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DNA metabarcoding of airborne pollen: new protocols for improved taxonomic identification of environmental samples
Authors:Kleopatra Leontidou  Cristiano Vernesi  Johannes De Groeve  Fabiana Cristofolini  Despoina Vokou  Antonella Cristofori
Institution:1.Department of Biodiversity and Molecular Ecology, Research and Innovation Centre,Fondazione Edmund Mach,San Michele all’Adige,Italy;2.Department of Ecology, School of Biology,Aristotle University of Thessaloniki,Thessaloniki,Greece;3.Department of Geography,Ghent University,Ghent,Belgium
Abstract:Metabarcoding is a promising DNA-based method for identifying airborne pollen from environmental samples with advantages over microscopic methods. Sample preparation and DNA extraction are of fundamental importance for obtaining an optimal DNA yield. Currently, there is no standard procedure for these steps, especially for gravimetric pollen samplers. Therefore, the aim of this study was to develop protocols for processing environmental samples for pollen DNA extraction and for metabarcoding analysis and to assess the efficacy of these protocols for the taxonomic assignment of airborne pollen collected by gravimetric (Tauber trap) and volumetric (Hirst-type trap) samplers. Protocols were tested across an increasing complexity of samples, from pure single-species pollen to environmental multi-species samples. A short fragment (about 150 base pairs) of the chloroplast trnL gene was amplified using universal primers for plants. After PCR amplification, amplicons were Sanger-sequenced and taxonomic assignment was accomplished by comparison with a custom-made reference database including chloroplast DNA sequences from most of the anemophilous taxa occurring in the study area (Trentino, northern Italy), representing 46 plant families. Using the classical morphological pollen analysis as a benchmark, we show that DNA metabarcoding is efficient and applicable even in complex samples, provided that protocols for sample preparation, DNA extraction, and metabarcoding analysis are carefully optimized.
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