Protein evolution is structure dependent and non-homogeneous across the tree of life

Pandey, Akanksha; Braun, Edward L.

doi:10.1145/3388440.3412473

Cited by 13 publications

(40 citation statements)

References 64 publications

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“…The amino acid frequencies conformed to our expectations; for example, polar amino acids dominated the solvent exposed positions whereas hydrophobic amino acids were more common in the buried environment. Likewise, the rate matrix exchangeabilities for the exposed and buried sites were similar to those observed by Pandey and Braun [11] (Supplementary File S2). Adding among-sites heterogeneity in amino acid frequencies using the PMSF approach improved model fit relative to site-homogeneous models for all data subsets.…”

Section: Rich Taxon Sampling Can Compensate For Low Model Complexitysupporting

confidence: 82%

“…The third and final conclusion of this study relates to the intersection of phylogenetics and protein structure: different topological signals can be associated with sites in different protein structural environments. Given the extensive evidence that patterns of protein evolution are structure dependent [6][7][8][10][11][12] it might not be surprising that structure can have an impact on estimates of phylogeny, especially for studies focused on difficult parts of the tree of life, like the position of the metazoan root, are examined. Wilke [102] lamented that a negative aspect of the efforts to improve models of sequence evolution "...has been that the underlying biophysical objects represented by the sequences, DNA molecules, RNA molecules, and proteins, have taken a back-seat in much computational molecular-evolution work."…”

Section: Discussionmentioning

confidence: 99%

“…The FSD comprised 1,566 globular proteins with 356,014 aligned sites and 39% missing data. The globular proteins were then subdivided using either relative solvent accessibility (RSA) or secondary structure (SS) as described by Pandey and Braun [11,12]. Briefly, the protein subdivision pipeline (available from (https://github.com/aakank-sha12/Structural_class_assignment_pipeline) used SCRATCH-1D [66], a suite of neural network programs for protein structure prediction (ACCpro for RSA and SSpro for SS).…”

Section: Methodsmentioning

confidence: 99%

“…Our understanding of the factors that determines rates of amino acid change have certainly expanded since those pioneering studies [4,5] but two important constants have been the idea that the buried residues in globular proteins evolve more slowly [6][7][8] and are more hydrophobic than solvent exposed residues [8,9]. Likewise, relative amino acid exchangeabilities also differ among structural environments [7,10,11]. However, the relationship between protein structure and phylogenetic signal is less clear.…”

Section: Introductionmentioning

confidence: 99%

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The Roles of Protein Structure, Taxon Sampling, and Model Complexity in Phylogenomics: A Case Study Focused on Early Animal Divergences

Pandey¹,

Braun²

2021

Preprint

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Despite the long history of using protein sequences to infer the tree of life the potential for different parts of protein structures to retain historical signal remains unclear. We propose that it might be possible to improve analyses of phylogenomic datasets by incorporating information about protein structure; we test this idea using the position of the root of Metazoa (animals) as a model system. We examined the distribution of “strongly decisive” sites (alignment positions that support a specific tree topology) in a dataset comprising &gt;1,500 proteins and almost 100 taxa. The proportion of each class of strongly decisive sites in different structural environments was very sensitive to the model used to analyze the data when a limited number of taxa were used but they were stable when taxa were added. As long as enough taxa were analyzed, sites in all structural environments supported the same topology (ctenophores sister to other animals) regardless of whether standard tree searches or decisive sites were used to select the optimal tree. However, the use of decisive sites revealed a difference between the support for minority topologies for sites in different structural environments; buried sites and sites in sheet and coil environments exhibited equal support for the minority topologies whereas solvent exposed and helix sites had unequal numbers of sites supporting the minority topologies. Given the plausible trees equal support for minority topologies is consistent with discordance among gene trees, making it possible the relatively slowly evolving buried (and sheet and coil) sites are giving an accurate picture of the true species tree as well as the amount of conflict among gene trees. Alternatively, the apparent support could reflect currently uncharacterized processes of molecular evolution. Regardless, it is clear that analyses of the deepest branches in the animal tree of life using sites in different structural environments are associated with a subtle data type effect that results in distinct phylogenetic signals.

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Section: Rich Taxon Sampling Can Compensate For Low Model Complexitysupporting

confidence: 82%

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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The Roles of Protein Structure, Taxon Sampling, and Model Complexity in Phylogenomics: A Case Study Focused on Early Animal Divergences

Pandey¹,

Braun²

2021

Preprint

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“…Pandey and Braun [17,20] described another data type effect involving solvent exposed versus buried residues in globular proteins that has an impact on the topology for the earliest divergences among metazoa. Although the basis for that data type effect is unclear, it is clear that the best models of sequence evolution differ for buried versus exposed residues [17,[29][30][31]. We believe that data type effects related to protein structure might be especially fertile ground for understanding data type effects.…”

Section: Introductionmentioning

confidence: 99%

Protein Structure, Models of Sequence Evolution, and Data Type Effects in Phylogenetic Analyses of Mitochondrial Data: A Case Study in Birds

Gordon¹,

Kimball²,

Braun³

2021

Preprint

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Phylogenomic analyses have revolutionized the study of biodiversity, but they have revealed that estimated tree topologies can depend, at least in part, on the subset of the genome that is analyzed. For example, estimates of trees for avian orders differ if protein coding or non-coding data are analyzed. The bird tree is a good study system because the historical signal for relationships among orders is very weak, which should permit subtle non-historical signals to be identified, while monophyly of orders is strongly corroborated, allowing identification of strong non-historical signals. Hydrophobic amino acids in mitochondrially-encoded proteins, which are expected to be found in transmembrane helices, have been hypothesized to be associated with non-historical signals. We tested this hypothesis by comparing the evolution of transmembrane helices and extramembrane segments of mitochondrial proteins from 420 bird species, sampled from most avian orders. We estimated amino acids exchangeabilities for both structural environments and assessed the performance of phylogenetic analysis using each data type. We compared those relative exchangeabilities with values calculated using a substitution dataset for transmembrane helices from a variety of sampled set of nuclear- and mitochondrially-encoded proteins, allowing us to compare the bird-specific mitochondrial models with a general model of transmembrane protein evolution. To complement our amino acid analyses, we examined the impact of protein structure on patterns of nucleotide evolution. Models of transmembrane and extramembrane sequence evolution for amino acids and nucleotides exhibited striking differences, but there was no evidence for strong topological data type effects. However, incorporating protein structure into analyses of mitochondrially-encoded proteins improved model fit. Thus, we believe that considering protein structure will improve analyses of mitogenomic data, both in birds and in other taxa.

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Selection among site-dependent structurally constrained substitution models of protein evolution by approximate Bayesian computation

Ferreiro,

Branco,

Arenas

2024

Bioinformatics

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Motivation The selection among substitution models of molecular evolution is fundamental for obtaining accurate phylogenetic inferences. At the protein level, evolutionary analyses are traditionally based on empirical substitution models but these models make unrealistic assumptions and are being surpassed by structurally constrained substitution (SCS) models. The SCS models often consider site-dependent evolution, a process that provides realism but complicates their implementation into likelihood functions that are commonly used for substitution model selection. Results We present a method to perform selection among site-dependent SCS models, also among empirical and site-dependent SCS models, based on the approximate Bayesian computation (ABC) approach and its implementation into the computational framework ProteinModelerABC. The framework implements ABC with and without regression adjustments and includes diverse empirical and site-dependent SCS models of protein evolution. Using extensive simulated data, we found that it provides selection among SCS and empirical models with acceptable accuracy. As illustrative examples, we applied the framework to analyse a variety of protein families observing that SCS models fit them better than the corresponding best-fitting empirical substitution models. Availability ProteinModelerABC is freely available from https://github.com/DavidFerreiro/ProteinModelerABC, can run in parallel and includes a graphical user interface. The framework is distributed with detailed documentation and ready-to-use examples. Supplementary information Supplementary material is available at Bioinformatics online.

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Protein evolution is structure dependent and non-homogeneous across the tree of life

Cited by 13 publications

References 64 publications

The Roles of Protein Structure, Taxon Sampling, and Model Complexity in Phylogenomics: A Case Study Focused on Early Animal Divergences

The Roles of Protein Structure, Taxon Sampling, and Model Complexity in Phylogenomics: A Case Study Focused on Early Animal Divergences

Protein Structure, Models of Sequence Evolution, and Data Type Effects in Phylogenetic Analyses of Mitochondrial Data: A Case Study in Birds

Selection among site-dependent structurally constrained substitution models of protein evolution by approximate Bayesian computation

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