Evidence map›Paper›PMID 30805154›Full record

ArticleEcology and evolution2019

Metabarcoding free-living marine nematodes using curated 18S and CO1 reference sequence databases for species-level taxonomic assignments.

Lara Macheriotou, Katja Guilini, Tania Nara Bezerra, Bjorn Tytgat, Dinh Tu Nguyen, Thi Xuan Phuong Nguyen, Febe Noppe, Maickel Armenteros, Fehmi Boufahja, Annelien Rigaux and 2 more

Abstract read
In one paragraph

Article in Ecology and evolution, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

28 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Lara MacheriotouMarine Biology Research Group, Department of Biology Ghent University Ghent Belgium.ORCID https://orcid.org/0000-0002-5662-5689
Katja GuiliniMarine Biology Research Group, Department of Biology Ghent University Ghent Belgium.ORCID https://orcid.org/0000-0003-1832-8875
Tania Nara BezerraMarine Biology Research Group, Department of Biology Ghent University Ghent Belgium.ORCID https://orcid.org/0000-0002-4414-7827
Bjorn TytgatMarine Biology Research Group, Department of Biology Ghent University Ghent Belgium.ORCID https://orcid.org/0000-0002-6926-3488
Dinh Tu NguyenDepartment of Nematology, Institute of Ecology and Biological Resources Vietnam Academy of Science and Technology Hanoi Vietnam.
Thi Xuan Phuong NguyenDepartment of Nematology, Institute of Ecology and Biological Resources Vietnam Academy of Science and Technology Hanoi Vietnam.ORCID https://orcid.org/0000-0001-8911-014X
Febe NoppeMarine Biology Research Group, Department of Biology Ghent University Ghent Belgium.
Maickel ArmenterosCentro de Investigaciones Marinas Universidad de La Habana Habana Cuba.ORCID https://orcid.org/0000-0002-9736-9247
Fehmi BoufahjaLaboratory of Biomonitoring of the Environment (LBE), Faculty of Sciences of Bizerte University of Carthage Carthage Tunisia.
Annelien RigauxMarine Biology Research Group, Department of Biology Ghent University Ghent Belgium.
Ann VanreuselMarine Biology Research Group, Department of Biology Ghent University Ghent Belgium.
Sofie DeryckeMarine Biology Research Group, Department of Biology Ghent University Ghent Belgium.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

High-throughput sequencing has the potential to describe biological communities with high efficiency yet comprehensive assessment of diversity with species-level resolution remains one of the most challenging aspects of metabarcoding studies. We investigated the utility of curated ribosomal and mitochondrial nematode reference sequence databases for determining phylum-specific species-level clustering thresholds. We compiled 438 ribosomal and 290 mitochondrial sequences which identified 99% and 94% as the species delineation clustering threshold, respectively. These thresholds were evaluated in HTS data from mock communities containing 39 nematode species as well as environmental samples from Vietnam. We compared the taxonomic description of the mocks generated by two read-merging and two clustering algorithms and the cluster-free Dada2 pipeline. Taxonomic assignment with the RDP classifier was assessed under different training sets. Our results showed that 36/39 mock nematode species were identified across the molecular markers (18S: 32, JB2: 19, JB3: 21) in UClust_ref OTUs at their respective clustering thresholds, outperforming UParse_denovo and the commonly used 97% similarity. Dada2 generated the most realistic number of ASVs (18S: 83, JB2: 75, JB3: 82), collectively identifying 30/39 mock species. The ribosomal marker outperformed the mitochondrial markers in terms of species and genus-level detections for both OTUs and ASVs. The number of taxonomic assignments of OTUs/ASVs was highest when the smallest reference database containing only nematode sequences was used and when sequences were truncated to the respective amplicon length. Overall, OTUs generated more species-level detections, which were, however, associated with higher error rates compared to ASVs. Genus-level assignments using ASVs exhibited higher accuracy and lower error rates compared to species-level assignments, suggesting that this is the most reliable pipeline for rapid assessment of alpha diversity from environmental samples.

Indexed as

metabarcodingmock communityNematodareference sequence databaseUClustUSearch9

Identifiers

PMID30805154
PMCPMC6374678

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.