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

Publication Overview
TitleAssociation Mapping Analysis for Fruit Quality Traits in Prunus persica Using SNP Markers
AuthorsFont I Forcada C, Guajardo V, Chin-Wo SR, Moreno MÁ
TypeJournal Article
Journal NameFrontiers in plant science
Volume9
Year2018
Page(s)2005
CitationFont I Forcada C, Guajardo V, Chin-Wo SR, Moreno MÁ. Association Mapping Analysis for Fruit Quality Traits in Prunus persica Using SNP Markers. Frontiers in plant science. 2018; 9:2005.

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.

Features
This publication contains information about 26 features:
Feature NameUniquenameType
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harvest dateGWAS0001790GWAS
anthocyanin contentGWAS0001791GWAS
flavonoid contentGWAS0001792GWAS
relative antioxidant capacityGWAS0001793GWAS
harvest dateGWAS0001794GWAS
anthocyanin contentGWAS0001795GWAS
sorbitol contentGWAS0001796GWAS
flower date firstGWAS0001797GWAS
harvest dateGWAS0001798GWAS
relative antioxidant capacityGWAS0001799GWAS
flower date firstGWAS0001800GWAS
harvest dateGWAS0001801GWAS
anthocyanin contentGWAS0001802GWAS
sorbitol contentGWAS0001803GWAS
sugar contentGWAS0001804GWAS
harvest dateGWAS0001805GWAS
harvest dateGWAS0001806GWAS
flavonoid contentGWAS0001807GWAS
sorbitol contentGWAS0001808GWAS
sugar contentGWAS0001809GWAS
harvest dateGWAS0001810GWAS
ripening indexGWAS0001811GWAS
harvest dateGWAS0001812GWAS
sorbitol contentGWAS0001813GWAS

Pages

Projects
This publication contains information about 1 projects:
Project NameDescription
Peach_fruit_quality_Forcada_2023
Stocks
This publication contains information about 1 stocks:
Stock NameUniquenameType
Peach_fruit_quality_Forcada_94Peach_fruit_quality_Forcada_94panel