Association Mapping Analysis for Fruit Quality Traits in Prunus persica Using SNP Markers.

ABSTRACT: The identification of genes involved in variation of peach fruit quality would assist breeders to create new cultivars with improved fruit quality. Peach is a genetic and genomic model within the Rosaceae. A large quantity of useful data suitable for fine mapping using Single Nucleotide Polymorphisms (SNPs) from the peach genome sequence was used in this study. A set of 94 individuals from a peach germplasm collection was phenotyped and genotyped, including local Spanish and modern cultivars maintained at the Experimental Station of Aula Dei, Spain. Phenotypic evaluation based on agronomical, pomological and fruit quality traits was performed at least 3 years. A set of 4,558 out of a total of 8,144 SNPs markers developed by the Illumina Infinium BeadArray (v1.0) technology platform, covering the peach genome, were analyzed for population structure analysis and genome-wide association studies (GWAS). Population structure analysis identified two subpopulations, with admixture within them. While one subpopulation contains only modern cultivars, the other one is formed by local Spanish and several modern cultivars from international breeding programs. To test the marker trait associations between markers and phenotypic traits, four models comprising both general linear model (GLM) and mixed linear model (MLM) were selected. The MLM approach using co-ancestry values from population structure and kinship estimates (K model) identified a maximum of 347 significant associations between markers and traits. The associations found appeared to map within the interval where many candidate genes involved in different pathways are predicted in the peach genome. These results represent a promising situation for GWAS in the identification of SNP variants associated to fruit quality traits, potentially applicable in peach breeding programs.

SUBMITTER: Font I Forcada C 

PROVIDER: S-EPMC6344403 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature