The Influence of Selection for Protein Stability on dN/dS Estimations

Understanding the relative contributions of various evolutionary processes—purifying selection, neutral drift, and adaptation—is fundamental to evolutionary biology. A common metric to distinguish these processes is the ratio of nonsynonymous to synonymous substitutions (i.e., dN/dS) interpreted fro...

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Main Authors: Dasmeh, Pouria, Serohijos, Adrian W.R., Kepp, Kasper P., Shakhnovich, Eugene I.
Format: Online
Language:English
Published: Oxford University Press 2014
Online Access:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4224349/
id pubmed-4224349
recordtype oai_dc
spelling pubmed-42243492014-11-10 The Influence of Selection for Protein Stability on dN/dS Estimations Dasmeh, Pouria Serohijos, Adrian W.R. Kepp, Kasper P. Shakhnovich, Eugene I. Research Article Understanding the relative contributions of various evolutionary processes—purifying selection, neutral drift, and adaptation—is fundamental to evolutionary biology. A common metric to distinguish these processes is the ratio of nonsynonymous to synonymous substitutions (i.e., dN/dS) interpreted from the neutral theory as a null model. However, from biophysical considerations, mutations have non-negligible effects on the biophysical properties of proteins such as folding stability. In this work, we investigated how stability affects the rate of protein evolution in phylogenetic trees by using simulations that combine explicit protein sequences with associated stability changes. We first simulated myoglobin evolution in phylogenetic trees with a biophysically realistic approach that accounts for 3D structural information and estimates of changes in stability upon mutation. We then compared evolutionary rates inferred directly from simulation to those estimated using maximum-likelihood (ML) methods. We found that the dN/dS estimated by ML methods (ωML) is highly predictive of the per gene dN/dS inferred from the simulated phylogenetic trees. This agreement is strong in the regime of high stability where protein evolution is neutral. At low folding stabilities and under mutation-selection balance, we observe deviations from neutrality (per gene dN/dS > 1 and dN/dS < 1). We showed that although per gene dN/dS is robust to these deviations, ML tests for positive selection detect statistically significant per site dN/dS > 1. Altogether, we show how protein biophysics affects the dN/dS estimations and its subsequent interpretation. These results are important for improving the current approaches for detecting positive selection. Oxford University Press 2014-10-21 /pmc/articles/PMC4224349/ /pubmed/25355808 http://dx.doi.org/10.1093/gbe/evu223 Text en © The Author(s) 2014. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
repository_type Open Access Journal
institution_category Foreign Institution
institution US National Center for Biotechnology Information
building NCBI PubMed
collection Online Access
language English
format Online
author Dasmeh, Pouria
Serohijos, Adrian W.R.
Kepp, Kasper P.
Shakhnovich, Eugene I.
spellingShingle Dasmeh, Pouria
Serohijos, Adrian W.R.
Kepp, Kasper P.
Shakhnovich, Eugene I.
The Influence of Selection for Protein Stability on dN/dS Estimations
author_facet Dasmeh, Pouria
Serohijos, Adrian W.R.
Kepp, Kasper P.
Shakhnovich, Eugene I.
author_sort Dasmeh, Pouria
title The Influence of Selection for Protein Stability on dN/dS Estimations
title_short The Influence of Selection for Protein Stability on dN/dS Estimations
title_full The Influence of Selection for Protein Stability on dN/dS Estimations
title_fullStr The Influence of Selection for Protein Stability on dN/dS Estimations
title_full_unstemmed The Influence of Selection for Protein Stability on dN/dS Estimations
title_sort influence of selection for protein stability on dn/ds estimations
description Understanding the relative contributions of various evolutionary processes—purifying selection, neutral drift, and adaptation—is fundamental to evolutionary biology. A common metric to distinguish these processes is the ratio of nonsynonymous to synonymous substitutions (i.e., dN/dS) interpreted from the neutral theory as a null model. However, from biophysical considerations, mutations have non-negligible effects on the biophysical properties of proteins such as folding stability. In this work, we investigated how stability affects the rate of protein evolution in phylogenetic trees by using simulations that combine explicit protein sequences with associated stability changes. We first simulated myoglobin evolution in phylogenetic trees with a biophysically realistic approach that accounts for 3D structural information and estimates of changes in stability upon mutation. We then compared evolutionary rates inferred directly from simulation to those estimated using maximum-likelihood (ML) methods. We found that the dN/dS estimated by ML methods (ωML) is highly predictive of the per gene dN/dS inferred from the simulated phylogenetic trees. This agreement is strong in the regime of high stability where protein evolution is neutral. At low folding stabilities and under mutation-selection balance, we observe deviations from neutrality (per gene dN/dS > 1 and dN/dS < 1). We showed that although per gene dN/dS is robust to these deviations, ML tests for positive selection detect statistically significant per site dN/dS > 1. Altogether, we show how protein biophysics affects the dN/dS estimations and its subsequent interpretation. These results are important for improving the current approaches for detecting positive selection.
publisher Oxford University Press
publishDate 2014
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4224349/
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