Literature DB >> 31290224

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

Thomas J Creedy1,2, Hannah Norman1,3, Cuong Q Tang1, Kai Qing Chin1, Carmelo Andujar1,2,4, Paula Arribas1,2, Rory S O'Connor5, Claire Carvell4, David G Notton1, Alfried P Vogler1,2.   

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.
© 2019 John Wiley & Sons Ltd.

Entities:  

Keywords:  community barcoding; contamination; double dual tagging; illumina sequencing; pollinators

Mesh:

Substances:

Year:  2019        PMID: 31290224     DOI: 10.1111/1755-0998.13056

Source DB:  PubMed          Journal:  Mol Ecol Resour        ISSN: 1755-098X            Impact factor:   7.090


  6 in total

1.  Toward global integration of biodiversity big data: a harmonized metabarcode data generation module for terrestrial arthropods.

Authors:  Paula Arribas; Carmelo Andújar; Kristine Bohmann; Jeremy R deWaard; Evan P Economo; Vasco Elbrecht; Stefan Geisen; Marta Goberna; Henrik Krehenwinkel; Vojtech Novotny; Lucie Zinger; Thomas J Creedy; Emmanouil Meramveliotakis; Víctor Noguerales; Isaac Overcast; Hélène Morlon; Anna Papadopoulou; Alfried P Vogler; Brent C Emerson
Journal:  Gigascience       Date:  2022-07-19       Impact factor: 7.658

2.  A DNA barcode-based survey of wild urban bees in the Loire Valley, France.

Authors:  Irene Villalta; Romain Ledet; Mathilde Baude; David Genoud; Christophe Bouget; Maxime Cornillon; Sébastien Moreau; Béatrice Courtial; Carlos Lopez-Vaamonde
Journal:  Sci Rep       Date:  2021-02-26       Impact factor: 4.379

Review 3.  Coming of age for COI metabarcoding of whole organism community DNA: Towards bioinformatic harmonisation.

Authors:  Thomas J Creedy; Carmelo Andújar; Emmanouil Meramveliotakis; Victor Noguerales; Isaac Overcast; Anna Papadopoulou; Hélène Morlon; Alfried P Vogler; Brent C Emerson; Paula Arribas
Journal:  Mol Ecol Resour       Date:  2021-09-30       Impact factor: 8.678

4.  Using metatranscriptomics to estimate the diversity and composition of zooplankton communities.

Authors:  Mark Louie D Lopez; Ya-Ying Lin; Mitsuhide Sato; Chih-Hao Hsieh; Fuh-Kwo Shiah; Ryuji J Machida
Journal:  Mol Ecol Resour       Date:  2021-10-03       Impact factor: 8.678

5.  Building of an Internal Transcribed Spacer (ITS) Gene Dataset to Support the Italian Health Service in Mushroom Identification.

Authors:  Alice Giusti; Enrica Ricci; Laura Gasperetti; Marta Galgani; Luca Polidori; Francesco Verdigi; Roberto Narducci; Andrea Armani
Journal:  Foods       Date:  2021-05-25

6.  Rapid, large-scale species discovery in hyperdiverse taxa using 1D MinION sequencing.

Authors:  Amrita Srivathsan; Emily Hartop; Jayanthi Puniamoorthy; Wan Ting Lee; Sujatha Narayanan Kutty; Olavi Kurina; Rudolf Meier
Journal:  BMC Biol       Date:  2019-11-29       Impact factor: 7.431

  6 in total

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