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Latrille T, Lartillot N. An Improved Codon Modeling Approach for Accurate Estimation of the Mutation Bias. Mol Biol Evol 2022; 39:6503505. [PMID: 35021218 PMCID: PMC8831783 DOI: 10.1093/molbev/msac005] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Phylogenetic codon models are routinely used to characterize selective regimes in coding sequences. Their parametric design, however, is still a matter of debate, in particular concerning the question of how to account for differing nucleotide frequencies and substitution rates. This problem relates to the fact that nucleotide composition in protein-coding sequences is the result of the interactions between mutation and selection. In particular, because of the structure of the genetic code, the nucleotide composition differs between the three coding positions, with the third position showing a more extreme composition. Yet, phylogenetic codon models do not correctly capture this phenomenon and instead predict that the nucleotide composition should be the same for all three positions. Alternatively, some models allow for different nucleotide rates at the three positions, an approach conflating the effects of mutation and selection on nucleotide composition. In practice, it results in inaccurate estimation of the strength of selection. Conceptually, the problem comes from the fact that phylogenetic codon models do not correctly capture the fixation bias acting against the mutational pressure at the mutation–selection equilibrium. To address this problem and to more accurately identify mutation rates and selection strength, we present an improved codon modeling approach where the fixation rate is not seen as a scalar, but as a tensor. This approach gives an accurate representation of how mutation and selection oppose each other at equilibrium and yields a reliable estimate of the mutational process, while disentangling the mean fixation probabilities prevailing in different mutational directions.
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Affiliation(s)
- T Latrille
- CNRS, Laboratoire de Biométrie et Biologie Évolutive UMR, Université de Lyon, Université Lyon 1, 5558, Villeurbanne, F-69622, France.,École Normale Supérieure de Lyon, Université de Lyon, Université Lyon 1, Lyon, France
| | - N Lartillot
- CNRS, Laboratoire de Biométrie et Biologie Évolutive UMR, Université de Lyon, Université Lyon 1, 5558, Villeurbanne, F-69622, France
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2
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Hubert L, Paganini J, Picard C, Chiaroni J, Abi-Rached L, Pontarotti P, Di Cristofaro J. HLA-H*02:07 Is a Membrane-Bound Ligand of Denisovan Origin That Protects against Lysis by Activated Immune Effectors. THE JOURNAL OF IMMUNOLOGY 2022; 208:49-53. [DOI: 10.4049/jimmunol.2100358] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Accepted: 11/01/2021] [Indexed: 04/08/2023]
Abstract
Abstract
The biological relevance of genes initially categorized as “pseudogenes” is slowly emerging, notably in innate immunity. In the HLA region on chromosome 6, HLA-H is one such pseudogene; yet, it is transcribed, and its variation is associated with immune properties. Furthermore, two HLA-H alleles, H*02:07 and H*02:14, putatively encode a complete, membrane-bound HLA protein. Here we thus hypothesized that HLA-H contributes to immune homeostasis similarly to tolerogenic molecules HLA-G, -E, and -F. We tested if HLA-H*02:07 encodes a membrane-bound protein that can inhibit the cytotoxicity of effector cells. We used an HLA-null human erythroblast cell line transduced with HLA-H*02:07 cDNA to demonstrate that HLA-H*02:07 encodes a membrane-bound protein. Additionally, using a cytotoxicity assay, our results support that K562 HLA-H*02:07 inhibits human effector IL-2–activated PBMCs and human IL-2–independent NK92-MI cell line activity. Finally, through in silico genotyping of the Denisovan genome and haplotypic association with Denisovan-derived HLA-A*11, we also show that H*02:07 is of archaic origin. Hence, admixture with archaic humans brought a functional HLA-H allele into modern European and Asian populations.
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Affiliation(s)
- Lucas Hubert
- *Aix-Marseille University, CNRS, EFS, ADES, “Biologie des Groupes Sanguins,” Marseille, France
- †Etablissement Français du Sang PACA Corse, Marseille, France
| | | | - Christophe Picard
- *Aix-Marseille University, CNRS, EFS, ADES, “Biologie des Groupes Sanguins,” Marseille, France
- †Etablissement Français du Sang PACA Corse, Marseille, France
| | - Jacques Chiaroni
- *Aix-Marseille University, CNRS, EFS, ADES, “Biologie des Groupes Sanguins,” Marseille, France
- †Etablissement Français du Sang PACA Corse, Marseille, France
| | - Laurent Abi-Rached
- §Aix Marseille University, IRD, APHM, MEPHI, IHU-Mediterranée Infection, Marseille, France; and
- ¶CNRS, Marseille, France
| | - Pierre Pontarotti
- §Aix Marseille University, IRD, APHM, MEPHI, IHU-Mediterranée Infection, Marseille, France; and
- ¶CNRS, Marseille, France
| | - Julie Di Cristofaro
- *Aix-Marseille University, CNRS, EFS, ADES, “Biologie des Groupes Sanguins,” Marseille, France
- †Etablissement Français du Sang PACA Corse, Marseille, France
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3
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Klein B, Holmér L, Smith KM, Johnson MM, Swain A, Stolp L, Teufel AI, Kleppe AS. A computational exploration of resilience and evolvability of protein-protein interaction networks. Commun Biol 2021; 4:1352. [PMID: 34857859 PMCID: PMC8639913 DOI: 10.1038/s42003-021-02867-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2020] [Accepted: 11/03/2021] [Indexed: 11/09/2022] Open
Abstract
Protein-protein interaction (PPI) networks represent complex intra-cellular protein interactions, and the presence or absence of such interactions can lead to biological changes in an organism. Recent network-based approaches have shown that a phenotype's PPI network's resilience to environmental perturbations is related to its placement in the tree of life; though we still do not know how or why certain intra-cellular factors can bring about this resilience. Here, we explore the influence of gene expression and network properties on PPI networks' resilience. We use publicly available data of PPIs for E. coli, S. cerevisiae, and H. sapiens, where we compute changes in network resilience as new nodes (proteins) are added to the networks under three node addition mechanisms-random, degree-based, and gene-expression-based attachments. By calculating the resilience of the resulting networks, we estimate the effectiveness of these node addition mechanisms. We demonstrate that adding nodes with gene-expression-based preferential attachment (as opposed to random or degree-based) preserves and can increase the original resilience of PPI network in all three species, regardless of gene expression distribution or network structure. These findings introduce a general notion of prospective resilience, which highlights the key role of network structures in understanding the evolvability of phenotypic traits.
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Affiliation(s)
- Brennan Klein
- Network Science Institute, Northeastern University, Boston, MA, USA. .,Laboratory for the Modeling of Biological and Socio-Technical Systems, Northeastern University, Boston, MA, USA.
| | - Ludvig Holmér
- grid.419684.60000 0001 1214 1861Center for Data Analytics, Stockholm School of Economics, Stockholm, Sweden
| | - Keith M. Smith
- grid.12361.370000 0001 0727 0669Department of Physics and Mathematics, Nottingham Trent University, Nottingham, UK
| | - Mackenzie M. Johnson
- grid.89336.370000 0004 1936 9924Department of Integrative Biology, University of Texas at Austin, Austin, TX USA
| | - Anshuman Swain
- grid.164295.d0000 0001 0941 7177Department of Biology, University of Maryland, College Park, MD USA
| | - Laura Stolp
- grid.7177.60000000084992262Graduate School of Science, University of Amsterdam, Amsterdam, The Netherlands
| | - Ashley I. Teufel
- grid.89336.370000 0004 1936 9924Department of Integrative Biology, University of Texas at Austin, Austin, TX USA ,grid.209665.e0000 0001 1941 1940Santa Fe Institute, Santa Fe, NM USA ,grid.469272.c0000 0001 0180 5693Texas A&M University, San Antonio, San Antonio, TX USA
| | - April S. Kleppe
- grid.5949.10000 0001 2172 9288Institute for Evolution and Biodiversity, University of Münster, Münster, Germany ,grid.7048.b0000 0001 1956 2722Department of Clinical Medicine (MOMA), Aarhus University, Aarhus, Denmark
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4
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Stark TL, Liberles DA. Characterizing Amino Acid Substitution with Complete Linkage of Sites on a Lineage. Genome Biol Evol 2021; 13:6377338. [PMID: 34581792 PMCID: PMC8557849 DOI: 10.1093/gbe/evab225] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/17/2021] [Indexed: 11/16/2022] Open
Abstract
Amino acid substitution models are commonly used for phylogenetic inference, for ancestral sequence reconstruction, and for the inference of positive selection. All commonly used models explicitly assume that each site evolves independently, an assumption that is violated by both linkage and protein structural and functional constraints. We introduce two new models for amino acid substitution which incorporate linkage between sites, each based on the (population-genetic) Moran model. The first model is a generalized population process tracking arbitrarily many sites which undergo mutation, with individuals replaced according to their fitnesses. This model provides a reasonably complete framework for simulations but is numerically and analytically intractable. We also introduce a second model which includes several simplifying assumptions but for which some theoretical results can be derived. We analyze the simplified model to determine conditions where linkage is likely to have meaningful effects on sitewise substitution probabilities, as well as conditions under which the effects are likely to be negligible. These findings are an important step in the generation of tractable phylogenetic models that parameterize selective coefficients for amino acid substitution while accounting for linkage of sites leading to both hitchhiking and background selection.
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Affiliation(s)
- Tristan L Stark
- Department of Biology and Center for Computational Genetics and Genomics, Temple University, Philadelphia, PA, USA
| | - David A Liberles
- Department of Biology and Center for Computational Genetics and Genomics, Temple University, Philadelphia, PA, USA
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5
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Youssef N, Susko E, Roger AJ, Bielawski JP. Shifts in amino acid preferences as proteins evolve: A synthesis of experimental and theoretical work. Protein Sci 2021; 30:2009-2028. [PMID: 34322924 PMCID: PMC8442975 DOI: 10.1002/pro.4161] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2021] [Revised: 07/19/2021] [Accepted: 07/26/2021] [Indexed: 11/08/2022]
Abstract
Amino acid preferences vary across sites and time. While variation across sites is widely accepted, the extent and frequency of temporal shifts are contentious. Our understanding of the drivers of amino acid preference change is incomplete: To what extent are temporal shifts driven by adaptive versus nonadaptive evolutionary processes? We review phenomena that cause preferences to vary (e.g., evolutionary Stokes shift, contingency, and entrenchment) and clarify how they differ. To determine the extent and prevalence of shifted preferences, we review experimental and theoretical studies. Analyses of natural sequence alignments often detect decreases in homoplasy (convergence and reversions) rates, and variation in replacement rates with time-signals that are consistent with temporally changing preferences. While approaches inferring shifts in preferences from patterns in natural alignments are valuable, they are indirect since multiple mechanisms (both adaptive and nonadaptive) could lead to the observed signal. Alternatively, site-directed mutagenesis experiments allow for a more direct assessment of shifted preferences. They corroborate evidence from multiple sequence alignments, revealing that the preference for an amino acid at a site varies depending on the background sequence. However, shifts in preferences are usually minor in magnitude and sites with significantly shifted preferences are low in frequency. The small yet consistent perturbations in preferences could, nevertheless, jeopardize the accuracy of inference procedures, which assume constant preferences. We conclude by discussing if and how such shifts in preferences might influence widely used time-homogenous inference procedures and potential ways to mitigate such effects.
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Affiliation(s)
- Noor Youssef
- Department of BiologyDalhousie UniversityHalifaxNova ScotiaCanada
| | - Edward Susko
- Department of Mathematics and StatisticsDalhousie UniversityHalifaxNova ScotiaCanada
| | - Andrew J. Roger
- Department of Biochemistry and Molecular BiologyDalhousie UniversityHalifaxNova ScotiaCanada
| | - Joseph P. Bielawski
- Department of BiologyDalhousie UniversityHalifaxNova ScotiaCanada
- Department of Mathematics and StatisticsDalhousie UniversityHalifaxNova ScotiaCanada
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6
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Selberg AGA, Gaucher EA, Liberles DA. Ancestral Sequence Reconstruction: From Chemical Paleogenetics to Maximum Likelihood Algorithms and Beyond. J Mol Evol 2021; 89:157-164. [PMID: 33486547 PMCID: PMC7828096 DOI: 10.1007/s00239-021-09993-1] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2020] [Accepted: 01/04/2021] [Indexed: 12/13/2022]
Abstract
As both a computational and an experimental endeavor, ancestral sequence reconstruction remains a timely and important technique. Modern approaches to conduct ancestral sequence reconstruction for proteins are built upon a conceptual framework from journal founder Emile Zuckerkandl. On top of this, work on maximum likelihood phylogenetics published in Journal of Molecular Evolution in 1996 was one of the first approaches for generating maximum likelihood ancestral sequences of proteins. From its computational history, future model development needs as well as potential applications in areas as diverse as computational systems biology, molecular community ecology, infectious disease therapeutics and other biomedical applications, and biotechnology are discussed. From its past in this journal, there is a bright future for ancestral sequence reconstruction in the field of evolutionary biology.
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Affiliation(s)
- Avery G A Selberg
- Department of Biology and Center for Computational Genetics and Genomics, Temple University, Philadelphia, PA, 19122, USA
| | - Eric A Gaucher
- Department of Biology, Georgia State University, Atlanta, GA, 30303, USA
| | - David A Liberles
- Department of Biology and Center for Computational Genetics and Genomics, Temple University, Philadelphia, PA, 19122, USA.
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7
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Chi PB, Kosater WM, Liberles DA. Detecting Signatures of Positive Selection against a Backdrop of Compensatory Processes. Mol Biol Evol 2020; 37:3353-3362. [PMID: 32895716 DOI: 10.1093/molbev/msaa161] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
There are known limitations in methods of detecting positive selection. Common methods do not enable differentiation between positive selection and compensatory covariation, a major limitation. Further, the traditional method of calculating the ratio of nonsynonymous to synonymous substitutions (dN/dS) does not take into account the 3D structure of biomacromolecules nor differences between amino acids. It also does not account for saturation of synonymous mutations (dS) over long evolutionary time that renders codon-based methods ineffective for older divergences. This work aims to address these shortcomings for detecting positive selection through the development of a statistical model that examines clusters of substitutions in clusters of variable radii. Additionally, it uses a parametric bootstrapping approach to differentiate positive selection from compensatory processes. A previously reported case of positive selection in the leptin protein of primates was reexamined using this methodology.
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Affiliation(s)
- Peter B Chi
- Department of Mathematics and Statistics, Villanova University, Villanova, PA.,Department of Biology and Center for Computational Genetics and Genomics, Temple University, Philadelphia, PA
| | - Westin M Kosater
- Department of Biology and Center for Computational Genetics and Genomics, Temple University, Philadelphia, PA
| | - David A Liberles
- Department of Biology and Center for Computational Genetics and Genomics, Temple University, Philadelphia, PA
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8
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Liberles DA, Teufel AI. Evolution and Structure of Proteins and Proteomes. Genes (Basel) 2018; 9:E583. [PMID: 30487453 PMCID: PMC6315575 DOI: 10.3390/genes9120583] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2018] [Accepted: 11/26/2018] [Indexed: 12/13/2022] Open
Abstract
This themed issue centered on the evolution and structure of proteins and proteomes is comprised of seven published manuscripts. [...].
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Affiliation(s)
- David A Liberles
- Department of Biology and Center for Computational Genetics and Genomics, Temple University, Philadelphia, PA 19122, USA.
| | - Ashley I Teufel
- Department of Integrative Biology, Institute for Cellular and Molecular Biology, and Center for Computational Biology and Bioinformatics, The University of Texas at Austin, Austin, TX 78712, USA.
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