Joint linkage analysis and GWAS in the NAM population identifies genes
associated with carotenoids and tocochromanols in maize grain
Alexander E. Lipka1,2, Maria Magallanes-Lundback3, Ruthie Angelovici3, Sabrina Gonzalez Jorge3, Jacabo
3
3
3
4
4
2,5,6
Arango , Eunha Kim , Dean DellaPenna , Brenda Owens , Torbert Rocheford , Edward S. Buckler , and
1
Michael Gore
ael54@cornell.edu
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
Highly Heritable and Oligogenic
Summary
Future Work
- 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
- 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
- One solution is biofortification of the maize grain, where
carotenoids and tocopherols are boosted through marker
assisted selection (MAS) on target genes
- Project ~56 million HapMapv2 SNPs onto NAM to
conduct GWAS with higher resolution
- 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
- Conduct GWAS in the maize 282 association panel
using data from the 2009 and 2010 field seasons
-All but two compounds have heritability > 0.70
-Average heritability: 0.82
Common QTL and Allelic Series
Phenotypic Data Collection
zds1: Chr. 7 17,354,856 to 17,355,388 bp
dxs2: Chr. 7 14,078,046 to 14,080,704 bp
Total Carotenoids
Grain from the NAM population
and 200 randomly selected
intermated B73xMo17 (IBM)
grown at Purdue University,
West Lafayette, IN in 2009
NAM Family
Source: Torbert Rocheford
Candidate Genes Found for Multiple Traits
> 8,500 high-pressure liquid
chromatography (HPLC) ran to
measure carotenoid and
tocopherol levels in grain
Source: www.ssi.shimadzu.com
Calculate BLUPs
Best linear unbiased predictors (BLUPs) of
each phenotype were predicted from a
random effects model that accounted for
field effects
Position of Identified QTL*
Estimated Effect Size Relative to B73
Average pairwise correlation between QTL allelic effects from
JL for these three traits: 0.94
*Average length of support interval: 3.2 Mb
α-Tocopherol
vte4: Chr. 5 199,527,911 -199,531,733 bp
Joint Linkage (JL) Analysis
NAM Family
Stepwise 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)
This work is supported by NSF Grant
0922493 and the USDA-ARS
Position of Identified QTL*
|
-0.6
Estimated Effect Size Relative to B73
*Average length of support interval: 14.0 Mb
Average pairwise correlation between QTL allelic effects from
JL for these three traits: 0.64