Evidence map›Paper›PMID 19592529›Full record

ArticleApplied and environmental microbiology2009

Defining DNA-based operational taxonomic units for microbial-eukaryote ecology.

David A Caron, Peter D Countway, Pratik Savai, Rebecca J Gast, Astrid Schnetzer, Stefanie D Moorthi, Mark R Dennett, Dawn M Moran, Adriane C Jones

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Article in Applied and environmental microbiology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 55 papers.

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0cells of the map it votes in
55citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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.

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3 · Its place in the literature

Who cites it

55 citing papers in PubMed.

  1. Article
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  5. Evaluation of theFrontiers in microbiology · 2023
    Article
  6. Exploring the taxonomic and functional diversity of marineSaudi journal of biological sciences · 2022
    Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Combining morphology, behaviour and genomics to understand the evolution and ecology of microbial eukaryotes.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2019
    Review
  13. Article
  14. Article
  15. Article
  16. Article
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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

9 authors.

David A CaronDepartment of Biological Sciences, University of Southern California, 3616 Trousdale Parkway, Los Angeles, CA 90089-0371, USA. dcaron@usc.edu
Peter D Countway
Pratik Savai
Rebecca J Gast
Astrid Schnetzer
Stefanie D Moorthi
Mark R Dennett
Dawn M Moran
Adriane C Jones

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

DNA sequence information has increasingly been used in ecological research on microbial eukaryotes. Sequence-based approaches have included studies of the total diversity of selected ecosystems, studies of the autecology of ecologically relevant species, and identification and enumeration of species of interest for human health. It is still uncommon, however, to delineate protistan species based on their genetic signatures. The reluctance to assign species-level designations based on DNA sequences is in part a consequence of the limited amount of sequence information presently available for many free-living microbial eukaryotes and in part a consequence of the problematic nature of and debate surrounding the microbial species concept. Despite the difficulties inherent in assigning species names to DNA sequences, there is a growing need to attach meaning to the burgeoning amount of sequence information entering the literature, and there is a growing desire to apply this information in ecological studies. We describe a computer-based tool that assigns DNA sequences from environmental databases to operational taxonomic units at approximately species-level distinctions. This approach provides a practical method for ecological studies of microbial eukaryotes (primarily protists) by enabling semiautomated analysis of large numbers of samples spanning great taxonomic breadth. Derivation of the algorithm was based on an analysis of complete small-subunit (18S) rRNA gene sequences and partial gene sequences obtained from the GenBank database for morphologically described protistan species. The program was tested using environmental 18S rRNA data sets for two oceanic ecosystems. A total of 388 operational taxonomic units were observed for 2,207 sequences obtained from samples collected in the western North Atlantic and eastern North Pacific oceans.

Indexed as

EcosystemAtlantic OceanClassificationComputational BiologyDNA, RibosomalEukaryotic CellsMolecular Sequence DataPacific OceanRNA, Ribosomal, 18SSeawaterSequence Analysis, DNADNA, RibosomalRNA, Ribosomal, 18S

Identifiers

PMID19592529
PMCPMC2747860

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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.