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Towards exhaustive community ecology via DNA metabarcoding.

Authors :
Ficetola GF
Taberlet P
Source :
Molecular ecology [Mol Ecol] 2023 Dec; Vol. 32 (23), pp. 6320-6329. Date of Electronic Publication: 2023 Feb 23.
Publication Year :
2023

Abstract

Exhaustive biodiversity data, covering all the taxa in an environment, would be fundamental to understand how global changes influence organisms living at different trophic levels, and to evaluate impacts on interspecific interactions. Molecular approaches such as DNA metabarcoding are boosting our ability to perform biodiversity inventories. Nevertheless, even though a few studies have recently attempted exhaustive reconstructions of communities, holistic assessments remain rare. The majority of metabarcoding studies published in the last years used just one or two markers and analysed a limited number of taxonomic groups. Here, we provide an overview of emerging approaches that can allow all-taxa biological inventories. Exhaustive biodiversity assessments can be attempted by combining a large number of specific primers, by exploiting the power of universal primers, or by combining specific and universal primers to obtain good information on key taxa while limiting the overlooked biodiversity. Multiplexes of primers, shotgun sequencing and capture enrichment may provide a better coverage of biodiversity compared to standard metabarcoding, but still require major methodological advances. Here, we identify the strengths and limitations of different approaches, and suggest new development lines that might improve broad scale biodiversity analyses in the near future. More holistic reconstructions of ecological communities can greatly increase the value of metabarcoding studies, improving understanding of the consequences of ongoing environmental changes on the multiple components of biodiversity.<br /> (© 2023 John Wiley & Sons Ltd.)

Details

Language :
English
ISSN :
1365-294X
Volume :
32
Issue :
23
Database :
MEDLINE
Journal :
Molecular ecology
Publication Type :
Academic Journal
Accession number :
36762839
Full Text :
https://doi.org/10.1111/mec.16881