Ecosystems monitoring powered by environmental genomics: A review of current strategies with an implementation roadmap

Cordier, Tristan; Alonso‐Sáez, Laura; Apothéloz-Perret-Gentil, Laure; Aylagas, Eva; Bohan, David; Bouchez, Agnès; Chariton, Anthony A.; Creer, Simon; Frühe, Larissa; Keck, François; Keeley, Nigel; Laroche, Olivier; Leese, Florian; Pochon, Xavier; Stoeck, Thorsten; Pawłowski, Jan; Lanzén, Anders

doi:10.1111/mec.15472

Cited by 163 publications

(128 citation statements)

References 317 publications

(625 reference statements)

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“…We explored the informative potential of pico-and nanoplankton communities for environmental status assessment using pelagic samples collected from diverse areas of the NW Mediterranean. As recently reviewed by Cordier et al (2020), various strategies to explore indicators based on environmental genetic data exist. Here, we explored the socalled 'structural community metrics strategy' by examining the potential of diversity and richness indices, and the 'de novo strategy' aimed at discovering new indicators of environmental status in the water column by analyzing the abundances of OTUs and taxonomic groups (and their ratios).…”

Section: Discussionmentioning

confidence: 99%

“…The lack of differences between these sites may be related to the implementation of policies to reduce the impact of urban areas on coastal systems The measurement of species diversity of an ecosystem has been proposed as a useful tool for assessing the impacts of human activities on marine ecosystems. The strategy based on community metrics aims at discovering and understanding the ecological processes shaping communities and their response to disturbances (see Cordier et al, 2020). Actually, the results of our previous work (Ferrera et al, 2017) indicated that it could be worth exploring the links between microbial diversity and environmental status of coastal waters.…”

Section: Discussionmentioning

confidence: 99%

“…Likewise, its potential to reflect environmental quality has been explored in biodiversity surveys (Ferrera et al, 2016;Cordier et al, 2020). A total of 9 prokaryotic and 6 eukaryotic taxonomic groups were found with significant IndVal and relative abundances higher than 0.4% (Table 2).…”

Section: Potential Indicator Taxamentioning

confidence: 99%

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Assessment of microbial plankton diversity as an ecological indicator in the NW Mediterranean coast

Ferrera

Reñé

Funosas

et al. 2020

Marine Pollution Bulletin

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Research highlights We evaluated microbial pico-and nanoplankton diversity as an ecological indicator in NW Mediterranean coastal waters using metabarcoding of rRNA genes Studied samples were subjected to varying degrees of continental pressures Diversity metrics from microbial eukaryotic communities displayed more suitability to be used as indicators than those of prokaryotes Few microbial planktonic taxa (both from prokaryotes and eukaryotes) showed potential as indicators Implementing fast and simple ecological indicators from the diversity of these planktonic components is challenging due to the complexity and dynamics of the pelagic communities *Highlights

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Assessment of microbial plankton diversity as an ecological indicator in the NW Mediterranean coast

Ferrera

Reñé

Funosas

et al. 2020

Marine Pollution Bulletin

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“…2019; Bush Alex 2019; Piper et al . 2019; Cordier et al . 2020; Cordier 2020), the applied use of metabarcoding is still in its infancy.…”

Section: Introductionmentioning

confidence: 99%

Biodiversity Soup II: A bulk-sample metabarcoding pipeline emphasizing error reduction

Yang

Bohmann

Wang

et al. 2020

Preprint

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AbstractDespite widespread recognition of its great promise to aid decision-making in environmental management, the applied use of metabarcoding requires improvements to reduce the multiple errors that arise during PCR amplification, sequencing, and library generation. We present a co-designed wet-lab and bioinformatic workflow for metabarcoding bulk samples that removes both false-positive (tag jumps, chimeras, erroneous sequences) and false-negative (‘drop-out’) errors. However, we find that it is not possible to recover relative-abundance information from amplicon data, due to persistent species-specific biases.To present and validate our workflow, we created eight mock arthropod soups, all containing the same 248 arthropod morphospecies but differing in absolute and relative DNA concentrations, and we ran them under five different PCR conditions. Our pipeline includes qPCR-optimized PCR annealing temperature and cycle number, twin-tagging, multiple independent PCR replicates per sample, and negative and positive controls. In the bioinformatic portion, we introduce Begum, which is a new version of DAMe (Zepeda Mendoza et al. 2016. BMC Res. Notes 9:255) that ignores heterogeneity spacers, allows primer mismatches when demultiplexing samples, and is more efficient. Like DAMe, Begum removes tag-jumped reads and removes sequence errors by keeping only sequences that appear in more than one PCR at above a minimum copy number.We report that OTU dropout frequency and taxonomic amplification bias are both reduced by using a PCR annealing temperature and cycle number on the low ends of the ranges currently used for the Leray-Fol-Degen-Rev primers. We also report that tag jumps and erroneous sequences can be nearly eliminated with Begum filtering, at the cost of only a small rise in drop-outs. We replicate published findings that uneven size distribution of input biomasses leads to greater drop-out frequency and that OTU size is a poor predictor of species input biomass. Finally, we find no evidence that different primer tags bias PCR amplification (‘tag bias’).To aid learning, reproducibility, and the design and testing of alternative metabarcoding pipelines, we provide our Illumina and input-species sequence datasets, scripts, a spreadsheet for designing primer tags, and a tutorial.

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“…DNA metabarcoding coupled with high-throughput sequencing is currently revolutionising the way we describe biodiversity across environments and taxa, and is therefore becoming a tool of choice for basic and applied research, as well as for biomonitoring applications (Deiner et al, 2017; Taberlet et al, 2018; Cordier et al, 2020). In recent years, various bioinformatic pipelines and tools have been developed to handle DNA metabarcoding data.…”

Section: Introductionmentioning

confidence: 99%

metabaR : an R package for the evaluation and improvement of DNA metabarcoding data quality

Zinger

Lionnet

Benoiston

et al. 2020

Preprint

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DNA metabarcoding is becoming the tool of choice for biodiversity studies across taxa and large-scale environmental gradients. Yet, the artefacts present in metabarcoding datasets often preclude a proper interpretation of ecological patterns. Bioinformatic pipelines removing experimental noise have been designed to address this issue. However, these often only partially target produced artefacts, or are marker specific. In addition, assessments of data curation quality and the appropriateness of filtering thresholds are seldom available in existing pipelines, partly due to the lack of appropriate visualisation tools.Here, we present metabaR, an R package that provides a comprehensive suite of tools to effectively curate DNA metabarcoding data after basic bioinformatic analyses. In particular, metabaR uses experimental negative or positive controls to identify different types of artefactual sequences, i.e. reagent contaminants and tag-jumps. It also flags potentially dysfunctional PCRs based on PCR replicate similarities when those are available. Finally, metabaR provides tools to visualise DNA metabarcoding data characteristics in their experimental context as well as their distribution, and facilitate assessment of the appropriateness of data curation filtering thresholds.metabaR is applicable to any DNA metabarcoding experimental design but is most powerful when the design includes experimental controls and replicates. More generally, the simplicity and flexibility of the package makes it applicable any DNA marker, and data generated with any sequencing platform, and pre-analysed with any bioinformatic pipeline. Its outputs are easily usable for downstream analyses with any ecological R package.metabaR complements existing bioinformatics pipelines by providing scientists with a variety of functions with customisable methods that will allow the user to effectively clean DNA metabarcoding data and avoid serious misinterpretations. It thus offers a promising platform for automatised data quality assessments of DNA metabarcoding data for environmental research and biomonitoring.

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Ecosystems monitoring powered by environmental genomics: A review of current strategies with an implementation roadmap

Abstract: This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

Cited by 163 publications

References 317 publications

Assessment of microbial plankton diversity as an ecological indicator in the NW Mediterranean coast

Assessment of microbial plankton diversity as an ecological indicator in the NW Mediterranean coast

Biodiversity Soup II: A bulk-sample metabarcoding pipeline emphasizing error reduction

metabaR : an R package for the evaluation and improvement of DNA metabarcoding data quality

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