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.

RNA-sequencing Analysis Identifies Genes Associated with Chilling-mediated Endodormancy Release in Apple

“…All of these transcriptome studies involved the heterozygous 'Golden Delicious' apple genome (Velasco et al, 2010). However, the genome sequence of a homozygous GDDH13 doubled-haploid apple line was recently published (Daccord et al, 2017). The estimated number of apple genes has decreased from 63,541 in the original apple genome (Velasco et al, 2010) to 42,140 in the new apple reference genome (Daccord et al, 2017), and many overlapping genes have been filtered out.…”

“…However, the genome sequence of a homozygous GDDH13 doubled-haploid apple line was recently published (Daccord et al, 2017). The estimated number of apple genes has decreased from 63,541 in the original apple genome (Velasco et al, 2010) to 42,140 in the new apple reference genome (Daccord et al, 2017), and many overlapping genes have been filtered out. A transcriptome analysis using the new apple reference genome may enable more accurate mapping, ultimately resulting in a more precise identification of DEGs and gene ontology (GO) analysis.…”

Using Living Germplasm Collections to Characterize, Improve, and Conserve Woody Perennials

“…Some efforts have been made to address these shortcomings-for example, by leveraging multiple germplasm collections simultaneously for genetic mapping. One study examined >1000 apple accessions from six European germplasm collections (France, United Kingdom, Belgium, Italy, and Czech Republic) for flowering and ripening (Urrestarazu et al, 2017). Similarly, >700 peach accessions from four European (France, Spain, and two Italian) germplasm collections and one Chinese germplasm collection were phenotyped for seven traits (Micheletti et al, 2015).…”

Evolutionary and ecological functional genomics, from lab to the wild

“…To date, GWAS have also identified the genetic basis of numerous agronomic traits, speeding up breeding programs of crops such as maize (Jiao et al ., ; Zila et al ., ; Wallace et al ., ; Hu et al ., ; Xu et al ., ) and rice (Huang et al ., , ; McCouch et al ., ; Wang et al ., ; Wang et al ., ), as well as crops with less well‐developed molecular resources such as wheat (Liu et al ., ; Kristensen et al ., ), soybean (Fang et al ., ), barley (Sharma et al ., ), cotton (Fang et al ., ; Du et al ., ), cassava (Kayondo et al ., ), foxtail millet (Jia et al ., ), spinach (Ma et al ., ) and cauliflower (Thorwarth et al ., ). GWAS are a particularly relevant tool for perennial species such as apple (Urrestarazu et al ., ), citrus (Minamikawa et al ., ), eucalyptus (Resende et al ., ) and poplar (Liu et al ., ). It is difficult to make QTL mapping populations for such tree species due to their high genetic loads, high levels of heterozygosity and long generation cycles coupled with large sizes.…”