Identification of selective sweeps in domesticated apple (Malus × domestica Borkh.)

The domesticated apple (Malus × domestica) is one of the most cultivated plant over the world and is one of the most genetically polymorphic agricultural species. Studying the genetic diversity of the apple germplasm could provide important hints about the domestication process as giving a valuable resource for high resolution genetic mapping, QTL analysis and breeding programs. Advances in next generation sequencing technologies have driven the costs of DNA sequencing down to the point that whole genome re-sequencing (WGS) is now feasible for high diversity, large genome species. The aim of this work is to gain information on genome-wide genetic variability patterns in apple and to identify regions of the genome that may have been selected during the process of plant domestication. SNPs were called from Illumina short reads for 63 apple cultivars representative of European germplasm diversity. The identified SNPs (over 15 millions) were filtered for quality and to avoid repeated and paralogous regions. Additional filters (minor allele frequency and Hardy-Weinberg equilibrium) were applied to discard variants derived from genotyping errors resulting in a final number of 426,321 SNPs . The SNPs kept after the quality filters were used to study the population structure and the genetic diversity. A weak stratification of the analyzed population emerged both from the principal component analysis (PCA) and a model based clustering approach performed using fastStructure. This analysis showed the presence of three subpopulations with a high level of admixture. FST between each couple of sub-groups was 0.055, 0.083 and 0.096 that indicate a moderate differentiation. Two different approaches were used to identify selective sweeps. The first is based on allelic frequencies and the site frequency spectrum (SFS) and it is implemented in the software SweeD. The second is based on linkage disequilibrium patterns and the omega statistic and it is implemented in the software OmegaPlus. Regions that were identified by both softwares were merged and used as candidate regions for positive selection resulting in 1,194 sweeps on the whole genome. A total of 153 gene predictions were extracted from these candidate regions and annotated using Gene Ontology terms and mapping on the KEGG pathway database. Similarity searches were also performed against plant databases to find gene orthologs and to better understand the function of candidates. The annotation revealed that genes under positive selection are involved in pathways like photosynthesis, protein ubiquitination, plant hormone signal transduction and starch and sucrose metabolism. In particular for the plant hormone signal transduction, were identified the auxin influx carrier and a SAUR family protein that lead to cell enlargement and plant growth and the ethylene insensitive protein 2 that leads to fruit ripening and senescence. The genes identified in regions under positive selection that were functionally annotated are consistent with the domestication traits for a better fruit: bigger, tastier and sweeter