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Identifying SNP markers tightly associated with six major genes in peach [Prunus persica (L.) Batsch] using a high-density SNP array with an objective of marker-assisted selection (MAS)
Authors:Patrick Lambert  Jose Antonio Campoy  Igor Pacheco  Jehan-Baptiste Mauroux  Cassia Da Silva Linge  Diego Micheletti  Daniele Bassi  Laura Rossini  Elisabeth Dirlewanger  Thierry Pascal  Michela Troggio  Maria Jose Aranzana  Andrea Patocchi  Pere Arús
Affiliation:1.GAFL, INRA,Montfavet,France;2.UMR 1332 B.P. INRA, Univ. Bordeaux,Villenave d’Ornon,France;3.Università degli Studi di Milano, DiSAA,Milan,Italy;4.INTA, Universidad de Chile,Santiago,Chile;5.IRTA, Centre de Recerca en Agrigenòmica CSIC-IRTA-UAB-UB,Barcelona,Spain;6.Research and Innovation Centre, Fondazione Edmund Mach (FEM),San Michele all’Adige,Italy;7.Parco Tecnologico Padano,Lodi,Italy;8.Research Station Agroscope,W?denswil,Switzerland
Abstract:One of the applications of genomics is to identify genetic markers linked to loci responsible for variation in phenotypic traits, which could be used in breeding programs to select individuals with favorable alleles, particularly at the seedling stage. With this aim, in the framework of the European project FruitBreedomics, we selected five main peach fruit characters and a resistance trait, controlled by major genes with Mendelian inheritance: fruit flesh color Y, fruit skin pubescence G, fruit shape S, sub-acid fruit D, stone adhesion-flesh texture F-M, and resistance to green peach aphid Rm2. They were all previously mapped in Prunus. We then selected three F1 and three F2 progenies segregating for these characters and developed genetic maps of the linkage groups including the major genes, using the single nucleotide polymorphism (SNP) genome-wide scans obtained with the International Peach SNP Consortium (IPSC) 9K SNP array v1. We identified SNPs co-segregating with the characters in all cases. Their positions were in agreement with the known positions of the major genes. The number of SNPs linked to each of these, as well as the size of the physical regions encompassing them, varied depending on the maps. As a result, the number of useful SNPs for marker-assisted selection varied accordingly. As a whole, this study establishes a sound basis for further development of MAS on these characters. Additionally, we also discussed some limitations that were observed regarding the SNP array efficiency.
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