Evidence map›Paper›PMID 36042479›Full record

ArticleBiology direct2022

Analysis of lineage-specific protein family variability in prokaryotes combined with evolutionary reconstructions.

Svetlana Karamycheva, Yuri I Wolf, Erez Persi, Eugene V Koonin, Kira S Makarova

Open access · goldAbstract read
In one paragraph

Article in Biology direct, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.1field-weighted citation impact, top 12% of its field
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

6 citing papers in PubMed, 14 citations in OpenAlex.

  1. Article
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  6. Compensatory relationship between low-complexity regions and gene paralogy in the evolution of prokaryotes.Proceedings of the National Academy of Sciences of the United States of America · 2023
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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 at 1 institution in 1 country.

Svetlana KaramychevaNational Center for Biotechnology Information, National Library of Medicine, Bethesda, MD, 20894, USA.
Yuri I WolfNational Center for Biotechnology Information, National Library of Medicine, Bethesda, MD, 20894, USA.
Erez PersiNational Center for Biotechnology Information, National Library of Medicine, Bethesda, MD, 20894, USA.
Eugene V KooninNational Center for Biotechnology Information, National Library of Medicine, Bethesda, MD, 20894, USA.
Kira S MakarovaNational Center for Biotechnology Information, National Library of Medicine, Bethesda, MD, 20894, USA. makarova@ncbi.nlm.nih.gov.
National Center for Biotechnology Information · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEvolutionary rate is a key characteristic of gene families that is linked to the functional importance of the respective genes as well as specific biological functions of the proteins they encode. Accurate estimation of evolutionary rates is a challenging task that requires precise phylogenetic analysis. Here we present an easy to estimate protein family level measure of sequence variability based on alignment column homogeneity in multiple alignments of protein sequences from Clade-Specific Clusters of Orthologous Genes (csCOGs).

resultsWe report genome-wide estimates of variability for 8 diverse groups of bacteria and archaea and investigate the connection between variability and various genomic and biological features. The variability estimates are based on homogeneity distributions across amino acid sequence alignments and can be obtained for multiple groups of genomes at minimal computational expense. About half of the variance in variability values can be explained by the analyzed features, with the greatest contribution coming from the extent of gene paralogy in the given csCOG. The correlation between variability and paralogy appears to originate, primarily, not from gene duplication, but from acquisition of distant paralogs and xenologs, introducing sequence variants that are more divergent than those that could have evolved in situ during the lifetime of the given group of organisms. Both high-variability and low-variability csCOGs were identified in all functional categories, but as expected, proteins encoded by integrated mobile elements as well as proteins involved in defense functions and cell motility are, on average, more variable than proteins with housekeeping functions. Additionally, using linear discriminant analysis, we found that variability and fraction of genomes carrying a given gene are the two variables that provide the best prediction of gene essentiality as compared to the results of transposon mutagenesis in Sulfolobus islandicus.

conclusionsVariability, a measure of sequence diversity within an alignment relative to the overall diversity within a group of organisms, offers a convenient proxy for evolutionary rate estimates and is informative with respect to prediction of functional properties of proteins. In particular, variability is a strong predictor of gene essentiality for the respective organisms and indicative of sub- or neofunctionalization of paralogs.

Indexed as

Evolution, MolecularProkaryotic CellsGene DuplicationPhylogenyProteinsSequence AlignmentProteinsClusters of orthologous genesEvolutionary reconstructionsParalogsVariability

Identifiers

PMID36042479
PMCPMC9425974
OpenAlexW4293555033

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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.