Novel genomic approaches unravel genetic architecture of complex traits in apple

Abstract

BackgroundUnderstanding the genetic architecture of quantitative traits is important for developing genome-based crop improvement methods. Genome-wide association study (GWAS) is a powerful technique for mining novel functional variants. Using a family-based design involving 1,200 apple (Malus × domestica Borkh.) seedlings genotyped for an 8K SNP array, we report the first systematic evaluation of the relative contributions of different genomic regions to various traits related to eating quality and susceptibility to some physiological disorders. Single-SNP analyses models that accounted for population structure, or not, were compared with models fitting all markers simultaneously. The patterns of linkage disequilibrium (LD) were also investigated.ResultsA high degree of LD even at longer distances between markers was observed, and the patterns of LD decay were similar across successive generations. Genomic regions were identified, some of which coincided with known candidate genes, with significant effects on various traits. Phenotypic variation explained by the loci identified through a whole-genome scan ranged from 3% to 25% across different traits, while fitting all markers simultaneously generally provided heritability estimates close to those from pedigree-based analysis. Results from ‘Q+K’ and ‘K’ models were very similar, suggesting that the SNP-based kinship matrix captures most of the underlying population structure. Correlations between allele substitution effects obtained from single-marker and all-marker analyses were about 0.90 for all traits. Use of SNP-derived realized relationships in linear mixed models provided a better goodness-of-fit than pedigree-based expected relationships. Genomic regions with probable pleiotropic effects were supported by the corresponding higher linkage group (LG) level estimated genetic correlations.ConclusionsThe accuracy of artificial selection in plants species can be increased by using more precise marker-derived estimates of realized coefficients of relationships. All-marker analyses that indirectly account for population- and pedigree structure will be a credible alternative to single-SNP analyses in GWAS. This study revealed large differences in the genetic architecture of apple fruit traits, and the marker-trait associations identified here will help develop genome-based breeding methods for apple cultivar development.

Identification and validation of a QTL influencing bitter pit symptoms in apple (Malus × domestica)

“…To this end, a single major QTL for bitter pit susceptibility was identified which mapped to LG16 of the map developed from the cross 'Redchief' × 'X6688' associated with two SSR markers; Hi22f06 and CH05c06. The QTL identified is in a similar position to markers strongly associated with bitter pit reported by Kumar et al (2013), who used SNPs from the IRSC whole genome genotyping array developed for apple by Chagne et al (2012) to identify trait-genotype associations using a total of 1,200 seedlings where bitter pit was scored as a binomial trait, and through mapping of the SNP marker most strongly associated with bitterpit incidence in that investigation, we have demonstrated that the QTL identified in the progenies mapped here is the same QTL identified by Kumar et al (2013). Bitter pit severity has been shown to be influenced by the environment (Ferguson and Watkins 1989), and the severity of bitter pit symptoms expressed by a genotype can vary widely depending on the environmental conditions and the stage of maturity of the plant.…”

“…Whilst SNP markers, such as those of the IRSC array employed by Kumar et al (2013), have the advantage of being abundant and widely distributed throughout the genomes of eukaryotic organisms (Schlotterer 2000;Toth et al 2000) they are binary in nature, and thus contain less information than multi-allelic marker types, with reports estimating that three or more SNPs are required in a haplotype block to contain the same information as a single SSR marker at any given locus (Rafalski 2002). …”

“…To determine if the QTL on LG16 in the present investigation was the same QTL identified in a previous study (Kumar et al 2013), primer pairs were designed to amplify the region of LG16 containing the SNP ss475883359 (a SNP contained in a gene encoding a leukoanthocyanidin reductase; LAR-1 MDP0000279135) most significantly associated with bitter pit incidence in the report of Kumar et al (2013). The primer pairs were designed using PRIMER3 to amplify a product of 335 bp with a Tm of 55-65°C (optimum 60°C), a primer length of 20-24 bp (optimum 22 bp) and a 2 bp GC-clamp at the 5' end.…”

“…Sequencing of the amplicons designed for marker ss475883359 most significantly associated with bitterpit susceptibility in the study of Kumar et al (2013) revealed the expected SNP in both parental genotypes of the R×X mapping population and thus the marker segregated approximating to a Mendelian 1:2:1 ratio in the mapping population. When the segregation data for the marker was incorporated into the outline SSR map developed for the population, the marker co-segregated with SSR marker Hi22f06 with no recombination events observed between the segregation patterns of the two markers.…”

“…Recently, Kumar et al (2013), using a factorial (4×2) female×male mating design, raised a set of fullsib progenies with sizes ranging from 40 -350 seedlings (total n=1200) in which bitter pit was scored as a binomial trait (i.e. present or absent in the seedlings).…”