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Goldberg ME, Noyes MD, Eichler EE, Quinlan AR, Harris K. Effects of parental age and polymer composition on short tandem repeat de novo mutation rates. Genetics 2024; 226:iyae013. [PMID: 38298127 PMCID: PMC10990422 DOI: 10.1093/genetics/iyae013] [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: 08/11/2023] [Revised: 08/11/2023] [Accepted: 01/05/2024] [Indexed: 02/02/2024] Open
Abstract
Short tandem repeats (STRs) are hotspots of genomic variability in the human germline because of their high mutation rates, which have long been attributed largely to polymerase slippage during DNA replication. This model suggests that STR mutation rates should scale linearly with a father's age, as progenitor cells continually divide after puberty. In contrast, it suggests that STR mutation rates should not scale with a mother's age at her child's conception, since oocytes spend a mother's reproductive years arrested in meiosis II and undergo a fixed number of cell divisions that are independent of the age at ovulation. Yet, mirroring recent findings, we find that STR mutation rates covary with paternal and maternal age, implying that some STR mutations are caused by DNA damage in quiescent cells rather than polymerase slippage in replicating progenitor cells. These results echo the recent finding that DNA damage in oocytes is a significant source of de novo single nucleotide variants and corroborate evidence of STR expansion in postmitotic cells. However, we find that the maternal age effect is not confined to known hotspots of oocyte mutagenesis, nor are postzygotic mutations likely to contribute significantly. STR nucleotide composition demonstrates divergent effects on de novo mutation (DNM) rates between sexes. Unlike the paternal lineage, maternally derived DNMs at A/T STRs display a significantly greater association with maternal age than DNMs at G/C-containing STRs. These observations may suggest the mechanism and developmental timing of certain STR mutations and contradict prior attribution of replication slippage as the primary mechanism of STR mutagenesis.
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Affiliation(s)
- Michael E Goldberg
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
- Departments of Human Genetics and Biomedical Informatics, University of Utah, Salt Lake City, UT 84112, USA
| | - Michelle D Noyes
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Evan E Eichler
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
- Howard Hughes Medical Institute, University of Washington, Seattle, WA 98195, USA
| | - Aaron R Quinlan
- Departments of Human Genetics and Biomedical Informatics, University of Utah, Salt Lake City, UT 84112, USA
| | - Kelley Harris
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
- Computational Biology Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
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2
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Sasani TA, Quinlan AR, Harris K. Epistasis between mutator alleles contributes to germline mutation spectrum variability in laboratory mice. eLife 2024; 12:RP89096. [PMID: 38381482 PMCID: PMC10942616 DOI: 10.7554/elife.89096] [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] [Indexed: 02/22/2024] Open
Abstract
Maintaining germline genome integrity is essential and enormously complex. Although many proteins are involved in DNA replication, proofreading, and repair, mutator alleles have largely eluded detection in mammals. DNA replication and repair proteins often recognize sequence motifs or excise lesions at specific nucleotides. Thus, we might expect that the spectrum of de novo mutations - the frequencies of C>T, A>G, etc. - will differ between genomes that harbor either a mutator or wild-type allele. Previously, we used quantitative trait locus mapping to discover candidate mutator alleles in the DNA repair gene Mutyh that increased the C>A germline mutation rate in a family of inbred mice known as the BXDs (Sasani et al., 2022, Ashbrook et al., 2021). In this study we developed a new method to detect alleles associated with mutation spectrum variation and applied it to mutation data from the BXDs. We discovered an additional C>A mutator locus on chromosome 6 that overlaps Ogg1, a DNA glycosylase involved in the same base-excision repair network as Mutyh (David et al., 2007). Its effect depends on the presence of a mutator allele near Mutyh, and BXDs with mutator alleles at both loci have greater numbers of C>A mutations than those with mutator alleles at either locus alone. Our new methods for analyzing mutation spectra reveal evidence of epistasis between germline mutator alleles and may be applicable to mutation data from humans and other model organisms.
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Affiliation(s)
- Thomas A Sasani
- Department of Human Genetics, University of UtahSalt Lake CityUnited States
| | - Aaron R Quinlan
- Department of Human Genetics, University of UtahSalt Lake CityUnited States
- Department of Biomedical Informatics, University of UtahSalt Lake CityUnited States
| | - Kelley Harris
- Department of Genome Sciences, University of WashingtonSeattleUnited States
- Herbold Computational Biology Program, Fred Hutch Cancer CenterSeattleUnited States
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3
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Goldberg ME, Noyes MD, Eichler EE, Quinlan AR, Harris K. Effects of parental age and polymer composition on short tandem repeat de novo mutation rates. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.22.573131. [PMID: 38187618 PMCID: PMC10769404 DOI: 10.1101/2023.12.22.573131] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/09/2024]
Abstract
Short tandem repeats (STRs) are hotspots of genomic variability in the human germline because of their high mutation rates, which have long been attributed largely to polymerase slippage during DNA replication. This model suggests that STR mutation rates should scale linearly with a father's age, as progenitor cells continually divide after puberty. In contrast, it suggests that STR mutation rates should not scale with a mother's age at her child's conception, since oocytes spend a mother's reproductive years arrested in meiosis II and undergo a fixed number of cell divisions that are independent of the age at ovulation. Yet, mirroring recent findings, we find that STR mutation rates covary with paternal and maternal age, implying that some STR mutations are caused by DNA damage in quiescent cells rather than the classical mechanism of polymerase slippage in replicating progenitor cells. These results also echo the recent finding that DNA damage in quiescent oocytes is a significant source of de novo SNVs and corroborate evidence of STR expansion in postmitotic cells. However, we find that the maternal age effect is not confined to previously discovered hotspots of oocyte mutagenesis, nor are post-zygotic mutations likely to contribute significantly. STR nucleotide composition demonstrates divergent effects on DNM rates between sexes. Unlike the paternal lineage, maternally derived DNMs at A/T STRs display a significantly greater association with maternal age than DNMs at GC-containing STRs. These observations may suggest the mechanism and developmental timing of certain STR mutations and are especially surprising considering the prior belief in replication slippage as the dominant mechanism of STR mutagenesis.
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Affiliation(s)
- Michael E. Goldberg
- Department of Genome Sciences, University of Washington, 3720 15 Ave NE, Seattle, WA, 98195
- Departments of Human Genetics and Biomedical Informatics, University of Utah, 15 S 2030 E, Salt Lake City, UT, 84112
| | - Michelle D. Noyes
- Department of Genome Sciences, University of Washington, 3720 15 Ave NE, Seattle, WA, 98195
| | - Evan E. Eichler
- Department of Genome Sciences, University of Washington, 3720 15 Ave NE, Seattle, WA, 98195
- Howard Hughes Medical Institute, 3720 15 Ave NE, University of Washington, Seattle, WA, 98195
| | - Aaron R. Quinlan
- Departments of Human Genetics and Biomedical Informatics, University of Utah, 15 S 2030 E, Salt Lake City, UT, 84112
- These authors contributed equally to this work
| | - Kelley Harris
- Department of Genome Sciences, University of Washington, 3720 15 Ave NE, Seattle, WA, 98195
- Computational Biology Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N, Seattle, WA, 98109
- These authors contributed equally to this work
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4
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Sasani TA, Quinlan AR, Harris K. Epistasis between mutator alleles contributes to germline mutation spectra variability in laboratory mice. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.25.537217. [PMID: 37162999 PMCID: PMC10168256 DOI: 10.1101/2023.04.25.537217] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/11/2023]
Abstract
Maintaining germline genome integrity is essential and enormously complex. Although many proteins are involved in DNA replication, proofreading, and repair [1], mutator alleles have largely eluded detection in mammals. DNA replication and repair proteins often recognize sequence motifs or excise lesions at specific nucleotides. Thus, we might expect that the spectrum of de novo mutations - the frequencies of C>T, A>G, etc. - will differ between genomes that harbor either a mutator or wild-type allele. Previously, we used quantitative trait locus mapping to discover candidate mutator alleles in the DNA repair gene Mutyh that increased the C>A germline mutation rate in a family of inbred mice known as the BXDs [2,3]. In this study we developed a new method to detect alleles associated with mutation spectrum variation and applied it to mutation data from the BXDs. We discovered an additional C>A mutator locus on chromosome 6 that overlaps Ogg1, a DNA glycosylase involved in the same base-excision repair network as Mutyh [4]. Its effect depended on the presence of a mutator allele near Mutyh, and BXDs with mutator alleles at both loci had greater numbers of C>A mutations than those with mutator alleles at either locus alone. Our new methods for analyzing mutation spectra reveal evidence of epistasis between germline mutator alleles and may be applicable to mutation data from humans and other model organisms.
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Affiliation(s)
| | - Aaron R. Quinlan
- Department of Human Genetics, University of Utah; Department of Biomedical Informatics, University of Utah · Funded by NIH/NHGRI R01HG012252
| | - Kelley Harris
- Department of Genome Sciences, University of Washington · Funded by NIH/NIGMS R35GM133428; Burroughs Wellcome Career Award at the Scientific Interface; Searle Scholarship; Pew Scholarship; Sloan Fellowship; Allen Discovery Center for Cell Lineage Tracing
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5
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Vollger MR, Dishuck PC, Harvey WT, DeWitt WS, Guitart X, Goldberg ME, Rozanski AN, Lucas J, Asri M, Munson KM, Lewis AP, Hoekzema K, Logsdon GA, Porubsky D, Paten B, Harris K, Hsieh P, Eichler EE. Increased mutation and gene conversion within human segmental duplications. Nature 2023; 617:325-334. [PMID: 37165237 PMCID: PMC10172114 DOI: 10.1038/s41586-023-05895-y] [Citation(s) in RCA: 24] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Accepted: 02/28/2023] [Indexed: 05/12/2023]
Abstract
Single-nucleotide variants (SNVs) in segmental duplications (SDs) have not been systematically assessed because of the limitations of mapping short-read sequencing data1,2. Here we constructed 1:1 unambiguous alignments spanning high-identity SDs across 102 human haplotypes and compared the pattern of SNVs between unique and duplicated regions3,4. We find that human SNVs are elevated 60% in SDs compared to unique regions and estimate that at least 23% of this increase is due to interlocus gene conversion (IGC) with up to 4.3 megabase pairs of SD sequence converted on average per human haplotype. We develop a genome-wide map of IGC donors and acceptors, including 498 acceptor and 454 donor hotspots affecting the exons of about 800 protein-coding genes. These include 171 genes that have 'relocated' on average 1.61 megabase pairs in a subset of human haplotypes. Using a coalescent framework, we show that SD regions are slightly evolutionarily older when compared to unique sequences, probably owing to IGC. SNVs in SDs, however, show a distinct mutational spectrum: a 27.1% increase in transversions that convert cytosine to guanine or the reverse across all triplet contexts and a 7.6% reduction in the frequency of CpG-associated mutations when compared to unique DNA. We reason that these distinct mutational properties help to maintain an overall higher GC content of SD DNA compared to that of unique DNA, probably driven by GC-biased conversion between paralogous sequences5,6.
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Affiliation(s)
- Mitchell R Vollger
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Division of Medical Genetics, University of Washington School of Medicine, Seattle, WA, USA
| | - Philip C Dishuck
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - William T Harvey
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - William S DeWitt
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Computational Biology Program, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley, CA, USA
| | - Xavi Guitart
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Michael E Goldberg
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Allison N Rozanski
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Julian Lucas
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Mobin Asri
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Katherine M Munson
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Alexandra P Lewis
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Kendra Hoekzema
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Glennis A Logsdon
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - David Porubsky
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Benedict Paten
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Kelley Harris
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - PingHsun Hsieh
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Evan E Eichler
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA.
- Howard Hughes Medical Institute, Chevy Chase, MD, USA.
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6
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Genome structure-based Juglandaceae phylogenies contradict alignment-based phylogenies and substitution rates vary with DNA repair genes. Nat Commun 2023; 14:617. [PMID: 36739280 PMCID: PMC9899254 DOI: 10.1038/s41467-023-36247-z] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Accepted: 01/20/2023] [Indexed: 02/06/2023] Open
Abstract
In lineages of allopolyploid origin, sets of homoeologous chromosomes may coexist that differ in gene content and syntenic structure. Presence or absence of genes and microsynteny along chromosomal blocks can serve to differentiate subgenomes and to infer phylogenies. We here apply genome-structural data to infer relationships in an ancient allopolyploid lineage, the walnut family (Juglandaceae), by using seven chromosome-level genomes, two of them newly assembled. Microsynteny and gene-content analyses yield identical topologies that place Platycarya with Engelhardia as did a 1980s morphological-cladistic study. DNA-alignment-based topologies here and in numerous earlier studies instead group Platycarya with Carya and Juglans, perhaps misled by past hybridization. All available data support a hybrid origin of Juglandaceae from extinct or unsampled progenitors nested within, or sister to, Myricaceae. Rhoiptelea chiliantha, sister to all other Juglandaceae, contains proportionally more DNA repair genes and appears to evolve at a rate 2.6- to 3.5-times slower than the remaining species.
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7
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Wang RJ, Al-Saffar SI, Rogers J, Hahn MW. Human generation times across the past 250,000 years. SCIENCE ADVANCES 2023; 9:eabm7047. [PMID: 36608127 PMCID: PMC9821931 DOI: 10.1126/sciadv.abm7047] [Citation(s) in RCA: 23] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
The generation times of our recent ancestors can tell us about both the biology and social organization of prehistoric humans, placing human evolution on an absolute time scale. We present a method for predicting historical male and female generation times based on changes in the mutation spectrum. Our analyses of whole-genome data reveal an average generation time of 26.9 years across the past 250,000 years, with fathers consistently older (30.7 years) than mothers (23.2 years). Shifts in sex-averaged generation times have been driven primarily by changes to the age of paternity, although we report a substantial increase in female generation times in the recent past. We also find a large difference in generation times among populations, reaching back to a time when all humans occupied Africa.
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Affiliation(s)
- Richard J. Wang
- Department of Biology, Indiana University, Bloomington, IN 47405, USA
- Department of Computer Science, Indiana University, Bloomington, IN 47405, USA
- Corresponding author.
| | - Samer I. Al-Saffar
- Department of Computer Science, Indiana University, Bloomington, IN 47405, USA
| | - Jeffrey Rogers
- Human Genome Sequencing Center and Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Matthew W. Hahn
- Department of Biology, Indiana University, Bloomington, IN 47405, USA
- Department of Computer Science, Indiana University, Bloomington, IN 47405, USA
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8
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Paz Sepúlveda PB, Mayordomo AC, Sala C, Sosa EJ, Zaiat JJ, Cuello M, Schwab M, Rodríguez Golpe D, Aquilano E, Santos MR, Dipierri JE, Alfaro Gómez EL, Bravi CM, Muzzio M, Bailliet G. Human Y chromosome sequences from Q Haplogroup reveal a South American settlement pre-18,000 years ago and a profound genomic impact during the Younger Dryas. PLoS One 2022; 17:e0271971. [PMID: 35976870 PMCID: PMC9385064 DOI: 10.1371/journal.pone.0271971] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Accepted: 07/11/2022] [Indexed: 11/18/2022] Open
Abstract
The settlement of the Americas has been the focus of incessant debate for more than 100 years, and open questions regarding the timing and spatial patterns of colonization still remain today. Phylogenetic studies with complete human Y chromosome sequences are used as a highly informative tool to investigate the history of human populations in a given time frame. To study the phylogenetic relationships of Native American lineages and infer the settlement history of the Americas, we analyzed Y chromosome Q Haplogroup, which is a Pan-American haplogroup and represents practically all Native American lineages in Mesoamerica and South America. We built a phylogenetic tree for Q Haplogroup based on 102 whole Y chromosome sequences, of which 13 new Argentine sequences were provided by our group. Moreover, 1,072 new single nucleotide polymorphisms (SNPs) that contribute to its resolution and diversity were identified. Q-M848 is known to be the most frequent autochthonous sub-haplogroup of the Americas. The present is the first genomic study of Q Haplogroup in which current knowledge on Q-M848 sub-lineages is contrasted with the historical, archaeological and linguistic data available. The divergence times, spatial structure and the SNPs found here as novel for Q-Z780, a less frequent sub-haplogroup autochthonous of the Americas, provide genetic support for a South American settlement before 18,000 years ago. We analyzed how environmental events that occurred during the Younger Dryas period may have affected Native American lineages, and found that this event may have caused a substantial loss of lineages. This could explain the current low frequency of Q-Z780 (also perhaps of Q-F4674, a third possible sub-haplogroup autochthonous of the Americas). These environmental events could have acted as a driving force for expansion and diversification of the Q-M848 sub-lineages, which show a spatial structure that developed during the Younger Dryas period.
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Affiliation(s)
- Paula B. Paz Sepúlveda
- Instituto Multidisciplinario de Biología Celular, Universidad Nacional de La Plata, Consejo Nacional de Investigaciones Científicas y Técnicas, Comisión de Investigaciones Científicas, La Plata, Buenos Aires, Argentina
- * E-mail: (PBPS); (MM); (GB)
| | - Andrea Constanza Mayordomo
- Instituto Multidisciplinario de Biología Celular, Universidad Nacional de La Plata, Consejo Nacional de Investigaciones Científicas y Técnicas, Comisión de Investigaciones Científicas, La Plata, Buenos Aires, Argentina
- Programa de Cáncer Hereditario, Hospital Italiano de Buenos Aires, Ciudad Autónoma de Buenos Aires, Buenos Aires, Argentina
| | - Camila Sala
- Instituto Multidisciplinario de Biología Celular, Universidad Nacional de La Plata, Consejo Nacional de Investigaciones Científicas y Técnicas, Comisión de Investigaciones Científicas, La Plata, Buenos Aires, Argentina
| | - Ezequiel Jorge Sosa
- Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Consejo Nacional de Investigaciones Científicas y Técnicas, Ciudad Autónoma de Buenos Aires, Buenos Aires, Argentina
| | - Jonathan Javier Zaiat
- Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Consejo Nacional de Investigaciones Científicas y Técnicas, Ciudad Autónoma de Buenos Aires, Buenos Aires, Argentina
| | - Mariela Cuello
- Instituto Multidisciplinario de Biología Celular, Universidad Nacional de La Plata, Consejo Nacional de Investigaciones Científicas y Técnicas, Comisión de Investigaciones Científicas, La Plata, Buenos Aires, Argentina
| | - Marisol Schwab
- Instituto Multidisciplinario de Biología Celular, Universidad Nacional de La Plata, Consejo Nacional de Investigaciones Científicas y Técnicas, Comisión de Investigaciones Científicas, La Plata, Buenos Aires, Argentina
| | - Daniela Rodríguez Golpe
- Instituto Multidisciplinario de Biología Celular, Universidad Nacional de La Plata, Consejo Nacional de Investigaciones Científicas y Técnicas, Comisión de Investigaciones Científicas, La Plata, Buenos Aires, Argentina
| | - Eliana Aquilano
- Instituto Multidisciplinario de Biología Celular, Universidad Nacional de La Plata, Consejo Nacional de Investigaciones Científicas y Técnicas, Comisión de Investigaciones Científicas, La Plata, Buenos Aires, Argentina
| | - María Rita Santos
- Instituto Multidisciplinario de Biología Celular, Universidad Nacional de La Plata, Consejo Nacional de Investigaciones Científicas y Técnicas, Comisión de Investigaciones Científicas, La Plata, Buenos Aires, Argentina
| | - José Edgardo Dipierri
- Instituto de Biología de la Altura, Facultad de Humanidades y Ciencias Sociales, Universidad Nacional de Jujuy, San Salvador de Jujuy, Jujuy, Argentina
| | - Emma L. Alfaro Gómez
- Instituto de Biología de la Altura, Facultad de Humanidades y Ciencias Sociales, Universidad Nacional de Jujuy, San Salvador de Jujuy, Jujuy, Argentina
- Instituto de Ecorregiones Andinas, Universidad Nacional de Jujuy, San Salvador de Jujuy, Jujuy, Argentina
| | - Claudio M. Bravi
- Instituto Multidisciplinario de Biología Celular, Universidad Nacional de La Plata, Consejo Nacional de Investigaciones Científicas y Técnicas, Comisión de Investigaciones Científicas, La Plata, Buenos Aires, Argentina
- Facultad de Ciencias Naturales y Museo, Universidad Nacional de La Plata, La Plata, Buenos Aires, Argentina
| | - Marina Muzzio
- Instituto Multidisciplinario de Biología Celular, Universidad Nacional de La Plata, Consejo Nacional de Investigaciones Científicas y Técnicas, Comisión de Investigaciones Científicas, La Plata, Buenos Aires, Argentina
- Facultad de Ciencias Naturales y Museo, Universidad Nacional de La Plata, La Plata, Buenos Aires, Argentina
- * E-mail: (PBPS); (MM); (GB)
| | - Graciela Bailliet
- Instituto Multidisciplinario de Biología Celular, Universidad Nacional de La Plata, Consejo Nacional de Investigaciones Científicas y Técnicas, Comisión de Investigaciones Científicas, La Plata, Buenos Aires, Argentina
- * E-mail: (PBPS); (MM); (GB)
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9
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Wang RJ, Raveendran M, Harris RA, Murphy WJ, Lyons LA, Rogers J, Hahn MW. De novo Mutations in Domestic Cat are Consistent with an Effect of Reproductive Longevity on Both the Rate and Spectrum of Mutations. Mol Biol Evol 2022; 39:msac147. [PMID: 35771663 PMCID: PMC9290555 DOI: 10.1093/molbev/msac147] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
The mutation rate is a fundamental evolutionary parameter with direct and appreciable effects on the health and function of individuals. Here, we examine this important parameter in the domestic cat, a beloved companion animal as well as a valuable biomedical model. We estimate a mutation rate of 0.86 × 10-8 per bp per generation for the domestic cat (at an average parental age of 3.8 years). We find evidence for a significant paternal age effect, with more mutations transmitted by older sires. Our analyses suggest that the cat and the human have accrued similar numbers of mutations in the germline before reaching sexual maturity. The per-generation mutation rate in the cat is 28% lower than what has been observed in humans, but is consistent with the shorter generation time in the cat. Using a model of reproductive longevity, which takes into account differences in the reproductive age and time to sexual maturity, we are able to explain much of the difference in per-generation rates between species. We further apply our reproductive longevity model in a novel analysis of mutation spectra and find that the spectrum for the cat resembles the human mutation spectrum at a younger age of reproduction. Together, these results implicate changes in life-history as a driver of mutation rate evolution between species. As the first direct observation of the paternal age effect outside of rodents and primates, our results also suggest a phenomenon that may be universal among mammals.
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Affiliation(s)
- Richard J Wang
- Department of Biology, Indiana University, Bloomington, IN, USA
| | - Muthuswamy Raveendran
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - R Alan Harris
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - William J Murphy
- Veterinary Integrative Biosciences, Texas A&M University, College Station, TX, USA
| | - Leslie A Lyons
- Department of Veterinary Medicine and Surgery, College of Veterinary Medicine, University of Missouri, Columbia, MO, USA
| | - Jeffrey Rogers
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Matthew W Hahn
- Department of Biology, Indiana University, Bloomington, IN, USA
- Department of Computer Science, Indiana University, Bloomington, IN, USA
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10
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Milligan WR, Amster G, Sella G. The impact of genetic modifiers on variation in germline mutation rates within and among human populations. Genetics 2022; 221:6603115. [PMID: 35666194 DOI: 10.1093/genetics/iyac087] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2022] [Accepted: 05/16/2022] [Indexed: 11/14/2022] Open
Abstract
Mutation rates and spectra differ among human populations. Here, we examine whether this variation could be explained by evolution at mutation modifiers. To this end, we consider genetic modifier sites at which mutations, "mutator alleles", increase genome-wide mutation rates and model their evolution under purifying selection due to the additional deleterious mutations that they cause, genetic drift, and demographic processes. We solve the model analytically for a constant population size and characterize how evolution at modifier sites impacts variation in mutation rates within and among populations. We then use simulations to study the effects of modifier sites under a plausible demographic model for Africans and Europeans. When comparing populations that evolve independently, weakly selected modifier sites (2Nes ≈ 1), which evolve slowly, contribute the most to variation in mutation rates. In contrast, when populations recently split from a common ancestral population, strongly selected modifier sites (2Nes » 1), which evolve rapidly, contribute the most to variation between them. Moreover, a modest number of modifier sites (e.g., 10 per mutation type in the standard classification into 96 types) subject to moderate to strong selection (2Nes > 1) could account for the variation in mutation rates observed among human populations. If such modifier sites indeed underlie differences among populations, they should also cause variation in mutation rates within populations and their effects should be detectable in pedigree studies.
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Affiliation(s)
- William R Milligan
- Department of Biological Sciences, Columbia University, New York, NY 10027, USA
| | - Guy Amster
- Department of Biological Sciences, Columbia University, New York, NY 10027, USA.,Flatiron Health Inc., New York, NY 10013, USA
| | - Guy Sella
- Department of Biological Sciences, Columbia University, New York, NY 10027, USA.,Program for Mathematical Genomics, Columbia University, New York, NY 10032, USA
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Different historical generation intervals in human populations inferred from Neanderthal fragment lengths and mutation signatures. Nat Commun 2021; 12:5317. [PMID: 34493715 PMCID: PMC8423828 DOI: 10.1038/s41467-021-25524-4] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2020] [Accepted: 08/13/2021] [Indexed: 12/30/2022] Open
Abstract
After the main Out-of-Africa event, humans interbred with Neanderthals leaving 1–2% of Neanderthal DNA scattered in small fragments in all non-African genomes today. Here we investigate what can be learned about human demographic processes from the size distribution of these fragments. We observe differences in fragment length across Eurasia with 12% longer fragments in East Asians than West Eurasians. Comparisons between extant populations with ancient samples show that these differences are caused by different rates of decay in length by recombination since the Neanderthal admixture. In concordance, we observe a strong correlation between the average fragment length and the mutation accumulation, similar to what is expected by changing the ages at reproduction as estimated from trio studies. Altogether, our results suggest differences in the generation interval across Eurasia, by up 10–20%, over the past 40,000 years. We use sex-specific mutation signatures to infer whether these changes were driven by shifts in either male or female age at reproduction, or both. We also find that previously reported variation in the mutational spectrum may be largely explained by changes to the generation interval. We conclude that Neanderthal fragment lengths provide unique insight into differences among human populations over recent history. Historical interbreeding between Neanderthals and humans should leave signatures of historical demographics in modern human genomes. Analysing the size distribution of Neanderthal fragments in non-African genomes suggests consistent differences in the generation interval across Eurasia, and that this could explain mutational spectrum variation.
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Seplyarskiy VB, Soldatov RA, Koch E, McGinty RJ, Goldmann JM, Hernandez RD, Barnes K, Correa A, Burchard EG, Ellinor PT, McGarvey ST, Mitchell BD, Vasan RS, Redline S, Silverman E, Weiss ST, Arnett DK, Blangero J, Boerwinkle E, He J, Montgomery C, Rao DC, Rotter JI, Taylor KD, Brody JA, Chen YDI, de Las Fuentes L, Hwu CM, Rich SS, Manichaikul AW, Mychaleckyj JC, Palmer ND, Smith JA, Kardia SLR, Peyser PA, Bielak LF, O'Connor TD, Emery LS, Gilissen C, Wong WSW, Kharchenko PV, Sunyaev S. Population sequencing data reveal a compendium of mutational processes in the human germ line. Science 2021; 373:1030-1035. [PMID: 34385354 PMCID: PMC9217108 DOI: 10.1126/science.aba7408] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2019] [Accepted: 07/14/2021] [Indexed: 12/16/2022]
Abstract
Biological mechanisms underlying human germline mutations remain largely unknown. We statistically decompose variation in the rate and spectra of mutations along the genome using volume-regularized nonnegative matrix factorization. The analysis of a sequencing dataset (TOPMed) reveals nine processes that explain the variation in mutation properties between loci. We provide a biological interpretation for seven of these processes. We associate one process with bulky DNA lesions that are resolved asymmetrically with respect to transcription and replication. Two processes track direction of replication fork and replication timing, respectively. We identify a mutagenic effect of active demethylation primarily acting in regulatory regions and a mutagenic effect of long interspersed nuclear elements. We localize a mutagenic process specific to oocytes from population sequencing data. This process appears transcriptionally asymmetric.
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Affiliation(s)
- Vladimir B Seplyarskiy
- Division of Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Ruslan A Soldatov
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Evan Koch
- Division of Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Ryan J McGinty
- Division of Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Jakob M Goldmann
- Department of Human Genetics, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Nijmegen, Netherlands
| | - Ryan D Hernandez
- Quantitative Life Sciences, McGill University, Montreal, QC, Canada
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA, USA
| | - Kathleen Barnes
- Department of Medicine, University of Colorado Denver, Aurora, CO 80045, USA
| | - Adolfo Correa
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
- Department of Pediatrics, University of Mississippi Medical Center, Jackson, MS, USA
- Department of Population Health Science, University of Mississippi Medical Center, Jackson, MS, USA
| | - Esteban G Burchard
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA, USA
- Department of Medicine, University of California, San Francisco, CA, USA
| | - Patrick T Ellinor
- Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Stephen T McGarvey
- International Health Institute, Brown University, Providence, RI, USA
- Department of Epidemiology, Brown University, Providence, RI, USA
- Department of Anthropology, Brown University, Providence, RI, USA
| | - Braxton D Mitchell
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
- Program for Personalized and Genomic Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
- Geriatrics Research and Education Clinical Center, Baltimore Veterans Administration Medical Center, Baltimore, MD, USA
| | - Ramachandran S Vasan
- Department of Medicine, Boston University School of Medicine, Boston, MA, USA
- Framingham Heart Study, Framingham, MA, USA
| | - Susan Redline
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Edwin Silverman
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Scott T Weiss
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Donna K Arnett
- Department of Epidemiology, University of Kentucky, Lexington, KY, USA
| | - John Blangero
- Department of Human Genetics, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
- South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | - Eric Boerwinkle
- University of Texas Health Science Center at Houston, Houston, TX, USA
- Baylor College of Medicine Human Genome Sequencing Center, Houston, TX, USA
| | - Jiang He
- Department of Epidemiology, Tulane University, New Orleans, LA, USA
- Tulane University Translational Science Institute, Tulane University, New Orleans, LA , USA
| | - Courtney Montgomery
- Division of Genomics and Data Science, Department of Arthritis and Clinical Immunology, Oklahoma Medical Research Foundation, Oklahoma City, OK, USA
| | - D C Rao
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Kent D Taylor
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Jennifer A Brody
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Yii-Der Ida Chen
- Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Lisa de Las Fuentes
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
- Department of Medicine, Cardiovascular Division, Washington University School of Medicine, St. Louis, MO, USA
| | - Chii-Min Hwu
- National Yang-Ming University School of Medicine, Taipei, Taiwan
| | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Ani W Manichaikul
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Josyf C Mychaleckyj
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Nicholette D Palmer
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Jennifer A Smith
- Department of Epidemiology, School of Public Health, University of Michigan, 1415 Washington Heights, Ann Arbor, MI 48109-2029, USA
- Survey Research Center, Institute for Social Research, University of Michigan 426 Thompson St, Room Ann Arbor, MI 48104, USA
| | - Sharon L R Kardia
- Survey Research Center, Institute for Social Research, University of Michigan 426 Thompson St, Room Ann Arbor, MI 48104, USA
| | - Patricia A Peyser
- Survey Research Center, Institute for Social Research, University of Michigan 426 Thompson St, Room Ann Arbor, MI 48104, USA
| | - Lawrence F Bielak
- Survey Research Center, Institute for Social Research, University of Michigan 426 Thompson St, Room Ann Arbor, MI 48104, USA
| | - Timothy D O'Connor
- Program for Personalized and Genomic Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA
- University of Maryland Marlene and Stewart Greenebaum Comprehensive Cancer Center, Baltimore, MD, USA
| | - Leslie S Emery
- University of Washington Department of Biostatistics, Seattle, WA 98195, USA
| | - Christian Gilissen
- Department of Human Genetics, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Nijmegen, Netherlands
| | - Wendy S W Wong
- Inova Translational Medicine Institute (ITMI), Inova Health Systems, Falls Church, VA, USA
| | - Peter V Kharchenko
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Shamil Sunyaev
- Division of Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
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13
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DeWitt WS, Harris KD, Ragsdale AP, Harris K. Nonparametric coalescent inference of mutation spectrum history and demography. Proc Natl Acad Sci U S A 2021; 118:e2013798118. [PMID: 34016747 PMCID: PMC8166128 DOI: 10.1073/pnas.2013798118] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
As populations boom and bust, the accumulation of genetic diversity is modulated, encoding histories of living populations in present-day variation. Many methods exist to decode these histories, and all must make strong model assumptions. It is typical to assume that mutations accumulate uniformly across the genome at a constant rate that does not vary between closely related populations. However, recent work shows that mutational processes in human and great ape populations vary across genomic regions and evolve over time. This perturbs the mutation spectrum (relative mutation rates in different local nucleotide contexts). Here, we develop theoretical tools in the framework of Kingman's coalescent to accommodate mutation spectrum dynamics. We present mutation spectrum history inference (mushi), a method to perform nonparametric inference of demographic and mutation spectrum histories from allele frequency data. We use mushi to reconstruct trajectories of effective population size and mutation spectrum divergence between human populations, identify mutation signatures and their dynamics in different human populations, and calibrate the timing of a previously reported mutational pulse in the ancestors of Europeans. We show that mutation spectrum histories can be placed in a well-studied theoretical setting and rigorously inferred from genomic variation data, like other features of evolutionary history.
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Affiliation(s)
- William S DeWitt
- Department of Genome Sciences, University of Washington, Seattle, WA 98195;
- Computational Biology Program, Fred Hutchinson Cancer Research Center, Seattle, WA 98109
| | - Kameron Decker Harris
- Paul G. Allen School of Computer Science & Engineering, University of Washington, Seattle, WA 98195
- Department of Biology, University of Washington, Seattle, WA 98195
| | - Aaron P Ragsdale
- National Laboratory of Genomics for Biodiversity, Unit of Advanced Genomics, Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional, Irapuato, Mexico 36821
| | - Kelley Harris
- Department of Genome Sciences, University of Washington, Seattle, WA 98195;
- Computational Biology Program, Fred Hutchinson Cancer Research Center, Seattle, WA 98109
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