1
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Witt ASA, Carvalho JVRP, Serafim MSM, Arias NEC, Rodrigues RAL, Abrahão JS. The GC% landscape of the Nucleocytoviricota. Braz J Microbiol 2024:10.1007/s42770-024-01496-7. [PMID: 39180708 DOI: 10.1007/s42770-024-01496-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2024] [Accepted: 08/14/2024] [Indexed: 08/26/2024] Open
Abstract
Genomic studies on sequence composition employ various approaches, such as calculating the proportion of guanine and cytosine within a given sequence (GC% content), which can shed light on various aspects of the organism's biology. In this context, GC% can provide insights into virus-host relationships and evolution. Here, we present a comprehensive gene-by-gene analysis of 61 representatives belonging to the phylum Nucleocytoviricota, which comprises viruses with the largest genomes known in the virosphere. Parameters were evaluated not only based on the average GC% of a given viral species compared to the entire phylum but also considering gene position and phylogenetic history. Our results reveal that while some families exhibit similar GC% among their representatives (e.g., Marseilleviridae), others such as Poxviridae, Phycodnaviridae, and Mimiviridae have members with discrepant GC% values, likely reflecting adaptation to specific biological cycles and hosts. Interestingly, certain genes located at terminal regions or within specific genomic clusters show GC% values distinct from the average, suggesting recent acquisition or unique evolutionary pressures. Horizontal gene transfer and the presence of potential paralogs were also assessed in genes with the most discrepant GC% values, indicating multiple evolutionary histories. Taken together, to the best of our knowledge, this study represents the first global and gene-by-gene analysis of GC% distribution and profiles within genomes of Nucleocytoviricota members, highlighting their diversity and identifying potential new targets for future studies.
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Affiliation(s)
- Amanda Stéphanie Arantes Witt
- Department of Microbiology, Institute of Biological Sciences, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | | | - Mateus Sá Magalhães Serafim
- Department of Microbiology, Institute of Biological Sciences, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - Nidia Esther Colquehuanca Arias
- Department of Microbiology, Institute of Biological Sciences, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - Rodrigo Araújo Lima Rodrigues
- Department of Microbiology, Institute of Biological Sciences, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - Jônatas Santos Abrahão
- Department of Microbiology, Institute of Biological Sciences, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil.
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2
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Chase MA, Vilcot M, Mugal CF. The role of recombination dynamics in shaping signatures of direct and indirect selection across the Ficedula flycatcher genome †. Proc Biol Sci 2024; 291:20232382. [PMID: 38228173 DOI: 10.1098/rspb.2023.2382] [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: 10/20/2022] [Accepted: 12/14/2023] [Indexed: 01/18/2024] Open
Abstract
Recombination is a central evolutionary process that reshuffles combinations of alleles along chromosomes, and consequently is expected to influence the efficacy of direct selection via Hill-Robertson interference. Additionally, the indirect effects of selection on neutral genetic diversity are expected to show a negative relationship with recombination rate, as background selection and genetic hitchhiking are stronger when recombination rate is low. However, owing to the limited availability of recombination rate estimates across divergent species, the impact of evolutionary changes in recombination rate on genomic signatures of selection remains largely unexplored. To address this question, we estimate recombination rate in two Ficedula flycatcher species, the taiga flycatcher (Ficedula albicilla) and collared flycatcher (Ficedula albicollis). We show that recombination rate is strongly correlated with signatures of indirect selection, and that evolutionary changes in recombination rate between species have observable impacts on this relationship. Conversely, signatures of direct selection on coding sequences show little to no relationship with recombination rate, even when restricted to genes where recombination rate is conserved between species. Thus, using measures of indirect and direct selection that bridge micro- and macro-evolutionary timescales, we demonstrate that the role of recombination rate and its dynamics varies for different signatures of selection.
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Affiliation(s)
- Madeline A Chase
- Department of Ecology and Genetics, Uppsala University, 75236 Uppsala, Sweden
- Swiss Ornithological Institute, 6204 Sempach, Switzerland
| | - Maurine Vilcot
- Department of Ecology and Genetics, Uppsala University, 75236 Uppsala, Sweden
- CEFE, University of Montpellier, CNRS, EPHE, IRD, 34293 Montpellier 5, France
| | - Carina F Mugal
- Department of Ecology and Genetics, Uppsala University, 75236 Uppsala, Sweden
- Laboratory of Biometry and Evolutionary Biology, University of Lyon 1, CNRS UMR 5558, 69622 Villeurbanne cedex, France
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3
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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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4
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Peona V, Kutschera VE, Blom MPK, Irestedt M, Suh A. Satellite DNA evolution in Corvoidea inferred from short and long reads. Mol Ecol 2023; 32:1288-1305. [PMID: 35488497 DOI: 10.1111/mec.16484] [Citation(s) in RCA: 17] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Revised: 04/11/2022] [Accepted: 04/17/2022] [Indexed: 11/29/2022]
Abstract
Satellite DNA (satDNA) is a fast-evolving portion of eukaryotic genomes. The homogeneous and repetitive nature of such satDNA causes problems during the assembly of genomes, and therefore it is still difficult to study it in detail in nonmodel organisms as well as across broad evolutionary timescales. Here, we combined the use of short- and long-read data to explore the diversity and evolution of satDNA between individuals of the same species and between genera of birds spanning ~40 millions of years of bird evolution using birds-of-paradise (Paradisaeidae) and crow (Corvus) species. These avian species highlighted the presence of a GC-rich Corvoidea satellitome composed of 61 satellite families and provided a set of candidate satDNA monomers for being centromeric on the basis of length, abundance, homogeneity and transcription. Surprisingly, we found that the satDNA of crow species rapidly diverged between closely related species while the satDNA appeared more similar between birds-of-paradise species belonging to different genera.
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Affiliation(s)
- Valentina Peona
- Department of Organismal Biology - Systematic Biology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Verena E Kutschera
- Department of Biochemistry and Biophysics, National Bioinformatics Infrastructure Sweden, Science for Life Laboratory, Stockholm University, Solna, Sweden
| | - Mozes P K Blom
- Department of Bioinformatics and Genetics, Swedish Museum of Natural History, Stockholm, Sweden.,Museum für Naturkunde, Leibniz Institut für Evolutions- und Biodiversitätsforschung, Berlin, Germany
| | - Martin Irestedt
- Department of Bioinformatics and Genetics, Swedish Museum of Natural History, Stockholm, Sweden
| | - Alexander Suh
- Department of Organismal Biology - Systematic Biology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden.,School of Biological Sciences-Organisms and the Environment, University of East Anglia, Norwich, UK
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5
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Ponnikas S, Sigeman H, Lundberg M, Hansson B. Extreme variation in recombination rate and genetic diversity along the Sylvioidea neo-sex chromosome. Mol Ecol 2022; 31:3566-3583. [PMID: 35578784 PMCID: PMC9327509 DOI: 10.1111/mec.16532] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Revised: 04/13/2022] [Accepted: 05/04/2022] [Indexed: 12/03/2022]
Abstract
Recombination strongly impacts sequence evolution by affecting the extent of linkage and the efficiency of selection. Here, we study recombination over the Z chromosome in great reed warblers (Acrocephalus arundinaceus) using pedigree-based linkage mapping. This species has extended Z and W chromosomes ("neo-sex chromosomes") formed by a fusion between a part of chromosome 4A and the ancestral sex chromosomes, which provides a unique opportunity to assess recombination and sequence evolution in sex-linked regions of different ages. We assembled an 87.54 Mbp and 90.19 cM large Z with a small pseudoautosomal region (0.89 Mbp) at one end and the fused Chr4A-part at the other end of the chromosome. A prominent feature in our data was an extreme variation in male recombination rate along Z with high values at both chromosome ends, but an apparent lack of recombination over a substantial central section, covering 78% of the chromosome. The nonrecombining region showed a drastic loss of genetic diversity and accumulation of repeats compared to the recombining parts. Thus, our data emphasize a key role of recombination in affecting local levels of polymorphism. Nonetheless, the evolutionary rate of genes (dN/dS) did not differ between high and low recombining regions, suggesting that the efficiency of selection on protein-coding sequences can be maintained also at very low levels of recombination. Finally, the Chr4A-derived part showed a similar recombination rate as the part of the ancestral Z that did recombine, but its sequence characteristics reflected both its previous autosomal, and current Z-linked, recombination patterns.
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Affiliation(s)
- Suvi Ponnikas
- Department of BiologyLund UniversityLundSweden
- Ecology and Genetics Research UnitUniversity of OuluOuluFinland
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6
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Wilcox JJS, Arca-Ruibal B, Samour J, Mateuta V, Idaghdour Y, Boissinot S. Linked-Read Sequencing of Eight Falcons Reveals a Unique Genomic Architecture in Flux. Genome Biol Evol 2022; 14:evac090. [PMID: 35700227 PMCID: PMC9214253 DOI: 10.1093/gbe/evac090] [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: 11/12/2021] [Revised: 05/27/2022] [Accepted: 06/06/2022] [Indexed: 11/12/2022] Open
Abstract
Falcons are diverse birds of cultural and economic importance. They have undergone major lineage-specific chromosomal rearrangements, resulting in greatly-reduced chromosome counts relative to other birds. Here, we use 10X Genomics linked reads to provide new high-contiguity genomes for two gyrfalcons, a saker falcon, a lanner falcon, three subspecies of peregrine falcons, and the common kestrel. Assisted by a transcriptome sequenced from 22 gyrfalcon tissues, we annotate these genomes for a variety of genomic features, estimate historical demography, and then investigate genomic equilibrium in the context of falcon-specific chromosomal rearrangements. We find that falcon genomes are not in AT-GC equilibrium with a bias in substitutions towards higher AT content; this bias is predominantly but not exclusively driven by hypermutability of CpG sites. Small indels and large structural variants were also biased towards insertions rather than deletions. Patterns of disequilibrium were linked to chromosomal rearrangements: falcons have lost GC content in regions that have fused to larger chromosomes from microchromosomes and gained GC content in regions of macrochromosomes that have translocated to microchromosomes. Inserted bases have accumulated on regions ancestrally belonging to microchromosomes, consistent with insertion-biased gene conversion. We also find an excess of interspersed repeats on regions of microchromosomes that have fused to macrochromosomes. Our results reveal that falcon genomes are in a state of flux. They further suggest that many of the key differences between microchromosomes and macrochromosomes are driven by differences in chromosome size, and indicate a clear role for recombination and biased-gene-conversion in determining genomic equilibrium.
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Affiliation(s)
- Justin J S Wilcox
- Center for Genomics & Systems Biology, New York University Abu Dhabi, Saadiyat Island, Abu Dhabi, United Arab Emirates
| | | | - Jaime Samour
- Wildlife Management and Falcon Medicine and Breeding Consultancy, Abu Dhabi, United Arab Emirates
| | | | - Youssef Idaghdour
- Center for Genomics & Systems Biology, New York University Abu Dhabi, Saadiyat Island, Abu Dhabi, United Arab Emirates
- Biology Program, New York University Abu Dhabi, Saadiyat Island, Abu Dhabi, United Arab Emirates
| | - Stéphane Boissinot
- Center for Genomics & Systems Biology, New York University Abu Dhabi, Saadiyat Island, Abu Dhabi, United Arab Emirates
- Biology Program, New York University Abu Dhabi, Saadiyat Island, Abu Dhabi, United Arab Emirates
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7
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Abstract
Recombination increases the local GC-content in genomic regions through GC-biased gene conversion (gBGC). The recent discovery of a large genomic region with extreme GC-content in the fat sand rat Psammomys obesus provides a model to study the effects of gBGC on chromosome evolution. Here, we compare the GC-content and GC-to-AT substitution patterns across protein-coding genes of four gerbil species and two murine rodents (mouse and rat). We find that the known high-GC region is present in all the gerbils, and is characterized by high substitution rates for all mutational categories (AT-to-GC, GC-to-AT, and GC-conservative) both at synonymous and nonsynonymous sites. A higher AT-to-GC than GC-to-AT rate is consistent with the high GC-content. Additionally, we find more than 300 genes outside the known region with outlying values of AT-to-GC synonymous substitution rates in gerbils. Of these, over 30% are organized into at least 17 large clusters observable at the megabase-scale. The unusual GC-skewed substitution pattern suggests the evolution of genomic regions with very high recombination rates in the gerbil lineage, which can lead to a runaway increase in GC-content. Our results imply that rapid evolution of GC-content is possible in mammals, with gerbil species providing a powerful model to study the mechanisms of gBGC.
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Affiliation(s)
- Rodrigo Pracana
- Department of Zoology, University of Oxford, Oxford, United Kingdom
| | | | - John F Mulley
- School of Natural Sciences, Bangor University, Bangor, Gwynedd, United Kingdom
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8
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Adapting Biased Gene Conversion theory to account for intensive GC-content deterioration in the human genome by novel mutations. PLoS One 2020; 15:e0232167. [PMID: 32353016 PMCID: PMC7192473 DOI: 10.1371/journal.pone.0232167] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2019] [Accepted: 04/09/2020] [Indexed: 12/23/2022] Open
Abstract
We examined seventy million well-characterized human mutations, and their impact on G+C-compositional dynamics, in order to understand the formation and maintenance of major genomic nucleotide sequence patterns. Among novel mutations, those that change a strong (S) base pair G:C/C:G to a weak (W) pair A:T/T:A occur at nearly twice the frequency of the opposite mutations. Such imbalance puts strong downward pressure on overall GC-content. However, along protracted paths to fixation, S→W mutations are much less likely to propagate than W→S mutations. The magnitude of relative propagation disadvantages for S→W mutations is inexplicable by any currently-accepted model. This fact forced us to re-examine the quantitative features of Biased Gene Conversion (BGC) theory. Revised parameters of BGC that, per average individual, convert 7–14 W base pairs into S pairs, would account for the S-content turnover differences between new and old mutations, and make BGC an instrumental force for nucleotide dynamics and evolution. BGC should thus be considered seriously in both theories and biomedical practice. In particular, BGC should be taken into account during allele imputations, where missing SNP alleles are computationally predicted based on the information about several neighboring alleles. Finally, we analyzed the effect of neighboring nucleotide context on the mutation frequencies, dynamics, and GC-composition turnover. For this purpose, we examined genomic regions having extremely biased nucleotide compositions (enriched for S-, W-, purine/pyrimidine strand asymmetry, or AC/GT-strand asymmetry). It was found that point mutations in these regions preferentially degrade the nucleotide inhomogeneities, decreasing the sequence biases. Degradation of sequence bias is highest for novel mutations, and considerably lower for older mutations (those widespread across populations). Besides BGC, there may be additional, still uncharacterized molecular mechanisms that either preserve genomic regions with biased nucleotide compositions from mutational degradation or fail to degrade such inhomogeneities in specific chromosomal regions.
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9
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Bolívar P, Mugal CF, Rossi M, Nater A, Wang M, Dutoit L, Ellegren H. Biased Inference of Selection Due to GC-Biased Gene Conversion and the Rate of Protein Evolution in Flycatchers When Accounting for It. Mol Biol Evol 2019; 35:2475-2486. [PMID: 30085180 PMCID: PMC6188562 DOI: 10.1093/molbev/msy149] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
The rate of recombination impacts on rates of protein evolution for at least two reasons: it affects the efficacy of selection due to linkage and influences sequence evolution through the process of GC-biased gene conversion (gBGC). We studied how recombination, via gBGC, affects inferences of selection in gene sequences using comparative genomic and population genomic data from the collared flycatcher (Ficedula albicollis). We separately analyzed different mutation categories (“strong”-to-“weak,” “weak-to-strong,” and GC-conservative changes) and found that gBGC impacts on the distribution of fitness effects of new mutations, and leads to that the rate of adaptive evolution and the proportion of adaptive mutations among nonsynonymous substitutions are underestimated by 22–33%. It also biases inferences of demographic history based on the site frequency spectrum. In light of this impact, we suggest that inferences of selection (and demography) in lineages with pronounced gBGC should be based on GC-conservative changes only. Doing so, we estimate that 10% of nonsynonymous mutations are effectively neutral and that 27% of nonsynonymous substitutions have been fixed by positive selection in the flycatcher lineage. We also find that gene expression level, sex-bias in expression, and the number of protein–protein interactions, but not Hill–Robertson interference (HRI), are strong determinants of selective constraint and rate of adaptation of collared flycatcher genes. This study therefore illustrates the importance of disentangling the effects of different evolutionary forces and genetic factors in interpretation of sequence data, and from that infer the role of natural selection in DNA sequence evolution.
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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
| | - Matteo Rossi
- Department of Evolutionary Biology, Evolutionary Biology Centre, Uppsala University, Uppsala, Sweden.,Department of Biology II, Faculty of Biology, Ludwig-Maximilians-Universität München, Planegg-Martinsried, Germany
| | - Alexander Nater
- Department of Evolutionary Biology, Evolutionary Biology Centre, Uppsala University, Uppsala, Sweden.,Chair in Zoology and Evolutionary Biology, Department of Biology, University of Konstanz, Konstanz, Germany
| | - Mi Wang
- Department of Evolutionary Biology, Evolutionary Biology Centre, Uppsala University, Uppsala, Sweden
| | - Ludovic Dutoit
- 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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10
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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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11
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Bolívar P, Guéguen L, Duret L, Ellegren H, Mugal CF. GC-biased gene conversion conceals the prediction of the nearly neutral theory in avian genomes. Genome Biol 2019; 20:5. [PMID: 30616647 PMCID: PMC6322265 DOI: 10.1186/s13059-018-1613-z] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2018] [Accepted: 12/17/2018] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND The nearly neutral theory of molecular evolution predicts that the efficacy of natural selection increases with the effective population size. This prediction has been verified by independent observations in diverse taxa, which show that life-history traits are strongly correlated with measures of the efficacy of selection, such as the dN/dS ratio. Surprisingly, avian taxa are an exception to this theory because correlations between life-history traits and dN/dS are apparently absent. Here we explore the role of GC-biased gene conversion on estimates of substitution rates as a potential driver of these unexpected observations. RESULTS We analyze the relationship between dN/dS estimated from alignments of 47 avian genomes and several proxies for effective population size. To distinguish the impact of GC-biased gene conversion from selection, we use an approach that accounts for non-stationary base composition and estimate dN/dS separately for changes affected or unaffected by GC-biased gene conversion. This analysis shows that the impact of GC-biased gene conversion on substitution rates can explain the lack of correlations between life-history traits and dN/dS. Strong correlations between life-history traits and dN/dS are recovered after accounting for GC-biased gene conversion. The correlations are robust to variation in base composition and genomic location. CONCLUSIONS Our study shows that gene sequence evolution across a wide range of avian lineages meets the prediction of the nearly neutral theory, the efficacy of selection increases with effective population size. Moreover, our study illustrates that accounting for GC-biased gene conversion is important to correctly estimate the strength of selection.
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Affiliation(s)
- Paulina Bolívar
- Department of Ecology and Genetics, Uppsala University, Norbyvägen 18D, 75236 Uppsala, Sweden
| | - Laurent Guéguen
- Laboratoire de Biologie et Biométrie Évolutive CNRS UMR 5558, Université Claude Bernard Lyon 1, Lyon, France
| | - Laurent Duret
- Laboratoire de Biologie et Biométrie Évolutive CNRS UMR 5558, Université Claude Bernard Lyon 1, Lyon, France
| | - Hans Ellegren
- Department of Ecology and Genetics, Uppsala University, Norbyvägen 18D, 75236 Uppsala, Sweden
| | - Carina F. Mugal
- Department of Ecology and Genetics, Uppsala University, Norbyvägen 18D, 75236 Uppsala, Sweden
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12
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Corcoran P, Gossmann TI, Barton HJ, Slate J, Zeng K. Determinants of the Efficacy of Natural Selection on Coding and Noncoding Variability in Two Passerine Species. Genome Biol Evol 2018; 9:2987-3007. [PMID: 29045655 PMCID: PMC5714183 DOI: 10.1093/gbe/evx213] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/16/2017] [Indexed: 02/06/2023] Open
Abstract
Population genetic theory predicts that selection should be more effective when the effective population size (Ne) is larger, and that the efficacy of selection should correlate positively with recombination rate. Here, we analyzed the genomes of ten great tits and ten zebra finches. Nucleotide diversity at 4-fold degenerate sites indicates that zebra finches have a 2.83-fold larger Ne. We obtained clear evidence that purifying selection is more effective in zebra finches. The proportion of substitutions at 0-fold degenerate sites fixed by positive selection (α) is high in both species (great tit 48%; zebra finch 64%) and is significantly higher in zebra finches. When α was estimated on GC-conservative changes (i.e., between A and T and between G and C), the estimates reduced in both species (great tit 22%; zebra finch 53%). A theoretical model presented herein suggests that failing to control for the effects of GC-biased gene conversion (gBGC) is potentially a contributor to the overestimation of α, and that this effect cannot be alleviated by first fitting a demographic model to neutral variants. We present the first estimates in birds for α in the untranslated regions, and found evidence for substantial adaptive changes. Finally, although purifying selection is stronger in high-recombination regions, we obtained mixed evidence for α increasing with recombination rate, especially after accounting for gBGC. These results highlight that it is important to consider the potential confounding effects of gBGC when quantifying selection and that our understanding of what determines the efficacy of selection is incomplete.
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Affiliation(s)
- Pádraic Corcoran
- Department of Animal and Plant Sciences, University of Sheffield, South Yorkshire, United Kingdom
| | - Toni I Gossmann
- Department of Animal and Plant Sciences, University of Sheffield, South Yorkshire, United Kingdom
| | - Henry J Barton
- Department of Animal and Plant Sciences, University of Sheffield, South Yorkshire, United Kingdom
| | | | - Jon Slate
- Department of Animal and Plant Sciences, University of Sheffield, South Yorkshire, United Kingdom
| | - Kai Zeng
- Department of Animal and Plant Sciences, University of Sheffield, South Yorkshire, United Kingdom
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13
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Dutta R, Saha-Mandal A, Cheng X, Qiu S, Serpen J, Fedorova L, Fedorov A. 1000 human genomes carry widespread signatures of GC biased gene conversion. BMC Genomics 2018; 19:256. [PMID: 29661137 PMCID: PMC5902838 DOI: 10.1186/s12864-018-4593-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2017] [Accepted: 03/12/2018] [Indexed: 11/23/2022] Open
Abstract
BACKGROUND GC-Biased Gene Conversion (gBGC) is one of the important theories put forward to explain profound long-range non-randomness in nucleotide compositions along mammalian chromosomes. Nucleotide changes due to gBGC are hard to distinguish from regular mutations. Here, we present an algorithm for analysis of millions of known SNPs that detects a subset of so-called "SNP flip-over" events representing recent gBGC nucleotide changes, which occurred in previous generations via non-crossover meiotic recombination. RESULTS This algorithm has been applied in a large-scale analysis of 1092 sequenced human genomes. Altogether, 56,328 regions on all autosomes have been examined, which revealed 223,955 putative gBGC cases leading to SNP flip-overs. We detected a strong bias (11.7% ± 0.2% excess) in AT- > GC over GC- > AT base pair changes within the entire set of putative gBGC cases. CONCLUSIONS On average, a human gamete acquires 7 SNP flip-over events, in which one allele is replaced by its complementary allele during the process of meiotic non-crossover recombination. In each meiosis event, on average, gBGC results in replacement of 7 AT base pairs by GC base pairs, while only 6 GC pairs are replaced by AT pairs. Therefore, every human gamete is enriched by one GC pair. Happening over millions of years of evolution, this bias may be a noticeable force in changing the nucleotide composition landscape along chromosomes.
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Affiliation(s)
- Rajib Dutta
- Program in Biomedical Sciences, University of Toledo, Health Science Campus, Toledo, OH 43614 USA
- Department of Medicine, University of Toledo, Health Science Campus, Toledo, OH 43614 USA
- Present Address: Center for Cardiovascular and Pulmonary Research, Nationwide Children’s Hospital, 700 Children’s Dr, Columbus, OH USA
| | - Arnab Saha-Mandal
- Program in Bioinformatics and Proteomics/Genomics, University of Toledo, Health Science Campus, Toledo, OH 43614 USA
- Present Address: Biochemistry and Molecular Biology Graduate Program, Cumming School of Medicine, University of Calgary, Calgary, AB T2N4N1 Canada
| | - Xi Cheng
- Program in Biomedical Sciences, University of Toledo, Health Science Campus, Toledo, OH 43614 USA
| | - Shuhao Qiu
- Program in Biomedical Sciences, University of Toledo, Health Science Campus, Toledo, OH 43614 USA
- Department of Medicine, University of Toledo, Health Science Campus, Toledo, OH 43614 USA
| | - Jasmine Serpen
- SURF Program, University of Toledo, Health Science Campus, Toledo, OH 43614 USA
- College of Arts and Sciences, Washington University in St. Louis, 1 Brookings Dr, St. Louis, MO 63130 USA
| | | | - Alexei Fedorov
- Department of Medicine, University of Toledo, Health Science Campus, Toledo, OH 43614 USA
- Program in Bioinformatics and Proteomics/Genomics, University of Toledo, Health Science Campus, Toledo, OH 43614 USA
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14
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Kawakami T, Mugal CF, Suh A, Nater A, Burri R, Smeds L, Ellegren H. Whole-genome patterns of linkage disequilibrium across flycatcher populations clarify the causes and consequences of fine-scale recombination rate variation in birds. Mol Ecol 2017; 26:4158-4172. [DOI: 10.1111/mec.14197] [Citation(s) in RCA: 69] [Impact Index Per Article: 9.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2017] [Revised: 05/02/2017] [Accepted: 05/15/2017] [Indexed: 12/17/2022]
Affiliation(s)
- Takeshi Kawakami
- Department of Evolutionary Biology; Evolutionary Biology Centre (EBC); Uppsala University; Uppsala Sweden
- Department of Animal and Plant Sciences; University of Sheffield; Sheffield UK
| | - Carina F. Mugal
- Department of Evolutionary Biology; Evolutionary Biology Centre (EBC); Uppsala University; Uppsala Sweden
| | - Alexander Suh
- Department of Evolutionary Biology; Evolutionary Biology Centre (EBC); Uppsala University; Uppsala Sweden
| | - Alexander Nater
- Department of Evolutionary Biology; Evolutionary Biology Centre (EBC); Uppsala University; Uppsala Sweden
- Department of Evolutionary Biology and Environmental Studies; University of Zurich; Zürich Switzerland
| | - Reto Burri
- Department of Evolutionary Biology; Evolutionary Biology Centre (EBC); Uppsala University; Uppsala Sweden
- Department of Population Ecology; Friedrich Schiller University Jena; Jena Germany
| | - Linnéa Smeds
- Department of Evolutionary Biology; Evolutionary Biology Centre (EBC); Uppsala University; Uppsala Sweden
| | - Hans Ellegren
- Department of Evolutionary Biology; Evolutionary Biology Centre (EBC); Uppsala University; Uppsala Sweden
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15
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Dutoit L, Vijay N, Mugal CF, Bossu CM, Burri R, Wolf J, Ellegren H. Covariation in levels of nucleotide diversity in homologous regions of the avian genome long after completion of lineage sorting. Proc Biol Sci 2017; 284:20162756. [PMID: 28202815 PMCID: PMC5326536 DOI: 10.1098/rspb.2016.2756] [Citation(s) in RCA: 31] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2016] [Accepted: 01/18/2017] [Indexed: 12/30/2022] Open
Abstract
Closely related species may show similar levels of genetic diversity in homologous regions of the genome owing to shared ancestral variation still segregating in the extant species. However, after completion of lineage sorting, such covariation is not necessarily expected. On the other hand, if the processes that govern genetic diversity are conserved, diversity may potentially covary even among distantly related species. We mapped regions of conserved synteny between the genomes of two divergent bird species-collared flycatcher and hooded crow-and identified more than 600 Mb of homologous regions (66% of the genome). From analyses of whole-genome resequencing data in large population samples of both species we found nucleotide diversity in 200 kb windows to be well correlated (Spearman's ρ = 0.407). The correlation remained highly similar after excluding coding sequences. To explain this covariation, we suggest that a stable avian karyotype and a conserved landscape of recombination rate variation render the diversity-reducing effects of linked selection similar in divergent bird lineages. Principal component regression analysis of several potential explanatory variables driving heterogeneity in flycatcher diversity levels revealed the strongest effects from recombination rate variation and density of coding sequence targets for selection, consistent with linked selection. It is also possible that a stable karyotype is associated with a conserved genomic mutation environment contributing to covariation in diversity levels between lineages. Our observations imply that genetic diversity is to some extent predictable.
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Affiliation(s)
- Ludovic Dutoit
- Department of Evolutionary Biology, Evolutionary Biology Centre, Uppsala University, Norbyvägen 18D, 752 36 Uppsala, Sweden
| | - Nagarjun Vijay
- Department of Evolutionary Biology, Evolutionary Biology Centre, Uppsala University, Norbyvägen 18D, 752 36 Uppsala, Sweden
| | - Carina F Mugal
- Department of Evolutionary Biology, Evolutionary Biology Centre, Uppsala University, Norbyvägen 18D, 752 36 Uppsala, Sweden
| | - Christen M Bossu
- Department of Evolutionary Biology, Evolutionary Biology Centre, Uppsala University, Norbyvägen 18D, 752 36 Uppsala, Sweden
| | - Reto Burri
- Department of Evolutionary Biology, Evolutionary Biology Centre, Uppsala University, Norbyvägen 18D, 752 36 Uppsala, Sweden
| | - Jochen Wolf
- Department of Evolutionary Biology, Evolutionary Biology Centre, Uppsala University, Norbyvägen 18D, 752 36 Uppsala, Sweden
- Division of Evolutionary Biology, Faculty of Biology II, Ludwig-Maximilians-Universität München, Grosshaderner Strasse 2, 82152 Planegg-Martinsried, Germany
| | - Hans Ellegren
- Department of Evolutionary Biology, Evolutionary Biology Centre, Uppsala University, Norbyvägen 18D, 752 36 Uppsala, Sweden
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16
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Symonová R, Majtánová Z, Arias-Rodriguez L, Mořkovský L, Kořínková T, Cavin L, Pokorná MJ, Doležálková M, Flajšhans M, Normandeau E, Ráb P, Meyer A, Bernatchez L. Genome Compositional Organization in Gars Shows More Similarities to Mammals than to Other Ray-Finned Fish. JOURNAL OF EXPERIMENTAL ZOOLOGY PART B-MOLECULAR AND DEVELOPMENTAL EVOLUTION 2016; 328:607-619. [DOI: 10.1002/jez.b.22719] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/17/2016] [Revised: 11/13/2016] [Accepted: 11/22/2016] [Indexed: 12/12/2022]
Affiliation(s)
- Radka Symonová
- Laboratory of Fish Genetics; Institute of Animal Physiology and Genetics; The Czech Academy of Sciences; Liběchov Czech Republic
- Department of Zoology; Faculty of Science; Charles University; Prague 2 Czech Republic
- Research Institute for Limnology; University of Innsbruck; Mondsee Austria
| | - Zuzana Majtánová
- Laboratory of Fish Genetics; Institute of Animal Physiology and Genetics; The Czech Academy of Sciences; Liběchov Czech Republic
- Department of Zoology; Faculty of Science; Charles University; Prague 2 Czech Republic
| | - Lenin Arias-Rodriguez
- División Académica de Ciencias Biológicas; Universidad Juárez Autónoma de Tabasco (UJAT); Villahermosa Tabasco México
| | - Libor Mořkovský
- Department of Zoology; Faculty of Science; Charles University; Prague 2 Czech Republic
| | - Tereza Kořínková
- Laboratory of Fish Genetics; Institute of Animal Physiology and Genetics; The Czech Academy of Sciences; Liběchov Czech Republic
| | - Lionel Cavin
- Muséum d'Histoire Naturelle; Geneva 6 Switzerland
| | - Martina Johnson Pokorná
- Laboratory of Fish Genetics; Institute of Animal Physiology and Genetics; The Czech Academy of Sciences; Liběchov Czech Republic
- Department of Ecology; Faculty of Science; Charles University; Prague 2 Czech Republic
| | - Marie Doležálková
- Laboratory of Fish Genetics; Institute of Animal Physiology and Genetics; The Czech Academy of Sciences; Liběchov Czech Republic
- Department of Zoology; Faculty of Science; Charles University; Prague 2 Czech Republic
| | - Martin Flajšhans
- Faculty of Fisheries and Protection of Waters; South Bohemian Research Centre of Aquaculture and Biodiversity of Hydrocenoses; University of South Bohemia in České Budějovice; Vodňany Czech Republic
| | - Eric Normandeau
- IBIS, Department of Biology, University Laval, Pavillon Charles-Eugène-Marchand; Avenue de la Médecine Quebec City; Canada
| | - Petr Ráb
- Laboratory of Fish Genetics; Institute of Animal Physiology and Genetics; The Czech Academy of Sciences; Liběchov Czech Republic
| | - Axel Meyer
- Chair in Zoology and Evolutionary Biology; Department of Biology; University of Konstanz; Konstanz Germany
| | - Louis Bernatchez
- IBIS, Department of Biology, University Laval, Pavillon Charles-Eugène-Marchand; Avenue de la Médecine Quebec City; Canada
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17
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Vijay N, Bossu CM, Poelstra JW, Weissensteiner MH, Suh A, Kryukov AP, Wolf JBW. Evolution of heterogeneous genome differentiation across multiple contact zones in a crow species complex. Nat Commun 2016; 7:13195. [PMID: 27796282 PMCID: PMC5095515 DOI: 10.1038/ncomms13195] [Citation(s) in RCA: 119] [Impact Index Per Article: 14.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2016] [Accepted: 09/09/2016] [Indexed: 12/31/2022] Open
Abstract
Uncovering the genetic basis of species diversification is a central goal in evolutionary biology. Yet, the link between the accumulation of genomic changes during population divergence and the evolutionary forces promoting reproductive isolation is poorly understood. Here, we analysed 124 genomes of crow populations with various degrees of genome-wide differentiation, with parallelism of a sexually selected plumage phenotype, and ongoing hybridization. Overall, heterogeneity in genetic differentiation along the genome was best explained by linked selection exposed on a shared genome architecture. Superimposed on this common background, we identified genomic regions with signatures of selection specific to independent phenotypic contact zones. Candidate pigmentation genes with evidence for divergent selection were only partly shared, suggesting context-dependent selection on a multigenic trait architecture and parallelism by pathway rather than by repeated single-gene effects. This study provides insight into how various forms of selection shape genome-wide patterns of genomic differentiation as populations diverge.
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Affiliation(s)
- Nagarjun Vijay
- Department of Evolutionary Biology and Science for Life Laboratories, Uppsala University, Norbyvägen 18D, Uppsala 75236, Sweden
| | - Christen M Bossu
- Department of Evolutionary Biology and Science for Life Laboratories, Uppsala University, Norbyvägen 18D, Uppsala 75236, Sweden.,Department of Zoology, Population Genetics, Stockholm University, Stockholm SE-106 91, Sweden
| | - Jelmer W Poelstra
- Department of Evolutionary Biology and Science for Life Laboratories, Uppsala University, Norbyvägen 18D, Uppsala 75236, Sweden
| | - Matthias H Weissensteiner
- Department of Evolutionary Biology and Science for Life Laboratories, Uppsala University, Norbyvägen 18D, Uppsala 75236, Sweden
| | - Alexander Suh
- Department of Evolutionary Biology and Science for Life Laboratories, Uppsala University, Norbyvägen 18D, Uppsala 75236, Sweden
| | - Alexey P Kryukov
- Laboratory of Evolutionary Zoology and Genetics, Institute of Biology and Soil Science, Far East Branch Russian Academy of Sciences, Vladivostok 690022, Russia
| | - Jochen B W Wolf
- Department of Evolutionary Biology and Science for Life Laboratories, Uppsala University, Norbyvägen 18D, Uppsala 75236, Sweden.,Division of Evolutionary Biology, Ludwig Maximilian University of Munich, Grosshaderner Street 2, Planegg-Martinsried 82152, Germany
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18
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Smeds L, Mugal CF, Qvarnström A, Ellegren H. High-Resolution Mapping of Crossover and Non-crossover Recombination Events by Whole-Genome Re-sequencing of an Avian Pedigree. PLoS Genet 2016; 12:e1006044. [PMID: 27219623 PMCID: PMC4878770 DOI: 10.1371/journal.pgen.1006044] [Citation(s) in RCA: 54] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2015] [Accepted: 04/19/2016] [Indexed: 01/04/2023] Open
Abstract
Recombination is an engine of genetic diversity and therefore constitutes a key process in evolutionary biology and genetics. While the outcome of crossover recombination can readily be detected as shuffled alleles by following the inheritance of markers in pedigreed families, the more precise location of both crossover and non-crossover recombination events has been difficult to pinpoint. As a consequence, we lack a detailed portrait of the recombination landscape for most organisms and knowledge on how this landscape impacts on sequence evolution at a local scale. To localize recombination events with high resolution in an avian system, we performed whole-genome re-sequencing at high coverage of a complete three-generation collared flycatcher pedigree. We identified 325 crossovers at a median resolution of 1.4 kb, with 86% of the events localized to <10 kb intervals. Observed crossover rates were in excellent agreement with data from linkage mapping, were 52% higher in male (3.56 cM/Mb) than in female meiosis (2.28 cM/Mb), and increased towards chromosome ends in male but not female meiosis. Crossover events were non-randomly distributed in the genome with several distinct hot-spots and a concentration to genic regions, with the highest density in promoters and CpG islands. We further identified 267 non-crossovers, whose location was significantly associated with crossover locations. We detected a significant transmission bias (0.18) in favour of 'strong' (G, C) over 'weak' (A, T) alleles at non-crossover events, providing direct evidence for the process of GC-biased gene conversion in an avian system. The approach taken in this study should be applicable to any species and would thereby help to provide a more comprehensive portray of the recombination landscape across organism groups.
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Affiliation(s)
- Linnéa Smeds
- 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
| | - Anna Qvarnström
- Department of Animal Ecology, Evolutionary Biology Centre, Uppsala University, Uppsala, Sweden
| | - Hans Ellegren
- Department of Evolutionary Biology, Evolutionary Biology Centre, Uppsala University, Uppsala, Sweden
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19
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Singhal S, Leffler EM, Sannareddy K, Turner I, Venn O, Hooper DM, Strand AI, Li Q, Raney B, Balakrishnan CN, Griffith SC, McVean G, Przeworski M. Stable recombination hotspots in birds. Science 2015; 350:928-32. [PMID: 26586757 PMCID: PMC4864528 DOI: 10.1126/science.aad0843] [Citation(s) in RCA: 198] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
The DNA-binding protein PRDM9 has a critical role in specifying meiotic recombination hotspots in mice and apes, but it appears to be absent from other vertebrate species, including birds. To study the evolution and determinants of recombination in species lacking the gene that encodes PRDM9, we inferred fine-scale genetic maps from population resequencing data for two bird species: the zebra finch, Taeniopygia guttata, and the long-tailed finch, Poephila acuticauda. We found that both species have recombination hotspots, which are enriched near functional genomic elements. Unlike in mice and apes, most hotspots are shared between the two species, and their conservation seems to extend over tens of millions of years. These observations suggest that in the absence of PRDM9, recombination targets functional features that both enable access to the genome and constrain its evolution.
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Affiliation(s)
- Sonal Singhal
- Department of Biological Sciences, Columbia University, New York, NY 10027, USA. Department of Systems Biology, Columbia University, New York, NY 10032, USA.
| | - Ellen M Leffler
- Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA. Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
| | - Keerthi Sannareddy
- Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA
| | - Isaac Turner
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
| | - Oliver Venn
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
| | - Daniel M Hooper
- Committee on Evolutionary Biology, University of Chicago, Chicago, IL 60637, USA
| | - Alva I Strand
- Department of Biological Sciences, Columbia University, New York, NY 10027, USA
| | - Qiye Li
- China National Genebank, BGI-Shenzhen, Shenzhen 518083, China
| | - Brian Raney
- Center for Biomolecular Science and Engineering, University of California-Santa Cruz, Santa Cruz, CA 95064, USA
| | | | - Simon C Griffith
- Department of Biological Sciences, Macquarie University, Sydney, NSW 2109, Australia
| | - Gil McVean
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
| | - Molly Przeworski
- Department of Biological Sciences, Columbia University, New York, NY 10027, USA. Department of Systems Biology, Columbia University, New York, NY 10032, USA.
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20
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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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21
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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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22
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Weber CC, Nabholz B, Romiguier J, Ellegren H. Kr/Kc but not dN/dS correlates positively with body mass in birds, raising implications for inferring lineage-specific selection. Genome Biol 2015; 15:542. [PMID: 25607475 PMCID: PMC4264323 DOI: 10.1186/s13059-014-0542-8] [Citation(s) in RCA: 46] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2014] [Accepted: 11/13/2014] [Indexed: 02/02/2023] Open
Abstract
Background The ratio of the rates of non-synonymous and synonymous substitution (dN/dS) is commonly used to estimate selection in coding sequences. It is often suggested that, all else being equal, dN/dS should be lower in populations with large effective size (Ne) due to increased efficacy of purifying selection. As Ne is difficult to measure directly, life history traits such as body mass, which is typically negatively associated with population size, have commonly been used as proxies in empirical tests of this hypothesis. However, evidence of whether the expected positive correlation between body mass and dN/dS is consistently observed is conflicting. Results Employing whole genome sequence data from 48 avian species, we assess the relationship between rates of molecular evolution and life history in birds. We find a negative correlation between dN/dS and body mass, contrary to nearly neutral expectation. This raises the question whether the correlation might be a method artefact. We therefore in turn consider non-stationary base composition, divergence time and saturation as possible explanations, but find no clear patterns. However, in striking contrast to dN/dS, the ratio of radical to conservative amino acid substitutions (Kr/Kc) correlates positively with body mass. Conclusions Our results in principle accord with the notion that non-synonymous substitutions causing radical amino acid changes are more efficiently removed by selection in large populations, consistent with nearly neutral theory. These findings have implications for the use of dN/dS and suggest that caution is warranted when drawing conclusions about lineage-specific modes of protein evolution using this metric. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0542-8) contains supplementary material, which is available to authorized users.
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Gossmann TI, Santure AW, Sheldon BC, Slate J, Zeng K. Highly variable recombinational landscape modulates efficacy of natural selection in birds. Genome Biol Evol 2015; 6:2061-75. [PMID: 25062920 PMCID: PMC4231635 DOI: 10.1093/gbe/evu157] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022] Open
Abstract
Determining the rate of protein evolution and identifying the causes of its variation across the genome are powerful ways to understand forces that are important for genome evolution. By using a multitissue transcriptome data set from great tit (Parus major), we analyzed patterns of molecular evolution between two passerine birds, great tit and zebra finch (Taeniopygia guttata), using the chicken genome (Gallus gallus) as an outgroup. We investigated whether a special feature of avian genomes, the highly variable recombinational landscape, modulates the efficacy of natural selection through the effects of Hill-Robertson interference, which predicts that selection should be more effective in removing deleterious mutations and incorporating beneficial mutations in high-recombination regions than in low-recombination regions. In agreement with these predictions, genes located in low-recombination regions tend to have a high proportion of neutrally evolving sites and relaxed selective constraint on sites subject to purifying selection, whereas genes that show strong support for past episodes of positive selection appear disproportionally in high-recombination regions. There is also evidence that genes located in high-recombination regions tend to have higher gene expression specificity than those located in low-recombination regions. Furthermore, more compact genes (i.e., those with fewer/shorter introns or shorter proteins) evolve faster than less compact ones. In sum, our results demonstrate that transcriptome sequencing is a powerful method to answer fundamental questions about genome evolution in nonmodel organisms.
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Affiliation(s)
- Toni I Gossmann
- Department of Animal and Plant Sciences, University of Sheffield, United Kingdom
| | - Anna W Santure
- Department of Animal and Plant Sciences, University of Sheffield, United KingdomSchool of Biological Sciences, University of Auckland, New Zealand
| | - Ben C Sheldon
- Edward Grey Institute, Department of Zoology, University of Oxford, United Kingdom
| | - Jon Slate
- Department of Animal and Plant Sciences, University of Sheffield, United Kingdom
| | - Kai Zeng
- Department of Animal and Plant Sciences, University of Sheffield, United Kingdom
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24
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Evolutionary consequences of DNA methylation on the GC content in vertebrate genomes. G3-GENES GENOMES GENETICS 2015; 5:441-7. [PMID: 25591920 PMCID: PMC4349097 DOI: 10.1534/g3.114.015545] [Citation(s) in RCA: 42] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
The genomes of many vertebrates show a characteristic variation in GC content. To explain its origin and evolution, mainly three mechanisms have been proposed: selection for GC content, mutation bias, and GC-biased gene conversion. At present, the mechanism of GC-biased gene conversion, i.e., short-scale, unidirectional exchanges between homologous chromosomes in the neighborhood of recombination-initiating double-strand breaks in favor for GC nucleotides, is the most widely accepted hypothesis. We here suggest that DNA methylation also plays an important role in the evolution of GC content in vertebrate genomes. To test this hypothesis, we investigated one mammalian (human) and one avian (chicken) genome. We used bisulfite sequencing to generate a whole-genome methylation map of chicken sperm and made use of a publicly available whole-genome methylation map of human sperm. Inclusion of these methylation maps into a model of GC content evolution provided significant support for the impact of DNA methylation on the local equilibrium GC content. Moreover, two different estimates of equilibrium GC content, one that neglects and one that incorporates the impact of DNA methylation and the concomitant CpG hypermutability, give estimates that differ by approximately 15% in both genomes, arguing for a strong impact of DNA methylation on the evolution of GC content. Thus, our results put forward that previous estimates of equilibrium GC content, which neglect the hypermutability of CpG dinucleotides, need to be reevaluated.
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25
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Figuet E, Ballenghien M, Romiguier J, Galtier N. Biased gene conversion and GC-content evolution in the coding sequences of reptiles and vertebrates. Genome Biol Evol 2014; 7:240-50. [PMID: 25527834 PMCID: PMC4316630 DOI: 10.1093/gbe/evu277] [Citation(s) in RCA: 48] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
Mammalian and avian genomes are characterized by a substantial spatial heterogeneity of GC-content, which is often interpreted as reflecting the effect of local GC-biased gene conversion (gBGC), a meiotic repair bias that favors G and C over A and T alleles in high-recombining genomic regions. Surprisingly, the first fully sequenced nonavian sauropsid (i.e., reptile), the green anole Anolis carolinensis, revealed a highly homogeneous genomic GC-content landscape, suggesting the possibility that gBGC might not be at work in this lineage. Here, we analyze GC-content evolution at third-codon positions (GC3) in 44 vertebrates species, including eight newly sequenced transcriptomes, with a specific focus on nonavian sauropsids. We report that reptiles, including the green anole, have a genome-wide distribution of GC3 similar to that of mammals and birds, and we infer a strong GC3-heterogeneity to be already present in the tetrapod ancestor. We further show that the dynamic of coding sequence GC-content is largely governed by karyotypic features in vertebrates, notably in the green anole, in agreement with the gBGC hypothesis. The discrepancy between third-codon positions and noncoding DNA regarding GC-content dynamics in the green anole could not be explained by the activity of transposable elements or selection on codon usage. This analysis highlights the unique value of third-codon positions as an insertion/deletion-free marker of nucleotide substitution biases that ultimately affect the evolution of proteins.
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Affiliation(s)
- Emeric Figuet
- CNRS, Université Montpellier 2, UMR 5554, Institut des Sciences de l'Evolution de Montpellier, France
| | - Marion Ballenghien
- CNRS, Université Montpellier 2, UMR 5554, Institut des Sciences de l'Evolution de Montpellier, France
| | - Jonathan Romiguier
- CNRS, Université Montpellier 2, UMR 5554, Institut des Sciences de l'Evolution de Montpellier, France Department of Ecology and Evolution, Biophore, University of Lausanne, Switzerland
| | - Nicolas Galtier
- CNRS, Université Montpellier 2, UMR 5554, Institut des Sciences de l'Evolution de Montpellier, France
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26
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Jarvis ED, Mirarab S, Aberer AJ, Li B, Houde P, Li C, Ho SYW, Faircloth BC, Nabholz B, Howard JT, Suh A, Weber CC, da Fonseca RR, Li J, Zhang F, Li H, Zhou L, Narula N, Liu L, Ganapathy G, Boussau B, Bayzid MS, Zavidovych V, Subramanian S, Gabaldón T, Capella-Gutiérrez S, Huerta-Cepas J, Rekepalli B, Munch K, Schierup M, Lindow B, Warren WC, Ray D, Green RE, Bruford MW, Zhan X, Dixon A, Li S, Li N, Huang Y, Derryberry EP, Bertelsen MF, Sheldon FH, Brumfield RT, Mello CV, Lovell PV, Wirthlin M, Schneider MPC, Prosdocimi F, Samaniego JA, Vargas Velazquez AM, Alfaro-Núñez A, Campos PF, Petersen B, Sicheritz-Ponten T, Pas A, Bailey T, Scofield P, Bunce M, Lambert DM, Zhou Q, Perelman P, Driskell AC, Shapiro B, Xiong Z, Zeng Y, Liu S, Li Z, Liu B, Wu K, Xiao J, Yinqi X, Zheng Q, Zhang Y, Yang H, Wang J, Smeds L, Rheindt FE, Braun M, Fjeldsa J, Orlando L, Barker FK, Jønsson KA, Johnson W, Koepfli KP, O'Brien S, Haussler D, Ryder OA, Rahbek C, Willerslev E, Graves GR, Glenn TC, McCormack J, Burt D, Ellegren H, Alström P, Edwards SV, Stamatakis A, Mindell DP, Cracraft J, Braun EL, Warnow T, Jun W, Gilbert MTP, Zhang G. Whole-genome analyses resolve early branches in the tree of life of modern birds. Science 2014; 346:1320-31. [PMID: 25504713 PMCID: PMC4405904 DOI: 10.1126/science.1253451] [Citation(s) in RCA: 1124] [Impact Index Per Article: 112.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
To better determine the history of modern birds, we performed a genome-scale phylogenetic analysis of 48 species representing all orders of Neoaves using phylogenomic methods created to handle genome-scale data. We recovered a highly resolved tree that confirms previously controversial sister or close relationships. We identified the first divergence in Neoaves, two groups we named Passerea and Columbea, representing independent lineages of diverse and convergently evolved land and water bird species. Among Passerea, we infer the common ancestor of core landbirds to have been an apex predator and confirm independent gains of vocal learning. Among Columbea, we identify pigeons and flamingoes as belonging to sister clades. Even with whole genomes, some of the earliest branches in Neoaves proved challenging to resolve, which was best explained by massive protein-coding sequence convergence and high levels of incomplete lineage sorting that occurred during a rapid radiation after the Cretaceous-Paleogene mass extinction event about 66 million years ago.
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Affiliation(s)
- Erich D Jarvis
- Department of Neurobiology, Howard Hughes Medical Institute (HHMI), and Duke University Medical Center, Durham, NC 27710, USA.
| | - Siavash Mirarab
- Department of Computer Science, The University of Texas at Austin, Austin, TX 78712, USA
| | - Andre J Aberer
- Scientific Computing Group, Heidelberg Institute for Theoretical Studies, Heidelberg, Germany
| | - Bo Li
- China National GeneBank, BGI-Shenzhen, Shenzhen 518083, China. College of Medicine and Forensics, Xi'an Jiaotong University Xi'an 710061, China. Centre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, Øster Voldgade 5-7, 1350 Copenhagen, Denmark
| | - Peter Houde
- Department of Biology, New Mexico State University, Las Cruces, NM 88003, USA
| | - Cai Li
- China National GeneBank, BGI-Shenzhen, Shenzhen 518083, China. Centre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, Øster Voldgade 5-7, 1350 Copenhagen, Denmark
| | - Simon Y W Ho
- School of Biological Sciences, University of Sydney, Sydney, New South Wales 2006, Australia
| | - Brant C Faircloth
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, CA 90095, USA. Department of Biological Sciences, Louisiana State University, Baton Rouge, LA 70803, USA
| | - Benoit Nabholz
- CNRS UMR 5554, Institut des Sciences de l'Evolution de Montpellier, Université Montpellier II Montpellier, France
| | - Jason T Howard
- Department of Neurobiology, Howard Hughes Medical Institute (HHMI), and Duke University Medical Center, Durham, NC 27710, USA
| | - Alexander Suh
- Department of Evolutionary Biology, Evolutionary Biology Centre, Uppsala University, SE-752 36 Uppsala Sweden
| | - Claudia C Weber
- Department of Evolutionary Biology, Evolutionary Biology Centre, Uppsala University, SE-752 36 Uppsala Sweden
| | - Rute R da Fonseca
- Centre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, Øster Voldgade 5-7, 1350 Copenhagen, Denmark
| | - Jianwen Li
- China National GeneBank, BGI-Shenzhen, Shenzhen 518083, China
| | - Fang Zhang
- China National GeneBank, BGI-Shenzhen, Shenzhen 518083, China
| | - Hui Li
- China National GeneBank, BGI-Shenzhen, Shenzhen 518083, China
| | - Long Zhou
- China National GeneBank, BGI-Shenzhen, Shenzhen 518083, China
| | - Nitish Narula
- Department of Biology, New Mexico State University, Las Cruces, NM 88003, USA. Biodiversity and Biocomplexity Unit, Okinawa Institute of Science and Technology Onna-son, Okinawa 904-0495, Japan
| | - Liang Liu
- Department of Statistics and Institute of Bioinformatics, University of Georgia, Athens, GA 30602, USA
| | - Ganesh Ganapathy
- Department of Neurobiology, Howard Hughes Medical Institute (HHMI), and Duke University Medical Center, Durham, NC 27710, USA
| | - Bastien Boussau
- Laboratoire de Biométrie et Biologie Evolutive, Centre National de la Recherche Scientifique, Université de Lyon, F-69622 Villeurbanne, France
| | - Md Shamsuzzoha Bayzid
- Department of Computer Science, The University of Texas at Austin, Austin, TX 78712, USA
| | - Volodymyr Zavidovych
- Department of Neurobiology, Howard Hughes Medical Institute (HHMI), and Duke University Medical Center, Durham, NC 27710, USA
| | - Sankar Subramanian
- Environmental Futures Research Institute, Griffith University, Nathan, Queensland 4111, Australia
| | - Toni Gabaldón
- Bioinformatics and Genomics Programme, Centre for Genomic Regulation, Dr. Aiguader 88, 08003 Barcelona, Spain. Universitat Pompeu Fabra, Barcelona, Spain. Institució Catalana de Recerca i Estudis Avançats, Barcelona, Spain
| | - Salvador Capella-Gutiérrez
- Bioinformatics and Genomics Programme, Centre for Genomic Regulation, Dr. Aiguader 88, 08003 Barcelona, Spain. Universitat Pompeu Fabra, Barcelona, Spain
| | - Jaime Huerta-Cepas
- Bioinformatics and Genomics Programme, Centre for Genomic Regulation, Dr. Aiguader 88, 08003 Barcelona, Spain. Universitat Pompeu Fabra, Barcelona, Spain
| | - Bhanu Rekepalli
- Joint Institute for Computational Sciences, The University of Tennessee, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
| | - Kasper Munch
- Bioinformatics Research Centre, Aarhus University, DK-8000 Aarhus C, Denmark
| | - Mikkel Schierup
- Bioinformatics Research Centre, Aarhus University, DK-8000 Aarhus C, Denmark
| | - Bent Lindow
- Centre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, Øster Voldgade 5-7, 1350 Copenhagen, Denmark
| | - Wesley C Warren
- The Genome Institute, Washington University School of Medicine, St Louis, MI 63108, USA
| | - David Ray
- Department of Biochemistry, Molecular Biology, Entomology and Plant Pathology, Mississippi State University, Mississippi State, MS 39762, USA. Institute for Genomics, Biocomputing and Biotechnology, Mississippi State University, Mississippi State, MS 39762, USA. Department of Biological Sciences, Texas Tech University, Lubbock, TX 79409, USA
| | - Richard E Green
- Department of Ecology and Evolutionary Biology, University of California Santa Cruz (UCSC), Santa Cruz, CA 95064, USA
| | - Michael W Bruford
- Organisms and Environment Division, Cardiff School of Biosciences, Cardiff University Cardiff CF10 3AX, Wales, UK
| | - Xiangjiang Zhan
- Organisms and Environment Division, Cardiff School of Biosciences, Cardiff University Cardiff CF10 3AX, Wales, UK. Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
| | - Andrew Dixon
- International Wildlife Consultants, Carmarthen SA33 5YL, Wales, UK
| | - Shengbin Li
- College of Medicine and Forensics, Xi'an Jiaotong University Xi'an, 710061, China
| | - Ning Li
- State Key Laboratory for Agrobiotechnology, China Agricultural University, Beijing 100094, China
| | - Yinhua Huang
- State Key Laboratory for Agrobiotechnology, China Agricultural University, Beijing 100094, China
| | - Elizabeth P Derryberry
- Department of Ecology and Evolutionary Biology, Tulane University, New Orleans, LA 70118, USA. Museum of Natural Science and Department of Biological Sciences, Louisiana State University, Baton Rouge, LA 70803, USA
| | - Mads Frost Bertelsen
- Center for Zoo and Wild Animal Health, Copenhagen Zoo Roskildevej 38, DK-2000 Frederiksberg, Denmark
| | - Frederick H Sheldon
- Museum of Natural Science and Department of Biological Sciences, Louisiana State University, Baton Rouge, LA 70803, USA
| | - Robb T Brumfield
- Museum of Natural Science and Department of Biological Sciences, Louisiana State University, Baton Rouge, LA 70803, USA
| | - Claudio V Mello
- Department of Behavioral Neuroscience, Oregon Health and Science University, Portland, OR 97239, USA. Brazilian Avian Genome Consortium (CNPq/FAPESPA-SISBIO Aves), Federal University of Para, Belem, Para, Brazil
| | - Peter V Lovell
- Department of Behavioral Neuroscience, Oregon Health and Science University, Portland, OR 97239, USA
| | - Morgan Wirthlin
- Department of Behavioral Neuroscience, Oregon Health and Science University, Portland, OR 97239, USA
| | - Maria Paula Cruz Schneider
- Brazilian Avian Genome Consortium (CNPq/FAPESPA-SISBIO Aves), Federal University of Para, Belem, Para, Brazil. Institute of Biological Sciences, Federal University of Para, Belem, Para, Brazil
| | - Francisco Prosdocimi
- Brazilian Avian Genome Consortium (CNPq/FAPESPA-SISBIO Aves), Federal University of Para, Belem, Para, Brazil. Institute of Medical Biochemistry Leopoldo de Meis, Federal University of Rio de Janeiro, Rio de Janeiro RJ 21941-902, Brazil
| | - José Alfredo Samaniego
- Centre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, Øster Voldgade 5-7, 1350 Copenhagen, Denmark
| | - Amhed Missael Vargas Velazquez
- Centre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, Øster Voldgade 5-7, 1350 Copenhagen, Denmark
| | - Alonzo Alfaro-Núñez
- Centre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, Øster Voldgade 5-7, 1350 Copenhagen, Denmark
| | - Paula F Campos
- Centre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, Øster Voldgade 5-7, 1350 Copenhagen, Denmark
| | - Bent Petersen
- Centre for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark Kemitorvet 208, 2800 Kgs Lyngby, Denmark
| | - Thomas Sicheritz-Ponten
- Centre for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark Kemitorvet 208, 2800 Kgs Lyngby, Denmark
| | - An Pas
- Breeding Centre for Endangered Arabian Wildlife, Sharjah, United Arab Emirates
| | - Tom Bailey
- Dubai Falcon Hospital, Dubai, United Arab Emirates
| | - Paul Scofield
- Canterbury Museum Rolleston Avenue, Christchurch 8050, New Zealand
| | - Michael Bunce
- Trace and Environmental DNA Laboratory Department of Environment and Agriculture, Curtin University, Perth, Western Australia 6102, Australia
| | - David M Lambert
- Environmental Futures Research Institute, Griffith University, Nathan, Queensland 4111, Australia
| | - Qi Zhou
- Department of Integrative Biology, University of California, Berkeley, CA 94720, USA
| | - Polina Perelman
- Laboratory of Genomic Diversity, National Cancer Institute Frederick, MD 21702, USA. Institute of Molecular and Cellular Biology, SB RAS and Novosibirsk State University, Novosibirsk, Russia
| | - Amy C Driskell
- Smithsonian Institution National Museum of Natural History, Washington, DC 20013, USA
| | - Beth Shapiro
- Department of Ecology and Evolutionary Biology, University of California Santa Cruz (UCSC), Santa Cruz, CA 95064, USA
| | - Zijun Xiong
- China National GeneBank, BGI-Shenzhen, Shenzhen 518083, China
| | - Yongli Zeng
- China National GeneBank, BGI-Shenzhen, Shenzhen 518083, China
| | - Shiping Liu
- China National GeneBank, BGI-Shenzhen, Shenzhen 518083, China
| | - Zhenyu Li
- China National GeneBank, BGI-Shenzhen, Shenzhen 518083, China
| | - Binghang Liu
- China National GeneBank, BGI-Shenzhen, Shenzhen 518083, China
| | - Kui Wu
- China National GeneBank, BGI-Shenzhen, Shenzhen 518083, China
| | - Jin Xiao
- China National GeneBank, BGI-Shenzhen, Shenzhen 518083, China
| | - Xiong Yinqi
- China National GeneBank, BGI-Shenzhen, Shenzhen 518083, China
| | - Qiuemei Zheng
- China National GeneBank, BGI-Shenzhen, Shenzhen 518083, China
| | - Yong Zhang
- China National GeneBank, BGI-Shenzhen, Shenzhen 518083, China
| | | | - Jian Wang
- BGI-Shenzhen, Shenzhen 518083, China
| | - Linnea Smeds
- Department of Evolutionary Biology, Evolutionary Biology Centre, Uppsala University, SE-752 36 Uppsala Sweden
| | - Frank E Rheindt
- Department of Biological Sciences, National University of Singapore, Republic of Singapore
| | - Michael Braun
- Department of Vertebrate Zoology, National Museum of Natural History, Smithsonian Suitland, MD 20746, USA
| | - Jon Fjeldsa
- Center for Macroecology, Evolution and Climate, Natural History Museum of Denmark, University of Copenhagen, Universitetsparken 15, DK-2100 Copenhagen Ø, Denmark
| | - Ludovic Orlando
- Centre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, Øster Voldgade 5-7, 1350 Copenhagen, Denmark
| | - F Keith Barker
- Bell Museum of Natural History, University of Minnesota, Saint Paul, MN 55108, USA
| | - Knud Andreas Jønsson
- Center for Macroecology, Evolution and Climate, Natural History Museum of Denmark, University of Copenhagen, Universitetsparken 15, DK-2100 Copenhagen Ø, Denmark. Department of Life Sciences, Natural History Museum, Cromwell Road, London SW7 5BD, UK. Department of Life Sciences, Imperial College London, Silwood Park Campus, Ascot SL5 7PY, UK
| | - Warren Johnson
- Smithsonian Conservation Biology Institute, National Zoological Park, Front Royal, VA 22630, USA
| | - Klaus-Peter Koepfli
- Smithsonian Conservation Biology Institute, National Zoological Park, Washington, DC 20008, USA
| | - Stephen O'Brien
- Theodosius Dobzhansky Center for Genome Bioinformatics, St. Petersburg State University, St. Petersburg, Russia 199004. Oceanographic Center, Nova Southeastern University, Ft Lauderdale, FL 33004, USA
| | - David Haussler
- Center for Biomolecular Science and Engineering, UCSC, Santa Cruz, CA 95064, USA
| | - Oliver A Ryder
- San Diego Zoo Institute for Conservation Research, Escondido, CA 92027, USA
| | - Carsten Rahbek
- Center for Macroecology, Evolution and Climate, Natural History Museum of Denmark, University of Copenhagen, Universitetsparken 15, DK-2100 Copenhagen Ø, Denmark. Department of Life Sciences, Imperial College London, Silwood Park Campus, Ascot SL5 7PY, UK
| | - Eske Willerslev
- Centre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, Øster Voldgade 5-7, 1350 Copenhagen, Denmark
| | - Gary R Graves
- Center for Macroecology, Evolution and Climate, Natural History Museum of Denmark, University of Copenhagen, Universitetsparken 15, DK-2100 Copenhagen Ø, Denmark. Department of Vertebrate Zoology, MRC-116, National Museum of Natural History, Smithsonian Institution, Washington, DC 20013, USA
| | - Travis C Glenn
- Department of Environmental Health Science, University of Georgia, Athens, GA 30602, USA
| | - John McCormack
- Moore Laboratory of Zoology and Department of Biology, Occidental College, Los Angeles, CA 90041, USA
| | - Dave Burt
- Department of Genomics and Genetics, The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush Campus, Midlothian EH25 9RG, UK
| | - Hans Ellegren
- Department of Evolutionary Biology, Evolutionary Biology Centre, Uppsala University, SE-752 36 Uppsala Sweden
| | - Per Alström
- Swedish Species Information Centre, Swedish University of Agricultural Sciences Box 7007, SE-750 07 Uppsala, Sweden. Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
| | - Scott V Edwards
- Department of Organismic and Evolutionary Biology and Museum of Comparative Zoology, Harvard University, Cambridge, MA 02138, USA
| | - Alexandros Stamatakis
- Scientific Computing Group, Heidelberg Institute for Theoretical Studies, Heidelberg, Germany. Institute of Theoretical Informatics, Department of Informatics, Karlsruhe Institute of Technology, D- 76131 Karlsruhe, Germany
| | - David P Mindell
- Department of Biochemistry and Biophysics, University of California, San Francisco, CA 94158, USA
| | - Joel Cracraft
- Department of Ornithology, American Museum of Natural History, New York, NY 10024, USA
| | - Edward L Braun
- Department of Biology and Genetics Institute, University of Florida, Gainesville, FL 32611, USA
| | - Tandy Warnow
- Department of Computer Science, The University of Texas at Austin, Austin, TX 78712, USA. Departments of Bioengineering and Computer Science, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA.
| | - Wang Jun
- BGI-Shenzhen, Shenzhen 518083, China. Department of Biology, University of Copenhagen, Ole Maaløes Vej 5, 2200 Copenhagen, Denmark. Princess Al Jawhara Center of Excellence in the Research of Hereditary Disorders, King Abdulaziz University, Jeddah 21589, Saudi Arabia. Macau University of Science and Technology, Avenida Wai long, Taipa, Macau 999078, China. Department of Medicine, University of Hong Kong, Hong Kong.
| | - M Thomas P Gilbert
- Centre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, Øster Voldgade 5-7, 1350 Copenhagen, Denmark. Trace and Environmental DNA Laboratory Department of Environment and Agriculture, Curtin University, Perth, Western Australia 6102, Australia.
| | - Guojie Zhang
- China National GeneBank, BGI-Shenzhen, Shenzhen 518083, China. Centre for Social Evolution, Department of Biology, Universitetsparken 15, University of Copenhagen, DK-2100 Copenhagen, Denmark.
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27
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Smeds L, Kawakami T, Burri R, Bolivar P, Husby A, Qvarnström A, Uebbing S, Ellegren H. Genomic identification and characterization of the pseudoautosomal region in highly differentiated avian sex chromosomes. Nat Commun 2014; 5:5448. [PMID: 25378102 PMCID: PMC4272252 DOI: 10.1038/ncomms6448] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2014] [Accepted: 09/30/2014] [Indexed: 02/07/2023] Open
Abstract
The molecular characteristics of the pseudoautosomal region (PAR) of sex chromosomes
remain elusive. Despite significant genome-sequencing efforts, the PAR of highly
differentiated avian sex chromosomes remains to be identified. Here we use linkage
analysis together with whole-genome re-sequencing to uncover the 630-kb PAR of an
ecological model species, the collared flycatcher. The PAR contains 22 protein-coding
genes and is GC rich. The genetic length is 64 cM in female meiosis, consistent
with an obligate crossing-over event. Recombination is concentrated to a hotspot region,
with an extreme rate of >700 cM/Mb in a 67-kb segment. We find no signatures
of sexual antagonism and propose that sexual antagonism may have limited influence on
PAR sequences when sex chromosomes are nearly fully differentiated and when a
recombination hotspot region is located close to the PAR boundary. Our results
demonstrate that a very small PAR suffices to ensure homologous recombination and proper
segregation of sex chromosomes during meiosis. The genetic basis of sex chromosome pseudoautosomal regions (PAR) in
organisms with female heterogamety is largely unknown. Smeds et al. provide the
first molecular characterization of the PAR in birds with differentiated sex chromosomes
and show a potential recombination hotspot and no evidence for strong sexual antagonism in
this region.
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Affiliation(s)
- Linnéa Smeds
- Department of Evolutionary Biology, Evolutionary Biology Centre, Uppsala University, Norbyvägen 18D, SE-752 36 Uppsala, Sweden
| | - Takeshi Kawakami
- Department of Evolutionary Biology, Evolutionary Biology Centre, Uppsala University, Norbyvägen 18D, SE-752 36 Uppsala, Sweden
| | - Reto Burri
- Department of Evolutionary Biology, Evolutionary Biology Centre, Uppsala University, Norbyvägen 18D, SE-752 36 Uppsala, Sweden
| | - Paulina Bolivar
- Department of Evolutionary Biology, Evolutionary Biology Centre, Uppsala University, Norbyvägen 18D, SE-752 36 Uppsala, Sweden
| | - Arild Husby
- 1] Department of Animal Ecology, Evolutionary Biology Centre, Uppsala University, Norbyvägen 18D, SE-752 36 Uppsala, Sweden [2] Department of Biology, Norwegian University of Science and Technology, N-7491 Trondheim, Norway
| | - Anna Qvarnström
- Department of Animal Ecology, Evolutionary Biology Centre, Uppsala University, Norbyvägen 18D, SE-752 36 Uppsala, Sweden
| | - Severin Uebbing
- Department of Evolutionary Biology, Evolutionary Biology Centre, Uppsala University, Norbyvägen 18D, SE-752 36 Uppsala, Sweden
| | - Hans Ellegren
- Department of Evolutionary Biology, Evolutionary Biology Centre, Uppsala University, Norbyvägen 18D, SE-752 36 Uppsala, Sweden
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Kawakami T, Smeds L, Backström N, Husby A, Qvarnström A, Mugal CF, Olason P, Ellegren H. A high-density linkage map enables a second-generation collared flycatcher genome assembly and reveals the patterns of avian recombination rate variation and chromosomal evolution. Mol Ecol 2014; 23:4035-58. [PMID: 24863701 PMCID: PMC4149781 DOI: 10.1111/mec.12810] [Citation(s) in RCA: 157] [Impact Index Per Article: 15.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2014] [Revised: 05/08/2014] [Accepted: 05/09/2014] [Indexed: 12/15/2022]
Abstract
Detailed linkage and recombination rate maps are necessary to use the full potential of genome sequencing and population genomic analyses. We used a custom collared flycatcher 50 K SNP array to develop a high-density linkage map with 37 262 markers assigned to 34 linkage groups in 33 autosomes and the Z chromosome. The best-order map contained 4215 markers, with a total distance of 3132 cm and a mean genetic distance between markers of 0.12 cm. Facilitated by the array being designed to include markers from most scaffolds, we obtained a second-generation assembly of the flycatcher genome that approaches full chromosome sequences (N50 super-scaffold size 20.2 Mb and with 1.042 Gb (of 1.116 Gb) anchored to and mostly ordered and oriented along chromosomes). We found that flycatcher and zebra finch chromosomes are entirely syntenic but that inversions at mean rates of 1.5–2.0 event (6.6–7.5 Mb) per My have changed the organization within chromosomes, rates high enough for inversions to potentially have been involved with many speciation events during avian evolution. The mean recombination rate was 3.1 cm/Mb and correlated closely with chromosome size, from 2 cm/Mb for chromosomes >100 Mb to >10 cm/Mb for chromosomes <10 Mb. This size dependence seemed entirely due to an obligate recombination event per chromosome; if 50 cm was subtracted from the genetic lengths of chromosomes, the rate per physical unit DNA was constant across chromosomes. Flycatcher recombination rate showed similar variation along chromosomes as chicken but lacked the large interior recombination deserts characteristic of zebra finch chromosomes.
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Affiliation(s)
- Takeshi Kawakami
- Department of Evolutionary Biology, Evolutionary Biology Centre (EBC), Uppsala University, Norbyvägen 18D, SE-752 36, Uppsala, Sweden
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Yazdi HP, Ellegren H. Old but Not (So) Degenerated—Slow Evolution of Largely Homomorphic Sex Chromosomes in Ratites. Mol Biol Evol 2014; 31:1444-1453. [DOI: 10.1093/molbev/msu101] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/30/2023] Open
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Abstract
Mutation is the ultimate source of genetic variation. The most direct and unbiased method of studying spontaneous mutations is via mutation accumulation (MA) lines. Until recently, MA experiments were limited by the cost of sequencing and thus provided us with small numbers of mutational events and therefore imprecise estimates of rates and patterns of mutation. We used whole-genome sequencing to identify nearly 1,000 spontaneous mutation events accumulated over ∼311,000 generations in 145 diploid MA lines of the budding yeast Saccharomyces cerevisiae. MA experiments are usually assumed to have negligible levels of selection, but even mild selection will remove strongly deleterious events. We take advantage of such patterns of selection and show that mutation classes such as indels and aneuploidies (especially monosomies) are proportionately much more likely to contribute mutations of large effect. We also provide conservative estimates of indel, aneuploidy, environment-dependent dominant lethal, and recessive lethal mutation rates. To our knowledge, for the first time in yeast MA data, we identified a sufficiently large number of single-nucleotide mutations to measure context-dependent mutation rates and were able to (i) confirm strong AT bias of mutation in yeast driven by high rate of mutations from C/G to T/A and (ii) detect a higher rate of mutation at C/G nucleotides in two specific contexts consistent with cytosine methylation in S. cerevisiae.
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Weber CC, Boussau B, Romiguier J, Jarvis ED, Ellegren H. Evidence for GC-biased gene conversion as a driver of between-lineage differences in avian base composition. Genome Biol 2014; 15:549. [PMID: 25496599 PMCID: PMC4290106 DOI: 10.1186/s13059-014-0549-1] [Citation(s) in RCA: 53] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2014] [Accepted: 11/19/2014] [Indexed: 11/23/2022] Open
Abstract
BACKGROUND While effective population size (Ne) and life history traits such as generation time are known to impact substitution rates, their potential effects on base composition evolution are less well understood. GC content increases with decreasing body mass in mammals, consistent with recombination-associated GC biased gene conversion (gBGC) more strongly impacting these lineages. However, shifts in chromosomal architecture and recombination landscapes between species may complicate the interpretation of these results. In birds, interchromosomal rearrangements are rare and the recombination landscape is conserved, suggesting that this group is well suited to assess the impact of life history on base composition. RESULTS Employing data from 45 newly and 3 previously sequenced avian genomes covering a broad range of taxa, we found that lineages with large populations and short generations exhibit higher GC content. The effect extends to both coding and non-coding sites, indicating that it is not due to selection on codon usage. Consistent with recombination driving base composition, GC content and heterogeneity were positively correlated with the rate of recombination. Moreover, we observed ongoing increases in GC in the majority of lineages. CONCLUSIONS Our results provide evidence that gBGC may drive patterns of nucleotide composition in avian genomes and are consistent with more effective gBGC in large populations and a greater number of meioses per unit time; that is, a shorter generation time. Thus, in accord with theoretical predictions, base composition evolution is substantially modulated by species life history.
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Affiliation(s)
- Claudia C Weber
- />Department of Evolutionary Biology, Evolutionary Biology Centre, Uppsala University, Norbyvägen 18D, SE-752 36 Uppsala, Sweden
| | - Bastien Boussau
- />Laboratoire de Biométrie et Biologie Evolutive, Université de Lyon, Université Lyon 1, CNRS, UMR5558 Villeurbanne, France
| | | | - Erich D Jarvis
- />Department of Neurobiology, Howard Hughes Medical Institute, Duke University Medical Center, Durham, NC USA
| | - Hans Ellegren
- />Department of Evolutionary Biology, Evolutionary Biology Centre, Uppsala University, Norbyvägen 18D, SE-752 36 Uppsala, Sweden
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Ellegren H. Genome sequencing and population genomics in non-model organisms. Trends Ecol Evol 2014; 29:51-63. [DOI: 10.1016/j.tree.2013.09.008] [Citation(s) in RCA: 392] [Impact Index Per Article: 39.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2013] [Revised: 09/02/2013] [Accepted: 09/16/2013] [Indexed: 12/20/2022]
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Affiliation(s)
- Hans Ellegren
- Department of Evolutionary Biology, Evolutionary Biology Center, Uppsala University, SE-752 36 Uppsala, Sweden;
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Capra JA, Hubisz MJ, Kostka D, Pollard KS, Siepel A. A model-based analysis of GC-biased gene conversion in the human and chimpanzee genomes. PLoS Genet 2013; 9:e1003684. [PMID: 23966869 PMCID: PMC3744432 DOI: 10.1371/journal.pgen.1003684] [Citation(s) in RCA: 52] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2013] [Accepted: 06/14/2013] [Indexed: 01/03/2023] Open
Abstract
GC-biased gene conversion (gBGC) is a recombination-associated process that favors the fixation of G/C alleles over A/T alleles. In mammals, gBGC is hypothesized to contribute to variation in GC content, rapidly evolving sequences, and the fixation of deleterious mutations, but its prevalence and general functional consequences remain poorly understood. gBGC is difficult to incorporate into models of molecular evolution and so far has primarily been studied using summary statistics from genomic comparisons. Here, we introduce a new probabilistic model that captures the joint effects of natural selection and gBGC on nucleotide substitution patterns, while allowing for correlations along the genome in these effects. We implemented our model in a computer program, called phastBias, that can accurately detect gBGC tracts about 1 kilobase or longer in simulated sequence alignments. When applied to real primate genome sequences, phastBias predicts gBGC tracts that cover roughly 0.3% of the human and chimpanzee genomes and account for 1.2% of human-chimpanzee nucleotide differences. These tracts fall in clusters, particularly in subtelomeric regions; they are enriched for recombination hotspots and fast-evolving sequences; and they display an ongoing fixation preference for G and C alleles. They are also significantly enriched for disease-associated polymorphisms, suggesting that they contribute to the fixation of deleterious alleles. The gBGC tracts provide a unique window into historical recombination processes along the human and chimpanzee lineages. They supply additional evidence of long-term conservation of megabase-scale recombination rates accompanied by rapid turnover of hotspots. Together, these findings shed new light on the evolutionary, functional, and disease implications of gBGC. The phastBias program and our predicted tracts are freely available. Interpreting patterns of DNA sequence variation in the genomes of closely related species is critically important for understanding the causes and functional effects of nucleotide substitutions. Classical models describe patterns of substitution in terms of the fundamental forces of mutation, recombination, neutral drift, and natural selection. However, an entirely separate force, called GC-biased gene conversion (gBGC), also appears to have an important influence on substitution patterns in many species. gBGC is a recombination-associated evolutionary process that favors the fixation of strong (G/C) over weak (A/T) alleles. In mammals, gBGC is thought to promote variation in GC content, rapidly evolving sequences, and the fixation of deleterious mutations. However, its genome-wide influence remains poorly understood, in part because, it is difficult to incorporate gBGC into statistical models of evolution. In this paper, we describe a new evolutionary model that jointly describes the effects of selection and gBGC and apply it to the human and chimpanzee genomes. Our genome-wide predictions of gBGC tracts indicate that gBGC has been an important force in recent human evolution. Our publicly available computer program, called phastBias, and our genome-wide predictions will enable other researchers to consider gBGC in their analyses.
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Affiliation(s)
- John A. Capra
- Gladstone Institutes, University of California, San Francisco, California, United States of America
| | - Melissa J. Hubisz
- Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, New York, United States of America
| | - Dennis Kostka
- Department of Developmental Biology and Computational & Systems Biology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Katherine S. Pollard
- Gladstone Institutes, University of California, San Francisco, California, United States of America
- Institute for Human Genetics and Division of Biostatistics, University of California, San Francisco, California, United States of America
- * E-mail: (KSP); (AS)
| | - Adam Siepel
- Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, New York, United States of America
- * E-mail: (KSP); (AS)
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