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Grass pollen is one of the major causes of allergy. Aerobiological monitoring is a necessary element of the complex of anti-allergic measures, but the similar pollen morphology of Poaceae species makes it challenging to discriminate species in airborne pollen mixes, which impairs the quality of aerobiological monitoring. One of the solutions to this problem is the metabarcoding approach employing DNA barcodes for taxonomical identification of species in a mix by high-throughput sequencing of the pollen DNA. A diverse set of 14 grass species of different genera were selected to create a local reference database of nuclear ITS1, ITS2, 5′-ETS, and plastome trnL-F DNA barcodes. Sequences for the database were Sanger sequenced from live field and herbarium specimens and collected from GenBank. New Poaceae-specific primers for 5′-ETS were designed and tested to obtain a 5′-ETS region less than 600 bp long, suitable for high-throughput sequencing. The DNA extraction method for single-species pollen samples and mixes was optimized to increase the yield for amplification and sequencing of pollen DNA. Barcode sequences were analyzed and compared by the barcoding gap and intra- and interspecific distances. Their capability to correctly identify grass pollen was tested on artificial pollen mixes of various complexity. Metabarcoding analysis of the artificial pollen mixes showed that nuclear DNA barcodes ITS1, ITS2, and 5′-ETS proved to be more efficient than the plastome barcode in both amplification from pollen DNA and identification of grass species. Although the metabarcoding results were qualitatively congruent with the actual composition of the pollen mixes in most cases, the quantitative results based on read-counts did not match the actual ratio of pollen grains in the mixes.

Assessment of ITS1, ITS2, 5′-ETS, and trnL-F DNA Barcodes for Metabarcoding of Poaceae Pollen