A validated workflow for rapid taxonomic assignment and monitoring of a national fauna of bees (Apiformes) using high throughput DNA barcoding. (8th October 2019)

• Record Type: Journal Article
• Authors: Creedy, Thomas J.; Norman, Hannah; Tang, Cuong Q.; Qing Chin, Kai; Andujar, Carmelo; Arribas, Paula; O'Connor, Rory S.; Carvell, Claire; Notton, David G.; Vogler, Alfried P.
• Is Part Of: Molecular ecology resources. Volume 20:Number 1(2020:Jan.)
• Page Start: 40
• Page End: 53
• Publication Date: 2019-10-08
• Subjects: community barcoding -- contamination -- double dual tagging -- illumina sequencing -- pollinators; Molecular ecology -- Periodicals; 572.8
• DOI: 10.1111/1755-0998.13056
• Languages: English
• ISSNs: 1755-098X

Abstract

Abstract: Improved taxonomic methods are needed to quantify declining populations of insect pollinators. This study devises a high‐throughput DNA barcoding protocol for a regional fauna (United Kingdom) of bees (Apiformes), consisting of reference library construction, a proof‐of‐concept monitoring scheme, and the deep barcoding of individuals to assess potential artefacts and organismal associations. A reference database of cytochrome oxidase c subunit 1 (cox1) sequences including 92.4% of 278 bee species known from the UK showed high congruence with morphological taxon concepts, but molecular species delimitations resulted in numerous split and (fewer) lumped entities within the Linnaean species. Double tagging permitted deep Illumina sequencing of 762 separate individuals of bees from a UK‐wide survey. Extracting the target barcode from the amplicon mix required a new protocol employing read abundance and phylogenetic position, which revealed 180 molecular entities of Apiformes identifiable to species. An additional 72 entities were ascribed to nuclear pseudogenes based on patterns of read abundance and phylogenetic relatedness to the reference set. Clustering of reads revealed a range of secondary operational taxonomic units (OTUs) in almost all samples, resulting from traces of insect species caught in the same traps, organisms associated with the insects including a known mite parasite of bees, and the common detection of human DNA, besides evidence for low‐level cross‐contamination in pan traps and laboratory procedures. Custom scripts were generated to conduct critical steps of the bioinformatics protocol. The resources built here will greatly aid DNA‐based monitoring to inform management and conservation policies for the protection of pollinators.