Upload
darrell-watts
View
222
Download
5
Tags:
Embed Size (px)
Citation preview
1United States Department of Agriculture-Agriculture Research Service (USDA-ARS), U.S. Arid-Land Agricultural Research Center, 21881 North Cardon Lane, Maricopa, AZ 85138, USA 2United States Department of Agriculture-Agricultural Research Service (USDA-ARS), Robert Holley Center for Agriculture and Health, Ithaca, NY 14853, USA 3Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI 48824, USA 4Department of Agronomy, Purdue University, West Lafayette, IN 47907, USA 5Institute for Genomic Diversity, Cornell University, Ithaca, NY 14853, USA 6Department of Plant Breeding and Genetics, Cornell University, Ithaca, NY 14853
Alexander E. Lipka1,2, Maria Magallanes-Lundback3, Ruthie Angelovici3, Sabrina Gonzalez Jorge3, Jacabo Arango3, Eunha Kim3, Dean DellaPenna3, Brenda Owens4, Torbert Rocheford4, Edward S. Buckler2,5,6, and
Michael Gore1
Joint linkage analysis and GWAS in the NAM population identifies genes associated with carotenoids and tocochromanols in maize grain
Summary- Vitamin A deficiency (VAD) and vitamin E deficiency (VED) are major health problems, and maize grain does not provide enough provitamin A and vitamin E
- One solution is biofortification of the maize grain, where carotenoids and tocopherols are boosted through marker assisted selection (MAS) on target genes - Our analysis of carotenoid and tocochromanol levels in grain from the nested association mapping (NAM) population are identifying these genes
- For more information, visit www.harvestplus.org
This work is supported by NSF Grant 0922493 and the USDA-ARS
Source: www.ssi.shimadzu.com
Phenotypic Data CollectionGrain from the NAM population and 200 randomly selected intermated B73xMo17 (IBM) grown at Purdue University, West Lafayette, IN in 2009
> 8,500 high-pressure liquid chromatography (HPLC) ran to measure carotenoid and tocopherol levels in grain
Calculate BLUPsBest linear unbiased predictors (BLUPs) of each phenotype were predicted from a random effects model that accounted for field effects
Highly Heritable and Oligogenic
Position of Identified QTL*
NA
M F
amily
Total Carotenoids
Estimated Effect Size Relative to B73
Position of Identified QTL*
NA
M F
amily
α-Tocopherol
Estimated Effect Size Relative to B73
Common QTL and Allelic Series
Joint Linkage (JL) AnalysisStepwise regression procedure determined significant marker(family) effects with 1106 SNPs genotyped in the NAM population (Buckler et al., 2009)
Genome-Wide Association Study (GWAS)Resampling procedure with 1.6 million HapMap v1 SNPs projected onto the NAM population (Valder et al., 2009; Gore et al., 2009)
dxs2: Chr. 7 14,078,046 to 14,080,704 bp
vte4: Chr. 5 199,527,911 -199,531,733 bp
*Average length of support interval: 3.2 Mb
*Average length of support interval: 14.0 Mb
Average pairwise correlation between QTL allelic effects from JL for these three traits: 0.94
Average pairwise correlation between QTL allelic effects from JL for these three traits: 0.64
Candidate Genes Found for Multiple Traits
Future Work- Combine these data with grain from NAM grown during 2010 field season (currently being measured with HPLC)
- Conduct linkage analysis within each NAM family to identify rare QTL
- Project ~56 million HapMapv2 SNPs onto NAM to conduct GWAS with higher resolution
- Conduct GWAS in the maize 282 association panel using data from the 2009 and 2010 field seasons
Source: Torbert Rocheford
zds1: Chr. 7 17,354,856 to 17,355,388 bp
-All but two compounds have heritability > 0.70-Average heritability: 0.82
| -0.6