scholarly journals Peer Review #2 of "Calculating site-specific evolutionary rates at the amino-acid or codon level yields similar rate estimates (v0.1)"

2017 ◽  
Author(s):  
GB Golding
Keyword(s):  
Amino Acid ◽  
Peer Review ◽  
Similar Rate ◽  
Evolutionary Rates ◽  
Site Specific

scholarly journals Calculating site-specific evolutionary rates at the amino-acid or codon level yields similar rate estimates

PeerJ ◽  
2017 ◽  
Vol 5 ◽  
pp. e3391 ◽  
Author(s):  
Dariya K. Sydykova ◽  
Claus O. Wilke
Keyword(s):  
Amino Acid ◽  
Conservation Score ◽  
Amino Acid Level ◽  
Sequence Divergence ◽  
Similar Rate ◽  
Amino Acid Sequences ◽  
Evolutionary Rates ◽  
Site Specific ◽  
Relative Conservation ◽  
The Relationship

Site-specific evolutionary rates can be estimated from codon sequences or from amino-acid sequences. For codon sequences, the most popular methods use some variation of the dN∕dS ratio. For amino-acid sequences, one widely-used method is called Rate4Site, and it assigns a relative conservation score to each site in an alignment. How site-wise dN∕dS values relate to Rate4Site scores is not known. Here we elucidate the relationship between these two rate measurements. We simulate sequences with known dN∕dS, using either dN∕dS models or mutation–selection models for simulation. We then infer Rate4Site scores on the simulated alignments, and we compare those scores to either true or inferred dN∕dS values on the same alignments. We find that Rate4Site scores generally correlate well with true dN∕dS, and the correlation strengths increase in alignments with greater sequence divergence and more taxa. Moreover, Rate4Site scores correlate very well with inferred (as opposed to true) dN∕dS values, even for small alignments with little divergence. Finally, we verify this relationship between Rate4Site and dN∕dS in a variety of empirical datasets. We conclude that codon-level and amino-acid-level analysis frameworks are directly comparable and yield very similar inferences.

scholarly journals Calculating site-specific evolutionary rates at the amino-acid or codon level yields similar rate estimates

2017 ◽  
Author(s):  
Dariya K. Sydykova ◽  
Claus O Wilke
Keyword(s):  
Amino Acid ◽  
Conservation Score ◽  
Amino Acid Level ◽  
Sequence Divergence ◽  
Similar Rate ◽  
Amino Acid Sequences ◽  
Evolutionary Rates ◽  
Sequence Alignments ◽  
Site Specific ◽  
Relative Conservation

Site-specific evolutionary rates can be estimated from codon sequences or from amino-acid sequences. For codon sequences, the most popular methods use some variation of the dN/dS ratio. For amino-acid sequences, one widely-used method is called Rate4Site, and it assigns a relative conservation score to each site in an alignment. How site-wise dN/dS values relate to Rate4Site scores is not known. Here we elucidate the relationship between these two rate measurements. We simulate sequences with known dN/dS, using either dN/dS models or mutation--selection models for simulation. We then infer Rate4Site scores on the simulated alignments, and we compare those scores to either true or inferred dN/dS values on the same alignments. We find that Rate4Site scores generally correlate well with true dN/dS, and the correlation strengths increase in alignments with higher sequence divergence and higher number of taxa. Moreover, Rate4Site scores correlate nearly perfectly with inferred dN/dS values, even for small alignments with little divergence. Finally, we verify this relationship between Rate4Site and dN/dS in a variety of natural sequence alignments. We conclude that codon-level and amino-acid-level analysis frameworks are directly comparable and yield near-identical inferences.

scholarly journals Calculating site-specific evolutionary rates at the amino-acid or codon level yields similar rate estimates

2017 ◽  
Author(s):  
Dariya K. Sydykova ◽  
Claus O Wilke
Keyword(s):  
Amino Acid ◽  
Conservation Score ◽  
Amino Acid Level ◽  
Sequence Divergence ◽  
Similar Rate ◽  
Amino Acid Sequences ◽  
Evolutionary Rates ◽  
Sequence Alignments ◽  
Site Specific ◽  
Relative Conservation

Site-specific evolutionary rates can be estimated from codon sequences or from amino-acid sequences. For codon sequences, the most popular methods use some variation of the dN/dS ratio. For amino-acid sequences, one widely-used method is called Rate4Site, and it assigns a relative conservation score to each site in an alignment. How site-wise dN/dS values relate to Rate4Site scores is not known. Here we elucidate the relationship between these two rate measurements. We simulate sequences with known dN/dS, using either dN/dS models or mutation--selection models for simulation. We then infer Rate4Site scores on the simulated alignments, and we compare those scores to either true or inferred dN/dS values on the same alignments. We find that Rate4Site scores generally correlate well with true dN/dS, and the correlation strengths increase in alignments with higher sequence divergence and higher number of taxa. Moreover, Rate4Site scores correlate nearly perfectly with inferred dN/dS values, even for small alignments with little divergence. Finally, we verify this relationship between Rate4Site and dN/dS in a variety of natural sequence alignments. We conclude that codon-level and amino-acid-level analysis frameworks are directly comparable and yield near-identical inferences.

scholarly journals Theory of measurement for site-specific evolutionary rates in amino-acid sequences

2017 ◽  
Author(s):  
Dariya K Sydykova ◽  
Claus O Wilke
Keyword(s):  
Amino Acid ◽  
Fitness Landscape ◽  
Protein Complexes ◽  
Theory Of Measurement ◽  
Amino Acid Sequences ◽  
Selection Model ◽  
Evolutionary Rates ◽  
Site Specific ◽  
The Matrix ◽  
Tree Inference

Many applications require the calculation of site-specific evolutionary rates from alignments of amino-acid sequences. For example, catalytic residues in enzymes and interface regions in protein complexes can be inferred from observed relative rates. While numerous approaches exist to calculate amino-acid rates, however, it is not entirely clear what physical quantities the inferred rates represent and how these rates relate to the underlying fitness landscape of the evolving protein. Further, amino-acid rates can be calculated in the context of different amino-acid exchangeability matrices, such as JTT, LG, or WAG, and again it is not known how the choice of the matrix influences the physical interpretation of the inferred rates. Here, we develop a theory of measurement for site-specific evolutionary rates, but analytically solving the maximum-likelihood equations for rate inference performed on sequences evolved under a mutation–selection model. We demonstrate that the measurement process can only recover the true expected rates of the mutation–selection model if rates are measured relative to a naïve exchangeability matrix, in which all exchangeabilities are equal to one. Rate measurements using other matrices are quantitatively close but not mathematically correct. Our results demonstrate that insights obtained from phylogenetic-tree inference do not necessarily apply to rate inference, and best practices for the former may be deleterious for the latter.

scholarly journals Large-Scale Analyses of Site-Specific Evolutionary Rates across Eukaryote Proteomes Reveal Confounding Interactions between Intrinsic Disorder, Secondary Structure, and Functional Domains

Genes ◽  
2018 ◽  
Vol 9 (11) ◽  
pp. 553 ◽  
Author(s):  
Joseph Ahrens ◽  
Jordon Rahaman ◽  
Jessica Siltberg-Liberles
Keyword(s):  
Amino Acid ◽  
Secondary Structure ◽  
Large Scale ◽  
Intrinsic Disorder ◽  
Secondary Structures ◽  
Amino Acid Replacement ◽  
Evolutionary Rates ◽  
Functional Domains ◽  
Site Specific ◽  
Statistical Trends

Various structural and functional constraints govern the evolution of protein sequences. As a result, the relative rates of amino acid replacement among sites within a protein can vary significantly. Previous large-scale work on Metazoan (Animal) protein sequence alignments indicated that amino acid replacement rates are partially driven by a complex interaction among three factors: intrinsic disorder propensity; secondary structure; and functional domain involvement. Here, we use sequence-based predictors to evaluate the effects of these factors on site-specific sequence evolutionary rates within four eukaryotic lineages: Metazoans; Plants; Saccharomycete Fungi; and Alveolate Protists. Our results show broad, consistent trends across all four Eukaryote groups. In all four lineages, there is a significant increase in amino acid replacement rates when comparing: (i) disordered vs. ordered sites; (ii) random coil sites vs. sites in secondary structures; and (iii) inter-domain linker sites vs. sites in functional domains. Additionally, within Metazoans, Plants, and Saccharomycetes, there is a strong confounding interaction between intrinsic disorder and secondary structure—alignment sites exhibiting both high disorder propensity and involvement in secondary structures have very low average rates of sequence evolution. Analysis of gene ontology (GO) terms revealed that in all four lineages, a high fraction of sequences containing these conserved, disordered-structured sites are involved in nucleic acid binding. We also observe notable differences in the statistical trends of Alveolates, where intrinsically disordered sites are more variable than in other Eukaryotes and the statistical interactions between disorder and other factors are less pronounced.

scholarly journals Theory of measurement for site-specific evolutionary rates in amino-acid sequences

2017 ◽  
Author(s):  
Dariya K Sydykova ◽  
Claus O Wilke
Keyword(s):  
Amino Acid ◽  
Fitness Landscape ◽  
Protein Complexes ◽  
Theory Of Measurement ◽  
Amino Acid Sequences ◽  
Selection Model ◽  
Evolutionary Rates ◽  
Site Specific ◽  
The Matrix ◽  
Tree Inference

Many applications require the calculation of site-specific evolutionary rates from alignments of amino-acid sequences. For example, catalytic residues in enzymes and interface regions in protein complexes can be inferred from observed relative rates. While numerous approaches exist to calculate amino-acid rates, however, it is not entirely clear what physical quantities the inferred rates represent and how these rates relate to the underlying fitness landscape of the evolving protein. Further, amino-acid rates can be calculated in the context of different amino-acid exchangeability matrices, such as JTT, LG, or WAG, and again it is not known how the choice of the matrix influences the physical interpretation of the inferred rates. Here, we develop a theory of measurement for site-specific evolutionary rates, but analytically solving the maximum-likelihood equations for rate inference performed on sequences evolved under a mutation–selection model. We demonstrate that the measurement process can only recover the true expected rates of the mutation–selection model if rates are measured relative to a naïve exchangeability matrix, in which all exchangeabilities are equal to one. Rate measurements using other matrices are quantitatively close but not mathematically correct. Our results demonstrate that insights obtained from phylogenetic-tree inference do not necessarily apply to rate inference, and best practices for the former may be deleterious for the latter.

Sign in / Sign up

Export Citation Format

Share Document