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Analysis of lineage-specific protein family variability in prokaryotes combined with evolutionary reconstructions
BACKGROUND: Evolutionary 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 phylo...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9425974/ https://www.ncbi.nlm.nih.gov/pubmed/36042479 http://dx.doi.org/10.1186/s13062-022-00337-7 |
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author | Karamycheva, Svetlana Wolf, Yuri I. Persi, Erez Koonin, Eugene V. Makarova, Kira S. |
author_facet | Karamycheva, Svetlana Wolf, Yuri I. Persi, Erez Koonin, Eugene V. Makarova, Kira S. |
author_sort | Karamycheva, Svetlana |
collection | PubMed |
description | BACKGROUND: Evolutionary 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). RESULTS: We 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. CONCLUSIONS: Variability, 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13062-022-00337-7. |
format | Online Article Text |
id | pubmed-9425974 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-94259742022-08-31 Analysis of lineage-specific protein family variability in prokaryotes combined with evolutionary reconstructions Karamycheva, Svetlana Wolf, Yuri I. Persi, Erez Koonin, Eugene V. Makarova, Kira S. Biol Direct Research BACKGROUND: Evolutionary 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). RESULTS: We 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. CONCLUSIONS: Variability, 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13062-022-00337-7. BioMed Central 2022-08-30 /pmc/articles/PMC9425974/ /pubmed/36042479 http://dx.doi.org/10.1186/s13062-022-00337-7 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Karamycheva, Svetlana Wolf, Yuri I. Persi, Erez Koonin, Eugene V. Makarova, Kira S. Analysis of lineage-specific protein family variability in prokaryotes combined with evolutionary reconstructions |
title | Analysis of lineage-specific protein family variability in prokaryotes combined with evolutionary reconstructions |
title_full | Analysis of lineage-specific protein family variability in prokaryotes combined with evolutionary reconstructions |
title_fullStr | Analysis of lineage-specific protein family variability in prokaryotes combined with evolutionary reconstructions |
title_full_unstemmed | Analysis of lineage-specific protein family variability in prokaryotes combined with evolutionary reconstructions |
title_short | Analysis of lineage-specific protein family variability in prokaryotes combined with evolutionary reconstructions |
title_sort | analysis of lineage-specific protein family variability in prokaryotes combined with evolutionary reconstructions |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9425974/ https://www.ncbi.nlm.nih.gov/pubmed/36042479 http://dx.doi.org/10.1186/s13062-022-00337-7 |
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