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

A Solanum neorickii introgression population providing a powerful complement to the extensively characterized Solanum pennellii population

“…Among the QTLs that were conserved are phenylalanine on chromosome 10 and methionine on chromosome 8. By contrast, the first reported GWAS study on primary metabolism in tomato did not reveal 44 candidate loci for fruit metabolic traits (Sauvage et al ., ), and a larger study by the same group (Bauchet et al ., ) did not identify associations with phenylalanine or methionine levels. This observation thus provides further support for the value of such populations.…”

QTLmapping andGWASreveal candidate genes controlling capsaicinoid content inCapsicum

“…Among them, five and 36 SNPs were also detected as being associated with capsaicin content, and only these reached the FDR threshold for this association. Several GWAS and QTL mapping studies have demonstrated that one locus can control multiple highly correlated traits (Bauchet et al ., ; Ben‐Chaim et al ., ; Crowell et al ., ; Han et al ., ; Wang et al ., ). We detected a high correlation between capsaicin, dihydrocapsaicin and total capsaicinoid contents; therefore, it is possible that some SNPs can affect these traits simultaneously.…”

Trait discovery and editing in tomato

“…In addition to these major mutations, several QTLs controlling fruit size, shape, color intensity, firmness, and composition were mapped. With the development of high throughput metabolome studies, the content of hundreds primary and secondary metabolites was assessed (Carrari et al ., ; Bauchet et al ., ; Tieman et al ., ). Concerning tomato sensory quality, many QTLs for sensory traits were mapped as well as QTLs for volatile organic compounds (Causse et al ., ; Tieman et al ., ) and a few were positionally cloned (Supplementary Table S1).…”

“…The genetic control of fruit anti‐nutritional alkaloids was also deciphered (Itkin et al ., ). GWAS studies coupled with mQTL analyses further identified several loci of interest for improving major fruit quality traits such as malic acid content (Ye et al ., ) or aromas (Bauchet et al ., ; Tieman et al ., ). More recently, Zhu et al .…”

“…The increased availability and low cost of deep sequencing now enabled the integration of ’omics and genetics information. Over the last few years, GWAS combined with extensive mapping of various traits including fruit metabolite content (mGWAS) of up to 398 tomato genotypes enabled both the identification of domestication and improvement sweeps (see for example Tieman et al ., ) along the genome and the dissection of genetic and biochemical bases of fruit primary metabolite and ascorbate contents (Sauvage et al ., ), malate content (Ye et al ., ), pink fruit color (Lin et al ., ), and flavor components (Bauchet et al ., ; Tieman et al ., ). Very recently, association studies were brought to an unprecedented resolution level by integrating SNP data (~26 million SNPs) with fruit transcriptome (RNA‐seq, ~30 000 genes) and metabolome (362 annotated metabolites) datasets from between 399 and 610 accessions of wild tomato species, S. pimpinellifolium , S. lycopersicum var.…”