Looking Beyond GWAS: Identifying Functional Roles of SNPs Using Metabolic Networks in Arabidopsis and Populus

Studies aimed at improving agricultural yield and understanding adaptive processes have focused on explaining genetic sources of phenotypic variation. GWAS identifies the genetic background behind a trait by examining associations between phenotypes and single-nucleotide polymorphisms (SNPs). Although such studies are common, they often lack the power required to uncover relatively small effect sizes conferred by most loci and are not directly informative of the governing biological mechanisms. SNPeffect is a complementary analysis that offers genotype-to-phenotype interpretations by constructing scenarios for the mechanistic roles of SNPs in enzyme-coding (or regulatory) regions, integrating metabolomics, proteomics, and metabolic network information into a self-consistent narrative. SNPeffect can thus be used a posteriori to functionally explain GWAS hits or a priori to generate linkages between SNPs, genes, enzymes, metabolites and phenotypes, to be used as priors in GWAS and other plant breeding techniques.

SNPeffect was used to explain differential growth and metabolite accumulation in A.thaliana and P. trichocarpa accessions as the outcome of activating and inactivating SNPs in enzyme-coding regions of the genotypes. To this end, we also constructed a P.trichocarpa genome-scale metabolic model, first for a perennial woody tree. As expected, our results indicate that plant growth is a complex polygenic trait governed by carbon and energy partitioning. Growth-affecting SNPs were found to be primarily in glycolysis, amino-acid, and energy metabolism. Faster-growing Arabidopsis genotypes were predicted to have higher fluxes through protein metabolism pathways and employ the energy efficient purine salvage pathway as opposed to de novo purine biosynthesis for generating nucleotides. In poplar, growth-determining SNPs with an upregulating role were in genes from cellulose and lignin biosynthesis, amino acid, and energy metabolism, in line with breeding strategies targeting pathways governing carbon and energy partition. SNPeffect also identified (putatively) functional SNPs in both species, distributed among pathways such as glycolysis, folate, and pyrimidine metabolism.