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Bao K, Strayer BR, Braker NP, Chan AA, Sharp NP. Mutations in yeast are deleterious on average regardless of the degree of adaptation to the testing environment. Proc Biol Sci 2024; 291:20240064. [PMID: 38889780 DOI: 10.1098/rspb.2024.0064] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Accepted: 04/29/2024] [Indexed: 06/20/2024] Open
Abstract
The role of spontaneous mutations in evolution depends on the distribution of their effects on fitness. Despite a general consensus that new mutations are deleterious on average, a handful of mutation accumulation experiments in diverse organisms instead suggest that beneficial and deleterious mutations can have comparable fitness impacts, i.e. the product of their respective rates and effects can be roughly equal. We currently lack a general framework for predicting when such a pattern will occur. One idea is that beneficial mutations will be more evident in genotypes that are not well adapted to the testing environment. We tested this prediction experimentally in the laboratory yeast Saccharomyces cerevisiae by allowing nine replicate populations to adapt to novel environments with complex sets of stressors. After >1000 asexual generations interspersed with 41 rounds of sexual reproduction, we assessed the mean effect of induced mutations on yeast growth in both the environment to which they had been adapting and the alternative novel environment. The mutations were deleterious on average, with the severity depending on the testing environment. However, we found no evidence that the adaptive match between genotype and environment is predictive of mutational fitness effects.
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Affiliation(s)
- Kevin Bao
- Department of Genetics, University of Wisconsin-Madison 425-G Henry Mall, Madison, Wisconsin 53706, USA
| | - Brant R Strayer
- Department of Genetics, University of Wisconsin-Madison 425-G Henry Mall, Madison, Wisconsin 53706, USA
| | - Neil P Braker
- Department of Genetics, University of Wisconsin-Madison 425-G Henry Mall, Madison, Wisconsin 53706, USA
| | - Alexandra A Chan
- Department of Genetics, University of Wisconsin-Madison 425-G Henry Mall, Madison, Wisconsin 53706, USA
| | - Nathaniel P Sharp
- Department of Genetics, University of Wisconsin-Madison 425-G Henry Mall, Madison, Wisconsin 53706, USA
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Joseph J. Increased Positive Selection in Highly Recombining Genes Does not Necessarily Reflect an Evolutionary Advantage of Recombination. Mol Biol Evol 2024; 41:msae107. [PMID: 38829800 PMCID: PMC11173204 DOI: 10.1093/molbev/msae107] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Revised: 04/08/2024] [Accepted: 05/28/2024] [Indexed: 06/05/2024] Open
Abstract
It is commonly thought that the long-term advantage of meiotic recombination is to dissipate genetic linkage, allowing natural selection to act independently on different loci. It is thus theoretically expected that genes with higher recombination rates evolve under more effective selection. On the other hand, recombination is often associated with GC-biased gene conversion (gBGC), which theoretically interferes with selection by promoting the fixation of deleterious GC alleles. To test these predictions, several studies assessed whether selection was more effective in highly recombining genes (due to dissipation of genetic linkage) or less effective (due to gBGC), assuming a fixed distribution of fitness effects (DFE) for all genes. In this study, I directly derive the DFE from a gene's evolutionary history (shaped by mutation, selection, drift, and gBGC) under empirical fitness landscapes. I show that genes that have experienced high levels of gBGC are less fit and thus have more opportunities for beneficial mutations. Only a small decrease in the genome-wide intensity of gBGC leads to the fixation of these beneficial mutations, particularly in highly recombining genes. This results in increased positive selection in highly recombining genes that is not caused by more effective selection. Additionally, I show that the death of a recombination hotspot can lead to a higher dN/dS than its birth, but with substitution patterns biased towards AT, and only at selected positions. This shows that controlling for a substitution bias towards GC is therefore not sufficient to rule out the contribution of gBGC to signatures of accelerated evolution. Finally, although gBGC does not affect the fixation probability of GC-conservative mutations, I show that by altering the DFE, gBGC can also significantly affect nonsynonymous GC-conservative substitution patterns.
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Affiliation(s)
- Julien Joseph
- Laboratoire de Biométrie et Biologie Evolutive, Université Lyon 1, CNRS, UMR 5558, Villeurbanne, France
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Sendrowski J, Bataillon T. fastDFE: Fast and Flexible Inference of the Distribution of Fitness Effects. Mol Biol Evol 2024; 41:msae070. [PMID: 38577958 PMCID: PMC11140822 DOI: 10.1093/molbev/msae070] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2024] [Revised: 03/19/2024] [Accepted: 03/25/2024] [Indexed: 04/06/2024] Open
Abstract
Estimating the distribution of fitness effects (DFE) of new mutations is of fundamental importance in evolutionary biology, ecology, and conservation. However, existing methods for DFE estimation suffer from limitations, such as slow computation speed and limited scalability. To address these issues, we introduce fastDFE, a Python-based software package, offering fast, and flexible DFE inference from site-frequency spectrum (SFS) data. Apart from providing efficient joint inference of multiple DFEs that share parameters, it offers the feature of introducing genomic covariates that influence the DFEs and testing their significance. To further simplify usage, fastDFE is equipped with comprehensive VCF-to-SFS parsing utilities. These include options for site filtering and stratification, as well as site-degeneracy annotation and probabilistic ancestral-allele inference. fastDFE thereby covers the entire workflow of DFE inference from the moment of acquiring a raw VCF file. Despite its Python foundation, fastDFE incorporates a full R interface, including native R visualization capabilities. The package is comprehensively tested and documented at fastdfe.readthedocs.io.
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Affiliation(s)
- Janek Sendrowski
- Bioinformatics Research Center, Aarhus University, Aarhus, Denmark
| | - Thomas Bataillon
- Bioinformatics Research Center, Aarhus University, Aarhus, Denmark
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Xu X, Qi Z, Wang L, Zhang M, Geng Z, Han X. Gsw-fi: a GLM model incorporating shrinkage and double-weighted strategies for identifying cancer driver genes with functional impact. BMC Bioinformatics 2024; 25:99. [PMID: 38448819 PMCID: PMC10916024 DOI: 10.1186/s12859-024-05707-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Accepted: 02/16/2024] [Indexed: 03/08/2024] Open
Abstract
BACKGROUND Cancer, a disease with high morbidity and mortality rates, poses a significant threat to human health. Driver genes, which harbor mutations accountable for the initiation and progression of tumors, play a crucial role in cancer development. Identifying driver genes stands as a paramount objective in cancer research and precision medicine. RESULTS In the present work, we propose a method for identifying driver genes using a Generalized Linear Regression Model (GLM) with Shrinkage and double-Weighted strategies based on Functional Impact, which is named GSW-FI. Firstly, an estimating model is proposed for assessing the background functional impacts of genes based on GLM, utilizing gene features as predictors. Secondly, the shrinkage and double-weighted strategies as two revising approaches are integrated to ensure the rationality of the identified driver genes. Lastly, a statistical method of hypothesis testing is designed to identify driver genes by leveraging the estimated background function impacts. Experimental results conducted on 31 The Cancer Genome Altas datasets demonstrate that GSW-FI outperforms ten other prediction methods in terms of the overlap fraction with well-known databases and consensus predictions among different methods. CONCLUSIONS GSW-FI presents a novel approach that efficiently identifies driver genes with functional impact mutations using computational methods, thereby advancing the development of precision medicine for cancer.
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Affiliation(s)
- Xiaolu Xu
- School of Computer and Artificial Intelligence, Liaoning Normal University, Dalian, China
| | - Zitong Qi
- Department of Statistics, University of Washington, Seattle, USA
| | - Lei Wang
- Center for Reproductive and Genetic Medicine, Dalian Women and Children's Medical Group, Dalian, China.
| | - Meiwei Zhang
- Center for Reproductive and Genetic Medicine, Dalian Women and Children's Medical Group, Dalian, China.
| | - Zhaohong Geng
- Department of Cardiology, Second Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Xiumei Han
- College of Artificial Intelligence, Dalian Maritime University, Dalian, China
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Lichter EZ, Trease AJ, Cooper K, Stauch KL, Fox HS. Effects of Parkin on the Mitochondrial Genome in the Heart and Brain of Mitochondrial Mutator Mice. Adv Biol (Weinh) 2023; 7:e2300154. [PMID: 37376822 DOI: 10.1002/adbi.202300154] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Indexed: 06/29/2023]
Abstract
Mitochondrial dysfunction has been implicated in neurodegenerative diseases like Parkinson's disease (PD). This study investigates the role of Parkin, a protein involved in mitochondrial quality control, and strongly linked to PD, in the context of mitochondrial DNA (mtDNA) mutations. Mitochondrial mutator mice (PolgD257A/D257A ) (Polg) are used and bred with Parkin knockout (PKO) mice or mice with disinhibited Parkin (W402A). In the brain, mtDNA mutations are analyzed in synaptosomes, presynaptic neuronal terminals, which are far from neuronal soma, which likely renders mitochondria there more vulnerable compared with brain homogenate. Surprisingly, PKO results in reduced mtDNA mutations in the brain but increased control region multimer (CRM) in synaptosomes. In the heart, both PKO and W402A lead to increased mutations, with W402A showing more mutations in the heart than PKO. Computational analysis reveals many of these mutations are deleterious. These findings suggest that Parkin plays a tissue-dependent role in regulating mtDNA damage response, with differential effects in the brain and heart. Understanding the specific role of Parkin in different tissues may provide insights into the underlying mechanisms of PD and potential therapeutic strategies. Further investigation into these pathways can enhance the understanding of neurodegenerative diseases associated with mitochondrial dysfunction.
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Affiliation(s)
- Eliezer Z Lichter
- Department of Neurological Sciences, University of Nebraska Medical Center, Omaha, NE, 68198, USA
| | - Andrew J Trease
- Department of Neurological Sciences, University of Nebraska Medical Center, Omaha, NE, 68198, USA
| | - Kathryn Cooper
- School of Interdisciplinary Informatics, University of Nebraska Omaha, Omaha, NE, 68182, USA
| | - Kelly L Stauch
- Department of Neurological Sciences, University of Nebraska Medical Center, Omaha, NE, 68198, USA
| | - Howard S Fox
- Department of Neurological Sciences, University of Nebraska Medical Center, Omaha, NE, 68198, USA
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Latrille T, Rodrigue N, Lartillot N. Genes and sites under adaptation at the phylogenetic scale also exhibit adaptation at the population-genetic scale. Proc Natl Acad Sci U S A 2023; 120:e2214977120. [PMID: 36897968 PMCID: PMC10089192 DOI: 10.1073/pnas.2214977120] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Accepted: 02/11/2023] [Indexed: 03/12/2023] Open
Abstract
Adaptation in protein-coding sequences can be detected from multiple sequence alignments across species or alternatively by leveraging polymorphism data within a population. Across species, quantification of the adaptive rate relies on phylogenetic codon models, classically formulated in terms of the ratio of nonsynonymous over synonymous substitution rates. Evidence of an accelerated nonsynonymous substitution rate is considered a signature of pervasive adaptation. However, because of the background of purifying selection, these models are potentially limited in their sensitivity. Recent developments have led to more sophisticated mutation-selection codon models aimed at making a more detailed quantitative assessment of the interplay between mutation, purifying, and positive selection. In this study, we conducted a large-scale exome-wide analysis of placental mammals with mutation-selection models, assessing their performance at detecting proteins and sites under adaptation. Importantly, mutation-selection codon models are based on a population-genetic formalism and thus are directly comparable to the McDonald and Kreitman test at the population level to quantify adaptation. Taking advantage of this relationship between phylogenetic and population genetics analyses, we integrated divergence and polymorphism data across the entire exome for 29 populations across 7 genera and showed that proteins and sites detected to be under adaptation at the phylogenetic scale are also under adaptation at the population-genetic scale. Altogether, our exome-wide analysis shows that phylogenetic mutation-selection codon models and the population-genetic test of adaptation can be reconciled and are congruent, paving the way for integrative models and analyses across individuals and populations.
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Affiliation(s)
- Thibault Latrille
- Université de Lyon, Université Lyon 1, CNRS, VetAgro Sup, Laboratoire de Biométrie et Biologie Evolutive, UMR5558, 69100Villeurbanne, France
- École Normale Supérieure de Lyon, Université de Lyon, 69342Lyon, France
- Department of Computational Biology, Université de Lausanne, 1015Lausanne, Switzerland
| | - Nicolas Rodrigue
- Department of Biology, Institute of Biochemistry, and School of Mathematics and Statistics, Carleton University, K1S 5B6Ottawa, Canada
| | - Nicolas Lartillot
- Université de Lyon, Université Lyon 1, CNRS, VetAgro Sup, Laboratoire de Biométrie et Biologie Evolutive, UMR5558, 69100Villeurbanne, France
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Liu C, Liu X, Wang R, Chen L, Zhao H, Zhou Y. A Novel NCSTN Mutation in a Three-Generation Chinese Family with Hidradenitis Suppurative. JOURNAL OF HEALTHCARE ENGINEERING 2022; 2022:1540774. [PMID: 35368949 PMCID: PMC8970804 DOI: 10.1155/2022/1540774] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/19/2022] [Revised: 02/11/2022] [Accepted: 03/03/2022] [Indexed: 11/23/2022]
Abstract
Objective Hidradenitis suppurativa (HS) is a rare autosomal dominant condition characterized by inflamed nodules, cysts, deep abscesses, draining sinuses in the axillae, inguinal, and anogenital regions. Mutations in the NCSTN gene have been perceived to be responsible for the major underlying changes in the disorder. The purpose of this study is to identify a novel gene mutation in a Chinese family with HS. Methods A Chinese family with HS present was investigated. The proband had manifested with multiple draining sinuses on the posterior neck, chest, bilateral axillae, and perineal regions. DNA was isolated from the peripheral blood of the family members. The encoding exons with introns of the NCSTN gene were analyzed by polymerase chain reactions (PCR) and direct DNA sequencing. Sanger sequencing was performed to confirm the next-generation sequencing results and to analyze each mutation's familial segregation. Furthermore, the identified mutation was localized onto a 3D structure model using the DeepView Swiss-PdbViewer 4.1 software. Results In this family comprising 10 HS patients, one novel mutation of the NCSTN gene was identified, involving a deletion mutation (c.447delC(p.N150Ifs∗52)) in the NCSTN gene resulting in a frameshift and the new formation of a hydrogen bond. Conclusion Our study reports the identification of a novel mutation that causes familial HS and could expand the spectrum of mutations in the γ-secretase genes underlying HS.
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Affiliation(s)
- Chengling Liu
- Department of Dermatology, The First Medical Center, Chinese PLA General Hospital, Beijing 100853, China
| | - Xingchen Liu
- Department of Pathology, Changhai Hospital, Navy Medical University, Shanghai 200433, China
| | - Rui Wang
- Department of Dermatology, The First Medical Center, Chinese PLA General Hospital, Beijing 100853, China
| | - Lang Chen
- Beijing Mygenostics Co, LTD., Beijing 101318, China
| | - Hua Zhao
- Department of Dermatology, The First Medical Center, Chinese PLA General Hospital, Beijing 100853, China
| | - Yong Zhou
- Department of Dermatology, The First Medical Center, Chinese PLA General Hospital, Beijing 100853, China
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Genetic load: genomic estimates and applications in non-model animals. Nat Rev Genet 2022; 23:492-503. [PMID: 35136196 DOI: 10.1038/s41576-022-00448-x] [Citation(s) in RCA: 60] [Impact Index Per Article: 30.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/10/2022] [Indexed: 12/11/2022]
Abstract
Genetic variation, which is generated by mutation, recombination and gene flow, can reduce the mean fitness of a population, both now and in the future. This 'genetic load' has been estimated in a wide range of animal taxa using various approaches. Advances in genome sequencing and computational techniques now enable us to estimate the genetic load in populations and individuals without direct fitness estimates. Here, we review the classic and contemporary literature of genetic load. We describe approaches to quantify the genetic load in whole-genome sequence data based on evolutionary conservation and annotations. We show that splitting the load into its two components - the realized load (or expressed load) and the masked load (or inbreeding load) - can improve our understanding of the population genetics of deleterious mutations.
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Chen J, Bataillon T, Glémin S, Lascoux M. What does the distribution of fitness effects of new mutations reflect? Insights from plants. THE NEW PHYTOLOGIST 2022; 233:1613-1619. [PMID: 34704271 DOI: 10.1111/nph.17826] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Accepted: 09/28/2021] [Indexed: 06/13/2023]
Abstract
The distribution of fitness effects (DFE) of new mutations plays a central role in molecular evolution. It is therefore crucial to be able to estimate it accurately from genomic data and to understand the factors that shape it. After a rapid overview of available methods to characterize the fitness effects of mutations, we review what is known on the factors affecting them in plants. Available data indicate that life history traits (e.g. mating system and longevity) have a major effect on the DFE. By contrast, the impact of demography within species appears to be more limited. These results remain to be confirmed, and methods to estimate the joint evolution of demography, life history traits, and the DFE need to be developed.
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Affiliation(s)
- Jun Chen
- College of Life Sciences, Zhejiang University, Hangzhou, Zhejiang, 310058, China
| | - Thomas Bataillon
- Bioinformatics Research Centre, Aarhus University, C.F. Möllers Allé 8, Aarhus C, DK-8000, Denmark
| | - Sylvain Glémin
- Centre National de la Recherche Scientifique (CNRS), ECOBIO (Ecosystèmes, Biodiversité, Evolution) - Unité Mixte de Recherche (UMR) 6553, Université de Rennes, Rennes, F-35000, France
- Program in Plant Ecology and Evolution, Department of Ecology and Genetics, Evolutionary Biology Centre, Uppsala University, Uppsala, 75236, Sweden
| | - Martin Lascoux
- Program in Plant Ecology and Evolution, Department of Ecology and Genetics, Evolutionary Biology Centre, Uppsala University, Uppsala, 75236, Sweden
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McGrath C. Highlight: Comparative Population Genomics—Answering Old Questions with New Data. Genome Biol Evol 2022. [PMCID: PMC8743037 DOI: 10.1093/gbe/evab278] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
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