A comparative approach for selecting orthologous candidate genes in genome-wide association studies across multiple species

Advances in quantitative genetics have enabled researchers to identify genomic regions associated with changes in phenotype. However, these regions can contain hundreds to thousands of genes, and progressing from genomic regions to causative genes is still challenging. In genome-wide association studies (GWAS) measuring elemental accumulation (ionomic) traits, only 5% of loci contain orthologs of genes known to control the ionome-indicating that many causal genes are still unknown. To identify candidates for the remaining 95% of loci, we developed a method that uses GWAS studies across multiple species to identify conserved causative genes. By Filtering the Results of Multi-species, Analogous, GWAS Experiments (FiReMAGE), we processed the GWAS of 19 ionomic traits in Arabidopsis (Arabidopsis thaliana), soybean (Glycine max), rice (Oryza sativa), maize (Zea mays), and sorghum and identified alleles affecting trait variation at genes conserved across these 5 species. Permutation testing demonstrated that homologous genes were present in loci affecting element accumulation more often than expected. The repeated recovery of homologs at GWAS loci highlights the conservation of ionomic genetic regulators in flowering plants. FiReMAGE identified more candidate genes encoding proteins with known roles in regulating the ionome than expected by chance, validating the approach. These alleles are directly available for improving plant nutrition, food nutritional value, and food safety. FiReMAGE also identified conserved genes with no previously identified function. This provides a path to discover mechanisms of trait variation and conserved genes of previously unknown function via GWAS. The scripts to run FiReMAGE and adapt it to any trait are available on GitHub.