Identification of major loci and genomic regions controlling acid and volatile content in tomato fruit: implications for flavor improvement

TLDR

Plant metabolites are crucial for food security because they influence crop yield and nutritional quality. The study profiled 60 metabolites across 300 tomato accessions and used 10,000 SNP markers to perform GWAS, followed by linkage‑disequilibrium analysis and allele mining to identify candidate genes. The GWAS uncovered 79 large‑effect associations for 13 primary and 19 secondary metabolites, clustered into four genomic regions, including two linked to fruit acidity and phenylpropanoid volatile production, demonstrating complex regulation and the utility of GWAS for crop improvement.

Abstract

Plant metabolites are important to world food security due to their roles in crop yield and nutritional quality. Here we report the metabolic profile of 300 tomato accessions (Solanum lycopersicum and related wild species) by quantifying 60 primary and secondary metabolites, including volatile organic compounds, over a period of 2 yr. Metabolite content and genetic inheritance of metabolites varied broadly, both within and between different genetic groups. Using genotype information gained from 10 000 single nucleotide polymorphism markers, we performed a metabolite genome-wide association mapping (GWAS) study. We identified 79 associations influencing 13 primary and 19 secondary metabolites with large effects at high resolution. Four genome regions were detected, highlighting clusters of associations controlling the variation of several metabolites. Local linkage disequilibrium analysis and allele mining identified possible candidate genes which may modulate the content of metabolites that are of significant importance for human diet and fruit consumption. We precisely characterized two associations involved in fruit acidity and phenylpropanoid volatile production. Taken together, this study reveals complex and distinct metabolite regulation in tomato subspecies and demonstrates that GWAS is a powerful tool for gene-metabolite annotation and identification, pathways elucidation, and further crop improvement.