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Johnston SE. Understanding the Genetic Basis of Variation in Meiotic Recombination: Past, Present, and Future. Mol Biol Evol 2024; 41:msae112. [PMID: 38959451 PMCID: PMC11221659 DOI: 10.1093/molbev/msae112] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2024] [Revised: 06/03/2024] [Accepted: 06/05/2024] [Indexed: 07/05/2024] Open
Abstract
Meiotic recombination is a fundamental feature of sexually reproducing species. It is often required for proper chromosome segregation and plays important role in adaptation and the maintenance of genetic diversity. The molecular mechanisms of recombination are remarkably conserved across eukaryotes, yet meiotic genes and proteins show substantial variation in their sequence and function, even between closely related species. Furthermore, the rate and distribution of recombination shows a huge diversity within and between chromosomes, individuals, sexes, populations, and species. This variation has implications for many molecular and evolutionary processes, yet how and why this diversity has evolved is not well understood. A key step in understanding trait evolution is to determine its genetic basis-that is, the number, effect sizes, and distribution of loci underpinning variation. In this perspective, I discuss past and current knowledge on the genetic basis of variation in recombination rate and distribution, explore its evolutionary implications, and present open questions for future research.
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Affiliation(s)
- Susan E Johnston
- Institute of Ecology and Evolution, School of Biological Sciences, University of Edinburgh, Edinburgh EH9 3FL, UK
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Caporale LH. Evolutionary feedback from the environment shapes mechanisms that generate genome variation. J Physiol 2024; 602:2601-2614. [PMID: 38194279 DOI: 10.1113/jp284411] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Accepted: 12/14/2023] [Indexed: 01/10/2024] Open
Abstract
Darwin recognized that 'a grand and almost untrodden field of inquiry will be opened, on the causes and laws of variation.' However, because the Modern Synthesis assumes that the intrinsic probability of any individual mutation is unrelated to that mutation's potential adaptive value, attention has been focused on selection rather than on the intrinsic generation of variation. Yet many examples illustrate that the term 'random' mutation, as widely understood, is inaccurate. The probabilities of distinct classes of variation are neither evenly distributed across a genome nor invariant over time, nor unrelated to their potential adaptive value. Because selection acts upon variation, multiple biochemical mechanisms can and have evolved that increase the relative probability of adaptive mutations. In effect, the generation of heritable variation is in a feedback loop with selection, such that those mechanisms that tend to generate variants that survive recurring challenges in the environment would be captured by this survival and thus inherited and accumulated within lineages of genomes. Moreover, because genome variation is affected by a wide range of biochemical processes, genome variation can be regulated. Biochemical mechanisms that sense stress, from lack of nutrients to DNA damage, can increase the probability of specific classes of variation. A deeper understanding of evolution involves attention to the evolution of, and environmental influences upon, the intrinsic variation generated in gametes, in other words upon the biochemical mechanisms that generate variation across generations. These concepts have profound implications for the types of questions that can and should be asked, as omics databases become more comprehensive, detection methods more sensitive, and computation and experimental analyses even more high throughput and thus capable of revealing the intrinsic generation of variation in individual gametes. These concepts also have profound implications for evolutionary theory, which, upon reflection it will be argued, predicts that selection would increase the probability of generating adaptive mutations, in other words, predicts that the ability to evolve itself evolves.
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Chen Z, Zhou M, Sun Y, Tang X, Zhang Z, Huang L. Exploration of Genome-Wide Recombination Rate Variation Patterns at Different Scales in Pigs. Animals (Basel) 2024; 14:1345. [PMID: 38731349 PMCID: PMC11083071 DOI: 10.3390/ani14091345] [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: 04/05/2024] [Revised: 04/27/2024] [Accepted: 04/28/2024] [Indexed: 05/13/2024] Open
Abstract
Meiotic recombination is a prevalent process in eukaryotic sexual reproduction organisms that plays key roles in genetic diversity, breed selection, and species evolution. However, the recombination events differ across breeds and even within breeds. In this study, we initially computed large-scale population recombination rates of both sexes using approximately 52 K SNP genotypes in a total of 3279 pigs from four different Chinese and Western breeds. We then constructed a high-resolution historical recombination map using approximately 16 million SNPs from a sample of unrelated individuals. Comparative analysis of porcine recombination events from different breeds and at different resolutions revealed the following observations: Firstly, the 1Mb-scale pig recombination maps of the same sex are moderately conserved among different breeds, with the similarity of recombination events between Western pigs and Chinese indigenous pigs being lower than within their respective groups. Secondly, we identified 3861 recombination hotspots in the genome and observed medium- to high-level correlation between historical recombination rates (0.542~0.683) and estimates of meiotic recombination rates. Third, we observed that recombination hotspots are significantly far from the transcription start sites of pig genes, and the silico-predicted PRDM9 zinc finger domain DNA recognition motif is significantly enriched in the regions of recombination hotspots compared to recombination coldspots, highlighting the potential role of PRDM9 in regulating recombination hotspots in pigs. Our study analyzed the variation patterns of the pig recombination map at broad and fine scales, providing a valuable reference for genomic selection breeding and laying a crucial foundation for further understanding the molecular mechanisms of pig genome recombination.
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Affiliation(s)
| | | | | | | | - Zhiyan Zhang
- National Key Laboratory for Swine Genetic Improvement and Germplasm Innovation, Jiangxi Agricultural University, Nanchang 330045, China
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AbuAlia KFN, Damm E, Ullrich KK, Mukaj A, Parvanov E, Forejt J, Odenthal-Hesse L. Natural variation in the zinc-finger-encoding exon of Prdm9 affects hybrid sterility phenotypes in mice. Genetics 2024; 226:iyae004. [PMID: 38217871 PMCID: PMC10917509 DOI: 10.1093/genetics/iyae004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Revised: 01/04/2024] [Accepted: 01/05/2024] [Indexed: 01/15/2024] Open
Abstract
PRDM9-mediated reproductive isolation was first described in the progeny of Mus musculus musculus (MUS) PWD/Ph and Mus musculus domesticus (DOM) C57BL/6J inbred strains. These male F1 hybrids fail to complete chromosome synapsis and arrest meiosis at prophase I, due to incompatibilities between the Prdm9 gene and hybrid sterility locus Hstx2. We identified 14 alleles of Prdm9 in exon 12, encoding the DNA-binding domain of the PRDM9 protein in outcrossed wild mouse populations from Europe, Asia, and the Middle East, 8 of which are novel. The same allele was found in all mice bearing introgressed t-haplotypes encompassing Prdm9. We asked whether 7 novel Prdm9 alleles in MUS populations and the t-haplotype allele in 1 MUS and 3 DOM populations induce Prdm9-mediated reproductive isolation. The results show that only combinations of the dom2 allele of DOM origin and the MUS msc1 allele ensure complete infertility of intersubspecific hybrids in outcrossed wild populations and inbred mouse strains examined so far. The results further indicate that MUS mice may share the erasure of PRDM9msc1 binding motifs in populations with different Prdm9 alleles, which implies that erased PRDM9 binding motifs may be uncoupled from their corresponding Prdm9 alleles at the population level. Our data corroborate the model of Prdm9-mediated hybrid sterility beyond inbred strains of mice and suggest that sterility alleles of Prdm9 may be rare.
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Affiliation(s)
- Khawla F N AbuAlia
- Research Group Meiotic Recombination and Genome Instability, Max Planck Institute for Evolutionary Biology, Plön D-24306, Germany
| | - Elena Damm
- Research Group Meiotic Recombination and Genome Instability, Max Planck Institute for Evolutionary Biology, Plön D-24306, Germany
| | - Kristian K Ullrich
- Research Group Meiotic Recombination and Genome Instability, Max Planck Institute for Evolutionary Biology, Plön D-24306, Germany
| | - Amisa Mukaj
- Laboratory of Mouse Molecular Genetics, Institute of Molecular Genetics, Czech Academy of Sciences, Vestec CZ-25250, Czech Republic
| | - Emil Parvanov
- Laboratory of Mouse Molecular Genetics, Institute of Molecular Genetics, Czech Academy of Sciences, Vestec CZ-25250, Czech Republic
- Department of Translational Stem Cell Biology, Research Institute of the Medical University of Varna, 9002 Varna, Bulgaria
- Ludwig Boltzmann Institute for Digital Health and Patient Safety, Medical University of Vienna, 1090 Vienna, Austria
| | - Jiri Forejt
- Laboratory of Mouse Molecular Genetics, Institute of Molecular Genetics, Czech Academy of Sciences, Vestec CZ-25250, Czech Republic
| | - Linda Odenthal-Hesse
- Research Group Meiotic Recombination and Genome Instability, Max Planck Institute for Evolutionary Biology, Plön D-24306, Germany
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Wang Y, Chen Y, Gao J, Xie H, Guo Y, Yang J, Liu J, Chen Z, Li Q, Li M, Ren J, Wen L, Tang F. Mapping crossover events of mouse meiotic recombination by restriction fragment ligation-based Refresh-seq. Cell Discov 2024; 10:26. [PMID: 38443370 PMCID: PMC10915157 DOI: 10.1038/s41421-023-00638-9] [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: 06/02/2023] [Accepted: 12/11/2023] [Indexed: 03/07/2024] Open
Abstract
Single-cell whole-genome sequencing methods have undergone great improvements over the past decade. However, allele dropout, which means the inability to detect both alleles simultaneously in an individual diploid cell, largely restricts the application of these methods particularly for medical applications. Here, we develop a new single-cell whole-genome sequencing method based on third-generation sequencing (TGS) platform named Refresh-seq (restriction fragment ligation-based genome amplification and TGS). It is based on restriction endonuclease cutting and ligation strategy in which two alleles in an individual cell can be cut into equal fragments and tend to be amplified simultaneously. As a new single-cell long-read genome sequencing method, Refresh-seq features much lower allele dropout rate compared with SMOOTH-seq. Furthermore, we apply Refresh-seq to 688 sperm cells and 272 female haploid cells (secondary polar bodies and parthenogenetic oocytes) from F1 hybrid mice. We acquire high-resolution genetic map of mouse meiosis recombination at low sequencing depth and reveal the sexual dimorphism in meiotic crossovers. We also phase the structure variations (deletions and insertions) in sperm cells and female haploid cells with high precision. Refresh-seq shows great performance in screening aneuploid sperm cells and oocytes due to the low allele dropout rate and has great potential for medical applications such as preimplantation genetic diagnosis.
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Affiliation(s)
- Yan Wang
- Biomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing, China
- Beijing Advanced Innovation Center for Genomics (ICG), Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Beijing, China
| | - Yijun Chen
- Biomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing, China
- Beijing Advanced Innovation Center for Genomics (ICG), Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Beijing, China
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
| | - Junpeng Gao
- Biomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing, China
- Beijing Advanced Innovation Center for Genomics (ICG), Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Beijing, China
- Emergency Center, Zhongnan Hospital of Wuhan University, Wuhan, Hubei, China
| | - Haoling Xie
- Biomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing, China
- Beijing Advanced Innovation Center for Genomics (ICG), Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Beijing, China
| | - Yuqing Guo
- Biomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing, China
- Beijing Advanced Innovation Center for Genomics (ICG), Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Beijing, China
| | - Jingwei Yang
- Biomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing, China
- Beijing Advanced Innovation Center for Genomics (ICG), Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Beijing, China
| | - Jun'e Liu
- Biomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing, China
- Beijing Advanced Innovation Center for Genomics (ICG), Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Beijing, China
| | - Zonggui Chen
- Biomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing, China
- Beijing Advanced Innovation Center for Genomics (ICG), Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Beijing, China
- Changping Laboratory, Beijing, China
| | - Qingqing Li
- Biomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing, China
- Beijing Advanced Innovation Center for Genomics (ICG), Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Beijing, China
| | - Mengyao Li
- Biomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing, China
- Beijing Advanced Innovation Center for Genomics (ICG), Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Beijing, China
| | - Jie Ren
- Biomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing, China
- Beijing Advanced Innovation Center for Genomics (ICG), Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Beijing, China
| | - Lu Wen
- Biomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing, China
- Beijing Advanced Innovation Center for Genomics (ICG), Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Beijing, China
| | - Fuchou Tang
- Biomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing, China.
- Beijing Advanced Innovation Center for Genomics (ICG), Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Beijing, China.
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.
- Changping Laboratory, Beijing, China.
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Abstract
The raison d'être of meiosis is shuffling of genetic information via Mendelian segregation and, within individual chromosomes, by DNA crossing-over. These outcomes are enabled by a complex cellular program in which interactions between homologous chromosomes play a central role. We first provide a background regarding the basic principles of this program. We then summarize the current understanding of the DNA events of recombination and of three processes that involve whole chromosomes: homolog pairing, crossover interference, and chiasma maturation. All of these processes are implemented by direct physical interaction of recombination complexes with underlying chromosome structures. Finally, we present convergent lines of evidence that the meiotic program may have evolved by coupling of this interaction to late-stage mitotic chromosome morphogenesis.
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Affiliation(s)
- Denise Zickler
- Institute for Integrative Biology of the Cell (I2BC), Centre National de la Recherche Scientifique (CNRS), Université Paris-Sud, Université Paris-Saclay, Gif-sur-Yvette, France
| | - Nancy Kleckner
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, Massachusetts, USA;
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Ball RL, Bogue MA, Liang H, Srivastava A, Ashbrook DG, Lamoureux A, Gerring MW, Hatoum AS, Kim M, He H, Emerson J, Berger AK, Walton DO, Sheppard K, Kassaby BE, Castellanos F, Kunde-Ramamoorthy G, Lu L, Bluis J, Desai S, Sundberg BA, Peltz G, Fang Z, Churchill GA, Williams RW, Agrawal A, Bult CJ, Philip VM, Chesler EJ. GenomeMUSter mouse genetic variation service enables multi-trait, multi-population data integration and analyses. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.08.552506. [PMID: 37609331 PMCID: PMC10441370 DOI: 10.1101/2023.08.08.552506] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/24/2023]
Abstract
Hundreds of inbred laboratory mouse strains and intercross populations have been used to functionalize genetic variants that contribute to disease. Thousands of disease relevant traits have been characterized in mice and made publicly available. New strains and populations including the Collaborative Cross, expanded BXD and inbred wild-derived strains add to set of complex disease mouse models, genetic mapping resources and sensitized backgrounds against which to evaluate engineered mutations. The genome sequences of many inbred strains, along with dense genotypes from others could allow integrated analysis of trait - variant associations across populations, but these analyses are not feasible due to the sparsity of genotypes available. Moreover, the data are not readily interoperable with other resources. To address these limitations, we created a uniformly dense data resource by harmonizing multiple variant datasets. Missing genotypes were imputed using the Viterbi algorithm with a data-driven technique that incorporates local phylogenetic information, an approach that is extensible to other model organism species. The result is a web- and programmatically-accessible data service called GenomeMUSter ( https://muster.jax.org ), comprising allelic data covering 657 strains at 106.8M segregating sites. Interoperation with phenotype databases, analytic tools and other resources enable a wealth of applications including multi-trait, multi-population meta-analysis. We demonstrate this in a cross-species comparison of the meta-analysis of Type 2 Diabetes and of substance use disorders, resulting in the more specific characterization of the role of human variant effects in light of mouse phenotype data. Other applications include refinement of mapped loci and prioritization of strain backgrounds for disease modeling to further unlock extant mouse diversity for genetic and genomic studies in health and disease.
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