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Wu K, Qin D, Qian Y, Liu H. A new era of mutation rate analyses: Concepts and methods. Zool Res 2024; 45:767-780. [PMID: 38894520 PMCID: PMC11298668 DOI: 10.24272/j.issn.2095-8137.2024.058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2024] [Accepted: 06/04/2024] [Indexed: 06/21/2024] Open
Abstract
The mutation rate is a pivotal biological characteristic, intricately governed by natural selection and historically garnering considerable attention. Recent advances in high-throughput sequencing and analytical methodologies have profoundly transformed our understanding in this domain, ushering in an unprecedented era of mutation rate research. This paper aims to provide a comprehensive overview of the key concepts and methodologies frequently employed in the study of mutation rates. It examines various types of mutations, explores the evolutionary dynamics and associated theories, and synthesizes both classical and contemporary hypotheses. Furthermore, this review comprehensively explores recent advances in understanding germline and somatic mutations in animals and offers an overview of experimental methodologies, mutational patterns, molecular mechanisms, and driving forces influencing variations in mutation rates across species and tissues. Finally, it proposes several potential research directions and pressing questions for future investigations.
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Affiliation(s)
- Kun Wu
- Center for Evolutionary & Organismal Biology and the Fourth Affiliated Hospital of Zhejiang University, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310058, China
| | - Danqi Qin
- Center for Evolutionary & Organismal Biology and the Fourth Affiliated Hospital of Zhejiang University, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310058, China
| | - Yang Qian
- Center for Evolutionary & Organismal Biology and the Fourth Affiliated Hospital of Zhejiang University, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310058, China
| | - Haoxuan Liu
- Center for Evolutionary & Organismal Biology and the Fourth Affiliated Hospital of Zhejiang University, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310058, China. E-mail:
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2
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Yu G, Liu Y, Li Z, Deng S, Wu Z, Zhang X, Chen W, Yang J, Chen X, Yang JR. Genome-wide probing of eukaryotic nascent RNA structure elucidates cotranscriptional folding and its antimutagenic effect. Nat Commun 2023; 14:5853. [PMID: 37730811 PMCID: PMC10511511 DOI: 10.1038/s41467-023-41550-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Accepted: 09/08/2023] [Indexed: 09/22/2023] Open
Abstract
The transcriptional intermediates of RNAs fold into secondary structures with multiple regulatory roles, yet the details of such cotranscriptional RNA folding are largely unresolved in eukaryotes. Here, we present eSPET-seq (Structural Probing of Elongating Transcripts in eukaryotes), a method to assess the cotranscriptional RNA folding in Saccharomyces cerevisiae. Our study reveals pervasive structural transitions during cotranscriptional folding and overall structural similarities between nascent and mature RNAs. Furthermore, a combined analysis with genome-wide R-loop and mutation rate approximations provides quantitative evidence for the antimutator effect of nascent RNA folding through competitive inhibition of the R-loops, known to facilitate transcription-associated mutagenesis. Taken together, we present an experimental evaluation of cotranscriptional folding in eukaryotes and demonstrate the antimutator effect of nascent RNA folding. These results suggest genome-wide coupling between the processing and transmission of genetic information through RNA folding.
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Affiliation(s)
- Gongwang Yu
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China
- Department of Genetics and Biomedical Informatics, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China
| | - Yao Liu
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China
- Department of Genetics and Biomedical Informatics, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China
| | - Zizhang Li
- Department of Genetics and Biomedical Informatics, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China
| | - Shuyun Deng
- Department of Genetics and Biomedical Informatics, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China
| | - Zhuoxing Wu
- Department of Genetics and Biomedical Informatics, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China
| | - Xiaoyu Zhang
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China
- Department of Genetics and Biomedical Informatics, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China
| | - Wenbo Chen
- Department of Genetics and Biomedical Informatics, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China
| | - Junnan Yang
- Department of Genetics and Biomedical Informatics, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China
| | - Xiaoshu Chen
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China
- Department of Genetics and Biomedical Informatics, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China
- Key Laboratory of Tropical Disease Control, Ministry of Education, Sun Yat-sen University, Guangzhou, 510080, China
| | - Jian-Rong Yang
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China.
- Department of Genetics and Biomedical Informatics, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China.
- Key Laboratory of Tropical Disease Control, Ministry of Education, Sun Yat-sen University, Guangzhou, 510080, China.
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Zhang J. What Has Genomics Taught An Evolutionary Biologist? GENOMICS, PROTEOMICS & BIOINFORMATICS 2023; 21:1-12. [PMID: 36720382 PMCID: PMC10373158 DOI: 10.1016/j.gpb.2023.01.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Revised: 01/06/2023] [Accepted: 01/19/2023] [Indexed: 01/30/2023]
Abstract
Genomics, an interdisciplinary field of biology on the structure, function, and evolution of genomes, has revolutionized many subdisciplines of life sciences, including my field of evolutionary biology, by supplying huge data, bringing high-throughput technologies, and offering a new approach to biology. In this review, I describe what I have learned from genomics and highlight the fundamental knowledge and mechanistic insights gained. I focus on three broad topics that are central to evolutionary biology and beyond-variation, interaction, and selection-and use primarily my own research and study subjects as examples. In the next decade or two, I expect that the most important contributions of genomics to evolutionary biology will be to provide genome sequences of nearly all known species on Earth, facilitate high-throughput phenotyping of natural variants and systematically constructed mutants for mapping genotype-phenotype-fitness landscapes, and assist the determination of causality in evolutionary processes using experimental evolution.
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Affiliation(s)
- Jianzhi Zhang
- Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI 48109, USA.
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Wood KA, Goriely A. The impact of paternal age on new mutations and disease in the next generation. Fertil Steril 2022; 118:1001-1012. [PMID: 36351856 PMCID: PMC10909733 DOI: 10.1016/j.fertnstert.2022.10.017] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2022] [Revised: 10/09/2022] [Accepted: 10/11/2022] [Indexed: 11/09/2022]
Abstract
Advanced paternal age is associated with an increased risk of fathering children with genetic disorders and other adverse reproductive consequences. However, the mechanisms underlying this phenomenon remain largely unexplored. In this review, we focus on the impact of paternal age on de novo mutations that are an important contributor to genetic disease and can be studied both indirectly through large-scale sequencing studies and directly in the tissue in which they predominantly arise-the aging testis. We discuss the recent data that have helped establish the origins and frequency of de novo mutations, and highlight experimental evidence about the close link between new mutations, parental age, and genetic disease. We then focus on a small group of rare genetic conditions, the so-called "paternal age effect" disorders that show a strong association between paternal age and disease prevalence, and discuss the underlying mechanism ("selfish selection") and implications of this process in more detail. More broadly, understanding the causes and consequences of paternal age on genetic risk has important implications both for individual couples and for public health advice given that the average age of fatherhood is steadily increasing in many developed nations.
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Affiliation(s)
- Katherine A Wood
- Radcliffe Department of Medicine, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, United Kingdom; National Institute for Health and Care Research (NIHR) Oxford Biomedical Research Centre, Oxford, United Kingdom
| | - Anne Goriely
- Radcliffe Department of Medicine, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, United Kingdom; National Institute for Health and Care Research (NIHR) Oxford Biomedical Research Centre, Oxford, United Kingdom.
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Rabbani M, Zheng X, Manske GL, Vargo A, Shami AN, Li JZ, Hammoud SS. Decoding the Spermatogenesis Program: New Insights from Transcriptomic Analyses. Annu Rev Genet 2022; 56:339-368. [PMID: 36070560 PMCID: PMC10722372 DOI: 10.1146/annurev-genet-080320-040045] [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] [Indexed: 01/19/2023]
Abstract
Spermatogenesis is a complex differentiation process coordinated spatiotemporally across and along seminiferous tubules. Cellular heterogeneity has made it challenging to obtain stage-specific molecular profiles of germ and somatic cells using bulk transcriptomic analyses. This has limited our ability to understand regulation of spermatogenesis and to integrate knowledge from model organisms to humans. The recent advancement of single-cell RNA-sequencing (scRNA-seq) technologies provides insights into the cell type diversity and molecular signatures in the testis. Fine-grained cell atlases of the testis contain both known and novel cell types and define the functional states along the germ cell developmental trajectory in many species. These atlases provide a reference system for integrated interspecies comparisons to discover mechanistic parallels and to enable future studies. Despite recent advances, we currently lack high-resolution data to probe germ cell-somatic cell interactions in the tissue environment, but the use of highly multiplexed spatial analysis technologies has begun to resolve this problem. Taken together, recent single-cell studies provide an improvedunderstanding of gametogenesis to examine underlying causes of infertility and enable the development of new therapeutic interventions.
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Affiliation(s)
- Mashiat Rabbani
- Department of Human Genetics, University of Michigan, Ann Arbor, Michigan, USA;
| | - Xianing Zheng
- Department of Human Genetics, University of Michigan, Ann Arbor, Michigan, USA;
| | - Gabe L Manske
- Cellular and Molecular Biology Graduate Program, University of Michigan, Ann Arbor, Michigan, USA
| | - Alexander Vargo
- Department of Human Genetics, University of Michigan, Ann Arbor, Michigan, USA;
| | - Adrienne N Shami
- Department of Human Genetics, University of Michigan, Ann Arbor, Michigan, USA;
| | - Jun Z Li
- Department of Human Genetics, University of Michigan, Ann Arbor, Michigan, USA;
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, USA
| | - Saher Sue Hammoud
- Department of Human Genetics, University of Michigan, Ann Arbor, Michigan, USA;
- Department of Obstetrics and Gynecology, University of Michigan, Ann Arbor, Michigan, USA
- Department of Urology, University of Michigan, Ann Arbor, Michigan, USA
- Cellular and Molecular Biology Graduate Program, University of Michigan, Ann Arbor, Michigan, USA
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Tzur YB. lncRNAs in fertility: redefining the gene expression paradigm? Trends Genet 2022; 38:1170-1179. [PMID: 35728988 DOI: 10.1016/j.tig.2022.05.013] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Revised: 05/02/2022] [Accepted: 05/26/2022] [Indexed: 01/24/2023]
Abstract
Comparative transcriptome approaches assume that highly or dynamically expressed genes are important. This has led to the identification of many genes critical for cellular activity and organism development. However, while testes express the highest levels of long noncoding RNAs (lncRNAs), there is scarcely any evidence for lncRNAs with significant roles in fertility. This was explained by changes in chromatin structure during spermatogenesis that lead to 'promiscuous transcription' with no functional roles for the transcripts. Recent discoveries offer novel and surprising alternatives. Here, I review the current knowledge regarding the involvement of lncRNAs in fertility, why I find gametogenesis different from other developmental processes, offer models to explain why the experimental evidence did not meet theoretical predictions, and suggest possible approaches to test the models.
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Affiliation(s)
- Yonatan B Tzur
- Department of Genetics, Institute of Life Sciences, Hebrew University of Jerusalem, Jerusalem 91904, Israel.
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Abstract
A study of the plant Arabidopsis thaliana detected lower mutation rates in genomic regions where mutations are more likely to be deleterious, challenging the principle that mutagenesis is blind to its consequence. To examine the generality of this finding, we analyze large mutational data from baker's yeast and humans. The yeast data do not exhibit this trend, whereas the human data show an opposite trend that disappears upon the control of potential confounders. We find that the Arabidopsis study identified substantially more mutations than reported in the original data-generating studies and expected from Arabidopsis' mutation rate. These extra mutations are enriched in polynucleotide tracts and have relatively low sequencing qualities so are likely sequencing errors. Furthermore, the polynucleotide “mutations” can produce the purported mutational trend in Arabidopsis. Together, our results do not support lower mutagenesis of genomic regions of stronger selective constraints in the plant, fungal, and animal models examined.
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Affiliation(s)
- Haoxuan Liu
- Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, Michigan 48109, USA.,Evolutionary and Organismal Biology Research Center, School of Medicine, Zhejiang University, Hangzhou, 310000, China
| | - Jianzhi Zhang
- Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, Michigan 48109, USA
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9
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Waneka G, Svendsen JM, Havird JC, Sloan DB. Mitochondrial mutations in Caenorhabditis elegans show signatures of oxidative damage and an AT-bias. Genetics 2021; 219:6346985. [PMID: 34849888 DOI: 10.1093/genetics/iyab116] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2021] [Accepted: 07/09/2021] [Indexed: 01/25/2023] Open
Abstract
Rapid mutation rates are typical of mitochondrial genomes (mtDNAs) in animals, but it is not clear why. The difficulty of obtaining measurements of mtDNA mutation that are not biased by natural selection has stymied efforts to distinguish between competing hypotheses about the causes of high mtDNA mutation rates. Several studies which have measured mtDNA mutations in nematodes have yielded small datasets with conflicting conclusions about the relative abundance of different substitution classes (i.e., the mutation spectrum). We therefore leveraged Duplex Sequencing, a high-fidelity DNA sequencing technique, to characterize de novo mtDNA mutations in Caenorhabditis elegans. This approach detected nearly an order of magnitude more mtDNA mutations than documented in any previous nematode mutation study. Despite an existing extreme AT bias in the C. elegans mtDNA (75.6% AT), we found that a significant majority of mutations increase genomic AT content. Compared to some prior studies in nematodes and other animals, the mutation spectrum reported here contains an abundance of CG→AT transversions, supporting the hypothesis that oxidative damage may be a driver of mtDNA mutations in nematodes. Furthermore, we found an excess of G→T and C→T changes on the coding DNA strand relative to the template strand, consistent with increased exposure to oxidative damage. Analysis of the distribution of mutations across the mtDNA revealed significant variation among protein-coding genes and as well as among neighboring nucleotides. This high-resolution view of mitochondrial mutations in C. elegans highlights the value of this system for understanding relationships among oxidative damage, replication error, and mtDNA mutation.
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Affiliation(s)
- Gus Waneka
- Department of Biology, Colorado State University, Fort Collins, CO 80523, USA and
| | - Joshua M Svendsen
- Department of Biology, Colorado State University, Fort Collins, CO 80523, USA and
| | - Justin C Havird
- Department of Integrative Biology, University of Texas at Austin, Austin, TX 78712, USA
| | - Daniel B Sloan
- Department of Biology, Colorado State University, Fort Collins, CO 80523, USA and
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Gene expression levels modulate germline mutation rates through the compound effects of transcription-coupled repair and damage. Hum Genet 2021; 141:1211-1222. [PMID: 34482438 DOI: 10.1007/s00439-021-02355-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2021] [Accepted: 08/25/2021] [Indexed: 12/16/2022]
Abstract
Of all mammalian organs, the testis has long been observed to have the most diverse gene expression profile. To account for this widespread gene expression, we have proposed a mechanism termed 'transcriptional scanning', which reduces germline mutation rates through transcription-coupled repair (TCR). Our hypothesis contrasts with an earlier observation that mutation rates are overall positively correlated with gene expression levels in yeast, implying that transcription is mutagenic due to effects dominated by transcription-coupled damage (TCD). Here we report evidence that the compound effects of both TCR and TCD during spermatogenesis modulate human germline mutation rates, with TCR dominating in most genes, thus supporting the transcriptional scanning hypothesis. Our analyses address potentially confounding factors, distinguish the differential mutagenic effects acting on the highly expressed genes and the low-to-moderately expressed genes, and resolve concerns relating to the validation of the results using a de novo mutation dataset. We also discuss the theoretical possibility of transcriptional scanning hypothesis from an evolutionary perspective. Together, these analyses support a model by which the coupling of transcription-coupled repair and damage establishes the pattern of germline mutation rates and provide an evolutionary explanation for widespread gene expression during spermatogenesis.
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