Your browser doesn't support javascript.
loading
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.
Afiliação
  • Karamycheva S; National Center for Biotechnology Information, National Library of Medicine, Bethesda, MD, 20894, USA.
  • Wolf YI; National Center for Biotechnology Information, National Library of Medicine, Bethesda, MD, 20894, USA.
  • Persi E; National Center for Biotechnology Information, National Library of Medicine, Bethesda, MD, 20894, USA.
  • Koonin EV; National Center for Biotechnology Information, National Library of Medicine, Bethesda, MD, 20894, USA.
  • Makarova KS; National Center for Biotechnology Information, National Library of Medicine, Bethesda, MD, 20894, USA. makarova@ncbi.nlm.nih.gov.
Biol Direct ; 17(1): 22, 2022 08 30.
Article em En | MEDLINE | ID: mdl-36042479
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.
Assuntos
Palavras-chave

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Células Procarióticas / Evolução Molecular Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Células Procarióticas / Evolução Molecular Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article