» Articles » PMID: 30705685

Association Mapping Analysis for Fruit Quality Traits in Using SNP Markers

Overview
Journal Front Plant Sci
Date 2019 Feb 2
PMID 30705685
Citations 12
Authors
Affiliations
Soon will be listed here.
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.

Citing Articles

Using Quantitative Trait Locus Mapping and Genomic Resources to Improve Breeding Precision in Peaches: Current Insights and Future Prospects.

Hayat U, Ke C, Wang L, Zhu G, Fang W, Wang X Plants (Basel). 2025; 14(2).

PMID: 39861529 PMC: 11768884. DOI: 10.3390/plants14020175.


Two vacuolar invertase inhibitors PpINHa and PpINH3 display opposite effects on fruit sugar accumulation in peach.

Mollah M, Zhang X, Zhao L, Jiang X, Ogutu C, Peng Q Front Plant Sci. 2023; 13:1033805.

PMID: 36589059 PMC: 9795002. DOI: 10.3389/fpls.2022.1033805.


Genetic Diversity and Genome-Wide Association Study of Morphological and Quality Traits in Peach Using Two Spanish Peach Germplasm Collections.

Mas-Gomez J, Cantin C, Moreno M, Martinez-Garcia P Front Plant Sci. 2022; 13:854770.

PMID: 35386674 PMC: 8979248. DOI: 10.3389/fpls.2022.854770.


Corrigendum: Multi-Locus Genome-Wide Association Studies Reveal Fruit Quality Hotspots in Peach Genome.

da Silva Linge C, Cai L, Fu W, Clark J, Worthington M, Rawandoozi Z Front Plant Sci. 2022; 13:879112.

PMID: 35371176 PMC: 8970174. DOI: 10.3389/fpls.2022.879112.


HS-SPME-GC-MS Volatile Profile Characterization of Peach ( L. Batsch) Varieties Grown in the Eastern Balkan Peninsula.

Mihaylova D, Popova A, Vrancheva R, Dincheva I Plants (Basel). 2022; 11(2).

PMID: 35050054 PMC: 8778425. DOI: 10.3390/plants11020166.


References
1.
Pritchard J, Stephens M, Rosenberg N, Donnelly P . Association mapping in structured populations. Am J Hum Genet. 2000; 67(1):170-81. PMC: 1287075. DOI: 10.1086/302959. View

2.
Remington D, Thornsberry J, Matsuoka Y, Wilson L, Whitt S, Doebley J . Structure of linkage disequilibrium and phenotypic associations in the maize genome. Proc Natl Acad Sci U S A. 2001; 98(20):11479-84. PMC: 58755. DOI: 10.1073/pnas.201394398. View

3.
Schulze T, McMahon F . Genetic association mapping at the crossroads: which test and why? Overview and practical guidelines. Am J Med Genet. 2002; 114(1):1-11. DOI: 10.1002/ajmg.10042. View

4.
Etienne C, Rothan C, Moing A, Plomion C, Bodenes C, Svanella-Dumas L . Candidate genes and QTLs for sugar and organic acid content in peach [ Prunus persica (L.) Batsch]. Theor Appl Genet. 2003; 105(1):145-159. DOI: 10.1007/s00122-001-0841-9. View

5.
Quilot B, Wu B, Kervella J, Genard M, Foulongne M, Moreau K . QTL analysis of quality traits in an advanced backcross between Prunus persica cultivars and the wild relative species P. davidiana. Theor Appl Genet. 2004; 109(4):884-97. DOI: 10.1007/s00122-004-1703-z. View