|MORRIS, GEOFFREY - University Of South Carolina|
|RHODES, DAVINA - University Of South Carolina|
|BRENTON, ZACHARY - University Of South Carolina|
|RAMU, PUNNA - International Crops Research Institute For Semi-Arid Tropics (ICRISAT) - India|
|THAYIL, VINAYAN MADHUMA - International Crops Research Institute For Semi-Arid Tropics (ICRISAT) - India|
|DESHPANDE, SHANTOSH - International Crops Research Institute For Semi-Arid Tropics (ICRISAT) - India|
|HASH, THOMAS - International Crops Research Institute For Semi-Arid Tropics (ICRISAT) - India|
|ACHARYA, CHARLOTTE - Cornell University|
|MITCHELL, SHARON - Cornell University|
|Buckler, Edward - Ed|
|YU, JIANMING - Iowa State University|
|KRESOVICH, STEPHEN - University Of South Carolina|
Submitted to: Genes, Genomes, Genetics
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/11/2013
Publication Date: 11/1/2013
Citation: Morris, G.P., Rhodes, D.H., Brenton, Z., Ramu, P., Thayil, V.L., Deshpande, S., Hash, T.C., Acharya, C., Mitchell, S.E., Buckler IV, E.S., Yu, J., Kresovich, S. 2013. Dissecting genome-wide association signals for loss-of-function phenotypes in sorghum flavonoid pigmentation traits. Genes, Genomes, Genetics. 3(11):2085-2094.
Interpretive Summary: We found that mapping in a biparental family using high-density SNP markers can achieve gene resolution. Traditionally, high-resolution SNP maps have not been used for biparental families due to technical limitations and the expectation that the small number of recombination events limits the utility of greater marker density. Given the substantial investment that has already been made in RIL development, the cost-effectiveness of GBS, and the suitability of the system for “genotype once, phenotype many times” approach, a broader effort to make high-density genotypes available for existing advanced mapping populations seems warranted. As genomic coverage increases, imputation methods improve, and mapping populations are refined and expanded, genome-wide mapping approaches will increasingly need to be optimized to identify causative variants as opposed to tagging SNPs. Given the ever-lowering costs of sequencing vs. the high cost of candidate gene validation efforts, the use of whole-genome resequencing to increase the resolution of mapping studies is likely to be cost effective. Although this study of relatively simple pigmentation traits highlights the trade-offs between population- and family-based mapping approaches because of the complexity of association signals, in either approach high density genotyping can facilitate gene resolution mapping of traits.
Technical Abstract: Genome-wide association studies (GWAS) are a powerful method to dissect the genetic basis of traits, though in practice the effects of complex genetic architecture and population structure remain poorly understood. To compare mapping strategies we dissect the genetic control of flavonoid pigmentation traits in the cereal grass sorghum using high-resolution genotyping-by-sequencing (GBS) SNP markers. Studying the grain tannin trait, we find that General Linear Models (GLM) are not able to precisely map tan1-a, a known loss-of-function allele of the Tannin1 gene, with either a small panel (n= 142) or large association panel (n = 336), and that indirect associations limit the mapping of the Tannin1 locus to Mb-resolution. A GLM that accounts for population structure (Q) or standard Mixed Linear Model (MLM) that accounts for kinship (K) can identify tan1-a, while compressed MLMs performs worse than the naive GLM. Interestingly, a simple loss-of-function genome scan, for genotype-phenotype covariation only in the putative loss-of-function allele, is able to precisely identify the Tannin1 gene without considering relatedness. We also find that the tan1-a allele can be mapped with gene resolution in a biparental recombinant inbred line (RIL) family (n = 263) using GBS markers, but lower precision in the mapping of vegetative pigmentation traits suggest that consistent gene-level resolution will likely require larger families or multiple RILs. These findings highlight that complex association signals can emerge from even the simplest traits given epistasis and structured alleles, but that gene-resolution mapping of these traits is possible with high marker density and appropriate models.