Evidence map›Paper›PMID 21426537›Full record

ArticleGenome biology2011

Community transcriptomics reveals universal patterns of protein sequence conservation in natural microbial communities.

Frank J Stewart, Adrian K Sharma, Jessica A Bryant, John M Eppley, Edward F DeLong

Abstract read
In one paragraph

Article in Genome biology, 2011. 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

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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

28 citing papers in PubMed.

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  14. Microbial community transcriptional networks are conserved in three domains at ocean basin scales.Proceedings of the National Academy of Sciences of the United States of America · 2015
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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

5 authors.

Frank J StewartSchool of Biology, Georgia Institute of Technology, Ford ES&T Building, Rm 1242, 311 Ferst Drive, Atlanta, GA 30332, USA.
Adrian K Sharma
Jessica A Bryant
John M Eppley
Edward F DeLong

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCombined metagenomic and metatranscriptomic datasets make it possible to study the molecular evolution of diverse microbial species recovered from their native habitats. The link between gene expression level and sequence conservation was examined using shotgun pyrosequencing of microbial community DNA and RNA from diverse marine environments, and from forest soil.

resultsAcross all samples, expressed genes with transcripts in the RNA sample were significantly more conserved than non-expressed gene sets relative to best matches in reference databases. This discrepancy, observed for many diverse individual genomes and across entire communities, coincided with a shift in amino acid usage between these gene fractions. Expressed genes trended toward GC-enriched amino acids, consistent with a hypothesis of higher levels of functional constraint in this gene pool. Highly expressed genes were significantly more likely to fall within an orthologous gene set shared between closely related taxa (core genes). However, non-core genes, when expressed above the level of detection, were, on average, significantly more highly expressed than core genes based on transcript abundance normalized to gene abundance. Finally, expressed genes showed broad similarities in function across samples, being relatively enriched in genes of energy metabolism and underrepresented by genes of cell growth.

conclusionsThese patterns support the hypothesis, predicated on studies of model organisms, that gene expression level is a primary correlate of evolutionary rate across diverse microbial taxa from natural environments. Despite their complexity, meta-omic datasets can reveal broad evolutionary patterns across taxonomically, functionally, and environmentally diverse communities.

Indexed as

Conserved SequenceMetagenomicsTranscriptomeAmino Acid SequenceBase CompositionCluster AnalysisDNA, ComplementaryEcosystemEvolution, MolecularGene Expression ProfilingPhylogenyRNA, RibosomalSequence Homology, Nucleic AcidSoil MicrobiologyDNA, ComplementaryRNA, Ribosomal

Identifiers

PMID21426537
PMCPMC3129676

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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.