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Ohadi M, Arabfard M, Khamse S, Alizadeh S, Vafadar S, Bayat H, Tajeddin N, Maddi AMA, Delbari A, Khorram Khorshid HR. Novel crossover and recombination hotspots massively spread across primate genomes. Biol Direct 2024; 19:70. [PMID: 39169390 PMCID: PMC11340189 DOI: 10.1186/s13062-024-00508-8] [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: 05/09/2024] [Accepted: 07/29/2024] [Indexed: 08/23/2024] Open
Abstract
BACKGROUND The recombination landscape and subsequent natural selection have vast consequences forevolution and speciation. However, most of the crossover and recombination hotspots are yet to be discovered. We previously reported the relevance of C and G trinucleotide two-repeat units (CG-TTUs) in crossovers and recombination. METHODS On a genome-wide scale, here we mapped all combinations of A and T trinucleotide two-repeat units (AT-TTUs) in human, consisting of AATAAT, ATAATA, ATTATT, TTATTA, TATTAT, and TAATAA. We also compared a number of the colonies formed by the AT-TTUs (distance between consecutive AT-TTUs < 500 bp) in several other primates and mouse. RESULTS We found that the majority of the AT-TTUs (> 96%) resided in approximately 1.4 million colonies, spread throughout the human genome. In comparison to the CG-TTU colonies, the AT-TTU colonies were significantly more abundant and larger in size. Pure units and overlapping units of the pure units were readily detectable in the same colonies, signifying that the units were the sites of unequal crossover. We discovered dynamic sharedness of several of the colonies across the primate species studied, which mainly reached maximum complexity and size in human. CONCLUSIONS We report novel crossover and recombination hotspots of the finest molecular resolution, massively spread and shared across the genomes of human and several other primates. With respect to crossovers and recombination, these genomes are far more dynamic than previously envisioned.
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Affiliation(s)
- Mina Ohadi
- Iranian Research Center on Aging, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran.
| | - Masoud Arabfard
- Chemical Injuries Research Center, Systems Biology and Poisonings Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran.
| | - Safoura Khamse
- Iranian Research Center on Aging, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran
| | - Samira Alizadeh
- Iranian Research Center on Aging, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran
| | - Sara Vafadar
- Iranian Research Center on Aging, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran
| | - Hadi Bayat
- Iranian Research Center on Aging, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran
- Biochemical Neuroendocrinology, Montreal Clinical and Research Institute (IRCM, affiliated to the McGill University, Montreal, QC, H2W 1R7, Canada
| | - Nahid Tajeddin
- Iranian Research Center on Aging, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran
- Department of Biology, Central Tehran Branch, Islamic Azad University, Tehran, Iran
| | - Ali M A Maddi
- Laboratory of Complex Biological Systems and Bioinformatics (CBB), Department of Bioinformatics, Institute of Biochemistry and Biophysics (IBB), University of Tehran, Tehran, Iran
| | - Ahmad Delbari
- Iranian Research Center on Aging, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran
| | - Hamid R Khorram Khorshid
- Personalized Medicine and Genometabolomics Research Center, Hope Generation Foundation, Tehran, Iran
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2
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Johnston SE. Understanding the Genetic Basis of Variation in Meiotic Recombination: Past, Present, and Future. Mol Biol Evol 2024; 41:msae112. [PMID: 38959451 PMCID: PMC11221659 DOI: 10.1093/molbev/msae112] [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: 04/17/2024] [Revised: 06/03/2024] [Accepted: 06/05/2024] [Indexed: 07/05/2024] Open
Abstract
Meiotic recombination is a fundamental feature of sexually reproducing species. It is often required for proper chromosome segregation and plays important role in adaptation and the maintenance of genetic diversity. The molecular mechanisms of recombination are remarkably conserved across eukaryotes, yet meiotic genes and proteins show substantial variation in their sequence and function, even between closely related species. Furthermore, the rate and distribution of recombination shows a huge diversity within and between chromosomes, individuals, sexes, populations, and species. This variation has implications for many molecular and evolutionary processes, yet how and why this diversity has evolved is not well understood. A key step in understanding trait evolution is to determine its genetic basis-that is, the number, effect sizes, and distribution of loci underpinning variation. In this perspective, I discuss past and current knowledge on the genetic basis of variation in recombination rate and distribution, explore its evolutionary implications, and present open questions for future research.
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Affiliation(s)
- Susan E Johnston
- Institute of Ecology and Evolution, School of Biological Sciences, University of Edinburgh, Edinburgh EH9 3FL, UK
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3
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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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4
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Vogl C, Karapetiants M, Yıldırım B, Kjartansdóttir H, Kosiol C, Bergman J, Majka M, Mikula LC. Inference of genomic landscapes using ordered Hidden Markov Models with emission densities (oHMMed). BMC Bioinformatics 2024; 25:151. [PMID: 38627634 PMCID: PMC11021005 DOI: 10.1186/s12859-024-05751-4] [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: 09/15/2023] [Accepted: 03/18/2024] [Indexed: 04/19/2024] Open
Abstract
BACKGROUND Genomes are inherently inhomogeneous, with features such as base composition, recombination, gene density, and gene expression varying along chromosomes. Evolutionary, biological, and biomedical analyses aim to quantify this variation, account for it during inference procedures, and ultimately determine the causal processes behind it. Since sequential observations along chromosomes are not independent, it is unsurprising that autocorrelation patterns have been observed e.g., in human base composition. In this article, we develop a class of Hidden Markov Models (HMMs) called oHMMed (ordered HMM with emission densities, the corresponding R package of the same name is available on CRAN): They identify the number of comparably homogeneous regions within autocorrelated observed sequences. These are modelled as discrete hidden states; the observed data points are realisations of continuous probability distributions with state-specific means that enable ordering of these distributions. The observed sequence is labelled according to the hidden states, permitting only neighbouring states that are also neighbours within the ordering of their associated distributions. The parameters that characterise these state-specific distributions are inferred. RESULTS We apply our oHMMed algorithms to the proportion of G and C bases (modelled as a mixture of normal distributions) and the number of genes (modelled as a mixture of poisson-gamma distributions) in windows along the human, mouse, and fruit fly genomes. This results in a partitioning of the genomes into regions by statistically distinguishable averages of these features, and in a characterisation of their continuous patterns of variation. In regard to the genomic G and C proportion, this latter result distinguishes oHMMed from segmentation algorithms based in isochore or compositional domain theory. We further use oHMMed to conduct a detailed analysis of variation of chromatin accessibility (ATAC-seq) and epigenetic markers H3K27ac and H3K27me3 (modelled as a mixture of poisson-gamma distributions) along the human chromosome 1 and their correlations. CONCLUSIONS Our algorithms provide a biologically assumption free approach to characterising genomic landscapes shaped by continuous, autocorrelated patterns of variation. Despite this, the resulting genome segmentation enables extraction of compositionally distinct regions for further downstream analyses.
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Affiliation(s)
- Claus Vogl
- Department of Biomedical Sciences and Pathobiology, Vetmeduni Vienna, Veterinärplatz 1, Vienna, Austria.
- Vienna Graduate School of Population Genetics, Vienna, Austria.
| | - Mariia Karapetiants
- Department of Biomedical Sciences and Pathobiology, Vetmeduni Vienna, Veterinärplatz 1, Vienna, Austria
| | - Burçin Yıldırım
- Department of Biomedical Sciences and Pathobiology, Vetmeduni Vienna, Veterinärplatz 1, Vienna, Austria
- Vienna Graduate School of Population Genetics, Vienna, Austria
- Department of Ecology and Genetics, Plant Ecology and Evolution, Uppsala University, Uppsala, Sweden
| | - Hrönn Kjartansdóttir
- Department of Biomedical Sciences and Pathobiology, Vetmeduni Vienna, Veterinärplatz 1, Vienna, Austria
| | - Carolin Kosiol
- Centre for Biological Diversity, School of Biology, University of St Andrews, St Andrews, Scotland, UK
| | - Juraj Bergman
- Department of Biology, Centre for Biodiversity Dynamics in a Changing World (BIOCHANGE) & Section for Ecoinformatics and Biodiversity, Aarhus University, Aarhus, Denmark
| | | | - Lynette Caitlin Mikula
- Centre for Biological Diversity, School of Biology, University of St Andrews, St Andrews, Scotland, UK.
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5
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Liu A, Wang N, Xie G, Li Y, Yan X, Li X, Zhu Z, Li Z, Yang J, Meng F, Dou M, Chen W, Ma N, Jiang Y, Gao Y, Wang Y. GC-biased gene conversion drives accelerated evolution of ultraconserved elements in mammalian and avian genomes. Genome Res 2023; 33:1673-1689. [PMID: 37884342 PMCID: PMC10691551 DOI: 10.1101/gr.277784.123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Accepted: 08/23/2023] [Indexed: 10/28/2023]
Abstract
Ultraconserved elements (UCEs) are the most conserved regions among the genomes of evolutionarily distant species and are thought to play critical biological functions. However, some UCEs rapidly evolved in specific lineages, and whether they contributed to adaptive evolution is still controversial. Here, using an increased number of sequenced genomes with high taxonomic coverage, we identified 2191 mammalian UCEs and 5938 avian UCEs from 95 mammal and 94 bird genomes, respectively. Our results show that these UCEs are functionally constrained and that their adjacent genes are prone to widespread expression with low expression diversity across tissues. Functional enrichment of mammalian and avian UCEs shows different trends indicating that UCEs may contribute to adaptive evolution of taxa. Focusing on lineage-specific accelerated evolution, we discover that the proportion of fast-evolving UCEs in nine mammalian and 10 avian test lineages range from 0.19% to 13.2%. Notably, up to 62.1% of fast-evolving UCEs in test lineages are much more likely to result from GC-biased gene conversion (gBGC). A single cervid-specific gBGC region embracing the uc.359 allele significantly alters the expression of Nova1 and other neural-related genes in the rat brain. Combined with the altered regulatory activity of ancient gBGC-induced fast-evolving UCEs in eutherians, our results provide evidence that synergy between gBGC and selection shaped lineage-specific substitution patterns, even in the most constrained regulatory elements. In summary, our results show that gBGC played an important role in facilitating lineage-specific accelerated evolution of UCEs, and further support the idea that a combination of multiple evolutionary forces shapes adaptive evolution.
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Affiliation(s)
- Anguo Liu
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
- Key Laboratory of Livestock Biology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Nini Wang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
- Faculty of Mathematics and Natural Sciences, University of Cologne, and Cologne Excellence Cluster for Cellular Stress Responses in Aging-Associated Diseases (CECAD), University Hospital Cologne, Cologne 50931, Germany
| | - Guoxiang Xie
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
- Key Laboratory of Livestock Biology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Yang Li
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
- Key Laboratory of Livestock Biology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Xixi Yan
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
- Key Laboratory of Livestock Biology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Xinmei Li
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
- Key Laboratory of Livestock Biology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Zhenliang Zhu
- Key Laboratory of Livestock Biology, Northwest A&F University, Yangling, Shaanxi 712100, China
- College of Veterinary Medicine, Northwest A&F University, Yangling, Shaanxi 712100, China
- Key Laboratory of Animal Biotechnology, Ministry of Agriculture, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Zhuohui Li
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
- Key Laboratory of Livestock Biology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Jing Yang
- Key Laboratory of Livestock Biology, Northwest A&F University, Yangling, Shaanxi 712100, China
- College of Veterinary Medicine, Northwest A&F University, Yangling, Shaanxi 712100, China
- Key Laboratory of Animal Biotechnology, Ministry of Agriculture, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Fanxin Meng
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Mingle Dou
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
- Key Laboratory of Livestock Biology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Weihuang Chen
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Nange Ma
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
- Key Laboratory of Livestock Biology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Yu Jiang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
- Key Laboratory of Livestock Biology, Northwest A&F University, Yangling, Shaanxi 712100, China
- Center for Functional Genomics, Institute of Future Agriculture, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Yuanpeng Gao
- Key Laboratory of Livestock Biology, Northwest A&F University, Yangling, Shaanxi 712100, China;
- College of Veterinary Medicine, Northwest A&F University, Yangling, Shaanxi 712100, China
- Key Laboratory of Animal Biotechnology, Ministry of Agriculture, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Yu Wang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China;
- Key Laboratory of Livestock Biology, Northwest A&F University, Yangling, Shaanxi 712100, China
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6
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Ragsdale AP, Thornton KR. Multiple Sources of Uncertainty Confound Inference of Historical Human Generation Times. Mol Biol Evol 2023; 40:msad160. [PMID: 37450583 PMCID: PMC10404577 DOI: 10.1093/molbev/msad160] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 07/05/2023] [Accepted: 07/07/2023] [Indexed: 07/18/2023] Open
Abstract
Wang et al. (2023) recently proposed an approach to infer the history of human generation intervals from changes in mutation profiles over time. As the relative proportions of different mutation types depend on the ages of parents, binning variants by the time they arose allows for the inference of changes in average paternal and maternal generation intervals. Applying this approach to published allele age estimates, Wang et al. (2023) inferred long-lasting sex differences in average generation times and surprisingly found that ancestral generation times of West African populations remained substantially higher than those of Eurasian populations extending tens of thousands of generations into the past. Here, we argue that the results and interpretations in Wang et al. (2023) are primarily driven by noise and biases in input data and a lack of validation using independent approaches for estimating allele ages. With the recent development of methods to reconstruct genome-wide gene genealogies, coalescence times, and allele ages, we caution that downstream analyses may be strongly influenced by uncharacterized biases in their output.
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Affiliation(s)
- Aaron P Ragsdale
- Department of Integrative Biology, University of Wisconsin-Madison, Madison, WI, USA
| | - Kevin R Thornton
- Department of Ecology and Evolutionary Biology, University of California, Irvine, CA, USA
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Liao K, Carlson J, Zöllner S. The effect of mutation subtypes on the allele frequency spectrum and population genetics inference. G3 (BETHESDA, MD.) 2023; 13:jkad035. [PMID: 36759699 PMCID: PMC10085755 DOI: 10.1093/g3journal/jkad035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Revised: 01/23/2023] [Accepted: 01/26/2023] [Indexed: 02/11/2023]
Abstract
Population genetics has adapted as technological advances in next-generation sequencing have resulted in an exponential increase of genetic data. A common approach to efficiently analyze genetic variation present in large sequencing data is through the allele frequency spectrum, defined as the distribution of allele frequencies in a sample. While the frequency spectrum serves to summarize patterns of genetic variation, it implicitly assumes mutation types (A→C vs C→T) as interchangeable. However, mutations of different types arise and spread due to spatial and temporal variation in forces such as mutation rate and biased gene conversion that result in heterogeneity in the distribution of allele frequencies across sites. In this work, we explore the impact of this simplification on multiple aspects of population genetic modeling. As a site's mutation rate is strongly affected by flanking nucleotides, we defined a mutation subtype by the base pair change and adjacent nucleotides (e.g. AAA→ATA) and systematically assessed the heterogeneity in the frequency spectrum across 96 distinct 3-mer mutation subtypes using n = 3556 whole-genome sequenced individuals of European ancestry. We observed substantial variation across the subtype-specific frequency spectra, with some of the variation being influenced by molecular factors previously identified for single base mutation types. Estimates of model parameters from demographic inference performed for each mutation subtype's AFS individually varied drastically across the 96 subtypes. In local patterns of variation, a combination of regional subtype composition and local genomic factors shaped the regional frequency spectrum across genomic regions. Our results illustrate how treating variants in large sequencing samples as interchangeable may confound population genetic frameworks and encourages us to consider the unique evolutionary mechanisms of analyzed polymorphisms.
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Affiliation(s)
- Kevin Liao
- Department of Biostatistics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Jedidiah Carlson
- Department of Integrative Biology, University of Texas at Austin, Austin, TX 78712, USA
- Department of Population Health, University of Texas at Austin, Austin, TX 78712, USA
| | - Sebastian Zöllner
- Department of Biostatistics, University of Michigan, Ann Arbor, MI 48109, USA
- Department of Psychiatry, University of Michigan, Ann Arbor, MI 48109, USA
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8
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Wang RJ, Al-Saffar SI, Rogers J, Hahn MW. Human generation times across the past 250,000 years. SCIENCE ADVANCES 2023; 9:eabm7047. [PMID: 36608127 PMCID: PMC9821931 DOI: 10.1126/sciadv.abm7047] [Citation(s) in RCA: 29] [Impact Index Per Article: 29.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
The generation times of our recent ancestors can tell us about both the biology and social organization of prehistoric humans, placing human evolution on an absolute time scale. We present a method for predicting historical male and female generation times based on changes in the mutation spectrum. Our analyses of whole-genome data reveal an average generation time of 26.9 years across the past 250,000 years, with fathers consistently older (30.7 years) than mothers (23.2 years). Shifts in sex-averaged generation times have been driven primarily by changes to the age of paternity, although we report a substantial increase in female generation times in the recent past. We also find a large difference in generation times among populations, reaching back to a time when all humans occupied Africa.
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Affiliation(s)
- Richard J. Wang
- Department of Biology, Indiana University, Bloomington, IN 47405, USA
- Department of Computer Science, Indiana University, Bloomington, IN 47405, USA
- Corresponding author.
| | - Samer I. Al-Saffar
- Department of Computer Science, Indiana University, Bloomington, IN 47405, USA
| | - Jeffrey Rogers
- Human Genome Sequencing Center and Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Matthew W. Hahn
- Department of Biology, Indiana University, Bloomington, IN 47405, USA
- Department of Computer Science, Indiana University, Bloomington, IN 47405, USA
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9
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Bergman J, Schierup MH. Evolutionary dynamics of pseudoautosomal region 1 in humans and great apes. Genome Biol 2022; 23:215. [PMID: 36253794 PMCID: PMC9575207 DOI: 10.1186/s13059-022-02784-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Accepted: 09/30/2022] [Indexed: 12/03/2022] Open
Abstract
BACKGROUND The pseudoautosomal region 1 (PAR1) is a 2.7 Mb telomeric region of human sex chromosomes. PAR1 has a crucial role in ensuring proper segregation of sex chromosomes during male meiosis, exposing it to extreme recombination and mutation processes. We investigate PAR1 evolution using population genomic datasets of extant humans, eight populations of great apes, and two archaic human genome sequences. RESULTS We find that PAR1 is fast evolving and closer to evolutionary nucleotide equilibrium than autosomal telomeres. We detect a difference between substitution patterns and extant diversity in PAR1, mainly driven by the conflict between strong mutation and recombination-associated fixation bias at CpG sites. We detect excess C-to-G mutations in PAR1 of all great apes, specific to the mutagenic effect of male recombination. Despite recent evidence for Y chromosome introgression from humans into Neanderthals, we find that the Neanderthal PAR1 retained similarity to the Denisovan sequence. We find differences between substitution spectra of these archaics suggesting rapid evolution of PAR1 in recent hominin history. Frequency analysis of alleles segregating in females and males provided no evidence for recent sexual antagonism in this region. We study repeat content and double-strand break hotspot regions in PAR1 and find that they may play roles in ensuring the obligate X-Y recombination event during male meiosis. CONCLUSIONS Our study provides an unprecedented quantification of population genetic forces governing PAR1 biology across extant and extinct hominids. PAR1 evolutionary dynamics are predominantly governed by recombination processes with a strong impact on mutation patterns across all species.
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Affiliation(s)
- Juraj Bergman
- Bioinformatics Research Centre, Aarhus University, DK-8000 Aarhus C, Denmark
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10
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Lee B, Cyrill SL, Lee W, Melchiotti R, Andiappan AK, Poidinger M, Rötzschke O. Analysis of archaic human haplotypes suggests that 5hmC acts as an epigenetic guide for NCO recombination. BMC Biol 2022; 20:173. [PMID: 35927700 PMCID: PMC9354366 DOI: 10.1186/s12915-022-01353-9] [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] [Received: 04/01/2021] [Accepted: 06/17/2022] [Indexed: 11/17/2022] Open
Abstract
Background Non-crossover (NCO) refers to a mechanism of homologous recombination in which short tracks of DNA are copied between homologue chromatids. The allelic changes are typically restricted to one or few SNPs, which potentially allow for the gradual adaptation and maturation of haplotypes. It is assumed to be a stochastic process but the analysis of archaic and modern human haplotypes revealed a striking variability in local NCO recombination rates. Methods NCO recombination rates of 1.9 million archaic SNPs shared with Denisovan hominids were defined by a linkage study and correlated with functional and genomic annotations as well as ChIP-Seq data from modern humans. Results We detected a strong correlation between NCO recombination rates and the function of the respective region: low NCO rates were evident in introns and quiescent intergenic regions but high rates in splice sites, exons, 5′- and 3′-UTRs, as well as CpG islands. Correlations with ChIP-Seq data from ENCODE and other public sources further identified epigenetic modifications that associated directly with these recombination events. A particularly strong association was observed for 5-hydroxymethylcytosine marks (5hmC), which were enriched in virtually all of the functional regions associated with elevated NCO rates, including CpG islands and ‘poised’ bivalent regions. Conclusion Our results suggest that 5hmC marks may guide the NCO machinery specifically towards functionally relevant regions and, as an intermediate of oxidative demethylation, may open a pathway for environmental influence by specifically targeting recently opened gene loci. Supplementary Information The online version contains supplementary material available at 10.1186/s12915-022-01353-9.
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Affiliation(s)
- Bernett Lee
- Singapore Immunology Network (SIgN), Agency of Science Technology and Research (A*STAR), 8A Biomedical Drive, Singapore, 138648, Singapore.,Present address: Lee Kong Chian School of Medicine, Nanyang Technological University, 50 Nanyang Avenue, Singapore, 639798, Singapore
| | - Samantha Leeanne Cyrill
- Singapore Immunology Network (SIgN), Agency of Science Technology and Research (A*STAR), 8A Biomedical Drive, Singapore, 138648, Singapore.,Present address: Cold Spring Harbor Laboratory, One Bungtown Road, NY, 11724, Cold Spring Harbor, USA
| | - Wendy Lee
- Singapore Immunology Network (SIgN), Agency of Science Technology and Research (A*STAR), 8A Biomedical Drive, Singapore, 138648, Singapore
| | - Rossella Melchiotti
- Singapore Immunology Network (SIgN), Agency of Science Technology and Research (A*STAR), 8A Biomedical Drive, Singapore, 138648, Singapore
| | - Anand Kumar Andiappan
- Singapore Immunology Network (SIgN), Agency of Science Technology and Research (A*STAR), 8A Biomedical Drive, Singapore, 138648, Singapore
| | - Michael Poidinger
- Singapore Immunology Network (SIgN), Agency of Science Technology and Research (A*STAR), 8A Biomedical Drive, Singapore, 138648, Singapore.,Present address: Murdoch Children's Research Institute, Royal Children's Hospital, Flemington Road, Parkville, Victoria, 3052, Australia
| | - Olaf Rötzschke
- Singapore Immunology Network (SIgN), Agency of Science Technology and Research (A*STAR), 8A Biomedical Drive, Singapore, 138648, Singapore.
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11
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Ho AT, Hurst LD. Unusual mammalian usage of TGA stop codons reveals that sequence conservation need not imply purifying selection. PLoS Biol 2022; 20:e3001588. [PMID: 35550630 PMCID: PMC9129041 DOI: 10.1371/journal.pbio.3001588] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2022] [Revised: 05/24/2022] [Accepted: 04/20/2022] [Indexed: 11/18/2022] Open
Abstract
The assumption that conservation of sequence implies the action of purifying selection is central to diverse methodologies to infer functional importance. GC-biased gene conversion (gBGC), a meiotic mismatch repair bias strongly favouring GC over AT, can in principle mimic the action of selection, this being thought to be especially important in mammals. As mutation is GC→AT biased, to demonstrate that gBGC does indeed cause false signals requires evidence that an AT-rich residue is selectively optimal compared to its more GC-rich allele, while showing also that the GC-rich alternative is conserved. We propose that mammalian stop codon evolution provides a robust test case. Although in most taxa TAA is the optimal stop codon, TGA is both abundant and conserved in mammalian genomes. We show that this mammalian exceptionalism is well explained by gBGC mimicking purifying selection and that TAA is the selectively optimal codon. Supportive of gBGC, we observe (i) TGA usage trends are consistent at the focal stop codon and elsewhere (in UTR sequences); (ii) that higher TGA usage and higher TAA→TGA substitution rates are predicted by a high recombination rate; and (iii) across species the difference in TAA <-> TGA substitution rates between GC-rich and GC-poor genes is largest in genomes that possess higher between-gene GC variation. TAA optimality is supported both by enrichment in highly expressed genes and trends associated with effective population size. High TGA usage and high TAA→TGA rates in mammals are thus consistent with gBGC’s predicted ability to “drive” deleterious mutations and supports the hypothesis that sequence conservation need not be indicative of purifying selection. A general trend for GC-rich trinucleotides to reside at frequencies far above their mutational equilibrium in high recombining domains supports the generality of these results.
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Affiliation(s)
- Alexander Thomas Ho
- Milner Centre for Evolution, University of Bath, Bath, United Kingdom
- * E-mail:
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12
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Soni V, Eyre-Walker A. OUP accepted manuscript. Genome Biol Evol 2022; 14:6528851. [PMID: 35166775 PMCID: PMC8882387 DOI: 10.1093/gbe/evac028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/09/2022] [Indexed: 12/05/2022] Open
Abstract
The rate of amino acid substitution has been shown to be correlated to a number of factors including the rate of recombination, the age of the gene, the length of the protein, mean expression level, and gene function. However, the extent to which these correlations are due to adaptive and nonadaptive evolution has not been studied in detail, at least not in hominids. We find that the rate of adaptive evolution is significantly positively correlated to the rate of recombination, protein length and gene expression level, and negatively correlated to gene age. These correlations remain significant when each factor is controlled for in turn, except when controlling for expression in an analysis of protein length; and they also generally remain significant when biased gene conversion is taken into account. However, the positive correlations could be an artifact of population size contraction. We also find that the rate of nonadaptive evolution is negatively correlated to each factor, and all these correlations survive controlling for each other and biased gene conversion. Finally, we examine the effect of gene function on rates of adaptive and nonadaptive evolution; we confirm that virus-interacting proteins (VIPs) have higher rates of adaptive and lower rates of nonadaptive evolution, but we also demonstrate that there is significant variation in the rate of adaptive and nonadaptive evolution between GO categories when removing VIPs. We estimate that the VIP/non-VIP axis explains about 5–8 fold more of the variance in evolutionary rate than GO categories.
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Affiliation(s)
- Vivak Soni
- School of Life Sciences, University of Sussex, Brighton, United Kingdom
| | - Adam Eyre-Walker
- School of Life Sciences, University of Sussex, Brighton, United Kingdom
- Corresponding author: E-mail:
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13
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Bergman J, Schierup MH. Population dynamics of GC-changing mutations in humans and great apes. Genetics 2021; 218:6291657. [PMID: 34081117 DOI: 10.1093/genetics/iyab083] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2021] [Accepted: 05/27/2021] [Indexed: 11/14/2022] Open
Abstract
The nucleotide composition of the genome is a balance between origin and fixation rates of different mutations. For example, it is well-known that transitions occur more frequently than transversions, particularly at CpG sites. Differences in fixation rates of mutation types are less explored. Specifically, recombination-associated GC-biased gene conversion (gBGC) may differentially impact GC-changing mutations, due to differences in their genomic distributions and efficiency of mismatch repair mechanisms. Given that recombination evolves rapidly across species, we explore gBGC of different mutation types across human populations and great ape species. We report a stronger correlation between segregating GC frequency and recombination for transitions than for transversions. Notably, CpG transitions are most strongly affected by gBGC in humans and chimpanzees. We show that the overall strength of gBGC is generally correlated with effective population sizes in humans, with some notable exceptions, such as a stronger effect of gBGC on non-CpG transitions in populations of European descent. Furthermore, species of the Gorilla and Pongo genus have a greatly reduced gBGC effect on CpG sites. We also study the dependence of gBGC dynamics on flanking nucleotides and show that some mutation types evolve in opposition to the gBGC expectation, likely due to hypermutability of specific nucleotide contexts. Our results highlight the importance of different gBGC dynamics experienced by GC-changing mutations and their impact on nucleotide composition evolution.
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Affiliation(s)
- Juraj Bergman
- Bioinformatics Research Institute, Aarhus University, DK-8000 Aarhus C, Denmark
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14
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Zhen Y, Huber CD, Davies RW, Lohmueller KE. Greater strength of selection and higher proportion of beneficial amino acid changing mutations in humans compared with mice and Drosophila melanogaster. Genome Res 2020; 31:110-120. [PMID: 33208456 PMCID: PMC7849390 DOI: 10.1101/gr.256636.119] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2019] [Accepted: 11/10/2020] [Indexed: 12/19/2022]
Abstract
Quantifying and comparing the amount of adaptive evolution among different species is key to understanding how evolution works. Previous studies have shown differences in adaptive evolution across species; however, their specific causes remain elusive. Here, we use improved modeling of weakly deleterious mutations and the demographic history of the outgroup species and ancestral population and estimate that at least 20% of nonsynonymous substitutions between humans and an outgroup species were fixed by positive selection. This estimate is much higher than previous estimates, which did not correct for the sizes of the outgroup species and ancestral population. Next, we jointly estimate the proportion and selection coefficient (p+ and s+, respectively) of newly arising beneficial nonsynonymous mutations in humans, mice, and Drosophila melanogaster by examining patterns of polymorphism and divergence. We develop a novel composite likelihood framework to test whether these parameters differ across species. Overall, we reject a model with the same p+ and s+ of beneficial mutations across species and estimate that humans have a higher p+s+ compared with that of D. melanogaster and mice. We show that this result cannot be caused by biased gene conversion or hypermutable CpG sites. We discuss possible biological explanations that could generate the observed differences in the amount of adaptive evolution across species.
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Affiliation(s)
- Ying Zhen
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, California 90095, USA.,Zhejiang Provincial Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang, 310024, China.,Institute of Biology, Westlake Institute for Advanced Study, Hangzhou, Zhejiang, 310024, China
| | - Christian D Huber
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, California 90095, USA.,School of Biological Sciences, The University of Adelaide, Adelaide, South Australia 5005, Australia
| | - Robert W Davies
- Program in Genetics and Genome Biology and The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, Ontario, M5G 0A4, Canada.,Department of Statistics, University of Oxford, Oxford, OX1 3LB, United Kingdom
| | - Kirk E Lohmueller
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, California 90095, USA.,Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, California 90095, USA
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15
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Abstract
Mutation of the human genome results in three classes of genomic variation: single nucleotide variants; short insertions or deletions; and large structural variants (SVs). Some mutations occur during normal processes, such as meiotic recombination or B cell development, and others result from DNA replication or aberrant repair of breaks in sequence-specific contexts. Regardless of mechanism, mutations are subject to selection, and some hotspots can manifest in disease. Here, we discuss genomic regions prone to mutation, mechanisms contributing to mutation susceptibility, and the processes leading to their accumulation in normal and somatic genomes. With further, more accurate human genome sequencing, additional mutation hotspots, mechanistic details of their formation, and the relevance of hotspots to evolution and disease are likely to be discovered.
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16
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Hämälä T, Tiffin P. Biased Gene Conversion Constrains Adaptation in Arabidopsis thaliana. Genetics 2020; 215:831-846. [PMID: 32414868 PMCID: PMC7337087 DOI: 10.1534/genetics.120.303335] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2020] [Accepted: 05/14/2020] [Indexed: 02/01/2023] Open
Abstract
Reduction of fitness due to deleterious mutations imposes a limit to adaptive evolution. By characterizing features that influence this genetic load we may better understand constraints on responses to both natural and human-mediated selection. Here, using whole-genome, transcriptome, and methylome data from >600 Arabidopsis thaliana individuals, we set out to identify important features influencing selective constraint. Our analyses reveal that multiple factors underlie the accumulation of maladaptive mutations, including gene expression level, gene network connectivity, and gene-body methylation. We then focus on a feature with major effect, nucleotide composition. The ancestral vs. derived status of segregating alleles suggests that GC-biased gene conversion, a recombination-associated process that increases the frequency of G and C nucleotides regardless of their fitness effects, shapes sequence patterns in A. thaliana Through estimation of mutational effects, we present evidence that biased gene conversion hinders the purging of deleterious mutations and contributes to a genome-wide signal of decreased efficacy of selection. By comparing these results to two outcrossing relatives, Arabidopsis lyrata and Capsella grandiflora, we find that protein evolution in A. thaliana is as strongly affected by biased gene conversion as in the outcrossing species. Last, we perform simulations to show that natural levels of outcrossing in A. thaliana are sufficient to facilitate biased gene conversion despite increased homozygosity due to selfing. Together, our results show that even predominantly selfing taxa are susceptible to biased gene conversion, suggesting that it may constitute an important constraint to adaptation among plant species.
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Affiliation(s)
- Tuomas Hämälä
- Department of Plant and Microbial Biology, University of Minnesota, St. Paul, Minnesota 55108
| | - Peter Tiffin
- Department of Plant and Microbial Biology, University of Minnesota, St. Paul, Minnesota 55108
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17
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Subramanian S. Population size influences the type of nucleotide variations in humans. BMC Genet 2019; 20:93. [PMID: 31805852 PMCID: PMC6894472 DOI: 10.1186/s12863-019-0798-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2019] [Accepted: 12/01/2019] [Indexed: 11/24/2022] Open
Abstract
Background It is well known that the effective size of a population (Ne) is one of the major determinants of the amount of genetic variation within the population. However, it is unclear whether the types of genetic variations are also dictated by the effective population size. To examine this, we obtained whole genome data from over 100 populations of the world and investigated the patterns of mutational changes. Results Our results revealed that for low frequency variants, the ratio of AT→GC to GC→AT variants (β) was similar across populations, suggesting the similarity of the pattern of mutation in various populations. However, for high frequency variants, β showed a positive correlation with the effective population size of the populations. This suggests a much higher proportion of high frequency AT→GC variants in large populations (e.g. Africans) compared to those with small population sizes (e.g. Asians). These results imply that the substitution patterns vary significantly between populations. These findings could be explained by the effect of GC-biased gene conversion (gBGC), which favors the fixation of G/C over A/T variants in populations. In large population, gBGC causes high β. However, in small populations, genetic drift reduces the effect of gBGC resulting in reduced β. This was further confirmed by a positive relationship between Ne and β for homozygous variants. Conclusions Our results highlight the huge variation in the types of homozygous and high frequency polymorphisms between world populations. We observed the same pattern for deleterious variants, implying that the homozygous polymorphisms associated with recessive genetic diseases will be more enriched with G or C in populations with large Ne (e.g. Africans) than in populations with small Ne (e.g. Europeans).
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Affiliation(s)
- Sankar Subramanian
- GeneCology Research Centre, University of the Sunshine Coast, 90 Sippy Downs Drive, Sippy Downs, QLD 4556, Australia.
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18
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Borges R, Szöllősi GJ, Kosiol C. Quantifying GC-Biased Gene Conversion in Great Ape Genomes Using Polymorphism-Aware Models. Genetics 2019; 212:1321-1336. [PMID: 31147380 PMCID: PMC6707462 DOI: 10.1534/genetics.119.302074] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2018] [Accepted: 05/20/2019] [Indexed: 11/18/2022] Open
Abstract
As multi-individual population-scale data become available, more complex modeling strategies are needed to quantify genome-wide patterns of nucleotide usage and associated mechanisms of evolution. Recently, the multivariate neutral Moran model was proposed. However, it was shown insufficient to explain the distribution of alleles in great apes. Here, we propose a new model that includes allelic selection. Our theoretical results constitute the basis of a new Bayesian framework to estimate mutation rates and selection coefficients from population data. We apply the new framework to a great ape dataset, where we found patterns of allelic selection that match those of genome-wide GC-biased gene conversion (gBGC). In particular, we show that great apes have patterns of allelic selection that vary in intensity-a feature that we correlated with great apes' distinct demographies. We also demonstrate that the AT/GC toggling effect decreases the probability of a substitution, promoting more polymorphisms in the base composition of great ape genomes. We further assess the impact of GC-bias in molecular analysis, and find that mutation rates and genetic distances are estimated under bias when gBGC is not properly accounted for. Our results contribute to the discussion on the tempo and mode of gBGC evolution, while stressing the need for gBGC-aware models in population genetics and phylogenetics.
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Affiliation(s)
- Rui Borges
- Institut für Populationsgenetik, Vetmeduni Vienna, 1210 Wien, Wien, Austria
| | - Gergely J Szöllősi
- Department of Biological Physics, MTA-ELTE "Lendulet" Evolutionary Genomics Research Group, Eötvös University, Pázmány P. stny. 1A, Budapest 1117, Hungary
| | - Carolin Kosiol
- Institut für Populationsgenetik, Vetmeduni Vienna, 1210 Wien, Wien, Austria
- Centre for Biological Diversity, School of Biology, University of St Andrews, Fife KY16 9TH, UK
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19
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Galtier N, Roux C, Rousselle M, Romiguier J, Figuet E, Glémin S, Bierne N, Duret L. Codon Usage Bias in Animals: Disentangling the Effects of Natural Selection, Effective Population Size, and GC-Biased Gene Conversion. Mol Biol Evol 2019; 35:1092-1103. [PMID: 29390090 DOI: 10.1093/molbev/msy015] [Citation(s) in RCA: 83] [Impact Index Per Article: 16.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Selection on codon usage bias is well documented in a number of microorganisms. Whether codon usage is also generally shaped by natural selection in large organisms, despite their relatively small effective population size (Ne), is unclear. In animals, the population genetics of codon usage bias has only been studied in a handful of model organisms so far, and can be affected by confounding, nonadaptive processes such as GC-biased gene conversion and experimental artefacts. Using population transcriptomics data, we analyzed the relationship between codon usage, gene expression, allele frequency distribution, and recombination rate in 30 nonmodel species of animals, each from a different family, covering a wide range of effective population sizes. We disentangled the effects of translational selection and GC-biased gene conversion on codon usage by separately analyzing GC-conservative and GC-changing mutations. We report evidence for effective translational selection on codon usage in large-Ne species of animals, but not in small-Ne ones, in agreement with the nearly neutral theory of molecular evolution. C- and T-ending codons tend to be preferred over synonymous G- and A-ending ones, for reasons that remain to be determined. In contrast, we uncovered a conspicuous effect of GC-biased gene conversion, which is widespread in animals and the main force determining the fate of AT↔GC mutations. Intriguingly, the strength of its effect was uncorrelated with Ne.
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Affiliation(s)
- Nicolas Galtier
- UMR5554, Institut des Sciences de l'Evolution, University Montpellier, CNRS, IRD, EPHE, Montpellier, France
| | - Camille Roux
- UMR5554, Institut des Sciences de l'Evolution, University Montpellier, CNRS, IRD, EPHE, Montpellier, France.,Department of Ecology and Evolution, University of Lausanne, Lausanne, Switzerland.,UMR 8198 - Evo-Eco-Paleo, CNRS, Université de Lille-Sciences et Technologies, Villeneuve d'Ascq, France
| | - Marjolaine Rousselle
- UMR5554, Institut des Sciences de l'Evolution, University Montpellier, CNRS, IRD, EPHE, Montpellier, France
| | - Jonathan Romiguier
- UMR5554, Institut des Sciences de l'Evolution, University Montpellier, CNRS, IRD, EPHE, Montpellier, France.,Department of Ecology and Evolution, University of Lausanne, Lausanne, Switzerland
| | - Emeric Figuet
- UMR5554, Institut des Sciences de l'Evolution, University Montpellier, CNRS, IRD, EPHE, Montpellier, France
| | - Sylvain Glémin
- UMR5554, Institut des Sciences de l'Evolution, University Montpellier, CNRS, IRD, EPHE, Montpellier, France.,Department of Ecology and Genetics, Evolutionary Biology Centre, Uppsala University, Uppsala, Sweden
| | - Nicolas Bierne
- UMR5554, Institut des Sciences de l'Evolution, University Montpellier, CNRS, IRD, EPHE, Montpellier, France
| | - Laurent Duret
- Laboratoire de Biométrie et Biologie Evolutive, UMR 5558, CNRS, Université de Lyon, Université Lyon 1, Villeurbanne, France
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20
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Rousselle M, Laverré A, Figuet E, Nabholz B, Galtier N. Influence of Recombination and GC-biased Gene Conversion on the Adaptive and Nonadaptive Substitution Rate in Mammals versus Birds. Mol Biol Evol 2019; 36:458-471. [PMID: 30590692 PMCID: PMC6389324 DOI: 10.1093/molbev/msy243] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
Recombination is expected to affect functional sequence evolution in several ways. On the one hand, recombination is thought to improve the efficiency of multilocus selection by dissipating linkage disequilibrium. On the other hand, natural selection can be counteracted by recombination-associated transmission distorters such as GC-biased gene conversion (gBGC), which tends to promote G and C alleles irrespective of their fitness effect in high-recombining regions. It has been suggested that gBGC might impact coding sequence evolution in vertebrates, and particularly the ratio of nonsynonymous to synonymous substitution rates (dN/dS). However, distinctive gBGC patterns have been reported in mammals and birds, maybe reflecting the documented contrasts in evolutionary dynamics of recombination rate between these two taxa. Here, we explore how recombination and gBGC affect coding sequence evolution in mammals and birds by analyzing proteome-wide data in six species of Galloanserae (fowls) and six species of catarrhine primates. We estimated the dN/dS ratio and rates of adaptive and nonadaptive evolution in bins of genes of increasing recombination rate, separately analyzing AT → GC, GC → AT, and G ↔ C/A ↔ T mutations. We show that in both taxa, recombination and gBGC entail a decrease in dN/dS. Our analysis indicates that recombination enhances the efficiency of purifying selection by lowering Hill-Robertson effects, whereas gBGC leads to an overestimation of the adaptive rate of AT → GC mutations. Finally, we report a mutagenic effect of recombination, which is independent of gBGC.
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Affiliation(s)
| | - Alexandre Laverré
- ISEM, Université de Montpellier, CNRS, IRD, EPHE, Montpellier, France
| | - Emeric Figuet
- ISEM, Université de Montpellier, CNRS, IRD, EPHE, Montpellier, France
| | - Benoit Nabholz
- ISEM, Université de Montpellier, CNRS, IRD, EPHE, Montpellier, France
| | - Nicolas Galtier
- ISEM, Université de Montpellier, CNRS, IRD, EPHE, Montpellier, France
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21
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Pouyet F, Aeschbacher S, Thiéry A, Excoffier L. Background selection and biased gene conversion affect more than 95% of the human genome and bias demographic inferences. eLife 2018; 7:e36317. [PMID: 30125248 PMCID: PMC6177262 DOI: 10.7554/elife.36317] [Citation(s) in RCA: 83] [Impact Index Per Article: 13.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2018] [Accepted: 08/17/2018] [Indexed: 12/15/2022] Open
Abstract
Disentangling the effect on genomic diversity of natural selection from that of demography is notoriously difficult, but necessary to properly reconstruct the history of species. Here, we use high-quality human genomic data to show that purifying selection at linked sites (i.e. background selection, BGS) and GC-biased gene conversion (gBGC) together affect as much as 95% of the variants of our genome. We find that the magnitude and relative importance of BGS and gBGC are largely determined by variation in recombination rate and base composition. Importantly, synonymous sites and non-transcribed regions are also affected, albeit to different degrees. Their use for demographic inference can lead to strong biases. However, by conditioning on genomic regions with recombination rates above 1.5 cM/Mb and mutation types (C↔G, A↔T), we identify a set of SNPs that is mostly unaffected by BGS or gBGC, and that avoids these biases in the reconstruction of human history.
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Affiliation(s)
- Fanny Pouyet
- Computational and Molecular Population Genetics, Institute of Ecology and EvolutionUniversity of BernBernSwitzerland
- Swiss Institute of BioinformaticsLausanneSwitzerland
| | - Simon Aeschbacher
- Computational and Molecular Population Genetics, Institute of Ecology and EvolutionUniversity of BernBernSwitzerland
- Swiss Institute of BioinformaticsLausanneSwitzerland
- Department of Evolutionary Biology and Environmental StudiesUniversity of ZurichZurichSwitzerland
| | - Alexandre Thiéry
- Computational and Molecular Population Genetics, Institute of Ecology and EvolutionUniversity of BernBernSwitzerland
- Swiss Institute of BioinformaticsLausanneSwitzerland
| | - Laurent Excoffier
- Computational and Molecular Population Genetics, Institute of Ecology and EvolutionUniversity of BernBernSwitzerland
- Swiss Institute of BioinformaticsLausanneSwitzerland
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22
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Patel R, Scheinfeldt LB, Sanderford MD, Lanham TR, Tamura K, Platt A, Glicksberg BS, Xu K, Dudley JT, Kumar S. Adaptive Landscape of Protein Variation in Human Exomes. Mol Biol Evol 2018; 35:2015-2025. [PMID: 29846678 PMCID: PMC6063297 DOI: 10.1093/molbev/msy107] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
The human genome contains hundreds of thousands of missense mutations. However, only a handful of these variants are known to be adaptive, which implies that adaptation through protein sequence change is an extremely rare phenomenon in human evolution. Alternatively, existing methods may lack the power to pinpoint adaptive variation. We have developed and applied an Evolutionary Probability Approach (EPA) to discover candidate adaptive polymorphisms (CAPs) through the discordance between allelic evolutionary probabilities and their observed frequencies in human populations. EPA reveals thousands of missense CAPs, which suggest that a large number of previously optimal alleles experienced a reversal of fortune in the human lineage. We explored nonadaptive mechanisms to explain CAPs, including the effects of demography, mutation rate variability, and negative and positive selective pressures in modern humans. Many nonadaptive hypotheses were tested, but failed to explain the data, which suggests that a large proportion of CAP alleles have increased in frequency due to beneficial selection. This suggestion is supported by the fact that a vast majority of adaptive missense variants discovered previously in humans are CAPs, and hundreds of CAP alleles are protective in genotype-phenotype association data. Our integrated phylogenomic and population genetic EPA approach predicts the existence of thousands of nonneutral candidate variants in the human proteome. We expect this collection to be enriched in beneficial variation. The EPA approach can be applied to discover candidate adaptive variation in any protein, population, or species for which allele frequency data and reliable multispecies alignments are available.
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Affiliation(s)
- Ravi Patel
- Institute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, PA
- Department of Biology, Temple University, Philadelphia, PA
| | - Laura B Scheinfeldt
- Institute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, PA
- Department of Biology, Temple University, Philadelphia, PA
- Coriell Institute for Medical Research, Camden, NJ
| | - Maxwell D Sanderford
- Institute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, PA
| | - Tamera R Lanham
- Institute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, PA
| | - Koichiro Tamura
- Department of Biology, Tokyo Metropolitan University, Tokyo, Japan
| | - Alexander Platt
- Institute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, PA
- Department of Biology, Temple University, Philadelphia, PA
- Center for Computational Genetics and Genomics, Temple University, Philadelphia, PA
| | - Benjamin S Glicksberg
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Ke Xu
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Joel T Dudley
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Sudhir Kumar
- Institute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, PA
- Department of Biology, Temple University, Philadelphia, PA
- Center for Excellence in Genome Medicine and Research, King Abdulaziz University, Jeddah, Saudi Arabia
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23
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Wang GD, Zhang BL, Zhou WW, Li YX, Jin JQ, Shao Y, Yang HC, Liu YH, Yan F, Chen HM, Jin L, Gao F, Zhang Y, Li H, Mao B, Murphy RW, Wake DB, Zhang YP, Che J. Selection and environmental adaptation along a path to speciation in the Tibetan frog Nanorana parkeri. Proc Natl Acad Sci U S A 2018; 115:E5056-E5065. [PMID: 29760079 PMCID: PMC5984489 DOI: 10.1073/pnas.1716257115] [Citation(s) in RCA: 47] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
Tibetan frogs, Nanorana parkeri, are differentiated genetically but not morphologically along geographical and elevational gradients in a challenging environment, presenting a unique opportunity to investigate processes leading to speciation. Analyses of whole genomes of 63 frogs reveal population structuring and historical demography, characterized by highly restricted gene flow in a narrow geographic zone lying between matrilines West (W) and East (E). A population found only along a single tributary of the Yalu Zangbu River has the mitogenome only of E, whereas nuclear genes of W comprise 89-95% of the nuclear genome. Selection accounts for 579 broadly scattered, highly divergent regions (HDRs) of the genome, which involve 365 genes. These genes fall into 51 gene ontology (GO) functional classes, 14 of which are likely to be important in driving reproductive isolation. GO enrichment analyses of E reveal many overrepresented functional categories associated with adaptation to high elevations, including blood circulation, response to hypoxia, and UV radiation. Four genes, including DNAJC8 in the brain, TNNC1 and ADORA1 in the heart, and LAMB3 in the lung, differ in levels of expression between low- and high-elevation populations. High-altitude adaptation plays an important role in maintaining and driving continuing divergence and reproductive isolation. Use of total genomes enabled recognition of selection and adaptation in and between populations, as well as documentation of evolution along a stepped cline toward speciation.
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Affiliation(s)
- Guo-Dong Wang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming 650223, China
| | - Bao-Lin Zhang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming 650204, Yunnan, China
| | - Wei-Wei Zhou
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
- Southeast Asia Biodiversity Research Institute, Chinese Academy of Sciences, Yezin, 05282 Nay Pyi Taw, Myanmar
| | - Yong-Xin Li
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming 650204, Yunnan, China
| | - Jie-Qiong Jin
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
| | - Yong Shao
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
| | - He-Chuan Yang
- Human Genetics, Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore 138672, Singapore
| | - Yan-Hu Liu
- Laboratory for Conservation and Utilization of Bio-Resources & Key Laboratory for Microbial Resources of the Ministry of Education, Yunnan University, Kunming 650091, China
| | - Fang Yan
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
| | - Hong-Man Chen
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
| | - Li Jin
- Key Laboratory of Freshwater Fish Reproduction and Development of the Ministry of Education and Key Laboratory of Aquatic Science of Chongqing, Southwest University School of Life Sciences, Chongqing 400715, China
| | - Feng Gao
- CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Yaoguang Zhang
- Key Laboratory of Freshwater Fish Reproduction and Development of the Ministry of Education and Key Laboratory of Aquatic Science of Chongqing, Southwest University School of Life Sciences, Chongqing 400715, China
| | - Haipeng Li
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming 650223, China
- CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Bingyu Mao
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming 650223, China
| | - Robert W Murphy
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
- Centre for Biodiversity and Conservation Biology, Royal Ontario Museum, Toronto, ON, Canada M5S 2C6
| | - David B Wake
- Department of Integrative Biology and Museum of Vertebrate Zoology, University of California, Berkeley, CA 94720-3160
| | - Ya-Ping Zhang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China;
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming 650223, China
| | - Jing Che
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China;
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming 650223, China
- Southeast Asia Biodiversity Research Institute, Chinese Academy of Sciences, Yezin, 05282 Nay Pyi Taw, Myanmar
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Distinguishing Among Evolutionary Forces Acting on Genome-Wide Base Composition: Computer Simulation Analysis of Approximate Methods for Inferring Site Frequency Spectra of Derived Mutations. G3-GENES GENOMES GENETICS 2018; 8:1755-1769. [PMID: 29588382 PMCID: PMC5940166 DOI: 10.1534/g3.117.300512] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
Inferred ancestral nucleotide states are increasingly employed in analyses of within- and between -species genome variation. Although numerous studies have focused on ancestral inference among distantly related lineages, approaches to infer ancestral states in polymorphism data have received less attention. Recently developed approaches that employ complex transition matrices allow us to infer ancestral nucleotide sequence in various evolutionary scenarios of base composition. However, the requirement of a single gene tree to calculate a likelihood is an important limitation for conducting ancestral inference using within-species variation in recombining genomes. To resolve this problem, and to extend the applicability of ancestral inference in studies of base composition evolution, we first evaluate three previously proposed methods to infer ancestral nucleotide sequences among within- and between-species sequence variation data. The methods employ a single allele, bifurcating tree, or a star tree for within-species variation data. Using simulated nucleotide sequences, we employ ancestral inference to infer fixations and polymorphisms. We find that all three methods show biased inference. We modify the bifurcating tree method to include weights to adjust for an expected site frequency spectrum, “bifurcating tree with weighting” (BTW). Our simulation analysis show that the BTW method can substantially improve the reliability and robustness of ancestral inference in a range of scenarios that include non-neutral and/or non-stationary base composition evolution.
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25
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Alves I, Houle AA, Hussin JG, Awadalla P. The impact of recombination on human mutation load and disease. Philos Trans R Soc Lond B Biol Sci 2017; 372:20160465. [PMID: 29109227 PMCID: PMC5698626 DOI: 10.1098/rstb.2016.0465] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/03/2017] [Indexed: 12/21/2022] Open
Abstract
Recombination promotes genomic integrity among cells and tissues through double-strand break repair, and is critical for gamete formation and fertility through a strict regulation of the molecular mechanisms associated with proper chromosomal disjunction. In humans, congenital defects and recurrent structural abnormalities can be attributed to aberrant meiotic recombination. Moreover, mutations affecting genes involved in recombination pathways are directly linked to pathologies including infertility and cancer. Recombination is among the most prominent mechanism shaping genome variation, and is associated with not only the structuring of genomic variability, but is also tightly linked with the purging of deleterious mutations from populations. Together, these observations highlight the multiple roles of recombination in human genetics: its ability to act as a major force of evolution, its molecular potential to maintain genome repair and integrity in cell division and its mutagenic cost impacting disease evolution.This article is part of the themed issue 'Evolutionary causes and consequences of recombination rate variation in sexual organisms'.
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Affiliation(s)
- Isabel Alves
- Ontario Institute of Cancer Research, 661 University Avenue, Suite 510, Toronto, Ontario, Canada M5G 0A3
| | - Armande Ang Houle
- Ontario Institute of Cancer Research, 661 University Avenue, Suite 510, Toronto, Ontario, Canada M5G 0A3
- Department of Molecular Genetics, University of Toronto, Medical Science Building, 1 King's College Circle, Toronto, Ontario, Canada M5S 1A8
| | - Julie G Hussin
- Montreal Heart Institute, Department of Medicine, University of Montreal, 5000 Rue Bélanger, Montréal, Quebec, Canada H1T 1C8
- The Wellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford OX3 7BN, UK
| | - Philip Awadalla
- Ontario Institute of Cancer Research, 661 University Avenue, Suite 510, Toronto, Ontario, Canada M5G 0A3
- Department of Molecular Genetics, University of Toronto, Medical Science Building, 1 King's College Circle, Toronto, Ontario, Canada M5S 1A8
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26
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Xie Z, Wang L, Wang L, Wang Z, Lu Z, Tian D, Yang S, Hurst LD. Mutation rate analysis via parent-progeny sequencing of the perennial peach. I. A low rate in woody perennials and a higher mutagenicity in hybrids. Proc Biol Sci 2017; 283:rspb.2016.1016. [PMID: 27798292 PMCID: PMC5095371 DOI: 10.1098/rspb.2016.1016] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2016] [Accepted: 09/01/2016] [Indexed: 12/30/2022] Open
Abstract
Mutation rates vary between species, between strains within species and between regions within a genome. What are the determinants of these forms of variation? Here, via parent–offspring sequencing of the peach we ask whether (i) woody perennials tend to have lower per unit time mutation rates compared to annuals, and (ii) hybrid strains have high mutation rates. Between a leaf from a low heterozygosity individual, derived from an intraspecific cross, to a leaf of its selfed progeny, the mutation rate is 7.77 × 10−9 point mutations per bp per generation, similar to Arabidopsis thaliana (7.0–7.4 × 10−9 point mutations per bp per generation). This suggests a low per unit time mutation rate as the generation time is much longer in peach. This is supported by our estimate of 9.48 × 10−9 point mutations per bp per generation from a 200-year-old low heterozygosity peach to its progeny. From a more highly heterozygous individual derived from an interspecific cross to its selfed progeny, the mutation rate is 1.38 × 10−8 mutations per site per generation, consistent with raised rates in hybrids. Our data thus suggest that (i) peach has an approximately order of magnitude lower mutation rate per unit time than Arabidopsis, consistent with reports of low evolutionary rates in woody perennials, and (ii) hybridization may, indeed, be associated with increased mutation rates as considered over a century ago.
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Affiliation(s)
- Zhengqing Xie
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing 210023, People's Republic of China
| | - Long Wang
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing 210023, People's Republic of China
| | - Lirong Wang
- Chinese Academy of Agriculture Sciences, Zhengzhou Fruit Research Institute, Zhengzhou 450009, People's Republic of China
| | - Zhiqiang Wang
- Chinese Academy of Agriculture Sciences, Zhengzhou Fruit Research Institute, Zhengzhou 450009, People's Republic of China
| | - Zhenhua Lu
- Chinese Academy of Agriculture Sciences, Zhengzhou Fruit Research Institute, Zhengzhou 450009, People's Republic of China
| | - Dacheng Tian
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing 210023, People's Republic of China
| | - Sihai Yang
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing 210023, People's Republic of China
| | - Laurence D Hurst
- The Milner Centre for Evolution, Department of Biology and Biochemistry, University of Bath, Bath BA2 7AY, UK
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27
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Schield DR, Adams RH, Card DC, Perry BW, Pasquesi GM, Jezkova T, Portik DM, Andrew AL, Spencer CL, Sanchez EE, Fujita MK, Mackessy SP, Castoe TA. Insight into the roles of selection in speciation from genomic patterns of divergence and introgression in secondary contact in venomous rattlesnakes. Ecol Evol 2017; 7:3951-3966. [PMID: 28616190 PMCID: PMC5468163 DOI: 10.1002/ece3.2996] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2017] [Accepted: 03/21/2017] [Indexed: 01/03/2023] Open
Abstract
Investigating secondary contact of historically isolated lineages can provide insight into how selection and drift influence genomic divergence and admixture. Here, we studied the genomic landscape of divergence and introgression following secondary contact between lineages of the Western Diamondback Rattlesnake (Crotalus atrox) to determine whether genomic regions under selection in allopatry also contribute to reproductive isolation during introgression. We used thousands of nuclear loci to study genomic differentiation between two lineages that have experienced recent secondary contact following isolation, and incorporated sampling from a zone of secondary contact to identify loci that are resistant to gene flow in hybrids. Comparisons of patterns of divergence and introgression revealed a positive relationship between allelic differentiation and resistance to introgression across the genome, and greater‐than‐expected overlap between genes linked to lineage‐specific divergence and loci that resist introgression. Genes linked to putatively selected markers were related to prominent aspects of rattlesnake biology that differ between populations of Western Diamondback rattlesnakes (i.e., venom and reproductive phenotypes). We also found evidence for selection against introgression of genes that may contribute to cytonuclear incompatibility, consistent with previously observed biased patterns of nuclear and mitochondrial alleles suggestive of partial reproductive isolation due to cytonuclear incompatibilities. Our results provide a genome‐scale perspective on the relationships between divergence and introgression in secondary contact that is relevant for understanding the roles of selection in maintaining partial isolation of lineages, causing admixing lineages to not completely homogenize.
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Affiliation(s)
- Drew R Schield
- Department of Biology The University of Texas at Arlington Arlington TX USA
| | - Richard H Adams
- Department of Biology The University of Texas at Arlington Arlington TX USA
| | - Daren C Card
- Department of Biology The University of Texas at Arlington Arlington TX USA
| | - Blair W Perry
- Department of Biology The University of Texas at Arlington Arlington TX USA
| | - Giulia M Pasquesi
- Department of Biology The University of Texas at Arlington Arlington TX USA
| | - Tereza Jezkova
- Department of Ecology and Evolutionary Biology University of Arizona Tucson AZ USA
| | - Daniel M Portik
- Department of Biology The University of Texas at Arlington Arlington TX USA
| | - Audra L Andrew
- Department of Biology The University of Texas at Arlington Arlington TX USA
| | - Carol L Spencer
- Museum of Vertebrate Zoology University of California Berkeley CA USA
| | - Elda E Sanchez
- National Natural Toxins Research Center and Department of Chemistry Texas A&M University Kingsville Kingsville TX USA
| | - Matthew K Fujita
- Department of Biology The University of Texas at Arlington Arlington TX USA
| | - Stephen P Mackessy
- School of Biological Sciences University of Northern Colorado Greeley CO USA
| | - Todd A Castoe
- Department of Biology The University of Texas at Arlington Arlington TX USA
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28
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Romiguier J, Roux C. Analytical Biases Associated with GC-Content in Molecular Evolution. Front Genet 2017; 8:16. [PMID: 28261263 PMCID: PMC5309256 DOI: 10.3389/fgene.2017.00016] [Citation(s) in RCA: 37] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2016] [Accepted: 02/06/2017] [Indexed: 12/19/2022] Open
Abstract
Molecular evolution is being revolutionized by high-throughput sequencing allowing an increased amount of genome-wide data available for multiple species. While base composition summarized by GC-content is one of the first metrics measured in genomes, its genomic distribution is a frequently neglected feature in downstream analyses based on DNA sequence comparisons. Here, we show how base composition heterogeneity among loci and taxa can bias common molecular evolution analyses such as phylogenetic tree reconstruction, detection of natural selection and estimation of codon usage. We then discuss the biological, technical and methodological causes of these GC-associated biases and suggest approaches to overcome them.
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Affiliation(s)
- Jonathan Romiguier
- Department of Ecology and Evolution, University of Lausanne Lausanne, Switzerland
| | - Camille Roux
- Department of Ecology and Evolution, University of Lausanne Lausanne, Switzerland
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29
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Liu H, Jia Y, Sun X, Tian D, Hurst LD, Yang S. Direct Determination of the Mutation Rate in the Bumblebee Reveals Evidence for Weak Recombination-Associated Mutation and an Approximate Rate Constancy in Insects. Mol Biol Evol 2017; 34:119-130. [PMID: 28007973 PMCID: PMC5854123 DOI: 10.1093/molbev/msw226] [Citation(s) in RCA: 67] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023] Open
Abstract
Accurate knowledge of the mutation rate provides a base line for inferring expected rates of evolution, for testing evolutionary hypotheses and for estimation of key parameters. Advances in sequencing technology now permit direct estimates of the mutation rate from sequencing of close relatives. Within insects there have been three prior such estimates, two in nonsocial insects (Drosophila: 2.8 × 10-9 per bp per haploid genome per generation; Heliconius: 2.9 × 10-9) and one in a social species, the honeybee (3.4 × 10-9). Might the honeybee's rate be ∼20% higher because it has an exceptionally high recombination rate and recombination may be directly or indirectly mutagenic? To address this possibility, we provide a direct estimate of the mutation rate in the bumblebee (Bombus terrestris), this being a close relative of the honeybee but with a much lower recombination rate. We confirm that the crossover rate of the bumblebee is indeed much lower than honeybees (8.7 cM/Mb vs. 37 cM/Mb). Importantly, we find no significant difference in the mutation rates: we estimate for bumblebees a rate of 3.6 × 10-9 per haploid genome per generation (95% confidence intervals 2.38 × 10-9 and 5.37 × 10-9) which is just 5% higher than the estimate that of honeybees. Both genomes have approximately one new mutation per haploid genome per generation. While we find evidence for a direct coupling between recombination and mutation (also seen in honeybees), the effect is so weak as to leave almost no footprint on any between-species differences. The similarity in mutation rates suggests an approximate constancy of the mutation rate in insects.
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Affiliation(s)
- Haoxuan Liu
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing, China
| | - Yanxiao Jia
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing, China
| | - Xiaoguang Sun
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing, China
| | - Dacheng Tian
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing, China
| | - Laurence D Hurst
- Department of Biology and Biochemistry, The Milner Centre for Evolution, University of Bath, Bath, United Kingdom
| | - Sihai Yang
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing, China
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30
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Abstract
Alpha-thalassemia (α-thal) is a disorder caused by the deletion of single or double α-globin genes, and/or point mutations in the α-globin genes. There are 2 common types of α-globin genes; HBA2 and HBA1. Recently, it has been discovered that the HBA2 gene is replaced by a unique HBA12 gene convert in 5.7% of the Saudi population. The α-globin genes have been emerging as a molecular target for the treatment of β-thalassemia (β-thal). Hence, it is essential to understand the molecular nature of α-globin genes to treat the most prevalent hemoglobin disorders, such as sickle cell disease, α-thal, and β-thal prevalent in the Kingdom of Saudi Arabia. Thirty-two different α-globin genotypes have been observed in the Saudi population. This review outlines the classification of the α-globin genes on the basis of their molecular nature and complex combinations of α-globin genes, and their variants predominant in Saudis.
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Affiliation(s)
- J Francis Borgio
- Center for Research and Medical Consultation, University of Dammam, Dammam, Kingdom of Saudi Arabia. E-mail.
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31
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The rate of meiotic gene conversion varies by sex and age. Nat Genet 2016; 48:1377-1384. [PMID: 27643539 PMCID: PMC5083143 DOI: 10.1038/ng.3669] [Citation(s) in RCA: 54] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2015] [Accepted: 08/16/2016] [Indexed: 12/14/2022]
Abstract
Meiotic recombination involves a combination of gene conversion and crossover events that, along with mutations, produce germline genetic diversity. Here we report the discovery of 3,176 SNP and 61 indel gene conversions. Our estimate of the non-crossover (NCO) gene conversion rate (G) is 7.0 for SNPs and 5.8 for indels per megabase per generation, and the GC bias is 67.6%. For indels, we demonstrate a 65.6% preference for the shorter allele. NCO gene conversions from mothers are longer than those from fathers, and G is 2.17 times greater in mothers. Notably, G increases with the age of mothers, but not the age of fathers. A disproportionate number of NCO gene conversions in older mothers occur outside double-strand break (DSB) regions and in regions with relatively low GC content. This points to age-related changes in the mechanisms of meiotic gene conversion in oocytes.
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32
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Abstract
Cellular processes mediated through nuclear DNA must contend with chromatin. Chromatin structural assays can efficiently integrate information across diverse regulatory elements, revealing the functional noncoding genome. In this study, we use a differential nuclease sensitivity assay based on micrococcal nuclease (MNase) digestion to discover open chromatin regions in the maize genome. We find that maize MNase-hypersensitive (MNase HS) regions localize around active genes and within recombination hotspots, focusing biased gene conversion at their flanks. Although MNase HS regions map to less than 1% of the genome, they consistently explain a remarkably large amount (∼40%) of heritable phenotypic variance in diverse complex traits. MNase HS regions are therefore on par with coding sequences as annotations that demarcate the functional parts of the maize genome. These results imply that less than 3% of the maize genome (coding and MNase HS regions) may give rise to the overwhelming majority of phenotypic variation, greatly narrowing the scope of the functional genome.
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33
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Arnheim N, Calabrese P. Germline Stem Cell Competition, Mutation Hot Spots, Genetic Disorders, and Older Fathers. Annu Rev Genomics Hum Genet 2016; 17:219-43. [PMID: 27070266 DOI: 10.1146/annurev-genom-083115-022656] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
Some de novo human mutations arise at frequencies far exceeding the genome average mutation rate. Examples include the common mutations at one or a few sites in the genes that cause achondroplasia, Apert syndrome, multiple endocrine neoplasia type 2B, and Noonan syndrome. These mutations are recurrent, provide a gain of function, are paternally derived, and are more likely to be transmitted as the father ages. Recent experiments have tested whether the high mutation frequencies are due to an elevated mutation rate per cell division, as expected, or to an advantage of the mutant spermatogonial stem cells over wild-type stem cells. The evidence, which includes the surprising discovery of testis mutation clusters, rules out the former model but not the latter. We propose how the mutations might alter spermatogonial stem cell function and discuss how germline selection contributes to the paternal age effect, the human mutational load, and adaptive evolution.
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Affiliation(s)
- Norman Arnheim
- Molecular and Computational Biology Program, University of Southern California, Los Angeles, California 90089-2910; ,
| | - Peter Calabrese
- Molecular and Computational Biology Program, University of Southern California, Los Angeles, California 90089-2910; ,
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34
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Distance from sub-Saharan Africa predicts mutational load in diverse human genomes. Proc Natl Acad Sci U S A 2015; 113:E440-9. [PMID: 26712023 DOI: 10.1073/pnas.1510805112] [Citation(s) in RCA: 155] [Impact Index Per Article: 17.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023] Open
Abstract
The Out-of-Africa (OOA) dispersal ∼ 50,000 y ago is characterized by a series of founder events as modern humans expanded into multiple continents. Population genetics theory predicts an increase of mutational load in populations undergoing serial founder effects during range expansions. To test this hypothesis, we have sequenced full genomes and high-coverage exomes from seven geographically divergent human populations from Namibia, Congo, Algeria, Pakistan, Cambodia, Siberia, and Mexico. We find that individual genomes vary modestly in the overall number of predicted deleterious alleles. We show via spatially explicit simulations that the observed distribution of deleterious allele frequencies is consistent with the OOA dispersal, particularly under a model where deleterious mutations are recessive. We conclude that there is a strong signal of purifying selection at conserved genomic positions within Africa, but that many predicted deleterious mutations have evolved as if they were neutral during the expansion out of Africa. Under a model where selection is inversely related to dominance, we show that OOA populations are likely to have a higher mutation load due to increased allele frequencies of nearly neutral variants that are recessive or partially recessive.
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35
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Ramos PS, Shedlock AM, Langefeld CD. Genetics of autoimmune diseases: insights from population genetics. J Hum Genet 2015; 60:657-64. [PMID: 26223182 PMCID: PMC4660050 DOI: 10.1038/jhg.2015.94] [Citation(s) in RCA: 110] [Impact Index Per Article: 12.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2015] [Revised: 06/12/2015] [Accepted: 06/19/2015] [Indexed: 12/14/2022]
Abstract
Human genetic diversity is the result of population genetic forces. This genetic variation influences disease risk and contributes to health disparities. Autoimmune diseases (ADs) are a family of complex heterogeneous disorders with similar underlying mechanisms characterized by immune responses against self. Collectively, ADs are common, exhibit gender and ethnic disparities, and increasing incidence. As natural selection is an important influence on human genetic variation, and immune function genes are enriched for signals of positive selection, it is thought that the prevalence of AD risk alleles seen in different population is partially the result of differing selective pressures (for example, due to pathogens). With the advent of high-throughput technologies, new analytical methodologies and large-scale projects, evidence for the role of natural selection in contributing to the heritable component of ADs keeps growing. This review summarizes the genetic regions associated with susceptibility to different ADs and concomitant evidence for selection, including known agents of selection exerting selective pressure in these regions. Examples of specific adaptive variants with phenotypic effects are included as an evidence of natural selection increasing AD susceptibility. Many of the complexities of gene effects in different ADs can be explained by population genetics phenomena. Integrating AD susceptibility studies with population genetics to investigate how natural selection has contributed to genetic variation that influences disease risk will help to identify functional variants and elucidate biological mechanisms. As such, the study of population genetics in human population holds untapped potential for elucidating the genetic causes of human disease and more rapidly focusing to personalized medicine.
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Affiliation(s)
- Paula S Ramos
- Division of Rheumatology and Immunology, Department of Medicine, and Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC, USA
| | - Andrew M Shedlock
- Department of Biology, College of Charleston, Charleston, SC, USA
- Hollings Marine Laboratory Center for Marine Biomedicine and College of Graduate Studies, Medical University of South Carolina, Charleston, SC, USA
| | - Carl D Langefeld
- Division of Public Health Sciences, Department of Biostatistical Sciences; and Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, NC, USA
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36
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Mugal CF, Weber CC, Ellegren H. GC-biased gene conversion links the recombination landscape and demography to genomic base composition. Bioessays 2015; 37:1317-26. [DOI: 10.1002/bies.201500058] [Citation(s) in RCA: 58] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Affiliation(s)
- Carina F. Mugal
- Department of Evolutionary Biology; Evolutionary Biology Centre; Uppsala University; Uppsala Sweden
| | - Claudia C. Weber
- Department of Evolutionary Biology; Evolutionary Biology Centre; Uppsala University; Uppsala Sweden
- Department of Biology; Center for Computational Genetics and Genomics; Temple University; Philadelphia PA USA
| | - Hans Ellegren
- Department of Evolutionary Biology; Evolutionary Biology Centre; Uppsala University; Uppsala Sweden
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37
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Bolívar P, Mugal CF, Nater A, Ellegren H. Recombination Rate Variation Modulates Gene Sequence Evolution Mainly via GC-Biased Gene Conversion, Not Hill-Robertson Interference, in an Avian System. Mol Biol Evol 2015; 33:216-27. [PMID: 26446902 PMCID: PMC4693978 DOI: 10.1093/molbev/msv214] [Citation(s) in RCA: 40] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
The ratio of nonsynonymous to synonymous substitution rates (ω) is often used to measure the strength of natural selection. However, ω may be influenced by linkage among different targets of selection, that is, Hill–Robertson interference (HRI), which reduces the efficacy of selection. Recombination modulates the extent of HRI but may also affect ω by means of GC-biased gene conversion (gBGC), a process leading to a preferential fixation of G:C (“strong,” S) over A:T (“weak,” W) alleles. As HRI and gBGC can have opposing effects on ω, it is essential to understand their relative impact to make proper inferences of ω. We used a model that separately estimated S-to-S, S-to-W, W-to-S, and W-to-W substitution rates in 8,423 avian genes in the Ficedula flycatcher lineage. We found that the W-to-S substitution rate was positively, and the S-to-W rate negatively, correlated with recombination rate, in accordance with gBGC but not predicted by HRI. The W-to-S rate further showed the strongest impact on both dN and dS. However, since the effects were stronger at 4-fold than at 0-fold degenerated sites, likely because the GC content of these sites is farther away from its equilibrium, ω slightly decreases with increasing recombination rate, which could falsely be interpreted as a consequence of HRI. We corroborated this hypothesis analytically and demonstrate that under particular conditions, ω can decrease with increasing recombination rate. Analyses of the site-frequency spectrum showed that W-to-S mutations were skewed toward high, and S-to-W mutations toward low, frequencies, consistent with a prevalent gBGC-driven fixation bias.
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Affiliation(s)
- Paulina Bolívar
- Department of Evolutionary Biology, Evolutionary Biology Centre, Uppsala University, Uppsala, Sweden
| | - Carina F Mugal
- Department of Evolutionary Biology, Evolutionary Biology Centre, Uppsala University, Uppsala, Sweden
| | - Alexander Nater
- Department of Evolutionary Biology, Evolutionary Biology Centre, Uppsala University, Uppsala, Sweden
| | - Hans Ellegren
- Department of Evolutionary Biology, Evolutionary Biology Centre, Uppsala University, Uppsala, Sweden
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38
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Simonti CN, Capra JA. The evolution of the human genome. Curr Opin Genet Dev 2015; 35:9-15. [PMID: 26338498 DOI: 10.1016/j.gde.2015.08.005] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2015] [Revised: 08/08/2015] [Accepted: 08/12/2015] [Indexed: 02/05/2023]
Abstract
Human genomes hold a record of the evolutionary forces that have shaped our species. Advances in DNA sequencing, functional genomics, and population genetic modeling have deepened our understanding of human demographic history, natural selection, and many other long-studied topics. These advances have also revealed many previously underappreciated factors that influence the evolution of the human genome, including functional modifications to DNA and histones, conserved 3D topological chromatin domains, structural variation, and heterogeneous mutation patterns along the genome. Using evolutionary theory as a lens to study these phenomena will lead to significant breakthroughs in understanding what makes us human and why we get sick.
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Affiliation(s)
- Corinne N Simonti
- Vanderbilt Genetics Institute, Vanderbilt University, Nashville, TN 37235, USA
| | - John A Capra
- Vanderbilt Genetics Institute, Vanderbilt University, Nashville, TN 37235, USA; Department of Biological Sciences, Vanderbilt University, Nashville, TN 37235, USA; Department of Biomedical Informatics, Vanderbilt University, Nashville, TN 37235, USA.
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39
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Glémin S, Arndt PF, Messer PW, Petrov D, Galtier N, Duret L. Quantification of GC-biased gene conversion in the human genome. Genome Res 2015; 25:1215-28. [PMID: 25995268 PMCID: PMC4510005 DOI: 10.1101/gr.185488.114] [Citation(s) in RCA: 89] [Impact Index Per Article: 9.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2014] [Accepted: 05/18/2015] [Indexed: 11/25/2022]
Abstract
Much evidence indicates that GC-biased gene conversion (gBGC) has a major impact on the evolution of mammalian genomes. However, a detailed quantification of the process is still lacking. The strength of gBGC can be measured from the analysis of derived allele frequency spectra (DAF), but this approach is sensitive to a number of confounding factors. In particular, we show by simulations that the inference is pervasively affected by polymorphism polarization errors and by spatial heterogeneity in gBGC strength. We propose a new general method to quantify gBGC from DAF spectra, incorporating polarization errors, taking spatial heterogeneity into account, and jointly estimating mutation bias. Applying it to human polymorphism data from the 1000 Genomes Project, we show that the strength of gBGC does not differ between hypermutable CpG sites and non-CpG sites, suggesting that in humans gBGC is not caused by the base-excision repair machinery. Genome-wide, the intensity of gBGC is in the nearly neutral area. However, given that recombination occurs primarily within recombination hotspots, 1%–2% of the human genome is subject to strong gBGC. On average, gBGC is stronger in African than in non-African populations, reflecting differences in effective population sizes. However, due to more heterogeneous recombination landscapes, the fraction of the genome affected by strong gBGC is larger in non-African than in African populations. Given that the location of recombination hotspots evolves very rapidly, our analysis predicts that, in the long term, a large fraction of the genome is affected by short episodes of strong gBGC.
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Affiliation(s)
- Sylvain Glémin
- Institut des Sciences de l'Evolution (ISEM - UMR 5554 Université de Montpellier-CNRS-IRD-EPHE), 34095 Montpellier, France; Department of Ecology and Genetics, Evolutionary Biology Centre, Uppsala University, SE-752 36 Uppsala, Sweden
| | - Peter F Arndt
- Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, 14195 Berlin, Germany
| | - Philipp W Messer
- Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, New York 14853, USA
| | - Dmitri Petrov
- Department of Biology, Stanford University, Stanford, California 94305-5020, USA
| | - Nicolas Galtier
- Institut des Sciences de l'Evolution (ISEM - UMR 5554 Université de Montpellier-CNRS-IRD-EPHE), 34095 Montpellier, France
| | - Laurent Duret
- Laboratoire de Biométrie et Biologie Evolutive, UMR CNRS 5558, Université Lyon 1, 69622 Villeurbanne, France
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40
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Wallberg A, Glémin S, Webster MT. Extreme recombination frequencies shape genome variation and evolution in the honeybee, Apis mellifera. PLoS Genet 2015; 11:e1005189. [PMID: 25902173 PMCID: PMC4406589 DOI: 10.1371/journal.pgen.1005189] [Citation(s) in RCA: 70] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2014] [Accepted: 04/01/2015] [Indexed: 01/10/2023] Open
Abstract
Meiotic recombination is a fundamental cellular process, with important consequences for evolution and genome integrity. However, we know little about how recombination rates vary across the genomes of most species and the molecular and evolutionary determinants of this variation. The honeybee, Apis mellifera, has extremely high rates of meiotic recombination, although the evolutionary causes and consequences of this are unclear. Here we use patterns of linkage disequilibrium in whole genome resequencing data from 30 diploid honeybees to construct a fine-scale map of rates of crossing over in the genome. We find that, in contrast to vertebrate genomes, the recombination landscape is not strongly punctate. Crossover rates strongly correlate with levels of genetic variation, but not divergence, which indicates a pervasive impact of selection on the genome. Germ-line methylated genes have reduced crossover rate, which could indicate a role of methylation in suppressing recombination. Controlling for the effects of methylation, we do not infer a strong association between gene expression patterns and recombination. The site frequency spectrum is strongly skewed from neutral expectations in honeybees: rare variants are dominated by AT-biased mutations, whereas GC-biased mutations are found at higher frequencies, indicative of a major influence of GC-biased gene conversion (gBGC), which we infer to generate an allele fixation bias 5 – 50 times the genomic average estimated in humans. We uncover further evidence that this repair bias specifically affects transitions and favours fixation of CpG sites. Recombination, via gBGC, therefore appears to have profound consequences on genome evolution in honeybees and interferes with the process of natural selection. These findings have important implications for our understanding of the forces driving molecular evolution. Evolution results from changes in allele frequencies in populations. The main forces that cause such changes are natural selection and random genetic drift. However, an additional process, GC-biased gene conversion (gBGC), associated with meiotic recombination, affects the probability that alleles are passed from one generation to the next. The honeybee, Apis mellifera, has extremely high recombination rates—more than 20 times to those observed in humans. However, the reason for this is unknown and the effects of such high recombination rates on evolution are not well understood. Here we use patterns of genetic variation in the genomes of 30 honeybees to infer variation in the rate of recombination across the genome. We find that recombination rates and levels of genetic variation are strongly correlated, which is indicative of a pervasive impact of natural selection on genetic variation. We also infer a major role of DNA methylation in determining recombination rates in genes. Patterns of genetic variation appear to be strongly skewed due to the effects of gBGC, suggesting that recombination generates a bias in transmission of alleles during meiosis. This process seems to be interfering with the efficacy of selection at removing deleterious alleles and favouring beneficial ones. Recombination therefore has a huge impact on genetic variation and evolution in honeybees and appears to play a dominant role in genome evolution.
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Affiliation(s)
- Andreas Wallberg
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Sylvain Glémin
- Institut des Sciences de l’Evolution (ISEM—UMR 5554 Université de Montpellier-CNRS-IRD-EPHE), France
- Department of Ecology and Genetics, Evolutionary Biology Centre, Uppsala University, Uppsala, Sweden
| | - Matthew T. Webster
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden
- * E-mail:
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Rodgers-Melnick E, Bradbury PJ, Elshire RJ, Glaubitz JC, Acharya CB, Mitchell SE, Li C, Li Y, Buckler ES. Recombination in diverse maize is stable, predictable, and associated with genetic load. Proc Natl Acad Sci U S A 2015; 112:3823-8. [PMID: 25775595 PMCID: PMC4378432 DOI: 10.1073/pnas.1413864112] [Citation(s) in RCA: 149] [Impact Index Per Article: 16.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
Among the fundamental evolutionary forces, recombination arguably has the largest impact on the practical work of plant breeders. Varying over 1,000-fold across the maize genome, the local meiotic recombination rate limits the resolving power of quantitative trait mapping and the precision of favorable allele introgression. The consequences of low recombination also theoretically extend to the species-wide scale by decreasing the power of selection relative to genetic drift, and thereby hindering the purging of deleterious mutations. In this study, we used genotyping-by-sequencing (GBS) to identify 136,000 recombination breakpoints at high resolution within US and Chinese maize nested association mapping populations. We find that the pattern of cross-overs is highly predictable on the broad scale, following the distribution of gene density and CpG methylation. Several large inversions also suppress recombination in distinct regions of several families. We also identify recombination hotspots ranging in size from 1 kb to 30 kb. We find these hotspots to be historically stable and, compared with similar regions with low recombination, to have strongly differentiated patterns of DNA methylation and GC content. We also provide evidence for the historical action of GC-biased gene conversion in recombination hotspots. Finally, using genomic evolutionary rate profiling (GERP) to identify putative deleterious polymorphisms, we find evidence for reduced genetic load in hotspot regions, a phenomenon that may have considerable practical importance for breeding programs worldwide.
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Affiliation(s)
| | - Peter J Bradbury
- Institute for Genomic Diversity, Cornell University, Ithaca, NY 14853; US Department of Agriculture-Agricultural Research Service, Ithaca, NY 14853; and
| | - Robert J Elshire
- Institute for Genomic Diversity, Cornell University, Ithaca, NY 14853
| | | | | | - Sharon E Mitchell
- Institute for Genomic Diversity, Cornell University, Ithaca, NY 14853
| | - Chunhui Li
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Yongxiang Li
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Edward S Buckler
- Institute for Genomic Diversity, Cornell University, Ithaca, NY 14853; US Department of Agriculture-Agricultural Research Service, Ithaca, NY 14853; and
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