|LI, XIANRAN - Kansas State University|
|ZHU, CHENGSONG - Kansas State University|
|YEH, CHENG-TING - Iowa State University|
|WU, WEI - Iowa State University|
|TAKACS, ELIZABETH - Cornell University - New York|
|PETSCH, KATHERINE - Cold Spring Harbor Laboratory|
|TIAN, FENG - Cornell University - New York|
|Buckler, Edward - Ed|
|MUEHLBAUER, GARY - University Of Minnesota|
|TIMMERMANS, MARJA C. P. - Cold Spring Harbor Laboratory|
|SCANLON, MICHAEL - Cornell University - New York|
|SCHNABLE, PATRICK - Iowa State University|
|YU, JIANMING - Kansas State University|
Submitted to: Genome Research
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 5/15/2012
Publication Date: 6/14/2012
Publication URL: http://genome.cshlp.org/content/early/2012/06/14/gr.140277.112.abstract
Citation: Li, X., Zhu, C., Yeh, C., Wu, W., Takacs, E.M., Petsch, K.A., Tian, F., Bai, G., Buckler Iv, E.S., Muehlbauer, G.J., Timmermans, M., Scanlon, M.J., Schnable, P.S., Yu, J. 2012. Genic and non-genic contributions to natural variation of quantitative traits in maize. Genome Research. 22:2436-2444.
Interpretive Summary: Many important traits in crop species are quantitative traits and are controlled by many genes with minor effects. The complex genomes of these crop species are major challenges to understand the genetic control of these traits. Here we conducted whole genome scans of quantitative traits to identify trait-associated DNA point mutations and assessed their genomic distribution in maize. The point mutations collectively explained 44 to 59% of the total variation across maize quantitative traits, and 79% of the explained variation could be attributed to mutations located in genes or within upstream promotor regions. Focusing on those regions is a cost-effective approach to study quantitative traits in the species with complex genomes.
Technical Abstract: The complex genomes of many economically important crops present tremendous challenges to understand the genetic control of many quantitative traits with great importance in crop production, adaptation, and evolution. Advances in genomic technology need to be integrated with strategic genetic design and novel perspectives to break new ground. Complementary to individual-gene targeted research, which remains challenging, a global assessment of the genomic distribution of trait-associated SNPs (TASs) discovered from genome scans of quantitative traits can provide insights into the genetic architecture and contribute to the design of future studies. Here we report the first systematic tabulation of the relative contribution of different genomic regions to quantitative trait variation in maize. We found that TASs were enriched in the non-genic regions, particularly within a 5 kb window upstream of genes, which highlights the importance of polymorphisms regulating gene expression in shaping the natural variation. Consistent with these findings, TASs collectively explained 44~59% of the total phenotypic variation across maize quantitative traits, and on average, 79% of the explained variation could be attributed to TASs located in genes or within 5 kb upstream of genes, which together comprise only 13% of the genome. Our findings suggest efficient, cost-effective GWAS in species with complex genomes can focus on genic and promoter regions.