Evidence map›Paper›PMID 30947688›Full record

ArticleBMC genomics2019

Marker genes as predictors of shared genomic function.

Joseph L Sevigny, Derek Rothenheber, Krystalle Sharlyn Diaz, Ying Zhang, Kristin Agustsson, R Daniel Bergeron, W Kelley Thomas

Abstract read
In one paragraph

Article in BMC genomics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 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

7 authors.

Joseph L SevignyMolecular, Cellular, and Biomedical Sciences, University of New Hampshire, 46 College Rd, Rudman Hall, Durham, NH, 03824, USA. jlsevigny1@wildcats.unh.edu.ORCID http://orcid.org/0000-0003-0024-3718
Derek RothenheberMolecular, Cellular, and Biomedical Sciences, University of New Hampshire, 46 College Rd, Rudman Hall, Durham, NH, 03824, USA.
Krystalle Sharlyn DiazMolecular, Cellular, and Biomedical Sciences, University of New Hampshire, 46 College Rd, Rudman Hall, Durham, NH, 03824, USA.
Ying ZhangDepartment of Computer Science, University of New Hampshire, 33 Academic Way, Kingsbury Hall, Durham, NH, 0324, USA.
Kristin AgustssonDepartment of Computer Science, University of New Hampshire, 33 Academic Way, Kingsbury Hall, Durham, NH, 0324, USA.
R Daniel BergeronDepartment of Computer Science, University of New Hampshire, 33 Academic Way, Kingsbury Hall, Durham, NH, 0324, USA.
W Kelley ThomasMolecular, Cellular, and Biomedical Sciences, University of New Hampshire, 46 College Rd, Rudman Hall, Durham, NH, 03824, USA.

Funding

Ultrastructural analysis of axonal Kv2-mediated endoplasmic reticulum/plasma membrane (ER/PM) junctionsP20GM103506 · NIGMS · DARTMOUTH COLLEGE · PI Yina Hsing Huang · 2012 to 2026
$60.1M
Gulf of Mexico Research Initiative 16-052: SA 16-18National Institutes of Health: New Hampshire Idea Network of Biological Research Excellence 5 P20 GM 10350605NIGMS NIH HHS P20 GM103506
6 · The paper itself

Abstract

backgroundAlthough high-throughput marker gene studies provide valuable insight into the diversity and relative abundance of taxa in microbial communities, they do not provide direct measures of their functional capacity. Recently, scientists have shown a general desire to predict functional profiles of microbial communities based on phylogenetic identification inferred from marker genes, and recent tools have been developed to link the two. However, to date, no large-scale examination has quantified the correlation between the marker gene based taxonomic identity and protein coding gene conservation. Here we utilize 4872 representative prokaryotic genomes from NCBI to investigate the relationship between marker gene identity and shared protein coding gene content.

resultsEven at 99-100% marker gene identity, genomes share on average less than 75% of their protein coding gene content. This occurs regardless of the marker gene(s) used: V4 region of the 16S rRNA, complete 16S rRNA, or single copy orthologs through a multi-locus sequence analysis. An important aspect related to this observation is the intra-organism variation of 16S copies from a single genome. Although the majority of 16S copies were found to have high sequence similarity (> 99%), several genomes contained copies that were highly diverged (< 97% identity).

conclusionsThis is the largest comparison between marker gene similarity and shared protein coding gene content to date. The study highlights the limitations of inferring a microbial community's functions based on marker gene phylogeny. The data presented expands upon the results of previous studies that examined one or few bacterial species and supports the hypothesis that 16S rRNA and other marker genes cannot be directly used to fully predict the functional potential of a bacterial community.

Indexed as

Genetic MarkersGenome, BacterialMetagenomeBacteriaDNA, BacterialEvolution, MolecularGenes, BacterialMicrobiotaPhylogenyRNA, Ribosomal, 16SSequence Analysis, DNADNA, BacterialGenetic MarkersRNA, Ribosomal, 16S16S rRNAAmpliconComparative genomicsFunctional capacityMarker geneMetabarcodingMetagenomics

Identifiers

PMID30947688
PMCPMC6449922

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LicenceCC BY
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Registered trials

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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.