Dissecting Genome-Wide Association Signals for Loss-of-Function Phenotypes in Sorghum Flavonoid Pigmentation Traits

Abstract

Genome-wide association studies are a powerful method to dissect the genetic basis of traits, although in practice the effects of complex genetic architecture and population structure remain poorly understood. To compare mapping strategies we dissected the genetic control of flavonoid pigmentation traits in the cereal grass sorghum by using high-resolution genotyping-by-sequencing single-nucleotide polymorphism markers. Studying the grain tannin trait, we find that general linear models (GLMs) 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 that accounts for kinship (K) can identify tan1-a, whereas a compressed mixed linear model 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 family (n = 263) using genotyping-by-sequencing markers but lower precision in the mapping of vegetative pigmentation traits suggest that consistent gene-level resolution will likely require larger families or multiple recombinant inbred lines. 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.

A High-Throughput, Field-Based Phenotyping Technology for Tall Biomass Crops

“…Dw2 has been mapped to chromosome 6 (Feltus et al, 2006;Zou et al, 2012;Nagaraja Reddy et al, 2013), and its effect on plant height is frequently detected in GWAS as a large genomic region encompassing almost the entire chromosome 6. This particular result is the consequence of the genetically converted sorghum accessions included in diversity panels such as the one investigated here (Klein et al, 2008;Morris et al, 2013;Zhang et al, 2015). Several linkage disequilibrium and linkage mapping studies also confirmed the location, importance, and effects of these two regions on chromosomes 6 and 9 on plant height (Upadhyaya et al, 2012;Zou et al, 2012;Morris et al, 2013, Nagaraja Reddy et al, 2013Zhang et al, 2015;Zhao et al, 2016).…”

“…This particular result is the consequence of the genetically converted sorghum accessions included in diversity panels such as the one investigated here (Klein et al, 2008;Morris et al, 2013;Zhang et al, 2015). Several linkage disequilibrium and linkage mapping studies also confirmed the location, importance, and effects of these two regions on chromosomes 6 and 9 on plant height (Upadhyaya et al, 2012;Zou et al, 2012;Morris et al, 2013, Nagaraja Reddy et al, 2013Zhang et al, 2015;Zhao et al, 2016). In spite of the similar performance and efficiency of both algorithms to estimate the actual morphological trait, Auto-PHe has the advantage of being an automatic processing pipeline with reduced run time and concomitant cost.…”

“…Maximum geographic and genotypic diversity as well as all sorghum types and races are represented in this panel, which has been used successfully in several association studies (Sukumaran et al, 2012;Morris et al, 2013;Mantilla Perez et al, 2014;Zhao et al, 2016).…”

“…The genome-wide markers used for the association analysis included (1) a public data set of ;260,000 SNPs (http://www.morrislab.org/data) obtained using genotyping-by-sequencing technology (Elshire et al, 2011;Morris et al, 2013); (2) 263 SNPs specifically targeting brassinosteroid biosynthesis and signaling genes (Mantilla Perez et al, 2014); and (3) 54 SNPs specifically developed to cover GA biosynthesis and signaling genes (Zhao et al, 2016). This complete set of SNPs was filtered to include only those with a minor allele frequency greater than 5% and missing data less than 40%.…”

A Genomic Resource for the Development, Improvement, and Exploitation of Sorghum for Bioenergy

“…Since this gene has been mapped in the SAP (Morris et al 2013b), pericarp pigmentation was used as a control in this study to validate the genetic data. As expected, all of the models in GAPIT (GLM, MLM, and CMLM to control for population structure and kinship) identified a single region within the transcript of the Y1 locus ( Sobic.001G397900 ) that was strongly associated with seed color in the BAP (Figure 3).…”