Genome-Wide Association Mapping of Flowering and Ripening Periods in Apple

Abstract

Deciphering the genetic control of flowering and ripening periods in apple is essential for breeding cultivars adapted to their growing environments. We implemented a large Genome-Wide Association Study (GWAS) at the European level using an association panel of 1,168 different apple genotypes distributed over six locations and phenotyped for these phenological traits. The panel was genotyped at a high-density of SNPs using the Axiom®Apple 480 K SNP array. We ran GWAS with a multi-locus mixed model (MLMM), which handles the putatively confounding effect of significant SNPs elsewhere on the genome. Genomic regions were further investigated to reveal candidate genes responsible for the phenotypic variation. At the whole population level, GWAS retained two SNPs as cofactors on chromosome 9 for flowering period, and six for ripening period (four on chromosome 3, one on chromosome 10 and one on chromosome 16) which, together accounted for 8.9 and 17.2% of the phenotypic variance, respectively. For both traits, SNPs in weak linkage disequilibrium were detected nearby, thus suggesting the existence of allelic heterogeneity. The geographic origins and relationships of apple cultivars accounted for large parts of the phenotypic variation. Variation in genotypic frequency of the SNPs associated with the two traits was connected to the geographic origin of the genotypes (grouped as North+East, West and South Europe), and indicated differential selection in different growing environments. Genes encoding transcription factors containing either NAC or MADS domains were identified as major candidates within the small confidence intervals computed for the associated genomic regions. A strong microsynteny between apple and peach was revealed in all the four confidence interval regions. This study shows how association genetics can unravel the genetic control of important horticultural traits in apple, as well as reduce the confidence intervals of the associated regions identified by linkage mapping approaches. Our findings can be used for the improvement of apple through marker-assisted breeding strategies that take advantage of the accumulating additive effects of the identified SNPs.

Keywords: GWAS; Malus × domestica Borkh.; SNP; adaptive traits; association genetics; germplasm collection; microsynteny; quantitative trait loci.

Figure 1

(A) Distribution of the genotypes according to ranges of genotypic means on flowering period at two different levels: (A1) Whole population; (A2) Geographic groups. The three geographic groups are depicted using the following color codes: Blue = North+East group; Green = West group; Red = South group. (B) Distribution of the genotypes according to ranges of genotypic means on ripening period at two different levels: (B1) Whole population; (B2) Geographic groups. The three geographic groups are depicted using the following color codes: Blue = North+East group; Green = West group; Red = South group.

Figure 2

Scatter plot of the first two dimensions of the Principal Component Analysis (PCA) performed on the 1,168 apple genotypes based on 275,223 SNPs. The geographic groups are depicted using the following color codes: Blue = North+East group; Green = West group; Red = South group; Black = Other.

Figure 3

LD decay according to the physical distance between SNPs. Both the usual r² and the r² after correcting for relatedness and population structure ($r_{\text{vs}}^2$) are given.

Figure 4

Partition of variance at the optimal models according to EBIC for the whole population and the six individual collections for flowering period (A) and ripening period (B). Gray: part of variance explained by structure; Blue: part of variance explained by SNPs retained as cofactors; Green: part of variance explained by kinship; Red: residual variance.