Bivariate genomic analysis identifies a hidden locus associated with bacteria hypersensitive response in Arabidopsis thaliana

Abstract

Multi-phenotype analysis has drawn increasing attention to high-throughput genomic studies, whereas only a few applications have justified the use of multivariate techniques. We applied a recently developed multi-trait analysis method on a small set of bacteria hypersensitive response phenotypes and identified a single novel locus missed by conventional single-trait genome-wide association studies. The detected locus harbors a minor allele that elevates the risk of leaf collapse response to the injection of avrRpm1-modified Pseudomonas syringae (P = 1.66e-08). Candidate gene AT3G32930 with in the detected region and its co-expressed genes showed significantly reduced expression after P. syringae interference. Our results again emphasize that multi-trait analysis should not be neglected in association studies, as the power of specific multi-trait genotype-phenotype maps might only be tractable when jointly considering multiple phenotypes.

Genome‐wide association studies on the phyllosphere microbiome: Embracing complexity in host–microbe interactions

“…This is borne out in an empirical dataset for A. thaliana– microbe interactions, where Wang et al . () used a bivariate GWAS model to discover a novel locus associated with the plant hypersensitive response to P. syringae that varied depending on effector genes present in the infecting strain. Second, multi‐trait GWAS offers improved power when applied to traits that are genetically correlated but somewhat inaccurately measured, analogous to improvements in GWAS performance that result as a consequence of phenotypes being measured across multiple, replicate individuals of each accession (Korol et al ., ).…”

Dual-trait pleiotropic analysis in highly stratified natural populations using genome-wide association summary statistics

“…Previous analyses in those datasets have revealed substantial connections between genotypic and phenotypic variations in this species. The application of association mapping has provided insights into the genetic basis of complex traits (Atwell et al, 2010;Shen et al, 2012;Wang et al, 2017), adaptation (Shen et al, 2014), and evolutionary process. Nevertheless, many essential genotype-phenotype links are still difficult to establish based on the current GWAS data, due to the substantial population stratification highly correlated with the sampling origins of the plants.…”

Dual-trait pleiotropic analysis in highly stratified natural populations using genome-wide association summary statistics

“…Previous analysis in those datasets have revealed substantial connections between genotypic and phenotypic variations in this species. The application of association mapping have provided insights to the genetic basis of complex traits [2, 11, 12], adaptation [13] and evolutionary process. Nevertheless, many essential genotype-phenotype links are still difficult to establish based on the current GWAS data, due to the substantial population stratification highly correlated with the sampling origins of the plants.…”