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First molecular phylogeny of Agrilus (Coleoptera: Buprestidae), the largest genus on Earth, with DNA barcode database for forestry pest diagnostics
I. Kelnarova, E. Jendek, VV. Grebennikov, L. Bocak,
Jazyk angličtina Země Anglie, Velká Británie
Typ dokumentu časopisecké články
NLK
ProQuest Central
od 2001-02-01 do Před 1 rokem
Health & Medicine (ProQuest)
od 2001-02-01 do Před 1 rokem
- MeSH
- brouci genetika MeSH
- fylogeneze * MeSH
- lesnictví MeSH
- mitochondriální DNA MeSH
- taxonomické DNA čárové kódování * MeSH
- zvířata MeSH
- Check Tag
- zvířata MeSH
- Publikační typ
- časopisecké články MeSH
All more than 3000 species of Agrilus beetles are phytophagous and some cause economically significant damage to trees and shrubs. Facilitated by international trade, Agrilus species regularly invade new countries and continents. This necessitates a rapid identification of Agrilus species, as the first step for subsequent protective measures. This study provides the first DNA reference library for ~100 Agrilus species from the Northern Hemisphere based on three mitochondrial markers: cox1-5' (DNA barcode fragment), cox1-3', and rrnL. All 329 Agrilus records available in the Barcode of Life Database format, including specimen images and geo data, are released through a public dataset 'Agrilus1 329' available at: dx.doi.org/10.5883/DS-AGRILUS1. All Agrilus species were identified using adult morphology and by using molecular phylogenetic trees, as well as distance- and tree-based algorithms. Most DNA-based species limits agree well with the morphology-based identification. Our results include cases of high intraspecific variability and multiple species para- and polyphyly. DNA barcoding is a powerful species identification tool in Agrilus, although it frequently fails to recover morphologically-delimited Agrilus species-group. Even though the current three-gene database covers only ~3% of the known Agrilus diversity, it contains representatives of all principal lineages from the Northern Hemisphere and represents the most extensive dataset built for DNA-delimited species identification within this genus so far. Molecular data analyses can rapidly and cost-effectively identify an unknown sample, including immature stages and/or non-native taxa, or species not yet formally named.
Canadian Food Inspection Agency 960 Carling Avenue Ottawa ON K1A 0Y9 Canada
Department of Zoology Faculty of Science UP Olomouc Czech Republic
Citace poskytuje Crossref.org
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