Meta-analysis identifies pleiotropic loci controlling phenotypic trade-offs in sorghum

Abstract

Community association populations are composed of phenotypically and genetically diverse accessions. Once these populations are genotyped, the resulting marker data can be reused by different groups investigating the genetic basis of different traits. Because the same genotypes are observed and scored for a wide range of traits in different environments, these populations represent a unique resource to investigate pleiotropy. Here we assembled a set of 234 separate trait datasets for the Sorghum Association Panel, a group of 406 sorghum genotypes widely employed by the sorghum genetics community. Comparison of genome wide association studies conducted with two independently generated marker sets for this population demonstrate that existing genetic marker sets do not saturate the genome and likely capture only 35-43% of potentially detectable loci controlling variation for traits scored in this population. While limited evidence for pleiotropy was apparent in cross-GWAS comparisons, a multivariate adaptive shrinkage approach recovered both known pleiotropic effects of existing loci and new pleiotropic effects, particularly significant impacts of known dwarfing genes on root architecture. In addition, we identified new loci with pleiotropic effects consistent with known trade-offs in sorghum development. These results demonstrate the potential for mining existing trait datasets from widely used community association populations to enable new discoveries from existing trait datasets as new, denser genetic marker datasets are generated for existing community association populations.

Genome-Wide Association Mapping of Resistance to the Sugarcane Aphid in Sorghum bicolor

“…One MTA on SBI-01 (S1_7584419) was ~1.5 Mb away from the known maturity gene Ma5 (PHYC) 48,49 , while S6_40987299 was 0.7 Mb away from major maturity locus Ma1 (SbPRR37) 50 . The other loci identi ed in this study are also found in the vicinity of QTLs reported in Sorghum QTL Atlas and from other studies 47,51 , with the ones on SBI-03 having the most signi cant associations. Some of the loci were not detected in previous studies compiled in the QTL atlas of Mace et al 47 and are reported here as novel loci identi ed in this study as they were very far from the known maturity loci (Supplementary Table S2-a).…”

Dissecting the Genetic Architecture of Carbon Partitioning in Sorghum Using Multiscale Phenotypes

“…While population genomic studies have historically utilized univariate LMMs, more recent works are finding that multivariate-response linear mixed models (MV-LMM) have higher true-positive rates particularly when correlated traits with low, medium, and high heritabilities are analyzed together in one MV-LMM (Rice et al, 2020 ). The use of MV-LMMs may also provide additional power to detect causal loci exhibiting pleiotropic effects across multiple traits (Mural et al, 2021 ). By using MV-LMMs on combinations of carbon-partitioning traits, we can better understand the interplay among these traits and predict the systemic effects of trait selection on the respective carbon sinks.…”

Dissecting the Genetic Architecture of Carbon Partitioning in Sorghum using Multiscale Phenotypes

“…While population genomic studies have historically utilized univariate LMMs, more recent works are finding that multivariate-response linear mixed models (MV-LMM) have higher true-positive rates particularly when correlated traits with low, medium, and high heritabilities are analyzed together in one MV-LMM [85]. The use of MV-LMMs may also provide additional power to detect causal loci exhibiting 13/26 pleiotropic effects across multiple traits [86]. By using MV-LMMs on combinations of carbon-partitioning traits, we can better understand the interplay among these traits and predict the systemic effects of trait selection on the respective carbon sinks.…”