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Genetic diversity assessed by genotyping by sequencing (GBS) and for phenological traits in blueberry cultivars.

Ana CampaJuan José Ferreira
Published in: PloS one (2018)
Blueberry is a small fruit crop which includes a complex group of different Vaccinium species of various ploidy levels. Commercial blueberries have been grown in Europe most recently, so there is not much information available about their adaptation into new regions. In this work we investigated adaptation to the environmental conditions of northern Spain, in terms of flowering and ripening seasons, of a set of 70 blueberry cultivars including several of the most important cultivated American species (V. corymbosum, V. virgatum, V. macrocarpon and V. uliginosum) in order to identify which types are best-suited in this geographical area of Europe. Most materials showed high chilling requirements for flowering under local conditions, while materials with low-chilling requirements showed problems in the maturation process of the flowers. Most cultivars were early or mid-season while a relative lack of late-season cultivars was observed. GBS was used for the analysis of genetic diversity in this sample of 70 cultivars. A total of 5255 SNP markers were obtained and a cluster analysis revealed three main groups associated with the ploidy level of the species. A Principal Component Analysis revealed a grouping of the V. corymbosum cultivars according to their chilling requirements. A total of 29 SNPs were identified as being highly informative for diversity analysis and potentially useful for cultivar identification and for breeding purposes. The results obtained from this research should contribute to the expansion of this crop, as well as providing data about genetic diversity useful for the preservation of genetic resources or for future breeding programs.
Keyphrases
  • genetic diversity
  • genome wide
  • single cell
  • climate change
  • public health
  • healthcare
  • gene expression
  • electronic health record
  • arabidopsis thaliana
  • deep learning
  • high throughput
  • copy number
  • mass spectrometry