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Versoza CJ, Ehmke EE, Jensen JD, Pfeifer SP. Characterizing the rates and patterns of de novo germline mutations in the aye-aye ( Daubentonia madagascariensis). BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.11.08.622690. [PMID: 39605388 PMCID: PMC11601268 DOI: 10.1101/2024.11.08.622690] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 11/29/2024]
Abstract
Given the many levels of biological variation in mutation rates observed to date in primates - spanning from species to individuals to genomic regions - future steps in our understanding of mutation rate evolution will be aided by both a greater breadth of species coverage across the primate clade, but also by a greater depth as afforded by an evaluation of multiple trios within individual species. In order to help bridge these gaps, we here present an analysis of a species representing one of the most basal splits on the primate tree (aye-ayes), combining whole-genome sequencing of seven parent-offspring trios from a three-generation pedigree with a novel computational pipeline that takes advantage of recently developed pan-genome graphs, thereby circumventing the application of (highly subjective) quality metrics that has previously been shown to result in notable differences in the detection of de novo mutations, and ultimately estimates of mutation rates. This deep sampling has enabled both a detailed picture of parental age effects as well as sex dependency in mutation rates which we here compare with previously studied primates, but has also provided unique insights into the nature of genetic variation in one of the most endangered primates on the planet.
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Affiliation(s)
- Cyril J. Versoza
- Center for Evolution and Medicine, School of Life Sciences, Arizona State University, Tempe, AZ, USA
| | | | - Jeffrey D. Jensen
- Center for Evolution and Medicine, School of Life Sciences, Arizona State University, Tempe, AZ, USA
| | - Susanne P. Pfeifer
- Center for Evolution and Medicine, School of Life Sciences, Arizona State University, Tempe, AZ, USA
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2
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Dittrich M, Bernhardt L, Penfold CA, Boroviak TE, Drummer C, Behr R, Müller T, Haaf T. Age-related and species-specific methylation changes in the protein-coding marmoset sperm epigenome. Aging Cell 2024; 23:e14200. [PMID: 38757354 PMCID: PMC11320356 DOI: 10.1111/acel.14200] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2024] [Revised: 04/10/2024] [Accepted: 04/26/2024] [Indexed: 05/18/2024] Open
Abstract
The sperm epigenome is thought to affect the developmental programming of the resulting embryo, influencing health and disease in later life. Age-related methylation changes in the sperm of old fathers may mediate the increased risks for reproductive and offspring medical problems. The impact of paternal age on sperm methylation has been extensively studied in humans and, to a lesser extent, in rodents and cattle. Here, we performed a comparative analysis of paternal age effects on protein-coding genes in the human and marmoset sperm methylomes. The marmoset has gained growing importance as a non-human primate model of aging and age-related diseases. Using reduced representation bisulfite sequencing, we identified age-related differentially methylated transcription start site (ageTSS) regions in 204 marmoset and 27 human genes. The direction of methylation changes was the opposite, increasing with age in marmosets and decreasing in humans. None of the identified ageTSS was differentially methylated in both species. Although the average methylation levels of all TSS regions were highly correlated between marmosets and humans, with the majority of TSS being hypomethylated in sperm, more than 300 protein-coding genes were endowed with species-specifically (hypo)methylated TSS. Several genes of the glycosphingolipid (GSL) biosynthesis pathway, which plays a role in embryonic stem cell differentiation and regulation of development, were hypomethylated (<5%) in human and fully methylated (>95%) in marmoset sperm. The expression levels and patterns of defined sets of GSL genes differed considerably between human and marmoset pre-implantation embryo stages and blastocyst tissues, respectively.
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Affiliation(s)
- Marcus Dittrich
- Institute of Human GeneticsJulius Maximilians UniversityWürzburgGermany
- Department of BioinformaticsJulius Maximilians UniversityWürzburgGermany
| | - Laura Bernhardt
- Institute of Human GeneticsJulius Maximilians UniversityWürzburgGermany
| | - Christopher A. Penfold
- Department of Physiology, Development and NeuroscienceUniversity of CambridgeCambridgeUK
- Centre for Trophoblast ResearchUniversity of CambridgeCambridgeUK
| | - Thorsten E. Boroviak
- Department of Physiology, Development and NeuroscienceUniversity of CambridgeCambridgeUK
- Centre for Trophoblast ResearchUniversity of CambridgeCambridgeUK
- Wellcome Trust – Medical Research Council Stem Cell Institute, Jeffrey Cheah Biomedical CentreUniversity of CambridgeCambridgeUK
| | - Charis Drummer
- Platform Degenerative DiseasesGerman Primate Center‐Leibniz Institute for Primate ResearchGöttingenGermany
- DZHK (German Centre for Cardiovascular Research)GöttingenGermany
| | - Rüdiger Behr
- Platform Degenerative DiseasesGerman Primate Center‐Leibniz Institute for Primate ResearchGöttingenGermany
- DZHK (German Centre for Cardiovascular Research)GöttingenGermany
| | - Tobias Müller
- Department of BioinformaticsJulius Maximilians UniversityWürzburgGermany
| | - Thomas Haaf
- Institute of Human GeneticsJulius Maximilians UniversityWürzburgGermany
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3
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Pfeifer SP, Baxter A, Savidge LE, Sedlazeck FJ, Bales KL. De Novo Genome Assembly for the Coppery Titi Monkey (Plecturocebus cupreus): An Emerging Nonhuman Primate Model for Behavioral Research. Genome Biol Evol 2024; 16:evae108. [PMID: 38758096 PMCID: PMC11140417 DOI: 10.1093/gbe/evae108] [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: 04/09/2024] [Revised: 05/07/2024] [Accepted: 05/09/2024] [Indexed: 05/18/2024] Open
Abstract
The coppery titi monkey (Plecturocebus cupreus) is an emerging nonhuman primate model system for behavioral and neurobiological research. At the same time, the almost entire absence of genomic resources for the species has hampered insights into the genetic underpinnings of the phenotypic traits of interest. To facilitate future genotype-to-phenotype studies, we here present a high-quality, fully annotated de novo genome assembly for the species with chromosome-length scaffolds spanning the autosomes and chromosome X (scaffold N50 = 130.8 Mb), constructed using data obtained from several orthologous short- and long-read sequencing and scaffolding techniques. With a base-level accuracy of ∼99.99% in chromosome-length scaffolds as well as benchmarking universal single-copy ortholog and k-mer completeness scores of >99.0% and 95.1% at the genome level, this assembly represents one of the most complete Pitheciidae genomes to date, making it an invaluable resource for comparative evolutionary genomics research to improve our understanding of lineage-specific changes underlying adaptive traits as well as deleterious mutations associated with disease.
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Affiliation(s)
- Susanne P Pfeifer
- School of Life Sciences, Arizona State University, Tempe, AZ, USA
- Center for Evolution and Medicine, Arizona State University, Tempe, AZ, USA
| | - Alexander Baxter
- Department of Psychology, University of California, Davis, CA, USA
- California National Primate Research Center, Neuroscience and Behavior Division, Davis, CA, USA
| | - Logan E Savidge
- Department of Psychology, University of California, Davis, CA, USA
- California National Primate Research Center, Neuroscience and Behavior Division, Davis, CA, USA
| | - Fritz J Sedlazeck
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Karen L Bales
- Department of Psychology, University of California, Davis, CA, USA
- California National Primate Research Center, Neuroscience and Behavior Division, Davis, CA, USA
- Department of Neurobiology, Physiology, and Behavior, University of California, Davis, CA, USA
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4
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Mikhaylova V, Rzepka M, Kawamura T, Xia Y, Chang PL, Zhou S, Paasch A, Pham L, Modi N, Yao L, Perez-Agustin A, Pagans S, Boles TC, Lei M, Wang Y, Garcia-Bassets I, Chen Z. Targeted phasing of 2-200 kilobase DNA fragments with a short-read sequencer and a single-tube linked-read library method. Sci Rep 2024; 14:7988. [PMID: 38580715 PMCID: PMC10997766 DOI: 10.1038/s41598-024-58733-0] [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: 08/15/2023] [Accepted: 04/02/2024] [Indexed: 04/07/2024] Open
Abstract
In the human genome, heterozygous sites refer to genomic positions with a different allele or nucleotide variant on the maternal and paternal chromosomes. Resolving these allelic differences by chromosomal copy, also known as phasing, is achievable on a short-read sequencer when using a library preparation method that captures long-range genomic information. TELL-Seq is a library preparation that captures long-range genomic information with the aid of molecular identifiers (barcodes). The same barcode is used to tag the reads derived from the same long DNA fragment within a range of up to 200 kilobases (kb), generating linked-reads. This strategy can be used to phase an entire genome. Here, we introduce a TELL-Seq protocol developed for targeted applications, enabling the phasing of enriched loci of varying sizes, purity levels, and heterozygosity. To validate this protocol, we phased 2-200 kb loci enriched with different methods: CRISPR/Cas9-mediated excision coupled with pulse-field electrophoresis for the longest fragments, CRISPR/Cas9-mediated protection from exonuclease digestion for mid-size fragments, and long PCR for the shortest fragments. All selected loci have known clinical relevance: BRCA1, BRCA2, MLH1, MSH2, MSH6, APC, PMS2, SCN5A-SCN10A, and PKI3CA. Collectively, the analyses show that TELL-Seq can accurately phase 2-200 kb targets using a short-read sequencer.
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Affiliation(s)
| | - Madison Rzepka
- Universal Sequencing Technology Corp., Carlsbad, CA, 92011, USA
| | | | - Yu Xia
- Universal Sequencing Technology Corp., Carlsbad, CA, 92011, USA
| | - Peter L Chang
- Universal Sequencing Technology Corp., Carlsbad, CA, 92011, USA
| | | | - Amber Paasch
- Universal Sequencing Technology Corp., Carlsbad, CA, 92011, USA
| | - Long Pham
- Universal Sequencing Technology Corp., Carlsbad, CA, 92011, USA
| | - Naisarg Modi
- Universal Sequencing Technology Corp., Carlsbad, CA, 92011, USA
| | - Likun Yao
- Department of Medicine, University of California, San Diego, La Jolla, CA, 92093, USA
| | - Adrian Perez-Agustin
- Department of Medical Sciences, School of Medicine, University of Girona, Girona, Spain
| | - Sara Pagans
- Department of Medical Sciences, School of Medicine, University of Girona, Girona, Spain
| | | | - Ming Lei
- Universal Sequencing Technology Corp., Canton, MA, 02021, USA
| | - Yong Wang
- Universal Sequencing Technology Corp., Canton, MA, 02021, USA
| | | | - Zhoutao Chen
- Universal Sequencing Technology Corp., Carlsbad, CA, 92011, USA.
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Jia H, Lin J, Lin Z, Wang Y, Xu L, Ding W, Ming R. Haplotype-resolved genome of Mimosa bimucronata revealed insights into leaf movement and nitrogen fixation. BMC Genomics 2024; 25:334. [PMID: 38570736 PMCID: PMC10993578 DOI: 10.1186/s12864-024-10264-8] [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: 11/09/2023] [Accepted: 03/27/2024] [Indexed: 04/05/2024] Open
Abstract
BACKGROUND Mimosa bimucronata originates from tropical America and exhibits distinctive leaf movement characterized by a relative slow speed. Additionally, this species possesses the ability to fix nitrogen. Despite these intriguing traits, comprehensive studies have been hindered by the lack of genomic resources for M. bimucronata. RESULTS To unravel the intricacies of leaf movement and nitrogen fixation, we successfully assembled a high-quality, haplotype-resolved, reference genome at the chromosome level, spanning 648 Mb and anchored in 13 pseudochromosomes. A total of 32,146 protein-coding genes were annotated. In particular, haplotype A was annotated with 31,035 protein-coding genes, and haplotype B with 31,440 protein-coding genes. Structural variations (SVs) and allele specific expression (ASE) analyses uncovered the potential role of structural variants in leaf movement and nitrogen fixation in M. bimucronata. Two whole-genome duplication (WGD) events were detected, that occurred ~ 2.9 and ~ 73.5 million years ago. Transcriptome and co-expression network analyses revealed the involvement of aquaporins (AQPs) and Ca2+-related ion channel genes in leaf movement. Moreover, we also identified nodulation-related genes and analyzed the structure and evolution of the key gene NIN in the process of symbiotic nitrogen fixation (SNF). CONCLUSION The detailed comparative genomic and transcriptomic analyses provided insights into the mechanisms governing leaf movement and nitrogen fixation in M. bimucronata. This research yielded genomic resources and provided an important reference for functional genomic studies of M. bimucronata and other legume species.
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Affiliation(s)
- Haifeng Jia
- College of Agriculture, Center for Genomics and Biotechnology, Fujian Agriculture and Forestry University, Fuzhou, 350002, China
| | - Jishan Lin
- National Key Laboratory for Tropical Crop Breeding, Institute of Tropical Bioscience and Biotechnology, Chinese Academy of Tropical Agricultural Sciences, Haikou, 570100, China
| | - Zhicong Lin
- College of Environment and Biological Engineering, Putian University, Putian, 351100, China
| | - Yibin Wang
- Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China
| | - Liangwei Xu
- College of Agriculture, Center for Genomics and Biotechnology, Fujian Agriculture and Forestry University, Fuzhou, 350002, China
- College of Life Science, Fujian Agriculture and Forestry University, Fuzhou, 350002, China
| | - Wenjie Ding
- College of Agriculture, Center for Genomics and Biotechnology, Fujian Agriculture and Forestry University, Fuzhou, 350002, China
- College of Life Science, Fujian Agriculture and Forestry University, Fuzhou, 350002, China
| | - Ray Ming
- College of Agriculture, Center for Genomics and Biotechnology, Fujian Agriculture and Forestry University, Fuzhou, 350002, China.
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6
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Drzewiecki CM, Fox AS. Understanding the heterogeneity of anxiety using a translational neuroscience approach. COGNITIVE, AFFECTIVE & BEHAVIORAL NEUROSCIENCE 2024; 24:228-245. [PMID: 38356013 PMCID: PMC11039504 DOI: 10.3758/s13415-024-01162-3] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 01/14/2024] [Indexed: 02/16/2024]
Abstract
Anxiety disorders affect millions of people worldwide and present a challenge in neuroscience research because of their substantial heterogeneity in clinical presentation. While a great deal of progress has been made in understanding the neurobiology of fear and anxiety, these insights have not led to effective treatments. Understanding the relationship between phenotypic heterogeneity and the underlying biology is a critical first step in solving this problem. We show translation, reverse translation, and computational modeling can contribute to a refined, cross-species understanding of fear and anxiety as well as anxiety disorders. More specifically, we outline how animal models can be leveraged to develop testable hypotheses in humans by using targeted, cross-species approaches and ethologically informed behavioral paradigms. We discuss reverse translational approaches that can guide and prioritize animal research in nontraditional research species. Finally, we advocate for the use of computational models to harmonize cross-species and cross-methodology research into anxiety. Together, this translational neuroscience approach will help to bridge the widening gap between how we currently conceptualize and diagnose anxiety disorders, as well as aid in the discovery of better treatments for these conditions.
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Affiliation(s)
- Carly M Drzewiecki
- California National Primate Research Center, University of California, Davis, CA, USA.
| | - Andrew S Fox
- California National Primate Research Center, University of California, Davis, CA, USA.
- Department of Psychology, University of California, Davis, CA, USA.
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7
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Mao Y, Harvey WT, Porubsky D, Munson KM, Hoekzema K, Lewis AP, Audano PA, Rozanski A, Yang X, Zhang S, Yoo D, Gordon DS, Fair T, Wei X, Logsdon GA, Haukness M, Dishuck PC, Jeong H, Del Rosario R, Bauer VL, Fattor WT, Wilkerson GK, Mao Y, Shi Y, Sun Q, Lu Q, Paten B, Bakken TE, Pollen AA, Feng G, Sawyer SL, Warren WC, Carbone L, Eichler EE. Structurally divergent and recurrently mutated regions of primate genomes. Cell 2024; 187:1547-1562.e13. [PMID: 38428424 PMCID: PMC10947866 DOI: 10.1016/j.cell.2024.01.052] [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: 03/28/2023] [Revised: 11/26/2023] [Accepted: 01/31/2024] [Indexed: 03/03/2024]
Abstract
We sequenced and assembled using multiple long-read sequencing technologies the genomes of chimpanzee, bonobo, gorilla, orangutan, gibbon, macaque, owl monkey, and marmoset. We identified 1,338,997 lineage-specific fixed structural variants (SVs) disrupting 1,561 protein-coding genes and 136,932 regulatory elements, including the most complete set of human-specific fixed differences. We estimate that 819.47 Mbp or ∼27% of the genome has been affected by SVs across primate evolution. We identify 1,607 structurally divergent regions wherein recurrent structural variation contributes to creating SV hotspots where genes are recurrently lost (e.g., CARD, C4, and OLAH gene families) and additional lineage-specific genes are generated (e.g., CKAP2, VPS36, ACBD7, and NEK5 paralogs), becoming targets of rapid chromosomal diversification and positive selection (e.g., RGPD gene family). High-fidelity long-read sequencing has made these dynamic regions of the genome accessible for sequence-level analyses within and between primate species.
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Affiliation(s)
- Yafei Mao
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA; Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China.
| | - William T Harvey
- 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
| | - Katherine M Munson
- 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
| | - Alexandra P Lewis
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Peter A Audano
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Allison Rozanski
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Xiangyu Yang
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Shilong Zhang
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - DongAhn Yoo
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - David S Gordon
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA; Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA
| | - Tyler Fair
- Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA, USA
| | - Xiaoxi Wei
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Glennis A Logsdon
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Marina Haukness
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Philip C Dishuck
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Hyeonsoo Jeong
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Ricardo Del Rosario
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Vanessa L Bauer
- BioFrontiers Institute, Department of Molecular, Cellular, and Developmental Biology, University of Colorado, Bouder, CO, USA
| | - Will T Fattor
- BioFrontiers Institute, Department of Molecular, Cellular, and Developmental Biology, University of Colorado, Bouder, CO, USA
| | - Gregory K Wilkerson
- Department of Veterinary Sciences, Michale E. Keeling Center for Comparative Medicine and Research, The University of Texas MD Anderson Cancer Center, Bastrop, TX, USA; Department of Clinical Sciences, North Carolina State University, Raleigh, NC, USA
| | - Yuxiang Mao
- Institute of Neuroscience, State Key Laboratory of Neuroscience, Center for Excellence in Brain Science & Intelligence Technology, Chinese Academy of Sciences, Shanghai, China; Shanghai Center for Brain Science and Brain-Inspired Intelligence Technology, Shanghai, China
| | - Yongyong Shi
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China; Institute of Neuroscience, State Key Laboratory of Neuroscience, Center for Excellence in Brain Science & Intelligence Technology, Chinese Academy of Sciences, Shanghai, China; Shanghai Center for Brain Science and Brain-Inspired Intelligence Technology, Shanghai, China
| | - Qiang Sun
- Institute of Neuroscience, State Key Laboratory of Neuroscience, Center for Excellence in Brain Science & Intelligence Technology, Chinese Academy of Sciences, Shanghai, China; Shanghai Center for Brain Science and Brain-Inspired Intelligence Technology, Shanghai, China
| | - Qing Lu
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Benedict Paten
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | | | - Alex A Pollen
- Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA, USA; Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Guoping Feng
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Sara L Sawyer
- BioFrontiers Institute, Department of Molecular, Cellular, and Developmental Biology, University of Colorado, Bouder, CO, USA
| | - Wesley C Warren
- Department of Animal Sciences, Bond Life Sciences Center, University of Missouri, Columbia, MO, USA; Department of Surgery, School of Medicine, University of Missouri, Columbia, MO, USA; Institute of Data Science and Informatics, University of Missouri, Columbia, MO, USA
| | - Lucia Carbone
- Department of Medicine, Knight Cardiovascular Institute, Oregon Health and Science University, Portland, OR, USA; Division of Genetics, Oregon National Primate Research Center, Beaverton, OR, USA; Department of Molecular and Medical Genetics, Oregon Health and Science University, Portland, OR, USA; Department of Medical Informatics and Clinical Epidemiology, Oregon Health and Science University, Portland, OR, USA
| | - Evan E Eichler
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA; Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA.
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Liao BY, Weng MP, Chang TY, Chang AYF, Ching YH, Wu CH. Degeneration of the Olfactory System in a Murid Rodent that Evolved Diurnalism. Mol Biol Evol 2024; 41:msae037. [PMID: 38376543 PMCID: PMC10906987 DOI: 10.1093/molbev/msae037] [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: 10/19/2022] [Revised: 01/03/2024] [Accepted: 02/13/2024] [Indexed: 02/21/2024] Open
Abstract
In mammalian research, it has been debated what can initiate an evolutionary tradeoff between different senses, and the phenomenon of sensory tradeoff in rodents, the most abundant mammalian clade, is not evident. The Nile rat (Arvicanthis niloticus), a murid rodent, recently adapted to a diurnal niche through an evolutionary acquisition of daylight vision with enhanced visual acuity. As such, this model provides an opportunity for a cross-species investigation where comparative morphological and multi-omic analyses of the Nile rat are made with its closely related nocturnal species, e.g. the mouse (Mus musculus) and the rat (Rattus norvegicus). Thus, morphological examinations were performed, and evolutionary reductions in relative sizes of turbinal bone surfaces, the cribriform plate, and the olfactory bulb were discovered in Nile rats. Subsequently, we compared multiple murid genomes, and profiled olfactory epithelium transcriptomes of mice and Nile rats at various ages with RNA sequencing. The results further demonstrate that, in comparison with mouse olfactory receptor (OR) genes, Nile rat OR genes have experienced less frequent gain, more frequent loss, and more frequent expression reduction during their evolution. Furthermore, functional degeneration of coding sequences in the Nile rat lineage was found in OR genes, yet not in other genes. Taken together, these results suggest that acquisition of improved vision in the Nile rat has been accompanied by degeneration of both olfaction-related anatomical structures and OR gene repertoires, consistent with the hypothesis of an olfaction-vision tradeoff initiated by the switch from a nocturnal to a diurnal lifestyle in mammals.
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Affiliation(s)
- Ben-Yang Liao
- Institute of Population Health Sciences, National Health Research Institutes, Taiwan, Republic of China
| | - Meng-Pin Weng
- Institute of Population Health Sciences, National Health Research Institutes, Taiwan, Republic of China
| | - Ting-Yan Chang
- Institute of Population Health Sciences, National Health Research Institutes, Taiwan, Republic of China
| | - Andrew Ying-Fei Chang
- Institute of Population Health Sciences, National Health Research Institutes, Taiwan, Republic of China
| | - Yung-Hao Ching
- Department of Molecular Biology and Human Genetics, Tzu Chi University, Taiwan, Republic of China
| | - Chia-Hwa Wu
- Laboratory Animal Center, National Health Research Institutes, Taiwan, Republic of China
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9
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Li Q, Calhoun VD, Iraji A. Revealing complex functional topology brain network correspondences between humans and marmosets. Neurosci Lett 2024; 822:137624. [PMID: 38218321 DOI: 10.1016/j.neulet.2024.137624] [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: 09/22/2023] [Revised: 11/29/2023] [Accepted: 01/01/2024] [Indexed: 01/15/2024]
Abstract
Functional correspondences are known to exist within the brains of both human and non-human primates however, our understanding of this phenomenon remains largely incomplete. The examination of the topological characteristics inherent in whole-brain functional connectivity bears immense promise in elucidating shared as well as distinctive patterns across different species. In this investigation, we applied topological graph analysis to brain networks and scrutinized the congruencies and disparities within the connectomes of human and marmoset monkey brains. The findings brought to light noteworthy similarities in functional connectivity patterns distributed across the entire brain, with a particular emphasis on the dorsal attention network, default mode network and visual network. Moreover, we discerned unique neural connections between humans and marmosets during both resting and task-oriented states. In essence, our study reveals a combination of shared and divergent functional brain connections underlying spontaneous and specific cognitive functions across these two species.
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Affiliation(s)
- Qiang Li
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA 30303, USA.
| | - Vince D Calhoun
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA 30303, USA
| | - Armin Iraji
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA 30303, USA
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10
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Harris RA, Raveendran M, Warren W, LaDeana HW, Tomlinson C, Graves-Lindsay T, Green RE, Schmidt JK, Colwell JC, Makulec AT, Cole SA, Cheeseman IH, Ross CN, Capuano S, Eichler EE, Levine JE, Rogers J. Whole Genome Analysis of SNV and Indel Polymorphism in Common Marmosets ( Callithrix jacchus). Genes (Basel) 2023; 14:2185. [PMID: 38137007 PMCID: PMC10742769 DOI: 10.3390/genes14122185] [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: 11/08/2023] [Revised: 11/27/2023] [Accepted: 11/29/2023] [Indexed: 12/24/2023] Open
Abstract
The common marmoset (Callithrix jacchus) is one of the most widely used nonhuman primate models of human disease. Owing to limitations in sequencing technology, early genome assemblies of this species using short-read sequencing suffered from gaps. In addition, the genetic diversity of the species has not yet been adequately explored. Using long-read genome sequencing and expert annotation, we generated a high-quality genome resource creating a 2.898 Gb marmoset genome in which most of the euchromatin portion is assembled contiguously (contig N50 = 25.23 Mbp, scaffold N50 = 98.2 Mbp). We then performed whole genome sequencing on 84 marmosets sampling the genetic diversity from several marmoset research centers. We identified a total of 19.1 million single nucleotide variants (SNVs), of which 11.9 million can be reliably mapped to orthologous locations in the human genome. We also observed 2.8 million small insertion/deletion variants. This dataset includes an average of 5.4 million SNVs per marmoset individual and a total of 74,088 missense variants in protein-coding genes. Of the 4956 variants orthologous to human ClinVar SNVs (present in the same annotated gene and with the same functional consequence in marmoset and human), 27 have a clinical significance of pathogenic and/or likely pathogenic. This important marmoset genomic resource will help guide genetic analyses of natural variation, the discovery of spontaneous functional variation relevant to human disease models, and the development of genetically engineered marmoset disease models.
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Affiliation(s)
- R. Alan Harris
- Human Genome Sequencing Center and Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA; (R.A.H.); (M.R.)
| | - Muthuswamy Raveendran
- Human Genome Sequencing Center and Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA; (R.A.H.); (M.R.)
| | - Wes Warren
- Bond Life Sciences Center, University of Missouri, Columbia, MO 65211, USA;
| | - Hillier W. LaDeana
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA 98104, USA; (H.W.L.); (E.E.E.)
| | - Chad Tomlinson
- McDonnell Genome Institute, Washington University, St. Louis, MO 63108, USA; (C.T.); (T.G.-L.)
| | - Tina Graves-Lindsay
- McDonnell Genome Institute, Washington University, St. Louis, MO 63108, USA; (C.T.); (T.G.-L.)
| | - Richard E. Green
- Department of Biomolecular Engineering, University of California, Santa Cruz, CA 95064, USA;
| | - Jenna K. Schmidt
- Wisconsin National Primate Research Center, University of Wisconsin, Madison, WI 53715, USA; (J.K.S.); (J.C.C.); (A.T.M.); (S.C.III); (J.E.L.)
| | - Julia C. Colwell
- Wisconsin National Primate Research Center, University of Wisconsin, Madison, WI 53715, USA; (J.K.S.); (J.C.C.); (A.T.M.); (S.C.III); (J.E.L.)
| | - Allison T. Makulec
- Wisconsin National Primate Research Center, University of Wisconsin, Madison, WI 53715, USA; (J.K.S.); (J.C.C.); (A.T.M.); (S.C.III); (J.E.L.)
| | - Shelley A. Cole
- Southwest National Primate Research Center, Texas Biomedical Research Institute, San Antonio, TX 78227, USA; (S.A.C.); (I.H.C.); (C.N.R.)
| | - Ian H. Cheeseman
- Southwest National Primate Research Center, Texas Biomedical Research Institute, San Antonio, TX 78227, USA; (S.A.C.); (I.H.C.); (C.N.R.)
| | - Corinna N. Ross
- Southwest National Primate Research Center, Texas Biomedical Research Institute, San Antonio, TX 78227, USA; (S.A.C.); (I.H.C.); (C.N.R.)
| | - Saverio Capuano
- Wisconsin National Primate Research Center, University of Wisconsin, Madison, WI 53715, USA; (J.K.S.); (J.C.C.); (A.T.M.); (S.C.III); (J.E.L.)
| | - Evan E. Eichler
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA 98104, USA; (H.W.L.); (E.E.E.)
- Howard Hughes Medical Institute, University of Washington, Seattle, WA 98195, USA
| | - Jon E. Levine
- Wisconsin National Primate Research Center, University of Wisconsin, Madison, WI 53715, USA; (J.K.S.); (J.C.C.); (A.T.M.); (S.C.III); (J.E.L.)
| | - Jeffrey Rogers
- Human Genome Sequencing Center and Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA; (R.A.H.); (M.R.)
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11
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Delorean EE, Youngblood RC, Simpson SA, Schoonmaker AN, Scheffler BE, Rutter WB, Hulse-Kemp AM. Representing true plant genomes: haplotype-resolved hybrid pepper genome with trio-binning. FRONTIERS IN PLANT SCIENCE 2023; 14:1184112. [PMID: 38034563 PMCID: PMC10687446 DOI: 10.3389/fpls.2023.1184112] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/11/2023] [Accepted: 10/17/2023] [Indexed: 12/02/2023]
Abstract
As sequencing costs decrease and availability of high fidelity long-read sequencing increases, generating experiment specific de novo genome assemblies becomes feasible. In many crop species, obtaining the genome of a hybrid or heterozygous individual is necessary for systems that do not tolerate inbreeding or for investigating important biological questions, such as hybrid vigor. However, most genome assembly methods that have been used in plants result in a merged single sequence representation that is not a true biologically accurate representation of either haplotype within a diploid individual. The resulting genome assembly is often fragmented and exhibits a mosaic of the two haplotypes, referred to as haplotype-switching. Important haplotype level information, such as causal mutations and structural variation is therefore lost causing difficulties in interpreting downstream analyses. To overcome this challenge, we have applied a method developed for animal genome assembly called trio-binning to an intra-specific hybrid of chili pepper (Capsicum annuum L. cv. HDA149 x Capsicum annuum L. cv. HDA330). We tested all currently available softwares for performing trio-binning, combined with multiple scaffolding technologies including Bionano to determine the optimal method of producing the best haplotype-resolved assembly. Ultimately, we produced highly contiguous biologically true haplotype-resolved genome assemblies for each parent, with scaffold N50s of 266.0 Mb and 281.3 Mb, with 99.6% and 99.8% positioned into chromosomes respectively. The assemblies captured 3.10 Gb and 3.12 Gb of the estimated 3.5 Gb chili pepper genome size. These assemblies represent the complete genome structure of the intraspecific hybrid, as well as the two parental genomes, and show measurable improvements over the currently available reference genomes. Our manuscript provides a valuable guide on how to apply trio-binning to other plant genomes.
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Affiliation(s)
- Emily E. Delorean
- Genomics and Bioinformatics Research Unit, USDA-ARS, Raleigh, NC, United States
- Crop and Soil Sciences Department, North Carolina State University, Raleigh, NC, United States
| | - Ramey C. Youngblood
- Institute for Genomics, Biocomputing and Biotechnology, Mississippi State University, Starkville, MS, United States
| | - Sheron A. Simpson
- Genomics and Bioinformatics Research Unit, United States Department of Agriculture - Agriculture Research Service (USDA-ARS), Stoneville, MS, United States
| | - Ashley N. Schoonmaker
- Crop and Soil Sciences Department, North Carolina State University, Raleigh, NC, United States
| | - Brian E. Scheffler
- Genomics and Bioinformatics Research Unit, United States Department of Agriculture - Agriculture Research Service (USDA-ARS), Stoneville, MS, United States
| | - William B. Rutter
- US Vegetable Laboratory, United States Department of Agriculture - Agriculture Research Service (USDA-ARS), Charleston, SC, United States
| | - Amanda M. Hulse-Kemp
- Genomics and Bioinformatics Research Unit, USDA-ARS, Raleigh, NC, United States
- Crop and Soil Sciences Department, North Carolina State University, Raleigh, NC, United States
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12
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Yang X, Mao Y, Wang XK, Ma DN, Xu Z, Gong N, Henning B, Zhang X, He G, Shi YY, Eichler EE, Li ZQ, Takahashi E, Li WD. Population genetics of marmosets in Asian primate research centers and loci associated with epileptic risk revealed by whole-genome sequencing. Zool Res 2023; 44:837-847. [PMID: 37501399 PMCID: PMC10559097 DOI: 10.24272/j.issn.2095-8137.2022.514] [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: 04/23/2023] [Accepted: 07/26/2023] [Indexed: 07/29/2023] Open
Abstract
The common marmoset ( Callithrix jacchus) has emerged as a valuable nonhuman primate model in biomedical research with the recent release of high-quality reference genome assemblies. Epileptic marmosets have been independently reported in two Asian primate research centers. Nevertheless, the population genetics within these primate centers and the specific genetic variants associated with epilepsy in marmosets have not yet been elucidated. Here, we characterized the genetic relationships and risk variants for epilepsy in 41 samples from two epileptic marmoset pedigrees using whole-genome sequencing. We identified 14 558 184 single nucleotide polymorphisms (SNPs) from the 41 samples and found higher chimerism levels in blood samples than in fingernail samples. Genetic analysis showed fourth-degree of relatedness among marmosets at the primate centers. In addition, SNP and copy number variation (CNV) analyses suggested that the WW domain-containing oxidoreductase ( WWOX) and Tyrosine-protein phosphatase nonreceptor type 21 ( PTPN21) genes may be associated with epilepsy in marmosets. Notably, KCTD18-like gene deletion was more common in epileptic marmosets than control marmosets. This study provides valuable population genomic resources for marmosets in two Asian primate centers. Genetic analyses identified a reasonable breeding strategy for genetic diversity maintenance in the two centers, while the case-control study revealed potential risk genes/variants associated with epilepsy in marmosets.
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Affiliation(s)
- XiangYu Yang
- Bio-X Institutes, Key Laboratory for the Genetics of Development and Neuropsychiatric Disorders (Ministry of Education), Shanghai Key Laboratory of Psychotic Disorders, and Brain Science and Technology Research Center, Shanghai Jiao Tong University, Shanghai 200240, China
- Institute of Psychology and Behavioral Science, Shanghai Jiao Tong University, Shanghai 200030, China
- WLA Laboratories, World Laureates Association, Shanghai 201203, China
| | - YaFei Mao
- Bio-X Institutes, Key Laboratory for the Genetics of Development and Neuropsychiatric Disorders (Ministry of Education), Shanghai Key Laboratory of Psychotic Disorders, and Brain Science and Technology Research Center, Shanghai Jiao Tong University, Shanghai 200240, China
- Department of Genome Sciences, University of Washington School of Medicine, Seattle WA 98195, USA
| | - Xuan-Kai Wang
- Bio-X Institutes, Key Laboratory for the Genetics of Development and Neuropsychiatric Disorders (Ministry of Education), Shanghai Key Laboratory of Psychotic Disorders, and Brain Science and Technology Research Center, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Dong-Ni Ma
- Bio-X Institutes, Key Laboratory for the Genetics of Development and Neuropsychiatric Disorders (Ministry of Education), Shanghai Key Laboratory of Psychotic Disorders, and Brain Science and Technology Research Center, Shanghai Jiao Tong University, Shanghai 200240, China
- WLA Laboratories, World Laureates Association, Shanghai 201203, China
| | - Zhen Xu
- Institute of Neuroscience, Key Laboratory of Primate Neurobiology, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China
| | - Neng Gong
- Institute of Neuroscience, Key Laboratory of Primate Neurobiology, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China
| | - Barbara Henning
- Department of Genome Sciences, University of Washington School of Medicine, Seattle WA 98195, USA
| | - Xu Zhang
- Bio-X Institutes, Key Laboratory for the Genetics of Development and Neuropsychiatric Disorders (Ministry of Education), Shanghai Key Laboratory of Psychotic Disorders, and Brain Science and Technology Research Center, Shanghai Jiao Tong University, Shanghai 200240, China
- WLA Laboratories, World Laureates Association, Shanghai 201203, China
| | - Guang He
- Bio-X Institutes, Key Laboratory for the Genetics of Development and Neuropsychiatric Disorders (Ministry of Education), Shanghai Key Laboratory of Psychotic Disorders, and Brain Science and Technology Research Center, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Yong-Yong Shi
- Bio-X Institutes, Key Laboratory for the Genetics of Development and Neuropsychiatric Disorders (Ministry of Education), Shanghai Key Laboratory of Psychotic Disorders, and Brain Science and Technology Research Center, Shanghai Jiao Tong University, Shanghai 200240, China
- Affiliated Hospital of Qingdao University & Biomedical Sciences Institute of Qingdao University, Qingdao Branch of SJTU Bio-X Institutes, Qingdao University, Qingdao, Shandong 266003, China
| | - Evan E Eichler
- Department of Genome Sciences, University of Washington School of Medicine, Seattle WA 98195, USA
- Howard Hughes Medical Institute, University of Washington, Seattle WA 98195, USA
| | - Zhi-Qiang Li
- Bio-X Institutes, Key Laboratory for the Genetics of Development and Neuropsychiatric Disorders (Ministry of Education), Shanghai Key Laboratory of Psychotic Disorders, and Brain Science and Technology Research Center, Shanghai Jiao Tong University, Shanghai 200240, China
- Affiliated Hospital of Qingdao University & Biomedical Sciences Institute of Qingdao University, Qingdao Branch of SJTU Bio-X Institutes, Qingdao University, Qingdao, Shandong 266003, China. E-mail:
| | - Eiki Takahashi
- Bio-X Institutes, Key Laboratory for the Genetics of Development and Neuropsychiatric Disorders (Ministry of Education), Shanghai Key Laboratory of Psychotic Disorders, and Brain Science and Technology Research Center, Shanghai Jiao Tong University, Shanghai 200240, China
- Department of Biomedicine, Graduate School of Medical Sciences, Kyushu University, Fukuoka 812-8582, Japan. E-mail:
| | - Wei-Dong Li
- Bio-X Institutes, Key Laboratory for the Genetics of Development and Neuropsychiatric Disorders (Ministry of Education), Shanghai Key Laboratory of Psychotic Disorders, and Brain Science and Technology Research Center, Shanghai Jiao Tong University, Shanghai 200240, China
- Institute of Psychology and Behavioral Science, Shanghai Jiao Tong University, Shanghai 200030, China
- WLA Laboratories, World Laureates Association, Shanghai 201203, China
- Global Institute of Future Technology, Shanghai Jiao Tong University, Shanghai 200240, China. E-mail:
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13
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Zhang C, Reid K, Sands AF, Fraimout A, Schierup MH, Merilä J. De Novo Mutation Rates in Sticklebacks. Mol Biol Evol 2023; 40:msad192. [PMID: 37648662 PMCID: PMC10503787 DOI: 10.1093/molbev/msad192] [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: 03/16/2023] [Revised: 08/21/2023] [Accepted: 08/24/2023] [Indexed: 09/01/2023] Open
Abstract
Mutation rate is a fundamental parameter in population genetics. Apart from being an important scaling parameter for demographic and phylogenetic inference, it allows one to understand at what rate new genetic diversity is generated and what the expected level of genetic diversity is in a population at equilibrium. However, except for well-established model organisms, accurate estimates of de novo mutation rates are available for a very limited number of organisms from the wild. We estimated mutation rates (µ) in two marine populations of the nine-spined stickleback (Pungitius pungitius) with the aid of several 2- and 3-generational family pedigrees, deep (>50×) whole-genome resequences and a high-quality reference genome. After stringent filtering, we discovered 308 germline mutations in 106 offspring translating to µ = 4.83 × 10-9 and µ = 4.29 × 10-9 per base per generation in the two populations, respectively. Up to 20% of the mutations were shared by full-sibs showing that the level of parental mosaicism was relatively high. Since the estimated µ was 3.1 times smaller than the commonly used substitution rate, recalibration with µ led to substantial increase in estimated divergence times between different stickleback species. Our estimates of the de novo mutation rate should provide a useful resource for research focused on fish population genetics and that of sticklebacks in particular.
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Affiliation(s)
- Chaowei Zhang
- Area of Ecology & Biodiversity, School of Biological Sciences, The University of Hong Kong, Hong Kong, Hong Kong SAR
| | - Kerry Reid
- Area of Ecology & Biodiversity, School of Biological Sciences, The University of Hong Kong, Hong Kong, Hong Kong SAR
| | - Arthur F Sands
- Area of Ecology & Biodiversity, School of Biological Sciences, The University of Hong Kong, Hong Kong, Hong Kong SAR
| | - Antoine Fraimout
- Area of Ecology & Biodiversity, School of Biological Sciences, The University of Hong Kong, Hong Kong, Hong Kong SAR
- Research Program in Organismal & Evolutionary Biology, Faculty Biological and Environmental Sciences, University of Helsinki, Helsinki, Finland
| | | | - Juha Merilä
- Area of Ecology & Biodiversity, School of Biological Sciences, The University of Hong Kong, Hong Kong, Hong Kong SAR
- Research Program in Organismal & Evolutionary Biology, Faculty Biological and Environmental Sciences, University of Helsinki, Helsinki, Finland
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14
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Zhou Y, Zhan X, Jin J, Zhou L, Bergman J, Li X, Rousselle MMC, Belles MR, Zhao L, Fang M, Chen J, Fang Q, Kuderna L, Marques-Bonet T, Kitayama H, Hayakawa T, Yao YG, Yang H, Cooper DN, Qi X, Wu DD, Schierup MH, Zhang G. Eighty million years of rapid evolution of the primate Y chromosome. Nat Ecol Evol 2023; 7:1114-1130. [PMID: 37268856 DOI: 10.1038/s41559-022-01974-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Accepted: 12/15/2022] [Indexed: 06/04/2023]
Abstract
The Y chromosome usually plays a critical role in determining male sex and comprises sequence classes that have experienced unique evolutionary trajectories. Here we generated 19 new primate sex chromosome assemblies, analysed them with 10 existing assemblies and report rapid evolution of the Y chromosome across primates. The pseudoautosomal boundary has shifted at least six times during primate evolution, leading to the formation of a Simiiformes-specific evolutionary stratum and to the independent start of young strata in Catarrhini and Platyrrhini. Different primate lineages experienced different rates of gene loss and structural and chromatin change on their Y chromosomes. Selection on several Y-linked genes has contributed to the evolution of male developmental traits across the primates. Additionally, lineage-specific expansions of ampliconic regions have further increased the diversification of the structure and gene composition of the Y chromosome. Overall, our comprehensive analysis has broadened our knowledge of the evolution of the primate Y chromosome.
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Affiliation(s)
| | | | | | - Long Zhou
- Centre for Evolutionary & Organismal Biology, and Women's Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Liangzhu Laboratory, Zhejiang University Medical Center, Hangzhou, China
| | - Juraj Bergman
- Section for Ecoinformatics & Biodiversity, Department of Biology, Aarhus University, Aarhus C., Denmark
- Bioinformatics Research Centre, Aarhus University, Aarhus C., Denmark
| | - Xuemei Li
- BGI-Shenzhen, Shenzhen, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | | | | | - Lan Zhao
- College of Life Sciences, Northwest University, Xi'an, China
| | | | | | - Qi Fang
- BGI-Shenzhen, Shenzhen, China
| | - Lukas Kuderna
- Institute of Evolutionary Biology (UPF-CSIC), PRBB, Barcelona, Spain
| | - Tomas Marques-Bonet
- Institute of Evolutionary Biology (UPF-CSIC), PRBB, Barcelona, Spain
- Catalan Institution of Research and Advanced Studies (ICREA), Barcelona, Spain
- CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Barcelona, Spain
- Institut Català de Paleontologia Miquel Crusafont, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Haruka Kitayama
- Graduate School of Environmental Science, Hokkaido University, Sapporo, Japan
| | - Takashi Hayakawa
- Faculty of Environmental Earth Science, Hokkaido University, Sapporo, Japan
- Japan Monkey Centre, Inuyama, Japan
| | - Yong-Gang Yao
- Kunming College of Life Science, University of the Chinese Academy of Sciences, Kunming, China
- Key Laboratory of Animal Models and Human Disease Mechanisms of Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, China
- National Resource Center for Non-Human Primates, Kunming Primate Research Center, and National Research Facility for Phenotypic & Genetic Analysis of Model Animals (Primate Facility), Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
- KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Huanming Yang
- BGI-Shenzhen, Shenzhen, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
- James D. Watson Institute of Genome Sciences, Hangzhou, China
- Guangdong Provincial Academician Workstation of BGI Synthetic Genomics, BGI-Shenzhen, Shenzhen, China
- The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences, Hangzhou, China
| | - David N Cooper
- Institute of Medical Genetics, School of Medicine, Cardiff University, Cardiff, UK
| | - Xiaoguang Qi
- College of Life Sciences, Northwest University, Xi'an, China
| | - Dong-Dong Wu
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, China
- National Resource Center for Non-Human Primates, Kunming Primate Research Center, and National Research Facility for Phenotypic & Genetic Analysis of Model Animals (Primate Facility), Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
- KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | | | - Guojie Zhang
- Centre for Evolutionary & Organismal Biology, and Women's Hospital, Zhejiang University School of Medicine, Hangzhou, China.
- Liangzhu Laboratory, Zhejiang University Medical Center, Hangzhou, China.
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China.
- Section for Ecology and Evolution, Department of Biology, University of Copenhagen, Copenhagen, Denmark.
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15
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Bi X, Zhou L, Zhang JJ, Feng S, Hu M, Cooper DN, Lin J, Li J, Wu DD, Zhang G. Lineage-specific accelerated sequences underlying primate evolution. SCIENCE ADVANCES 2023; 9:eadc9507. [PMID: 37262186 PMCID: PMC10413682 DOI: 10.1126/sciadv.adc9507] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Accepted: 05/05/2023] [Indexed: 06/03/2023]
Abstract
Understanding the mechanisms underlying phenotypic innovation is a key goal of comparative genomic studies. Here, we investigated the evolutionary landscape of lineage-specific accelerated regions (LinARs) across 49 primate species. Genomic comparison with dense taxa sampling of primate species significantly improved LinAR detection accuracy and revealed many novel human LinARs associated with brain development or disease. Our study also yielded detailed maps of LinARs in other primate lineages that may have influenced lineage-specific phenotypic innovation and adaptation. Functional experimentation identified gibbon LinARs, which could have participated in the developmental regulation of their unique limb structures, whereas some LinARs in the Colobinae were associated with metabolite detoxification which may have been adaptive in relation to their leaf-eating diet. Overall, our study broadens knowledge of the functional roles of LinARs in primate evolution.
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Affiliation(s)
- Xupeng Bi
- Centre for Evolutionary & Organismal Biology, and Women’s Hospital, Zhejiang University School of Medicine, Hangzhou 310058, China
| | - Long Zhou
- Centre for Evolutionary & Organismal Biology, and Women’s Hospital, Zhejiang University School of Medicine, Hangzhou 310058, China
| | - Jin-Jin Zhang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
| | - Shaohong Feng
- Centre for Evolutionary & Organismal Biology, and Women’s Hospital, Zhejiang University School of Medicine, Hangzhou 310058, China
- Liangzhu Laboratory, Zhejiang University Medical Center, 1369 West Wenyi Road, Hangzhou 311121, China
| | - Mei Hu
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
| | - David N. Cooper
- Institute of Medical Genetics, School of Medicine, Cardiff University, Heath Park, Cardiff CF14 4XN, UK
| | - Jiangwei Lin
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
| | - Jiali Li
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
| | - Dong-Dong Wu
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, 32 Jiaochang Donglu, Kunming 650223, China
- National Resource Center for Non-Human Primates, Kunming Primate Research Center, and National Research Facility for Phenotypic & Genetic Analysis of Model Animals (Primate Facility), Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650107, China
| | - Guojie Zhang
- Centre for Evolutionary & Organismal Biology, and Women’s Hospital, Zhejiang University School of Medicine, Hangzhou 310058, China
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
- Liangzhu Laboratory, Zhejiang University Medical Center, 1369 West Wenyi Road, Hangzhou 311121, China
- Villum Center for Biodiversity Genomics, Section for Ecology and Evolution, Department of Biology, University of Copenhagen, Copenhagen, Denmark
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16
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Kuderna LFK, Gao H, Janiak MC, Kuhlwilm M, Orkin JD, Bataillon T, Manu S, Valenzuela A, Bergman J, Rousselle M, Silva FE, Agueda L, Blanc J, Gut M, de Vries D, Goodhead I, Harris RA, Raveendran M, Jensen A, Chuma IS, Horvath JE, Hvilsom C, Juan D, Frandsen P, Schraiber JG, de Melo FR, Bertuol F, Byrne H, Sampaio I, Farias I, Valsecchi J, Messias M, da Silva MNF, Trivedi M, Rossi R, Hrbek T, Andriaholinirina N, Rabarivola CJ, Zaramody A, Jolly CJ, Phillips-Conroy J, Wilkerson G, Abee C, Simmons JH, Fernandez-Duque E, Kanthaswamy S, Shiferaw F, Wu D, Zhou L, Shao Y, Zhang G, Keyyu JD, Knauf S, Le MD, Lizano E, Merker S, Navarro A, Nadler T, Khor CC, Lee J, Tan P, Lim WK, Kitchener AC, Zinner D, Gut I, Melin AD, Guschanski K, Schierup MH, Beck RMD, Umapathy G, Roos C, Boubli JP, Rogers J, Farh KKH, Marques Bonet T. A global catalog of whole-genome diversity from 233 primate species. Science 2023; 380:906-913. [PMID: 37262161 DOI: 10.1126/science.abn7829] [Citation(s) in RCA: 44] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2021] [Accepted: 02/06/2023] [Indexed: 06/03/2023]
Abstract
The rich diversity of morphology and behavior displayed across primate species provides an informative context in which to study the impact of genomic diversity on fundamental biological processes. Analysis of that diversity provides insight into long-standing questions in evolutionary and conservation biology and is urgent given severe threats these species are facing. Here, we present high-coverage whole-genome data from 233 primate species representing 86% of genera and all 16 families. This dataset was used, together with fossil calibration, to create a nuclear DNA phylogeny and to reassess evolutionary divergence times among primate clades. We found within-species genetic diversity across families and geographic regions to be associated with climate and sociality, but not with extinction risk. Furthermore, mutation rates differ across species, potentially influenced by effective population sizes. Lastly, we identified extensive recurrence of missense mutations previously thought to be human specific. This study will open a wide range of research avenues for future primate genomic research.
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Affiliation(s)
- Lukas F K Kuderna
- IBE, Institute of Evolutionary Biology (UPF-CSIC), Department of Medicine and Life Sciences, Universitat Pompeu Fabra. PRBB, C. Doctor Aiguader N88, 08003 Barcelona, Spain
- Illumina Artificial Intelligence Laboratory, Illumina Inc., Foster City, CA 94404, USA
| | - Hong Gao
- Illumina Artificial Intelligence Laboratory, Illumina Inc., Foster City, CA 94404, USA
| | - Mareike C Janiak
- School of Science, Engineering & Environment, University of Salford, Salford M5 4WT, UK
| | - Martin Kuhlwilm
- IBE, Institute of Evolutionary Biology (UPF-CSIC), Department of Medicine and Life Sciences, Universitat Pompeu Fabra. PRBB, C. Doctor Aiguader N88, 08003 Barcelona, Spain
- Department of Evolutionary Anthropology, University of Vienna, Djerassiplatz 1, 1030 Vienna, Austria
- Human Evolution and Archaeological Sciences (HEAS), University of Vienna, Austria
| | - Joseph D Orkin
- IBE, Institute of Evolutionary Biology (UPF-CSIC), Department of Medicine and Life Sciences, Universitat Pompeu Fabra. PRBB, C. Doctor Aiguader N88, 08003 Barcelona, Spain
- Département d'anthropologie, Université de Montréal, 3150 Jean-Brillant, Montréal, QC H3T 1N8, Canada
| | - Thomas Bataillon
- Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark
| | - Shivakumara Manu
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India
- Laboratory for the Conservation of Endangered Species, CSIR-Centre for Cellular and Molecular Biology, Hyderabad 500007, India
| | - Alejandro Valenzuela
- IBE, Institute of Evolutionary Biology (UPF-CSIC), Department of Medicine and Life Sciences, Universitat Pompeu Fabra. PRBB, C. Doctor Aiguader N88, 08003 Barcelona, Spain
| | - Juraj Bergman
- Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark
- Section for Ecoinformatics and Biodiversity, Department of Biology, Aarhus University, Aarhus, Denmark
| | | | - Felipe Ennes Silva
- Research Group on Primate Biology and Conservation, Mamirauá Institute for Sustainable Development, Estrada da Bexiga 2584, CEP 69553-225, Tefé, Amazonas, Brazil
- Evolutionary Biology and Ecology (EBE), Département de Biologie des Organismes, Université libre de Bruxelles (ULB), Av. Franklin D. Roosevelt 50, CP 160/12, B-1050 Brussels Belgium
| | - Lidia Agueda
- CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Baldiri I Reixac 4, 08028 Barcelona, Spain
| | - Julie Blanc
- CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Baldiri I Reixac 4, 08028 Barcelona, Spain
| | - Marta Gut
- CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Baldiri I Reixac 4, 08028 Barcelona, Spain
| | - Dorien de Vries
- School of Science, Engineering & Environment, University of Salford, Salford M5 4WT, UK
| | - Ian Goodhead
- School of Science, Engineering & Environment, University of Salford, Salford M5 4WT, UK
| | - R Alan Harris
- Human Genome Sequencing Center and Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Muthuswamy Raveendran
- Human Genome Sequencing Center and Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Axel Jensen
- Department of Ecology and Genetics, Animal Ecology, Uppsala University, SE-75236 Uppsala, Sweden
| | | | - Julie E Horvath
- North Carolina Museum of Natural Sciences, Raleigh, NC 27601, USA
- Department of Biological and Biomedical Sciences, North Carolina Central University, Durham, NC 27707, USA
- Department of Biological Sciences, North Carolina State University, Raleigh, NC 27695, USA
- Department of Evolutionary Anthropology, Duke University, Durham, NC 27708, USA
- Renaissance Computing Institute, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | | | - David Juan
- IBE, Institute of Evolutionary Biology (UPF-CSIC), Department of Medicine and Life Sciences, Universitat Pompeu Fabra. PRBB, C. Doctor Aiguader N88, 08003 Barcelona, Spain
| | | | - Joshua G Schraiber
- Illumina Artificial Intelligence Laboratory, Illumina Inc., Foster City, CA 94404, USA
| | | | - Fabrício Bertuol
- Universidade Federal do Amazonas, Departamento de Genética, Laboratório de Evolução e Genética Animal (LEGAL), Manaus, Amazonas 69080-900, Brazil
| | - Hazel Byrne
- Department of Anthropology, University of Utah, Salt Lake City. UT 84102, USA
| | | | - Izeni Farias
- Universidade Federal do Amazonas, Departamento de Genética, Laboratório de Evolução e Genética Animal (LEGAL), Manaus, Amazonas 69080-900, Brazil
| | - João Valsecchi
- Research Group on Terrestrial Vertebrate Ecology, Mamirauá Institute for Sustainable Development, Tefé, Amazonas, Brazil
- Rede de Pesquisa para Estudos sobre Diversidade, Conservação e Uso da Fauna na Amazônia - RedeFauna, Manaus, Amazonas, Brazil
- Comunidad de Manejo de Fauna Silvestre en la Amazonía y en Latinoamérica - ComFauna, Iquitos, Loreto, Peru
| | - Malu Messias
- Universidade Federal de Rondônia, Porto Velho, Rondônia, Brazil
| | | | - Mihir Trivedi
- Laboratory for the Conservation of Endangered Species, CSIR-Centre for Cellular and Molecular Biology, Hyderabad 500007, India
| | - Rogerio Rossi
- Instituto de Biociências, Universidade Federal do Mato Grosso, Cuiabá, MT, Brazil
| | - Tomas Hrbek
- Universidade Federal do Amazonas, Departamento de Genética, Laboratório de Evolução e Genética Animal (LEGAL), Manaus, Amazonas 69080-900, Brazil
- Department of Biology, Trinity University, San Antonio, TX 78212, USA
| | - Nicole Andriaholinirina
- Life Sciences and Environment, Technology and Environment of Mahajanga, University of Mahajanga, Mahajanga, Madagascar
| | - Clément J Rabarivola
- Life Sciences and Environment, Technology and Environment of Mahajanga, University of Mahajanga, Mahajanga, Madagascar
| | - Alphonse Zaramody
- Life Sciences and Environment, Technology and Environment of Mahajanga, University of Mahajanga, Mahajanga, Madagascar
| | - Clifford J Jolly
- Department of Anthropology, New York University, New York, NY 10003, USA
| | - Jane Phillips-Conroy
- Department of Neuroscience, Washington University School of Medicine in St. Louis, St. Louis, MO 63110, USA
| | - Gregory Wilkerson
- Keeling Center for Comparative Medicine and Research, MD Anderson Cancer Center, Bastrop TX 78602, USA
| | - Christian Abee
- Keeling Center for Comparative Medicine and Research, MD Anderson Cancer Center, Bastrop TX 78602, USA
| | - Joe H Simmons
- Keeling Center for Comparative Medicine and Research, MD Anderson Cancer Center, Bastrop TX 78602, USA
| | | | - Sree Kanthaswamy
- School of Mathematical and Natural Sciences, Arizona State University, Phoenix, AZ 85004, USA
| | - Fekadu Shiferaw
- Guinea Worm Eradication Program, The Carter Center Ethiopia, Addis Ababa, Ethiopia
| | - Dongdong Wu
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650223, China
| | - Long Zhou
- Center for Evolutionary and Organismal Biology, Zhejiang University School of Medicine, Hangzhou 310058, China
| | - Yong Shao
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650223, China
| | - Guojie Zhang
- Center for Evolutionary and Organismal Biology, Zhejiang University School of Medicine, Hangzhou 310058, China
- Villum Centre for Biodiversity Genomics, Section for Ecology and Evolution, Department of Biology, University of Copenhagen, DK-2100 Copenhagen, Denmark
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650223, China
- Liangzhu Laboratory, Zhejiang University Medical Center, 1369 West Wenyi Road, Hangzhou 311121, China
- Women's Hospital, School of Medicine, Zhejiang University, 1 Xueshi Road, Shangcheng District, Hangzhou 310006, China
| | - Julius D Keyyu
- Tanzania Wildlife Research Institute (TAWIRI), Head Office, P.O. Box 661, Arusha, Tanzania
| | - Sascha Knauf
- Institute of International Animal Health/One Health, Friedrich-Loeffler-Institut, Federal Research Institute for Animal Health, 17493 Greifswald-Insel Riems, Germany
| | - Minh D Le
- Department of Environmental Ecology, Faculty of Environmental Sciences, University of Science and Central Institute for Natural Resources and Environmental Studies, Vietnam National University, Hanoi, Vietnam
| | - Esther Lizano
- IBE, Institute of Evolutionary Biology (UPF-CSIC), Department of Medicine and Life Sciences, Universitat Pompeu Fabra. PRBB, C. Doctor Aiguader N88, 08003 Barcelona, Spain
- Institut Català de Paleontologia Miquel Crusafont, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Stefan Merker
- Department of Zoology, State Museum of Natural History Stuttgart, Stuttgart, Germany
| | - Arcadi Navarro
- IBE, Institute of Evolutionary Biology (UPF-CSIC), Department of Medicine and Life Sciences, Universitat Pompeu Fabra. PRBB, C. Doctor Aiguader N88, 08003 Barcelona, Spain
- Institució Catalana de Recerca i Estudis Avançats (ICREA) and Universitat Pompeu Fabra. Pg. Luís Companys 23, 08010 Barcelona, Spain
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Av. Doctor Aiguader, N88, 08003 Barcelona, Spain
- BarcelonaBeta Brain Research Center, Pasqual Maragall Foundation, C. Wellington 30, 08005 Barcelona, Spain
| | - Tilo Nadler
- Cuc Phuong Commune, Nho Quan District, Ninh Binh Province, Vietnam
| | - Chiea Chuen Khor
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore
| | - Jessica Lee
- Mandai Nature, 80 Mandai Lake Road, Singapore
| | - Patrick Tan
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore
- SingHealth Duke-NUS Institute of Precision Medicine (PRISM), Singapore
- Cancer and Stem Cell Biology Program, Duke-NUS Medical School, Singapore
| | - Weng Khong Lim
- SingHealth Duke-NUS Institute of Precision Medicine (PRISM), Singapore
- Cancer and Stem Cell Biology Program, Duke-NUS Medical School, Singapore
- SingHealth Duke-NUS Genomic Medicine Centre, Singapore
| | - Andrew C Kitchener
- Department of Natural Sciences, National Museums Scotland, Chambers Street, Edinburgh EH1 1JF, UK, and School of Geosciences, Drummond Street, Edinburgh EH8 9XP, UK
| | - Dietmar Zinner
- Cognitive Ethology Laboratory, Germany Primate Center, Leibniz Institute for Primate Research, 37077 Göttingen, Germany
- Department of Primate Cognition, Georg-August-Universität Göttingen, 37077 Göttingen, Germany
- Leibniz ScienceCampus Primate Cognition, 37077 Göttingen, Germany
| | - Ivo Gut
- CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Baldiri I Reixac 4, 08028 Barcelona, Spain
| | - Amanda D Melin
- Department of Anthropology and Archaeology, University of Calgary, 2500 University Dr NW, Calgary, AB T2N 1N4, Canada
- Department of Medical Genetics, University of Calgary, 3330 Hospital Drive NW, HMRB 202, Calgary, AB T2N 4N1, Canada
- Alberta Children's Hospital Research Institute, University of Calgary, 3330 Hospital Drive NW, HMRB 202, Calgary, AB T2N 4N1, Canada
| | - Katerina Guschanski
- Department of Ecology and Genetics, Animal Ecology, Uppsala University, SE-75236 Uppsala, Sweden
- Institute of Ecology and Evolution, School of Biological Sciences, University of Edinburgh, Edinburgh, UK
| | | | - Robin M D Beck
- School of Science, Engineering & Environment, University of Salford, Salford M5 4WT, UK
| | - Govindhaswamy Umapathy
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India
- Laboratory for the Conservation of Endangered Species, CSIR-Centre for Cellular and Molecular Biology, Hyderabad 500007, India
| | - Christian Roos
- Gene Bank of Primates and Primate Genetics Laboratory, German Primate Center, Leibniz Institute for Primate Research, Kellnerweg 4, 37077 Göttingen, Germany
| | - Jean P Boubli
- School of Science, Engineering & Environment, University of Salford, Salford M5 4WT, UK
| | - Jeffrey Rogers
- Human Genome Sequencing Center and Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Kyle Kai-How Farh
- Illumina Artificial Intelligence Laboratory, Illumina Inc., Foster City, CA 94404, USA
| | - Tomas Marques Bonet
- IBE, Institute of Evolutionary Biology (UPF-CSIC), Department of Medicine and Life Sciences, Universitat Pompeu Fabra. PRBB, C. Doctor Aiguader N88, 08003 Barcelona, Spain
- CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Baldiri I Reixac 4, 08028 Barcelona, Spain
- Institut Català de Paleontologia Miquel Crusafont, Universitat Autònoma de Barcelona, Barcelona, Spain
- Institució Catalana de Recerca i Estudis Avançats (ICREA) and Universitat Pompeu Fabra. Pg. Luís Companys 23, 08010 Barcelona, Spain
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17
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Shao Y, Zhou L, Li F, Zhao L, Zhang BL, Shao F, Chen JW, Chen CY, Bi X, Zhuang XL, Zhu HL, Hu J, Sun Z, Li X, Wang D, Rivas-González I, Wang S, Wang YM, Chen W, Li G, Lu HM, Liu Y, Kuderna LFK, Farh KKH, Fan PF, Yu L, Li M, Liu ZJ, Tiley GP, Yoder AD, Roos C, Hayakawa T, Marques-Bonet T, Rogers J, Stenson PD, Cooper DN, Schierup MH, Yao YG, Zhang YP, Wang W, Qi XG, Zhang G, Wu DD. Phylogenomic analyses provide insights into primate evolution. Science 2023; 380:913-924. [PMID: 37262173 DOI: 10.1126/science.abn6919] [Citation(s) in RCA: 36] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Accepted: 01/26/2023] [Indexed: 06/03/2023]
Abstract
Comparative analysis of primate genomes within a phylogenetic context is essential for understanding the evolution of human genetic architecture and primate diversity. We present such a study of 50 primate species spanning 38 genera and 14 families, including 27 genomes first reported here, with many from previously less well represented groups, the New World monkeys and the Strepsirrhini. Our analyses reveal heterogeneous rates of genomic rearrangement and gene evolution across primate lineages. Thousands of genes under positive selection in different lineages play roles in the nervous, skeletal, and digestive systems and may have contributed to primate innovations and adaptations. Our study reveals that many key genomic innovations occurred in the Simiiformes ancestral node and may have had an impact on the adaptive radiation of the Simiiformes and human evolution.
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Affiliation(s)
- Yong Shao
- State Key Laboratory of Genetic Resources and Evolution, Kunming Natural History Museum of Zoology, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650201, China
| | - Long Zhou
- Center of Evolutionary & Organismal Biology, and Women's Hospital at Zhejiang University School of Medicine, Hangzhou 310058, China
| | - Fang Li
- Section for Ecology and Evolution, Department of Biology, University of Copenhagen, DK-2100 Copenhagen, Denmark
- Institute of Animal Sex and Development, ZhejiangWanli University, Ningbo 315100, China
| | - Lan Zhao
- Shaanxi Key Laboratory for Animal Conservation, College of Life Sciences, Northwest University, Xi'an 710069, China
| | - Bao-Lin Zhang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Natural History Museum of Zoology, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650201, China
| | - Feng Shao
- Key Laboratory of Freshwater Fish Reproduction and Development (Ministry of Education), Southwest University School of Life Sciences, Chongqing 400715, China
| | | | - Chun-Yan Chen
- School of Ecology and Environment, Northwestern Polytechnical University, Xi'an 710072, China
| | - Xupeng Bi
- Center of Evolutionary & Organismal Biology, and Women's Hospital at Zhejiang University School of Medicine, Hangzhou 310058, China
| | - Xiao-Lin Zhuang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Natural History Museum of Zoology, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650201, China
- Kunming College of Life Science, University of the Chinese Academy of Sciences, Kunming 650204, China
| | | | - Jiang Hu
- Grandomics Biosciences, Beijing 102206, China
| | - Zongyi Sun
- Grandomics Biosciences, Beijing 102206, China
| | - Xin Li
- Grandomics Biosciences, Beijing 102206, China
| | - Depeng Wang
- Grandomics Biosciences, Beijing 102206, China
| | | | - Sheng Wang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Natural History Museum of Zoology, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650201, China
| | - Yun-Mei Wang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Natural History Museum of Zoology, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650201, China
| | - Wu Chen
- Guangzhou Zoo & Guangzhou Wildlife Research Center, Guangzhou 510070, China
| | - Gang Li
- College of Life Sciences, Shaanxi Normal University, Xi'an 710119, China
| | - Hui-Meng Lu
- School of Life Sciences, Northwestern Polytechnical University, Xi'an 710072, China
| | - Yang Liu
- College of Life Sciences, Shaanxi Normal University, Xi'an 710119, China
| | - Lukas F K Kuderna
- Institute of Evolutionary Biology (UPF-CSIC), PRBB, 08003 Barcelona, Spain
- Illumina Artificial Intelligence Laboratory, Illumina Inc, San Diego, CA 92122, USA
| | - Kyle Kai-How Farh
- Illumina Artificial Intelligence Laboratory, Illumina Inc, San Diego, CA 92122, USA
| | - Peng-Fei Fan
- School of Life Sciences, Sun Yat-sen University, Guangzhou, Guangdong 510275, China
| | - Li Yu
- State Key Laboratory for Conservation and Utilization of Bio-Resource in Yunnan, School of Life Sciences, Yunnan University, Kunming 650091, China
| | - Ming Li
- CAS Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
| | - Zhi-Jin Liu
- College of Life Sciences, Capital Normal University, Beijing 100048, China
| | - George P Tiley
- Department of Biology, Duke University, Durham, NC 27708, USA
| | - Anne D Yoder
- Department of Biology, Duke University, Durham, NC 27708, USA
| | - Christian Roos
- Gene Bank of Primates and Primate Genetics Laboratory, German Primate Center, Leibniz Institute for Primate Research, 37077 Göttingen, Germany
| | - Takashi Hayakawa
- Faculty of Environmental Earth Science, Hokkaido University, Sapporo, Hokkaido 060-0810, Japan
- Japan Monkey Centre, Inuyama, Aichi 484-0081, Japan
| | - Tomas Marques-Bonet
- Institute of Evolutionary Biology (UPF-CSIC), PRBB, 08003 Barcelona, Spain
- Catalan Institution of Research and Advanced Studies (ICREA), Passeig de Lluís Companys, 23, 08010 Barcelona, Spain
- CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), 08028 Barcelona, Spain
- Institut Català de Paleontologia Miquel Crusafont, Universitat Autònoma de Barcelona, Edifici ICTA-ICP, c/ Columnes s/n, 08193 Cerdanyola del Vallès, Barcelona, Spain
| | - Jeffrey Rogers
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Peter D Stenson
- Institute of Medical Genetics, School of Medicine, Cardiff University, Cardiff CF14 4XN, UK
| | - David N Cooper
- Institute of Medical Genetics, School of Medicine, Cardiff University, Cardiff CF14 4XN, UK
| | | | - Yong-Gang Yao
- Kunming College of Life Science, University of the Chinese Academy of Sciences, Kunming 650204, China
- Key Laboratory of Animal Models and Human Disease Mechanisms of Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650201, China
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming 650201, China
- National Resource Center for Non-Human Primates, Kunming Primate Research Center, and National Research Facility for Phenotypic & Genetic Analysis of Model Animals (Primate Facility), Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650107, China
| | - Ya-Ping Zhang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Natural History Museum of Zoology, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650201, China
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming 650201, China
- National Resource Center for Non-Human Primates, Kunming Primate Research Center, and National Research Facility for Phenotypic & Genetic Analysis of Model Animals (Primate Facility), Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650107, China
| | - Wen Wang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Natural History Museum of Zoology, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650201, China
- School of Ecology and Environment, Northwestern Polytechnical University, Xi'an 710072, China
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming 650201, China
| | - Xiao-Guang Qi
- Shaanxi Key Laboratory for Animal Conservation, College of Life Sciences, Northwest University, Xi'an 710069, China
| | - Guojie Zhang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Natural History Museum of Zoology, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650201, China
- Center of Evolutionary & Organismal Biology, and Women's Hospital at Zhejiang University School of Medicine, Hangzhou 310058, China
- Section for Ecology and Evolution, Department of Biology, University of Copenhagen, DK-2100 Copenhagen, Denmark
- Liangzhu Laboratory, Zhejiang University Medical Center, Hangzhou 311121, China
| | - Dong-Dong Wu
- State Key Laboratory of Genetic Resources and Evolution, Kunming Natural History Museum of Zoology, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650201, China
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming 650201, China
- National Resource Center for Non-Human Primates, Kunming Primate Research Center, and National Research Facility for Phenotypic & Genetic Analysis of Model Animals (Primate Facility), Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650107, China
- KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650204, China
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18
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Han R, Han L, Zhao X, Wang Q, Xia Y, Li H. Haplotype-resolved Genome of Sika Deer Reveals Allele-specific Gene Expression and Chromosome Evolution. GENOMICS, PROTEOMICS & BIOINFORMATICS 2023; 21:470-482. [PMID: 36395998 PMCID: PMC10787017 DOI: 10.1016/j.gpb.2022.11.001] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Revised: 10/24/2022] [Accepted: 11/07/2022] [Indexed: 11/16/2022]
Abstract
Despite the scientific and medicinal importance of diploid sika deer (Cervus nippon), its genome resources are limited and haplotype-resolved chromosome-scale assembly is urgently needed. To explore mechanisms underlying the expression patterns of the allele-specific genes in antlers and the chromosome evolution in Cervidae, we report, for the first time, a high-quality haplotype-resolved chromosome-scale genome of sika deer by integrating multiple sequencing strategies, which was anchored to 32 homologous groups with a pair of sex chromosomes (XY). Several expanded genes (RET, PPP2R1A, PPP2R1B, YWHAB, YWHAZ, and RPS6) and positively selected genes (eIF4E, Wnt8A, Wnt9B, BMP4, and TP53) were identified, which could contribute to rapid antler growth without carcinogenesis. A comprehensive and systematic genome-wide analysis of allele expression patterns revealed that most alleles were functionally equivalent in regulating rapid antler growth and inhibiting oncogenesis. Comparative genomic analysis revealed that chromosome fission might occur during the divergence of sika deer and red deer (Cervus elaphus), and the olfactory sensation of sika deer might be more powerful than that of red deer. Obvious inversion regions containing olfactory receptor genes were also identified, which arose since the divergence. In conclusion, the high-quality allele-aware reference genome provides valuable resources for further illustration of the unique biological characteristics of antler, chromosome evolution, and multi-omics research of cervid animals.
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Affiliation(s)
- Ruobing Han
- College of Wildlife and Protected Area, Northeast Forestry University, Harbin 150040, China
| | - Lei Han
- College of Wildlife and Protected Area, Northeast Forestry University, Harbin 150040, China
| | - Xunwu Zhao
- College of Wildlife and Protected Area, Northeast Forestry University, Harbin 150040, China
| | - Qianghui Wang
- College of Wildlife and Protected Area, Northeast Forestry University, Harbin 150040, China
| | - Yanling Xia
- College of Wildlife and Protected Area, Northeast Forestry University, Harbin 150040, China
| | - Heping Li
- College of Wildlife and Protected Area, Northeast Forestry University, Harbin 150040, China.
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19
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Yang Y, You C, Wang N, Wu M, Le Y, Wang M, Zhang X, Yu Y, Lin Z. Gossypium mustelinum genome and an introgression population enrich interspecific genetics and breeding in cotton. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2023; 136:130. [PMID: 37199762 DOI: 10.1007/s00122-023-04379-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Subscribe] [Scholar Register] [Received: 03/04/2023] [Accepted: 05/05/2023] [Indexed: 05/19/2023]
Abstract
KEY MESSAGE Genomic and genetic resources of G. mustelinum were effective for identifying genes for qualitative and quantitative traits. Gossypium mustelinum represents the earliest diverging evolutionary lineage of polyploid Gossypium, representing a rich gene pool for numerous desirable traits lost in cotton cultivars. Accurate information of the genomic features and the genetic architecture of objective traits are essential for the discovery and utilization of G. mustelinum genes. Here, we presented a chromosome-level genome assembly of G. mustelinum and developed an introgression population of the G. mustelinum in the background of G. hirsutum that contained 264 lines. We precisely delimited the boundaries of the 1,662 introgression segments with the help of G. mustelinum genome assembly, and 87% of crossover regions (COs) were less than 5 Kb. Genes for fuzzless and green fuzz were discovered, and a total of 14 stable QTLs were identified with 12 novel QTLs across four independent environments. A new fiber length QTL, qUHML/SFC-A11, was confined to a 177-Kb region, and GmOPB4 and GmGUAT11 were considered as the putative candidate genes as potential negative regulator for fiber length. We presented a genomic and genetic resource of G. mustelinum, which we demonstrated that it was efficient for identifying genes for qualitative and quantitative traits. Our study built a valuable foundation for cotton genetics and breeding.
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Affiliation(s)
- Yang Yang
- National Key Laboratory of Crop Genetic Improvement, College of Plant Sciences and Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, China
- Institute of Nuclear and Biotechnology, Xinjiang Academy of Agricultural Sciences/Xinjiang Key Laboratory of Crop Biotechnology/The State Key Laboratory of Genetic Improvement and Germplasm Innovation of Crop Resistance in Arid Desert Regions, Urumqi, 830091, Xinjiang, China
| | - Chunyuan You
- National Key Laboratory of Crop Genetic Improvement, College of Plant Sciences and Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, China
- Cotton Research Institute, Shihezi Academy of Agriculture Science, Shihezi, 832000, Xinjiang, China
| | - Nian Wang
- National Key Laboratory of Crop Genetic Improvement, College of Plant Sciences and Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, China
| | - Mi Wu
- National Key Laboratory of Crop Genetic Improvement, College of Plant Sciences and Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, China
| | - Yu Le
- National Key Laboratory of Crop Genetic Improvement, College of Plant Sciences and Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, China
| | - Maojun Wang
- National Key Laboratory of Crop Genetic Improvement, College of Plant Sciences and Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, China
| | - Xianlong Zhang
- National Key Laboratory of Crop Genetic Improvement, College of Plant Sciences and Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, China
| | - Yu Yu
- Cotton Research Institute, Xinjiang Academy of Agriculture and Reclamation Science, Shihezi, 832000, Xinjiang, China.
| | - Zhongxu Lin
- National Key Laboratory of Crop Genetic Improvement, College of Plant Sciences and Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, China.
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20
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Perez-Cruz C, Rodriguez-Callejas JDD. The common marmoset as a model of neurodegeneration. Trends Neurosci 2023; 46:394-409. [PMID: 36907677 DOI: 10.1016/j.tins.2023.02.002] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Revised: 01/29/2023] [Accepted: 02/14/2023] [Indexed: 03/12/2023]
Abstract
Human life expectancy has increased over the past few centuries, and the incidence of dementia in the older population is also projected to continue to rise. Neurodegenerative diseases are complex multifactorial conditions for which no effective treatments are currently available. Animal models are necessary to understand the causes and progression of neurodegeneration. Nonhuman primates (NHPs) offer significant advantages for the study of neurodegenerative disease. Among them, the common marmoset, Callithrix jacchus, stands out due to its easy handling, complex brain architecture, and occurrence of spontaneous beta-amyloid (Aβ) and phosphorylated tau aggregates with aging. Furthermore, marmosets present physiological adaptations and metabolic alterations associated with the increased risk of dementia in humans. In this review, we discuss the current literature on the use of marmosets as a model of aging and neurodegeneration. We highlight aspects of marmoset physiology associated with aging, such as metabolic alterations, which may help understand their vulnerability to developing a neurodegenerative phenotype that goes beyond normal aging.
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Affiliation(s)
- Claudia Perez-Cruz
- Department of Pharmacology, Center of Research and Advance Studies (Cinvestav-I.P.N.), Av. Politecnico Nacional 2508, San Pedro Zacatenco, Gustavo A. Madero, 07360, Mexico City, Mexico.
| | - Juan de Dios Rodriguez-Callejas
- Department of Pharmacology, Center of Research and Advance Studies (Cinvestav-I.P.N.), Av. Politecnico Nacional 2508, San Pedro Zacatenco, Gustavo A. Madero, 07360, Mexico City, Mexico
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21
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Mao Y, Harvey WT, Porubsky D, Munson KM, Hoekzema K, Lewis AP, Audano PA, Rozanski A, Yang X, Zhang S, Gordon DS, Wei X, Logsdon GA, Haukness M, Dishuck PC, Jeong H, Del Rosario R, Bauer VL, Fattor WT, Wilkerson GK, Lu Q, Paten B, Feng G, Sawyer SL, Warren WC, Carbone L, Eichler EE. Structurally divergent and recurrently mutated regions of primate genomes. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.07.531415. [PMID: 36945442 PMCID: PMC10028934 DOI: 10.1101/2023.03.07.531415] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/10/2023]
Abstract
To better understand the pattern of primate genome structural variation, we sequenced and assembled using multiple long-read sequencing technologies the genomes of eight nonhuman primate species, including New World monkeys (owl monkey and marmoset), Old World monkey (macaque), Asian apes (orangutan and gibbon), and African ape lineages (gorilla, bonobo, and chimpanzee). Compared to the human genome, we identified 1,338,997 lineage-specific fixed structural variants (SVs) disrupting 1,561 protein-coding genes and 136,932 regulatory elements, including the most complete set of human-specific fixed differences. Across 50 million years of primate evolution, we estimate that 819.47 Mbp or ~27% of the genome has been affected by SVs based on analysis of these primate lineages. We identify 1,607 structurally divergent regions (SDRs) wherein recurrent structural variation contributes to creating SV hotspots where genes are recurrently lost (CARDs, ABCD7, OLAH) and new lineage-specific genes are generated (e.g., CKAP2, NEK5) and have become targets of rapid chromosomal diversification and positive selection (e.g., RGPDs). High-fidelity long-read sequencing has made these dynamic regions of the genome accessible for sequence-level analyses within and between primate species for the first time.
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Affiliation(s)
- Yafei Mao
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - William T Harvey
- 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
| | - Katherine M Munson
- 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
| | - Alexandra P Lewis
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Peter A Audano
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Allison Rozanski
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Xiangyu Yang
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Shilong Zhang
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - David S Gordon
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA
| | - Xiaoxi Wei
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Glennis A Logsdon
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Marina Haukness
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Philip C Dishuck
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Hyeonsoo Jeong
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Ricardo Del Rosario
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Vanessa L Bauer
- BioFrontiers Institute, Department of Molecular, Cellular, and Developmental Biology, University of Colorado, Boulder, CO, USA
| | - Will T Fattor
- BioFrontiers Institute, Department of Molecular, Cellular, and Developmental Biology, University of Colorado, Boulder, CO, USA
| | - Gregory K Wilkerson
- Department of Veterinary Sciences, Michale E. Keeling Center for Comparative Medicine and Research, The University of Texas MD Anderson Cancer Center, Bastrop, TX, USA
- Department of Clinical Sciences, North Carolina State University, Raleigh, NC, USA
| | - Qing Lu
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Benedict Paten
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Guoping Feng
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Sara L Sawyer
- BioFrontiers Institute, Department of Molecular, Cellular, and Developmental Biology, University of Colorado, Boulder, CO, USA
| | - Wesley C Warren
- Department of Animal Sciences, Bond Life Sciences Center, University of Missouri, Columbia, MO, USA
- Department of Surgery, School of Medicine, University of Missouri, Columbia, MO, USA
- Institute of Data Science and Informatics, University of Missouri, Columbia, MO, USA
| | - Lucia Carbone
- Department of Medicine, Knight Cardiovascular Institute, Oregon Health and Science University, Portland, OR, USA
- Division of Genetics, Oregon National Primate Research Center, Beaverton, OR, USA
- Department of Molecular and Medical Genetics, Oregon Health and Science University, Portland, OR, USA
- Department of Medical Informatics and Clinical Epidemiology, Oregon Health and Science University, Portland, OR, USA
| | - Evan E Eichler
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA
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22
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Mikhaylova V, Rzepka M, Kawamura T, Xia Y, Chang PL, Zhou S, Pham L, Modi N, Yao L, Perez-Agustin A, Pagans S, Boles TC, Lei M, Wang Y, Garcia-Bassets I, Chen Z. Targeted Phasing of 2-200 Kilobase DNA Fragments with a Short-Read Sequencer and a Single-Tube Linked-Read Library Method. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.05.531179. [PMID: 36945366 PMCID: PMC10028795 DOI: 10.1101/2023.03.05.531179] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/11/2023]
Abstract
In the human genome, heterozygous sites are genomic positions with different alleles inherited from each parent. On average, there is a heterozygous site every 1-2 kilobases (kb). Resolving whether two alleles in neighboring heterozygous positions are physically linked-that is, phased-is possible with a short-read sequencer if the sequencing library captures long-range information. TELL-Seq is a library preparation method based on millions of barcoded micro-sized beads that enables instrument-free phasing of a whole human genome in a single PCR tube. TELL-Seq incorporates a unique molecular identifier (barcode) to the short reads generated from the same high-molecular-weight (HMW) DNA fragment (known as 'linked-reads'). However, genome-scale TELL-Seq is not cost-effective for applications focusing on a single locus or a few loci. Here, we present an optimized TELL-Seq protocol that enables the cost-effective phasing of enriched loci (targets) of varying sizes, purity levels, and heterozygosity. Targeted TELL-Seq maximizes linked-read efficiency and library yield while minimizing input requirements, fragment collisions on microbeads, and sequencing burden. To validate the targeted protocol, we phased seven 180-200 kb loci enriched by CRISPR/Cas9-mediated excision coupled with pulse-field electrophoresis, four 20 kb loci enriched by CRISPR/Cas9-mediated protection from exonuclease digestion, and six 2-13 kb loci amplified by PCR. The selected targets have clinical and research relevance (BRCA1, BRCA2, MLH1, MSH2, MSH6, APC, PMS2, SCN5A-SCN10A, and PKI3CA). These analyses reveal that targeted TELL-Seq provides a reliable way of phasing allelic variants within targets (2-200 kb in length) with the low cost and high accuracy of short-read sequencing.
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Affiliation(s)
| | - Madison Rzepka
- Universal Sequencing Technology Corp., Carlsbad, CA 92011, USA
| | | | - Yu Xia
- Universal Sequencing Technology Corp., Carlsbad, CA 92011, USA
| | - Peter L. Chang
- Universal Sequencing Technology Corp., Carlsbad, CA 92011, USA
| | | | - Long Pham
- Universal Sequencing Technology Corp., Carlsbad, CA 92011, USA
| | - Naisarg Modi
- Universal Sequencing Technology Corp., Carlsbad, CA 92011, USA
| | - Likun Yao
- Department of Medicine, University of California, San Diego, La Jolla, CA 92093 USA
| | - Adrian Perez-Agustin
- Department of Medical Sciences, School of Medicine, University of Girona, Girona, Spain
| | - Sara Pagans
- Department of Medical Sciences, School of Medicine, University of Girona, Girona, Spain
| | | | - Ming Lei
- Universal Sequencing Technology Corp., Canton, MA 02021, USA
| | - Yong Wang
- Universal Sequencing Technology Corp., Canton, MA 02021, USA
| | | | - Zhoutao Chen
- Universal Sequencing Technology Corp., Carlsbad, CA 92011, USA
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23
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Li T, Du D, Zhang D, Lin Y, Ma J, Zhou M, Meng W, Jin Z, Chen Z, Yuan H, Wang J, Dong S, Sun S, Ye W, Li B, Liu H, Zhang Z, Jiao Y, Xie Z, Qiu W, Liu Y. CRISPR-based targeted haplotype-resolved assembly of a megabase region. Nat Commun 2023; 14:22. [PMID: 36596772 PMCID: PMC9810730 DOI: 10.1038/s41467-022-35389-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Accepted: 11/29/2022] [Indexed: 01/04/2023] Open
Abstract
Constructing high-quality haplotype-resolved genome assemblies has substantially improved the ability to detect and characterize genetic variants. A targeted approach providing readily access to the rich information from haplotype-resolved genome assemblies will be appealing to groups of basic researchers and medical scientists focused on specific genomic regions. Here, using the 4.5 megabase, notoriously difficult-to-assemble major histocompatibility complex (MHC) region as an example, we demonstrated an approach to construct haplotype-resolved assembly of the targeted genomic region with the CRISPR-based enrichment. Compared to the results from haplotype-resolved genome assembly, our targeted approach achieved comparable completeness and accuracy with reduced computing complexity, sequencing cost, as well as the amount of starting materials. Moreover, using the targeted assembled personal MHC haplotypes as the reference both improves the quantification accuracy for sequencing data and enables allele-specific functional genomics analyses of the MHC region. Given its highly efficient use of resources, our approach can greatly facilitate population genetic studies of targeted regions, and may pave a new way to elucidate the molecular mechanisms in disease etiology.
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Affiliation(s)
- Taotao Li
- MOE Key Laboratory of Metabolism and Molecular Medicine, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences and Shanghai Xuhui Central Hospital, Fudan University, Shanghai, China.,State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Institutes of Brain Science, Fudan University, Shanghai, China
| | - Duo Du
- MOE Key Laboratory of Metabolism and Molecular Medicine, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences and Shanghai Xuhui Central Hospital, Fudan University, Shanghai, China.,State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Institutes of Brain Science, Fudan University, Shanghai, China
| | - Dandan Zhang
- MOE Key Laboratory of Metabolism and Molecular Medicine, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences and Shanghai Xuhui Central Hospital, Fudan University, Shanghai, China.,State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Institutes of Brain Science, Fudan University, Shanghai, China
| | - Yicheng Lin
- MOE Key Laboratory of Metabolism and Molecular Medicine, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences and Shanghai Xuhui Central Hospital, Fudan University, Shanghai, China.,State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Institutes of Brain Science, Fudan University, Shanghai, China
| | - Jiakang Ma
- MOE Key Laboratory of Metabolism and Molecular Medicine, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences and Shanghai Xuhui Central Hospital, Fudan University, Shanghai, China.,State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Institutes of Brain Science, Fudan University, Shanghai, China
| | - Mengyu Zhou
- MOE Key Laboratory of Metabolism and Molecular Medicine, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences and Shanghai Xuhui Central Hospital, Fudan University, Shanghai, China.,State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Institutes of Brain Science, Fudan University, Shanghai, China
| | - Weida Meng
- MOE Key Laboratory of Metabolism and Molecular Medicine, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences and Shanghai Xuhui Central Hospital, Fudan University, Shanghai, China.,State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Institutes of Brain Science, Fudan University, Shanghai, China
| | - Zelin Jin
- MOE Key Laboratory of Metabolism and Molecular Medicine, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences and Shanghai Xuhui Central Hospital, Fudan University, Shanghai, China.,State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Institutes of Brain Science, Fudan University, Shanghai, China
| | - Ziqiang Chen
- MOE Key Laboratory of Metabolism and Molecular Medicine, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences and Shanghai Xuhui Central Hospital, Fudan University, Shanghai, China.,State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Institutes of Brain Science, Fudan University, Shanghai, China
| | - Haozhe Yuan
- MOE Key Laboratory of Metabolism and Molecular Medicine, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences and Shanghai Xuhui Central Hospital, Fudan University, Shanghai, China.,State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Institutes of Brain Science, Fudan University, Shanghai, China
| | - Jue Wang
- MOE Key Laboratory of Metabolism and Molecular Medicine, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences and Shanghai Xuhui Central Hospital, Fudan University, Shanghai, China.,State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Institutes of Brain Science, Fudan University, Shanghai, China
| | - Shulong Dong
- MOE Key Laboratory of Metabolism and Molecular Medicine, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences and Shanghai Xuhui Central Hospital, Fudan University, Shanghai, China.,State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Institutes of Brain Science, Fudan University, Shanghai, China
| | - Shaoyang Sun
- MOE Key Laboratory of Metabolism and Molecular Medicine, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Fudan University, Shanghai, China
| | - Wenjing Ye
- Division of Rheumatology and Immunology, Huashan Hospital, Fudan University, Shanghai, China
| | - Bosen Li
- MOE Key Laboratory of Metabolism and Molecular Medicine, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Fudan University, Shanghai, China
| | - Houbao Liu
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Zhao Zhang
- MOE Key Laboratory of Metabolism and Molecular Medicine, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Fudan University, Shanghai, China
| | - Yuchen Jiao
- State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Zhi Xie
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China
| | - Wenqing Qiu
- MOE Key Laboratory of Metabolism and Molecular Medicine, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences and Shanghai Xuhui Central Hospital, Fudan University, Shanghai, China. .,Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai, China.
| | - Yun Liu
- MOE Key Laboratory of Metabolism and Molecular Medicine, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences and Shanghai Xuhui Central Hospital, Fudan University, Shanghai, China. .,State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Institutes of Brain Science, Fudan University, Shanghai, China.
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24
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Liu S, Zhou C, Meng G, Wan T, Tang M, Yang C, Murphy RW, Fan Z, Liu Y, Zeng T, Zhao Y, Liu S. Evolution and diversification of Mountain voles (Rodentia: Cricetidae). Commun Biol 2022; 5:1417. [PMID: 36572770 PMCID: PMC9792541 DOI: 10.1038/s42003-022-04371-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2022] [Accepted: 12/13/2022] [Indexed: 12/27/2022] Open
Abstract
The systematics of the Cricetid genus Neodon have long been fraught with uncertainty due to sampling issues and a lack of comprehensive datasets. To gain better insights into the phylogeny and evolution of Neodon, we systematically sampled Neodon across the Hengduan and Himalayan Mountains, which cover most of its range in China. Analyses of skulls, teeth, and bacular structures revealed 15 distinct patterns corresponding to 15 species of Neodon. In addition to morphological analyses, we generated a high-quality reference genome for the mountain vole and generated whole-genome sequencing data for 47 samples. Phylogenomic analyses supported the recognition of six new species, revealing a long-term underestimation of Neodon diversity. We further identified positively selected genes potentially related to high-elevation adaptation. Together, our results illuminate how climate change caused the plateau to become the centre of Neodon origin and diversification and how mountain voles have adapted to the hypoxic high-altitude plateau environment.
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Affiliation(s)
- Shaoying Liu
- Sichuan Academy of Forestry, No.18, Xinhui xilu, Chengdu, 610081, China.
| | - Chengran Zhou
- BGI-Shenzhen, Shenzhen, 518083, China
- Key Laboratory of Bio-Resource and Eco-Environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, 610065, China
| | - Guanliang Meng
- Zoological Research Museum Alexander Koenig, D-53113, Bonn, Germany
| | - Tao Wan
- Sichuan Academy of Forestry, No.18, Xinhui xilu, Chengdu, 610081, China
| | - Mingkun Tang
- Sichuan Academy of Forestry, No.18, Xinhui xilu, Chengdu, 610081, China
| | | | - Robert W Murphy
- Reptilia Sanctuary and Education Centre, Concord, ON, L4K 2N6, Canada
- Centre for Biodiversity and Conservation Biology, Royal Ontario Museum, Toronto, ON, M5S 2C6, Canada
| | - Zhenxin Fan
- Key Laboratory of Bio-Resource and Eco-Environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, 610065, China
| | - Yang Liu
- Sichuan Academy of Forestry, No.18, Xinhui xilu, Chengdu, 610081, China
| | - Tao Zeng
- Key Laboratory of Bio-Resource and Eco-Environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, 610065, China
| | - Yun Zhao
- Key Laboratory of Bio-Resource and Eco-Environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, 610065, China
| | - Shanlin Liu
- Department of Entomology, College of Plant Protection, China Agricultural University, Beijing, 100193, China.
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25
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Toh H, Yang C, Formenti G, Raja K, Yan L, Tracey A, Chow W, Howe K, Bergeron LA, Zhang G, Haase B, Mountcastle J, Fedrigo O, Fogg J, Kirilenko B, Munegowda C, Hiller M, Jain A, Kihara D, Rhie A, Phillippy AM, Swanson SA, Jiang P, Clegg DO, Jarvis ED, Thomson JA, Stewart R, Chaisson MJP, Bukhman YV. A haplotype-resolved genome assembly of the Nile rat facilitates exploration of the genetic basis of diabetes. BMC Biol 2022; 20:245. [DOI: 10.1186/s12915-022-01427-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Accepted: 09/29/2022] [Indexed: 11/09/2022] Open
Abstract
Abstract
Background
The Nile rat (Avicanthis niloticus) is an important animal model because of its robust diurnal rhythm, a cone-rich retina, and a propensity to develop diet-induced diabetes without chemical or genetic modifications. A closer similarity to humans in these aspects, compared to the widely used Mus musculus and Rattus norvegicus models, holds the promise of better translation of research findings to the clinic.
Results
We report a 2.5 Gb, chromosome-level reference genome assembly with fully resolved parental haplotypes, generated with the Vertebrate Genomes Project (VGP). The assembly is highly contiguous, with contig N50 of 11.1 Mb, scaffold N50 of 83 Mb, and 95.2% of the sequence assigned to chromosomes. We used a novel workflow to identify 3613 segmental duplications and quantify duplicated genes. Comparative analyses revealed unique genomic features of the Nile rat, including some that affect genes associated with type 2 diabetes and metabolic dysfunctions. We discuss 14 genes that are heterozygous in the Nile rat or highly diverged from the house mouse.
Conclusions
Our findings reflect the exceptional level of genomic resolution present in this assembly, which will greatly expand the potential of the Nile rat as a model organism.
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26
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Jarvis ED, Formenti G, Rhie A, Guarracino A, Yang C, Wood J, Tracey A, Thibaud-Nissen F, Vollger MR, Porubsky D, Cheng H, Asri M, Logsdon GA, Carnevali P, Chaisson MJP, Chin CS, Cody S, Collins J, Ebert P, Escalona M, Fedrigo O, Fulton RS, Fulton LL, Garg S, Gerton JL, Ghurye J, Granat A, Green RE, Harvey W, Hasenfeld P, Hastie A, Haukness M, Jaeger EB, Jain M, Kirsche M, Kolmogorov M, Korbel JO, Koren S, Korlach J, Lee J, Li D, Lindsay T, Lucas J, Luo F, Marschall T, Mitchell MW, McDaniel J, Nie F, Olsen HE, Olson ND, Pesout T, Potapova T, Puiu D, Regier A, Ruan J, Salzberg SL, Sanders AD, Schatz MC, Schmitt A, Schneider VA, Selvaraj S, Shafin K, Shumate A, Stitziel NO, Stober C, Torrance J, Wagner J, Wang J, Wenger A, Xiao C, Zimin AV, Zhang G, Wang T, Li H, Garrison E, Haussler D, Hall I, Zook JM, Eichler EE, Phillippy AM, Paten B, Howe K, Miga KH. Semi-automated assembly of high-quality diploid human reference genomes. Nature 2022; 611:519-531. [PMID: 36261518 PMCID: PMC9668749 DOI: 10.1038/s41586-022-05325-5] [Citation(s) in RCA: 91] [Impact Index Per Article: 30.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2021] [Accepted: 09/06/2022] [Indexed: 01/01/2023]
Abstract
The current human reference genome, GRCh38, represents over 20 years of effort to generate a high-quality assembly, which has benefitted society1,2. However, it still has many gaps and errors, and does not represent a biological genome as it is a blend of multiple individuals3,4. Recently, a high-quality telomere-to-telomere reference, CHM13, was generated with the latest long-read technologies, but it was derived from a hydatidiform mole cell line with a nearly homozygous genome5. To address these limitations, the Human Pangenome Reference Consortium formed with the goal of creating high-quality, cost-effective, diploid genome assemblies for a pangenome reference that represents human genetic diversity6. Here, in our first scientific report, we determined which combination of current genome sequencing and assembly approaches yield the most complete and accurate diploid genome assembly with minimal manual curation. Approaches that used highly accurate long reads and parent-child data with graph-based haplotype phasing during assembly outperformed those that did not. Developing a combination of the top-performing methods, we generated our first high-quality diploid reference assembly, containing only approximately four gaps per chromosome on average, with most chromosomes within ±1% of the length of CHM13. Nearly 48% of protein-coding genes have non-synonymous amino acid changes between haplotypes, and centromeric regions showed the highest diversity. Our findings serve as a foundation for assembling near-complete diploid human genomes at scale for a pangenome reference to capture global genetic variation from single nucleotides to structural rearrangements.
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Affiliation(s)
- Erich D. Jarvis
- grid.134907.80000 0001 2166 1519Vertebrate Genome Laboratory, The Rockefeller University, New York, NY USA ,grid.413575.10000 0001 2167 1581Howard Hughes Medical Institute, Chevy Chase, MD USA
| | - Giulio Formenti
- grid.134907.80000 0001 2166 1519Vertebrate Genome Laboratory, The Rockefeller University, New York, NY USA
| | - Arang Rhie
- grid.94365.3d0000 0001 2297 5165Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD USA
| | - Andrea Guarracino
- grid.510779.d0000 0004 9414 6915Genomics Research Centre, Human Technopole, Viale Rita Levi-Montalcini, Milan, Italy
| | - Chentao Yang
- grid.21155.320000 0001 2034 1839BGI-Shenzhen, Shenzhen, China
| | - Jonathan Wood
- grid.10306.340000 0004 0606 5382Tree of Life, Wellcome Sanger Institute, Cambridge, UK
| | - Alan Tracey
- grid.10306.340000 0004 0606 5382Tree of Life, Wellcome Sanger Institute, Cambridge, UK
| | - Francoise Thibaud-Nissen
- grid.94365.3d0000 0001 2297 5165National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD USA
| | - Mitchell R. Vollger
- grid.34477.330000000122986657Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA USA
| | - David Porubsky
- grid.34477.330000000122986657Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA USA
| | - Haoyu Cheng
- grid.65499.370000 0001 2106 9910Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA USA ,grid.38142.3c000000041936754XDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA USA
| | - Mobin Asri
- grid.205975.c0000 0001 0740 6917UC Santa Cruz Genomics Institute, University of California, Santa Cruz, CA USA
| | - Glennis A. Logsdon
- grid.34477.330000000122986657Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA USA
| | - Paolo Carnevali
- grid.507326.50000 0004 6090 4941Chan Zuckerberg Initiative, Redwood City, CA USA
| | - Mark J. P. Chaisson
- grid.42505.360000 0001 2156 6853Quantitative and Computational Biology, University of Southern California, Los Angeles, CA USA
| | | | - Sarah Cody
- grid.4367.60000 0001 2355 7002McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO USA
| | - Joanna Collins
- grid.10306.340000 0004 0606 5382Tree of Life, Wellcome Sanger Institute, Cambridge, UK
| | - Peter Ebert
- grid.411327.20000 0001 2176 9917Institute for Medical Biometry and Bioinformatics, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany
| | - Merly Escalona
- grid.205975.c0000 0001 0740 6917Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA USA
| | - Olivier Fedrigo
- grid.134907.80000 0001 2166 1519Vertebrate Genome Laboratory, The Rockefeller University, New York, NY USA
| | - Robert S. Fulton
- grid.4367.60000 0001 2355 7002McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO USA
| | - Lucinda L. Fulton
- grid.4367.60000 0001 2355 7002McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO USA
| | - Shilpa Garg
- grid.5254.60000 0001 0674 042XDepartment of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Jennifer L. Gerton
- grid.250820.d0000 0000 9420 1591Stowers Institute for Medical Research, Kansas City, MO USA
| | - Jay Ghurye
- grid.504403.6Dovetail Genomics, Scotts Valley, CA USA
| | | | - Richard E. Green
- grid.205975.c0000 0001 0740 6917UC Santa Cruz Genomics Institute, University of California, Santa Cruz, CA USA
| | - William Harvey
- grid.34477.330000000122986657Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA USA
| | - Patrick Hasenfeld
- grid.4709.a0000 0004 0495 846XEuropean Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
| | - Alex Hastie
- grid.470262.50000 0004 0473 1353Bionano Genomics, San Diego, CA USA
| | - Marina Haukness
- grid.205975.c0000 0001 0740 6917UC Santa Cruz Genomics Institute, University of California, Santa Cruz, CA USA
| | - Erich B. Jaeger
- grid.185669.50000 0004 0507 3954Illumina, Inc., San Diego, CA USA
| | - Miten Jain
- grid.205975.c0000 0001 0740 6917UC Santa Cruz Genomics Institute, University of California, Santa Cruz, CA USA
| | - Melanie Kirsche
- grid.21107.350000 0001 2171 9311Department of Computer Science, Johns Hopkins University, Baltimore, MD USA
| | - Mikhail Kolmogorov
- grid.266100.30000 0001 2107 4242Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA USA
| | - Jan O. Korbel
- grid.4709.a0000 0004 0495 846XEuropean Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
| | - Sergey Koren
- grid.94365.3d0000 0001 2297 5165Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD USA
| | - Jonas Korlach
- grid.423340.20000 0004 0640 9878Pacific Biosciences, Menlo Park, CA USA
| | - Joyce Lee
- grid.470262.50000 0004 0473 1353Bionano Genomics, San Diego, CA USA
| | - Daofeng Li
- grid.4367.60000 0001 2355 7002Department of Genetics, Washington University School of Medicine, St. Louis, MO USA ,grid.4367.60000 0001 2355 7002The Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, MO USA
| | - Tina Lindsay
- grid.4367.60000 0001 2355 7002McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO USA
| | - Julian Lucas
- grid.205975.c0000 0001 0740 6917UC Santa Cruz Genomics Institute, University of California, Santa Cruz, CA USA
| | - Feng Luo
- grid.26090.3d0000 0001 0665 0280School of Computing, Clemson University, Clemson, SC USA
| | - Tobias Marschall
- grid.411327.20000 0001 2176 9917Institute for Medical Biometry and Bioinformatics, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany
| | - Matthew W. Mitchell
- grid.282012.b0000 0004 0627 5048Coriell Institute for Medical Research, Camden, NJ USA
| | - Jennifer McDaniel
- grid.94225.38000000012158463XMaterial Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD USA
| | - Fan Nie
- grid.216417.70000 0001 0379 7164Hunan Provincial Key Lab on Bioinformatics, School of Computer Science and Engineering, Central South University, Changsha, China
| | - Hugh E. Olsen
- grid.205975.c0000 0001 0740 6917UC Santa Cruz Genomics Institute, University of California, Santa Cruz, CA USA
| | - Nathan D. Olson
- grid.94225.38000000012158463XMaterial Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD USA
| | - Trevor Pesout
- grid.205975.c0000 0001 0740 6917UC Santa Cruz Genomics Institute, University of California, Santa Cruz, CA USA
| | - Tamara Potapova
- grid.250820.d0000 0000 9420 1591Stowers Institute for Medical Research, Kansas City, MO USA
| | - Daniela Puiu
- grid.21107.350000 0001 2171 9311Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD USA
| | - Allison Regier
- grid.511991.40000 0004 4910 5831DNAnexus, Mountain View, CA USA
| | - Jue Ruan
- grid.410727.70000 0001 0526 1937Agricultural Genomics Institute, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Steven L. Salzberg
- grid.21107.350000 0001 2171 9311Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD USA
| | - Ashley D. Sanders
- grid.419491.00000 0001 1014 0849Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany
| | - Michael C. Schatz
- grid.21107.350000 0001 2171 9311Department of Computer Science, Johns Hopkins University, Baltimore, MD USA
| | | | - Valerie A. Schneider
- grid.94365.3d0000 0001 2297 5165National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD USA
| | | | - Kishwar Shafin
- grid.205975.c0000 0001 0740 6917UC Santa Cruz Genomics Institute, University of California, Santa Cruz, CA USA
| | - Alaina Shumate
- grid.21107.350000 0001 2171 9311Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD USA
| | - Nathan O. Stitziel
- grid.4367.60000 0001 2355 7002McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO USA ,grid.4367.60000 0001 2355 7002Department of Genetics, Washington University School of Medicine, St. Louis, MO USA ,grid.4367.60000 0001 2355 7002Cardiovascular Division, John T. Milliken Department of Internal Medicine, Washington University School of Medicine, St. Louis, USA
| | - Catherine Stober
- grid.4709.a0000 0004 0495 846XEuropean Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
| | - James Torrance
- grid.10306.340000 0004 0606 5382Tree of Life, Wellcome Sanger Institute, Cambridge, UK
| | - Justin Wagner
- grid.94225.38000000012158463XMaterial Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD USA
| | - Jianxin Wang
- grid.216417.70000 0001 0379 7164Hunan Provincial Key Lab on Bioinformatics, School of Computer Science and Engineering, Central South University, Changsha, China
| | - Aaron Wenger
- grid.423340.20000 0004 0640 9878Pacific Biosciences, Menlo Park, CA USA
| | - Chuanle Xiao
- grid.12981.330000 0001 2360 039XState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China
| | - Aleksey V. Zimin
- grid.21107.350000 0001 2171 9311Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD USA
| | - Guojie Zhang
- grid.13402.340000 0004 1759 700XCenter for Evolutionary & Organismal Biology, Zhejiang University School of Medicine, Hangzhou, China
| | - Ting Wang
- grid.4367.60000 0001 2355 7002McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO USA ,grid.4367.60000 0001 2355 7002Department of Genetics, Washington University School of Medicine, St. Louis, MO USA ,grid.4367.60000 0001 2355 7002The Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, MO USA
| | - Heng Li
- grid.65499.370000 0001 2106 9910Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA USA
| | - Erik Garrison
- grid.267301.10000 0004 0386 9246Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN USA
| | - David Haussler
- grid.413575.10000 0001 2167 1581Howard Hughes Medical Institute, Chevy Chase, MD USA ,grid.205975.c0000 0001 0740 6917Department of Ecology and Evolutionary Biology, University of California Santa Cruz, Santa Cruz, CA USA
| | - Ira Hall
- grid.47100.320000000419368710Yale School of Medicine, New Haven, CT USA
| | - Justin M. Zook
- grid.94225.38000000012158463XMaterial Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD USA
| | - Evan E. Eichler
- grid.413575.10000 0001 2167 1581Howard Hughes Medical Institute, Chevy Chase, MD USA ,grid.34477.330000000122986657Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA USA
| | - Adam M. Phillippy
- grid.94365.3d0000 0001 2297 5165Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD USA
| | - Benedict Paten
- grid.205975.c0000 0001 0740 6917UC Santa Cruz Genomics Institute, University of California, Santa Cruz, CA USA
| | - Kerstin Howe
- grid.10306.340000 0004 0606 5382Tree of Life, Wellcome Sanger Institute, Cambridge, UK
| | - Karen H. Miga
- grid.205975.c0000 0001 0740 6917UC Santa Cruz Genomics Institute, University of California, Santa Cruz, CA USA
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27
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Bergman J, Schierup MH. Evolutionary dynamics of pseudoautosomal region 1 in humans and great apes. Genome Biol 2022; 23:215. [PMID: 36253794 PMCID: PMC9575207 DOI: 10.1186/s13059-022-02784-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Accepted: 09/30/2022] [Indexed: 12/03/2022] Open
Abstract
BACKGROUND The pseudoautosomal region 1 (PAR1) is a 2.7 Mb telomeric region of human sex chromosomes. PAR1 has a crucial role in ensuring proper segregation of sex chromosomes during male meiosis, exposing it to extreme recombination and mutation processes. We investigate PAR1 evolution using population genomic datasets of extant humans, eight populations of great apes, and two archaic human genome sequences. RESULTS We find that PAR1 is fast evolving and closer to evolutionary nucleotide equilibrium than autosomal telomeres. We detect a difference between substitution patterns and extant diversity in PAR1, mainly driven by the conflict between strong mutation and recombination-associated fixation bias at CpG sites. We detect excess C-to-G mutations in PAR1 of all great apes, specific to the mutagenic effect of male recombination. Despite recent evidence for Y chromosome introgression from humans into Neanderthals, we find that the Neanderthal PAR1 retained similarity to the Denisovan sequence. We find differences between substitution spectra of these archaics suggesting rapid evolution of PAR1 in recent hominin history. Frequency analysis of alleles segregating in females and males provided no evidence for recent sexual antagonism in this region. We study repeat content and double-strand break hotspot regions in PAR1 and find that they may play roles in ensuring the obligate X-Y recombination event during male meiosis. CONCLUSIONS Our study provides an unprecedented quantification of population genetic forces governing PAR1 biology across extant and extinct hominids. PAR1 evolutionary dynamics are predominantly governed by recombination processes with a strong impact on mutation patterns across all species.
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Affiliation(s)
- Juraj Bergman
- Bioinformatics Research Centre, Aarhus University, DK-8000 Aarhus C, Denmark
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28
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Genomic basis of neotropical primate adaptations. Proc Natl Acad Sci U S A 2022; 119:e2213527119. [PMID: 36170247 PMCID: PMC9546596 DOI: 10.1073/pnas.2213527119] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
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29
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de Manuel M, Wu FL, Przeworski M. A paternal bias in germline mutation is widespread in amniotes and can arise independently of cell division numbers. eLife 2022; 11:e80008. [PMID: 35916372 PMCID: PMC9439683 DOI: 10.7554/elife.80008] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Accepted: 08/01/2022] [Indexed: 11/13/2022] Open
Abstract
In humans and other mammals, germline mutations are more likely to arise in fathers than in mothers. Although this sex bias has long been attributed to DNA replication errors in spermatogenesis, recent evidence from humans points to the importance of mutagenic processes that do not depend on cell division, calling into question our understanding of this basic phenomenon. Here, we infer the ratio of paternal-to-maternal mutations, α, in 42 species of amniotes, from putatively neutral substitution rates of sex chromosomes and autosomes. Despite marked differences in gametogenesis, physiologies and environments across species, fathers consistently contribute more mutations than mothers in all the species examined, including mammals, birds, and reptiles. In mammals, α is as high as 4 and correlates with generation times; in birds and snakes, α appears more stable around 2. These observations are consistent with a simple model, in which mutations accrue at equal rates in both sexes during early development and at a higher rate in the male germline after sexual differentiation, with a conserved paternal-to-maternal ratio across species. Thus, α may reflect the relative contributions of two or more developmental phases to total germline mutations, and is expected to depend on generation time even if mutations do not track cell divisions.
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Affiliation(s)
- Marc de Manuel
- Department of Biological Sciences, Columbia UniversityNew YorkUnited States
| | - Felix L Wu
- Department of Biological Sciences, Columbia UniversityNew YorkUnited States
| | - Molly Przeworski
- Department of Systems Biology, Columbia UniversityNew YorkUnited States
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30
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Steinberg ER, Bressa MJ, Mudry MD. Sex chromosome systems in Neotropical Primates: What have we learnt so far from cytogenetics and genomics? J Evol Biol 2022; 35:1589-1600. [PMID: 35731796 DOI: 10.1111/jeb.14039] [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: 01/30/2022] [Revised: 05/10/2022] [Accepted: 05/26/2022] [Indexed: 11/29/2022]
Abstract
Neotropical Primates (Platyrrhini) show great diversity in their life histories, ecology, behaviour and genetics. This diversity extends to their chromosome complements, both to autosomes and to sex chromosomes. In this contribution, we will review what is currently known about sex chromosomes in this group, both from cytogenetic and from genomic evidence. The X and Y chromosomes in Neotropical Primates, also known as New World Monkeys, have striking structural differences compared with Old World Monkeys when Catarrhini sex chromosomes are considered. The XY bivalent displays a different meiotic behaviour in prophase I, and their Y chromosome shows extensive genomic differences. Even though the most widespread sex chromosome system is the XX/XY and thus considered the ancestral one for Platyrrhini, modifications of this sexual system are observed within this group. Multiple sex chromosome systems originated from Y-autosome translocations were described in several genera (Aotus, Callimico and Alouatta). In the howler monkeys, genus Alouatta, an independent origin of the sexual systems in South American and Mesoamerican species was postulated. All the above-mentioned evidence suggests that the Y chromosome of Platyrrhini has a different evolutionary history compared with the Catarrhini Y. There is still much to understand regarding their sex chromosome systems.
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Affiliation(s)
- Eliana Ruth Steinberg
- Grupo de Investigación en Biología Evolutiva (GIBE). Instituto de Ecología, Genética y Evolución de Buenos Aires (IEGEBA), Departamento de Ecología, Genética y Evolución (EGE), Facultad de Ciencias Exactas y Naturales (FCEyN), Universidad de Buenos Aires (UBA), CONICET, Ciudad Autónoma de Buenos Aires, Buenos Aires, Argentina
| | - María José Bressa
- Grupo de Citogenética de Insectos. Instituto de Ecología, Genética y Evolución de Buenos Aires (IEGEBA), Departamento de Ecología, Genética y Evolución (EGE), Facultad de Ciencias Exactas y Naturales (FCEyN), Universidad de Buenos Aires (UBA), CONICET, Ciudad Autónoma de Buenos Aires, Buenos Aires, Argentina
| | - Marta Dolores Mudry
- Grupo de Investigación en Biología Evolutiva (GIBE). Instituto de Ecología, Genética y Evolución de Buenos Aires (IEGEBA), Departamento de Ecología, Genética y Evolución (EGE), Facultad de Ciencias Exactas y Naturales (FCEyN), Universidad de Buenos Aires (UBA), CONICET, Ciudad Autónoma de Buenos Aires, Buenos Aires, Argentina
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31
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A complete, telomere-to-telomere human genome sequence presents new opportunities for evolutionary genomics. Nat Methods 2022; 19:635-638. [PMID: 35689027 DOI: 10.1038/s41592-022-01512-4] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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32
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Formenti G, Rhie A, Walenz BP, Thibaud-Nissen F, Shafin K, Koren S, Myers EW, Jarvis ED, Phillippy AM. Merfin: improved variant filtering, assembly evaluation and polishing via k-mer validation. Nat Methods 2022; 19:696-704. [PMID: 35361932 PMCID: PMC9745813 DOI: 10.1038/s41592-022-01445-y] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2021] [Accepted: 03/07/2022] [Indexed: 12/15/2022]
Abstract
Variant calling has been widely used for genotyping and for improving the consensus accuracy of long-read assemblies. Variant calls are commonly hard-filtered with user-defined cutoffs. However, it is impossible to define a single set of optimal cutoffs, as the calls heavily depend on the quality of the reads, the variant caller of choice and the quality of the unpolished assembly. Here, we introduce Merfin, a k-mer based variant-filtering algorithm for improved accuracy in genotyping and genome assembly polishing. Merfin evaluates each variant based on the expected k-mer multiplicity in the reads, independently of the quality of the read alignment and variant caller's internal score. Merfin increased the precision of genotyped calls in several benchmarks, improved consensus accuracy and reduced frameshift errors when applied to human and nonhuman assemblies built from Pacific Biosciences HiFi and continuous long reads or Oxford Nanopore reads, including the first complete human genome. Moreover, we introduce assembly quality and completeness metrics that account for the expected genomic copy numbers.
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Affiliation(s)
- Giulio Formenti
- Vertebrate Genome Laboratory, The Rockefeller University, New York, NY, USA.
- Laboratory of Neurogenetics of Language, The Rockefeller University, New York, NY, USA.
- Howard Hughes Medical Institute, Chevy Chase, MD, USA.
| | - Arang Rhie
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA.
| | - Brian P Walenz
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Françoise Thibaud-Nissen
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA
| | | | - Sergey Koren
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Eugene W Myers
- Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
| | - Erich D Jarvis
- Vertebrate Genome Laboratory, The Rockefeller University, New York, NY, USA
- Laboratory of Neurogenetics of Language, The Rockefeller University, New York, NY, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
| | - Adam M Phillippy
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
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33
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Aitken RJ. Role of sperm DNA damage in creating de novo mutations in human offspring: the ‘post-meiotic oocyte collusion’ hypothesis. Reprod Biomed Online 2022; 45:109-124. [PMID: 35513995 DOI: 10.1016/j.rbmo.2022.03.012] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Revised: 03/10/2022] [Accepted: 03/11/2022] [Indexed: 11/24/2022]
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34
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Yang X, Chen Z, Wang Z, He G, Li Z, Shi Y, Gong N, Zhao B, Kuang Y, Takahashi E, Li W. A natural marmoset model of genetic generalized epilepsy. Mol Brain 2022; 15:16. [PMID: 35144651 PMCID: PMC8832845 DOI: 10.1186/s13041-022-00901-2] [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: 12/28/2021] [Accepted: 01/28/2022] [Indexed: 11/10/2022] Open
Abstract
Epilepsy has been extensively studied as a common neurological disease. Efforts have been made on rodent and other animal models to reveal the pathogenic mechanisms of epilepsy and develop new drugs for treatment. However, the features of current epilepsy models cannot fully mimic different types of epilepsy in humans, hence non-human primate models of epilepsy are required. The common marmoset (Callithrix jacchus) is a New World monkey that is widely used to study brain function. Here, we present a natural marmoset model of generalized epilepsy. In this unique marmoset family, generalized epilepsy was successfully induced by handling operations in some individuals. We mapped the marmoset family with handling-sensitive epilepsy and found that the epileptic phenotype can be inherited. These marmosets were more sensitive to the epilepsy inducers pentylenetetrazol. Using electrocorticogram (ECoG) recordings, we detected epileptiform discharge in marmosets with a history of seizures. In summary, we report a family of marmosets with generalized seizures induced by handling operations. This epileptic marmoset family provides insights to better understand the mechanism of generalized epilepsy and helps to develop new therapeutic methods.
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Affiliation(s)
- Xiangyu Yang
- Bio-X Institutes, Key Laboratory for the Genetics of Development and Neuropsychiatric Disorders (Ministry of Education), Shanghai Key Laboratory of Psychotic Disorders, and Brain Science and Technology Research Center, Institute of Psychology and Behavioral Sciences, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Zhitang Chen
- Bio-X Institutes, Key Laboratory for the Genetics of Development and Neuropsychiatric Disorders (Ministry of Education), Shanghai Key Laboratory of Psychotic Disorders, and Brain Science and Technology Research Center, Institute of Psychology and Behavioral Sciences, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Ziying Wang
- Bio-X Institutes, Key Laboratory for the Genetics of Development and Neuropsychiatric Disorders (Ministry of Education), Shanghai Key Laboratory of Psychotic Disorders, and Brain Science and Technology Research Center, Institute of Psychology and Behavioral Sciences, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Guang He
- Bio-X Institutes, Key Laboratory for the Genetics of Development and Neuropsychiatric Disorders (Ministry of Education), Shanghai Key Laboratory of Psychotic Disorders, and Brain Science and Technology Research Center, Institute of Psychology and Behavioral Sciences, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Zhiqiang Li
- Bio-X Institutes, Key Laboratory for the Genetics of Development and Neuropsychiatric Disorders (Ministry of Education), Shanghai Key Laboratory of Psychotic Disorders, and Brain Science and Technology Research Center, Institute of Psychology and Behavioral Sciences, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Yongyong Shi
- Bio-X Institutes, Key Laboratory for the Genetics of Development and Neuropsychiatric Disorders (Ministry of Education), Shanghai Key Laboratory of Psychotic Disorders, and Brain Science and Technology Research Center, Institute of Psychology and Behavioral Sciences, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Neng Gong
- Institute of Neuroscience, Key Laboratory of Primate Neurobiology, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Binglei Zhao
- Bio-X Institutes, Key Laboratory for the Genetics of Development and Neuropsychiatric Disorders (Ministry of Education), Shanghai Key Laboratory of Psychotic Disorders, and Brain Science and Technology Research Center, Institute of Psychology and Behavioral Sciences, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Yifang Kuang
- Bio-X Institutes, Key Laboratory for the Genetics of Development and Neuropsychiatric Disorders (Ministry of Education), Shanghai Key Laboratory of Psychotic Disorders, and Brain Science and Technology Research Center, Institute of Psychology and Behavioral Sciences, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Eiki Takahashi
- Bio-X Institutes, Key Laboratory for the Genetics of Development and Neuropsychiatric Disorders (Ministry of Education), Shanghai Key Laboratory of Psychotic Disorders, and Brain Science and Technology Research Center, Institute of Psychology and Behavioral Sciences, Shanghai Jiao Tong University, Shanghai, 200240, China.
| | - Weidong Li
- Bio-X Institutes, Key Laboratory for the Genetics of Development and Neuropsychiatric Disorders (Ministry of Education), Shanghai Key Laboratory of Psychotic Disorders, and Brain Science and Technology Research Center, Institute of Psychology and Behavioral Sciences, Shanghai Jiao Tong University, Shanghai, 200240, China. .,WLA Laboratories, World Laureates Association, Shanghai, 201203, China.
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35
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Bergeron LA, Besenbacher S, Turner T, Versoza CJ, Wang RJ, Price AL, Armstrong E, Riera M, Carlson J, Chen HY, Hahn MW, Harris K, Kleppe AS, López-Nandam EH, Moorjani P, Pfeifer SP, Tiley GP, Yoder AD, Zhang G, Schierup MH. The mutationathon highlights the importance of reaching standardization in estimates of pedigree-based germline mutation rates. eLife 2022; 11:73577. [PMID: 35018888 PMCID: PMC8830884 DOI: 10.7554/elife.73577] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Accepted: 01/11/2022] [Indexed: 11/13/2022] Open
Abstract
In the past decade, several studies have estimated the human per-generation germline mutation rate using large pedigrees. More recently, estimates for various nonhuman species have been published. However, methodological differences among studies in detecting germline mutations and estimating mutation rates make direct comparisons difficult. Here, we describe the many different steps involved in estimating pedigree-based mutation rates, including sampling, sequencing, mapping, variant calling, filtering, and appropriately accounting for false-positive and false-negative rates. For each step, we review the different methods and parameter choices that have been used in the recent literature. Additionally, we present the results from a ‘Mutationathon,’ a competition organized among five research labs to compare germline mutation rate estimates for a single pedigree of rhesus macaques. We report almost a twofold variation in the final estimated rate among groups using different post-alignment processing, calling, and filtering criteria, and provide details into the sources of variation across studies. Though the difference among estimates is not statistically significant, this discrepancy emphasizes the need for standardized methods in mutation rate estimations and the difficulty in comparing rates from different studies. Finally, this work aims to provide guidelines for computational and statistical benchmarks for future studies interested in identifying germline mutations from pedigrees.
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Affiliation(s)
- Lucie A Bergeron
- Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Søren Besenbacher
- Department of Molecular Medicine (MOMA), Aarhus University, Aarhus N, Denmark
| | - Tychele Turner
- Department of Genetics, Washington University in St. Louis, Saint Louis, United States
| | - Cyril J Versoza
- Center for Evolution and Medicine, Arizona State University, Tempe, United States
| | - Richard J Wang
- Department of Biology, Indiana University, Bloomington, United States
| | - Alivia Lee Price
- Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Ellie Armstrong
- Department of Biology, Stanford University, Stanford, United States
| | - Meritxell Riera
- Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark
| | - Jedidiah Carlson
- Department of Genome Sciences, University of Washington, Seattle, United States
| | - Hwei-Yen Chen
- Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Matthew W Hahn
- Department of Biology, Indiana University, Bloomington, United States
| | - Kelley Harris
- Department of Genome Sciences, University of Washington, Seattle, United States
| | | | | | - Priya Moorjani
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, United States
| | - Susanne P Pfeifer
- School of Life Sciences, Arizona State University, Tempe, United States
| | - George P Tiley
- Department of Biology, Duke University, Durham, United States
| | - Anne D Yoder
- Department of Biology, Duke University, Durham, United States
| | - Guojie Zhang
- Department of Biology, University of Copenhagen, Copenhagen, Denmark
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