Evidence map›Paper›PMID 38606340›Full record

ArticleEcology and evolution2024

A full-length 18S ribosomal DNA metabarcoding approach for determining protist community diversity using Nanopore sequencing.

Chetan C Gaonkar, Lisa Campbell

Abstract read
In one paragraph

Article in Ecology and evolution, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
–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

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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

7 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Systematic Review: Long-Read Sequencing in Algal Studies.International journal of molecular sciences · 2026
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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

2 authors.

Chetan C GaonkarDepartment of Oceanography Texas A&M University College Station Texas USA.ORCID https://orcid.org/0000-0001-9754-1863
Lisa CampbellDepartment of Oceanography Texas A&M University College Station Texas USA.ORCID https://orcid.org/0000-0003-2756-2743

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Protist diversity studies are frequently conducted using DNA metabarcoding methods. Currently, most studies have utilized short read sequences to assess protist diversity. One limitation of using short read sequences is the low resolution of the markers. For better taxonomic resolution longer sequences of the 18S rDNA are required because the full-length has both conserved and hypervariable regions. In this study, a new primer pair combination was used to amplify the full-length 18S rDNA and its efficacy was validated with a test community and then validated with field samples. Full-length sequences obtained with the Nanopore MinION for protist diversity from field samples were compared with Illumina MiSeq V4 and V8-V9 short reads. Sequences generated from the high-throughput sequencers are Amplicon Sequence Variants (ASVs). Metabarcoding results show high congruency among the long reads and short reads in taxonomic annotation at the major taxonomic group level; however, not all taxa could be successfully detected from sequences. Based on the criteria of ≥95% similarity and ≥1000 bp query length, 298 genera were identified by all markers in the field samples, 250 (84%) were detected by 18S, while only 226 (76%) by V4 and 213 (71%) by V8-V9. Of the total 85 dinoflagellate genera observed, 19 genera were not defined by 18S dinoflagellate ASVs compared to only three among the total 52 diatom genera. The discrepancy in this resolution is due to the lack of taxonomically available 18S reference sequences in particular for dinoflagellates. Overall, this preliminary investigation demonstrates that application of the full-length 18S rDNA approach can be successful in field studies.

Indexed as

ciliatesdiatomsdinoflagellatesmicrobial diversityminIONprimer design

Identifiers

PMID38606340
PMCPMC11007259

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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.