Development of Sheath Blight-Resistant Breeding Lines for

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Development of Sheath Blight-Resistant BreedingLines for Southern U.S. Environments andMorphological and Genetic Survey of GiantSalvinia Populations in Louisiana and TexasDominique Clark GalamLouisiana State University and Agricultural and Mechanical College, [email protected]

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Recommended CitationGalam, Dominique Clark, "Development of Sheath Blight-Resistant Breeding Lines for Southern U.S. Environments andMorphological and Genetic Survey of Giant Salvinia Populations in Louisiana and Texas" (2019). LSU Doctoral Dissertations. 4881.https://digitalcommons.lsu.edu/gradschool_dissertations/4881

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DEVELOPMENT OF SHEATH BLIGHT-RESISTANT BREEDING LINES FOR SOUTHERN U. S. ENVIRONMENTS AND

MORPHOLOGICAL AND GENETIC SURVEY OF GIANT SALVINIA POPULATIONS

IN LOUISIANA AND TEXAS

A Dissertation

Submitted to the Graduate Faculty of the Louisiana State University and

Agricultural and Mechanical College in partial fulfillment of the

requirements for the degree of Doctor of Philosophy

in

The School of Plant, Environmental Sciences and Soil Sciences

by Dominique Clark Galam

B.S., Central Luzon State University, Philippines, 1998 M.S., Iwate University, Japan, 2009

May 2019

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To my loving parents, Rolando and Clarita This dissertation is humbly dedicated

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ACKNOWLEDGEMENTS

My deepest gratitude to my adviser, Dr. James H. Oard, for his invaluable support,

assistance and guidance whilst doing my dissertation work. Also, for giving me the opportunity

to pursue my graduate studies, the encouragements and wisdom are commendable, for without

him this work would have not been completed.

My graduate committee members, Dr. Steven Linscombe, Dr. Stephen Harrison, Dr.

Aaron Smith, Dr. Jong Ham, and Dr. Philipp Lynn Kennedy, for their constructive criticism

while preparing this dissertation and for their commitment for both my general exam and

research, their assistance is highly appreciated.

My heartfelt gratitude to Dr. Donald Groth and the whole staff and workers of the H.

Rouse Caffey Rice Research Station at Crowley, Louisiana for providing me support and help

during the conduct of my field experiments. The financial support extended by Louisiana Rice

Research Board for without their endeavors, this work would not been possible.

My current labmates, Democrito, Lenard, Paola, and Anna and to my former labmates,

Yamid, Christian, Manuel, Roberto and Federico for sharing their knowledge, assistance,

friendship and the fun times shared together during the conduct of my field, greenhouse and

laboratory experiments, I am indebted to all of them. Also, Dr. James Silva for providing the

SAS codes for my statistical analysis, thank you.

My sincerest thanks also to Dr. Samuel Ordonez and family for inviting me to come to

LSU to pursue my PhD degree. My friends, Ronald, Teresa, Marilyn and Ate Evelyn who

became my refuge and second family away from home, their encouragements and matured

suggestions during the stressful times, are whole-heartedly appreciated. My newly found relative

here in Baton Rouge, Kuya Al and Madam Rowena Mangaoil and Ma’am Rowena Cruz and

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family for their moral and spiritual support, I thank you sincerely. To Democ who became my

big brother, spiritual adviser and gym partner, thank you for the inspiration.

I would also thank the whole Filipino community for the friendship and support during

my time here in LSU.

My grandparents, uncle and aunts, and my friends from all over thank you for the

unending encouragement and support.

My deepest and genuine gratitude to my family for their unwavering love and support

throughout my life for without them I would not be what I am today. My dad and mom, Rolando

and Clarita, my siblings, Dwayne Mark, Dwight Lark and Dunstan Rodney, thank you for the

unconditional love care, support and understanding through the duration of my studies. My

sisters-in-law, Maricris and Mariel, my nieces, Chelsea Dane, Clarisse and Daeneris Marienne,

you are all my inspiration and constant source of strength.

Finally, to the LORD, my GOD, who gives me strength and my health. The hope,

wisdom and blessings bestowed on me to conquer the challenges during the whole duration of

my PhD program.

THANK YOU…….

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TABLE OF CONTENTS ACKNOWLEDGEMENTS………………………………………………………………………iii LIST OF TABLES…………………………………………………………………………….....vii LIST OF FIGURES……………………………………………………………………………….x ABSTRACT ……………………………………………………………………………………..xi CHAPTER 1. GENERAL INTRODUCTION …………………………………………………... 1

1.1. Global Rice Situation ....……………………………………………………………...1 1.2. Rice Breeding in Asia and the United States………………………………………....2 1.3. Rice Sheath Blight Disease …………………………………………………………..3 1.4. Molecular Breeding for Rice Diseases……………………………………………….4 1.5. Salvinia molesta, Noxious Aquatic Weed in Louisiana and Texas….……………….6 1.6. Research Objectives…………………………………………………………………..9 1.7. References…………………………………………………………………………….9

CHAPTER 2. DEVELOPMENT OF DISEASE RESISTANT GERMPLASM………………...14 2.1. Introduction………………………………………………………………………….14 2.2. Materials and Methods………………………………………………………………17 2.3. Results and Discussion ……………………………………………………………...23

2.4. References…………………………………………………………………………...45 CHAPTER 3. IDENTIFICATION AND EVALUATION OF NON-SYNONYMOUS

SNPs MARKERS FOR SHEATH BLIGHT RESISTANT GERMPLASM ..…………. 48 3.1. Introduction………………………………………………………………………….48 3.2. Materials and Methods……………………………………………………………....52 3.3. Results ……………………………………………………………………………....53 3.4. Discussion ………………………………………………………………………......65

3.5. References …………………………………………………………………………..70

CHAPTER 4. GENETIC ANALYSIS OF NOXIOUS AQUATIC WEED IN LOUISIANA AND TEXAS …………………….……………………………………....77

4.1. Introduction………………………………………………………………………….77 4.2. Materials and Methods……………………………………………………………....79 4.3. Results ………………………………………………………………………………85

4.4. Discussion …………………………………………………………………………..92 4.5. References …………………………………………………………………………..94

CHAPTER 5. SUMMARY AND CONCLUSION ……………………………………………..98 5.1. Identification and Development of Breeding Lines and Populations ……………....98

5.2. Identification and Evaluation of Non-synonymous SNP Markers for SB Resistance……...………………………………………………………………...98 5.3. Genetic and Phenotypic Diversity of S. molesta in Louisiana and Texas .……….... 9

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APPENDIX A. RANKING OF 136 nsSNPs MARKERS ACROSS 20 SUSCEPTIBLE RILs OF THE RICECAP SB2 MAPPING POPULATION BASED ON RAW P, HOCHBERG, BONFERRONI, FALSE DISCOVERY AND R-SQUARED VALUES (Sanabria, 2015) ……………………………..101

APPENDIX B. PRIMER SEQUENCES FOR SNP-BASED MARKERS

LOCATED IN PREVIOUSLY REPORTED QTL’S FOR SHEATH BLIGHT RESISTANCE (Sanabria, 2015) ………………………...104

APPENDIX C. EIGENVALUES AND PROPORTIION OF TOTAL VARIABILITY

AMONG S. MOLESTA AS EXPLAINED BY FIRST THREE PRINCIPAL COMPONENTS USING THE MORPHOLOGICAL DATA …………………………………………………108

APPENDIX D. CORRELATION BETWEEN THE MORPHOLOGICAL DATA

AND THE FIRST THREE PRINCIPAL COMPONENTS…………………...108 APPENDIX E. CORRELATION BETWEEN DISSIMILARITY MATRICES

OBTAINED WITH DIFFERENT MARKER TYPES (MANTEL TEST)……………..........................................................................108

APPENDIX F. SUMMARY OF PEARSON’S LINEAR CORRELATION OF AFLP

MARKER AND GAPCP GENE TO MORPHOLOGICAL TRAITS …………………………..……………………108

APPENDIX G. EIGENVECTORS, EIGENVALUES, INDIVIDUAL AND

CUMULATIVE PERCENTAGE OF VARIATION EXPLAINED BY THE FIRST FIVE PRINCIPAL COMPONENTS (PC) A FTER ASSESSING MORPHOLOGICAL TRAITS OF S. MOLESTA FROM LOUISIANA AND TEXAS ………………………………………….119

APPENDIX H. PERMISSION LETTER……………………………………………………...110 VITA……………………………………………………………………………………………112

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LIST OF TABLES 2.1 Pedigree, generation and number of lines of sheath blight lines initially

evaluated during the 2013 Field Season at H. Rouse Caffey Rice Research Station, Crowley, Louisiana ……………………………………………………………..17

2.2 Sheath blight rating, plant height, and pedigrees, 33 F4-F5 sheath blight lines,

four check varieties, 2013 SB field trial, H. Rouse Caffey Rice Research Station, Crowley, Louisiana ……………………………………………………………..24

2.3 Analysis of variance on SB disease rating of the selected SB resistant lines

and resistant and susceptible checks from the 2013 SB field evaluation trial, H. Rouse Caffey Rice Research Station, Crowley, Louisiana …………………………..25

2.4 Analysis of variance on plant height of the selected SB resistant lines and

resistant and susceptible checks from the 2013 SB field evaluation trial, H. Rouse Caffey Rice Research Station, Crowley, Louisiana…………………………...25

2.5 Sheath blight rating, plant height, and pedigree of 39 selected F5

sheath blight lines, 4 SB inbred lines and four check varieties from 2014 SB field evaluation trial, H. Rouse Caffey Rice Research Station, Crowley, Louisiana…………………………………………………...26

2.6 Analysis of variance of SB disease rating of the selected SB

resistant lines and resistant and susceptible checks from the 2014 SB field evaluation trial, H. Rouse Caffey Rice Research Station, Crowley, Louisiana …………………………………………………..28

2.7 Analysis of variance of plant height of the selected SB


2.8 Sheath blight rating, plant height, and pedigree of 31 selected

lines including 16 F6, 4 F3 and 5 inbred sheath blight lines and four check varieties from 2015 SB field evaluation trial, H. Rouse Caffey Rice Research Station, Crowley, Louisiana …………………………..29

2.9 Analysis of variance of SB disease rating of the selected SB



resistant lines and resistant and susceptible checks from the 2015 SB field evaluation trial, H. Rouse Caffey Rice

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Research Station, Crowley, Louisiana …………………………………………………..31 2.11 Plant height and SB ratings for F4 and F7 selections evaluated at the RRS, 2016……….31 2.12 Analysis of variance of SB disease rating of the selected SB

resistant lines and resistant and susceptible checks from the 2016 SB field evaluation trial, H. Rouse Caffey Rice Research Station, Crowley, Louisiana…………………………………………………...32



2.14 Plant height and SB ratings for F3, F4 derived F8 and BC2F3

selections evaluated at the RRS, 2017 …………………………………………………..33 2.15 Analysis of variance of SB disease rating of the selected SB


2.16 Analysis of variance of plant height of the selected SB resistant lines and resistant and susceptible checks from the 2016 SB field evaluation trial, H. Rouse Caffey Rice Research Station, Crowley, Louisiana …………………………………………………..36

2.17 Maturity, plant height and 0-9 SB ratings for F3, F4, F4 derived F9

and BC2F3, BC3F2 selections evaluated at the RRS, 2018 ………………………………36 2.18 Analysis of variance on 50% days to heading of the selected SB

resistant lines and resistant and susceptible checks from the 2018 SB field evaluation trial, H. Rouse Caffey Rice Research Station, Crowley, Louisiana ………………………………………………….40

2.19 Analysis of variance of on SB disease rating of the selected SB


2.20 Analysis of variance on plant disease rating of the selected SB


2.21 Yield reduction of the selected resistant lines from 2016

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and 2017 (combined data)………………………………………………………………..43 2.22 Correlation analysis of days to heading, disease score, plant

height and grain weight of the resistant check, selected sheath blight lines and the susceptible checks ………………………………………………………....45

3.1 SNP genotypes of selected resistant and susceptible lines from 2014 SB field evaluation plots, RRS, Crowley, Louisiana ………………………..56

3.2 Genotyping results of the selected resistant lines including

2 resistant and 6 susceptible checks in 2015 SB field evaluation ……………………….59 3.3 Genotypes of the 7 selected lines from the 2016-2017 field evaluation

at RRS, Crowley, Louisiana ……………………………………………………………..62

4.1 Geographic location of S. molesta populations and description of collection sites……...80 4.2 Analysis of variance (ANOVA) of five morphological characteristics;

colony width (mm), ramets per colony, rhizome length per colony (mm), leaf width per colony (mm), root length per colony (mm) for five populations of S. molesta …………………………………………………………...86

4.3 Correlation matrix of five morphological traits of the five populations of S. molesta from Louisiana and Texas …………………………………………………...89

4.4 Analysis of molecular variance using AFLP marker and the gapCp gene sequence for six populations of S. molesta from Louisiana and Texas………………….91

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LIST OF FIGURES 2.1 F1 seedlings grown in the greenhouse and F1 nursery field; a. F1 seedlings

growing in peat pots inside the greenhouse; b. 30-day seedlings growing in the F1 nursery; c. seedlings at tillering stage growing in F1 nursery ………………….22

4.1 Principal Component Analysis (PCA) of the five traits from S. molesta evaluated in this study. Pyramid = Gheens, LA; Cylinder = Bell River, LA; Cube = Thibodaux, LA; Club = Caddo Lake, LA; Balloon = Lake Bistineau, LA. Green = Cluster 1; Black = Cluster 2; Red = Cluster 3; Magenta = Cluster 4; Purple = Cluster 5 ……………………………………………………………………….88

4.2 Box plot for root length (mm) for 20 individuals each of S. molesta at

Gheens, LA; Bell River, LA; Thibodaux, LA; Caddo Lake, LA………………………...90

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ABSTRACT

The southern US environment is a very conducive environment for agriculture and

fisheries. Rice farming, shrimping and water related activities help drive the local economy.

However, there are several factors that impede the success of these activities. Sheath blight (SB)

disease caused by Rhizoctonia solani is one of the major biotic constraints to high grain yield and

quality for most commercial U.S. rice varieties. Although different breeding lines with high

levels of "partial resistance" have been developed none has been used directly as a commercial

variety. The first research objective of this research was to identify and develop advanced

breeding lines for sheath blight resistance with high grain yield and quality through traditional

breeding methods. The second research objective was to identify and evaluate non-synonymous

SNP markers for SB resistance. Seven elite breeding lines showed relatively high yields vs

commercial checks in inoculated field plots. The selected lined carried SNP markers within

candidate genes for sheath blight resistance including a regulatory gene on chromosome 9 was

shown in RNA-Seq studies to play a role in resistance. This research demonstrated that a

combination of traditional breeding and genomic approaches can facilitate rapid development of

elite breeding lines with high grain yield and quality traits for southern U.S. environments.

The third research objective was focused on Salvinia molesta, giant aquatic fern which

invades bayous, large lagoons and lakes and is considered as a major problem to Louisiana and

Texas. Genetic and phenotypic diversity study of S. molesta in these locations showed a

significant variation for all five morphological traits measured both within and across collection

sites. Although substantial morphological and molecular variations were detected both within

and among populations, all data from this study suggested that these six populations were

derived originally from the same clonal or related populations. A practical implication of this

xii

result is that different and location-specific control strategies for S. molesta most likely will be

needed.

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CHAPTER 1. GENERAL INTRODUCTION

1.1. Global Rice Situation

Rice (Oryza sativa L.) is an important crop of stable food security for more than half of

the world’s population (Jia et al. 2009). The majority of developing countries, especially from

the Asia-Pacific region, depends on rice as their primary calorie source and main livelihood crop.

During the crop year of 2016-2017, ~ 161million hectares were devoted for rice cultivation

worldwide. In 2017, global rice production was ~ 489 million metric tons and around 478

million metric tons of rice was consumed during that time (http://www. fas.usda.gov/psdonline/

psdAvailability.aspx).

Total U.S. rice production in 2017 dropped 20 percent from the previous year with ~ 10

million tons harvested from 960,000 hectares with an average yield of 9.2 tons per hectare

(https://www.ers.usda.gov/data-products/rice-yearbook.aspx#57007). Child (2017) reported that

the drop of rice production in the US was attributed to three primary factors: a weak price

outlook for long grain rice, heavy rainfall and flooding in the spring, both in the mid-South and

California, and the effects of Gulf Coast hurricanes during the late summer.

As the human population is expected to rise to ~ nine billion by 2050, rice crop yields will

need to at least double by that time (Khush, 2005; Skamnioti and Gurr, 2010; Li et al. 2014). In

major Asian countries rice consumption will increase faster than the population growth.

Similarly, with the ensuing effects of urbanization, farms intended for rice production have

diminished in number due to conversion for commercial purposes. Moreover, a 25 to 30 percent

annual yield loss caused by disease, insect, and weed pressure will be exacerbated by climate

change (http://www.fao.org/news/story/en/item/1062612/icode/). Therefore, improvement of

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yield is a logical approach to counteract losses by biotic and abiotic stresses (Delteil et al. 2010;

Godfray, 2010; Lobell et al. 2011).

1.2. Rice Breeding in Asia and the United States

Rice is the basic staple for the majority of Asian nations including the region’s 560

million poor (http://ricepedia.org/rice-around-the-world/asia). Asia contributes up to 88 percent

and 91 percent of the world’s rice area and production, respectively. In addition, it is in this

region where 90% of the rice is produced and consumed. Moreover, more than 140 million

farming households rely on rice as their primary source of livelihood (FAO 2014). From the start

of the 21st century, rice production in Asia has increased continuously through the introduction

and adoption of new and high-yielding varieties. China is the world’s largest rice producer, with

~142 million tons generated in 2016 that accounts for as much as 35% of the total world rice

production (FAO 2017).

Utilization of hybrid vigor in Chinese rice breeding has made a significant impact to the

country as a whole. In 1974 the first hybrid rice was commercially released in China and yields

were about 15 to 20 percent greater than those of improved or high-yielding varieties of the same

growth duration. With the success of hybrid rice technology in China, rice growing countries in

the region – Vietnam, India, the Philippines and Bangladesh have attempted commercial

production of hybrid rice (Hu et al. 2000; Jin et al. 2002; Virmani and Kumar, 2004; Shi and Hu,

2017). However, adoption of the technology has been slow. For example, the total hybrid rice

area planted was 4.5 million hectares distributed across several Asian countries outside of China

that represent 1 to 9 % of the total rice area in each country (FAO, 2014). In the Philippines, only

9 % of the total area for rice production was planted with hybrid rice (Bordey et al. 2016).

3

In the US, rice is grown in six states - Arkansas, California, Louisiana, Mississippi, Texas

and Missouri. Arkansas accounts for ~ 50 percent of all rice produced in the United States,

primarily long and medium grain varieties. The first hybrid rice line was released in the Mid-

South in 2000 with the substantial benefit of increased yields associated with its adoption. Thus,

rice producers in the region have been adopting hybrids since their commercial release. Hybrid

acreage has increased from 15% in 2005 to over 40% in 2013 (Nalley et al. 2017). Clearfield

hybrids have been widely adopted as a control measure for weedy red rice.

1.3. Rice Sheath Blight Disease

A major impediment to high grain yield and quality for rice producers is sheath blight

disease caused by the soilborne fungal pathogen Rhizoctonia solani Kuhn, second only to rice

blast in reducing both grain yield and quality (Lee et al. 1983; Ou, 1985; Rush et al. 1992;

Savary et al. 2006). Sheath blight has been regarded as a serious threat to stable rice production

and is found in many rice production areas around the world. The pathogen has a wide host

range, often infecting legume crops grown in rotation with rice (Pan et al. 1999; Zou at al. 2000;

Mew et al. 2004; Pinson et al. 2005). One major constraint in sheath blight management is the

inability to identify genetic sources, from either cultivated or wild varieties of rice, which

provide adequate levels of durable and inheritable sheath blight resistance that can be readily

transferred to commercial varieties (Bonman et al. 1992; Taguchi-Shiobara et al. 2013).

In the southern United States, yield losses up to 50% were reported when susceptible

cultivars were planted (http://www.knowledgebank.irri.org/ipm/sheath-blight/economic-

importance.html). Management and cultural practices include the use of semi-dwarf cultivars,

intensive nitrogen fertilization, high plant density and rotation with soybean which is an

alternative host for the pathogen. These factors favor disease build-up and high severity of sheath

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blight disease (Biswas, 2001; Singh et al. 2004; Groth and Bond, 2007). Fungicide application is

the most common practice to manage the disease, but this approach is generally not sustainable

nor cost effective (Nicolaisen et al. 2018). There are also preventive low-cost measures and

practices which include burning of crop residues and avoiding excess nitrogen-based fertilizers.

However, even these low-impact control measures are not always successful under disease-

favorable conditions (Skamnioti and Gurr, 2009). Although various cultural practices have been

used to manage the disease, it is advantageous and important to screen rice germplasm and to

develop rice cultivars with adequate levels of disease resistance to reduce or eliminate losses

caused by the disease. Therefore, utilization of host resistance is the most economical and

environment-friendly strategy to manage this disease (Liu et al. 2009).

1.4. Molecular Breeding for Rice Diseases

The subsequent development of molecular markers – simple sequence repeats (SSR),

insertion-deletions (InDel), single nucleotide polymorphisms (SNPs) and functional genomics

has led to increased genetic studies of diseases in rice. In a review by Collard and Mackill

(2008), efficiency and precision of conventional plant breeding can be greatly improved by

marker-assisted selection (MAS) for certain trats.

MAS has been shown to be successful in developing disease resistant varieties of rice –

bacterial leaf blight (BB) resistant rice, tungro-resistant rice, and blast resistance (Amante-

Bordeos et al. 1992; Brar and Khush, 1997; Ashkani et al. 2015). Linked markers pTA248,

RG136 and RG556 associated to BB resistance genes Xa21, xa13 and xa5 were successfully

introgressed into BB-susceptible Basmati variety CSR-30 through MAS without compromising

the Basmati traits (Baliyan et al. 2018). Similarly, Suh et al (2011) developed multiple brown

plant hopper (BPH) - resistance introgressions (ILs) or near-isogenic lines (NILs) through

5

molecular assisted backcrossing using a Bph18-cosegregation marker 7312. T4A for positive

selection, and 260 SSR markers across all 12 rice chromosomes for background selection, Bph18

was transferred into an elite japonica variety ‘Junambyeo’ and ILs with enhanced BPH

resistance. Recently, three dominant blast resistance genes were successfully introgressed into an

aromatic rice cultivar, Musk Budji through MAS (Khan et al. 2018). Background selection was

carried out using 78 SSR and STS markers to reduce linkage drag around resistance genes Pi54,

Pi1 and Pita. The LSU AgCenter H. Rouse Caffey Rice Research Station has recently developed

SNP markers for traits such as blast resistance, plant height (sd1), resistance to Newpath and

Provisia herbicides, amylose content, grain length, aroma and others (Famoso, unpublished

results).

Significant progress has also been made via next-generation high-throughput DNA

sequencing technologies (Nadeem et al. 2018). A coordinated research, education, and extension

project was initiated in 2005 for the application of genomic discoveries to improve rice in the

United States (RiceCAP Project, https://ricecap.hosted.uark.edu/index.html). Chu et al (2006)

developed the SB2 doubled-haploid mapping population from a cross of the susceptible

Louisiana variety Cocodrie (PI 606331) with the resistant line MCR010277 (PI 641932). A total

of 325 doubled-haploid lines were produced from this cross.

One important contribution of the RiceCAP project was whole-genome sequencing of 13

japonica and indica lines that represented elite breeding materials used in modern varietal

development in the U.S. and Asia. Evaluation of the sequencing data resulted in the

identification of 136 non-synonymous SNPs markers associated with sheath blight resistance.

(Silva et al. 2012). In subsequent research, extreme phenotypes from the SB2 population were

screened using a subset of markers identified by Silva et al (2012) (Yamid Sanabria, unpublished

6

results). A total of 37 candidate nsSNPs markers from four loci on chromosomes 6, 8, 9 and 12

were identified for subsequent research.

A method that has become very popular in elucidating molecular mechanisms involved

in plant stress resistance and the crosstalk that occurs between different signaling pathways is

RNA-sequencing (RNA-Seq) (Qi et al. 2011; Mochida and Shinozaki 2011; AbuQamar et al.

2016; Nasr Esfahani et al. 2017). Several studies have already been conducted on host-

pathogen interactions for major plant diseases using RNA-Seq including Magnaporthe oryzae

(Oh et al. 2008), Ustilago maydis (Skibbe et al. 2010) and Phytophthora infestans (Gao et al.

2013).

Dr. Pankaj Jaiswal at Oregon State University has carried out an RNA-Seq experiment in

cooperation with Dr. Oard’s laboratory on sheath blight (unpublished results). The SB

susceptible variety, Cocodrie (PI 606331) and the resistant line MCR010277 (PI 641932) was

inoculated with R. solani under greenhouse condition at LSU. Leaf samples were collected at 0,

1, 3, 5 hours post-inoculation, and subjected to RNA-Seq analysis by Jaiswal’s laboratory. Three

genes were postulated to be involved in the sheath blight defense response: chitin elicitor binding

protein (CEBiP), chitin elicitor receptor kinase (CERK), and wall-associated kinase gene family

(WAK91). A non-synonymous SNP in WAK91 on chromosome 9 was identified as a candidate

marker for sheath blight resistance breeding.

1.5. Salvinia molesta, Noxious Aquatic Weed in Louisiana and Texas

Louisiana and Texas contain many slow-moving bayous, large lagoons, lakes and the

Mississippi river. The climate of these areas is humid subtropical, but most of the year it is warm

to hot along the Gulf Coast. Favorable to agriculture and fisheries, rice farming, fishing, and

7

shrimping contribute to the southern Gulf Coast economy. In addition, recreational activities like

boating, swimming and other water activities abound.

One major reason that impedes such activities is the persistent growth of the noxious

weed, Giant salvinia (Salvinia molesta D.S. Mitchell) in these bodies of water. In 1995, S.

molesta was first observed in South Carolina and was later reported from Louisiana and Texas in

1998 (McFarland et al. 2004; Mukherjee et al. 2014). Giant salvinia was first identified in the

Houston area in the spring 1998, but was discovered in Toledo Bend Reservoir, Texas’s largest

body of water, later that same year (https://tpwd.texas.gov/huntwild/wild/species/exotic/

salvinia.phtml).

By the time giant salvinia was reported in Texas in 1998, waterways and inland waters in

Louisiana had also experienced infestation of this weed. It was seen in Cameron Parish in 2000

and in the Atchafalaya Basin in 2006. In a report by the Louisiana Department of Agriculture

and Forestry, by 2008 most lakes in northwest Louisiana had a severe infestation, and the

freshwater marsh from Lafitte to Morgan City had unmanageable infestations. (https://www.

lsuagcenter.com/portals/communications/publications/agmag/archive/2010/fall/invasive-aquatic-

weeds-in-louisiana).

In a report published online by Scott Jackson (2016; http://nwdistrict .ifas.ufl.edu

/nat/2016/02/26/nisaw-2016-working-together-to-remove-giant-salvinia-salvinia-molesta-from-

northwest-florida/), a University of Florida/IFAS Extension Agent, an infestation of giant

salvinia in Northwest Florida was observed. The 2.5 acre infestation was on a 3.6 acre divided

pond which was precariously close to Deer Point Lake, a 5,000 acre water body that is the main

source of drinking water for Panama City and surrounding Bay County. The occurrence of Giant

8

Salvinia in the area was the second only reported enormous infestation and a high control of this

fern is a priority for the state of Florida due to its high invasive potential.

The gulf coast’s warm climate and mild winter are very conducive to exponential growth

of S. molesta (Mitchell and Tur 1975, Rani and Bharnbie 1983, Madsen and Wersal, 2008).

Another factor affecting S. molesta’s growth success is eutrophication, the high the concentration

of nutrients in the water. Al-Hamdani and Sirna (2008) observed an increased growth rate of S.

molesta grown under laboratory conditions by accumulating nitrogen and phosphorus under

different imitating eutrophic environments.

Dense mats of S. molesta fill in waterbodies as a result, significantly affect the

diversity of native aquatic plants and animals (Mitchell 1979). Conversely, exponential growth

of S. molesta impedes access to waterways for human activities like boating, fishing and

swimming which results in substantial economic losses and to crop production. S. molesta was

observed to clog water intakes and interfere with agricultural irrigation and farmlands. Moreover,

S. molesta is considered as a weed in certain rice growing regions that reduces production by

competing for water, nutrients and space (Anon., 1987). In a 1987 economic impact assessment

of S. molesta to irrigated rice in Sri Lanka, crop losses in affected areas were 2-3% (Doeleman,

1989).

Did the current infested areas of Louisiana and Texas arise from the same or from

different populations of S. molesta? To develop effective control and management strategies for

Louisiana and Texas, it is important to understand the population diversity of S. molesta both at

the genetic and whole-plant level.

9

1.6. Research Objectives

1. Identify and develop advanced breeding lines and populations for sheath blight resistance

through traditional breeding methods.

2. Identify and evaluate non-synonymous SNP markers for sheath blight resistance

germplasm for southern US environments through development of allele-specific DNA

markers identified by SNP databases and selective genotyping.

3. Determine genetic and phenotypic diversity of S. molesta in Louisiana and Texas.

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14

CHAPTER 2. DEVELOPMENT OF DISEASE RESISTANT GERMPLASM

2.1. Introduction

Breeding for sheath blight (SB) disease has achieved limited success in the U.S. and

elsewhere due to use of only a few highly resistant accessions with complex inheritance patterns

(Eizenga et al. 2002; Wang et al. 2011). Germplasm stocks and associated mapping populations

for breeding and study of sheath blight have been released in the U.S. for public use (Chu et al.

2006; Groth et al. 2007; Pinson et al. 2008, Groth et al. 2011; Rush et al. 2011; Jia et al. 2012;

Jia et al. 2015). The information below identifies and describes sources of resistance used in my

research to develop elite adapted lines with resistance to SB disease.

In cooperation with the USDA-funded RiceCAP project (http://www.uark.edu/ua/

ricecap), the SB2 mapping population was developed as a resource for mapping QTLs for sheath

blight resistance and other traits (Chu et al. 2006). SB2 consists of 325 true-breeding doubled-

haploid (DH) lines (Genetic Stocks Oryza (GSOR) accessions 200001 to 200325) developed

from susceptible parent Cocodrie (PI 606331) and the moderately-resistant breeding line

MCR010277 (PI 641932). Four DH lines from the SB2 population (SB2-3, SB2-102, SB2-174,

SB2-225; http://www.uark.edu/ua/ricecap) were used as sources of resistance in my breeding

efforts.

MCR010277 was selected with at least two sources of partial resistance in the F7-F8

generation from the cross LSBR-5/Lemont//Katy/3/ Cypress/Teqing (Nelson et al., 2011). The

resistance rating (0-9 scale; where 0=no disease and 9=very susceptible) for MCR10277 has

varied from 3-5 across multiple years at the H. Rouse Caffey Rice Research Station, Crowley,

LA (Oard, unpublished results). Three putative sources of resistance are present in the pedigree

of MCR10277. The first is LSBR-5, reported to be derived from somaclonal tissue of the U.S.

15

long-grain cultivar Labelle (Xie et al. 1992), but subsequent DNA marker analysis showed that

LSBR-5 was most likely derived from an unknown indica source (Nelson et al. 2012). The

second source is the long-grain Arkansas variety Katy (PI527707) derived from the cross Bonnet

73/CI9722// Starbonnet/Tetep/3/Lebonnet that produced a SB rating of 5 in Arkansas

(Moldenhaur et al. 1990) and ratings of 5 to 6 in Louisiana (Oard, unpublished results). The

Vietnamese long-grain variety Tetep (PI280682) in the pedigree of Katy is a known source for

SB resistance (Moldenhauer et al. 1990). The third source is the medium-grain cultivar Teqing

(PI536047), reported to carry a single dominant gene for resistance (Pan et al. 1999). Teqing has

shown consistently high levels of resistance to SB with ratings typically ranging from 3 to 4 in

multiple inoculated field trials at the RRS (Oard, unpublished results). The susceptible varieties

Lemont (PI475833) and Cypress (PI 561734) have shown susceptible SB ratings of 7 to 9 in

various inoculated field trials at the RRS (unpublished results).

The long-grain indica variety Jasmine 85 (PI 595927) was initially developed at the

International Rice Research Institute (IRRI), Philippines, from the cross ‘Peta*3/Taichung

Native 1’ and released in the U.S. by the USDA-ARS and the Texas Agricultural Experiment

Station in 1998 (Marchetti et al. 1998). Jasmine 85 is known to exhibit high levels of resistance

to SB in Louisiana, Texas, and Arkansas (Marchetti et al. 1998; Jia and Liu, 2011).

Unfortunately, Jasmine 85 has exhibited high levels of seed dormancy in Louisiana soils, so field

evaluation of this material is currently restricted at the RRS. The Vietnamese indica line WSS2,

derived from Tetep, was reported to show high levels of resistance (Wasano, 1998). H4/CODF is

a cobalt radiation-induced mutation derived from the Sri Lankan cultivar H4 (Rush et al. 2011)

and is partial resistant to SB disease (Sha, 1998). The long-grain resistant indica varieties

Taducan and Azmil were introduced into the U.S. from the Philippines with good SB resistance

16

(Rush et al. 2011). Similarly, Yangdao 6 is an elite indica line bred through irradiation induced

mutation showing resistance to multiple diseases (Dai et al. 2006). The restorer line Minghui 63,

developed by Xie et al (1987), is a Chinese indica variety derived from the cross IR30×Gui 630

with good resistance to SB. IR30 is a semi-dwarf variety from IRRI with good plant type, high

resistance to blast, bacterial blight, and brown plant hoppers and a good restorer for WA CMS A-

lines. The other parent, Gui 630, is an imported rice line from Guyana with high grain weight,

desirable grain quality and high yield potential (Xie et al. 1987). Starbonnet and Nortai were

developed and released cooperatively by the Agricultural Research Service, USDA and the

Arkansas Agricultural Experiment Station (Johnston, et al, 1968, 1973). Starbonnet was selected

in 1960 from the F6 generation from a cross between `Century Patna 231' (C.I. 8993) and

`Bluebonnet' (C.I. 8322) in Arkansas (Johnston, et al, 1968). Nortai was developed from the

cross ‘Northrose’ x P.I. 215936 (Johnston et al, 1973). CIAT 4 (Oryzica Llanos 5) developed by

the International Center for Tropical Agriculture, Cali, Colombia, was developed from the cross

P5269/P2060-F4-2-5-2. CIAT 7 (Araure 3) from Venezuela was derived from the cross

IR8/Peta5//Belle Patna and released as a variety 1984. Both indica cultivars show resistance to

SB disease in south America and Louisiana (personal communication, Y. Sanabria; Oard,

unpublished results). Drs. Rush, Groth, and Sha released 25 SB resistant lines in 2011 including

PI6658321 (Cypress/4/LSBR-5/Lemont//Teqing/3 /H4CODF) showing an average SB rating of 5

in field inoculated trials from 2007 to 2009 at Crowley. PI658327 (LSBR-5/LMNT//Teqing/

3/Cocodrie/4/Priscilla) produced an average resistance rating of 3.3 across the same field trials.

Field evaluations of different populations at RRS-Crowley, LA from 2013 to 2018

showed different sources of resistance. In the lines with the following pedigrees:

CIAT7/MCR010277, CPRS//CIAT4/ MCR010277, CCDR//CIAT8/ MCR010277, MCR010277

17

and CIAT 4 and CIAT 7 are the sources of resistance (Nelson et al. 2011);

KATY/CPRS/J85//CTHL line, the sources of SB resistance were from KATY (Moldenhauer, et

al. 1990) and J85 (Marchetti et al. 1998) and a line of this pedigree,

JODN/3/TDCN/SBNT//LSBR5/LMNT have the sources of resistance from Taducan (Rush et al.

2011) and LSBR5 (Xie et al. 1992). A line from the CCDR/SB5 RIL 46 cross: one of the

parents, SB5 RIL 46 is a recombinant inbred line developed from the cross Lemont/Jasmine 85.

The Lemont/Jasmine 85 mapping population, or SB5 mapping population, was developed under

the Rice Coordinated Agricultural Project (RiceCAP) and released on August 31, 2009 by USDA

ARS and University of Arkansas, Division of Agriculture. Another line developed for the

RiceCAP project was a doubled haploid mapping population (SB2 mapping population) from the

cross Cocodrie/MCR01027.

2.2. Materials and Methods

2.2.1. Plant materials

For the 2013 field season, approximately 700 F4-F5 sheath blight lines developed by Drs.

Oard and Rush (Table 2.1) were planted at the LSU AgCenter H. Rouse Caffey Rice Research

Station (RRS), Crowley, Louisiana. Previous research by Oard and Rush showed these lines

produced moderate to high levels of resistance in inoculated plots (unpublished results).

Table 2.1. Pedigree, generation and number of lines of sheath blight lines initially evaluated during the 2013 Field Season at H. Rouse Caffey Rice Research Station, Crowley, Louisiana.

Pedigree Generation No. of lines 09DN/RUSH072 F4-F5 30 09DN/RUSH222 F4-F5 35 09DN/RUSH222//SBR174 F4-F5 35 09DN157//TRP545/CL161 F4-F5 30 09SB131/SB125 F4-F5 30 35-9/41-3 F4-F5 30

Table 2.1 continued

18

2.2.2. Field evaluation of elite breeding lines

Thirty-three selections from the 700 F4-F5 sheath blight lines described above were

planted and advanced in the summers of 2014-2018at the H. Rouse Caffey Rice Research

Station, LSU AgCenter, Crowley, Louisiana. The breeding material was typically planted in late

March or in early April of each year with the Hege 90 Magazine planter in 2-meter rows, 0.025

meter row width, with approximately 50 seeds per row. The number of rows per population or

line varied with seed availability. High plant density was desired for better disease induction.

Management of the crop, pests and diseases was based on the LSU Rice Production handbook.

Nitrogen application consisted of 120 kg/ha on dry soil pre-flood, and herbicide application was

carried out at the 2 to 4-leaf stage for control of broad-leaf and grassy weeds.

Pedigree Generation No. of lines CIAT 4/MCR010277 F4-F5 35 CIAT 7/MCR010277 F4-F5 35 CIAT 8/MCR010277 F4-F5 35 GSOR101019 F4-F5 35 JODN/3/TDCN/SBNT//LSRR5/LMNT F4-F5 30 KATY/CPRS/J85//CTHL F4-F5 30 PI658321 Inbred 10 PI658327 Inbred 10 RUSH C99-1166 Inbred 10 RUSHSBR4 F4-F5 30 RUSHSBR4/09125 F4-F5 30 SB125/SB131 F4-F5 30 SB2-102 F4-F5 30 SB2-174 F4-F5 30 SB2-225 F4-F5 30 SB2-3 F4-F5 30 SB5 RIL 46 F4-F5 30 WELLS/CANTORSB51//97URN128/96CR921 F4-F5 30

19

Plants in each row were inoculated with isolate LR172 of R. solani at the late-tillering –

joint elongation stage. The inoculum was prepared by Dr. Groth at the RRS (inoculum

preparation discussed below). Disease scoring was recorded at the soft-dough stage using the 0 -

9 rating where 0 = highly resistant and 9 =highly susceptible. From five to eight panicles from

each selected row were harvested by hand at maturity, threshed, cleaned, and dried to 12%

moisture for storage at 4C.

For the 2016 and 2017 field seasons, the 7 best lines selected from the 2015 field

evaluation was planted in 3 rows plot with one replication for inoculated plot and the other in

uninoculated in a completely randomized block design. Susceptible checks, CL151, CL111,

CL152, CL153, Cocodrie, and Catahoula, as well as Teqing and MCR010277 were planted. This

was done to determine the percent (%) yield reduction in an inoculated SB plot.

2.2.3. R. solani – LR172 inoculum preparation

Isolate LR172 was originally identified from a naturally infected rice plant (cv.

Lebonnet) in Louisiana by the late Dr. Rush in 1972 (Groth and Bond, 2006). Briefly, the

inoculum was produced on a moist, autoclaved rice grain/rice hull mixture (1:2 vol/vol)

incubated in the dark for 12 to 14 days at 30°C. The grain-hull inoculum was broken into small

(3- to 7-mm diameter) particles, consisting of several rice grains held together by fungal mycelia.

Approximately 100 ml (17 ml m-2) were distributed evenly over each row by hand except for

non-inoculated controls.

2.2.4. Crosses of elite lines to Louisiana varieties

Louisiana commercial varieties are known to be moderately to highly susceptible to SB

disease (Rush et al., 2011). Traditionally bred Louisiana varieties, such as Cypress (Linscombe

et al. 1993), Cocodrie (Linscombe et al. 2000), Catahoula (Blanche et al. 2009) and the

20

Clearfield varieties CL111 (Oard et al. 2013), CL151 (Blanche et al. 2010), CL152 (Oard et al.

2013), CL153 (Famoso et al. 2016) and CL161 (Blanche et al. 2011) were used as recurrent

parents for the breeding activities. Selected SB lines from the field evaluation were used as

pollen donors.

The designated female parent (recurrent parent) must have its anthers removed before

being pollinated with pollen donor (male parent). Briefly, the anthers were emasculated with hot

water treatment and vacuum suction. First, the spikelets of the recurrent parent was treated with

hot water treatment in a water bath, 45o for 5 minutes. Immediately after being removed from the

hot water, the spikelets were allowed to air dry before clipping. The panicle was trimmed from

the bottom upward to leave 25-35 well-spaced spikelets to be emasculated. One-third of the

glume was clipped off of each spikelet, and remaining spikelets that have not opened were cut

off with a pair of scissors. An opening is then cut on each of the selected spikelets separately so

that the anthers come free to be vacuumed out of the spikelet through suction force by using a

small vacuum pump. The emasculated panicle was then covered with a labeled glassine crossing

bag before the plant was moved back into the greenhouse ready for pollination.

Immediately after emasculation cross pollination was done inside the greenhouse when

available pollen from a donor plant was readily available for pollination. Pollination was done by

slowly and carefully swirling the flowering male panicle of the donor plant above the

emasculated female panicle of the recurrent parent in a glassine crossing bag. After pollination,

the appropriate information on the parent donor plant was written on the glassine cross bag and

the bag is placed back over the recurrent parent panicle. The F1 seeds from each cross were

allowed to mature and harvested in about 28-34 days. For this study, a total of 102 crosses were

made for each year from 2014 to 2018 using 17 original donor lines (SB5 RIL 46, SB2-174,

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SB2-3, CIAT4/MCR010277, CIAT7/MCR010277, SB2-102, SB2-225,

JODN/3/TDCN/SBNT//LSRR5/LMNT, PI658321 - C99-1249

CPRS/4/LSBR5/LMNT//TQNG/3/H4CODF, PI658327 - C99-1166

LSBR5/LMNT//TQNG/3/CCDR/4/PSCL, PI658335 - COO-1700 LSBR5/LMNT//TQNG

/4/LSBR5/LMNT/3/ H4CODF//NTAI(03-10993-11019, RUSH C99-1166 (LSBR5),

KATY/CPRS/J85//CTHL, 09DN/RUSH222//SBR174, RUSHSBR4, RUSHSBR4/09125, 35-

9/41-3, GSOR101019) and 7 recurrent parents (Catahoula, Cocodrie, CL111, CL151, CL153 and

CL161). Breeding material was advanced from the F1 to the BC2F3 generation from 2014 to

2018.

2.2.5. F1 nursery

The F1 seeds produced from each of the crosses including the parents were sown in the

greenhouse in a 11.29 cm2 x 5.08 cm peat pots tall with garden soil mixed with ShowScape

potting soil in a 1:1 ratio until the seedlings are ready to be transplanted in the F1 nursery field.

Twenty-one to 30 day old rice seedlings were planted in a slightly flooded field in 5 seedlings

per 1 m row, 30.48 cm apart per seedlings (Figure 2.1) to produce good amount of tillers and

spikelets needed for crossing activities.

2.2.6. Population development of SB lines F1 seeds produced from the different crosses were planted in the F1 nursery at RRS in

2014. Plants in the F1 with good plant height and plant type were selected and tagged with a

white painted wooden stake marked with its parental cross for identification. F2 seeds were

harvested from individual selected plants from each row. Twenty to 30 grams of seeds from the

selected F2 plants were planted in the Puerto Rico off-season nursery in July 2014. F2 plants were

selected based on maturity, height, tillering, panicle size, panicle exsertion, grain shape, disease

22

Figure 2.1. F1 seedlings grown in the greenhouse and field at Crowley; a. F1seedlings growing in peat pots inside the greenhouse; b. 30-day old seedlings growing in the field nursery; c. seedlings at tillering stage growing in field nursery. resistance and overall plant type. Panicles harvested in the off-season nursery were sent back to

Crowley and planted for the 2015 summer field evaluation experiments. The breeding materials

(F3) were grown as panicle (head) rows and the best rows were selected to advance to the next

generation.

2.2.7. Data analyses

During the field evaluations, sheath blight disease score was recorded at the soft-dough

stage using the 0 - 9 rating where 0 = highly resistant and 9 =highly susceptible. Three rows per

line were scored. Plant height of 3 random plants in each row was measured. For the 2016 and

2017 field season where there was inoculated and inoculated plots, 3 rows per replication were

harvested to determine the grain yield.

Analysis of variance (ANOVA) was computed with Fisher’s Least Significant Difference

(L.S.D.) post hoc test, coefficient of variation (C.V.), and standard error (S.E.). Correlation

analysis was also computed on days to heading, disease score, plant height and grain weight of

a b

c

23

the resistant donor plants, selected sheath blight lines and the susceptible plants in the inoculated

conditions.

2.3. Results and Discussion 2.3.1. Field evaluation of elite breeding lines

2013 Field Trial

Both SB sources MCR and Teqing showed resistant SB ratings of 1.0 as shown in Table

2.2 that were consistent with previous field research at the RRS (Rush et al. 2011; Groth et al.

2013). SB lines PI658321 and PI658327 produced moderately-resistant ratings of 4.0 that were

comparable to the respective ratings of 4.9 and 3.3 as reported by Rush et al. in 2011 at the RRS.

The susceptible checks Catahoula and Cocodrie produced susceptible rating of 7.5 and 8.0 in

2013 that were akin to previous field trials at the RRS (Groth et al. 2013).

From a total of 700 lines inoculated with R. solani in 2013 at the RRS, 29 selected

breeding lines produced moderate to high levels of resistance with ratings varying from 3.5 to

5.0 (Table 2.2). A total of 17 SB sources were used as parents to develop the selected lines.

Resistant parents CIAT 8 and MCR presumably contributed to resistance in lines 3, 6, 9, 27, and

29. MCR was crossed to resistant CIAT 4 and 7 and to susceptible Cocodrie and Trenasse in

selected lines 7, 8, 10, 25, 26, 28 with ratings that varied from 4.0 to 5.0. These selected lines

produced similar disease reactions to PI658321 and PI658327, but the lines were on average 2 to

5 cm taller, most likely due to the tall CIAT accessions from South America. RiceCAP RILs

SB5-46 (line 4) produced a resistant response of 3.5 and good height of 98 cm. Lines 20 and 21

exhibited moderate resistance levels of 4.0 with good plant heights of 93 and 94 cm,

respectively. SB2-3 crossed to Catahoula in line 5 showed moderate resistance, but with a tall

plant height of 121 cm.

24

Table 2.2. Sheath blight rating, plant height, and pedigree of 32 selected F4-F5 sheath blight lines and four check varieties from 2013 SB field evaluation trial, H. Rouse Caffey Rice Research Station, Crowley, Louisiana.

2013 Line Pedigree SB Rating

(0-9)* Plant Height

(cm)* 1 MCR010277 (PI 641932) 1.0 99 2 Teqing (PI536047) 1.0 111 3 CCDR//CIAT 8/MCR010277 3.5 117 4 GSOR101019 (SB5 RIL 46 - (LMNT/Jasmine 85)) 3.5 98 5 CTHL/SB2-3 4.0 121 6 CCDR//CIAT 7/MCR010277 4.0 115 7 TRNS//CIAT 8/MCR010277 4.0 115 8 CCDR//CIAT 7/MCR010277 4.0 108 9 RUSHSBR4/09125 4.0 108 10 35-9/41-3 4.0 112 11 09SB131/SB125 4.0 101 12 SB2-102 4.0 98 13 SB125/SB131 4.0 107 14 RUSHSBR4 4.0 105 15 WELLS/CANTORSB51//97URN128/96CR921 4.0 107 16 PI658321 (CPRS/4/LSBR5/LMNT//TQNG/3/H4CODF) 4.0 96 17 PI658327 (LSBR-5/LMNT//Teqing/3/Cocodrie/4/Priscilla) 4.0 88 18 09DN/RUSH222//SBR174 4.0 93 19 09DN157//TRP545/CL161 4.0 94 20 KATY/CPRS/J85//CTHL 4.0 103 21 CCDR//09DN/RUSH072 4.5 112 22 CCDR/SB5 RIL 46 4.5 118 23 CPRS//CIAT 4/MCR010277 4.5 120 24 CCDR//CIAT 7/MCR010277 4.5 126 25 CCDR//CIAT 8/MCR010277 4.5 110 26 CCDR//CIAT 7/MCR010277 4.5 112 27 CCDR//CIAT 8/MCR010277 5.0 113 28 JODN/3/TDCN/SBNT//LSRR5/LMNT 5.0 104 29 LSBR-5 5.0 95 30 CCDR//09DN/RUSH072 5.5 107 31 SB125/SB131 5.5 115 32 CCDR/SB2-174 6.5 107 34 SB2-225 6.5 105

Table 2.2. continued

25

2013 Line Pedigree SB Rating

(0-9)* Plant Height

(cm)* 35 Catahoula 7.5 104 36 Cocodrie 8.0 84

LSD 0.05 1.07 13.78 Std. dev 1.35 9.54

*Mean values from 3 replications, 3 rows per replication; red cells – resistant check varieties; yellow cells – susceptible check varieties 2014 Field Trial

SB lines MCR and Teqing showed ratings of 3 to 4 in 2014 Crowley field trials as shown

in Table 2 that were consistent with the 2013 field trials (Table 2.). Similarly, susceptible checks

Cocodrie and Catahoula produced high ratings of 7 and 9 in 2014 that were comparable to the

2013 results. Lines 17 (WELLS/CANTORSB51//97URN128/96CR921), 19 (PI658327), and 27

(CCDR//CIAT 8/MCR010277) showed consistency in disease response as the 2014 SB rating of

4 for this material was identical to those in the 2013 trial. On the other hand, several

Table 2.3. Analysis of variance on SB disease rating of the selected SB resistant lines and resistant and susceptible checks from the 2013 SB field evaluation trial, H. Rouse Caffey Rice Research Station, Crowley, Louisiana.

Source of Variation SS df MS F P-value F crit

Between Groups 45.57 2 22.78 43.73 7.0299E-10 3.29

Within Groups 16.67 32 0.52

Total 62.24 34 Table 2.4. Analysis of variance on plant height of the selected SB resistant lines and resistant and susceptible checks from the 2013 SB field evaluation trial, H. Rouse Caffey Rice Research Station, Crowley, Louisiana.


Between Groups 343.19 2 171.60 1.99 0.15 3.29


Total 3092.74 34

26

lines that produced relatively low SB scores in 2013 nonetheless showed substantially higher

scores in the 2014 trial. For example, line 4 in 2013 produced a resistant rating of 3 while the

2014 trial it had a rating of 6, indicating a susceptible disease response to R. solani. These results

underscore the challenge of breeding for SB resistance when large GxE effects are present.

Nevertheless, lines 17, 19, and 27 showing consistent infection response that were selected for

additional evaluation in the 2015 field trials.

Table 2.5. Sheath blight rating, plant height, and pedigree of 39 selected F4 derived F5 sheath blight lines, 4 SB inbred lines and four check varieties from 2014 SB field evaluation trial, H. Rouse Caffey Rice Research Station, Crowley, Louisiana.

2013 Line Pedigree Generation SB Rating

(0-9)* Plant Height

(cm)* 1 MCR010277 (PI 641932) Inbred 3 99

2 Teqing (PI536047) Inbred 4 111

17 WELLS/CANTORSB51//97URN128/96CR921 F5 4 106

19 PI658327 Inbred 4 92

27 CCDR//CIAT 8/MCR010277 F5 4 114

23 CCDR//09DN/RUSH072 F5 5 104

19 PI658327 Inbred 5 90

20 09DN/RUSH222//SBR174 F5 5 94

16 RUSHSBR4 Inbred 5 106

12 35-9/41-3 F5 5 106

23 CCDR//09DN/RUSH072 F5 5 111

28 CCDR//CIAT 8/MCR010277 F5 5 119

28 CCDR//CIAT 7/MCR010277 F5 5 113

19 PI658327 Inbred 5 89

31 LSBR-5 Inbred 5 94

20 09DN/RUSH222//SBR174 F5 5 93

21 09DN157//TRP545/CL161 F5 5 92

24 CPRS//CIAT 4/MCR010277 F5 5 118

11 RUSHSBR4/09125 F5 5 109

21 09DN157//TRP545/CL161 F5 5 95

29 CCDR//CIAT 8/MCR010277 F5 5 108

33 SB125/SB131 F5 5 120

33 SB125/SB131 F5 5 108


27

2013 Line

Pedigree Generation SB Rating

(0-9)* Plant Height

(cm)* 18 PI658321 Inbred 5 97

28 CCDR//CIAT 7/MCR010277 F5 5.5 115

28 CCDR//CIAT 7/MCR010277 F5 6 110

24 CCDR/SB5 RIL 46 F5 6 123

28 CCDR//CIAT 8/MCR010277 F5 6 105

28 CCDR//CIAT 8/MCR010277 F5 6 112

26 CCDR//CIAT 7/MCR010277 F5 6 121

26 CCDR//CIAT 7/MCR010277 F5 6 115

35 SB2-225 F5 6 103

33 SB125/SB131 F5 6 107

28 CCDR//CIAT 7/MCR010277 F5 6 113

5 CTHL/SB2-3 F5 7 119

14 SB2-102 F5 6 96

29 CCDR//CIAT 8/MCR010277 F5 6 118

13 09SB131/SB125 F5 6 100

4 GSOR101019 F5 6 100

9 TRNS//CIAT 8/MCR010277 F5 6 117

34 CCDR/SB2-174 F5 6 109

26 CCDR//CIAT 7/MCR010277 F5 6 124

4 GSOR101019 F5 6 97

28 CCDR//CIAT 7/MCR010277 F5 7 114

28 CCDR//CIAT 8/MCR010277 F5 7 116

23 CCDR//09DN/RUSH072 F5 9 108

36 Catahoula Inbred 7 105

37 Cocodrie Inbred 9 93 LSD 0.05 1.12 14.69 Std. dev 0.98 10.05

*Mean values from 3 replications, 3 rows per replication; red cells – resistant check varieties; yellow cells – susceptible check varieties 2015 Field Trial

Table 2.8 shows that MCR and Teqing produced resistant reactions in 2015 as in the

previous two years at Crowley. Susceptible checks Cocodrie and Catahoula also exhibited

consistent results across the three years of field trials. The average SB rating across the 25

selected lines in 2015 was 4.3 vs. 7.5 for the Cocodrie and Catahoula susceptible checks and

28

3.0 for resistant MCR and Teqing. The majority of the selected lines evaluated in 2015 produced moderate to resistant SB reactions of 3 to 5 that were similar to those observed in 2014 (Table

2.5) and in 2013 (Table 2.2). Certain lines such as 5 (CTHL/SB2-3) were inconsistent in their

disease reactions across the three years. Mean plant height of the 25 selected lines in 2015 was

Table 2.6. Analysis of variance of SB disease rating of the selected SB resistant lines and resistant and susceptible checks from the 2014 SB field evaluation trial, H. Rouse Caffey Rice Research Station, Crowley, Louisiana.


Between Groups 20.65 2 10.33 17.19

1.96353E-06 3.18


Total 51.29 53 Table 2.7. Analysis of variance of plant height of the selected SB resistant lines and resistant and susceptible checks from the 2014 SB field evaluation trial, H. Rouse Caffey Rice Research Station, Crowley, Louisiana.

Source of Variation SS Df MS F P-value F crit

Between Groups 96.82 2 48.41 0.47 0.63 3.18

Within Groups 5251.54 51 102.97

Total 5348.37 53

111 cm vs. 105 for resistant lines Teqing and MCR and 97 cm for Cocodrie and Catahoula.

Selection 17 (WELLS/ CANTORSB51//97URN128/96CR921) showed a mean disease rating of

4.0 across the three years with an average height of 104 cm.

The eight new lines 38 to 45 shown in Table 2.8 were comprised of additional Plant

Introductions (Rush et al. 2011) such as PI658335 (line 39) and crosses of original selections

(Table 2.2) to susceptible varieties such as line 38 or new sources of resistance such as line 41.

29

Disease ratings for the new lines in 2015 ranged from 4 to 6 and plant height varied greatly from

93 to 122 cm. New line 38 (CCDR/PI658335) produced the identical disease rating of 4 as the

donor parent PI 658335 with a substantial height reduction of 12 cm at 95 cm.

2016 Field Trial Table 2.11 shows plant height and 0-9 SB ratings for F3 and F6 selections evaluated in the

2016 RRS field trial. Resistant Teqing and MCR and susceptible Catahoula and Cocodrie

showed expected responses to R. solani infection as in the 2013-2015 RRS field trials. Ten Plant

Introductions displayed similar SB ratings in the 2016 trial compared to the trial reported by

Rush et al. in 2011. Five selections in the F6 generation (WELLS/CANTORSB51

//97URN128/96CR921; JODN/3/TDCN/SBNT//LSRR5/LMNT; SB131/SB125; CCDR

//09DN/RUSH072; CTHL/SB2-3) produced SB ratings of 3 to 4 that were consistent with

Table 2.8. Sheath blight rating, plant height, and pedigree of 31 selected lines including 16 F6, 4 F3 and 5 inbred sheath blight lines and four check varieties from 2015 SB field evaluation trial, H. Rouse Caffey Rice Research Station, Crowley, Louisiana.


2013 Line Pedigree Generation SB Rating

(0-9)* Plant Height

(cm)* 1 MCR010277 (PI 641932) Inbred 3 99

2 Teqing (PI536047) Inbred 3 111

30 JODN/3/TDCN/SBNT//LSR5/LMNT F6 3 103

21 09DN157//TRP545/CL161 F6 3 105

20 09DN/RUSH222//SBR174 F6 3 107

19 PI658327 Inbred 4 102

17 WELLS/CANTORSB51//97URN128/96CR921//CTHL F6 4 98

16 RUSHSBR4 F6 4 105

23 CCDR//09DN/RUSH072 F6 4 106

31 LSBR-5 Inbred 4 99

38¨ CCDR/PI658335 F3 4 95

39¨ PI 658335 Inbred 4 107

15 SB125/SB131 F6 4 102

32 CCDR//09DN/RUSH072 F6 4 106

40¨ CTHL//SB131/SB125 F3 4 120

30

*Mean values from 3 replications, 3 rows per replication; red cells – resistant check varieties; yellow cells – susceptible check varieties; ¨additional lines added in 2015 trial at Crowley. previous RRS trials in 2015. The F3 selection CCDR/12:964-1 (PI 658335) exhibited a SB rating

of 5 that was identical to the original resistant donor line PI 658325. Plant height of the selected

lines ranged from 89 cm to 105 cm which was acceptable for parental breeding germplasm.



Between Groups 25.88 2 12.94 31.87 5.2768E-09 3.23


Total 42.12 42

2013 Line Pedigree Generation

SB Rating (0-9)*

Plant Height (cm)*

7 CCDR//CIAT 7/MCR010277 F6 4 126

12 35-9/41-3 F6 4 119

6 CCDR//CIAT 8/MCR010277 F6 5 113

7 CCDR//CIAT 7/MCR010277 F6 5 118

21 09DN157//TRP545/CL161 F6 5 129

41¨ MCR010277/YANGDAO 4 F3 5 104

42¨ PI 658320 Inbred 5 110

25 CPRS//CIAT 4/MCR010277 F6 5 119

43¨ CCDR/RUSH8:247 F3 5 114

28 CCDR//CIAT 7/MCR010277 F6 5 125

44¨ CTHL//SB131/SB125 F3 5 122

45¨ PI658321 Inbred 6 93

5 CTHL/SB2-3 F6 6 93

37 Catahoula Inbred 7 104

37 Cocodrie Inbred 8 90 LSD 0.05 0.93 13.82 Std. dev 1.00 9.53

31

Table 2.10. Analysis of variance of plant height of the selected SB resistant lines and resistant and susceptible checks from the 2015 SB field evaluation trial, H. Rouse Caffey Rice Research Station, Crowley, Louisiana.


Between Groups 256.60 2 128.30 1.44 0.24 3.23


Total 3813.00 42 Table 2.11. Plant height and SB ratings for F4 and F7 selections evaluated at the RRS, 2016

Pedigree Generation SB Rating (0-9)*

Plant Height (cm)*

Teqing (PI536047) Inbred 3 110

MCR010277 (PI 641932) Inbred 4 99

WELLS/CANTORSB51//97URN128/96CR921 F7 3 98

JODN/3/TDCN/SBNT//LSRR5/LMNT F7 3 89

SB131/SB125 F7 3 96

CCDR//09DN/RUSH072 F7 4 102

PI 658320 Inbred 3 94

SB125/SB131 F7 4 96

SB2-225 F7 4 94

PI658327 Inbred 4 80

SB125/SB132 F7 4 103

CTHL/SB2-3 F7 4 105

PI 658327 Inbred 4 85

PI 658331 Inbred 4 85

CL111/GSOR101021 F4 4 97

PI 658330 Inbred 4 86

PI 658314 Inbred 5 105

CCDR/PI 658335 F4 5 100

PI 658321 Inbred 5 81

PI 658329 Inbred 5 101

PI 658325 Inbred 5 79

Catahoula Inbred 8 100

Cocodrie Inbred 9 92

LSD 0.05 0.56 7.78 Std. dev 0.95 5.37

*Mean values from 3 replications, 3 rows per replication; red cells – resistant check varieties; yellow cells – susceptible check varieties

32



Between Groups 54.68 2 27.34 187.56 1.1553E-21 3.22


Total 60.8 44 Table 2.13. Analysis of variance of plant height of the selected SB resistant lines and resistant and susceptible checks from the 2016 SB field evaluation trial, H. Rouse Caffey Rice Research Station, Crowley, Louisiana.


Between Groups 80.47 2 40.24 1.42 0.25 3.22


Total 1269.31 44 2017 Field Trial

Table 2.14 shows plant height and 0-9 SB ratings for F3, F8 and BC2F3 selections

evaluated at the RRS in 2017. As in previous trials, the resistant and susceptible checks produced

expected SB ratings. Six selections in the F8 generation (09DN157//TRP545/CL161;

CTHL/SB2-3; CCDR/PI 658335; SB131/SB125; CCDR//09DN/RUSH072;

WELLS/CANTORSB51//97URN128/96CR921) showed good levels of resistance (SB ratings =

3) that were similar to previous trials in 2015 and 2016. Several F2 and BC2F2 selections

displayed apparent high levels of resistance, but this early-generation material will require

additional field testing to confirm the 2017 results.

33

Table 2.14. Plant height and SB ratings for F3, F4 derived F8 and BC2F3 selections evaluated at the RRS, 2017.

Pedigree Generation SB Rating (0-9)*

Plant Height (cm)*

Teqing (PI536047) Inbred 1 111

MCR010277 (PI 641932) Inbred 3 98

RUSH C99-1166 (LSBR-5) F 3 95

09DN157//TRP545/CL161 F8 3 92


CTHL/SB2-3 F8 3 91

CCDR/PI 658335 F5 3 93

PI 658327 Inbred 3 96

PI 658335 Inbred 3 89

SB131/SB125 F8 3 95

CCDR//09DN/RUSH072 F8 3 104

WELLS/CANTORSB51//97URN128/96CR921 F8 3 97

15HB125/SB125/SB131 F8 3 101

15HB180/PI658327 F3 3 94

15HB181/09DN157//TRP545/CL161 F3 3 101

15HB114/SB125/SB131 F3 3 100

15HB017/09DN/RUSH222//SBR174 F3 3 88

15HB017/09DN157//TRP545/CL161 F3 3 90

15HB180/PI658327 F3 3 100

15HB017/CTHL/SB2-3 F3 3 91

15HB180/09DN/RUSH222//SBR174 F3 3 102

15HB017/RUSHSBR4 F3 3 96

15HB114/JODN/3/TDCN/SBNT//LSRR5/LMNT F3 3 101

15HB127/PI658327 F3 3 97

15HB128/PI658327 F3 3 98

15HB180/09SB131/SB125 F3 3 98

15HB128/JODN/3/TDCN/SBNT//LSRR5/LMNT F3 4 107

15HB180/09DN157//TRP545/CL161 F3 4 97

15HB181/RUSH C99-1166 (LSBR-5) F3 4 93

15HB017/09DN/RUSH222 F3 4 92

15HB017/WELLS/CANTORSB51//97URN128/96CR921//CTHL F3 4 90


34


(0-9)* Plant Height

(cm)*

15HB050/SB131/SB125 F3 4 104

CL161//CL161/PI 658314 BC2F3 4 98

CCDR//09DN/RUSH072 BC2F3 4 98

CCDR//CCDR/PI658327 BC2F3 4 103

CCDR//CPRS//CIAT 4/MCR010277 BC2F3 4 95

CCDR//WELLS/CANTORSB51//97URN128/96CR921 BC2F3 4 102

CCDR//JODN/3/TDCN/SBNT//LSRR5/LMNT BC2F3 4 97

CCDR//SB125/SB131 BC2F3 4 100

CCDR//CCDR/09DN/RUSH222 BC2F3 4 94

CCDR//CCDR/PI 658314 BC2F3 4 94

CTHL//WELLS/CANTORSB51//97URN128/96CR921 BC2F3 4 102

CTHL//JODN/3/TDCN/SBNT//LSRR5/LMNT BC2F3 4 103

CTHL//CTHL/RUSHSBR4 BC2F3 4 103

CTHL//SB125/SB131 BC2F3 4 101

CTHL//CTHL/SB2-225 BC2F3 4 98

CTHL//CTHL/RUSH C99-1166 (LSBR-5) BC2F3 4 102

CTHL//09DN/RUSH222 BC2F3 4 96


CTHL//SB131/SB125 BC2F3 4 97

CTHL//CPRS/Oryzica Llanos 5 BC2F3 4 96

CTHL//RUSHSBR4/09125 BC2F3 4 98

CTHL//SB131/SB125 BC2F3 4 101

CTHL//SB125/SB131 BC2F3 4 108

CTHL//CTHL/PI658327 BC2F3 4 98


CTHL//CTHL/RUSHSBR4 BC2F3 4 97

CL161//09DN/RUSH222//SBR174 BC2F3 4 95

CL161//CL161/PI 658321 BC2F3 4 101


15HB172/PI658327 F3 4 97

15HB180/SB2-225 F3 4 101

CL151//CPRS/Oryzica Llanos 5 F3 4 93

CL151//CCDR/PI658335 F3 4 107

CCDR/PI658335 F4 4 105


35


(0-9)* Plant Height

(cm)*

CTHL//CCDR/PI658335 BC2F3 4 104

PI 658320 Inbred 4 105

CTHL/SB2-3 F8 4 113

CL111/GSOR101021 F4 4 100

15HB172/RUSHSBR4 F3 4 100

CCDR//CCDR/RUSH C99-1166 (LSBR-5) BC2F3 5 100

CCDR/PI658335 F4 5 106

CPRS/Oryzica Llanos 5 F3 5 112

CCDR//CPRS/Oryzica Llanos 5 F3 6 111

SB125/SB132 F8 6 100

CL152 Inbred 6 95

CL153 Inbred 6 84

CL111 Inbred 7 88

CL151 Inbred 8 102

Catahoula Inbred 8 86

Cocodrie Inbred 8 89 LSD 0.05 0.90 8.28 Std. dev 0.83 6.10

*Mean values from 3 replications, 3 rows per replication; red cells – resistant check varieties; yellow cells – susceptible check varieties Table 2.15. Analysis of variance of SB disease rating of the selected SB resistant lines and resistant and susceptible checks from the 2016 SB field evaluation trial, H. Rouse Caffey Rice Research Station, Crowley, Louisiana.


Between Groups 62.57 2 31.28 75.40 8.2144E-26 3.04


Total 156.34 228

36

Table 2.16. Analysis of variance of plant height of the selected SB resistant lines and resistant and susceptible checks from the 2016 SB field evaluation trial, H. Rouse Caffey Rice Research Station, Crowley, Louisiana.


Between Groups 579.83 2 289.92 8.28 0.0003 3.036

Within Groups 7905.05 226 34.98

Total 8484.89 228 2018 Field Trial

Table 2.17 below shows 50% heading date, plant height and 0-9 SB ratings for F3, F4, F9,

BC2F3 and BC3F2 selections evaluated at the RRS in 2018. As in previous trials, the resistant and

susceptible checks produced expected SB ratings. Ten selections in the F8 generation

(JODN/3/TDCN/SBNT//LSRR5/LMNT, 09DN157//TRP545/CL161, CTHL/SB2-3, CCCDR/PI

658335, CCDR//09DN/RUSH072, SB131/SB125, CL111/GSOR101021,

CCDR//09DN/RUSH072, WELLS/CANTORSB51//97URN128/96CR921, SB125/SB132)

showed good levels of resistance (SB ratings = 3) that were similar to previous trials in 2015,

2016, or 2017 at the RRS.

Several F3, F4 and BC2F3 and BC3F2 selections displayed apparent high levels of

resistance, desirable maturity, and plant height, but this early-generation material will require

additional field testing to confirm the 2018 results.

Table 2.17. Maturity, plant height and 0-9 SB ratings for F3, F4, F4 derived F9 and BC2F3, BC3F2 selections evaluated at the RRS, 2018.

Pedigree Generation 50%

Heading

Plant Height (cm)*

SB Rating (0-9)*

MCR010277 Inbred 102 90 3 TEQING Inbred 110 111 3 CCDR//CCDR/PI658327 BC2F3 103 100 4 CCDR//CCDR/PI658327 BC2F3 103 102 5


37


Heading

Plant Height (cm)*

SB Rating (0-9)*

CCDR//CPRS//CIAT 4/MCR010277 BC2F3 97 99 4 CCDR//CPRS//CIAT 4/MCR010277 BC2F3 97 106 4 CCDR//WELLS/CANTORSB51//97URN128/96CR921 BC2F3 99 97 5 CCDR//JODN/3/TDCN/SBNT//LSRR5/LMNT BC2F3 95 99 5 CCDR//JODN/3/TDCN/SBNT//LSRR5/LMNT BC2F3 95 103 4 CCDR//JODN/3/TDCN/SBNT//LSRR5/LMNT BC2F3 95 102 4 CCDR//JODN/3/TDCN/SBNT//LSRR5/LMNT BC2F3 95 101 3 CCDR//SB125/SB131 BC2F3 95 104 4 CCDR//SB125/SB131 BC2F3 105 103 3 CCDR//SB125/SB131 BC2F3 103 102 4 CCDR//SB125/SB131 BC2F3 103 102 5 CCDR//SB125/SB131 BC2F3 103 109 3 CCDR//CCDR/09DN/RUSH222 BC2F3 103 100 4 CCDR//RUSHSBR4/09125 BC2F3 103 101 4 CCDR//RUSHSBR4/09125 BC2F3 103 98 5 CCDR//RUSHSBR4/09125 BC2F3 101 93 5 CCDR//SB131/SB125 BC2F3 98 100 5 CTHL//WELLS/CANTORSB51//97URN128/96CR921 BC2F3 99 101 5 CTHL//WELLS/CANTORSB51//97URN128/96CR921 BC2F3 99 93 5 CTHL//WELLS/CANTORSB51//97URN128/96CR921 BC2F3 99 97 3 CTHL//WELLS/CANTORSB51//97URN128/96CR921 BC2F3 99 99 4 CTHL//WELLS/CANTORSB51//97URN128/96CR921 BC2F3 99 99 3 CTHL//WELLS/CANTORSB51//97URN128/96CR921 BC2F3 99 99 4 CTHL//JODN/3/TDCN/SBNT//LSRR5/LMNT BC2F3 95 95 4 CTHL//JODN/3/TDCN/SBNT//LSRR5/LMNT BC2F3 95 99 3 CTHL//JODN/3/TDCN/SBNT//LSRR5/LMNT BC2F3 95 101 3 CTHL//JODN/3/TDCN/SBNT//LSRR5/LMNT BC2F3 95 98 5 CTHL//JODN/3/TDCN/SBNT//LSRR5/LMNT BC2F3 95 100 5 CTHL//CTHL/RUSHSBR4 BC2F3 97 103 4 CTHL//SB125/SB131 BC2F3 101 103 4 CTHL//SB131/SB125 BC2F3 98 105 4 CTHL//CPRS/Oryzica Llanos 5 BC2F3 98 93 4 CTHL//RUSHSBR4/09125 BC2F3 103 100 4 CTHL//SB131/SB125 BC2F3 101 101 4 CTHL//SB125/SB131 BC2F3 101 108 4 CL161//09DN157//TRP545/CL161 BC2F3 100 100 4 CL161//CL161/PI 658314 BC2F3 100 101 4 15HB017/09DN/RUSH222 F3 98 93 4 15HB017/09DN/RUSH222 F3 98 100 4 15HB017/WELLS/CANTORSB51//97URN128/96CR921//CTHL F3 98 96 3 15HB017/CTHL/SB2-3 F3 96 101 4 15HB017/RUSHSBR4/09125 F3 99 89 4 15HB017/09DN157//TRP545/CL161 F3 101 91 4 15HB050/WELLS/CANTORSB51//97URN128/96CR921//CTHL F3 99 97 4


38


Heading

Plant Height (cm)*

SB Rating (0-9)*

15HB050/SB131/SB125 F3 101 95 4 15HB114/JODN/3/TDCN/SBNT//LSRR5/LMNT F3 95 98 4 15HB017/09DN157//TRP545/CL161 F3 95 103 3 15HB017/RUSHSBR4/09125 F3 100 98 4 15HB127/PI658327 F3 103 107 3 CCDR//09DN/RUSH072 F4 105 98 4 SB125/SB131 F4 103 103 4 CTHL//CTHL/PI 658320 (17SB 28-3) BC3F2 97 107 4 CTHL//CTHL/PI 658320 (17SB 29-4) BC3F2 97 111 3 CTHL//CTHL/PI 658320 (17SB 31-4) BC3F2 97 106 3 CTHL//CTHL/PI 658335 (17SB 37-1) BC3F2 97 94 5 CTHL//CCCDR/PI 658335 (17SB 48-1) BC3F2 106 112 3 CTHL//CTHL/SB2-3 (bulk) BC3F2 99 100 5 CTHL//CTHL/SB2-3 (17SB 53-2) BC3F2 99 102 5 CTHL//CTHL/SB2-3 (17SB 55-2) BC3F2 99 93 5 CTHL//CTHL/SB2-3 (17SB 56-2) BC3F2 99 98 4 CTHL//CTHL/SB2-3 (17SB 57-1) BC3F2 99 100 4 CL152//CL152/RUSH C99-1166 (17SB 70-4) BC3F2 99 90 5 CL152//CTHL/SB2-3 (17SB 85-1) BC3F2 99 101 4 CL152//CL152/PI 658327 (bulk) BC3F2 99 103 4 CL152//CL152/ PI 658327 (17SB 91-3) BC3F2 99 93 4 CL152//CL152/ PI 658327 (17SB 93-1) BC3F2 99 94 5 CL152//CL152/09DN157//TRP545/CL161 (17SB 94-7) BC3F2 99 95 4 CL152//CL152/09DN157//TRP545/CL161 (17SB 94-8) BC3F2 99 101 3 CL152//CL152/PI 658320 (17SB 97-4) BC3F2 99 96 5 CL152//CL152/PI 658320 (17SB 98-1) BC3F2 99 94 4 CL152//CL152/PI 658320 (17SB 101-2) BC3F2 99 100 5 CL152//CL152/PI 658320 (bulk) BC3F2 99 103 5 CL151//CL151/LSRR5 (bulk) BC3F2 101 90 5 CL151//CL151/C99-1166 (17SB 114-2) BC3F2 101 89 5 CL151//CL151/09DN157//TRP545/CL161 (17SB 132-1) BC3F2 101 88 4 CL151//CL151/09DN157//TRP545/CL161 (17SB 132-7) BC3F2 101 108 5 CL151//CL151/09DN157//TRP545/CL161 (17SB 133-1) BC3F2 101 99 4 CL151//CL151/PI 658320 (bulk) BC3F2 101 104 5 CL151//CL151/PI 658320 (17SB 136-2) BC3F2 101 106 4 CL151//CL151/PI 658320 (17SB 138-2) BC3F2 101 105 4 CL151//CL151/PI 658320 (17SB 139-1) BC3F2 101 100 3 CL151//CL151/PI 658320 (17SB 140-4) BC3F2 101 97 4 CL151//CL151/PI 658320 (17SB 144-1) BC3F2 101 100 5 CL151//CL151/PI 658320 (bulk) BC3F2 101 107 5 CL151//CTHL/SB2-3 (bulk) BC3F2 101 98 5 CL151//CTHL/SB2-3 (17SB 162-1) BC3F2 101 94 4 CL111//CL111/09DN157//TRP545/CL161 (17SB 195-2) BC3F2 95 91 4 CL111//CL111/PI 658335 (17SB 201-5) BC3F2 95 98 5


39


Heading

Plant Height (cm)*

SB Rating (0-9)*

CL111//CL111/PI 658335 (17SB 208-4) BC3F2 95 94 6 CL111//CTHL/SB2-3 (bulk) BC3F2 95 99 4 CL111//CTHL/SB2-3 (17SB 221-5) BC3F2 98 91 5 CL111//CTHL/SB2-3 (17SB 223-4) BC3F2 98 102 4 CL111//CL111/PI 658320 (17SB 235-15) BC3F2 98 102 5 CTHL//CTHL/LSRR5 (17SB 15-3) BC3F2 93 94 3 CTHL//CTHL/PI 658320 (bulk) BC3F2 98 103 5 CTHL//CTHL/PI 658320 (17SB 29-4) BC3F2 98 104 4 CTHL//CCCDR/PI 658335 (17SB 50-3) BC3F2 96 94 5 CTHL//CTHL/SB2-3 (bulk) BC3F2 97 99 4 CTHL//CTHL/SB2-3 (17SB 53-4) BC3F2 97 100 3 CTHL//CTHL/SB2-3 (17SB 54-4) BC3F2 97 106 4 CTHL//CTHL/SB2-3 (17SB 55-4) BC3F2 97 100 5 CL152//CTHL/SB2-3 (17SB 85-5) BC3F2 104 101 4 CL152//CTHL/SB2-3 (17SB 87-2) BC3F2 104 99 5 CL152//CL152/PI 658327 (bulk) BC3F2 104 102 3 CL152//CL152/PI 658327(17SB 90-3) BC3F2 104 101 3 CL152//CL152/PI 658327 (17SB 92-3) BC3F2 104 102 5 JODN/3/TDCN/SBNT//LSRR5/LMNT F9 95 101 4 LSBR5 Inbred 104 84 3 09DN157//TRP545/CL161 F9 102 86 3 CTHL/SB2-3 F9 110 98 4 CCDR/PI 658335 F9 114 81 3 PI 658327 Inbred 103 83 3 PI 658320 Inbred 99 103 3 PI 658335 Inbred 103 97 3 CCDR//09DN/RUSH072 F9 99 101 4 SB131/SB125 F9 105 97 3 CTHL/SB2-3 F9 97 96 5 CTHL/SB2-3 F4 97 104 5 CL111/GSOR101021 F4 95 90 5 CCDR//09DN/RUSH072 F9 99 99 5 WELLS/CANTORSB51//97URN128/96CR921 F9 99 97 3 SB131/SB125 F9 107 93 3 SB125/SB132 F9 107 101 3 CL152 Inbred 100 97 6 CL111 Inbred 94 84 9 CL151 Inbred 95 91 7 CL153 Inbred 95 85 7 CTHL Inbred 97 93 7 CCDR Inbred 99 96 6 LSD 0.05 4.80 7.90 1.10 Std. dev 3.52 5.80 0.99

*Mean values from 3 replications, 3 rows per replication; red cells – resistant check varieties; yellow cells – susceptible check varieties

40

Table 2.18. Analysis of variance on 50% days to heading of the selected SB resistant lines and resistant and susceptible checks from the 2018 SB field evaluation trial, H. Rouse Caffey Rice Research Station, Crowley, Louisiana.


Between Groups 133.30 2 66.65 5.76 0.004 3.07

Within Groups 1503.53 130 11.57

Total 1636.83 132 Table 2.19. Analysis of variance of on SB disease rating of the selected SB resistant lines and resistant and susceptible checks from the 2018 SB field evaluation trial, H. Rouse Caffey Rice Research Station, Crowley, Louisiana.


Between Groups 133.30 2 66.65 5.76 0.004 3.066

Within Groups 1503.53 130 11.57

Total 1636.83 132 Table 2.20. Analysis of variance on plant disease rating of the selected SB resistant lines and resistant and susceptible checks from the 2018 SB field evaluation trial, H. Rouse Caffey Rice Research Station, Crowley, Louisiana.


Between Groups 360.59 2 180.30 5.74 0.004 3.07

Within Groups 4082.61 130 31.40

Total 4443.20 132

Two years of field trials at the RRS showed that the seven selected sheath blight lines

were virtually identical as a group for sheath blight resistance compared to the two donor lines

MCR and Teqing (Table 12.21). Mean sheath blight score of the selected lines at 3.3 was nearly

identical to the 3.5 average of the two donor lines. In contrast, the six known susceptible checks

displayed sheath blight scores of 6 to 8 that were higher than the seven selections and donors

41

based on LSD0.05. As a group, the seven selected SB lines showed improvement for several key

agronomic traits in 2016 and 2017 trials vs. the two known resistant lines MCR and Teqing

(Table 12.21). For example, heading dates for the selected lines were 15 to 25 days vs. the

resistant donor lines in both inoculated and non-inoculated plots. Two of the SB selections

(Catahoula//Cocodrie/MCR, PI 658335) were within two to six days of 50% heading vs. the

earlier maturing MCR donor. Similarly, mean plant height of the selected resistant material was

eight cm shorter compared to the two donor lines across all plots.

Ability of the selected material, donors, and susceptible recipient lines to produce grain

under disease and disease-free conditions was determined by evaluation and comparison of grain

yields in inoculated and non-inoculated plots (Table 2.21). Resistant donor Teqing produced

relatively high grain yields compared to all lines tested in both inoculated and non-inoculated

plots, even though its own percent yield reduction was surprisingly high at 21%. Teqing has been

used extensively as a donor for germplasm development as shown by the pedigrees of MCR and

three of the SB selected lines evaluated in this study. Mean percent yield reduction for the seven

selected lines at 13% was comparable to 17% for the two donor lines, although the range for the

selections varied substantially from 4% to 30%. Selections PI 658320 and PI 658335 were noted

for relative high grain yields in both disease and disease-free environments. The two selections

also produced higher grain yield than the commercial susceptible checks in inoculated plots.

PI658335 produced similar or higher yield than four of the checks under disease-free conditions.

These results underscore the importance of evaluating and selecting breeding material under both

disease and disease-free conditions.

Correlation analyses for days to heading, disease score, plant height and grain weight of

the two resistant checks, the 7 selected SB lines and the six susceptible checks are shown in

42

(Table 2.22). The results showed that days to heading was negatively correlated with disease

score. In other words, later-maturing lines were correlated with reduced amount of disease

caused by R. solani infection. This result has been reported previously in the literature. (Lee and

Rush, 1983). Delayed maturity was also associated with increased plant height and grain yield

for the material evaluated in this study.

Plant height was positively correlated to the days to 50% heading as observed with the

plants evaluated. The shorter maturity time the plant is, the shorter in height as observed in the

susceptible checks, while the taller the plants showed longer the maturity as observed in the SB

resistant plants and the resistant check. The mean difference in plant height between the SB lines

was 6 cm longer than the susceptible check of 90 cm. Moreover, plant height was strongly

correlated with the observed disease response. The tall the plants were resistant in the selected

43

Table 2.21. Yield reduction of the selected resistant lines from 2016 and 2017 (combined data).

1 Disease Score: 1 = no disease, 9 = dead plant 4 Grain Wt. (gm)/0.5 m2 = Mean rough rice, of 3 reps, 0.5m2/plot

2 Days to 50% heading = days from planting to 50% heads emerged. 5 % Yield Reduction = [(GW uninoculated-GW inoculated)/GW inoculated]*100 3 Plant height = distance in cm from soil to tip of longest panicle.

Inoculated Non-inoculated

Line Pedigree Generation Disease Score (0-9)2

Days to 50%

heading1

Plant height (cm)3

Grain Wt. (gm) / 0.5 m2

Disease Score (0-9)2

Days to 50%

heading

Plant height (cm)3

Grain Wt. (gm) / 0.5 m2

% Yield Reduction5

% Yield Reduction (MEAN)

MCR010277 LSBR-5/Lemont//Katy/3/ Cypress/Teqing

Inbred 4 86 98 163 0 86 99 187 13 17

Teqing Teqing Inbred 3 113 111 192 0 113 110 243 21

(LSBR-5) LSBR-5 Inbred 3 95 95 123 0 97 90 139 12 13

09DN157//TRP545/CL161 09DN157//TRP545/CL161 F7 3 90 92 152 0 90 91 161 6

Catahoula//Cocodrie/MCR Catahoula//Cocodrie/MCR F7 4 98 91 144 0 98 93 185 22

Cocodrie/PI 658335 Cocodrie/PI 658335 F7 3 90 93 115 0 98 97 164 30

PI 658327 C99-1166 LSBR-5/LMNT/TQNG/3/CCDR/4PSCL

Inbred 3 90 96 155 0 90 96 176 12

PI 658320 C98-974 CPRS/AZMIL Inbred 4 88 105 178 0 90 104 185 4

PI 658335

COO-1700 LSBR5/LMNT//TQNG/LSBR5/LMNT/3/H4CODF//NTA(03-10993-11019)

Inbred 3 92 100 191 0 92 98 199 4

CL152 CL152 Inbred 6 80 95 141 0 82 91 187 25 26

CL111 CL111 Inbred 7 74 88 141 0 75 87 197 29

CL151 CL151 Inbred 7 77 89 145 0 79 89 204 29

CL153 CL153 Inbred 6 76 84 126 0 78 89 152 17

Catahoula Catahoula Inbred 8 76 96 141 0 79 98 210 33

Cocodrie Cocodrie Inbred 8 77 89 131 0 80 80 177 26

L.S.D.0.05 1.22 10.78 9.24 36.24

0 11.08 9.68 39.58 21.45

C.V. 0.41 0.12 0.73 0.16 0 0.12 0.08 0.14 3.88

S.E.mean

0.51 2.74 1.77 6.02 0 2.64 1.9 6.7 0.6

44

SB lines with a mean height of 96 and with a disease score range from 3-5 that was similar to the

disease resistant checks. The susceptible checks on the other hand, were shorter than the SB

resistant lines with a mean height 90 cm that showed disease ratings of 6-8. My findings

confirmed those of Sharma et al. (2009) in families derived from a cross between two

tropical japonica U.S. rice cultivars, Rosemont (semi-dwarf, SB susceptible) and Pecos (tall, SB

resistant). The families were evaluated for disease reactions, plant height (PH), and heading date

(HD) in replicated field trials for 2 years and genotyped with 149 simple sequence repeat

markers. Correlation analysis between SB ratings with PH and HD showed that both agronomic

traits were significantly correlated with SB resistance.

Grain weight was moderately correlated to days to 50% heading as observed within the

plants evaluated; however, it was negatively correlated to the disease score. The correlation

value of disease score to grain weight was -0.37, considered as a relatively weakly correlation.

On the contrary, plant height was highly correlated to grain weight. The selected SB resistant

lines were comparable to the heights of the resistant checks, with plant height mean of 6 cm

taller than the average height of the susceptible check. The grain weight of SB resistant lines and

the resistant checks ranged from 151 to 178 grams while the susceptible checks exhibited a mean

grain weight of 138 grams. This finding was similar to the report of Zhang et al. (2017) who

identified a novel MYB-like transcription factor OsMPH1 (MYB-like gene of Plant Height 1)

involved in the regulation of plant height in rice. Overexpression of OsMPH1 lead to increased

plant height and grain yield in rice. The plant height - grain weight correlation was also observed

in other crops such as sorghum. In a report by the Texas Sorghum Producers (2018), plant height

was positively correlated with grain yield as observed for every production region in Texas

(http://texassorghum.org/hybrid-selection-plant-height-and-grain-yield.html).

45

Table 2.22. Correlation analysis of days to heading, disease score, plant height and grain weight

of the resistant check, selected sheath blight lines and the susceptible checks.

Morphological traits

Days to 50%

heading

Disease score

(0-9)

Plant height

(cm)

Grain weight

(gm)

Days to 50% heading 1 -0.80 0.70 0.50

Disease Score (0-9) 1 -0.50 -0.37

Plant height (cm) 1 0.78

Grain weight (gm) 1

*a=0.05

2.4. References

Blanche SB, Linscombe SD, Sha X, Bearb KF, Groth DE, White LM and Harrell DL (2009)

Registration of ‘Catahoula’ rice. Crop Science Vol. 3 No. 2, p. 146-149.

doi:10.3198/jpr2008.11.0677crc.

Blanche SB, Sha X, Harrell DL, Groth DE, Bearb KF, White LM and Linscombe, SD (2010)

Registration of ‘CL151’ rice. Crop Science Vol. 5 No. 2, p. 177-180.

doi:10.3198/jpr2010.05.0245crc.

Dai Z, Li A, Huang L, Liu G, Zhou C, Zhang H (2006) Utilization of an elite rice germplasm-

Yangdao 6 with high combining ability created by 60Co γ-irradiation. Acta Agriculturae

Nucleatae Sinica. ISSN 1000-8551 v. 20(2); p. 83-86.

Famoso AN, Oard JH, Harrell DL, Groth DE, Bearb KF, White III LM, Zaunbrecher RE and

Linscombe SD (2016) Registration of ‘CL153’ rice. Crop Science Vol. 11 No. 1, p. 38-

41. doi:10.3198/jpr2016.04.0023crc.

Groth DE, Hollier CA, Olaya G, Tally A, Lanclos D and Zaunbrecher J (2013) Management of

QoI-Resistant Rhizoctonia solani, the Causal Agent of Rice Sheath Blight, in Southern

Louisiana. In: Fungicide Resistance in North America, Second Edition, APS Press,

Minneapolis, MN.

Johnston TH and Henry SE (1965) Registration of ‘Northrose’ rice. Crop Science Society of

America 5:285.

Johnston TH, Webb BD, and Evans KO (1968) Registration of ‘Starbonnet’ rice. Crop Science

Society of America. Received March 6, 1968.

Johnston TH, Webb BD, and Evans KO (1973) Registration of ‘Nortai’ rice. Crop Science

Society of America. Received September 7, 1973.

46

Marchetti M, Bollich C, Webb B, Jackson B, McClung A, Scott J, Hung H (1998). Registration

of ‘Jasmine’85 rice. Crop Science Vol.38 pp. 895-896.

McClung AM, Fjellstrom RG, Bergman CJ, Bormans CA, Park WD and Marchetti MA (2004)

Registration of ‘Saber’ rice. Crop Sci. 44:493.

Moldenhauer KAK, Lee FN, Norman RJ, Helms RS, Wells BR, Dilday RH, Rohman PC,

Marchetti MA (1990) Registration of ‘Katy’ rice. Crop Science Vol.30 No.3 ref.6

pp.747-748

Nelson JC, Oard JH, Groth D, Utomo HS, Jia Y, Liu G, Moldenhauer KAK, Correa-Victoria FJ,

Fjellstrom RG, Scheffler B, Prado GA (2011) Sheath-blight resistance QTLS in japonica

rice germplasm. Euphytica DOI 10.1007/s10681-011-0475-1.

Linscombe SD, Jodari F, Bollich PK, Groth DE, White III LM, Chu QR, Dunand RT, Sanders

DE (2000). Registration of `Cocodrie' rice. Crop Science 40(1):294.

doi:10.2135/cropsci2000.0007rcv.

Oard JH, Harrell DL, Groth DE, Bearb KF, White III LM and Linscombe SD (2013)


doi:10.3198/jpr2013.06.0035crc.

Oard JH, Harrell DL, Groth DE, Bearb KF, White III LM and Linscombe SD (2013)


doi:10.3198/jpr2013.06.0029crc.

Pan XB, Rush MC, Sha XY, Xie QJ, Linscombe SD, Stetina SR, Oard JH (1999) Major gene,

nonallelic sheath blight resistance from the rice cultivars Jasmine 85 and Teqing. Crop

Sci 39:338–346.

Rice Coordinated Agricultural Project (RiceCAP), USDA ARS and University of Arkansas,

Division of Agriculture. (http://www.uark.edu/ua/ricecap).

Rush MC, Groth DE., Sha X (2011) Registration of 25 sheath blight disease resistant germplasm

lines with good agronomic traits. Journal of Plant Registrations, Vol.5 No.3; p. 400-402.

Wasano K (1988) The resistance to the rice diseases of bacterial leaf blight (Xanthomonas campestris pv. Oryzae) and sheath blight (Rhizoctonia solani), and some problems in

breeding of disease resistance of crops. In “Recent Advances in Research on Plant

Breeding vol. 30” Japanese Society of Breeding (ed.), Yokendo, Tokyo. p. 103-121.

Xie H, Zheng J, Zhang S (1987) Rice breeding for the hybrid combination of Shanyou 63 and its

restorer line Minghui 63. Fujian J Agric Sci 2(1):32–38 (in Chinese).

Xie F and Zhang J (2018) Shanyou 63: An elite mega rice hybrid in China. Rice 11:17;

doi.org/10.1186/s12284-018-0210-9.

47

Xie Q, Linscombe SD, Rush MC (1992) Registration of LSBR-33 and LSBR-5 sheath light-

resistant germplasm lines of rice. Crop Science 32: 507; doi:10.1094/Phyto-06-10-0151

Xie QJ, Rush MC, Cao J (1990) Somaclonal variation for disease resistance in rice (Oryza sativa L.). Pest Management in Rice. 491-509. B.T.Grayson, M.B.Green, and L.G.Copping

(Ed.) Elsevier Applied Science. London.

Zhang Y, Yu C, Lin J, Liu J, Liu B, Wang J, Huang A, Li H, Zhao T (2017) OsMPH1 regulates

plant height and improves grain yield in rice. PLoS One 2017; 12(7): e0180825.

48

CHAPTER 3. IDENTIFICATION AND EVALUATION OF NON-SYNONYMOUS SNPs MARKERS FOR SHEATH BLIGHT

RESISTANT GERMPLASM 3.1. Introduction

Resistance breeding against sheath blight disease has achieved limited success in part due

to existence of only a few highly resistant accessions (Eizenga et al. 2002; Wang et al. 2011).

Teqing, Jasmine 85, Minghui 63, WSS2, and Tetep are some of the lines that have been used as

donors to develop near-isogenic lines (NILs) or chromosome segment substitution lines (CSSLs)

to identify QTLs that can measurably improve resistance (Li et al. 1995; Pan et al. 1999; Zou et

al. 2000; Han et al. 2002; Sato et al, 2004; Pinson et al. 2005; Liu et al. 2009;

Channamallikarjuna et al. 2010). Moreover, germplasm stocks and associated mapping

populations for breeding and study of sheath blight have been released in the U.S. for public use

(Chu et al. 2006; Groth et al. 2007; Pinson et al. 2008, Groth et al. 2011; Rush et al. 2011; Jia et

al. 2012; Jia et al. 2015). In cooperation with the USDA-funded RiceCAP project

(http://www.uark.edu/ua/ricecap), the SB2 mapping population was developed as a resource to

map QTLs for sheath blight resistance and other traits (Chu et al. 2006). SB2 consists of 325

true-breeding doubled-haploid (DH) lines from the Genetic Stocks Oryza Collection (GSOR

accessions 200001 to 200325) developed from susceptible parent Cocodrie (PI 606331) and the

moderately-resistant breeding line MCR010277 (PI 641932).

Resistance to rice sheath blight is considered a quantitative trait controlled by multiple

genes of small effect referred to as quantitative trait loci (QTL) (Zhou et al. 2000; Pinson et al.

2005; Jia et al. 2009). Li et al. (1995) identified six QTL contributing to sheath blight-resistance

in two years of field evaluation using an F4 bulked population from a cross between the

susceptible variety Lemont and the resistant variety Teqing. The QTL Qsbr3a detected between

49

markers RG348 and RG944 on rice chromosome three exhibited the largest effect. Pan et al.

(1999) identified three QTLs for sheath blight resistance on chromosomes 2, 3, and 7 using an F2

population derived from a cross between resistant variety Jasmine 85 and Lemont by bulk

segregant analysis. In the following year, Zou et al. (2000) reported six QTL conferring sheath

blight resistance on chromosomes 2, 3, 7, 9 and 11 using the same Jasmine 85/Lemont F2

population.

Various populations, including segregating F2 populations, double haploids (DHs) and

recombinant inbred lines (RILs), have been developed to identify QTLs associated with sheath

blight resistance on rice chromosomes 2, 3, 5, 7, 9 and 11 (Pan et al. 1999; Zou et al. 2000; Han

et al. 2002; Kunihiro et al, 2002; Che et al. 2003; Sato et al. 2004; Pinson et al. 2005; Tan et al.

2005; Liu et al. 2009). Han et al. (2002) identified two sheath blight resistance QTLs on

chromosomes 5 and 9 using a RIL population derived from Zhenshan 97B and Minghui 63

parents. A DH population derived from a cross between Zhaiyeqing 8 and Jingxi 17, Kunihiro et

al. (2002) detected four sheath blight QTLs on chromosomes 2, 3, 7 and 11. The QTL, qSBR-7,

detected between the markers RG511 and TCT122 on chromosome 7 showed the largest effect.

Sato et al. (2004) identified two sheath blight QTLs on chromosomes 3 and 12 using a BC1F1

population derived from a cross of Hinohikari/WSS2//Hinohikari. The two QTLs identified

explained 30% of the phenotypic variation, and the resistance alleles were derived from the

resistant parent WSS2.

Pinson et al. (2005) confirmed the locations and effects of six sheath blight–resistance

QTLs that were identified by previous researchers and detected eight new loci using a RIL

population derived from the Lemont/Teqing cross. Xie et al. (2008) performed a QTL analysis

using reciprocal introgression line populations derived from Lemont/Teqing evaluated in 2006–

50

2007. A total of 10 main-effect QTLs and 13 epistatic QTLs were mapped using data obtained

from different years and genetic backgrounds. They also verified six main effect QTLs

identified in 2006 that were successfully detected in 2007, suggesting stable expression across

years.

Li et al. (2009) identified sheath blight QTLs using different introgression lines

containing chromosome segments from Tarom Molaii and Binam in IR64 and Teqing

backgrounds. In the same year, Liu et al. (2009) identified 10 QTLs on chromosomes 1, 2, 3, 5,

6, and 9 using an F5 RIL population derived from Lemont/Jasmine 85 by measuring inoculated

seedlings using micro chamber and mist-chamber assays under greenhouse conditions.

Recent research has identified certain “large effect” QTLs in progeny from different

japonica x indica crosses. For example, 12 QTL mapping studies, as summarized in Zuo et al.

2014a, identified a large region of ~ 2 Mbp associated with sheath blight resistance at the bottom

of the long arm of chromosome 9. A subsequent fine mapping study reported a substantially

smaller region (146 kb) in the same chromosomal region (Zuo et al. 2014b).

Recent advances in biotechnology, genome research and molecular marker applications

with conventional breeding practices have proved beneficial in some cases for crop improvement

(Moose and Mumm, 2008). For example, using RL-SAGE and microarray technologies, Venu et

al. (2007) isolated RNA isolated from R. solani-infected leaves of Jasmine 85. A large

percentage (70%) of the genes responsive to sheath blight fungal infection were located in

known sheath blight resistance QTL regions. Zhao et al. (2008) identified numerous defense-

related genes induced by R. solani through the suppression subtractive hybridization method.

However, none of the candidate genes reported in the literature using these technologies has been

validated in subsequent studies.

51

Silva et al. (2012) previously identified 333 candidate nsSNPs on 11 chromosomes

associated with sheath blight resistance using whole genome sequencing. Yamid Sanabria of Dr.

Oard’s lab (unpublished results) evaluated certain selected candidate SNPs associated with

sheath blight resistance from the work of Silva et al. (2012) by using the RiceCAP SB2 mapping

population and a panel of elite varieties with known reaction to R. solani. Ten each of extreme

resistant and susceptible sheath blight lines from the SB2 mapping population were used to

evaluate 136 candidate nsSNPs that were ranked by ANOVA based on phenotypic and genotypic

profiles. SNPs in reported genomic regions for sheath blight resistance were identified including

eight markers located on chromosomes 6, 8, 9, and 12 that were used in a marker-assisted

backcrossing strategy by crossing seven different resistant lines to four susceptible U.S.

commercial varieties. A total of 45 doubled-haploid (DH) lines were developed from 28 BC2F1

individuals containing different combinations of selected SNPs.

One promising approach for studying regulatory mechanisms and signaling networks of

plant defense responses and identifying the genes involved in disease response is RNA

sequencing (Wise et al. 2007). A microarray study was recently conducted by Yuan et al. (2018)

to understand the mechanisms underlying YSBR1 resistance to R. solani compared to the R.

solani-susceptible Lemont cultivar. They observed dynamic and different responses of the two

rice cultivars during R. solani infection. YSBR1 exhibited stronger and earlier transcriptional

response to R. solani than Lemont. Genes that encode cell wall-modifying and glycosyl-

degrading enzymes or anti-microbial proteins were specifically induced in YSBR1. MapMan

analysis also revealed that more differentially expressed genes related with cell wall, β-

glucanases, respiratory burst, phenylpropanoids and lignin were highly induced by R. solani in

YSBR1 than in Lemont.

52

Dr. Pankaj Jaiswal at Oregon State University has carried out an RNA-Seq experiment in

cooperation with Dr. Oard’s laboratory on sheath blight (unpublished results). The SB

susceptible variety, Cocodrie (PI 606331) and the resistant line MCR010277 (PI 641932) was

inoculated with R. solani under greenhouse condition at LSU. Leaf samples were collected at 0,

1, 3, 5 hours post-inoculation, and subjected to RNA-Seq analysis by Jaiswal’s laboratory. Three

genes were postulated to be involved in the sheath blight defense response: chitin elicitor binding

protein (CEBiP), chitin elicitor receptor kinase (CERK), and a wall-associated kinase (WAK91).

A non-synonymous SNP in WAK91 on chromosome 9 was identified as a candidate marker for

sheath blight resistance breeding.

Hence, this study will identify and evaluate non-synonymous SNP markers for sheath

blight resistance germplasm for southern US environments through development of allele-

specific DNA markers identified by SNP databases and selective genotyping.


3.2.1. DNA extraction and polymerase chain reaction

Leaf tissue of 15 lines which inclues the 7 best line from the field evaluation: RUSH

C99-1166 (LSBR5), 09DN157//TRP545/CL161, CTHL/SB2-3, CCDR/PI 658335, PI 658327, PI

658320, PI 65833; 6 susceptible checks, CL111, CL151, CL152, CHENEIRE, COCODRIE and

CTHL and 2 resistant checks, TEQING and MCR010277 was collected 40 to 50 days after

planting and oven-dry at 50°C for three days. DNA isolation was conducted using the modified

CTAB method described by Lorieux (2002); and Murray and Thompson (1980). Briefly,

approximately 150 mg of oven-dried leaf tissue was ground using the Mini-Bead Beater by

Biospec followed by addition of pre-heated 480 μL of extraction buffer at 74°C. The extraction

buffer is a mixture of 20 mM EDTA, 100 mM Tris, 1.4 M NaCl, 1% PEG 6000, 2% MATAB

53

and 0.5% sodium bisulfite. The mixture was incubated in water bath for 25 to 30 min at 74°C.

Subsequently, 480 μL chloroform:isoamyl (24:1) was added, mixed slowly by par inversion for 5

min, and centrifuged at 4000 rpm for 15 min at room temperature. The supernatant was

precipitated with 270 μL isopropanol, mixed by hand inversion until an evident formation of a

thread was visible and stored at -20 °C for at least 15 min and re-centrifuged at 4000 rpm for 15

min. The DNA pellets were obtained and washed with 100 μL ethanol and centrifuged for 4000

rpm for 10 min. The supernatant was again discarded and the remaining pellet was air-dried and

resuspended to 50 μL 10% TE buffer. The isolated DNA was stored in -20°C for future use.

A 10 uL reaction mixture was prepared for polymerase chain reaction (PCR), containing

3 μL of DNA template (20 to 30 ng/μL), 3 μL REDTaq Ready Mix from Sigma Aldrich (20 mM

Tris-HCl (pH 8.3), 100 mM KCl, 3 mM MgCl2, 0.002 % gelatin, 0.4 mM dNTP mix (dATP,

dCTP, dGTP, TTP), stabilizers and 0.06 unit/mL of Taq DNA Polymerase), 0.2 μL each of the

forward and reverse primers (20 μM) and 3.6 μL sterile distilled water. Sequences of the primer

pairs are shown in Appendix Table 3.2. The PCR conditions were as follows: 95 °C denaturation

for 3 min, followed by 95 °C for 30 sec, 62 °C for 30 sec, 72 °C for 30 sec, repeat previous three

steps for 32X, and 72 °C for 5 min. The final holding temperature was set at 4 °C. Amplified

PCR products were visualized on a 2% agarose gel stained with ethidium bromide.

3.3. Results

Genotyping of 29 polymorphic nsSNP on chromosomes 2, 4, 6, 8, 9 and 12 was carried

out using the selected SB lines from the 2014 SB field evaluation trial at RRS plus the 2 resistant

checks (Teqing and MCR010277), and 6 susceptible cultivars (Catahoula, Cocodrie, CL111,

CL151, and CL152). These lines were selected on SB resistance, plant type, plant height and

maturity. The selected resistant lines are from the selections from 2013 field evaluation at RRS

54

for SB resistance (Table 2.1). These materials were genotyped using non-synonymous SNPs

markers developed previously by Yamid Sanabria in Dr. Oard’s laboratory (Sanabria, 2015).

These nsSNPs markers were identified and developed by comparing DNA sequences of Lemont

and Teqing at http://oryzasnp.org/iric-portal/. Initially, a subset of markers based on R2 value

were used to genotype the selected lines (Appendix Table 3.1). These markers are

representatives of the QTL markers associated with sheath blight resistance that were previously

published: QTLs on chromosomes 2, 6, 8, 9 and 12. LOC_Os09g32860, LOC_Os09g37800,

LOC_Os12g13100, LOC_Os02g34850, LOC_Os06g13040, LOC_Os06g22460 and

LOC_Os08g20020 are the markers identified (Table 3.1).

Genotyping of the best lines including 2 resistant cultivars, Teqing and MCR010277, and

6 susceptible cultivars: 3 conventional varieties, Catahoula, Cocodrie, and Mermentau and 3

Clearfield hybrids, CL111, CL151, and CL152, showed polymorphism between the resistant and

the susceptible cultivars (Table 3.1). Teqing and MCR010277 are varieties known to be

moderately resistant to sheath blight under field conditions. Genotyping results of the resistant

Teqing and MCR010277 showed the resistant allele across the markers tested. The susceptible

check cultivars, Catahoula, Cocodrie, Mermentau, CL111, CL151, and CL152, on the other

hand, showed the susceptible allele as expected. Although susceptible varieties CL111 and

Mermentau were showing some resistant alleles, the presence of few resistant alleles would not

give enough resistance to these cultivars against the disease.

Likewise, each of the selected resistant SB lines showed the resistant allele/s in different

genotypic profiles. Accumulation of resistant alleles in the best SB lines for SB resistance is

evident. One of the selected line, CCDR/SB2-174 cross with SB score of 6, contained 18

55

resistant alleles including 8 out 8 from chromosome 12, 3 from chromosome 9, 4 from

chromosome 6 and 3 from chromosome 4 (Table 3.1). Another line,

CCDR//CIAT8/MCR010277 showed 14 resistant alleles including 2 from chromosomes 2, 3

from chromosome 4, 3 from chromosome 6 and 6 out of 10 from chromosome 9. For line

CCDR//09DN/RUSH072, a combination of resistant alleles from chromosomes 4 and 12 was

observed; for CIAT7/MCR010277 line, the resistant alleles were from 3 from chromosomes

56

Table 3.1. SNP genotypes of selected resistant and susceptible lines from 2014 SB field evaluation plots, RRS, Crowley, Louisiana.

*Markers identified from the ranking of nsSNPs markers using their R2 value; fuschia; resistant varieties; blue: SB selected lines; green: susceptible varieties; red: resistant nsSNP; yellow: susceptible nsSNP.

PEDIGREE

Dise

ase

Rat

ing

(0- 9

) Chr. 2 Chr. 4 Chr. 6 Chr. 8 Chr. 9 Chr. 12

LOC

_Os0

2g34

490

LOC

_Os0

2g34

850*

LOC

_Os0

4g10

460

LOC

_Os0

4g15

650

LOC

_Os0

4g20

680

LOC

_Os0

6g13

040*

LOC

_Os0

6g22

020

LOC

_Os0

6g22

460*

LOC

_Os0

6g28

124

LOC

_Os0

8g19

694

LOC

_Os0

8g20

020*

LOC

_Os0

9g32

860*

LOC

_Os0

9g34

180

LOC

_Os0

9g36

900

LOC

_Os0

9g37

590

LOC

_Os0

9g37

800*

LOC

_Os0

9g37

880

LOC

_Os0

9g38

700

L OC

_Os0

9g38

850

LOC

_Os0

9g38

970

LOC

_Os0

9g39

620

LOC

_Os1

2g06

980

LOC

_Os1

2g07

950

LOC

_Os1

2g09

710

LOC

_Os1

2g10

180

LOC

_Os1

2g10

330

LOC

_Os1

2g10

410

LOC

_Os1

2g13

100*

LOC

_Os1

2g15

460

MCR010277 3.5 R R R R R R R R R R R R R R R R R R R R R R R R R R R R R

TEQING 3.5 R R R R R R R R R R R R R R R R R R R R R R R R R R R R R

RUSH C99-1166 4 S S S S S S S S S S S S S S S S S S S S S R R S S S S S S

PI658327 4 S S S S S S S S S S S S S S S S S S S S S S S S S S S S S

WELLS/CANTORSB51//97URN 4 S S S S S S S S S S S S S S S S S S S S S S S S S S S S S

JODN/3TDCN/SBNT//LSRR5/ 4 S S S S S S S S S S S S S S S S S S S S S S S S S S S S S

09DN/RUSH222//SBR174 4 S S S S S S S S S S S S S S S S S S S S S S S S S S S S S

CIAT7/MCR010277 4 S S S S S S R R R S S S S S S S S S S S R S S S S S S S S

CCDR//CIAT8/MCR010277 4 R R R R R S R R R S S S S R R S R R R R S S S S S S S S S

CCDR//09DN/RUSH072 5 S S S R R R S S S S S S S S S S S S S S S R R S S S S S S

PI658321 5 S S S S S S S S S S S S S S S S S S S S S S S S S S S S S

09SB131-1/SB125-1 6.5 S S R R R S S S S S S S S S S S S S S S S R R R R R R S S

CCDR/SB2-174 6 S S R R R R R R R S S R R R S S S S S S S R R R R R R R R

GSOR101019 6 S R S S S S S S S S S S S S S S S S S S S S S S S S S S S

CATAHOULA 8 S S S S S S S S S S S S S S S S S S S S S S S S S S S S S

COCODRIE 8 S S S S S S S S S S S S S S S S S S S S S S S S S S S S S

CL152 8 S S S S S S S S S S S S S S S S S S S S S S S S S S S S S

CL111 8 S S S S S S S S S S S S S S S S S S S S S S S S S S S S S

MERMENTAU 8 S S S S S S R S S S S S S S S S S S S S S S S S S S S S S

CL151 8 S S S S S S S S S R R S S S S R S S S S S S S S S S S S S

57

6 and 1 from chromosome 9. For RUSH C99-1166 (‘LSBR5’) and GSOR101019 lines however,

the resistant alleles are from chromosomes 9 and 2 only. Finally, there are lines (PI658327,

PI658321, WELLS/CANTORSB51//97URN, JODN/3TDCN/SBNT//LSRR5/,

09DN/RUSH222//SBR174) that were scored 4, considered moderately resistant to the disease,

but did not contain any of my genotyped alleles. These results suggest that additional loci not

evaluated in this study were associated with resistance in these particular lines.

During the 2015 field season, some selected SB lines from the previous year showed

severe susceptibility to the disease. For example, breeding lines WELLS/CANTORSB51 //

97URN, JODN/3TDCN/SBNT//LSRR5/, 09DN/RUSH222//SBR174 and ‘PI 658321’ were

scored 4 to 6 during 2014 season, but were scored 7 to 8 in the 2015 field trials at the RRS.

However, RUSH C99-1166 (‘LSBR5’) and ‘PI 658327’ from the 2014 field evaluation showed

the same disease score of 4 and 5 the following year. Similarly, the susceptible check varieties

showed the susceptible allele as expected (Table 3.2).

Six nsSNPs markers on chromosome 11 were added to the list of markers previously

tested because the new selected lines did not yield polymorphism to some of the nsSNPs markers

previously tested. Genotyping of the resistant check varieties, Teqing and MCR010277 showed

the expected resistant alleles across the markers. Resistant alleles on chromosome 11 were

observed in 09DN157//TRP545/CL161, ‘PI 658327” and RUSH C99-1166 (‘LSBR5’).

However, two additional genes on LOC_Os12g06980 and LOC_Os12g07950 were present only

in RUSH C99-1166 (‘LSBR5’). The resistant alleles in CCDR/PI 658335 and ‘PI 658335’

exhibited the same genotypic profiles on chromosomes 2, 6, 8 and 9. The only difference was

that some resistant alleles present in ‘PI 658335’on chromosomes 4, 6 11 and 12 were not

present in CCDR/PI 658335 cross. This difference could be attributed to recombination. On the

58

other hand, no resistant alleles were found on CTHL/SB2-3 cross and PI658320 using the tested

SNP-based markers.

A total of 136 non-synonymous SNP markers were tested in 2016 and 2017, but only 83

markers, which included the 36 markers genotyped in 2015 evaluation, showed clear

polymorphism between and among the lines tested (Table 3.3). Non-synonymous SNPs markers

on chromosomes 2, 4, 6, 8, 9, 11, and 12 showed polymorphisms between the resistant and

susceptible varieties. The resistant check varieties, Teqing and MCR010277 consistently showed

the resistant alleles. As expected, MCR010277 (PI 641932), which was developed by M.C.

Rush (2011), was known to have high levels of resistance to sheath blight, and Teqing, an indica

variety which was used to identify the nsSNPs (Silva et al. 2012). The susceptible check varieties

(Cocodrie, Catahoula, Mermentau, CL111, CL151, CL152), on the other hand, consistently

showed the susceptible alleles.

59

Table 3.2. Genotyping results of the selected resistant lines including 2 resistant and 6 susceptible checks in 2015 SB field evaluation.

Table 3.2 continued

PEDIGREE

SB R

atin

g (0

-9)

Chr.2 Chr. 4 Chr. 6 Chr. 8 Chr. 9

LOC

_Os0

2g34

490

LOC

_Os0

2g34

850

LOC

_Os0

4g10

460

LOC

_Os0

4g20

680

LOC

_Os0

6g13

040

LOC

_Os0

6g22

020

LOC

_Os0

6g22

460

LOC

_Os0

6g28

124

LOC

_Os0

8g19

694

LOC

_Os0

8g20

020

LOC

_Os0

9g32

860

LOC

_Os0

9g34

180

LOC

_Os0

9g36

900

LOC

_Os0

9g37

230

LOC

_Os0

9g37

590

LOC

_Os0

9g37

800

LOC

_Os0

9g37

880

LOC

_Os0

9g38

700

LOC

_Os0

9g38

710

LOC

_Os0

9g38

850

LOC

_Os0

9g38

970

LOC

_Os0

9g39

620

MCR010277 3 R R R R R R R R R R R R R R R R R R R R R R TEQING 3 R R R R R R R R R R R R R R R R R R R R R R RUSH C99-1166 (LSBR5) 4 S S S S S S S S S S S S S S S S S S S S S S 09DN157//TRP545/CL161 3 S S S S S S S S S S S S S S S S S S S S S S CTHL/SB2-3 6 S S S S S S S S S S S S S S S S S S S S S S CCDR/PI 658335 4 R R S S S R R R R R S S R R R R R R R R R R PI 658327 5 S S S S S S S S S S S S S S S S S S S S S S PI 658320 5 S S S S S S S S S S S S S S S S S S S S S S PI 658335 4 R R R R R R R R R R S S R R R R R R R R R R CTHL 8 S S S S S S S S S S S S S S S S S S S S S S CCDR 9 S S S S S S S S S S S S S S S S S S S S S S CLI52 8 S S S S S S S S S S S S S S S S S S S S S S CL111 7 S S S S S S S S S S S S S S S S S S S S S S MRMT 8 S S S S S R S S S S S S S S S S S S S S S S CL151 8 S S S S S S S S S S S S S S S R S S S S S S

60

* Fuschia; resistant varieties; blue: SB selected line; green: susceptible varieties; red: resistant allele; yellow: susceptible allele.

Similarly, genotyping results of the selected lines using the candidate polymorphic

markers showed 5 different haplotypes (Table 3.3): on chromosomes 9 and 11; chromosomes 2

and 12; chromosomes 2, 6, 8, 9; chromosomes 2 and 12, chromosomes 4, 8; and on

chromosomes 2, 4, 6, 8, 9, 11, 12. The resistance allele on PI 658320, C98-974 CPRS/AZMIL

(Rush et al., 2011) are on chromosomes 4 and 8 and are only specific to Azmil, the source of

resistance. RUSH C99-1166 (‘LSBR5’), 09DN157//TRP545/CL161, ‘PI 658327’ and ‘PI

658335’ have common resistant alleles from chromosomes 9 and 11. The resistant donor of these

resistant alleles are from ‘LSBR5’ (Rush et al, 2011). LSBR5 is a somaclonal mutant presumably

PEDIGREE D

iseas

e R

atin

g (0

- 9)

Chr. 11 Chr. 12

LOC

_Os1

1g24

060

LOC

_Os1

1g24

770

Loc_

Os1

1g13

650

Loc_

Os1

1g19

700

Loc_

Os1

1g24

180

Loc_

Os1

1g28

950

LOC

_Os1

2g06

980

LOC

_Os1

2g07

950

LOC

_Os1

2g09

710

LOC

_Os1

2g10

180

LOC

_Os1

2g10

330

LOC

_Os1

2g10

410

LOC

_Os1

2g13

100

LOC

_Os1

2g15

480

MCR010277 3 R R R R R R R R R R R R R R

TEQING 3 R R R R R R R R R R R R R R

RUSH C99-1166 (LSBR5) 4 R R S R R R R R S S S S S S

09DN157//TRP545/CL161 3 R R S R R R S S S S S S S S

CTHL/SB2-3 6 S S S S S S S S S S S S S S

CCDR/PI 658335 4 S S S S S S S S S S S S S S

PI 658327 5 R R S R R R S S S S S S S S

PI 658320 5 S S S S S S S S S S S S S S

PI 658335 4 R R R R R R R R R R S R R S

CTHL 8 S S S S S S S S S S S S S S

CCDR 9 S S S S S S S S S S S S S S

CLI52 8 S S S S S S S S S S S S S S

CL111 7 S S S S S S S S S S S S S S

MRMT 8 S S S S S S S S S S S S S S

CL151 8 S S S S S S R R S S S S S S

61

derived from the susceptible japonica variety Labelle (Xia et al., 1992). However, Nelson et al.,

(2012) further studied LSBR5 and found that it carried eight resistant alleles of the fourteen

markers evaluated suggesting that the origin of LSBR5 maybe from an indica source rather than

from Labelle. CTHL/SB2-3 line contained resistant alleles from chromosomes 2 and 12, where

SB2-3 mapping population is the product of Cocodrie (PI 606331) X MCR010277 (PI 641932)

cross.

The resistant alleles in ‘PI 658335’ (COO-1700 LSBR5/LMNT//TQNG/4/ LSBR5/

LMNT/3/H4CODF//NTAI (03-10993-11019) (Rush et al., 2011), are from chromosomes 2, 4, 6,

8, 9, 11 and 12. Resistant alleles from chromosome 9 are the most abundant in this line with

‘LSBR5’, TQNG and H4CODF as the presumed donors. H4CODF is a mutant derived from Sri

Lanka cultivar H4 by cobalt radiation and is partially resistant to sheath blight disease (Sha,

differenober1998). A Cocodrie/PI 658335 cross carries 39 resistance alleles including 11 out of

16 from chromosome 2, 14 from chromosome 6, one allele on 8 and 13 out 17 evaluated on

chromosome 9. This is slightly different from the DH line from the same cross produced by Y.

Sanabria (unpublished result). This result suggests that through recombination, potential new

combinations of alleles are produced that can prove beneficial for breeding purposes. In addition,

a haplotype on chromosomes 9 and 11 was specific only to LSBR5; the haplotype on

chromosome 2 and 12 was specific to 'SB2-3' and a haplotype on chromosomes 2, 6, 8 and 9

specific to PI 658335 was detected.

62

Table 3.3. Genotypes of the 7 selected lines from the 2016-2017 field evaluation at RRS, Crowley, Louisiana.

Table 3.3 continued

PED

IGR

EE

TE

QIN

G

MC

R010277

RU

SH

C99- 1

166 (

LS

BR

5)

09D

N157//

TR

P545/C

L161

CT

HL

/SB

2- 3

CC

DR

/PI

658335

PI

658327

PI

658320

PI

658335

CA

TA

HO

UL

A

CO

CO

DR

IE

CH

EN

IER

E

CL

111

CL

151

CL

152

CL

153

Disease Rating (0-9) 3 4 3 3 4 4 4 3 3 8 9 8 7 7 6 6

LOC_Os02g02650 R R S S R S S S S S S R S S S S

LOC_Os02g11820 R R S S S R S S R S S S S S S S




LOC_Os02g39590 R R S S R R S S R S S S S S S S

LOC_Os02g43460 R R S S R S S S S S S S S S S S



LOC_Os02g51900 R R S S S S S S R S S S S S S S







LOC_Os04g05030 R R S S S S S R R S S S S S S S





LOC_Os04g56250 R R S S S S S S S S S S S S S S






63

PED

IGR

EE TE

QIN

G

MC

R010277

RU

SH

C99- 1

166 (

LS

BR

5)

09D

N157//

TR

P545/C

L161

CT

HL

/SB

2- 3

CC

DR

/PI

658335

PI

658327

PI

658320

PI

658335

CA

TA

HO

UL

A

CO

CO

DR

IE

CH

EN

IER

E

CL

111

CL

151

CL

152

CL

153

Disease Rating (0-9) 3 4 3 3 4 4 4 3 3 8 9 8 7 7 6 6















LOC_Os08g19694 R R S S S R S S R S S S R S S S

LOC_Os08g30910 R R S S S S S R R S S S R S S S






LOC_Os09g25620 R R R R S R R S R S S S S S S S

LOC_Os09g25890 R R R R S R R S R S S S S S S S

LOC_Os09g26300 S R R R S R R S R S S S S S S S




Table 3.3 continued

64

PED

IGR

EE

TE

QIN

G

MC

R010277

RU

SH

C99- 1

166 (

LS

BR

5)

09D

N157//

TR

P545/C

L161

CT

HL

/SB

2- 3

CC

DR

/PI

658335

PI

658327

PI

658320

PI

658335

CA

TA

HO

UL

A

CO

CO

DR

IE

CH

EN

IER

E

CL

111

CL

151

CL

152

CL

153

Disease Rating (0-9) 3 4 3 3 4 4 4 3 3 8 9 8 7 7 6 6









LOC_Os11g19700 R R R R S S R S R S S S S S S S





LOC_Os11g28950 R R S S S S R S R S S S S S S S

LOC_Os12g03554 R R S S R S S S S S S R S S S S


LOC_Os12g06740 R R S S S S S S R S S S S S S R









LOC_Os12g15460 R R S S S S S S R S S S S R S R

* Legend: fuschia - resistant checks; blue - SB selected lines; green - susceptible checks; red - resistant nsSNP allele; yellow - susceptible nsSNP allele.

65

3.4. Discussion

Sheath blight resistance in rice is a quantitatively inherited trait. There is no known single

validated major gene that is effective across multiple germplasm sources. Instead, multiple genes

with small effect control resistance levels suitable for resistance breeding. Several accessions

with complex gene control have shown moderate resistance to SB disease (Eizenga et al. 2002;

Wang et al. 2011). Breeding for this trait is of utmost importance in south Louisiana because

most commercial varieties are known to be moderately to highly susceptible.

Molecular marker applications with conventional breeding have proved beneficial in

some cases for crop improvement (Moose and Mumm, 2008). DNA markers consisting of Single

nucleotide polymorphisms (SNPs) markers are robust, scalable, and relatively easy to use

(Thomson et al. 2017). Non-synonymous SNPs marker on 11 chromosomes associated with

sheath blight resistance using whole genome sequencing were previously identified in Oard’s

laboratory by by Silva et al. (2012). The markers developed by Y. Sanabria (Sanabria, 2015) was

used in genotyping the selected lines described in this study. The nsSNPs markers identified for

SB resistance in my study on chromosomes 2, 4, 6, 8, 9, 11, and 12 mapped in or near several

QTLs reported in the literature (Li et al. 1995; Pan et al. 1999; Zou et al. 2000; Han et al. 2002;

Kunihiro et al. 2002; Che et al. 2003; Sato et al. 2004; Pinson et al. 2005; Tan et al. 2005; Xie et

al. 2008; Liu et al. 2009; Channamallikarjuna et al. 2009; Sharma et al. 2009; Nelson et al. 2012;

Tagushi-Shiobara et al. 2013; Zuo et al. 2014).

Selected SB lines from the field evaluations of advanced lines at the RRS showed

moderate resistance compared to the disease reaction of the susceptible varieties. Genotyping

using the nsSNPs markers revealed one or more resistant allelic combinations in the selected SB

lines. A haplotype specific to only one source of resistance was observed. One example is PI

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658320 (CPRS/AZMIL (Rush et al. 2011), with a haplotype combination on chromosomes 4 and

8 while CTHL/SB2-3 produced resistance alleles from chromosomes 2 and 12 (Table 3.3).

Resistance alleles from chromosomes 9, 11 and 12 were observed for donor RUSH C99-1166

(LSBR5) and lines CCDR/PI 658335, PI 658327, and PI 658335.

PI 658335 with SB score of 3 showed slightly higher levels of resistance than the cross,

CCDR/PI 658335 with SB score of 4 (Table 3.3). This slight increase in resistance may be due to

presence of two or more resistance alleles on chromosomes 2, 8, and 9. Moreover, PI 658335

carried resistant alleles on chromosomes 4, 11 and 12 that were absent in the CCDR/PI 658335

cross. The SB line PI 658335 was developed from LSBR5, TEQING and H4CODF as resistant

donors (COO-1700 LSBR5/LMNT//TQNG/4/LSBR5/LMNT/3/ H4CODF//NTAI (03-10993-

11019) (Rush et al. 2011). A DH line with the same cross, CCDR/PI 658335, developed by Y.

Sanabria from Dr. Oard’s lab (unpublished result), was different with the resistant allele

composition of the CCDR/PI 658335 line evaluated in my study.

Similar haplotypes were also observed from the selections evaluated in 2014 which

corresponded to the MCR010277 source of resistance. Resistance alleles on chromosomes 4, 6, 9

and 12 was observed in CCDR/SB2-174 cross while the resistance alleles from CCDR//CIAT8/

MCR010277 were found on chromosomes 2, 4, 6 and 9. Another haplotype was detected on

chromosomes 2, 6, and 9, which corresponded to reported disease resistance loci RPM1

(LOC_Os06g22460), OsWAK14 (LOC_Os02g42150), and OsWAK91 (LOC_Os09g38850)

specific only to CCDR/PI 658335 and ‘PI 658335’ (Rush et al. 2011).

The different selected SB lines in this study identified through marker evaluation were

found to carry resistant alleles on chromosomes 2, 4, 6, 8, 9, 11 and 12. QTLs on chromosome 9

related to sheath blight resistance have been found to have a moderate effect on resistance to SB

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among different sources of resistance (Srinivasachary et al. 2011) including Teqing (Li et

al.1995; Pinson et al. 2005), Jasmine 85 (Liu et al. 2009; Pan et al. 1999; Zou et al. 2000),

Minghui 63 (Han et al. 2002; Zuo et al. 2014), WSS2 (Sato et al. 2004), Tetep

(Channamallikarjuna et al. 2010), Pecos (Sharma et al. 2009) and MCR010277 (Nelson et al.

2012). Although effects for SB resistance were detected previously on chromosome 9 (Nelson et

al., 2012), the combined contributions of chromosomes 2, 4, 6, 8, 9, 11 and 12 most likely were

associated with increased resistance compared to the susceptible parents.

Three resistant alleles on chromosome 9 (LOC_Os09g25620, LOC_Os09g25890,

LOC_Os09g26300), combined with the five resistant alleles on chromosome 11

(LOC_Os11g19700, LOC_Os11g24060, LOC_Os11g24180, LOC_Os11g24770,

LOC_Os11g28950), were common to the five best lines, RUSH C99-1166 (LSBR5),

09DN157//TRP545/CL161, CCDR/PI 658335, PI 658327, and PI 658335. LOC_Os09g25890

encoides trehalose-6-phosphate synthase, reported to play a role in response to infection by the

rice blast fungus Magnaporthe oryzae (Fernandez and Wilson, 2011) while the ankyrin repeat

domain containing protein LOC_Os11g24770 presumably plays a role in rice immunity (Mou et

al. 2013).

The QTL associated with SB resistance on chromosome 9 that has been previously

reported by Nelson et al. (2012) at the bottom of the long arm of chromosome 9 have been

confirmed to exert a moderate effect on SB resistance. Dr. Pankaj Jaiswal of Oregon State

University recently postulated that the following three genes, based on RNA-Seq studies, may be

involved in the sheath blight defense response: CeBIP (Chitin elicitor-binding protein), CERK

(Chitin elicitor receptor kinase 1) and WAK91 (Wall associated kinase). Delteil et al. (2016)

68

reported that the WAK91 gene in rice was one of the several wall-associated kinases involved in

basal defense against the rice blast disease. WAK91 protein belongs to the Receptor-like Kinase

(RLK) gene family that may play key roles in basal immunity, characterized by an extracellular

domain composed of one or several repeats of the Epidermal Growth Factor (EGF) domain

(Cayrol et al. 2016). The EGF domain is known in animals to bind to a very large range of small

peptides and to dimerize upon calcium binding (Hynes and MacDonald, 2009). In maize, two

distinct wall-associated kinases were shown to be responsible for a QTL for resistance to soil-

borne fungus Sporisorium reilianum (ZmWAK) (Zuo et al. 2015) and one against the foliar

fungal pathogen Exserohilum turcicum (Htn) (Hurni et al. 2015). Receptor-like kinases have

been associated with resistance to Magnaporthe grisea and Xanthomonas oryzae diseases.

Therefore, LOC_Os09g38850 may play a role in the host defense response to R. solani. Another

member of the WAK gene family was found on chromosome 2 specifically at LOC_Os02g42150

(OsWAK21) which encodes a wall-associated receptor like cytoplasmic kinase (OsWAK-

RLCK). According to Zhang et al. (2005), the physical location of OsWAK21 is at the bottom of

the long arm of chromosome 2. The resistance alleles of this gene were observed in CTHL/SB2-

3, PI 658335, and CCDR/PI 658335.

Fine mapping of qSB-9TQ, a major quantitative trait locus that confers significant

resistance to rice sheath blight (SB) has yielded 12 candidate genes in this region (Zuo et al.

2014). Conversely, LOC_Os09g38850 was not identified in the fine mapped QTL, although

another protein kinase (LOC_Os09g37230) was found in that region. Essentially, the mapping

population used in the fine mapping and the sources of resistance used in my breeding

population are totally different. The fine-mapped QTL containing the LOC_Os09g37230 might

69

work for the Lemont x Teqing population used by Zuo et al., (2014), but is not significant in the

lines generated in my study or in those lines described by Rush et al. (2011).

Of the SB resistant lines identified in this study, RUSH C99-1166 (LSBR5),

09DN157//TRP545/CL161, PI 658327 and PI 658335, have resistant alleles from chromosome

11. This region contains genes that encodes for receptor-like protein kinases, the same gene

family where WAK91 gene belongs. RLKs have been identified to act in both broad-spectrum,

elicitor-initiated defense responses and as dominant resistance (R) genes in race-specific

pathogen defense (Goff and Ramonell, 2007). However as mentioned above, to increase the

resistance levels against SB, interaction with resistant alleles from other chromosomes may be

required. A gene on LOC_Os02g58540 which encodes for RING-H2 finger protein, was

identified and is common to PI 658335 and CCDR/PI 658335. RING H2- finger protein, is an E3

ubiquitin ligase that is induced by chitin and involved in basal resistance to the biotrophic fungal

pathogen, Golovinomyces cichoracearum (G. cichoracearum) Deng et al. (2017). It was reported

that ectopic expression of the rice OsRHC1, encoding a RING finger protein other than the ATL

family members, in Arabidopsis thaliana shows enhanced disease resistance and elevated

expression of defense related genes (Cheung et al. 2007). The other 5 resistant lines, RUSH C99-

1166 (LSBR5), 09DN157//TRP545/CL161, CTHL/SB2-3, PI 658327 and PI 658320 did not

carry the resistant allele of LOC_Os02g58540, but contained resistant alleles from the other

chromosomes, resulting in a resistant response. The gene on LOC_Os02g58540 alone cannot

exert increased defense response unless associated with other defense related genes. Hence, a

positive interaction with resistant alleles from other chromosomes may be required to improve

resistance to SB disease.

70

Candidate nsSNPS markers identified in this study may be beneficial for development of

SB resistant rice germplasm in conjunction with traditional breeding practices. To identify other

possible resistant alleles involved in the SB resistance, further research will be required to

identify additional makers not covered in this study. Identifying the specific combination of

resistant alleles from specific sources of resistant is also necessary to understand the mechanisms

of resistance to SB and increase efficiency of markers-assisted selection. There has been little

progress toward understanding the genetic mechanisms involved in sheath blight resistance in

rice. Hence, traditional breeding methods coupled with SNP-based markers used in this study

resulted in considerable gains in SB resistance that represents a valuable source of information to

direct future applied research on resistance to R. solani in rice. RNA-Seq technology appeared to

be an important biological tool to understand mechanisms involved in SB resistance. The genetic

material and marker information produced from this study may also facilitate future studies to

investigate mechanisms of rice-R. solani interactions.

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CHAPTER 5. GENETIC ANALYSIS OF NOXIOUS AQUATIC WEED IN LOUISIANA AND TEXAS

4.1. Introduction

Salvinia molesta Mitchell [Salviniaceae] is a floating, rootless aquatic fern introduced

from South America that has been found at more than 150 locations since 1995 in 69 freshwater

sites in Alabama, Arizona, California, Florida, Georgia, Hawaii, Louisiana, Mississippi, North

Carolina, Puerto Rico, South Carolina, Texas, and Virginia (http://www.gri.msstate.edu/ipams

/species.php?CName=Giant%20salvinia). S. molesta is considered a noxious weed in Louisiana

and other states because it out-competes water hyacinths (Eichhornia crassipes (Mart.) Solms)

and indigenous aquatic species. Moreover, rapid, dense growth of S. molesta restricts penetration

of oxygen and light below surface water negatively affecting all plants and animals beneath.

Decomposition of S. molesta leads to substantial reductions in dissolved oxygen required by fish

and other aquatic life (Thomas and Room, 1986). The growth rate of S. molesta varied from 5 to

41 days in doubling time depending on environmental and nutrient conditions (Mitchell and Tur,

1975). Without competitive factors during summer months, S. molesta can be colonized by

sedges, grasses, and even small trees to create a floating island of vegetation.

S. molesta is a pentaploid neotropical species considered a member of the “Salvinia

auriculata complex” that also includes S. auriculata Aublet, S. biloba Raddi, and S. herzogii de

la Sota (Loyal and Grewal, 1966). Vegetative reproduction of S. molesta by stem fragments has

been reported (McFarland et al., 2004), but fertility of the fruiting bodies or sporocarps is still

not known. The basic vegetative reproductive unit is referred to as the “ramet” consisting of a

rhizomatous structure connected to three leaves in a whorl, two of which are floating and green,

This chapter previously appeared in Morphological and genetic survey of Giant Salvinia populations in Louisiana

and Texas, Galam D et al., Elsevier: Aquatic Botany, 2015.

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while the remaining leaf is white, submersed and often misidentified as a root. The apparent

inability of S. molesta to reproduce sexually may result in proliferation of separate and distinct

clonal lineages.

In Louisiana, S. molesta was first observed in 1998 at the Toledo Bend Reservoir and at

the Sabine River (McFarland et al. 2004). This invasive fern was subsequently detected in

Cameron Parish in 2001 (http://www.seagrantfish .lsu.edu/ pdfs/ giantsalvinia_control.pdf) and

in Lake Bistineau in 2005 and in Caddo Lake in 2006 (http://www.doi.gov/ocl/hearings/112

/GiantSalvinia_062711.cfm). The first infestation sites in Texas were found at Toledo Bend and

at Swinney Marsh in 1998 (Jacono 1999; Jacono and Pitman 2001).

The control of S. molesta by herbicides may be inconsistent or ineffective due to presence

of below-water buds and stems, “unwettable” hair-covered leaves, and a thick layer of vegetation

formed on the surface of the water (McFarland et al. 2004). Many conventional aquatic

herbicides are completely ineffective (unpublished data). Success of C. salviniae as a biological

control agent for S. molesta in Florida varied with swings in population levels of C. salviniae and

the aquatic fern (Room, 1990). Release of C. salviniae into infested areas of Louisiana and Texas

has shown potential as a biocontrol strategy (Tipping et al. 2008). Large-scale rearing and release

of C. salviniae is currently used in Louisiana and Texas to help suppress growth of S. molesta in

concert with herbicides (http://cise. tamu.edu/ media/355740/gs_manual_10-15-12.pdf).

Madeira et al. (2003) conducted a genetic survey of the related S. minima, an introduced

clonally propagated fern that has a U.S. distribution range similar to that of S. molesta. RAPD

Ramdonly Amplifed Polymorphic DNA (RAPD) markers located at 88 different genomic

regions of S. minima were used to evaluate diversity of 38 different populations within and

outside of Florida. Their study showed that S. minima essentially belonged to the same genetic

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population, although samples from Mississippi may have been genetically distinct from those in

Florida.

The nuclear encoded glyceraldehyde 3-phosphate dehydrogenase gene (gapCp) has been

used to examine population diversity in various species including bacteria (Figge et al. 1999),

insects (Ishiyama et al. 2006), a fungal plant pathogen (Ramdeen and Rampersad, 2013), and the

mangrove Bruguiera gymnorhiza (Minobe et al. 2010). Schuettpelz et al. 2008 examined gapCp

sequence diversity to study the evolutionary history of polyploid ferns.

The effects of nitrogen level and water temperature on growth rate of S. molesta were

previously investigated under greenhouse conditions (Cary and Weerts, 1983a). Over a period of

19 days, S. molesta increased maximum biomass 38-fold when grown at 22°C and supplied with

20 mg NH4-N l-1. Under these conditions, doubling time for leaf number occurred in ~ 2.2 days.

In a related study (Cary and Weerts, 1983b), maximum growth rate of the fern occurred 32-fold

under greenhouse conditions at 22°C when provided 1 to 10 mg PO4-P l-1.

No morphological or genetic diversity study of S. molesta has been conducted in the

southern U.S.


4.2.1. Collection of S. molesta samples and morphological data

Salvinia molesta was first observed in Louisiana in1998 at the Toledo Bend Reservoir

and at the Sabine River (McFarland et al., 2004). This invasive fern was subsequently detected in

Cameron Parish in 2001 (http://www.seagrantfish.lsu.edu/pdfs/giantsalvinia_control.pdf,

accessed March 4, 2015) and in Lake Bistineau in 2005 and in Caddo Lake in 2006

(http://www.doi.gov/ocl/hearings/112 /GiantSalvinia_062711.cfm, accessed March 4, 2015). In

Texas, the first infestation sites were found at Toledo Bend and at Swinney Marsh in 1998

(Jacono, 1999; Jacono and Pitman, 2001).

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Leaves and lateral buds were collected at each of six sites in Louisiana and Texas from

May 26 to June 10, 2009. The collection sites (Table 4.1) for this study because are recognized

by the Louisiana Department of Wildlife and Fisheries and the Texas Parks and Wildlife

Department as historical or persistent infestations at ecologically diverse locations in both states.

Table 4.1. Geographic location of S. molesta populations and description of collection sites.

At each site, 40 individual colonies of S. molesta were collected a minimum of 10 m

apart, washed thoroughly with distilled water before collecting measurements from each colony

Collection Site

GPS Coordinates

Description

Caddo Lake, Louisiana

N 32.734874°; W 94.021751°

Large lake ~ 108 km in length that stretches across into Texas consisting of interconnecting sloughs, bayous and ponds.

Lake Bistineau, Louisiana

N 32.440811°; W 93.380742°

Long (23 km) and narrow (2 km) lake presumably created in 1800 from a log jam on the Red river.

Gheens, Louisiana

N 29.410802°; W 90.265386°

Slow moving streams (bayous) in south Louisiana with dense infestations of S. molesta

Thibodaux, Louisiana

N 29.394169°; W 90.433939°

Slow moving streams (bayous) in south Louisiana with dense infestations of S. molesta.

Belle River, Louisiana

N 29.553052°; W 91.142103°

Popular boat launch for fishing in south Louisiana with S. molesta infestation detected at the river’s edge.

Toledo Bend, Texas

N 31.298415°; W 93.753011°

Fifth largest man-made body of water in the U.S; located on the Texas side along the Sabine River between Louisiana and Texas.

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for width, ramets/colony, rhizome length, leaf width, and root length. A total of 20 randomly

selected colonies from each site were used to measure the five traits from each colony. For each

trait, three independent measurements per colony were collected. Colonies were examined for

presence of fruiting bodies (sporocarps) and the weevil C. salviniae. Samples were then blotted

dry and placed in individual 50 mL sterilized centrifuge tubes containing desiccated silica gel.

The centrifuge tubes were subsequently stored in the laboratory at room temperature in the dark

until DNA extraction. Except for the Toledo Bend Reservoir, a one-liter sample of water at each

site was taken to determine pH and N, P, and K concentrations. Samples were analyzed ~ 24 hr

after collection by the Department of Agricultural Chemistry, Louisiana State University

AgCenter, Baton Rouge, LA.

4.2.2. DNA extraction, amplified fragment length polymorphism (AFLP) and gapCp gene sequence analysis

A range of 36 to 42 silica-dried aerial leaves and lateral buds from individual colonies

across locations were collected for DNA extraction using the Qiagen DNeasy Plant Mini Kit

(QIAGEN, Valencia, CA, USA) as recommended by the manufacturer. AFLP marker analysis

was carried out on 40 S. molesta samples from each collection site using the basic protocol of

Vos et al. (1995). Briefly, ~ 200 ng DNA/μL from each sample was digested with EcoRI and

MseI restriction enzymes. Digested fragments were ligated to EcoRI and MseI adaptors, and

pre-selective amplification was carried out with with EcoRI+A and MseI+C primers. Amplified

PCR products were diluted 10-fold as templates for selective amplification. Eight AFLP primer

pairs (E-ACC/M-CAA, E-AAC/M-CAA, E-ACC/CAC, E-AAC/M-CAC, E-AGA/M-CAG, E-

AGG/M-CAG, E-AAA/M-CCC, E-AAA/M-CGC) were labeled with IR dye (700 and 800 P:

MWG, Germany) with three selective nucleotides used for fingerprinting of 10 samples from

each population. Two AFLP primer pairs, E-AAC/M-CAC and E-AAA/M-CCC, produced

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repeatable and scorable fragments that were used to genotype all samples. Selective

amplifications were conducted with 10 μL final volume containing 2 μL diluted pre-

amplification product, 1.0 μL 1 μM IR-labeled EcoRI primer, 1.0 μL 1 μM IR-labeled MseI

primer, 0.2 μL 5 U/μL Taq DNA polymerase (Promega, Madison, WI), 1.0 μL 5 mM dNTPs, 3.2

μL 5x PCR buffer (Promega, Madison, WI), and 0.6 μL sterilized water. Amplified products

were combined with 5 μL 5x Bromo-phenol Blue loading dye and denatured at 95°C for 5

minutes. A total of 0.75 μL was loaded onto 6.5% polyacrylamide denaturing gels using the

LiCor 4300 DNA Analyzer (LiCor Inc., Lincoln, NE). Clear and unambiguous AFLP fragments

were manually scored as ‘1’ for presence and ‘0’ for absence.

Conserved regions as described by Ebihara et al, (2005) from Pinus sylvestris gapCp

exons and introns 8, 9, 10, and 11 (GenBank accession AJ001706; Meyer-Gauen et al., 1998)

were used to design primers (see below) for PCR amplification of corresponding S. molesta

fragments. PCR reactions consisted of 10X PCR Buffer containing MgCl2, 10 μM each dNTP, 5

U/µl AmpliTaq® DNA Polymerase (Life Technologies, USA), 20 μM primer ESGAPCP8F1 (5’

to 3’ = ATYCCAAGYTCAACTGGTGCTGC), 20 μM primer ESGAPCP11R1 (5’ to 3’ =

TATCCC CAYTCRTTGTCRTACC), 1 µl template DNA in 20 µl reaction. PCR conditions

consisted of initial denaturation step (94°C for 5 min), denaturation, annealing, and elongation

step (94°C for 1 min, 59°C for 1 min, 72°C for 2 min) for 35 cycles and elongation step (72°C

for 10 min).

PCR products were resolved on a 4% agarose gel and subsequently cloned using the

TOPO TA Cloning kit (Invitrogen by Life Technologies, USA). Cloning reactions included 0.4

µl salt from the cloning kit, 0.4 µl TOPO vector, and 0.7 µl PCR product with incubation for 30

min at room temperature. Transformations were carried out with 0.7 µl cloning mixture and 16.7

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µl One Shot TOP10 competent cells as recommended by the manufacturer’s protocol.

Transformed cells were grown on plates containing Luria broth, 50 mg/L ampicillin and X-gal

(Gold Biotechnology, USA) for 16 hr at 37°C. Cells from 15 or more white colonies from each

plate were added to 20 µl PCR reactions prepared as above, but with the M13 Forward (-20) and

M13 Reverse primers (Life Technologies, Grand Island, NY, USA). PCR was carried out as

described above with isolated amplified fragments of ~ 650 bp in length selected for sequencing.

Selected PCR products were submitted to the Louisiana State University Pennington Biomedical

Research Center-CORE facility for sequencing using the M13 Forward (-20) and M13 Reverse

primers.

Selected PCR products were purified using the QIAquick PCR Purification Kit

(QIAGEN, Valencia, CA, USA) following the manufacturer’s protocol. Sequencing of the PCR

products was carried out with the BigDye Terminator v3.1 Cycle Sequencing Kit (Life

Technologies, Grand Island, NY, USA) per the manufacturer’s instructions. Each 10 μL reaction

incorporated 0.375x BigDye Terminator Ready Reaction Mix (Life Technologies, Grand Island,

NY, USA), 0.625x BigDye Terminator Sequencing Buffer (Life Technologies, Grand Island,

NY, USA), 1 μM primer [M13 Forward (-20) and M13 Reverse primers] and 2 μL purified PCR

product. Sample electrophoresis and analysis were performed using an ABI 3130xL DNA

Analyzer (Life Technologies, Grand Island, NY, USA).

4.2.3. Analyses of morphological and molecular data

Morphological traits like root length, colony width, rhizome length, leaf width and

number of ramets per colony were collected from 20 randomly-selected colonies at each site.

Principal component analysis of the five traits and polymorphic AFLP loci and the was carried

out using PROOC PRINCOMP of SAS v9.3 with default settings (SAS Institute Inc., 2010). The

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Analysis of Variance (ANOVA) and Tukey’s Studentized Range (HSD) Test for the

morphological traits was computed using PROC GLM. PROC CLUSTER was implemented to

group observations together when the underlying structure was unknown. This was carried out

with average linkage analysis where distance between two clusters was the average between

pairs of observations or one in each cluster. Data points with the smallest average distances

between them were grouped together. Data with the next smallest distances were added to each

group until all observations clustered together into one group.

Nei’s average number of pairwise allelic differences within and between populations (Nei

and Li, 1989) for both AFLP binary fragments and gapCp sequence data were computed using

Arlequin v3.5.1.3 (Excoffier and Lischer, 2010). AMOVA of raw AFLP binary and gapCp

sequence data was performed using GenAlEx6.5 software with the Codom – Genotypic

(Haploid) option for distance calculation based on Peakall and Smouse, 2012. A nonparametric

permutation procedure with 9999 pairwise-permutations was carried out to test the significance

of the variable components associated with possible levels of genetic structure.

Nucleotide diversity (π) of gapCp data was computed by the average number of

nucleotide substitutions per site (DXY) between populations and the number of net nucleotide

substitutions per site between populations (DA) based on Nei (1987) using DnaSP 5.10 software

(Rozas et al., 2003). Arlequin v3.5.1.3 software (Excoffier and Lischer, 2010) was used to

calculate π for the AFLP data, Wright’s fixation index (Fst) (Wright, 1951) and measure of

polymorphism per nucleotide (θ) under the finite sites model (Tajima, 1996).

Cloned PCR products of S. molesta described above were sequenced from 237

individuals ranging from 36 to 42 individuals across the six populations of this study. Individual

sequences per population were subjected to multiple sequence alignments with the exons and

85

introns the P. sylvestris gapCp gene using the ClustalW v2.1 software (www.clustal.org). The

NCBI BLAST search tool was utilized to identify regions of similarity. For both AFLP marker

data and gapCp sequences, Mantel’s isolation by distance test (Mantel, 1967) was conducted

using GenAlEx v6.5 (Peakall and Smouse, 2012). Nei’s pairwise genetic distance between

populations (Nei and Li, 1989) based on AFLP and gapCp sequence data was used to generate

genetic distance matrices.

4.3. Results

4.3.1. Phenotypic diversity of S. molesta in Louisiana

The ANOVA carried out for the five traits evaluated in this study produced significant F

values (P < 0.0001) for all traits, suggesting substantial phenotypic variability was present for the

morphological characters evaluated across collection sites (Table 4.2). S. molesta from

Bistineaux, Louisiana had the highest colony width with 164 mm while samples from BellRiver

and Thibodaux, LA had the lowest colony width. For the number of ramets per colony, samples

from Caddo, LA had the highest number of ramets per colony across the sampling sites. Caddo

Lake and Bistineaux, LA showed the longest rhizome length per colony with 15mm respectively

while samples from Gheens, LA had the shortest rhizome per colony across the sites.

Additionaly, leaf width per colony from Caddo and Bistineaux, LA were significantly higher

with a range of 30 -33mm than the samples from BellRiver, Thibodaux and Gheens, Louisiana.

Lastly, samples from Bistineaux, LA had significantly higher root length per colony with 344mm

across the sampling site while samples from Thibodaux and BellRiver, LA had the shortest root

length per colony with 40 and 48mm respectively. Pearson’s linear correlation (r) values

between traits showed that root length was moderately associated with colony width, rhizome

length, and leaf width (r > 0.5, p < 0.001, Table 4.3). However, when each site was analyzed

86

separately, only ramets/colony was associated with colony width at the Gheens, Bell River, and

Lake Bistineau sites (r > 0.5, p < 0.001).

Table 4.2. Analysis of variance (ANOVA) of five morphological characteristics; colony width (mm), ramets per colony, rhizome length per colony (mm), leaf width per colony (mm), root length per colony (mm) for five populations of S. molesta.

Letter notation indicates Tukey’s mean comparison test with means indicated by the same letter is not significantly different at the 0.05 probability level.

Principal Component Analysis (PCA) was used to identify clustering of the five traits in

one or more of the study sites. The PCA generated five clusters with PC1, PC2, and PC3

eigenvalues explaining a combined 85% of the observed variation (Fig. 4.1). The Bistineau

location formed two distinct clusters, but the remaining groups were formed by an overlap

between different populations. Moreover, a single cluster was not always associated with a

single location as was observed for the Bistineau site. A similar pattern was observed where two

clusters were detected at each of the Gheens and Caddo Lake sites. Based on the morphological

traits, root length per colony (mm) was detected to have the highest observed variation value

(PC1 = 53%) while ramets per colony (mm) had the lowest (PC1 = 28%).

Both Lake Bistineau and Caddo Lake produced greater median root lengths than the three

southern locations (Fig. 4.2). The Thibodaux site produced the smallest median value as was

Sources of variation

Populations Gheens,

LA BellRiver,

LA Thibodaux,

LA Caddo,

LA Bistineaux,

LA

Colony width (mm) 116b 70c 58c 96b 164a

Number of ramets per colony 25 23 24 41a 27

Rhizome length per colony (mm) 7c 10b 10b 15a 15a

Leaf width per colony (mm) 26b 30a 21c 30a 33a

Root length per colony (mm) 65c 48c 40c 163b 344a

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observed for colony width and leaf width. Tukey’s analysis showed that the two northern sites

were each assigned to separate clusters while the three southern locations formed a second

group.

Bistineau site in north Louisiana that contrasted with the smallest range and median value

at the Thibodaux site in south Louisiana. Colony width at Lake Bistineau in north Louisiana

produced the greatest mean value (164 mm) that was statistically different based on Tukey’s test

from the second (Gheens, 116 mm; Caddo Lake, 96 mm) and third group (Bell River, 70 mm;

Thibodaux, 58 mm). The same trend was observed in the number ramets per colony, leaf width

(mm), and length of rhizomes per colony (mm), where substantial variations were detected at all

locations. Median values for ramets per colony ranged from 23.3 to 41.1 mm across locations.

Similar trends were observed for the other morphological traits (data not shown). For example,

the greatest range and median values for colony width (mm) were observed at the Lake northern

sites at Lake Bistineau and Caddo Lake generated the widest median leaf widths at 29.6 to 33.0

mm compared to the three southern locations with overall median value of 28.0 mm. The

greatest range and median values for the number of rhizome per colony was detected at the two

north Louisiana sites vs. the three southern locations, particularly at Gheens that exhibited the

smallest median value.

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Figure 4.1. Principal Component Analysis (PCA) of the five traits from S. molesta evaluated in this study. Pyramid = Gheens, LA; Cylinder = Bell River, LA; Cube = Thibodaux, LA; Club = Caddo Lake, LA; Balloon = Lake Bistineau, LA. Green = Cluster 1; Black = Cluster 2; Red = Cluster 3; Magenta = Cluster 4; Purple = Cluster 5.

4.3.2 Molecular diversity of S. molesta in Louisiana and Texas

Using the AFLP DNA marker and gapCp gene sequence information collected within

and across Louisiana and Texas sites, significant differences (P<0.0005) were detected by

AMOVA both within and among the populations (Table 4). When considering total AFLP

marker information, the vast majority of the variation was detected within populations (93%) as

compared to variation among populations (7%). A similar trend was observed for exon and

intron sequences of the gapCp gene where most of the variability (87%) was attributed to within-

population variation.

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Table 4. 3. Correlation matrix of five morphological traits of the five populations of S. molesta from Louisiana and Texas. Values above the diagonal are the P-values with 999 permutations and the Pearson correlation coefficient values between pairs of traits below the diagonal. P values were significant at < 0.05.

Morphological Traits

Colony width

Ramets per

colony

Rhizome length per

colony

Leaf width

Root length

Colony width - 0.000 0.000 0.000 <0.000

Ramets per colony 0.34 - 0.000 0.218 0.158

Rhizome length per colony

0.37 0.37 - <0.000 <0.000

Leaf width 0.34 0.12 0.45 - <0.000

Root length 0.62 0.14 0.66 0.52 -

Principal Component Analysis (PCA) was performed with AFLP data for the six

collection sites of this study. PC1, PC2, and PC3 eigenvalues explained a combined 42 % of the

observed variation that produced five distinct clusters. One large cluster consisted of 86% of all

individuals originating from all six collection sites. The remaining clusters were small, loose

groups containing few (3 to 13) individuals. The Mantel test (Mantel, 1967) was used to evaluate

geographical and genetic relationships among the six collection sites in Louisiana and Texas. No

correlation between genetic and geographical distances was detected by AFLP data (P = 0.290)

or the gapCp sequences (P=0.374). Similar to the AFLP data, PCA analysis of the S. molesta

gapCp sequence data produced 85% of the total variation that revealed four major clusters each

comprised of individuals from more than one collection site. The Mantel test revealed no

correlation between sequence and geographical distance for the gapCp gene.

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Overall pairwise analysis of nucleotide diversity (π) of gapCp sequences at 0.25

suggested relatively high levels of variability for the six collection sites. The average number of

gapCp nucleotide substitutions per site between populations was relatively high. For example,

Figure 4.2. Box plot for root length (mm) for 20 individuals each of S. molesta at Gheens, LA; Bell River, LA; Thibodaux, LA; Caddo Lake, LA; and Lake Bistineau, LA. The top and bottom of the colored boxes represent the 75th and 25th percentile, respectively, while the horizontal band in a box represents the 50th percentile (median). Vertical lines with horizontal “caps” above and below the boxes denote the smallest and largest values. Black dots outside the boxes represent individual values considered as “outliers” (< or > 3/2 value of 75th or 25th percentile). Letter notation above the plot indicates Tukey’s mean comparison test with means indicated by the same letters are not significantly different at the 0.05 probability level.

the Thibodaux, LA and Toledo Bend sites exhibited the highest average number of nucleotide

substitutions per site with 0.54, followed by Caddo Lake, LA vs Toledo Bend, BellRiver

Landing, LA vs Toledo Bend and Bell River Landing, LA vs Lake Bistineau, LA with values

ranging for 0.50 to 0.53. The comparison of Gheens, LA vs Lake Bistineau, LA revealed the

lowest average of nucleotide substitutions at 0.24.

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Table 4.4. Analysis of molecular variance using AFLP marker and the gapCp gene sequence for six populations of S. molesta from Louisiana and Texas.

Sources of variation Degrees of

freedom Percentage of

variation

AFLP

Among Population 5 6.58

Within Population 234 93.42

Total 239

GapCp sequence

Among Population 5 12.68

Within Population 227 87.31

Total 232

Haplotype analysis of gapCp sequences by DnaSP 5.10 software (Rozas et al., 2003)

revealed a total of 108 haplotypes across locations of which 23 (21%) haplotypes were detected

at Bell River Landing, LA, Thibodaux, LA and Toledo Bend, TX. The number of haplotypes

ranged on average from 1 to 6 across locations while the number of individuals per haplotype

across locations varied from 1 to 63. A total of 122 nucleotide substitutions and 82 indels were

detected among/across the sampled individuals. Non-synonymous substitutions were

substantially greater in number than synonymous variants across exons and across locations

except for the Thibodaux, LA and Caddo Lake, LA sites. The gapCp haplotypes were used to

estimate population differentiation as measured by Wright’s Fst fixation index that produced an

overall value of 0.033. This low value indicates the absence of distinct populations that were

evaluated in this study. Moreover, variance component analysis of gapCp sequences (Table 4)

indicated that the vast majority of variation occurred within populations (87%) which is

consistent with AFLP marker results as described above.

PCA of molecular and morphological traits showed that PC1 eigenvalues for AFLP

markers accounted for 32% of variation observed for root length across all locations while PC1

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eigenvalues for ramets per colony, rhizome length per colony, and leaf width per colony ranged

from 24% to 27%. In contrast, PC1 eigenvalues for gapCp sequences accounted for only small

percentages of observed variation for the five traits varying from 1% to 8%.

4.4. Discussion

Morphological and molecular variation of S. molesta were examined at diverse infested

locations in Louisiana and Texas. Significant levels of variation in both morphological

characters and molecular markers were detected at each of the collection sites. We observed a

general pattern where morphological traits tended to exhibit greater values from the two sites in

north Louisiana vs. the remaining locations in the south. This outcome may be explained in part

by specific environmental conditions at each location. For example, open waters of the two lakes

in north Louisiana likely afforded greater opportunity for increased growth of individual ramets

and colonies vs. the limited growth conditions in the small bayous at Gheens or Thibodaux or at

the edge of Belle River in south Louisiana. Our low correlation values between the traits suggest

that those measured characteristics associated with growth and size of S. molesta acted

independently of each other in a location-specific manner.

PCA of the five traits evaluated in this study revealed more than one cluster within a

single location, the most prominent example found at Lake Bistineau as shown in Fig. 1. Two

clusters were also observed within the remaining sites with the exception of Thibodaux. Presence

of more than one cluster suggests that subpopulations of S. molesta may exist at the different

collection sites, but larger sample sizes and detailed analysis of population structure would be

required to confirm these findings.

The AMOVA results showed that there was considerably more molecular variation

within each population than across collection sites. We interpret this result to mean that each

93

population was variable, but none on average was significantly different than the other. With

similar levels of molecular variation, we suggest that the six populations of S. molesta were

originally introduced and dispersed from common or related sources. Madeira et al. (2003) also

detected relatively high levels of molecular diversity for the related S. minima collected in seven

southern U.S. states, and found low levels of variance (8%) between the regions surveyed.

PCA detected moderate associations of 25% to 30% for AFLP markers and root length,

ramets per colony, rhizome length per colony, and leaf width per colony. These results are not

unexpected given that only 46 polymorphic AFLP loci were used in this study. Future studies

that evaluate more loci or utilize genomic sequences may reveal additional information to link

molecular diversity and reproductive success of S. molesta. In contrast, high levels of gapCp

variation were not associated with any trait evaluated in our study. The lack of association was

most likely due to sampling of only a single locus for traits governed by complex genetic control.

If the S. molesta clones from the six locations originated from a single clonal source,

what is the cause(s) of the extensive molecular and morphological variation observed in this

study? The first factor that may explain the observed variation is numerous somatic mutations

across the genome of S. molesta that could affect reproductive capacity and adaption to changing

environments. Our study uncovered high levels of molecular variation using AFLP markers, and

we detected high levels of variants within gapCp at each location that can impact protein

structure, function, and adaption. Relatively high levels of morphological diversity have been

reported in other clonally propagated species (Clark-Tapia et al., 2005; Ellstrand and Roose,

1987; Widen et al., 1994).

The second factor associated with high diversity levels in S. molesta may be the different

environments encountered during this study. Each environment most likely exerted an important

94

but different impact on genetic makeup and expression of traits of S. molesta at each location.

The practical implication is that different and location-specific control strategies for S. molesta

most likely will be needed. A recent Australian study by Schooler et al. (2011) suggested that

greater attention to the growth dynamics of both S. molesta and C. salviniae, at each infested site

may provide a useful strategy for long-term control of this noxious weed. Consistent with that

assessment was a recent study that showed temperature at different infestation sites had a

dramatic impact on winter survival rates of C. salviniae in north vs. south Louisiana (Tipping et

al., 2012).

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98

CHAPTER 5. SUMMARY AND CONCLUSION

5.1. Identification and Development of Breeding Lines and Populations

Sheath blight (SB) disease caused by the fungus Rhizoctonia solani is one of most

important disease in rice causing important losses in southern U.S. especially in Louisiana where

environmental conditions is very conducive for the growth and proliferation of the fungus.

Several sources of resistance exist but are not adapted to the southern U.S. environment.

Louisiana commercial varieties are highly susceptible to the disease. Hence, it is necessary to

introgress the resistance to our adapted germplasm. Field evaluation of different populations

against SB disease, I was able to identify promising lines with good disease resistance, desirable

plant height and the days to maturity are comparable to the Louisiana varieties. These promising

lines have a significant decrease yield reduction ranges from 4 to 43% as compared to the

susceptible Louisiana varieties. The lines have different sources of resistance (RUSH C99-1166

– ‘LSBR 5’, 09DN157//TRP545/CL161, CTHL/SB2-3, CCDR/PI 658335, PI 658327, PI

658320, PI 658335) and are crossed six susceptible Louisiana varieties (Cocodrie, Catahoula,

CL111, CL151, CL152, CL153). Several generations, F3, F4, and BC2F3, BC3F2 have already

been produced and the progenies of these crosses have already been evaluated. Because the

populations are at early generation stages, further evaluation is needed to advance this material.

5.2. Identification and Evaluation of Non-synonymous SNP Markers for SB Resistance

Resistance to sheath blight disease is a quantitative trait controlled by several genes with

small effects. Many QTLs related to SB resistance have been identified in several populations.

The use of different types of markers with varying levels of polymorphism were used to

genotype populations with hundreds of individuals. Single nucleotide polymorphic (SNPs)

99

markers are the marker of choice because it is more affordable and ease of use. In my study, 83

non-synonymous SNP-based markers with clear polymorphism between and among the lines

selected in Chapter 2 were identified. These non-synonymous SNPs markers mapped to

chromosomes 2, 4, 6, 8, 9, 11, and 12 that were within QTLs previously reported (Nelson et al.

2012; Sanabria, 2015). These markers may be used efficiently in the development of SB resistant

lines through marker-assisted selection strategy.

5.3. Genetic and Phenotypic Diversity of S. molesta in Louisiana and Texas.

The southern Gulf Coast is surrounded with bayous, large lagoons and lakes is favorable

to agriculture and fisheries, rice farming, fishing, and shrimping. However, these industries and

human activities are being slowed down due to the invasive growth of giant aquatic fern called

Salvinia molesta. To develop effective control and management strategies for Louisiana and

Texas, it is important to understand the population diversity of S. molesta both at the genetic and

whole-plant level. Both morphological characters and molecular markers detected on S. molesta

in diverse infested locations in Louisiana and Texas were significantly different at each of the

collection sites. We observed a general pattern where morphological traits tended to exhibit

greater values from the two sites in north Louisiana vs. the remaining locations in the south.

This outcome may be explained in part by specific environmental conditions at each location.

Analysis of molecular variance (AMOVA) showed considerably more molecular variation within

each population than across collection sites. PCA detected moderate associations of 25% to 30%

for AFLP markers and root length, ramets per colony, rhizome length per colony, and leaf width

per colony. On the other hand, high levels of gapCp variation were not associated with any trait

evaluated in our study.

100

But what is the cause(s) of the extensive molecular and morphological variation observed

in this study? If the S. molesta clones from the six locations originated from a single clonal

source. The first factor that may explain the observed variation is numerous somatic mutations

across the genome of S. molesta that could affect reproductive capacity and adaption to changing

environments. Our study uncovered high levels of molecular variation using AFLP markers, and

we detected high levels of variants within gapCp at each location that can impact protein

structure, function, and adaption. Relatively high levels of morphological diversity have been

reported in other clonally propagated species (Clark-Tapia et al., 2005; Ellstrand and Roose,

1987; Widen et al., 1994). The second factor associated with high diversity levels in S. molesta

may be the different environments encountered during this study. Each environment most likely

exerted an important but different impact on genetic makeup and expression of traits of S.

molesta at each location. The practical implication is that different and location-specific control

strategies for S. molesta most likely will be needed.

101

APPENDIX A. RANKING OF 136 nsSNPs MARKERS ACROSS 20 SUSCEPTIBLE RILs OF THE RICECAP SB2 MAPPING POPULATION BASED ON RAW P, HOCHBERG, BONFERRONI, FALSE DISCOVERY AND R-SQUARED VALUES (Sanabria, 2015).

Rank

Marker

F Value

Raw_P-Value

Hochberg

p-value

Stepdown Bonferroni

False Discovery

Rate p-value

R-Squared

1 LOC_Os09g32860 149.154 0 0 0 0 0.892315 2 LOC_Os09g33710 61.04 0 0.00004 0.00004 0 0.772268 3 LOC_Os09g34180 61.04 0 0.00004 0.00004 0 0.772268 4 LOC_Os09g36900 61.04 0 0.00004 0.00004 0 0.772268 5 LOC_Os09g37230 61.04 0 0.00004 0.00004 0 0.772268 6 LOC_Os09g37240 61.04 0 0.00004 0.00004 0 0.772268 7 LOC_Os09g37590 61.04 0 0.00004 0.00004 0 0.772268 8 LOC_Os09g37800 61.04 0 0.00004 0.00004 0 0.772268 9 LOC_Os09g37880 61.04 0 0.00004 0.00004 0 0.772268 10 LOC_Os09g38700 61.04 0 0.00004 0.00004 0 0.772268 11 LOC_Os09g38710 61.04 0 0.00004 0.00004 0 0.772268 12 LOC_Os09g38850 61.04 0 0.00004 0.00004 0 0.772268 13 LOC_Os09g38970 61.04 0 0.00004 0.00004 0 0.772268 14 LOC_Os12g10330 41.633 0 0.00052 0.00053 0.00004 0.698154 15 LOC_Os12g10410 41.633 0 0.00052 0.00053 0.00004 0.698154 16 LOC_Os12g13100 41.633 0 0.00052 0.00053 0.00004 0.698154 17 LOC_Os12g15460 41.633 0 0.00052 0.00053 0.00004 0.698154 18 LOC_Os09g39620 37.145 0.00001 0.00106 0.00106 0.00008 0.673587 19 LOC_Os12g09710 33.113 0.00002 0.00211 0.00211 0.00016 0.56581 20 LOC_Os12g10180 33.113 0.00002 0.00211 0.00211 0.00016 0.56581 21 LOC_Os09g32020 23.457 0.00013 0.01449 0.01462 0.00097 0.483682 22 LOC_Os12g06980 23.457 0.00013 0.01449 0.01462 0.00097 0.483585 23 LOC_Os12g09000 16.856 0.00066 0.07303 0.07303 0.00468 0.449908 24 LOC_Os12g07950 14.722 0.00121 0.13166 0.13166 0.00807 0.351999 25 LOC_Os06g13040 9.778 0.00583 0.62916 0.62916 0.03699 0.3322 26 LOC_Os06g15170 8.954 0.00781 0.83613 0.83613 0.04726 0.284212 27 LOC_Os12g03554 7.147 0.0155 0.9835 1 0.08949 0.263827 28 LOC_Os12g04660 7.147 0.0155 0.9835 1 0.08949 0.263827 29 LOC_Os02g34490 6.283 0.02201 0.9835 1 0.10351 0.258734 30 LOC_Os02g34850 6.283 0.02201 0.9835 1 0.10351 0.258734 31 LOC_Os02g35210 6.283 0.02201 0.9835 1 0.10351 0.258734 32 LOC_Os12g07800 6.451 0.02053 0.9835 1 0.10351 0.255983 33 LOC_Os12g06740 6.451 0.02053 0.9835 1 0.10351 0.242599 34 LOC_Os08g19694 6.193 0.02284 0.9835 1 0.10361 0.241195 35 LOC_Os08g20020 5.721 0.02788 0.9835 1 0.11423 0.241195 36 LOC_Os08g30850 5.721 0.02788 0.9835 1 0.11423 0.187053 37 LOC_Os08g30910 5.765 0.02736 0.9835 1 0.11423 0.187053 38 LOC_Os06g19110 3.852 0.06535 0.9835 1 0.20748 0.17626 39 LOC_Os06g22020 3.852 0.06535 0.9835 1 0.20748 0.17626 40 LOC_Os06g22460 3.852 0.06535 0.9835 1 0.20748 0.17626 41 LOC_Os06g23530 3.852 0.06535 0.9835 1 0.20748 0.17626 42 LOC_Os06g28124 3.852 0.06535 0.9835 1 0.20748 0.17626 43 LOC_Os06g28670 3.852 0.06535 0.9835 1 0.20748 0.17626 44 LOC_Os06g29700 3.852 0.06535 0.9835 1 0.20748 0.17626 45 LOC_Os06g29844 4.142 0.05684 0.9835 1 0.20748 0.17626 46 LOC_Os03g43684 4.142 0.05684 0.9835 1 0.20748 0.165702 47 LOC_Os06g31070 3.575 0.07486 0.9835 1 0.23189 0.120051 48 LOC_Os06g32350 2.204 0.15499 0.9835 1 0.33529 0.120051 49 LOC_Os04g10460 2.204 0.15499 0.9835 1 0.33529 0.117506 50 LOC_Os04g11640 2.204 0.15499 0.9835 1 0.33529 0.117506

APPEDIX A. continued

102

Rank

Marker

F Value

Raw_P-Value

Hochberg

p-value

Stepdown Bonferroni

False Discovery

Rate p-value

R-Squared

51 LOC_Os04g11970 2.204 0.15499 0.9835 1 0.33529 0.117506 52 LOC_Os04g15650 2.397 0.13899 0.9835 1 0.33529 0.117506 53 LOC_Os04g20680 2.397 0.13899 0.9835 1 0.33529 0.117506 54 LOC_Os04g21890 2.397 0.13899 0.9835 1 0.33529 0.117506 55 LOC_Os04g23620 2.397 0.13899 0.9835 1 0.33529 0.117506 56 LOC_Os04g23890 2.397 0.13899 0.9835 1 0.33529 0.117506 57 LOC_Os09g16540 2.397 0.13899 0.9835 1 0.33529 0.109532 58 LOC_Os09g17600 2.397 0.13899 0.9835 1 0.33529 0.109532 59 LOC_Os09g17630 2.397 0.13899 0.9835 1 0.33529 0.109532 60 LOC_Os03g30130 2.456 0.13451 0.9835 1 0.33529 0.109069 61 LOC_Os03g37720 2.456 0.13451 0.9835 1 0.33529 0.109069 62 LOC_Os03g39150 2.166 0.1584 0.9835 1 0.33529 0.109069 63 LOC_Os03g40250 2.166 0.1584 0.9835 1 0.33529 0.109069 64 LOC_Os08g10560 2.214 0.15407 0.9835 1 0.33529 0.107387 65 LOC_Os08g12800 2.214 0.15407 0.9835 1 0.33529 0.107387 66 LOC_Os08g13870 2.214 0.15407 0.9835 1 0.33529 0.107387 67 LOC_Os03g63110 1.475 0.24022 0.9835 1 0.46294 0.076657 68 LOC_Os02g42412 1.473 0.24058 0.9835 1 0.46294 0.075747 69 LOC_Os02g44730 1.473 0.24058 0.9835 1 0.46294 0.075636 70 LOC_Os02g45160 1.473 0.24058 0.9835 1 0.46294 0.075636 71 LOC_Os02g45980 1.473 0.24058 0.9835 1 0.46294 0.075636 72 LOC_Os02g48210 1.494 0.2373 0.9835 1 0.46294 0.075636 73 LOC_Os08g42930 1.203 0.2872 0.9835 1 0.54439 0.062643 74 LOC_Os11g13650 1.043 0.32068 0.9835 1 0.59891 0.062643 75 LOC_Os02g58540 0.929 0.34792 0.9835 1 0.63123 0.054766 76 LOC_Os01g13300 0.929 0.34792 0.9835 1 0.63123 0.049072 77 LOC_Os04g56250 0.898 0.35586 0.9835 1 0.63654 0.049072 78 LOC_Os08g35310 0.851 0.36855 0.9835 1 0.64118 0.04752 79 LOC_Os02g39590 0.851 0.36855 0.9835 1 0.64118 0.045129 80 LOC_Os02g51900 0.753 0.39685 0.9835 1 0.68108 0.045129 81 LOC_Os02g52060 0.615 0.44303 0.9835 1 0.70947 0.045129 82 LOC_Os02g02650 0.536 0.47334 0.9835 1 0.70947 0.04017 83 LOC_Os02g43460 0.536 0.47334 0.9835 1 0.70947 0.033049 84 LOC_Os02g53970 0.536 0.47334 0.9835 1 0.70947 0.02894 85 LOC_Os02g54330 0.536 0.47334 0.9835 1 0.70947 0.02894 86 LOC_Os02g54500 0.533 0.47484 0.9835 1 0.70947 0.02894 87 LOC_Os02g55180 0.533 0.47484 0.9835 1 0.70947 0.02894 88 LOC_Os04g57670 0.533 0.47484 0.9835 1 0.70947 0.028746 89 LOC_Os04g58720 0.533 0.47484 0.9835 1 0.70947 0.028746 90 LOC_Os04g58820 0.533 0.47484 0.9835 1 0.70947 0.028746 91 LOC_Os04g58910 0.533 0.47484 0.9835 1 0.70947 0.028746 92 LOC_Os04g59060 0.508 0.48531 0.9835 1 0.71668 0.028746 93 LOC_Os04g59540 0.433 0.51884 0.9835 1 0.74688 0.028746 94 LOC_Os05g50660 0.424 0.5234 0.9835 1 0.74688 0.028746 95 LOC_Os09g26300 0.424 0.5234 0.9835 1 0.74688 0.027427 96 LOC_Os04g05030 0.343 0.56525 0.9835 1 0.74778 0.023491 97 LOC_Os05g37040 0.343 0.56525 0.9835 1 0.74778 0.022989 98 LOC_Os05g39760 0.356 0.55839 0.9835 1 0.74778 0.022989 99 LOC_Os08g36320 0.362 0.55499 0.9835 1 0.74778 0.020628 100 LOC_Os08g36760 0.379 0.54578 0.9835 1 0.74778 0.020628 101 LOC_Os09g27570 0.379 0.54578 0.9835 1 0.74778 0.020628 102 LOC_Os06g44820 0.379 0.54578 0.9835 1 0.74778 0.019706 103 LOC_Os02g49986 0.137 0.71588 0.9835 1 0.85611 0.019372

APPENDIX A. continued

103

Rank

Marker

F Value

Raw_P-Value

Hochberg

p-value

Stepdown Bonferroni

False Discovery

Rate p-value

R-Squared

104 LOC_Os02g09820 0.137 0.71588 0.9835 1 0.85611 0.018711 105 LOC_Os02g10120 0.137 0.71588 0.9835 1 0.85611 0.018711 106 LOC_Os02g56380 0.127 0.7261 0.9835 1 0.85611 0.007887 107 LOC_Os02g56480 0.143 0.70964 0.9835 1 0.85611 0.007887 108 LOC_Os02g57960 0.143 0.70964 0.9835 1 0.85611 0.007887 109 LOC_Os06g35850 0.143 0.70964 0.9835 1 0.85611 0.007887 110 LOC_Os06g37500 0.143 0.70964 0.9835 1 0.85611 0.007887 111 LOC_Os01g52330 0.112 0.74152 0.9835 1 0.85611 0.007538 112 LOC_Os01g52880 0.112 0.74152 0.9835 1 0.85611 0.007538 113 LOC_Os01g53420 0.112 0.74152 0.9835 1 0.85611 0.007538 114 LOC_Os09g25620 0.143 0.70964 0.9835 1 0.85611 0.007307 115 LOC_Os09g25890 0.143 0.70964 0.9835 1 0.85611 0.007307 116 LOC_Os02g10900 0.139 0.71698 0.9835 1 0.85611 0.006985 117 LOC_Os05g40790 0.132 0.7201 0.9835 1 0.85611 0.006195 118 LOC_Os05g41130 0.132 0.7201 0.9835 1 0.85611 0.006195 119 LOC_Os05g41290 0.132 0.7201 0.9835 1 0.85611 0.006195 120 LOC_Os11g19700 0.042 0.83928 0.9835 1 0.89571 0.002629 121 LOC_Os11g24060 0.042 0.83928 0.9835 1 0.89571 0.002629 122 LOC_Os11g24180 0.042 0.83928 0.9835 1 0.89571 0.002629 123 LOC_Os11g24770 0.042 0.83928 0.9835 1 0.89571 0.002629 124 LOC_Os11g28950 0.047 0.83001 0.9835 1 0.89571 0.002629 125 LOC_Os03g53220 0.047 0.83001 0.9835 1 0.89571 0.002347 126 LOC_Os03g56400 0.047 0.83001 0.9835 1 0.89571 0.002347 127 LOC_Os03g57160 0.047 0.83001 0.9835 1 0.89571 0.002347 128 LOC_Os03g58390 0.047 0.83001 0.9835 1 0.89571 0.002347 129 LOC_Os04g55760 0.031 0.86218 0.9835 1 0.91248 0.00172 130 LOC_Os02g11820 0 0.9835 0.9835 1 0.9835 0.000065 131 LOC_Os01g54350 0 0.9835 0.9835 1 0.9835 0.000024 132 LOC_Os01g54515 0 0.9835 0.9835 1 0.9835 0.000024 133 LOC_Os01g55050 0 0.9835 0.9835 1 0.9835 0.000024 134 LOC_Os01g56040 0 0.9835 0.9835 1 0.9835 0.000024 135 LOC_Os01g57230 0 0.9835 0.9835 1 0.9835 0.000024 136 LOC_Os01g57900 0.001 0.97305 0.9835 1 0.9835 0.000024

104

APPENDIX B. PRIMER SEQUENCES FOR SNP-BASED MARKERS LOACTED IN PREVIOUSLY REPORTED QTL’S FOR SHEATH BLIGHT RESISTANCE (Sanabria, 2015).

Gene

Function

SNP Position

Ref. Allele

Var. Allele

Ref. AA

Var. AA

Primer Ref Forward (Susceptible Allele)

Primer Ref Reverse (Susceptible Allele)

Primer Alt Forward (Resistant Allele)

Primer Alt Reverse (Resistant Allele)

LOC_Os02g02650 THION21 - Plant thionin family protein precursor

975892 T G N T GATGACTGCAGCCCCAACACGAA TGATATGTTGTTGACAGACATCAGCGTGAAT

GGATGACTGCAGCCCCAACAACAC TGATATGTTGTTGACAGACATCAGCGTGAAT

LOC_Os02g11820 GTPase-activating protein, putative, expressed

6114451 T A V E AGCCTGCTAGTGCACAGCCCGT AAAAATGAAGAATGTGACTGCCCCATCA

CAGCCTGCTAGTGCACAGCCACA AAAGAAATGGAAGGTACACAGATCGACTTCTGATA

LOC_Os02g34490 Leucine Rich Repeat family protein, expressed

20661950 G C W S TTGAAGCTCTGAGAGGGAGGTGATCTCTC

ATGTGTATCGGCTCCCATATTGCTTGTTATC

AGCTCTGAGAGGGAGGTGATCTGCG

ATGTGTATCGGCTCCCATATTGCTTGTTATC

LOC_Os02g34850 histone-lysine N-methyltransferase ASHH2, putative, expressed

20899450 T A V D CAAGTACTTCCTCAGCATCCTCCTGCA

GAGATAATTTGTGCAAATGAAACGTATCCTTCAGT

GCACCAAGTACTTCCTCAGCATCCTCCTTAT

CCACATGCAAAAGACCCCAATTCAAG

LOC_Os02g35210 resistance protein, putative 21160861 G A D N GGACTCTGTCCTCAGCAAGCTCATCG CATCTCCTTGGCAATTTGGTAGTGATTCC

ATGGACTCTGTCCTCAGCAAGCTCAACA

CATCTCCTTGGCAATTTGGTAGTGATTCC

LOC_Os02g39590 GDSL-like lipase/acylhydrolase, putative

23887432 T A K M CATGGCCGAGCTTCTGTACCACCA AGCTGAAGTGTTCATTCTTCAGTAGTACATTGTGG

TGGCCGAGCTTCTGTACCGCAT TATGGTTGTAAGCCTGGTGCTCCTGTGTAAT

LOC_Os02g43460 required to maintain repression 1, putative

26228789 C G A G TCGGCGTACGGTGGGGATTGTAC TTTGGTCCATTGTTTCTGACGCATTGT

GGCGTACGGTGGGGATTGAGG TTCCTCCTCTGAGCAATCTTTACATTTCTCTTG

LOC_Os02g44730 tetracycline transporter protein, putative, expressed

27099654 T A M K GGGCAATCTGGTGCAAGTGGGAT TACAACAAGCTGGGCTGGCTTCTATGAC

AGGGCAATCTGGTGCAAGTGAGGA TGGCATTAACTCATGTCTGAAGCTCCG

LOC_Os02g45160 aluminum-activated malate transporter, putative, expressed

27387949 A G S P TGACGGTGCCGGAGGGCTAGT TCGAAGACCACGACAACCGTCATG GACGGTGCCGGAGGGCTCAC AAACACGGTGAGGAACACAGCAAACTG

LOC_Os02g51900 cytokinin-O-glucosyltransferase 2, putative, expressed

31782340 G C H D CAGGCCCGACCTCGTCGCTA TTGCTTTCGCTCTCATATCCTTGCTTTTC

CAGGCCCGACCTCGTCGCTG TTGCTTTCGCTCTCATATCCTTGCTTTTC

LOC_Os02g54330 OsFBDUF14 - F-box and DUF domain containing protein

33307448 C G R T GGATACAGGTGACGAGGAATCCCCTTC

CACGCCATGATCAACCTCCGGT TACAGGTGACGAGGAATCCCCACG CACGCCATGATCAACCTCCGGT

LOC_Os02g54500 WD40-like, putative, expressed

33367587 A G T A CACCCTGCTGCACAGGGAATTACA CAACTATCCACCAGAAAATTAGGCAGTAACAGCTAT

CCTGCTGCACAGGGAATTCGG CAACTATCCACCAGAAAATTAGGCAGTAACAGCTAT

LOC_Os02g55180 ubiquitin carboxyl-terminal hydrolase domain containing protein, expressed

33794880 C T T I CTGTTAACTTGCCCATGAAAACAGAGCATAC

AGTGAGCTTCAGATGCCTGGCCATT

TGTTAACTTGCCCATGAAAACAGAGCAACT

AGTGAGCTTCAGATGCCTGGCCATT

LOC_Os02g56380 OsWAK21 - OsWAK receptor-like cytoplasmic kinase OsWAK-RLCK

34511349 C A A S GATGACAAGCTCAACGCCAAAGTCG CATGAGGAGGTCTGCAATCTCTGTTGC

TTGATGACAAGCTCAACGCCAAAGTCT

CATGAGGAGGTCTGCAATCTCTGTTGC

LOC_Os02g56480 PB1 domain containing protein, expressed

34568863 T C H R GGAGGACGCTGGTGTAGTAGATGGGGT

TCCTACCGGTGCCGGGAAGGTATA GGAGGACGCTGGTGTAGTAGATGGCTC

AGTACTACTTGCCCAAGTACCAGGAGAAGCC

LOC_Os02g58540 RING-H2 finger protein, putative, expressed

35778055 G A A V ATCTGCGTCGCCGGCCTGTC CGTGGGTCCCCAGCCACGTA ATCTGCGTCGCCGGCCTTGT GGCCGGGGAGAGGGAGGAATAAT

LOC_Os04g05030 serine-rich 25 kDa antigen protein, putative, expressed

2441294 G A D N GAGCTGCCAAAGAAAGGTGCCG TTGCACAGCAACAGAAGATGACAAATCTG

CGTGAGCTGCCAAAGAAAGGTGCTA

TTGCACAGCAACAGAAGATGACAAATCTG

LOC_Os04g11970 O-methyltransferase, putative, expressed

6560546 G A A T CGTGGTTCAGGGATGGACGAAATG TATCCTCAAACATGTCGCCAGCGATAA

CGTGGTTCAGGGATGGACGAAAGA TATCCTCAAACATGTCGCCAGCGATAA

LOC_Os04g15650 Leucine Rich Repeat family protein, expressed

8505140 G T G C CAGTGGCATGCCCAGTATGCCTG GGTTTTCGTGGTCCAATGTTGAGCATAG

GCAGTGGCATGCCCAGTATGCTCT GGTTTTCGTGGTCCAATGTTGAGCATAG

LOC_Os04g21890 disease resistance protein RPM1, putative, expressed

12387967 A C Q P AGGATATTATGAAGTGGTGTTGTGGTCGACA

ATAAGTAATCATGCGCTAGCTCTTCCATCGTAGT

AAAGGATATTATGAAGTGGTGTTGTGGTCTTCC

ATAAGTAATCATGCGCTAGCTCTTCCATCGTAGT

LOC_Os04g23620 D-mannose binding lectin family protein

13514379 A C S A CTGCGCCCCACCCTGCCTAT GCAATGACTGCCCAGGGACCAAT CTGCGCCCCACCCTGCCTTG GCAATGACTGCCCAGGGACCAAT

LOC_Os04g23890 AGC_PVPK_like_kin82y.10 - ACG kinases include homologs to PKA, PKG

13640560 T C Q R CAGGGAGGCCATCAGGGAGGA TTGAAGCTCCCCCTGCACTCACA CAGGGAGGCCATCAGGGAGGG TTGAAGCTCCCCCTGCACTCACA

LOC_Os04g56250 OsFBX152 - F-box domain containing protein, expressed

33349688 G A T I AAGGATTCCATCTTCTCCCACTCCAATG

GATTCAAGACGAGGACGGCGAGTG

CAAGGATTCCATCTTCTCCCACTCCAATA

GATTCAAGACGAGGACGGCGAGTG

LOC_Os04g58910 receptor protein kinase TMK1 precursor, putative, expressed

34856814 T C N D TGGGTCGAACTACTGTTGCCATCATTTTT

GTGTGAAGGTGAATGTGACCGGCA GGGTCGAACTACTGTTGCCATCATTCTC

GTGTGAAGGTGAATGTGACCGGCA

APPENDIX B. continued

105

Gene

Function

SNP Position

Ref. Allele

Var. Allele

Ref. AA

Var. AA





LOC_Os04g59060 heat shock protein DnaJ, putative, expressed

34943898 T G I L GCAGCCTTGAGGACATTGCGGAT ATTTCTGTATGGCACTACAAGTAGGTGCTCCA

GCAGCCTTGAGGACATTGCCGAG ATTTCTGTATGGCACTACAAGTAGGTGCTCCA

LOC_Os06g13040 WD domain, G-beta repeat domain containing protein, expressed

7208678 C A G C CACCTCGTCCTGCACGTCCGA CCAAGTTGATGTACGGCTCAGGGTTCT

CCACCTCGTCCTGCACGTCCTT ATTTTATGCTTAACTAGCTTGATGTGATCATGCAAA

LOC_Os06g15170 3-ketoacyl-CoA synthase, putative, expressed

8598272 T C I V CAGGCTGCAGTTGACGACGAGGAT CTCGAGCACGCGAGGCAGGT CAGGCTGCAGTTGACGACGAGTCC CGGCCACCGTGTACCTCGTGAT

LOC_Os06g22020 cytochrome P450, putative 12751175 A G M V TGCCCCACATCTCCCTCCGAG CGCCGCCTCAGTGATCCTGG CTTGCCCCACATCTCCCTCCGTA CGCCGCCTCAGTGATCCTGG

LOC_Os06g22460 disease resistance protein RPM1, putative, expressed

13056419 T C S G CATGGTGGTCAGTGTGTGGGGAATTA

CATCTTCAAATGCATCTTTGCTATCGAACC

TGGTGGTCAGTGTGTGGGGAATTG CATCTTCAAATGCATCTTTGCTATCGAACC

LOC_Os06g23530 pre-mRNA-splicing factor ATP-dependent RNA helicase, putative, expressed

13725000 A C D E AGTGGCGTGATATCAGGAACGACGAT

ACTTGATTGTCACGAACAGCTTCGATAAGC

AGTGGCGTGATATCAGGAACGAGGTG

GTGTAACCTGGGTTGTTTTCCCTGAACC

LOC_Os06g28124 glycosyltransferase, putative, expressed

15968674 T C K R CATCGTCGACTTCAACCAGGACAGCTA

ACCACCCGGGAGAACTCCTCGA TCGTCGACTTCAACCAGGACAGAGG

ACCACCCGGGAGAACTCCTCGA

LOC_Os06g28670 polygalacturonase, putative, expressed

16329889 G T V F CACGGTCACGTCCGACACCAC ACCATACAGAACAGCGCCAGGTTCC

GCACGGTCACGTCCGACACAAA AGAGCACGAACGTGGCGGTGA

LOC_Os06g29700 OsFBD11 - F-box and FBD domain containing protein, expressed

17044919 A G H R CGTCTTCAGCTGATCGTCCGCA GGCTTTCGCATGACAAATAACACAGCTAAATA

CGTCTTCAGCTGATCGTCCGCG GGCTTTCGCATGACAAATAACACAGCTAAATA

LOC_Os06g29844 MATE efflux family protein, putative, expressed

17195755 T G S A GCCCAGGAGATGATACTGCCGGTC CTCACATATTTTCTCTGTCCAAGACTCTTCCTGTT

GCCCAGGAGATGATACTGCCGTGA CAAGCAAATCCGTGTCGCAATTTTG

LOC_Os06g31070 PROLM24 - Prolamin precursor, expressed

18071409 T A K N CAAGAACCGCAATGACCAGTAGCACCT

GGGAGCAGTCACGCAGGCTACAAC CAAGAACCGCAATGACCAGTAGCAAGA

AACCCGTGCAATGAGTTCGTGAGG

LOC_Os06g32350 THION12 - Plant thionin family protein precursor

18827854 A C N K GGACACAACGGTGACAGTCTGAGCTACA

CAATATTTCTGGCTCAATCATTCTTGCCTG

CACAACGGTGACAGTCTGAGCTGCC

CAATATTTCTGGCTCAATCATTCTTGCCTG

LOC_Os06g35850 lectin protein kinase family protein, putative, expressed

20916895 G C R T GCAAAGCAGTGTCATGACTAGATTAAGAGGGAG

TCCAGGATTTTGACCACCATGGACAT

GCAAAGCAGTGTCATGACTAGATTAAGAGGCTC

TCCAGGATTTTGACCACCATGGACAT

LOC_Os06g37500 cytokinin dehydrogenase precursor, putative

22193618 C T V I GATCACCGAGAGCCGACATGTGAAC TGGCGTCCTCACTAGTTACGATGTTTCTTC

GATCACCGAGAGCCGACATGTCATT

TCGTCACTAGCTTCCTCTCTACTGTCCCCTA

LOC_Os06g44820 PPR repeat domain containing protein, putative

27075561 G A E K ATCAAAGATGCTCAGAGGATCCTACCCG

CAGACACTTAAGCTTTGGCGTAGTAGCTTATCTACC

GATCAAAGATGCTCAGAGGATCCTACCCA

CAGACACTTAAGCTTTGGCGTAGTAGCTTATCTACC

LOC_Os08g19694 NB-ARC domain containing protein, expressed

11786501 A C D E AACAGGATACTGTCCCTGAGCTTCGGT

ATGGGAAGTAGTCACCATCATGCAGCTC

CAGGATACTGTCCCTGAGCTTCGCG

ATGGGAAGTAGTCACCATCATGCAGCTC

LOC_Os08g30910 YDG/SRA domain containing protein, expressed

19085103 T C I T TGGCGGGCAAGGACAACCTTCT AGGTCAACTCTTCGAATCTTCAATGAACCC

TGGCGGGCAAGGACAACCTTTC GCTCAACTCTGTACATAAATTCGTCACCAACTTC

LOC_Os08g35310 O-methyltransferase, putative

22277158 C A G C CAGAGCTCTGGTGCCACACTTTCG CCAATACCATCAACAAGGAGGCGAGATAC

GCAGAGCTCTGGTGCCACACTTTCT

GGTTGATTGGCATGTGTGCTCAGTGT

LOC_Os08g36320 decarboxylase, putative, expressed

22876630 T C D G CCTTGGTGGCGTTCTCGCTCAAGTA CAGTACGCGAAGATCTCCCTCTCGG

CTTGGTGGCGTTCTCGCTCAAGAG CAGTACGCGAAGATCTCCCTCTCGG

LOC_Os08g42930 disease resistance protein RGA1, putative, expressed

27130720 A G H R AAGTTTGGCCTGATGGAGCGCA CAAGTCGCCTTCGCAACAACTCAATT

AAGTTTGGCCTGATGGAGCCCG CAAGTCGCCTTCGCAACAACTCAATT

LOC_Os09g16540 protein kinase, putative, expressed

10153331 A G R G CTGACAAAGACCGACATCAGCGAGA GACATGGTTGCCATCCTTCTCCCA GCTGACAAAGACCGACATCAGCGAAG

GACATGGTTGCCATCCTTCTCCCA

LOC_Os09g17600 membrane protein, putative, expressed

10766714 G A R K GAGTTGGCATCTCAAACATGATTCATCG

CAATGTGAATATGTGATACATGCTGTACTGGCTT

GGAGTTGGCATCTCAAACATGATTCAAAA

CAATGTGAATATGTGATACATGCTGTACTGGCTT

LOC_Os09g17630 receptor-like protein kinase 2, putative, expressed

10792494 T C I T TTGAGCCTGCTTGAGGGGCAGAT TCACTATCCTAAAGATTTAAGCAGAGTGTCCATCTT

TTGAGCCTGCTTGAGGGGCAAAC TCACTATCCTAAAGATTTAAGCAGAGTGTCCATCTT

LOC_Os09g25620 CPuORF8 - conserved peptide uORFcontaining transcript, expressed

15385777 A G L S CATCACCGCATCGCAGCTTCAT ACGGCGGGACCATAAATGCCAT CATCACCGCATCGCAGCTTGTC ACGGCGGGACCATAAATGCCAT

LOC_Os09g25890 trehalose-6-phosphate synthase, putative, expressed

15532799 T A F I CATGTCGACGCCGACGGAGAGTAA CGCGTCGGGTTTTTCCTCCACT CATGTCGACGCCGACGGAGAGTAT GCGCGTCGTCGAGGTGCTCT

LOC_Os09g26300 hypro1, putative, expressed 15891490 A G V A GGTGGACGCGCAGCTGGTTGT ACACGACGTAGCCCATCCCGTG GTGGACGCGCAGCTGGTGAC CGTGCGTGTCGTTGTACCGCA

LOC_Os09g27570 OsFBA3 - F-box and FBA domain containing protein, expressed

16748987 A G F S CACAGCAACAAATACAAGGTGGCTAGATGTTT

GCTAGCGTCTCACTGAAAAAGCAAGCAC

CACAGCAACAAATACAAGGTGGCTAGATGTTC

GCTAGCGTCTCACTGAAAAAGCAAGCAC


106

Gene

Function

SNP Position

Ref. Allele

Var. Allele

Ref. AA

Var. AA





LOC_Os09g32860 OsFBX336 - F-box domain containing protein, expressed

19591594 C T L F GGTTGATACACCAATATTGCCTAGCAAAGTCC

TAGAAACCGGTGATCTCCACACTCCG

ATGGTTGATACACCAATATTGCCTAGCAAAGTCT

TAGAAACCGGTGATCTCCACACTCCG

LOC_Os09g33710 Os9bglu33 - beta-glucosidase homologue, expressed

19913544 T G N H CCCAGCATTTGGGACACCTTCTTCA TCATATCTGAACTTATCACTGACCTTGTAATGGTGA

CCAGCATTTGGGACACCTTCAACC CCATGTCATACATAAGCTTTACATCCTCCTGAAA

LOC_Os09g36900 WD domain, G-beta repeat domain containing protein, expressed

21279866 C T P L GGCACGAGTCATCATCATTGTCACG GCCCAACTGAAACTAAAGCCTGCATTCT

GGGCACGAGTCATCATCATTGTCAAA

CCCACTGACATGATAGATTGATAGATTCCTGC

LOC_Os09g37590 OsFBDUF47 - F-box and DUF domain containing protein, expressed

21666818 T C M T AGTGACTTCCACGACGCCTCGC CTCTGTGAACTGGATATTAACTTCCAAAAGCTCC

GACGTAAGTGACTTCCACGACGCCTACT

CTCTGTGAACTGGATATTAACTTCCAAAAGCTCC

LOC_Os09g37880 serine/threonine-protein kinase receptor precursor, putative, expressed

21841580 G C V L GAACACCAGCGCCATTGTCTTCC TGCACGGCCAAGAAGCCGTC CGTCGGTGTCGATGATCGCGTC ATGAACACCGGCAACCTCGTCG

LOC_Os09g38700 STRUBBELIG-RECEPTOR FAMILY 5 precursor, putative, expressed

22245913 C T * * AATGCTCCAGTGACTTCATGTTGACCG

TGATAGCTGTGCTTCTTGCAGCTCTGATT

GAATGCTCCAGTGACTTCATGTTGGCTA

TGATAGCTGTGCTTCTTGCAGCTCTGATT

LOC_Os09g38710 HEAT repeat family protein, putative, expressed

22252462 G A * * GCAGCGCCACCATCCCCATATC ATGGTTGGTCCCTTCTTGTCTTGCG GCAGCGCCACCATCCCCATAAT TCAACAAGATTGCAGACAGGGACACCTAC

LOC_Os09g38850 OsWAK91 - OsWAK receptor-like protein kinase, expressed

22317968 T C * Q GAACACTTTCGAGTGTCATCTCCACCAA

CATTCCAGCTGAACAAACTGGGATAACAAC

ACACTTTCGAGTGTCATCTCCACCCG

CATTCCAGCTGAACAAACTGGGATAACAAC

LOC_Os09g38970 zinc finger family protein, putative, expressed

22381404 T A S R ACGCTGGAAGGCATTAGGAGGATGA ACATCTTATGTTCGGGAGAACCGGAGAG

CACGCTGGAAGGCATTAGGAGGAACT

ACATCTTATGTTCGGGAGAACCGGAGAG

LOC_Os09g39620 protein kinase family protein, putative, expressed

22736162 G A A T CCCTTGTCTCCTCAGCCGGTAGTACTTG

ATGGAAATACAACCGTTGTTGCCTGCT

CCCTTGTCTCCTCAGCCGGTAGTACATA

ATGGAAATACAACCGTTGTTGCCTGCT

LOC_Os11g19700 cycloeucalenol cycloisomerase, putative, expressed

11342380 C A N K CTTGCATGGTTCCAGGTGCAGATC AGTATCTGTCCGGCTGTCGGCTCA TGCATGGTTCCAGGTGCAGCAA CTCCCTAAAACAGGGCGCAACGA

LOC_Os11g24060 permease domain containing protein, putative, expressed

13199356 T C V A CCGGCGTTCGTCACCATCGT GCCCTGTCCAAATTCATCAGGGATCT

CCGGCGTTCGTCACCATGTC GCCCTGTCCAAATTCATCAGGGATCT

LOC_Os11g24180 OsSCP50 - Putative Serine Carboxypeptidase homologue, expressed

13321629 A T V E CTGGTTCGAGGTGGACGTGGACA CAGCAAGCTCGAAACTAATCCGGTGAT

TCTGGTTCGAGGTGGACGTGGTTT ACGCAGGGTCCAGACTCCACCA

LOC_Os11g24770 ankyrin repeat domain containing protein

13648166 T A S C CGCTGCGTGGAAAGGGCAGA CGCACTGACCCGCTCATCACTG ATCGCTGCGTGGAAAGGGCTCT CGCACTGACCCGCTCATCACTG

LOC_Os11g28950 pollen signalling protein with adenylyl cyclase activity, putative, expressed

16287232 T C E G GAAGGCACCTCAGTTTGCAACGGT TGGCTTGTTGCACCCAACTACCTGATAT

GGAAGGCACCTCAGTTTGCAACGAC

TTTGGGTGTTCACTGCCAAATTGGA

LOC_Os12g03554 zinc finger C-x8-C-x5-C-x3-H type family protein

1411478 C T R W AGGGGTGTCCTTGATTGCATGCC CCACCATGCGTTGAAGAAGTGGGT TCATTAGGGGTGTCCTTGATTGCATTGT

CCACCATGCGTTGAAGAAGTGGGT

LOC_Os12g04660 zinc finger, C3HC4 type domain containing protein, expressed

1973059 G C T R ATGCGAGCAGGGCATCCACG TCGCCCAGGTAGTCGGACGCT AATGCGAGCAGGGCATCCACC TCGCCCAGGTAGTCGGACGCT

LOC_Os12g06740 F-box domain containing protein, expressed

3280174 A G I V TCCCCGGCCACGAAAGACGTA CCATGTATCCAATACCTGCGGAAAATCA

CTCCCCGGCCACGAAAGACAAT CCATGTATCCAATACCTGCGGAAAATCA

LOC_Os12g06980 SAP domain containing protein, expressed

3410207 G T Q K CCCATGTACTTCTGAATTCACCCCCTG

TTTCTGACAGGCAAAAATCCAGGAAGC

ACCCATGTACTTCTGAATTCACCCGCTT

AAAACGGAGAAGAACTTCAATGGAAATGTCA

LOC_Os12g07800 S-locus-like receptor protein kinase, putative, expressed

3941715 T C M T CTACACAGAGCAACAAAGGAACGGGAAT

CATATCGCCCACGGCCAAGCT CACAGAGCAACAAAGGAACGGGGAC

CTCGGCCTCACCTTGCTTCACATC

LOC_Os12g07950 transcriptional regulator Sir2 family protein, putative, expressed

4033132 C T R H GCAATTCAACTGGCTTACTCCCAGCTC

TGCTCTCCTCATTTGTCCAAATCAGCTTAC

GCAATTCAACTGGCTTACTCCCAGGAT

TGCTCTCCTCATTTGTCCAAATCAGCTTAC

LOC_Os12g09000 phosphomethylpyrimidine kinase/thiaminphosphate pyrophosphorylase, putative

4709578 T C L S GCAGATGGTGTCCATGTTGGTCAGTT ATGCCGCCAATAGCGACCACAG GCAGATGGTGTCCATGTTGGTCAAAC

TTTCTTGTTTCGGCTACGACACTCGG

LOC_Os12g09710 NBS-LRR disease resistance protein, putative

5128266 T A I N GACTTCTCCCACAAGCCTAGTGAAGCTATGA

GCGCAAGAGCAAAGATGTGGCTG TCCCACAAGCCTAGTGAAGCTGGGT

GCGCAAGAGCAAAGATGTGGCTG

LOC_Os12g10180 NBS-LRR type disease resistance protein Rps1-k-2, putative, expressed

5378630 T G M L CCTCGAGACCAAGTCATCCAGGGTG CTTCTCCAACACCAGCTCAGAAAGATGC

TCGAGACCAAGTCATCCAGGCCC CTTCTCCAACACCAGCTCAGAAAGATGC

LOC_Os12g10410 NB-ARC domain containing protein, expressed

5508921 G C A G GTTCAATTGGCAGCCTAGACATACTCCATG

GATTGTAAGGGGCCCTGGAGGTGA GAGTTCAATTGGCAGCCTAGACATACTCCTTC

GATTGTAAGGGGCCCTGGAGGTGA


107

Gene

Function

SNP Position

Ref. Allele

Var. Allele

Ref. AA

Var. AA





LOC_Os12g13100 WW domain containing protein, expressed

7284433 C T R C CTACCCAGCCAACCGTCGTCCTC GCAAGCAAGCAAGCACCAACTGC CTACCCAGCCAACCGTCGTCGAT GCAAGCAAGCAAGCACCAACTGC

LOC_Os12g15460 pentatricopeptide, putative, expressed

8826281 A G * * GTTCCAGCATTCCATCAAACGCCT GCCTGTGGAAAGGCCTGCGAC TGTTCCAGCATTCCATCAAACAGCC

GCCTGTGGAAAGGCCTGCGAC

108

APPENDIX C. EIGENVALUES AND PROPORTIION OF TOTAL VARIABILITY AMONG S. MOLESTA AS EXPLAINED BY FIRST THREE PRINCIPAL COMPONENTS USING THE MORPHOLOGICAL DATA.

APPENDIX D. CORRELATION BETWEEN THE MORPHOLOGICAL DATA AND THE FIRST THREE PRINCIPAL COMPONENTS. Morphological Traits PC1 PC2 PC3 Colony width (mm) 0.46 0.12 0.73*

Number of ramets per colony 0.28 0.86* 0.22

Rhizome length per colony 0.49* 0.03 0.40

Leaf width per colony (mm) 0.42 -0.39 0.45*

Root length per colony (mm) 0.53* -0.28 -0.21

*Values with the most significant trait that contributes to the variation in each PC

.

APPENDIX E. CORRELATION BETWEEN DISSIMILARITY MATRICES OBTAINED WITH DIFFERENT MARKER TYPES (MANTEL TEST). Morphology AFLP gapCp

Morphology 0.02 0.09

AFLP 0.09

p=0.001 APPENDIX F. SUMMARY OF PEARSON’S LINEAR CORRELATION OF AFLP MARKER AND GAPCP GENE TO MORPHOLOGICAL TRAITS. Morphological Traits AFLP GapCp Colony width (mm) 0.01 0.30

Number of ramets per colony 0.04 0.15

Rhizome length per colony 0.01 0.19

Leaf width per colony (mm) 0.06 0.33

Root length per colony (mm) 0.12 0.06

p < 0.01

Axis Eigenvalue Percent of variation Cumulative

1 2.65 0.53 0.53

2 0.96 0.19 0.72

3 0.66 0.13 0.85

109

APPENDIX G. EIGENVECTORS, EIGENVALUES, INDIVIDUAL AND CUMULATIVE PERCENTAGE OF VARIATION EXPLAINED BY THE FIRST FIVE PRINCIPAL COMPONENTS (PC) AFTER ASSESSING MORPHOLOGICAL TRAITS OF S. MOLESTA FROM LOUISIANA AND TEXAS.

*Values correspond to the most significant variation that contributes in each PC.

Morphological Traits AFLP marker gapCp gene

PC1 PC2 PC3 PC4 PC5 PC1 PC2 PC3 PC4 PC5 Colony width (mm) 0.16 0.37 0.40* 0.02 -0.21 0.02 0.11* -0.01 0.02 -0.03 Number of ramets per colony 0.27 0.36 0.41* 0.14 -0.06 0.02 0.04 0.00 -0.07* -0.05 Rhizome length per colony 0.24* 0.18 0.04 0.13 -0.08 0.00 0.05* 0.04 0.00 0.00 Leaf width per colony (mm) 0.25* 0.18 -0.07 0.07 0.17 0.08* -0.04 0.00 -0.01 -0.01 Root length per colony (mm) 0.32* 0.07 -0.06 -0.15 0.26 0.08* -0.04 0.00 -0.01 0.00 Eigenvalue 13.94 3.18 2.46 1.88 1.61 148.16 50.24 9.58 6.91 2.33 Individual percent 30.31 6.91 5.35 4.09 3.50 60.72 20.59 3.93 2.83 0.95 Accumulated variation (%) 30.31 37.22 42.57 46.66 50.15 60.72 81.31 85.24 88.07 89.03

110

APPENDIX H. PERMISSION LETTER

Dear Dr. Galam Thank you for your email. Please use the below link and choose the appropriate dropdowns to secure permission: https://s100.copyright.com/AppDispatchServlet?publisherName=ELS&contentID=S0304377015300103&orderBeanReset=true Govind Mohan Journal Manager Global Journals Production Tel: +9144 4299 4666 ELSEVIER Ascendas International Tech Park (Crest, 12th Floor), Taramani road, Taramani, Chennai 600 113 Find out some simple ways to share your research data, including features that are directly available when you submit your research article to an Elsevier journal. For assistance, please visit our Customer Support site where you can search for solutions on a range of topics and find answers to frequently asked questions.

From:Elsevier Author FormsDate:28/11/2018 04.46 AM

From:Galam,Dominique<[email protected]>Sent:Tuesday,November27,201811:05PM

111

To:Article_Status(ELS)<[email protected]>Subject:Re:PermissionRequest

*** External email: use caution ***

Sir/Madam,

Iwouldliketorequestyoutokindlygrantthepermissiontousethebelowcitedpublicationaspartofdissertationwork.

Articletitle:MorphologicalandGeneticSurveyofGiantSalviniaPopulationsinLouisianaandTexas

Reference::AQBOT2805

Journaltitle:AquaticBotany

Correspondingauthor:Dr.JamesH.Oard

Firstauthor:Dr.DominiqueGalam

Acceptedmanuscript(uneditedversion)availableonline:29-JUL-2015DOIinformation:10.1016/j.aquabot.2015.07.005

Regards,

DominiqueClarkA.Galam

GraduateStudent

RiceGeneticsLab

SchoolofPlant,EnvironmentalandSoilSciences

104MadisonB.SturgisHall

LouisianaStateUniversity

BatonRouge,LA70803

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[---001:002305:35465---]

112

VITA

Dominique Clark Anolin Galam was born and grew up in Dibuluan, Jones, Isabela, Philippines.

The eldest of the four children of Rolando and Clarita Galam. Graduated with the degree of

Bachelor of Science in Biology at Central Luzon State University, Science City of Munoz,

Nueva Ecija.

In 1999, he started his first job as a Research Assistant at the Philippine Rice Research Institute

where he worked there for 5 years. While working as a research assistant, he was accepted for

Panasonic Scholarships Japan for graduate studies. In the summer of 2006, he started his

Masteral studies where he obtained his Master in Agro-Bioscience in March 2009 at Iwate

University, Iwate, Japan.

He then went back to the Philippine Rice Research Institute and worked as Senior Science

Researcher at the Plant Breeding and Biotechnology Division and worked there for a few

months. At the same year, he was offered by Dr. James Oard of Louisiana State University

Agricultural Center to work in his project -rice breeding and germplasm development.

He was then accepted in the Doctoral program at Louisiana State University in 2012 and was

awarded an assistantship through the School of Plant, Environmental and Soil Sciences under the

supervision of Dr. James H. Oard. After 7 years, he is graduating in the spring of 2019

Documents

Development of Sheath Blight-Resistant Breeding Lines for