Background: Fruit quality traits have a significant effect on consumer acceptance and subsequently on peach (Prunus persica (L.) Batsch) consumption. Determining the genetic bases of key fruit quality traits is essential for industry to improve fruit quality and increase consumption. A Bayesian approach embedded in the FlexQTL software increases the accuracy of QTL mapping and the probability of identifying new and validating known QTLs across a wide range of genetic backgrounds.
Results: Phenotypic data of seven F1 low to medium chill full-sib families were collected over two years at two locations and genotyped using the 9K SNP Illumina array. One major QTL for fruit blush was found on linkage group 4 (LG4) at 40–46 cM that explained from 20 to 32% of the total phenotypic variance and showed three QTL alleles of different effects. For SSC, one QTL was mapped on LG5 at 60-72cM and explained from 17 to 39% of the phenotypic variance. A major QTL for TA that co-localized with the major locus for low-acid fruit (D-locus) was mapped at the proximal end of LG5 and explained 35 to 80% of the phenotypic variance. The new QTL for TA on the distal end of LG5 explained 14 to 22% of the phenotypic variance. This QTL co-localized with the QTL for SSC and affected TA only when the first QTL is homozygous for high acidity (epistasis). Haplotype analyses revealed SNP haplotypes and predictive SNP marker(s) associated with desired QTL alleles.
Conclusions: A multi-family-based QTL discovery approach enhanced the ability to discover a new TA QTL and validated other QTLs which were reported in previous studies. Identified predictive SNPs and their original sources will facilitate the selection of parents and/or seedlings that have desired haplotype alleles. Our findings will help peach breeders develop new predictive, DNA-based molecular marker tests for routine use in marker-assisted breeding (MAB).