice GrowerMeeting, Weiner,AR

120 Cartwright No RiceCAPPowerPointincluded in oralpresentation;RiceCAP poster

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2008 Events




1/23/08 Rice GrowerMeeting,Jonesboro, AR

80 Cartwright No RiceCAPPowerPoint inoral presentation

2/14/08 Rice GrowerMeeting, Searcy,AR

32 Cartwright No RiceCAPPowerPoint inoral presentation

2/17-18/08 RTWG Meeting,San Diego, CA

400 Cartwright Yes RiceCAP Poster;Modular Display

2/26/08 IntroductoryPlant PathologyClass, ArkansasState University,Jonesboro, AR

22 Cartwright No Guest LectureincludedRiceCAPoverview tojunior and seniorlevel collegestudents

7/10/08 Rice IPMMeeting,Crawfordsville,AR

19 Cartwright No RiceCAPoverviewincluded in oralcomments togrowers andconsultants

7/22/08 Rice In-ServiceTraining,Lonoke, AR

34 Cartwright No RiceCAPoverview to ricecounty extensionagents; Posterdisplayed

8/1/08 Rice ConsultantTraining,Waldenburg, AR

75 Cartwright No RiceCAPoverview to riceconsultants;question andanswer session

Approximately 5000 RiceCAP brochures were distributed at the above meetings;the posters and the Flip Chart were used as opportunity permitted.

Of note, Cartwright operated an invited booth at the National Farm BureauConvention in New Orleans, January 13 - 14, 2008. It featured the Plant Diversitymodular display, the new RiceCAP Poster as well as materials from the University ofArkansas Division of Agriculture Cooperative Extension Service on practical pestmanagement of crops, biosecurity and future crop production concerns.Approximately 1100 persons toured the booth area and more than 300 personalcontacts from 34 states were made during the two days. Rice grain pens (87),brochures (226), and RiceCAP sticky pads (234) were handed out to personalcontacts.

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Leong presented the RiceCAP poster at the dedication of the ARS Cereal CropsResearch Unit in Madison, WI on April 5, 2007, which was attended by GailBuchanan, undersecretary of USDA(http://www.uark.edu/ua/ricecap/Communication/newsletters/RiceCAPv3n7_Apr07.pdf)

(1) Give presentations to rice milling and marketing industry--Dr. Anna McClunggave an invited presentation to the American Society of Cereal Chemists at theirannual meeting held Oct 7-10, 2007 in San Antonio, TX. Some 2000 public andindustry researchers representing all major cereal crops were in attendance. Herpresentation was titled: “RiceCAP: Development of molecular markers associatedwith long grain milling yield” and summarized the work of several otherRiceCAP scientists. (Seehttp://www.uark.edu/ua/ricecap/Communication/newsletters/RiceCAPv4n2_Oct07.pdf).

Dr. Cartwright made contact with Riceland Foods, Riviana, RiceTec andProducers Rice Mills representatives in January 2007 about providing RiceCAPpresentations featuring Dr. Ken Korth. However, the milling industry wasreluctant to receive presentations about new genetic technologies at that time.(2) Review lay language summaries of research reports--No summaries werewritten by researchers for review by the Extension/Outreach group.

ii) Develop and implement evaluation tools.--An evaluation instrument for assessingthe impact of RiceCAP presentations was developed by Drs. Cartwright, KarenBallard and Rich Poling of the University of Arkansas Division of AgricultureCooperative Extension Service. The instrument (questionnaire) included collection ofdemographic data, a pre/post topic assessment, a brief survey on relevantRiceCAP-related statements and a free comment section. A copy of the questionnairewas made available on the website in the Outreach Section, from Terri Phelan or oneof the Outreach Team members and was to be used in assessing the impact ofpresentations and educational materials used at meetings. The return ofquestionnaires was required in order to qualify for outreach travel funds (see Section10.D.1.g.).

A copy of the evaluation questionnaire follows.

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In 2007, 436 evaluation forms were returned by 770 attendees (64% return) atArkansas grower meetings and field days featuring RiceCAP presentations in Prairie,Craighead, Jackson, Poinsett, Clay, Arkansas, and Lawrence counties.

Demographics: Based on the forms, 32% of attendees were 18-40 years of age;54% were 41-60 years; and 14% were 62+, while 94% were male. Most attendeeslisted farming as their profession (66%), with others reporting consulting (16%);

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Buying/Milling (4%); Farm Supply (6%); Seed/Crop Protection (5%); and University(3%). Most attendees reported their race as white (98%) with the remainder reportingBlack/African American (2%) and none reporting Hispanic/Latino ethnicity.

Respondents identifying where they had heard about RiceCAP listed thefollowing: Extension 86%; Newspaper 1%; Radio 1%; Farm Magazines 6%;RiceCAP Brochure 4%; RiceCAP Website 1%; Rice Industry 1%; Other 0%.

Percent of responses for the following knowledge and opinions were as follows:

Comments in 2007 included:• Could the RiceCAP project be used to prevent the LL or GMO contamination

problem in the future?• We would like handouts with the presentation info.• Slides were very good, would like hard copy for further study.• Why are Europeans so stupid?• We need more research on defensive rice varieties, not just high yield?• Could RiceCAP help develop aromatic and other varieties for the domestic Asian

market and reduce our rice imports?• Cartwright is good at explaining complex stuff so I can understand.• Would have liked more time on this topic.• We don't need GMO rice?

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• We should not be talking about GMO rice.• Science is interesting but should be regulated more closely. We can't afford

another GMO mess.• Good presentation. Good to know that this research is not developing GMO

varieties?• Use GMO to make less expensive to grow varieties?• Get rid of hybrids.• University ought to be more progressive in research.• Avoid talking about GMO rice.• Bayer and LSU suck. Also USDA.• Good pictures and explanation that I could understand.• Interesting future to rice research.• We need more control on research of this type.• We need less talk about GMO and more common sense.

In 2008, 197 evaluation forms were returned by 425 attendees (46% return) atArkansas grower meetings and field days featuring RiceCAP presentations in Clay,Craighead, and Poinsett counties.

Demographics: Based on the forms, 26% of attendees were 18-40 years of age;56% were 41-60 years; and 18% were 62+, while 98% were male. Most attendeeslisted farming as their profession (58%), but also reported consulting (22%);Buying/Milling (2%); Farm Supply (3%); Seed/Crop Protection (7%); and University(8%). Most attendees reported their race as white (97%) with the remainder reportingBlack/African American (1%); other (2%) and none reporting Hispanic/Latinoethnicity.

Respondents identifying where they had heard about RiceCAP listed thefollowing: Extension 80%; Newspaper 2%; Radio 1%; Farm Magazines 8%;RiceCAP Brochure 8%; RiceCAP Website 1%; Rice Industry 0%; Other 0%.

Percent of responses for the following knowledge and opinion were as follows:

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Comments in 2008 included:• Good presentation, future should be interesting.• We hope we don't have another GMO mess.• More resistant rice varieties.• Hybrids suck.• Need better varieties.• Need better research.• Less talk on GMO problem, more research.• Need more education on this topic….good job, not an egghead talk that I couldn't

understand.

Dr. Ballard also developed a set of interview questions based on informationpresented at the educational workshops described in Objective 3. The report is listedunder Objective 3, Section 9.C.

C. Integration with other CAP projectsLemaux is an Outreach PI for Barley CAP and serves on the Advisory Board forWheatCAP and Conifer CAP to review their outreach and extension efforts. RiceCAPboth benefited from this involvement and also provided insights to the other CAPsfrom approaches and efforts that succeeded and failed.

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D. Funded personnel involved:Barbara Alonso, UC Berkeley - 30%. Alonso and Lemaux design and developRiceCAP outreach and extension educational materials.

E. DeliverablesRiceCAP WebsiteRiceCAP NewsletterRiceCAP LogoRiceCAP Poster (1st and 2nd editions)RiceCAP Brochure (1st and 2nd editions)RiceCAP FlipchartRiceCAP Modularized PosterRiceCAP PensRiceCAP Sticky NotesRiceCAP Fact Sheet Template RiceCAP Fact SheetsRiceCAP Pod cast

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11. COLLABORATIVE EFFORTS AS A RESULT OF RICECAP

The collaborative efforts as a result of RiceCAP are divided into two sections. The first sectiondescribes interactions among the scientists participating in RiceCAP either as co-PIs or membersof the advisory board. The second section describes grant funding, anticipated grant funding, andcollaborations outside RiceCAP PIs but related to the RiceCAP effort.

A. New Collaborations Amongst RiceCAP ParticipantsCollaborations related to the Objective 1 - Sheath Blight component include Dr.Fernando Correa, formerly at CIAT, Colombia, So. America, introducing themicro-chamber method of inducing the SB disease to CIAT and the method subsequentlybeing transferred to several National Rice Research Programs in other Latin Americancountries. Also, eight South American rice varieties which showed SB tolerance similarto Jasmine 85 in Latin America are now being evaluated in the US for SB tolerance.

Interactions related to the Objective 1 - Milling Yield component included Dr.Farman Jodari, traveling to IRRI, Philippines in August 2006 to visit with Dr. MelissaFitzgerald at the rice quality lab and discuss milling quality issues as they relate to ricechemistry and assess the feasibility of using a grain analysis instrument to quantifyfissuring of brown rice samples. Applications are in place for fissure quantification ofmedium and short grain brown and milled rice using this procedure but applications forlong grain brown and milled rice were under development.

The collaboration having the most impact was for Objective 1 - Molecular Markercomponent where interaction began with Dr. Brian Scheffler, with whom there was nointeraction between the rice community and the USDA-ARS Mid-South Area GenomicsLaboratory before RiceCAP. Through Mississippi State rice breeder, Dr. Dwight Kanter,Dr. Scheffler who had limited experience in rice research, was brought into the RiceCAPproject, along with the tremendous genomics capabilities of his lab. As a result, the MSAGenomics lab is now a key component to the milling, sheath blight, breeding andassociation mapping studies fundamental to the project. Also, Dr. Scheffler has taken thelead in having the MY2 parents LaGrue and Cypress re-sequenced by the NationalCenter for Genome Resources, Santa Fe, New Mexico, using the Illumina Solexatechnology. Beyond RiceCAP, the MSA Genomics Laboratory has completed thesequencing various rice accessions for blast alleles for Dr. Yulin Jia.

Collaborations involving Objective 2 participants included Dr. Jan Leach makingBC10-10 and BC116 lines available from other research projects involving “broadspectrum resistance” to US rice researchers. Dr. Leach has been and is involved inseveral collaborations with IRRI but this was the first collaboration with U.S. riceresearchers.

Dr. Jim Oard's group successfully tested the first set of enhanced resistance lines forresistance to SB developed by Dr. Pam Ronald. He found slightly enhanced resistance toSB in these lines. Seed from these lines is being increase for additional screening toconfirm Dr. Oard's results.

In the area of bioinformatics, RiceCAP brought the US rice researchers together withDr. Clare Nelson who has been able to update the “QGene” software with several newoptions for looking at trait data and analyzing QTLs. QGene is one of two softwarepackages capable of mapping QTLs in advanced-backcross populations. This analysis is

84

necessary for the three populations with the SB resistant wild Oryza species developedby Dr. Georgia Eizenga as part of RiceCAP.

Dr. Peggy Lemaux is part of the Objective 4 team for RiceCAP. Also, she is anExtension and Education PI for Barley CAP and serves on the Advisory Board forEducation and Extension for WheatCAP and Conifer CAP, thus she reviews efforts in allthese CAPs. RiceCAP has benefited from this involvement but, more importantly for theCAPs, the work with RiceCAP has allowed Lemaux to provide insights to the otherCAPs on approaches and efforts that have succeeded and those that failed. This is notedin section C. Integration with other CAP projects in Objective 4 relating to “Extensionand Outreach”.

B. External Interactions and Funding Efforts Related to RiceCAPAnother aspect of RiceCAP was the collaborations outside of RiceCAP participants thatdeveloped and the additional funding that was applied for and obtained based on theresults obtained with RiceCAP funding. A summary of these interactions and grants islisted below.

Dr. Jan Leach obtained funding from USDA-CSREES-NRI to re-sequence 20 diverserice varieties from worldwide sources including two US varieties, Cypress (southern USvariety) and M202 (California variety) along with colleagues C. Robin Buell, and HeiLeung. The grant was entitled “Sequencing multiple and diverse rice varieties to allowconnection of whole-genome variation with phenotype” and provided valuable SNPinformation for the US rice community for other projects.

Previously, 145 US rice cultivars were genotyped with 169 SSR markers as part of aUSDA-CSREES-NRI Grant to TH Tai, SR McCouch and JN Rutger and the results werereported in Crop Science 45:66-76 (2005). About 130 of these 145 cultivars wereincluded in the association mapping study of 470 rice lines supported by RiceCAP andwere genotyped with SNP markers using a SNP-chip developed with Illuminatechnology.

The Illumina SNP chip was developed utilizing the SNP information from there-sequencing effort lead by Jan Leach described above and is part of an associationmapping study for the currently funded NSF-project “Exploring the genetic basis oftransgressive variation in rice”, to SR McCouch (PI), AM McClung, GC Eizenga, CBustamante (co-PIs). Collaboration between RiceCAP and this NSF project provided theneeded bioinformatics expertise to analyze the SNP chip data and will make SNP data onapproximately 900 diverse rice available to the US rice community for selecting newDNA markers and other genomics projects.

Based on the collaboration begun with RiceCAP funds, Dr. Dwight Kanter(Mississippi State Univ.) and Dr. Brian Scheffler obtained funds from the MississippiRice Promotion Board to continue the Marker Assisted Selection research as part of therice breeding program in Mississippi.

Dr. Brian Scheffler is leading the genotyping part of an effort with funding from theUSA Rice Foundation to map novel blast resistance genes assisted with co-PIs WenguiYan, Anna McClung, Jim Correll and Bob Fjellstrom.

The Rhizotonia solani phytotoxin research completed with RiceCAP funds to Dr.Steve Brooks provided the basis of additional funding from the USDA-ARS, to hire a

85

post-doc to continue mapping toxin sensitivity genes and begin the map-based cloningeffort.

RiceCAP provided a forum for Drs. Rod Wing and Dave Kudrna (Univ. Arizona) toreport their findings regarding the relationship between the various wild Oryza speciesaccessions based on the DNA sequencing work conducted as part of the NSF-funded“Oryza Map Alignment Project (OMAP)” and establish a relationship with the US ricebreeding community. In addition four accessions representing O. barthii, O. glaberrima,O. nivara, and O. rufipogon, which were part of the OMAP sequencing effort wereincluded in the sheath blight screening test conducted by Dr. Georgia Eizenga.

Recently, Dr. Yulin Jia and several IRRI scientists, some of whom are associatedwith RiceCAP, developed a concept paper entitled “Maximizing rice yield performancein intensive production systems through enhanced sheath blight resistance and optimizedplant types”. In the near future, this paper should expanded into a broader collaboration,modeled after the RiceCAP effort.

Using research results obtained with RiceCAP funding, Guo-Liang Wang and YulinJia recently received NSF funding to characterize chromatin modifications and epigenticprocesses in rice in collaboration with Blake Meyers (Univ. Delaware); and StevenJacobsen and Matteo Pellegrini (Univ. California - Los Angeles).

Jan Leach through funding from the USAID-IRRI Linkage Program grant“Understanding genome variation to achieve broad-spectrum disease resistance in rice”,developed several rice lines with “broad spectrum resistance” that were tested by J. Oardas part of RiceCAP.

Using research results from RiceCAP, Dr. Yinong Yang submitted a pre-proposal tothe Joint Genome Institute for “Whole genome shotgun sequencing of Rhizoctoniasolani, a wide host range fungal plant pathogen” that was recommended for a fullproposal. Subsequently, Dr. Yang decided to wait with his funding request and now is inthe processes of submitting a different proposal to sequence R. solani.

Based on research results obtained with RiceCAP funds, a graduate student workingwith Jan Leach was awarded a Ford Foundation Diversity Fellowship which will providefull funding for the remainder of her graduate research.

RiceCAP graduate students and postdocs supported by RiceCAP obtained additionalUSDA-NRI-CSREES funding to attend the International Rice Genetics Symposium andthe International Rice Functional Genomics Symposium in 2005, 2006, 2007, and 2008.

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12. NEW TECHNOLOGIES PURSUED AS A RESULT OF RICECAP

The original plan for RiceCAP was to have some inherent flexibility in the research plansand budget based on discoveries made during the program or due to changing technologies.Therefore a few extra projects were added to the overall project due to the importance ofdeveloping technologies. The association mapping project was one of those which utilized1536 SNPs derived from Perlegen Technology. A resequencing effort of two RiceCAPparental varieties also is in progress as well as the development of true SSR multiplexingreactions for breeding programs.

Perlegen Technology is a means of resequencing rice genomes based on hybridization ofgenomic DNA onto high density arrays. From there a comprehensive SNP discovery across20 lines (19 + reference genome) was performed to derive the 1536 SNPs used in theassociation mapping study (separate report provided). This sequencing effort was funded bya separate project and funding agency but the information was provided to RiceCAP.

Since the majority of the parents used in the Perlegen study do not represent US cultivars,it was anticipated that an additional effort would be needed to uncover other SNPs relevantto US breeding efforts. A resequencing effort using Illumina Solexa technology is presentlybeing performed to generate 1 gigabase of DNA sequence for each of the two cultivarsLaGrue and Cypress, which are the two parents used in the MY2 mapping population. Bothare considered relatively diverse in the southern US gene pool. Cypress is known for itsoutstanding milling quality, excellent seedling vigor, and is a semidwarf, from LA. LaGrue isknown for its high yield, unstable milling quality, and is a tall cultivar, from AR. The ARgermplasm has always been different from TX and LA germplasm. Both cultivars are in theparentage of many other breeding lines and cultivars in US rice germplasm. Theresequencing effort should be finished by early 2009. The sequence data will be providedthrough the National Center for Genome Resources in New Mexico and will be displayedusing their web-based Alpheus software. The sequences will be aligned to the referencesequence Nipponbare and a list of SNPs will be generated. The USDA-ARS MSA GenomicsLaboratory (Dr. Brian Scheffler) has a Illumina Bead Express station and a RocheLightCycler that will allow the discovered SNPs to be utilized on existing and ongoing ricemapping projects as well as further association mapping projects.

In order to transfer the technology of rice molecular biology to breeding efforts, an effortis being made to utilize SSR markers in a true multiplex format. Often SSRs are run inseparate PCR reactions and are then pooled for analysis on capillary electrophoresis. Whilethis saves on running costs associated with capillary electrophoresis, it does not reduceprocessing time or costs associated with PCR. In addition, this pooling technique oftenrequires post PCR testing to determine which PCR reactions are compatible and as to howmuch of the PCR reaction can be added to the pooled sample. By predetermining the truemultiplexing conditions, significant savings can be uncovered for costs and processing time.In addition, the multiplexing format that is being developed in RiceCAP is utilizing a lowcost and fast DNA extraction procedure (modified NaOH extraction). The majority of thereaction sets developed so far are based on quality traits as well as disease resistance genes.Another advantage of the multiplexing reactions is a breeder will get more markerinformation than normally requested, but at no additional cost. In the case of the interactionbetween Dr. Scheffler and Drs. Kanter and Beighley, that means Dr. Scheffler can moreeasily meet their needs in a high throughput manner as reactions can be setup on 384 wells

87

without significant regard as to if a given primer within the set needs to be run on only someof the 384 DNA samples. Presently 6 multiplex sets have been developed for 6-8 primers perset. One of these sets was designed to discriminate between japonica and indicia accessionsin the germplasm collection in Stuttgart. Another set in development will be used inFoundation seed plots to assure purity and this set will include a marker for red pericarpallele which is responsible for “red rice.” An earlier version of this set was used in 2008 inMississippi foundation seed fields to identify contaminants. The multiplex technology wasalso used to develop six sets for MY3 mapping that used 3-6 markers in a set.

Group Marker Common Name Location cM

1- Marker RM190waxy (amylosecontent) Chr 6 8

Assisted Aroma Aroma Chr 8 Selection RM44 elongation Chr 8 54(tested & Pi-ta2 rice blast: Pi-ta indica Chr 12 50confirmed) AP005128 rice blast: Pi-i Chr 9 30 AP5659 rice blast: Pi-z Chr 6 59 RM224 rice blast: Pi-k Chr 11 114 RM208 rice blast: Pi-b Chr 2 155

2- Marker RM190waxy (amylosecontent) Chr 6 8

Assisted Aroma aroma Chr 8 Selection AP005128 rice blast: Pi-i Chr 9 30(tested & AP5659 rice blast: Pi-z Chr 6 59confirmed) RM224 rice blast: Pi-k Chr 11 114 Pi-ta2 rice blast: Pi-ta indica Chr 12 503- Fingerprint RM7102 rice blast: Pi-ta Chr 12 54for Breeding RM249 fingerprint Chr 5 87(tested & RM304 milling yield Chr 10 52confirmed) RM232 fingerprint Chr 3 44 RM224 rice blast: Pi-k Chr 11 114 RM210 aroma Chr 8 854- Fingerprint RM234 fingerprint Chr 7 94for Breeding RM1339 semi-dwarf Chr 1 147(tested & RM214 fingerprint Chr 7 50confirmed) RM266 rice blast: Pi-b Chr 2 157 RM219 fingerprint Chr 9 19 RM1359 fingerprint Chr 4 565- DiversityStudy RM136 fingerprint Chr 6 38Discriminating RM19 fingerprint Chr 12 21indica vsjaponica RM315 fingerprint Chr 1 165(tested & RM7 fingerprint Chr 3 64

Group Marker Common Name Location cM

88

confirmed) RM477 fingerprint Chr 8 137 RM484 fingerprint Chr 10 976-Marker AP005128 rice blast: Pi-i Chr 9 30Assisted RM224 rice blast: Pi-k Chr 11 114Selection RM208 rice blast: Pi-b Chr 2 155for Resistance Pi-ta2 rice blast: Pi-ta indica Chr 12 50(tested & confirmed) 7-Marker RM3855 rice blast: Pi-i Chr 9 27Assisted RM224 rice blast: Pi-k Chr 11 114Selection RM527 rice blast: Pi-z Chr 6 61for Resistance RM1384 fingerprint Chr 8 54(tested & confirmed)

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PUBLICATIONS, ABSTRACTS, AND

SCIENTIFIC PRESENTATIONS

90

13. PUBLICATIONS

91

92

93

94

95

13. ABSTRACTS AND SCIENTIFIC PRESENTATIONS

(Total to October 2008 = 91)

Andaya, V.C., Colowit, P.M., Jodari, F., Oster, J., Jiang, J., Johnson, C., Kim, S., Roughton,I., Mckenzie, K.S., Tai, T. 2006. Application of DNA markers to the rice experimentstation breeding programs.. Rice Field Day Abstract.

Boza, E.J., Moldenhauer, K.A.K., Gibbons, J.W., Lee, F.N., Cartwright, R.D., Jia, Y.,Boyett, V., and Blocker, M.M. 2006. RiceCAP (MY1) Mapping Population in Arkansas.Field day. Rice Research and Extension Center, Stuttgart, AR. August 9, 2006.

Boza, E.J., Moldenhauer, K.A.K., Gibbons, J.W., Lee, F.N., Cartwright, R.D., Jia, Y.,Boyett, V., and Blocker, M.M. 2006. Field and milling quality analysis of the MY1mapping population in Arkansas. 31st RTWG. The Woodlands, TX. Feb. 26-28, 2006.

Brooks, S.A. “Genomic Research for Rice Improvement”. RiceCAP outreach program(Korth), Agriculture Extension Center, University of Arkansas, Lonoke, AR, 2006.

Brooks, S.A. 2006. Cultivar specific response to the host-selective toxin produced byRhizoctonia solani, the causal pathogen of sheath blight disease of rice. Phytopathology96:S16.

Brooks, S.A. Differential response of rice cultivars to RS toxin, a pathogenicity factor inSheath Blight disease of rice. 31st RTWG. The Woodlands, TX. Feb. 26-28, 2006.

Bruce, M.A., P. M. Manosalva, S. Lee, R. Davidson, J. Snelling, H. Leung, J. E Leach. 2008.Silencing 14-3-3 Protein Gene GF14e In Rice Causes Lesion Mimic Phenotype AndEnhanced Resistance To Bacterial Blight. Poster presentation at the Plant and AnimalGenome Meetings, SanDiego, CA. January 12-16.http://www.intl-pag.org/16/abstracts/PAG16_P07b_753.html

Carrillo, M.C., Goodwin, P.H., Leach, J.E., Leung, H., Vera Cruz, C.M. 2008. Phylogeny,function and structure of rice oxalate oxidases. Phytopathology 98:S31.

Carrillo, G., P. Goodwin, M. Reveche, J. E. Leach, H. Leung, C. M. Vera Cruz. 2007.Phylogenomic analyses of rice oxalate oxidases, candidate genes for quantitativeresistance to rice blast. Phytopathology 97: S18.

Correll, J.C., Beighley, D., Brooks, S.A., Cartwright, R.D., Correa-Victoria, F.J., Eizenga,G.C., Fjellstrom, R.G., Hulbert, S.H., Jia, Y., Jodari, F., Kanter, D., Korth, K.L., Leach,J.E., Lemaux, P.G., Leong, S., McClung, A.M., Moldenhauer, K.A.K., Nelson, J.C.,Nguyen, H., Oard, J.H., Pinson, S.R.M., Ronald, P., Rutger, J.N., Scheffler, B., Utomo,H.S., Wang, G-L., Yang, Y. 2009. RiceCAP: A Coordinated Research, Education, AndExtension Project For The Application Of Genomic Discoveries To Improve Rice In TheUnited States. XVII Plant and Animal Genomics Meeting. San Diego, CA.

Davidson, R.M., Manosalva, P., Vera Cruz, C., Leung, H., Leach, J.E. 2008. Sequencepolymorphisms confer differential allele regulation of germin-like protein gene familymembers associated with rice blast QTL. Phytopathology 98:S44

Davidson, R., Manosalva, P., Vera Cruz, C., Leung, H., Leach, J. 2006. Expression patternsof oxalate oxidase-like genes associated with blast resistance QTL on chr. 8 of O. sativa.Pp. 148-152 in Biology of Plant-Microbe Interactions, Vol 5, eds. F. Sanchez, C. Quiton,I. Lopez-Lara, and O. Geiger. IS-MPMI Press, Minneapolis.

Davidson, R., Manosalva, P., Vera Cruz, C., Leung, H., Leach, J. 2006. Expression patternsof oxalate oxidase-like genes associated with blast resistance QTL on chromosome 8 of

96

Oryza sativa. 5th International Rice Genetics Symposium and the 3rd International RiceFunctional Genomics Symposium, Manila, Philippines, November 2005.

Davidson, R., Manosalva, P., Vera Cruz, C., Leung, H., Leach, J. 2006. Expression patternsof oxalate oxidase-like genes associated with blast resistance QTL on chromosome 8 ofOryza sativa. Selected oral presentation at the XII International Congress on MolecularPlant-Microbe Interactions in Merida, Mexico, December 2005.

Eizenga, G.C., Agrama, H.A., and Lee, F.N. Mapping R-genes in rice wild relatives (Oryzaspp.) Proc. Rice Technical Working Group. The Woodlands, Texas. 26 Feb.-1 Mar. 2006.

Eizenga, G.C., Agrama, H.A., Prasad, B., Bryant, R.J., Neves, P.C.F., Mackill, D.J. 2007.Developing mapping populations between US rice cultivars and selected O. nivaraaccessions. 5th International Symposium of Rice Functional Genomics, Tsukuba, Japan,Oct. 15-17, 2007.

Fjellstrom, R. 2008. Rice Genomics. Field Day. August 14, 2008; Stuttgart, AR.Fjellstrom R. 2005. How to Map a Marker Associated with a Major Gene. Markers

Unleashed: An overview of DNA marker technology as it applies to rice improvement.RiceCAP Marker Assisted Breeding Workshop, June 14-16, 2005, Stuttgart, AR.

Fjellstrom, R. G., Linscombe, S., Oard, J., Moldenhauer, K.A.K., Boza, E., Jodari, F.,Nelson, J.C., Yeater, K. and McClung, A. 2007. RiceCAP: Identification Of QTLAssociated With Rice Milling Yield In A Long Grain Cross. Plant and Animal GenomeConf. Poster, Abstract for Plant and Animal Genome XV Conference, Jan 13-17, 2007,San Diego, CA

Guo, Z., Nelson J. C. 2007. Shrinkage interval mapping for QTL and QTL epistasis analysisin line crosses. Poster, Plant and Animal Genome XV Conference, Jan 13-17, 2007, SanDiego, CA.

Jia Y., Liu, G. and McClung, A. 2008. Development of the Recombinant Inbred LinePopulation of Tropical Japonica Lemont Crossed with Indica Jasmine 85. Phytopathology98. S75. (poster presentation).

Jia Y., Liu G., and McClung A. 2008. Development of the recombinant inbred linePopulation of tropical japonica Lemont crossed with indica Jasmine 85. Paper presentedin APS 2008 Centennial Meeting, Minneapolis, July 26-30, 2008

Jia, Y. Invited oral presentation on “Signaling in the Rhizoctonia solani-rice pathosystem”for 4th International Symposium on Rhizoctonia, 20-22 August 2008, Berlin, Germany.

Jia, Y., Rutger, J.N. and Xie, J. 2005. Development and characterization of rice mutantpopulations for functional genomics of host-parasite interactions. Phytopathology95:S48.

Jia, Y., Singh, P., Jia, M.H., Wang, G., Wamishe, Y., Zhu, L and Zhou, E. Development ofmolecular strategies to control rice sheath blight disease. 31st RTWG. The Woodlands,TX. Feb. 26-28, 2006.

Jia, Y. Wang, G. - L., and Valent, B. Compare and contrast invasive growths and global geneexpressions of rice after infections with rice blast and sheath blight pathogens. Proc. 32ndRice Technical Working Group. San Diego, California. 18-20 Feb. 2008.

Jodari, F., Roughton, A.I., Fjellstrom,R.G., Scheffler, B., and Nelson, J.C. 2008. Factorscontributing to milling quality differences in MY3, a ‘RiceCAP’ project millingpopulation. Proc. 32nd Rice Technical Working Group. San Diego, California. 18-20Feb. 2008.

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Jodari, F. and Y. Roughton. California Rice Field Day, 2006. “RiceCAP efforts in California;The Focus on Fissuring resistance.” Biggs, CA.

Jodari, F. and A.I. Roughton. California Rice Field Day, 2005. “RiceCAP” Efforts at RESAimed at Improving Milling Quality; Biggs, CA.

Korth, K.L. (2006). An overview of the RiceCAP goals, outreach efforts, and the teacherworkshop, was presented in a poster at the annual meeting of the American Society ofPlant Biologists. Education and Outreach Efforts of the Rice Coordinated AgricultureProject - RICECAP. August 3rd -6th, 2006, Boston, MA.

Leach, J. 2007. Durable Disease Resistance in Plants. First RR Nelson Memorial Lecture,Department of Plant Pathology, Penn State University, April 15-16.

Leach, J. Approaches to Broad-Spectrum Durable Disease Resistance. Seminar speaker,Department of Botany, University of Sao Paulo, Brazil. March 2, 2007.

Leach, J. Associating genomic variation of diverse rice varieties to understand diseaseresistance. Invited Symposium speaker, Stadler Genetic Symposium, Columbia, MOOctober 2-4, 2006.

Leach, J. Gene Candidates for Broad-Spectrum Durable Resistance in Rice. InvitedSymposium speaker 4th International Symposium on Rice Functional Genomics,Montpellier, France, October 9-11, 2006.

Leach, J. Understanding Durable Resistance. Invited Symposium speaker, Northeast DivisionMeetings of the American Phytopathological Society, Burlington, VT, November 7-9,2006.

Leach, J., P. Manosalva, R. Davidson, S. Lee, M. Bruce, M. Genaleen Diaz, B. Liu, C. VeraCruz, H. Leung. Approaches to Durable Resistance in Rice. Invited Symposium Speaker,Cold Spring Harbor Symposium: Plant Genomics. Cold Spring Harbor, NY, March13-15, 2007.

Leach, J., P. Manosalva, R. Davidson, S. Lee, M. Bruce, M. Genaleen Diaz, B. Liu, C. VeraCruz, H. Leung. Gene Candidates for Broad-Spectrum Durable Resistance in Rice.Invited Symposium Speaker, Cold Spring Harbor Symposium: Plant Genomics.

Leach, J., P. Manosalva, R. Davidson, S. Lee, M. Bruce, M. Genaleen Diaz, B. Liu, C. VeraCruz, H. Leung. Gene Candidates for Broad-Spectrum Durable Resistance in Rice.Invited Symposium Speaker, International Symposium in Brazil on Molecular Geneticsof Plants, Natal, Brazil. March 5-7.

Leach, J.E. 2006. Understanding Broad-Spectrum, Durable Resistance in Rice. Symposiumspeaker at the 5th International Rice Genetics Symposium and the 3rd International RiceFunctional Genomics Symposium, Manila, Philippines, November 2005.

Lee, S., Jeung, J., Han, S., Ra, D., Leung, H., Hulbert, S., Leach, J. 2008. Quantitative traitloci (QTL) associated with bacterial blight and blast resistance in Korean ricepopulations. Phytopathology 98:S88

Leong, S. A., Tian, S., and Splinter BonDurant, S. Discovery of Genomic DNAPolymorphisms using Oligonucleotide Arrays. 31st RTWG. The Woodlands, TX. Feb.26-28, 2006.

Liu, G., Jia, Y. and McClung, A. 2008. Development and Characterization of theRecombinant Inbred Line Population of Tropical Japonica Lemont Crossed with IndicaJasmine 85. Poster presentation. Arkansas Rice Field Day August 13, 2008.

Liu, G., Jia, Y., Correa-Victoria, F.J., McClung, A., Correll, J.C. Identification ofQuantitative Trait Loci (QTLs) Responsible for Sheath Blight Resistance in Rice Using

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Recombinant Inbred Line Population of LemontÍJasmine 85. Phytopathology 98. S92(oral presentation).

Liu, G., Y. Jia, M.H. Jia, R.G. Fjellstrom, A. Sharma, Z. Li, and S.R.M. Pinson. 2007.Molecular Characterization of a Population of Backcross Introgression Lines Derivedfrom Crossing the US Japonica Rice Cultivar ‘Lemont’ as the Recurrent Parent with theChinese Indica Cultivar ‘TeQing’. Plant and Animal Genome XV, January 13-17, 2007,San Diego, CA; http://www.intl-pag.org/15/abstracts/PAG15_P05b_240.html

Liu, G., Jia, Y., Correa-Victoria, F.J., Jia, M.H., McClung, A., and Correll, J.C..Identification of Sheath Blight Resistance QTLs in Rice Using Recombinant Inbred LinePopulation of Lemont/Jasmine 85. Proc. 32nd Rice Technical Working Group. SanDiego, California. 18-20 Feb. 2008.

Liu, G., Jia, M.H., Jia, Y., McClung, A., Correll, J.C and Rutger, J.N. MolecularCharacterization of the Recombinant Inbred Line Population of the Cross of Lemont withJasmine 85. Proc. 32nd Rice Technical Working Group. San Diego, California. 18-20Feb. 2008.

Liu, G., Jia, Y., and McClung, A. Molecular Characterization of the RIL Population ofJaponica Lemont Crossed with Indica Jasmine 85 for Mapping Rice Disease Resistance.August 13, 2008, Arkansas Rice Field Day.

McClung A.M, Fjellstrom, R., Oard, J., Linscombe, S., Moldenhauer, K.A.K., Jodari, F.,Lacaze, X., Leong, S., Nguyen, H., Wang, G.-L., and Nelson, J.C. 2008. RiceCAP:Mapping Rice Milling Yield QTL In A U.S. Long Grain Cross. Oral presentation atASA-SSA-CSSA Joint Annual Meeting, Houston TX.

McClung, A.M., Groth, D., Oard, J., Utomo, H., Moldenhauer, K., Boza, E., Scheffler, B.,Jia, Y., Liu, G., Correa-Victoria, F.J., and Fjellstrom, R. 2008. Development andCharacterization of RiceCAP QTL Mapping Population for Sheath Blight Resistance.Poster at RTWG, San Diego CA.

McClung, A., Boza, E., Fjellstrom, R.G., Guo, Z., Jodari, F., Linscombe, S., Moldenhauer,K.A.K., Nelson, J.C., Oard, J.H., Scheffler, B. and Sun, X. 2007. RiceCAP: Developmentof molecular markers associated with long grain milling. AACC International AnnualMeeting Oct.7-10, 2007, San Antonio, TX.

McClung, A.M., Groth, D.E., J. H. Oard, H. Utomo, Moldenhauer, K.A.K., Boza, E.,Scheffler, B., Jia, Y., Liu, G., Correa-Victoria, F.J., and Fjellstrom, R.G. 2007.Development and Characterization of RiceCAP QTL Mapping Population for SheathBlight Resistance. ASA Meeting New Orleans, LA, Nov. 3-9.

Mysore, S., Venu, R.C., Nobuta, K. Meyers, B.C., Wang, G-L. Analysis of Developing SeedTranscriptomes of Rice Using Massively Parallel Signature Sequencing. Poster presentedat the ASPB Annual meeting in Chicago, July 7-11, 2007.

Nelson J. C. 2006. Basic data relations for markers, traits, and genotypes. Markers, Mapping,and Beyond: RiceCAP second annual marker workshop, June 4-9, 2006, Ardmore, OK.

Nelson J. C. 2006. Constructing linkage maps in plants: theory and practice. Markers,Mapping, and Beyond: RiceCAP second annual marker workshop, June 4-9, 2006,Ardmore, OK.

Nelson, J.C. 2005. Basics of QTL analysis. Markers Unleashed: An overview of DNAmarker technology as it applies to rice improvement. RiceCAP Marker Assisted BreedingWorkshop, June 14-16, 2005, Stuttgart, AR.

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Nelson, J. C., Sun, X, McClung, A, Fjellstrom, R, Moldenhauer, K, Boza E., Jodari, F., Oard,J., Linscombe, S., Guo, Z. QTL mapping for milling-quality traits in a US japonica xindica rice cross. Poster. 32nd Rice Technical Working Group. San Diego, California.18-20 Feb. 2008.

OryzaSNP Discovery Workshop held at The 5th International Symposium of Rice FunctionalGenomics, Oct 16, Tskuba, Japan. Coordinated by J. Leach with presentations by K.McNally (IRRI), K. Childs (MSU), R. Davidson (CSU), Mashiro Yano (NIAS), H.Leung (IRRI). The 3 h workshop purpose was to introduce the rice research communityto the OryzaSNP data set. RiceCap funded travel for Rebecca Davidson and KevinChilds, who presented at the workshop.

Park, D.S., Sayler, R.J., Hong, Y.G., and Yang, Y. 2006. An improved method for theinoculation and evaluation of sheath blight. The 31st Meeting of Rice Technical WorkingGroup, Woodlands, Texas, Feb. 26- Mar.1, 2006.

Pinson, S.R.M. 2008. Rice Genetics. Presentation at the annual Field Day at the Texas A&MUniversity Agricultural Experiment Station, Beaumont TX, July 10, 2008.

Pinson SRM. 2005. Development and handling of plant materials for marker analysis.Markers Unleashed: An overview of DNA marker technology as it applies to riceimprovement. RiceCAP Marker Assisted Breeding Workshop, June 14-16, 2005,Stuttgart, AR.

Pinson SRM. 2005. Putting sheath blight resistance genes to work in the rice field. TexasRice, July 2005 edition, Special section, pp. VIII-IX;http://beaumont.tamu.edu/eLibrary/Newsletter/2005_Highlights_in_Research.pdf

Pinson, S.R.M. New Molecular Tools For Breeders. Rice Field Day, Beaumont, TX. July 13,2006. (Oral)

Pinson, S.R.M. Incorporating Foreign Sheath Blight Resistance Genes into US RiceGermplasm. Texas Rice, July 2006 edition, Special section, pp. VI-VII;http://beaumont.tamu.edu/eLibrary/Newsletter/2006_Highlights_in_Research.pdf. 2006.

Pinson, S.R.M., J.H. Oard, D. Groth, R. Miller, G. Liu, Y. Jia, M.H. Jia, and R.G. Fjellstrom.2007. New Breeding Parents Containing Novel QTL for Rice Sheath Blight ResistanceIdentified by Combining Phenotypic and Molecular Characterizations. Poster Abstractfor Plant and Animal Genome XV Conference, Jan 13-17, 2007, San Diego, CA

Pinson, S.R.M., Jia, Y., Oard, J.H., Fjellstrom, R.G., Jia, M.H., Hulbert, S., Liu, K. andNelson, C. Bringing Quantitative Traits Under Breeder Control by Combining QTLMapping with Candidate Gene Approaches: A Case Study of Rice Sheath BlightResistance Proc. 31st Rice Tech. Work. Group Meet., The Woodlands, TX in press Feb.26 - March 1, 2006.

Pinson, S. R.M., Wang, Y., Liu, G., Jia, M.H., Jia, Y., Sharma, A. and Fjellstrom, R.G. 2008.Using a Set of TeQing-into-Lemont Chromosome Segment Substitution Lines for FineMapping QTL: Case Studies on Sheath Blight Resistance, Spreading Culm, andMesocotyl Elongation. Oral presentation for 32nd Rice Technical Working Group. SanDiego, California. 18-20 Feb. 2008.

Prasad, B. and Eizenga, G.C. 2009. Identification of rice sheath blight QTLs in a Bengal/O.nivara advanced backcross population. Plant and Animal Genome XVII. San Diego, CA10-14 January 2009.

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Prasad, B. and Eizenga, G.C. 2008. Developing a Bengal/O. nivara advanced backcrossmapping population to identify sheath blight QTL. Proc. 32nd Rice Technical WorkingGroup. San Diego, California. 18-20 Feb. 2008.

Prasad, B. and Eizenga, G.C. 2008. Identification of resistant sources for rice sheath blightdisease from wild Oryza species. Field day. U Arkansas Rice Research and ExtensionCenter, Stuttgart, AR. August 13, 2008.

Prasad, B. and Eizenga, G.C. 2008. Development of a mapping population using sheathblight resistant wild Oryza spp. Field day. U Arkansas Rice Research and ExtensionCenter, Stuttgart, AR. August 13, 2008.

Prasad, B. and Eizenga, G.C. 2007. Development of mapping populations using sheath blightresistant wild species. Field day. Rice Research and Extension Center, Stuttgart, AR.August 8, 2007.

Ronald, P. Candidate genes for sheath blight resistance. RiceCAP Annual Meeting, Feb23-25, Houston Texas

Ronald, P. Candidate genes for sheath blight resistance. RiceCAP Annual Meeting, June12-16, Little Rock, Arkansas

Ronald, P. Genetic engineering and agriculture. Rice technical working group. Houston, Feb25, 2006.

Roughton, A.I. and F.Jodari. California Rice Field Day, 2008. Induced Fissuring Protocolsused in Characterization of 3 ‘RiceCAP’ Milling Populations. Biggs, CA

Roughton, A.I., Jodari, F., Moldenhauer, K.A.K., Linscombe, S.D., and McClung, A.M.Refining induced fissuring procedures used in characterization of ‘RiceCAP’ millingpopulations. (Poster) 32nd Rice Technical Working Group. San Diego, California. 18-20Feb. 2008.

Roughton, A. I. and F.Jodari. California Rice Field Day, 2007. ‘RiceCAP’ efforts at RES;Year 3 progress report.; Biggs, CA.

Sharma, A., Kepiro, J., R.G. Fjellstrom, S.R.M. Pinson, A.R. Shank, A.M. McClung,R.E.Tabien. Mapping sheath blight resistance QTL(s) in rice. Plant and Animal GenomeXIV, San Diego, CA; http://www.intl-pag.org/pag/14/abstracts/PAG14_P244.html.Jan.14-18, 2006.

Sharma, A., J. Kepiro, S.R.M. Pinson, R.G. Fjellstrom, R.E. Tabien, R. Shank, and A.M.McClung. RiceCAP - Mapping Sheath Blight Resistance QTL(s) in Tropical JaponicaRice. Proc. 31st Rice Tech. Work. Group Meet., The Woodlands, TX in press Feb. 26 -March 1, 2006.

Scheffler, B.E. USDA RiceCAP and its impact on developing new cultivars. AgronomicCrops Field Day 2007. Mississippi State University, Stoneville, MS, 07-19-2007.

Scheffler, B.E. SNP discovery and utilization: Are we finally looking at the holy grail ofblending plant breeding and molecular biology? Proc. 32nd Rice Technical WorkingGroup. San Diego, California. 18-20 Feb. 2008.

Snelling, J., R. Davidson, J. E. Leach. 2007. Hydrogen peroxide accumulation and oxalateoxidase activity correlate with quantitative disease resistance in rice. Annual Mtg of theAmerican Society of Plant Biologists, Chicago, Ill. July 8. Poster Presentation.

Solomon, W., Oard, J., McClung, A., Wright M., Zhao, K., Reynolds, A., Bustamante, C.,McCouch, S., Scheffler, B.E. Analysis of the RiceCAP germplasm panel for SNPdiversity, population structure and seven yield-component traits of rice. Plant and AnimalGenome Conference 2009. San Diego, CA 01-10-15, 2009.

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Utomo, H.S. 2005. RiceCAP update. Rice Research Station News Vol. 2(2). p.4.Utomo, H.S., I. Wenefrida, S.D. Linscombe, D. Groth, X. Sha, and J. Oard. 2006.

Preliminary marker genotyping of sheath blight mapping population SB2. Rice ResearchStation Field Day (poster).

Wang, Y., Pinson, S.R.M., Fjellstrom, R.G., Tabien, R.E. 2008. Spreading culm locusdiscovered while dissecting a sheath blight resistance QTL within a set ofTeQing-into-Lemont introgression lines. Poster at the American Society of Agronomy(ASA) meetings, Houstong, Texas 6 - 9 Oct. 2008.

Wang, Y., Pinson, S.R.M., Fjellstrom, R.G., Sharma, A., Brooks, S., Tabien, R.E. 2008.Using TeQing-into-Lemont Introgression Lines (TILs) to Dissect Sheath BlightResistance QTLs and Fine-Map a Spreading Culm Gene. Poster at 32nd Rice TechnicalWorking Group. San Diego, California. 18-20 Feb. 2008.

Wang GL. SAGE and microarray analysis of the rice defense transcriptome duringRhizoctonia solani infection. Invited oral presentation at the APS/CPS/MSA Jointmeeting, Quebec, Canada 7/28-8/2, 2006.

Wang, G.-L. Deep Transcriptome analysis of the rice and rice blast genomes usingLongSAGE and MPSS Technologies. International Conference on the Frontier of PlantMolecular Biology, Oct. 26-29, 2005, Shanghai, China.

Wang, G.-L. SAGE and MPSS profiling of sheath blight resistance and milling quality.RiceCAP Annual Meeting, June 12-16, 2005, Little Rock, Arkansas.

Zhou, Y., Bailey, T.A. and Yang, Y. 2006. Antagonistic interaction of ethylene and abscisicacid signaling modulates disease resistance and abiotic stress tolerance in rice. The 31stMeeting of Rice Technical Working Group, Woodlands, Texas, Feb. 26- Mar.1, 2006.

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RiceCAP Cumulative Project Report - University of …...RiceCAP Cumulative Project Report January 12, 2009 San Diego, CA Applied Plant Genomics Coordinated Agricultural Project A coordinated