Evidence map›Paper›PMID 21169433›Full record

ArticleApplied and environmental microbiology2011

Influence of molecular resolution on sequence-based discovery of ecological diversity among Synechococcus populations in an alkaline siliceous hot spring microbial mat.

Melanie C Melendrez, Rachel K Lange, Frederick M Cohan, David M Ward

Abstract read
In one paragraph

Article in Applied and environmental microbiology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing 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

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3 · Its place in the literature

Who cites it

23 citing papers in PubMed.

  1. Article
  2. Biogeography of American Northwest Hot Spring A/BFrontiers in microbiology · 2020
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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

4 authors.

Melanie C MelendrezLand Resources and Environmental Science, Montana State University, Bozeman, Montana, USA. melendrezmc@afrims.org
Rachel K Lange
Frederick M Cohan
David M Ward

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Previous research has shown that sequences of 16S rRNA genes and 16S-23S rRNA internal transcribed spacer regions may not have enough genetic resolution to define all ecologically distinct Synechococcus populations (ecotypes) inhabiting alkaline, siliceous hot spring microbial mats. To achieve higher molecular resolution, we studied sequence variation in three protein-encoding loci sampled by PCR from 60°C and 65°C sites in the Mushroom Spring mat (Yellowstone National Park, WY). Sequences were analyzed using the ecotype simulation (ES) and AdaptML algorithms to identify putative ecotypes. Between 4 and 14 times more putative ecotypes were predicted from variation in protein-encoding locus sequences than from variation in 16S rRNA and 16S-23S rRNA internal transcribed spacer sequences. The number of putative ecotypes predicted depended on the number of sequences sampled and the molecular resolution of the locus. Chao estimates of diversity indicated that few rare ecotypes were missed. Many ecotypes hypothesized by sequence analyses were different in their habitat specificities, suggesting different adaptations to temperature or other parameters that vary along the flow channel.

Indexed as

BiodiversityBacterial ProteinsBase SequenceGenetic LociGenetic VariationGenotypeHot SpringsHot TemperatureMolecular Sequence DataPhylogenyPolymerase Chain ReactionRNA, Ribosomal, 16SRNA, Ribosomal, 23SSequence AlignmentSequence Analysis, DNASequence Analysis, ProteinBacterial ProteinsRNA, Ribosomal, 16SRNA, Ribosomal, 23SSilicon Dioxide

Identifiers

PMID21169433
PMCPMC3067246

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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.