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Evaluation of the DNA barcoding approach to develop a reference data-set for the threatened flora of Sicily

  • Authors: Giovino, A; Marino, P; Domina, G; Scialabba, A; Schicchi, R; Diliberto, G; Rizza, C; Scibetta, S
  • Publication year: 2016
  • Type: Articolo in rivista (Articolo in rivista)
  • OA Link:


The Mediterranean Basin is one of the most significantly altered World Biodiversity Hotspots with extensive habitat loss and fast genetic population erosion, for which urgent biodiversity reconnaissance and preservation actions are required. In particular, Sicily has about 600 taxa classified as threatened or near-threatened. The correct recognition and identification of such biodiversity is required for supporting further activities. The objective of this work is to assess the ability of the DNA barcoding approach to identify different taxonomic groups from a collection of the most threatened plant taxa, throughout natural Sicilian populations. The evaluation of the DNA barcoding core markers, rbcL and matK, was carried out on 30 taxa belonging to 13 families. DNA barcode fragments were recovered from all taxa (100%). The rbcL gene was recovered from 97% of the taxa and matK gene from 73%. In this test, 19 taxa overall (63%) were totally resolved at the specific or subspecific level, by at least one of the core markers. Fourteen of the 17 most threatened taxa (EN, CR) included in this work were totally discriminated. The matK and rbcL locus, respectively, resolved 64% and 48% of the taxa successfully sequenced. The matK gene expressed the highest genetic distance (K2P value), from 0.4% to 8.6%, against a range of 0.1–2% of rbcL gene. However, the rbcL gene appeared a good compromise between PCR, sequencing success and species-level resolution. Cryptic groups suggest the implementation of additional barcoding markers or different primer combinations, particularly for matK, in order to increase the performances. However, this preliminary result confirms the potential of the barcoding approach for quick identification of unknown and heterogeneous plant groups to generate a dedicated reference data-set of the threatened Sicilian flora for a wide range of applications.