Ecosystems Monitoring Powered by Environmental Genomics: A Review of Current Strategies with An Implementation Roadmap

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

doi:10.20944/preprints202001.0278.v1

Cited by 12 publications

(12 citation statements)

References 163 publications

(203 reference statements)

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Biodiversity studies increasingly use environmental DNA (eDNA)based methods to assess community patterns (Cordier et al, 2020;Dornelas et al, 2019), to discover rare organisms (Jerde et al, 2011), and to detect invasive species (Holman et al, 2019).Comparisons between non-molecular and eDNA biodiversity surveys have consistently shown that eDNA surveys are highly sensitive and can detect species accurately at a reduced cost (Blackman

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confidence: 99%

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How does eDNA decay affect metabarcoding experiments?

2021

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Biodiversity studies increasingly use environmental DNA (eDNA)based methods to assess community patterns (Cordier et al., 2020;Dornelas et al., 2019), to discover rare organisms (Jerde et al., 2011), and to detect invasive species (Holman et al., 2019).Comparisons between non-molecular and eDNA biodiversity surveys have consistently shown that eDNA surveys are highly sensitive and can detect species accurately at a reduced cost (Blackman

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confidence: 99%

“…Biodiversity studies increasingly use environmental DNA (eDNA)based methods to assess community patterns (Cordier et al, 2020;Dornelas et al, 2019), to discover rare organisms (Jerde et al, 2011), and to detect invasive species (Holman et al, 2019).…”

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confidence: 99%

How does eDNA decay affect metabarcoding experiments?

2021

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“…Regarding the extraction of geographic metadata from NCBI records, the completeness and collection of data can improve drastically the biogeographic and ecological research, allowing not only to explore sampling areas, but also to improve phylogeography investigations, biodiversity monitoring and environmental genomics strategies [12, 47].…”

Section: Extaxsimentioning

confidence: 99%

ExTaxsI: an exploration tool of biodiversity molecular data

Agostinetto

Sandionigi

et al. 2020

Preprint

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Background: The increasing availability of multi omics data is leading to continually revise estimates of existing biodiversity data. In particular, the molecular data enable to characterize novel species yet unknown and to increase the information linked to those already observed with new genomic data. For this reason, the management and visualization of existing molecular data, and their related metadata, through the implementation of easy to use IT tools have become a key point for the development of future research. The more users are able to access biodiversity related information, the greater the ability of the scientific community to expand the knowledge in this area. Results: In our research we have focused on the development of ExTaxsI (Exploring Taxonomies Information), an IT tool able to retrieve biodiversity data stored in NCBI databases and provide a simple and explorable visualization. Through the three case studies presented here, we have shown how an efficient organization of the data already present can lead to obtaining new information that is fundamental as a starting point for new research. Our approach was also able to highlight the limits in the distribution data availability, a key factor to consider in the experimental design phase of broad spectrum studies, such as metagenomics. Conclusions: ExTaxI can easily produce explorable visualization of molecular data and its metadata, with the aim to help researchers to improve experimental designs and highlight the main gaps in the coverage of available data. Keywords: Biodiversity; Data visualization; Molecular data; Database; Data integration; Taxonomy gaps

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“…DNA metabarcoding coupled with high‐throughput sequencing is currently revolutionising the way we assess and 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 (Cordier et al., 2020; Deiner et al., 2017; Taberlet et al., 2018). 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

et al. 2021

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DNA metabarcoding is becoming the tool of choice for biodiversity assessment across taxa and environments. Yet, the artefacts present in metabarcoding datasets often preclude a proper interpretation of ecological patterns. Bioinformatic pipelines to remove experimental noise exist. However, these often only partially target produced artefacts, or are marker specific. In addition, assessments of data curation quality and chosen 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, that is, 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 facilitates 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 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

Cited by 12 publications

References 163 publications

How does eDNA decay affect metabarcoding experiments?

How does eDNA decay affect metabarcoding experiments?

ExTaxsI: an exploration tool of biodiversity molecular data

metabaR: An r package for the evaluation and improvement of DNA metabarcoding data quality

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