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Journal Articles GigaScience Year : 2022

Inferring microbiota functions from taxonomic genes: a review

Christophe Djemiel
Pierre-Alain Maron
Sébastien Terrat
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Samuel S. Dequiedt
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Aurélien Cottin
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Lionel Ranjard
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Abstract

Abstract Deciphering microbiota functions is crucial to predict ecosystem sustainability in response to global change. High-throughput sequencing at the individual or community level has revolutionized our understanding of microbial ecology, leading to the big data era and improving our ability to link microbial diversity with microbial functions. Recent advances in bioinformatics have been key for developing functional prediction tools based on DNA metabarcoding data and using taxonomic gene information. This cheaper approach in every aspect serves as an alternative to shotgun sequencing. Although these tools are increasingly used by ecologists, an objective evaluation of their modularity, portability, and robustness is lacking. Here, we reviewed 100 scientific papers on functional inference and ecological trait assignment to rank the advantages, specificities, and drawbacks of these tools, using a scientific benchmarking. To date, inference tools have been mainly devoted to bacterial functions, and ecological trait assignment tools, to fungal functions. A major limitation is the lack of reference genomes—compared with the human microbiota—especially for complex ecosystems such as soils. Finally, we explore applied research prospects. These tools are promising and already provide relevant information on ecosystem functioning, but standardized indicators and corresponding repositories are still lacking that would enable them to be used for operational diagnosis.
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Dates and versions

hal-03696995 , version 1 (14-03-2023)

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Christophe Djemiel, Pierre-Alain Maron, Sébastien Terrat, Samuel S. Dequiedt, Aurélien Cottin, et al.. Inferring microbiota functions from taxonomic genes: a review. GigaScience, 2022, 11, ⟨10.1093/gigascience/giab090⟩. ⟨hal-03696995⟩
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