Measuring evolutionary rates of proteins in a structural context.
Ontology highlight
ABSTRACT:
SUBMITTER: Sydykova DK
PROVIDER: S-EPMC5676193 | biostudies-literature | 2017
REPOSITORIES: biostudies-literature
Publications
Measuring evolutionary rates of proteins in a structural context.
Sydykova Dariya K DK Jack Benjamin R BR Spielman Stephanie J SJ Wilke Claus O CO
F1000Research 20171016
We describe how to measure site-specific rates of evolution in protein-coding genes and how to correlate these rates with structural features of the expressed protein, such as relative solvent accessibility, secondary structure, or weighted contact number. We present two alternative approaches to rate calculations: One based on relative amino-acid rates, and the other based on site-specific codon rates measured as <i>dN</i>/ <i>dS</i>. We additionally provide a code repository containing scripts ...[more]
Similar Datasets
Project description:Understanding patterns of rRNA evolution is critical for a number of fields, including structure prediction and phylogeny. The standard model of RNA evolution is that compensatory mutations in stems make up the bulk of the changes between homologous sequences, while unpaired regions are relatively homogeneous. We show that considerable heterogeneity exists in the relative rates of evolution of different secondary structure categories (stems, loops, bulges, etc.) within the rRNA, and that in eukaryotes, loops actually evolve much faster than stems. Both rates of evolution and abundance of different structural categories vary with distance from functionally important parts of the ribosome such as the tRNA path and the peptidyl transferase center. For example, fast-evolving residues are mainly found at the surface; stems are enriched at the subunit interface, and junctions near the peptidyl transferase center. However, different secondary structure categories evolve at different rates even when these effects are accounted for. The results demonstrate that relative rates and patterns of evolution are lineage specific, suggesting that phylogenetically and structurally specific models will improve evolutionary and structural predictions.
| S-EPMC1904297 | biostudies-literature
Project description:Proteins evolve at very different rates and, most notably, at rates inversely proportional to the level at which they are produced. The relative frequency of highly expressed proteins in the proteome, and thus their impact on the cell budget, increases steeply with growth rate. The maximal growth rate is a key life-history trait reflecting trade-offs between rapid growth and other fitness components. We show that the maximal growth rate is weakly affected by genetic drift. The negative correlation between protein expression levels and evolutionary rate and the positive correlation between expression levels of highly expressed proteins and growth rates, suggest that investment in growth affects the evolutionary rate of proteins, especially the highly expressed ones. Accordingly, analysis of 61 families of orthologs in 74 proteobacteria shows that differences in evolutionary rates between lowly and highly expressed proteins depend on maximal growth rates. Analyses of complexes with key roles in bacterial growth and strikingly different expression levels, the ribosome and the replisome, confirm these patterns and suggest that the growth-related sequence conservation is associated with protein synthesis. Maximal growth rates also shape protein evolution in the other bacterial clades. Long-branch attractions associated with this effect might explain why clades with persistent history of slow growth are attracted to the root when the tree of prokaryotes is inferred using highly, but not lowly, expressed proteins. These results indicate that reconstruction of deep phylogenies can be strongly affected by maximal growth rates, and highlight the importance of life-history traits and their physiological consequences for protein evolution.
| S-EPMC3250144 | biostudies-literature
Project description:The relative evolutionary rates at individual sites in proteins are informative measures of conservation or adaptation. Often used as evolutionarily aware conservation scores, relative rates reveal key functional or strongly selected residues. Estimating rates in a phylogenetic context requires specifying a protein substitution model, which is typically a phenomenological model trained on a large empirical data set. A strong emphasis has traditionally been placed on selecting the "best-fit" model, with the implicit understanding that suboptimal or otherwise ill-fitting models might bias inferences. However, the pervasiveness and degree of such bias has not been systematically examined. We investigated how model choice impacts site-wise relative rates in a large set of empirical protein alignments. We compared models designed for use on any general protein, models designed for specific domains of life, and the simple equal-rates Jukes Cantor-style model (JC). As expected, information theoretic measures showed overwhelming evidence that some models fit the data decidedly better than others. By contrast, estimates of site-specific evolutionary rates were impressively insensitive to the substitution model used, revealing an unexpected degree of robustness to potential model misspecification. A deeper examination of the fewer than 5% of sites for which model inferences differed in a meaningful way showed that the JC model could uniquely identify rapidly evolving sites that models with empirically derived exchangeabilities failed to detect. We conclude that relative protein rates appear robust to the applied substitution model, and any sensible model of protein evolution, regardless of its fit to the data, should produce broadly consistent evolutionary rates.
| S-EPMC6107055 | biostudies-literature
Project description:Functional RNAs (fRNAs) are being recognized as an important regulatory component in biological processes. Interestingly, recent computational studies suggest that the number and biological significance of functional RNAs within coding regions (coding fRNAs) may have been underestimated. We hypothesized that such coding fRNAs will impose additional constraint on sequence evolution because the DNA primary sequence has to simultaneously code for functional RNA secondary structures on the messenger RNA in addition to the amino acid codons for the protein sequence. To test this prediction, we first utilized computational methods to predict conserved fRNA secondary structures within multiple species alignments of Saccharomyces sensu strico genomes. We predict that as much as 5% of the genes in the yeast genome contain at least one functional RNA secondary structure within their protein-coding region. We then analyzed the impact of coding fRNAs on the evolutionary rate of protein-coding genes because a decrease in evolutionary rate implies constraint due to biological functionality. We found that our predicted coding fRNAs have a significant influence on evolutionary rates (especially at synonymous sites), independent of other functional measures. Thus, coding fRNA may play a role on sequence evolution. Given that coding regions of humans and flies contain many more predicted coding fRNAs than yeast, the impact of coding fRNAs on sequence evolution may be substantial in genomes of higher eukaryotes.
| S-EPMC2216430 | biostudies-literature
Project description:Transcription factor (TF) and microRNA (miRNA) are two crucial trans-regulatory factors that coordinately control gene expression. Understanding the impacts of these two factors on the rate of protein sequence evolution is of great importance in evolutionary biology. While many biological factors associated with evolutionary rate variations have been studied, evolutionary analysis of simultaneously accounting for TF and miRNA regulations across metazoans is still uninvestigated. Here, we provide a series of statistical analyses to assess the influences of TF and miRNA regulations on evolutionary rates across metazoans (human, mouse and fruit fly). Our results reveal that the negative correlations between trans-regulation and evolutionary rates hold well across metazoans, but the strength of TF regulation as a rate indicator becomes weak when the other confounding factors that may affect evolutionary rates are controlled. We show that miRNA regulation tends to be a more essential indicator of evolutionary rates than TF regulation, and the combination of TF and miRNA regulations has a significant dependent effect on protein evolutionary rates. We also show that trans-regulation (especially miRNA regulation) is much more important in human/mouse than in fruit fly in determining protein evolutionary rates, suggesting a considerable variation in rate determinants between vertebrates and invertebrates.
| S-EPMC3711421 | biostudies-literature
Project description:Domains are distinct units within proteins that typically can fold independently into recognizable three-dimensional structures to facilitate their functions. The structural and functional independence of protein domains is reflected by their apparent modularity in the context of multi-domain proteins. In this work, we examined the coupling of evolution of domain sequences co-occurring within multi-domain proteins to see if it proceeds independently, or in a coordinated manner. We used continuous information theory measures to assess the extent of correlated mutations among domains in multi-domain proteins from organisms across the tree of life. In all multi-domain architectures we examined, domains co-occurring within protein sequences had to some degree undergone concerted evolution. This finding challenges the notion of complete modularity and independence of protein domains, providing new perspective on the evolution of protein sequence and function.
| S-EPMC6118372 | biostudies-literature
Project description:We have classified 865 sequences of EF-hand proteins from five proteomes into 156 subfamilies. These subfamilies were put into six groups. Evolutionary relationships among subfamilies and groups were analyzed from the inferred ancestral sequence for each subfamily. CTER, CPV, and PEF groups arose from a common EF-lobe (pair of adjacent EF-hands). They have two or more EF-lobes; the relative positions of their EF-lobes differ from each other. Comparisons of the ancestral sequences and the inferred structures of the EF-lobes of these groups indicate that the mutual positions of EF-lobes were established soon after divergence of an EF-lobe for each group and before the duplication and fusion of EF-lobe gene(s). These ancestral sequences reveal that some subfamilies in low similarity and isolated groups did not evolve from the EF-lobe precursor, even if their conformations are similar to the canonical EF-hand. This is an example of convergent evolution.
| S-EPMC5606533 | biostudies-literature
Project description:Phosphatidylinositol transfer proteins (PITP) are a family of monomeric proteins that bind and transfer phosphatidylinositol and phosphatidylcholine between membrane compartments. They are required for production of inositol and diacylglycerol second messengers, and are found in most metazoan organisms. While PITPs are known to carry out crucial cell-signaling roles in many organisms, the structure, function and evolution of the majority of family members remains unexplored; primarily because the ubiquity and diversity of the family thwarts traditional methods of global alignment. To surmount this obstacle, we instead took a novel approach, using MEME and a parsimony-based analysis to create a cladogram of conserved sequence motifs in 56 PITP family proteins from 26 species. In keeping with previous functional annotations, three clades were supported within our evolutionary analysis; two classes of soluble proteins and a class of membrane-associated proteins. By, focusing on conserved regions, the analysis allowed for in depth queries regarding possible functional roles of PITP proteins in both intra- and extra- cellular signaling.
| S-EPMC4943071 | biostudies-literature
Project description:The amino acid sequences of transmembrane regions of helical membrane proteins are highly constrained, diverging at slower rates than their extramembrane regions and than water-soluble proteins. Moreover, helical membrane proteins seem to fall into fewer families than water-soluble proteins. The reason for the differential restrictions on sequence remains unexplained. Here, we show that the evolution of transmembrane regions is slowed by a previously unrecognized structural constraint: Transmembrane regions bury more residues than extramembrane regions and soluble proteins. This fundamental feature of membrane protein structure is an important contributor to the differences in evolutionary rate and to an increased susceptibility of the transmembrane regions to disease-causing single-nucleotide polymorphisms.
| S-EPMC2764890 | biostudies-literature
Project description:BackgroundWhile web-based tools such as BLAST have made identifying conserved gene homologs appear easy, genes with variable sequences pose significant challenges. Functionally important noncoding RNAs (ncRNA) often show low sequence conservation due to genetic variations, including insertions and deletions. Rather than conserved sequences, these RNAs possess highly conserved structural features across a broad phylogenetic range. Such features can be identified using the covariance models approach, which combines sequence alignment with a secondary RNA structure consensus. However, running standard implementation of that approach (Infernal) requires advanced bioinformatics knowledge compared to user-friendly web services like BLAST. The issue is partially addressed by RNAcentral, which can be used to search for homologs across a broad range of ncRNA sequence collections from diverse organisms but not across the genome assemblies.ResultsHere, we present GERONIMO, which conducts evolutionary searches across hundreds of genomes in a fully automated way. It provides results extended with taxonomy context, as summary tables and visualizations, to facilitate analysis for user convenience. Additionally, GERONIMO supplements homologous sequences with genomic regions to analyze promoter motifs or gene collinearity, enhancing the validation of results.ConclusionGERONIMO, built using Snakemake, has undergone extensive testing on hundreds of genomes, establishing itself as a valuable tool in the identification of ncRNA homologs across diverse taxonomic groups. Consequently, GERONIMO facilitates the investigation of the evolutionary patterns of functionally significant ncRNA players, whose understanding has previously been limited to individual organisms and close relatives.
| S-EPMC10580375 | biostudies-literature