Location: Plant, Soil and Nutrition ResearchTitle: Association mapping across numerous traits reveals patterns of functional variation in maize
|WALLACE, JASON - Cornell University - New York|
|ZHANG, NENGYI - Cornell University - New York|
|GIBON, YVES - Max Planck Institute Of Molecular Plant Physiology|
|STITT, MARK - Max Planck Institute Of Molecular Plant Physiology|
|Buckler, Edward - Ed|
Submitted to: PLoS Genetics
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/23/2014
Publication Date: 12/4/2014
Citation: Wallace, J., Bradbury, P., Zhang, N., Gibon, Y., Stitt, M., Buckler IV, E.S. 2014. Association mapping across numerous traits reveals patterns of functional variation in maize. PLoS Genetics. 10(2). doi: 10.1371/journal.pgen.1004845.
Interpretive Summary: Genome-wide association studies (GWAS) find associations between genetic variants, which arise through mutation, and observable traits. Not all variants identified by GWAS directly cause changes in traits, called functional variation, but many do. This research seeks to learn about types of variants that are likely to be identified in GWAS. Information about what types of genetic variants result in functional variation is important, because that will help researchers decide which GWAS results are causal in future studies. This study re-analyzed data for 41 different traits using about 5,000 maize inbred lines and nearly 30 million variants and found around 4800 variants associated with one or more traits. While these variants are enriched in genes, most occur between genes, often in regions responsible for regulating genes. The study also found a significant enrichment in duplicated genes, suggesting that divergence after gene duplication plays a role in trait variation. Overall these analyses provide important insight into the unifying patterns of variation in maize.
Technical Abstract: Phenotypic variation in natural populations results from a combination of genetic effects, environmental effects, and gene-by-environment interactions. Despite the vast amount of genomic data becoming available, many pressing questions remain about the nature of genetic mutations that underlie functional variation. We present the results of combining genome-wide association analysis of 41 different phenotypes in ~5,000 inbred maize lines to analyze patterns of high-resolution genetic association among of 28.9 million single-nucleotide polymorphisms (SNPs) and ~800,000 copy-number variants (CNVs). We show that genic and intergenic regions have opposite patterns of enrichment, minor allele frequencies, and effect sizes, implying tradeoffs among the probability that a given polymorphism will have an effect, the detectable size of that effect, and its frequency in the population. We also find that genes tagged by GWAS are enriched for regulatory functions and are ~50% more likely to have a paralog than expected by chance, indicating that gene regulation and gene duplication are strong drivers of phenotypic variation. These results will likely apply to many other organisms, especially ones with large and complex genomes like maize.