Abstract
BackgroundGenome structural variations (SVs) have been associated with key traits in a wide range of agronomically important species; however, SV profiles of peach and their functional impacts remain largely unexplored.ResultsHere, we present an integrated map of 202,273 SVs from 336 peach genomes. A substantial number of SVs have been selected during peach domestication and improvement, which together affect 2268 genes. Genome-wide association studies of 26 agronomic traits using these SVs identify a number of candidate causal variants. A 9-bp insertion in Prupe.4G186800, which encodes a NAC transcription factor, is shown to be associated with early fruit maturity, and a 487-bp deletion in the promoter of PpMYB10.1 is associated with flesh color around the stone. In addition, a 1.67 Mb inversion is highly associated with fruit shape, and a gene adjacent to the inversion breakpoint, PpOFP1, regulates flat shape formation.ConclusionsThe integrated peach SV map and the identified candidate genes and variants represent valuable resources for future genomic research and breeding in peach.
Highlights
Structural variations (SVs), comprising insertions/deletions, duplications, inversions, and translocations, are widely present in genomes [1,2,3,4]
We analyzed the putative effects of the SVs on the genome during peach domestication and improvement and found that almost all genes in peach were affected by SVs and that the very few unaffected genes were almost all involved in core biological processes
A Genome-wide association studies (GWAS) approach using SVs was found to be more efficient than GWAS using single nucleotide polymorphism (SNP) in identifying candidate genes and causal variants, and based on the SV dataset we generated here, we performed GWAS for 26 peach agronomic traits
Summary
Structural variations (SVs), comprising insertions/deletions (indels), duplications, inversions, and translocations, are widely present in genomes [1,2,3,4]. A pioneer study using SV data for GWAS in plants was reported in cucumber, where a large duplication controlling the reproductive morphology trait was detected [8]. Such an approach represents a more direct method for identifying candidate genes and casual variants, and the development of new bioinformatics methodologies, including more tools for analyzing SVs, has further enabled genome-wide SV mining. Genome structural variations (SVs) have been associated with key traits in a wide range of agronomically important species; SV profiles of peach and their functional impacts remain largely unexplored
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