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Ribosomal DNA polymorphisms reveal genetic structure and a phylogeographic pattern in the Burgundy truffle Tuber aestivum Vittad.

Claudia RiccioniAndrea RubiniAziz TürkoğluBeatrice BelfioriFrancesco Paolocci
Published in: Mycologia (2019)
Ectomycorrhizal ascomycetes belonging to the genus Tuber produce edible fruiting bodies known as truffles. Tuber aestivum, in particular, is a fungus appreciated worldwide and has a natural distribution throughout Europe. Most of the molecular studies conducted on this species have been focused on the question as to whether or not T. aestivum and the morphologically similar T. uncinatum are conspecific. Conversely, only a handful of studies have assessed the level and distribution of genetic diversity and occurrence of phylogeographic patterns in this species. Here, we analyzed the genetic diversity of T. aestivum over a wide geographic range, performing an extensive sampling of specimens from Turkey, which is novel, to the best of our knowledge. We compared the internal transcribed spacer (ITS) profiles of 45 samples collected in different Turkish areas with those of 144 samples from all over Europe. We identified 63 haplotypes, 32 of which were exclusively present in Turkey. The majority of these haplotyes were also population specific. Haplotype network analysis and statistical tests highlighted the presence of a genetic structure and phylogeographic pattern, with three spatially distinct genetic clusters (northeastern Europe, southern Europe, and Turkey), with Turkey representing a diversity hotspot. Based on these results, we hypothesize the presence of glacial refugia for T. aestivum in Turkey, whereas European populations likely experienced a population bottleneck. The possible occurrence of cryptic species among Turkish T. aestivum samples also emerged. Our results are of practical relevance for the marketing of T. aestivum truffles and mycorrhizal seedlings and the preservation of the biodiversity of this species.
Keyphrases
  • genetic diversity
  • genome wide
  • network analysis
  • risk assessment
  • healthcare
  • gene expression
  • dna methylation
  • single cell