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Cousins T, Scally A, Durbin R. A structured coalescent model reveals deep ancestral structure shared by all modern humans. Nat Genet 2025; 57:856-864. [PMID: 40102687 PMCID: PMC11985351 DOI: 10.1038/s41588-025-02117-1] [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: 03/24/2024] [Accepted: 02/05/2025] [Indexed: 03/20/2025]
Abstract
Understanding the history of admixture events and population size changes leading to modern humans is central to human evolutionary genetics. Here we introduce a coalescence-based hidden Markov model, cobraa, that explicitly represents an ancestral population split and rejoin, and demonstrate its application on simulated and real data across multiple species. Using cobraa, we present evidence for an extended period of structure in the history of all modern humans, in which two ancestral populations that diverged ~1.5 million years ago came together in an admixture event ~300 thousand years ago, in a ratio of ~80:20%. Immediately after their divergence, we detect a strong bottleneck in the major ancestral population. We inferred regions of the present-day genome derived from each ancestral population, finding that material from the minority correlates strongly with distance to coding sequence, suggesting it was deleterious against the majority background. Moreover, we found a strong correlation between regions of majority ancestry and human-Neanderthal or human-Denisovan divergence, suggesting the majority population was also ancestral to those archaic humans.
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Affiliation(s)
- Trevor Cousins
- Department of Genetics, University of Cambridge, Cambridge, UK
| | - Aylwyn Scally
- Department of Genetics, University of Cambridge, Cambridge, UK
| | - Richard Durbin
- Department of Genetics, University of Cambridge, Cambridge, UK.
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2
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Ishigohoka J, Liedvogel M. High-recombining genomic regions affect demography inference based on ancestral recombination graphs. Genetics 2025; 229:iyaf004. [PMID: 39790013 PMCID: PMC11912872 DOI: 10.1093/genetics/iyaf004] [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: 02/05/2024] [Accepted: 12/23/2024] [Indexed: 01/12/2025] Open
Abstract
Multiple methods of demography inference are based on the ancestral recombination graph. This powerful approach uses observed mutations to model local genealogies changing along chromosomes by historical recombination events. However, inference of underlying genealogies is difficult in regions with high recombination rate relative to mutation rate due to the lack of mutations representing genealogies. Despite the prevalence of high-recombining genomic regions in some organisms, such as birds, its impact on demography inference based on ancestral recombination graphs has not been well studied. Here, we use population genomic simulations to investigate the impact of high-recombining regions on demography inference based on ancestral recombination graphs. We demonstrate that inference of effective population size and the time of population split events is systematically affected when high-recombining regions cover wide breadths of the chromosomes. Excluding high-recombining genomic regions can practically mitigate this impact, and population genomic inference of recombination maps is informative in defining such regions although the estimated values of local recombination rate can be biased. Finally, we confirm the relevance of our findings in empirical analysis by contrasting demography inferences applied for a bird species, the Eurasian blackcap (Sylvia atricapilla), using different parts of the genome with high and low recombination rates. Our results suggest that demography inference methods based on ancestral recombination graphs should be carried out with caution when applied in species whose genomes contain long stretches of high-recombining regions.
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Affiliation(s)
- Jun Ishigohoka
- Max Planck Research Group Behavioural Genomics, Max Planck Institute for Evolutionary Biology, August-Thienemann-Straße 2, Plön 24306, Germany
| | - Miriam Liedvogel
- Max Planck Research Group Behavioural Genomics, Max Planck Institute for Evolutionary Biology, August-Thienemann-Straße 2, Plön 24306, Germany
- Institute of Avian Research, An der Vogelwarte 21, Wilhelmshaven 26386, Germany
- Department of Biology and Environmental Sciences, Carl von Ossietzky Universität Oldenburg, Ammerländer Heerstraße 114-118, Oldenburg 26129, Germany
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3
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Miyagawa S, DeSalle R, Nóbrega VA, Nitschke R, Okumura M, Tattersall I. Linguistic capacity was present in the Homo sapiens population 135 thousand years ago. Front Psychol 2025; 16:1503900. [PMID: 40134728 PMCID: PMC11933122 DOI: 10.3389/fpsyg.2025.1503900] [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: 09/30/2024] [Accepted: 02/06/2025] [Indexed: 03/27/2025] Open
Abstract
Recent genome-level studies on the divergence of early Homo sapiens, based on single nucleotide polymorphisms, suggest that the initial population division within H. sapiens from the original stem occurred approximately 135 thousand years ago. Given that this and all subsequent divisions led to populations with full linguistic capacity, it is reasonable to assume that the potential for language must have been present at the latest by around 135 thousand years ago, before the first division occurred. Had linguistic capacity developed later, we would expect to find some modern human populations without language, or with some fundamentally different mode of communication. Neither is the case. While current evidence does not tell us exactly when language itself appeared, the genomic studies do allow a fairly accurate estimate of the time by which linguistic capacity must have been present in the modern human lineage. Based on the lower boundary of 135 thousand years ago for language, we propose that language may have triggered the widespread appearance of modern human behavior approximately 100 thousand years ago.
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Affiliation(s)
- Shigeru Miyagawa
- Department of Linguistics and Philosophy, Massachusetts Institute of Technology, Cambridge, MA, United States
- Biosciences Institute, University of São Paulo, São Paulo, Brazil
- Research Center for Super-Smart Society, Seikei University, Tokyo, Japan
| | - Rob DeSalle
- American Museum of Natural History, Institute for Comparative Genomics, New York, NY, United States
| | | | - Remo Nitschke
- Institute for the Interdisciplinary Study of Language Evolution, University of Zurich, Zurich, Switzerland
- Department of Linguistics, University of Arizona, Tucson, AZ, United States
| | - Mercedes Okumura
- Laboratory of Human Evolutionary Studies, Department of Genetics and Evolutionary Biology, University of São Paulo, São Paulo, Brazil
| | - Ian Tattersall
- American Museum of Natural History, Division of Anthropology, New York, NY, United States
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4
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Haba Y, Aardema ML, Afonso MO, Agramonte NM, Albright J, Alho AM, Almeida AP, Alout H, Alten B, Altinli M, Amara Korba R, Andreadis SS, Anghel V, Arich S, Arsenault-Benoit A, Atyame C, Aubry F, Avila FW, Ayala D, Azrag RS, Babayan L, Bear A, Becker N, Bega AG, Bejarano S, Ben-Avi I, Benoit JB, Boubidi SC, Bradshaw WE, Bravo-Barriga D, Bueno-Marí R, Bušić N, Čabanová V, Cabeje B, Caputo B, Cardo MV, Carpenter S, Carreton E, Chouaïbou MS, Christian M, Coetzee M, Conner WR, Cornel A, Culverwell CL, Cupina AI, De Wolf K, Deblauwe I, Deegan B, Delacour-Estrella S, Torre AD, Diaz D, Dool SE, dos Anjos VL, Dugassa S, Ebrahimi B, Eisa SY, Elissa N, Fallatah SA, Faraji A, Fedorova MV, Ferrill E, Fonseca DM, Foss KA, Foxi C, França CM, Fricker SR, Fritz ML, Frontera E, Fuehrer HP, Futami K, Ghallab EH, Girod R, Gordeev MI, Greer D, Gschwind M, Guarido MM, Guat Ney T, Gunay F, Haklay E, Hamad AA, Hang J, Hardy CM, Hartle JW, Hesson JC, Higa Y, Holzapfel CM, Honnen AC, Ionica AM, Jones L, Kadriaj P, Kamal HA, Kamdem C, Karagodin DA, Kasai S, Kavran M, Khater EI, Kiene F, Kim HC, Kioulos I, Klein A, Klemenčić M, Klobučar A, Knutson E, Koenraadt CJ, Kothera L, Kreienbühl P, Labbé P, Lachmi I, Lambrechts L, Landeka N, Lee CH, Lessard BD, Leycegui I, Lundström JO, Lustigman Y, MacIntyre C, Mackay AJ, Magori K, Maia C, Malcolm CA, Marquez RJO, Martins D, Masri RA, McDivitt G, McMinn RJ, Medina J, Mellor KS, Mendoza J, Merdić E, Mesler S, Mestre C, Miranda H, Miterpáková M, Montarsi F, Moskaev AV, Mu T, Möhlmann TW, Namias A, Ng’iru I, Ngangué MF, Novo MT, Orshan L, Oteo JA, Otsuka Y, Panarese R, Paredes-Esquivel C, Paronyan L, Peper ST, Petrić DV, Pilapil K, Pou-Barreto C, Puechmaille SJ, Radespiel U, Rahola N, Raman VK, Redouane H, Reiskind MH, Reissen NM, Rice BL, Robert V, Ruiz-Arrondo I, Salamat R, Salamone A, Sarih M, Satta G, Sawabe K, Schaffner F, Schultz KE, Shaikevich EV, Sharakhov IV, Sharakhova MV, Shatara N, Sibataev AK, Sicard M, Smith E, Smith RC, Smitz N, Soriano N, Spanoudis CG, Stone CM, Studentsky L, Sulesco T, Tantely LM, Thao LK, Tietze N, Tokarz RE, Tsai KH, Tsuda Y, Turić N, Uhran MR, Unlu I, Van Bortel W, Vardanyan H, Vavassori L, Velo E, Venter M, Vignjević G, Vogels CB, Volkava T, Vontas J, Ward HM, Ahmad NW, Weill M, West JD, Wheeler SS, White GS, Wipf NC, Wu TP, Yu KD, Zimmermann E, Zittra C, Korlević P, McAlister E, Lawniczak MK, Schumer M, Rose NH, McBride CS. Ancient origin of an urban underground mosquito. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2025:2025.01.26.634793. [PMID: 39975080 PMCID: PMC11838412 DOI: 10.1101/2025.01.26.634793] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 02/21/2025]
Abstract
Understanding how life is adapting to urban environments represents an important challenge in evolutionary biology. Here we investigate a widely cited example of urban adaptation, Culex pipiens form molestus, also known as the London Underground Mosquito. Population genomic analysis of ~350 contemporary and historical samples counter the popular hypothesis that molestus originated belowground in London less than 200 years ago. Instead, we show that molestus first adapted to human environments aboveground in the Middle East over the course of >1000 years, likely in concert with the rise of agricultural civilizations. Our results highlight the role of early human society in priming taxa for contemporary urban evolution and have important implications for understanding arbovirus transmission.
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Affiliation(s)
- Yuki Haba
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544, USA
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ 08544, USA
| | | | - Maria O. Afonso
- Global Health and Tropical Medicine, GHTM, LA-REAL, Instituto de Higiene e Medicina Tropical, Universidade NOVA de Lisboa, Lisboa, Portugal
| | | | - John Albright
- Shasta Mosquito and Vector Control District, Anderson, CA 96007, USA
| | - Ana Margarida Alho
- Public Health Unit USP Francisco George, Primary Medical Healthcare Cluster Lisbon North, Largo Professor Arnaldo Sampaio, 1549-010 Lisboa, Portugal
| | - Antonio P.G. Almeida
- Global Health and Tropical Medicine, GHTM, LA-REAL, Instituto de Higiene e Medicina Tropical, Universidade NOVA de Lisboa, Lisboa, Portugal
| | - Haoues Alout
- ASTRE, UMR 117, INRAE-CIRAD, Montpellier, France
| | - Bulent Alten
- Hacettepe University, Faculty of Science, Department of Biology, VERG Laboratories, Beytepe, Ankara, Turkey
| | - Mine Altinli
- Institut des Sciences de l’Évolution de Montpellier (UMR 5554, CNRS-UM-IRD-EPHE), Université de Montpellier, Montpellier, 34095, France
- Bernhard-Nocht-Institute for Tropical Medicine, Bernhard Nocht Str. 74, 20359, Hamburg, Germany
| | - Raouf Amara Korba
- Laboratory of Health and Environment, Faculty of Life and Natural Sciences and of Earth and Universe Sciences, Mohamed El Bachir El Ibrahimi University, Bordj Bou Arreridj, 34030, Algeria
| | - Stefanos S. Andreadis
- Institute of Plant Breeding and Genetic Resources, Hellenic Agricultural Organization - DIMITRA, 57001 Thermi, Greece
| | - Vincent Anghel
- Southern Nevada Health District, Las Vegas, NV 89107, USA
| | - Soukaina Arich
- Institut des Sciences de l’Évolution de Montpellier (UMR 5554, CNRS-UM-IRD-EPHE), Université de Montpellier, Montpellier, 34095, France
- Service de Parasitologie et des Maladies Vectorielles, Institut Pasteur du Maroc, Casablanca 20360, Morocco
| | | | - Célestine Atyame
- University of Reunion Island, UMR PIMIT (Processus Infectieux en Milieu Insulaire Tropical) CNRS 9192, INSERM 1187, IRD 249, University of Reunion Island, Reunion Island, France
| | - Fabien Aubry
- Institut Pasteur, Université Paris Cité, CNRS UMR2000, Insect-Virus Interactions Unit, 75015 Paris, France
| | - Frank W. Avila
- Max Planck Tandem Group in Mosquito Reproductive Biology, Universidad de Antioquia, Medellín, 050010, Colombia
| | - Diego Ayala
- MIVEGEC, University of Montpellier, CNRS, IRD, 34394 Montpellier, France
- CIRMF, Franceville, Gabon
| | - Rasha S. Azrag
- Department of Zoology, Faculty of Science, University of Khartoum, Khartoum, Sudan
| | - Lilit Babayan
- National Center of Disease Control and Prevention, Ministry of Health, Yerevan 0025, Republic of Armenia
| | - Allon Bear
- E7 Ministry of Environmental Protection, Ramla, Israel
| | - Norbert Becker
- Center for Organismal Studies, University of Heidelberg, Heidelberg, Germany
- German Mosquito Control Association, Speyer, Germany
| | - Anna G. Bega
- Laboratory of Experimental Biology and Biotechnology, Scientific and Educational Center in Chernogolovka, Federal State University of Education, Moscow 105005, Russia
- Vavilov Institute of General Genetics, Russian Academy of Sciences, 119991 Moscow, Russia
| | - Sophia Bejarano
- County of San Diego, Vector Control Program, San Diego, CA 92123, USA
| | | | - Joshua B. Benoit
- Department of Biological Sciences, University of Cincinnati, Cincinnati, OH 45211, USA
| | - Saïd C. Boubidi
- Entomology Unit, Laboratory of Parasitology, Pasteur Institute of Algeria, Algiers, Algeria
| | - William E. Bradshaw
- Institute of Ecology and Evolution, 5289 University of Oregon, Eugene, OR 97403-5289, USA
| | - Daniel Bravo-Barriga
- Parasitología, Departamento de Sanidad Animal, Facultad de Veterinaria, Universidad de Extremadura, Cáceres, Spain
- Department of Animal Health Department (Parasitology and Parasitic Diseases), Faculty of Veterinary Medicine, University of Córdoba, Sanidad Animal Building, Rabanales Campus, Córdoba, Spain
| | - Rubén Bueno-Marí
- European Center of Excellence for Vector Control, Laboratorios Lokímica - Rentokil Initial, Valencia, Spain
| | - Nataša Bušić
- Department of Biology, Josip Juraj Strossmayer University of Osijek, Osijek, 31000, Croatia
| | - Viktoria Čabanová
- Department of Virus Ecology, Institute of Virology, Biomedical Research Center Slovak Academy of Sciences, Bratislava, 845 05, Slovakia
| | - Brittany Cabeje
- County of San Diego, Vector Control Program, San Diego, CA 92123, USA
| | - Beniamino Caputo
- Department of Public Health and Infectious Diseases, Sapienza University, Rome, 00185, Italy
| | - Maria V. Cardo
- Ecología de Enfermedades Transmitidas por Vectores, Instituto de Investigación e Ingeniería Ambiental, UNSAM, CONICET, Buenos Aires, Argentina
| | - Simon Carpenter
- The Pirbright Institute, Ash Road, Woking, Surrey, GU24 0NF, UK
| | - Elena Carreton
- Faculty of Veterinary Medicine, Research Institute of Biomedical and Health Sciences, University of Las Palmas de Gran Canaria, Las Palmas de Gran Canaria, Spain
| | | | | | - Maureen Coetzee
- Wits Research Institute for Malaria, School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- Centre for Emerging Zoonotic & Parasitic Diseases, National Institute for Communicable Diseases, Johannesburg, South Africa
| | - William R. Conner
- Department of Evolution and Ecology, University of California, Davis, CA 95616, USA
| | - Anton Cornel
- Kearney Agricultural Research and Extension Center, Parlier, CA 93648, USA
| | - C. Lorna Culverwell
- University of Helsinki, Medicum, Department of Virology, Helsinki 00014, Finland
- Department of Life Sciences, The Natural History Museum, London, SW7 5BD, UK
| | - Aleksandra I. Cupina
- Faculty of Agriculture, Centre of Excellence One Health Vectors and Climate, Laboratory for Medical and Veterinary Entomology, University of Novi Sad, 21101 Novi Sad, Serbia
| | - Katrien De Wolf
- Entomology Unit, Department of Biomedical Sciences, Institute of Tropical Medicine, 2000 Antwerp, Belgium
| | - Isra Deblauwe
- Entomology Unit, Department of Biomedical Sciences, Institute of Tropical Medicine, 2000 Antwerp, Belgium
| | - Brittany Deegan
- Consolidated Mosquito Abatement District, Parlier, CA 93648, USA
| | - Sarah Delacour-Estrella
- Department of Animal Pathology, Faculty of Veterinary Medicine at the University of Zaragoza, Zaragoza, Spain
| | - Alessandra della Torre
- Department of Public Health and Infectious Diseases, Sapienza University, Rome, 00185, Italy
| | | | - Serena E. Dool
- Zoological Institute and Museum, University of Greifswald, Greifswald, 17489, Germany
| | - Vitor L dos Anjos
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544, USA
| | - Sisay Dugassa
- Aklilu Lemma Institute of Pathobiology, Addis Ababa University, Addis Ababa, Ethiopia
| | - Babak Ebrahimi
- Santa Clara County Vector Control District, San Jose, CA 95112, USA
| | - Samar Y.M. Eisa
- Department of Zoology, Faculty of Science, University of Khartoum, Khartoum, Sudan
| | - Nohal Elissa
- Département Faune et Actions de Salubrité, Service Parisien de Santé Environnementale, Direction de la Santé Publique, Ville de Paris, Paris 75019, France
| | - Sahar A.B. Fallatah
- Biology Department, College of Science, Imam Abdulrahman bin Faisal University, Dammam 31113, Kingdom of Saudi Arabia
| | - Ary Faraji
- Salt Lake City Mosquito Abatement District, Salt Lake City, UT 84116, USA
| | | | - Emily Ferrill
- County of San Diego, Vector Control Program, San Diego, CA 92123, USA
| | - Dina M. Fonseca
- Center for Vector Biology, Rutgers University, New Brunswick, NJ, USA
| | - Kimberly A. Foss
- Northeast Massachusetts Mosquito Control District, 118 Tenney Street, Georgetown, MA 01833, USA
| | - Cipriano Foxi
- Istituto Zooprofilattico Sperimentale della Sardegna, 07100, Sassari, Italy
| | - Caio M. França
- Department of Biology, Southern Nazarene University, Bethany, OK, USA
| | - Stephen R. Fricker
- STEM, University of South Australia, Adelaide, South Australia, 5000, Australia
- Medical Entomology, Centre for Disease Control and Environmental Health, NT Health, NT, Australia
| | - Megan L. Fritz
- Department of Entomology, University of Maryland, College Park, MD 20742, USA
| | - Eva Frontera
- Parasitología, Departamento de Sanidad Animal, Facultad de Veterinaria, Universidad de Extremadura, Cáceres, Spain
| | - Hans-Peter Fuehrer
- Institute of Parasitology, Department of Pathobiology, University of Veterinary Medicine, 1210 Vienna, Austria
| | - Kyoko Futami
- Department of Vector Ecology and Environment, Institute of Tropical Medicine, Nagasaki University, Nagasaki, Japan
| | - Enas H.S. Ghallab
- Department of Entomology, Faculty of Science, Ain Shams University, Abbassia, Cairo 11566, Egypt
| | - Romain Girod
- Medical Entomology Unit, Institut Pasteur de Madagascar, Antananarivo, Madagascar
| | - Mikhail I. Gordeev
- Department of General Biology and Ecology, Federal State University of Education, 105005 Moscow, Russia
| | - David Greer
- Southern Nevada Health District, Las Vegas, NV 89107, USA
| | - Martin Gschwind
- Swiss Tropical and Public Health Institute, Allschwil, Switzerland
- University of Basel, Basel, Switzerland
| | - Milehna M. Guarido
- Centre for Emerging and Reemerging Arbo and Respiratory Virus Research (CEARV), Department Medical Virology, University of Pretoria, South Africa
- Department of Production Animal Studies, Faculty of Veterinary Science, University of Pretoria, Onderstepoort, 0110, South Africa
| | - Teoh Guat Ney
- Medical Entomology Unit, Infectious Disease Research Centre, Institute For Medical Research, National Institutes of Health, Jalan Pahang 50588, Kuala Lumpur, Malaysia
| | - Filiz Gunay
- Hacettepe University, Faculty of Science, Department of Biology, VERG Laboratories, Beytepe, Ankara, Turkey
| | - Eran Haklay
- Ministry of Environmental Protection, Jerusalem, Israel
| | - Alwia A.E. Hamad
- Department of Zoology, Faculty of Science, University of Khartoum, Khartoum, Sudan
| | - Jun Hang
- Walter Reed Army Institute of Research, Silver Spring, MD 20910, USA
| | | | - Jacob W. Hartle
- Placer Mosquito & Vector Control District, Roseville, CA 95678, USA
| | - Jenny C. Hesson
- Department of Medical Biochemistry and Microbiology/Zoonosis Science Center, Uppsala University, Uppsala, SE-75123, Sweden
- Biologisk Myggkontroll, Nedre Dalälven Utvecklings AB, Uppsala, SE- 75646, Sweden
| | - Yukiko Higa
- Department of Medical Entomology, National Institute of Infectious Diseases, Tokyo 162-8640, Japan
| | - Christina M. Holzapfel
- Institute of Ecology and Evolution, 5289 University of Oregon, Eugene, OR 97403-5289, USA
| | - Ann-Christin Honnen
- Swiss Tropical and Public Health Institute, Allschwil, Switzerland
- University of Basel, Basel, Switzerland
| | - Angela M. Ionica
- Department of Parasitology and Parasitic Diseases, University of Agricultural Sciences and Veterinary Medicine of Cluj-Napoca, 400372, Cluj-Napoca, Romania
| | - Laura Jones
- The Pirbright Institute, Ash Road, Woking, Surrey, GU24 0NF, UK
| | - Përparim Kadriaj
- Vector Control Unit, Department of Epidemiology and Control of Infectious Diseases, Institute of Public Health, Tirana, Albania
| | - Hany A. Kamal
- Department of Pest Control Projects, Dallah Company, Jeddah, Kingdom of Saudi Arabia
| | - Colince Kamdem
- Department of Biological Sciences, The University of Texas at El Paso, 500 W. University Ave., El Paso, TX 79968, USA
| | | | - Shinji Kasai
- Department of Medical Entomology, National Institute of Infectious Diseases, Tokyo 162-8640, Japan
| | - Mihaela Kavran
- Faculty of Agriculture, Centre of Excellence One Health Vectors and Climate, Laboratory for Medical and Veterinary Entomology, University of Novi Sad, 21101 Novi Sad, Serbia
| | - Emad I.M. Khater
- Department of Entomology, Faculty of Science, Ain Shams University, Abbassia, Cairo 11566, Egypt
| | - Frederik Kiene
- Institute of Zoology and Institute of Parasitology, Centre for Infection Medicine, University of Veterinary Medicine Hannover, 30559 Hanover, Germany
| | - Heung-Chul Kim
- Force Health Protection and Preventive Medicine, Medical Department Activity-Korea/65th Medical Brigade, Unit 15281, APO AP 96271-5281, USA
| | - Ilias Kioulos
- Department of Crop Science, Agricultural University of Athens, 11855, Athens, Greece
| | - Annette Klein
- Institute of Zoology and Institute of Parasitology, Centre for Infection Medicine, University of Veterinary Medicine Hannover, 30559 Hanover, Germany
| | - Marko Klemenčić
- Croatian Institute for Public Health of Međimurje County, 40000 Čakovec, Croatia
| | - Ana Klobučar
- Department of Epidemiology, Andrija Stampar Teaching Institute of Public Health, Zagreb, 10000, Croatia
| | - Erin Knutson
- Washington State Department of Health, Olympia, WA 98504, USA
| | | | - Linda Kothera
- Centers for Disease Control and Prevention, Fort Collins, CO, USA
| | - Pauline Kreienbühl
- Institut Pasteur, Université Paris Cité, CNRS UMR2000, Insect-Virus Interactions Unit, 75015 Paris, France
| | - Pierrick Labbé
- Institut des Sciences de l’Évolution de Montpellier (UMR 5554, CNRS-UM-IRD-EPHE), Université de Montpellier, Montpellier, 34095, France
- Institut Universitaire de France, 75005, Paris, France
| | - Itay Lachmi
- Nature and Parks Authority, Jerusalem, Israel
| | - Louis Lambrechts
- Institut Pasteur, Université Paris Cité, CNRS UMR2000, Insect-Virus Interactions Unit, 75015 Paris, France
| | - Nediljko Landeka
- Institute of Public Health of the Istrian County, 52100 Pula, Croatia
| | - Christopher H. Lee
- Department of Plant Pathology, Entomology and Microbiology Iowa State University, Ames, IA 50011, USA
| | - Bryan D. Lessard
- Australian National Insect Collection, National Research Collections Australia, CSIRO, Canberra, Australia
| | | | - Jan O. Lundström
- Department of Medical Biochemistry and Microbiology/Zoonosis Science Center, Uppsala University, Uppsala, SE-75123, Sweden
- Biologisk Myggkontroll, Nedre Dalälven Utvecklings AB, Uppsala, SE- 75646, Sweden
| | | | - Caitlin MacIntyre
- Zoonotic Arbo- and Respiratory Virus Program, Centre for Viral Zoonoses, Faculty of Health Sciences, University of Pretoria, Pretoria, South Africa
| | - Andrew J. Mackay
- Illinois Natural History Survey, Prairie Research Institute, University of Illinois at Urbana-Champaign, Champaign, IL 61820, USA
| | - Krisztian Magori
- Department of Biology, Eastern Washington University, Cheney, WA 99004, USA
| | - Carla Maia
- Global Health and Tropical Medicine, GHTM, LA-REAL, Instituto de Higiene e Medicina Tropical, Universidade NOVA de Lisboa, Lisboa, Portugal
| | - Colin A. Malcolm
- School of Health, Medicine and Life Sciences, University of Hertfordshire, Hatfield, Hertfordshire, AL10 9AB, United Kingdom
| | | | - Dino Martins
- Mpala Research Centre, 555-10400, Nanyuki, Kenya
| | - Reem A. Masri
- Department of Entomology and Fralin Life Sciences Institute, Virginia Polytechnic and State University, Blacksburg, VA 24061, USA
| | - Gillian McDivitt
- County of San Diego, Vector Control Program, San Diego, CA 92123, USA
| | - Rebekah J. McMinn
- Department of Microbiology, Immunology, and Pathology, Colorado State University, Fort Collins, CO, USA
| | - Johana Medina
- Miami-Dade County Mosquito Control, Miami, FL 33178, USA
| | - Karen S. Mellor
- Antelope Valley Mosquito & Vector Control District, Lancaster, CA 93535, USA
| | - Jason Mendoza
- County of San Diego, Vector Control Program, San Diego, CA 92123, USA
| | - Enrih Merdić
- Department of Biology, Josip Juraj Strossmayer University of Osijek, Osijek, 31000, Croatia
| | - Stacey Mesler
- County of San Diego, Vector Control Program, San Diego, CA 92123, USA
| | - Camille Mestre
- Institut des Sciences de l’Évolution de Montpellier (UMR 5554, CNRS-UM-IRD-EPHE), Université de Montpellier, Montpellier, 34095, France
| | - Homer Miranda
- County of San Diego, Vector Control Program, San Diego, CA 92123, USA
| | | | - Fabrizio Montarsi
- Laboratorio di Entomologia Sanitaria e Patogeni Trasmessi da Vettori, Istituto Zooprofilattico Sperimentale delle Venezie, 35020, Legnaro, Italy
| | - Anton V. Moskaev
- Laboratory of Experimental Biology and Biotechnology, Scientific and Educational Center in Chernogolovka, Federal State University of Education, Moscow 105005, Russia
| | - Tong Mu
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544, USA
| | - Tim W.R. Möhlmann
- Laboratory of Entomology, Wageningen University & Research, Wageningen, The Netherlands
| | - Alice Namias
- Institut des Sciences de l’Évolution de Montpellier (UMR 5554, CNRS-UM-IRD-EPHE), Université de Montpellier, Montpellier, 34095, France
| | - Ivy Ng’iru
- Mpala Research Centre, 555-10400, Nanyuki, Kenya
| | | | - Maria T. Novo
- Global Health and Tropical Medicine, GHTM, LA-REAL, Instituto de Higiene e Medicina Tropical, Universidade NOVA de Lisboa, Lisboa, Portugal
| | | | - José A. Oteo
- Department of Infectious Diseases, Center of Rickettsiosis and Arthropod-Borne Diseases (CRETAV), San Pedro University Hospital-Center for Biomedical Research from La Rioja (CIBIR), Logroño, 26006, Spain
| | - Yasushi Otsuka
- Research Center for the Pacific Islands, Kagoshima University, Kagoshima, Japan
| | - Rossella Panarese
- Dipartimento di Medicina Veterinaria, Università degli Studi di Bari, 70010, Valenzano, Italy
| | - Claudia Paredes-Esquivel
- Parasitology and Mediterranean Ecoepidemiology Research Group, University of the Balearic Islands, 07122 Palma, Spain
| | - Lusine Paronyan
- National Center of Disease Control and Prevention, Ministry of Health, Yerevan 0025, Republic of Armenia
| | - Steven T. Peper
- Anastasia Mosquito Control District of St. Johns County, Augustine, FL 32092, USA
| | - Dušan V. Petrić
- Faculty of Agriculture, Centre of Excellence One Health Vectors and Climate, Laboratory for Medical and Veterinary Entomology, University of Novi Sad, 21101 Novi Sad, Serbia
| | - Kervin Pilapil
- County of San Diego, Vector Control Program, San Diego, CA 92123, USA
| | - Cristina Pou-Barreto
- Instituto Universitario de Enfermedades Tropicales y Salud Pública de Canarias. Universidad de La Laguna, Tenerife, 38206, Spain
| | - Sebastien J. Puechmaille
- Institut des Sciences de l’Évolution de Montpellier (UMR 5554, CNRS-UM-IRD-EPHE), Université de Montpellier, Montpellier, 34095, France
- Institut Universitaire de France, 75005, Paris, France
- Applied Zoology and Nature Conservation, University of Greifswald, 17489, Greifswald, Germany
| | - Ute Radespiel
- Institute of Zoology, University of Veterinary Medicine Hannover, 30559 Hanover, Germany
| | - Nil Rahola
- MIVEGEC, University of Montpellier, CNRS, IRD, 34394 Montpellier, France
| | - Vivek K Raman
- Southern Nevada Health District, Las Vegas, NV 89107, USA
| | | | - Michael H. Reiskind
- Department of Entomology and Plant Pathology, North Carolina State University, Raleigh, NC, 27695 USA
| | - Nadja M. Reissen
- Salt Lake City Mosquito Abatement District, Salt Lake City, UT 84116, USA
| | - Benjamin L. Rice
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544, USA
- Madagascar Health and Environmental Research (MAHERY), Maroantsetra, Madagascar
| | - Vincent Robert
- MIVEGEC, University of Montpellier, CNRS, IRD, 34394 Montpellier, France
| | - Ignacio Ruiz-Arrondo
- Department of Infectious Diseases, Center of Rickettsiosis and Arthropod-Borne Diseases (CRETAV), San Pedro University Hospital-Center for Biomedical Research from La Rioja (CIBIR), Logroño, 26006, Spain
| | - Ryan Salamat
- County of San Diego, Vector Control Program, San Diego, CA 92123, USA
| | - Amy Salamone
- Washington State Department of Health, Olympia, WA 98504, USA
| | - M’hammed Sarih
- Service de Parasitologie et des Maladies Vectorielles, Institut Pasteur du Maroc, Casablanca 20360, Morocco
| | - Giuseppe Satta
- Istituto Zooprofilattico Sperimentale della Sardegna, 07100, Sassari, Italy
| | - Kyoko Sawabe
- Department of Medical Entomology, National Institute of Infectious Diseases, Tokyo 162-8640, Japan
| | - Francis Schaffner
- Francis Schaffner Consultancy, Riehen, Switzerland
- National Centre for Vector Entomology, Institute of Parasitology, Vetsuisse Faculty, University of Zürich, Zürich, Switzerland
| | - Karen E. Schultz
- Mosquito and Vector Management District of Santa Barbara County, Summerland, CA 93067, USA
| | - Elena V. Shaikevich
- Vavilov Institute of General Genetics, Russian Academy of Sciences, 119991 Moscow, Russia
| | - Igor V. Sharakhov
- Department of Entomology and Fralin Life Sciences Institute, Virginia Polytechnic and State University, Blacksburg, VA 24061, USA
- Department of Genetics and Cell Biology, Tomsk State University, Tomsk 634050, Russia
| | - Maria V. Sharakhova
- Department of Entomology and Fralin Life Sciences Institute, Virginia Polytechnic and State University, Blacksburg, VA 24061, USA
- Laboratory of Cell Differentiation Mechanisms, Institute of Cytology and Genetics, 10, Ac. Lavrentieva ave., Novosibirsk 630090, Russia
| | - Nader Shatara
- San Francisco Department of Public Health, San Francisco, CA, USA
| | - Anuarbek K. Sibataev
- Department of Biology, Plant Protection and Quarantine, S.Seifullin Kazakh Agrotechnical Research University, Astana, Kazakhstan
- Department of General Biology and Genomics, Eurasian National University, Astana, Kazakhstan
| | - Mathieu Sicard
- Institut des Sciences de l’Évolution de Montpellier (UMR 5554, CNRS-UM-IRD-EPHE), Université de Montpellier, Montpellier, 34095, France
| | - Evan Smith
- Department of Biological Sciences, University of Cincinnati, Cincinnati, OH 45211, USA
| | - Ryan C. Smith
- Department of Plant Pathology, Entomology and Microbiology Iowa State University, Ames, IA 50011, USA
| | - Nathalie Smitz
- Royal Museum for Central Africa, Leuvensesteenweg 13, 3080, Tervuren, Belgium
| | - Nicolas Soriano
- County of San Diego, Vector Control Program, San Diego, CA 92123, USA
| | - Christos G. Spanoudis
- Faculty of Agriculture, Forestry and Natural Environment, School of Agriculture, Laboratory of Applied Zoology and Parasitology, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
| | - Christopher M. Stone
- Illinois Natural History Survey, Prairie Research Institute, University of Illinois at Urbana-Champaign, Champaign, IL 61820, USA
| | | | - Tatiana Sulesco
- Bernhard-Nocht-Institute for Tropical Medicine, Bernhard Nocht Str. 74, 20359, Hamburg, Germany
| | - Luciano M. Tantely
- Unité d’Entomologie Médicale, Institut Pasteur de Madagascar, Antananarivo 101, Madagascar
| | - La K. Thao
- Kern Mosquito & Vector Control District, Bakersfield, CA 93314, USA
| | - Noor Tietze
- Santa Clara County Vector Control District, San Jose, CA 95112, USA
| | - Ryan E. Tokarz
- Department of International and Global Studies, Mercer University, Macon, GA 31207, USA
| | - Kun-Hsien Tsai
- Department of Public Health, Institute of Environmental and Occupational Health Sciences, College of Public Health, National Taiwan University, No. 17, Xu-Zhou Road, Taipei 100025, Taiwan
| | - Yoshio Tsuda
- Department of Medical Entomology, National Institute of Infectious Diseases, Tokyo 162-8640, Japan
| | - Nataša Turić
- Department of Biology, Josip Juraj Strossmayer University of Osijek, Osijek, 31000, Croatia
| | - Melissa R. Uhran
- Department of Biological Sciences, University of Cincinnati, Cincinnati, OH 45211, USA
| | - Isik Unlu
- Miami-Dade County Mosquito Control, Miami, FL 33178, USA
| | - Wim Van Bortel
- Entomology Unit, Department of Biomedical Sciences, Institute of Tropical Medicine, 2000 Antwerp, Belgium
- Outbreak Research Team, Department of Biomedical Sciences, Institute of Tropical Medicine, 2000 Antwerp, Belgium
| | - Haykuhi Vardanyan
- National Center of Disease Control and Prevention, Ministry of Health, Yerevan 0025, Republic of Armenia
| | - Laura Vavassori
- Swiss Tropical and Public Health Institute, Allschwil, Switzerland
- University of Basel, Basel, Switzerland
| | - Enkelejda Velo
- Vector Control Unit, Department of Epidemiology and Control of Infectious Diseases, Institute of Public Health, Tirana, Albania
| | - Marietjie Venter
- Centre for Emerging and Reemerging Arbo and Respiratory Virus Research (CEARV), Department Medical Virology, University of Pretoria, South Africa
- Emerging Viral Threats, One Health Vaccines and Surveillance (EVITOH) Division, Infectious Disease and Oncology Research Institute (IDORI), University of the Witwatersrand, Johannesburg, South Africa
| | - Goran Vignjević
- Department of Biology, Josip Juraj Strossmayer University of Osijek, Osijek, 31000, Croatia
| | - Chantal B.F. Vogels
- Laboratory of Entomology, Wageningen University & Research, Wageningen, The Netherlands
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT 06510, USA
| | - Tatsiana Volkava
- Laboratory of Parasitology, The State Scientific and Production Amalgamation, The Scientific and Practical Center of the National Academy of Sciences of Belarus for Biological Resources, Belarus, Minsk
| | - John Vontas
- Department of Crop Science, Agricultural University of Athens, 11855, Athens, Greece
- Institute Molecular Biology Biotechnology Foundation for Research and Technology, 70013, Heraklion, Crete, Greece
| | - Heather M. Ward
- Anastasia Mosquito Control District of St. Johns County, Augustine, FL 32092, USA
| | - Nazni Wasi Ahmad
- Medical Entomology Unit, Infectious Disease Research Centre, Institute For Medical Research, National Institutes of Health, Jalan Pahang 50588, Kuala Lumpur, Malaysia
| | - Mylène Weill
- Institut des Sciences de l’Évolution de Montpellier (UMR 5554, CNRS-UM-IRD-EPHE), Université de Montpellier, Montpellier, 34095, France
| | - Jennifer D. West
- Placer Mosquito & Vector Control District, Roseville, CA 95678, USA
| | - Sarah S. Wheeler
- Sacramento-Yolo Mosquito & Vector Control District, Elk Grove, CA, 95624, USA
| | - Gregory S. White
- Salt Lake City Mosquito Abatement District, Salt Lake City, UT 84116, USA
| | - Nadja C. Wipf
- Swiss Tropical and Public Health Institute, Allschwil, Switzerland
- University of Basel, Basel, Switzerland
- Vector Biology Department, Liverpool School of Tropical Medicine, Liverpool, UK
| | - Tai-Ping Wu
- Wuhan Center for Disease Control and Prevention, Wuhan, China
| | - Kai-Di Yu
- Institute of Environmental and Occupational Health Sciences, College of Public Health, National Taiwan University, Taipei 100, Taiwan
| | - Elke Zimmermann
- Institute of Zoology, University of Veterinary Medicine Hannover, 30559 Hanover, Germany
| | - Carina Zittra
- Division Limnology, Department of Functional and Evolutionary Ecology, University of Vienna, 1030 Vienna, Austria
| | - Petra Korlević
- Wellcome Sanger Institute, Hinxton CB10 1SA, United Kingdom
| | - Erica McAlister
- Department of Life Sciences, The Natural History Museum, London, SW7 5BD, UK
| | | | - Molly Schumer
- Department of Biology and Howard Hughes Medical Institute, Stanford University, Stanford, CA, USA
| | - Noah H. Rose
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544, USA
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ 08544, USA
| | - Carolyn S. McBride
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544, USA
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ 08544, USA
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5
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Cousins T, Durvasula A. Insufficient Evidence for a Severe Bottleneck in Humans During the Early to Middle Pleistocene Transition. Mol Biol Evol 2025; 42:msaf041. [PMID: 39921621 PMCID: PMC11848514 DOI: 10.1093/molbev/msaf041] [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: 10/24/2024] [Revised: 01/21/2025] [Accepted: 01/27/2025] [Indexed: 02/10/2025] Open
Abstract
A recently proposed model suggests a severe bottleneck in the panmictic ancestral population of modern humans during the Early to Middle Pleistocene transition. Here, we show this model provides a worse fit to the data than a panmictic model without the bottleneck.
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Affiliation(s)
- Trevor Cousins
- Department of Genetics, University of Cambridge, Cambridge, UK
| | - Arun Durvasula
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
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6
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Soni V, Jensen JD. Inferring demographic and selective histories from population genomic data using a two-step approach in species with coding-sparse genomes: an application to human data. G3 (BETHESDA, MD.) 2025:jkaf019. [PMID: 39883523 DOI: 10.1093/g3journal/jkaf019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/20/2024] [Revised: 01/14/2025] [Accepted: 01/27/2025] [Indexed: 01/31/2025]
Abstract
The demographic history of a population, and the distribution of fitness effects (DFE) of newly arising mutations in functional genomic regions, are fundamental factors dictating both genetic variation and evolutionary trajectories. Although both demographic and DFE inference has been performed extensively in humans, these approaches have generally either been limited to simple demographic models involving a single population, or, where a complex population history has been inferred, without accounting for the potentially confounding effects of selection at linked sites. Taking advantage of the coding-sparse nature of the genome, we propose a 2-step approach in which coalescent simulations are first used to infer a complex multi-population demographic model, utilizing large non-functional regions that are likely free from the effects of background selection. We then use forward-in-time simulations to perform DFE inference in functional regions, conditional on the complex demography inferred and utilizing expected background selection effects in the estimation procedure. Throughout, recombination and mutation rate maps were used to account for the underlying empirical rate heterogeneity across the human genome. Importantly, within this framework it is possible to utilize and fit multiple aspects of the data, and this inference scheme represents a generalized approach for such large-scale inference in species with coding-sparse genomes.
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Affiliation(s)
- Vivak Soni
- School of Life Sciences, Center for Evolution & Medicine, Arizona State University, Tempe, AZ 85281, USA
| | - Jeffrey D Jensen
- School of Life Sciences, Center for Evolution & Medicine, Arizona State University, Tempe, AZ 85281, USA
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7
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Parreira BR, Gopalakrishnan S, Chikhi L. Effects of Social Structure on Effective Population Size Change Estimates. Evol Appl 2025; 18:e70063. [PMID: 39816161 PMCID: PMC11732743 DOI: 10.1111/eva.70063] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2024] [Revised: 11/26/2024] [Accepted: 12/03/2024] [Indexed: 01/18/2025] Open
Abstract
Most methods currently used to infer the "demographic history of species" interpret this expression as a history of population size changes. The detection, quantification, and dating of demographic changes often rely on the assumption that population structure can be neglected. However, most vertebrates are typically organized in populations subdivided into social groups that are usually ignored in the interpretation of genetic data. This could be problematic since an increasing number of studies have shown that population structure can generate spurious signatures of population size change. Here, we simulate microsatellite data from a species subdivided into social groups where reproduction occurs according to different mating systems (monogamy, polygynandry, and polygyny). We estimate the effective population size (N e) and quantify the effect of social structure on estimates of changes in N e. We analyze the simulated data with two widely used methods for demographic inference. The first approach, BOTTLENECK, tests whether the samples are at mutation-drift equilibrium and thus whether a single N e can be estimated. The second approach, msvar, aims at quantifying and dating changes in N e. We find that social structure may lead to signals of departure from mutation-drift equilibrium including signals of expansion and bottlenecks. We also find that expansion signals may be observed under simple stationary Wright-Fisher models with low diversity. Since small populations tend to characterize many endangered species, we stress that methods trying to infer N e should be interpreted with care and validated with simulated data incorporating information about structure. Spurious expansion signals due to social structure can mask critical population size changes. These can obscure true bottleneck events and be particularly problematic in endangered species.
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Affiliation(s)
- Bárbara Ribeiro Parreira
- Center for Evolutionary HologenomicsGlobe Institute, University of CopenhagenCopenhagenDenmark
- Instituto Gulbenkian de CiênciaOeirasPortugal
| | - Shyam Gopalakrishnan
- Center for Evolutionary HologenomicsGlobe Institute, University of CopenhagenCopenhagenDenmark
| | - Lounès Chikhi
- Instituto Gulbenkian de CiênciaOeirasPortugal
- Centre de Recherche sur la Biodiversité et l'Environnement (CRBE) UMR 5300Université de Toulouse, CNRS, IRD, Toulouse INP, Université Toulouse 3 Paul Sabatier (UT3)ToulouseFrance
- Centre for Ecology, Evolution and Environmental Changes (cE3c)Faculdade de Ciências da Universidade de LisboaLisboaPortugal
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8
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Soni V, Jensen JD. Inferring demographic and selective histories from population genomic data using a two-step approach in species with coding-sparse genomes: an application to human data. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.09.19.613979. [PMID: 39605418 PMCID: PMC11601476 DOI: 10.1101/2024.09.19.613979] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 11/29/2024]
Abstract
The demographic history of a population, and the distribution of fitness effects (DFE) of newly arising mutations in functional genomic regions, are fundamental factors dictating both genetic variation and evolutionary trajectories. Although both demographic and DFE inference has been performed extensively in humans, these approaches have generally either been limited to simple demographic models involving a single population, or, where a complex population history has been inferred, without accounting for the potentially confounding effects of selection at linked sites. Taking advantage of the coding-sparse nature of the genome, we propose a 2-step approach in which coalescent simulations are first used to infer a complex multi-population demographic model, utilizing large non-functional regions that are likely free from the effects of background selection. We then use forward-in-time simulations to perform DFE inference in functional regions, conditional on the complex demography inferred and utilizing expected background selection effects in the estimation procedure. Throughout, recombination and mutation rate maps were used to account for the underlying empirical rate heterogeneity across the human genome. Importantly, within this framework it is possible to utilize and fit multiple aspects of the data, and this inference scheme represents a generalized approach for such large-scale inference in species with coding-sparse genomes.
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Affiliation(s)
- Vivak Soni
- School of Life Sciences, Center for Evolution & Medicine, Arizona State University, Tempe, AZ, US
| | - Jeffrey D. Jensen
- School of Life Sciences, Center for Evolution & Medicine, Arizona State University, Tempe, AZ, US
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9
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Cheng X, Steinrücken M. Population Genomic Scans for Natural Selection and Demography. Annu Rev Genet 2024; 58:319-339. [PMID: 39227130 DOI: 10.1146/annurev-genet-111523-102651] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/05/2024]
Abstract
Uncovering the fundamental processes that shape genomic variation in natural populations is a primary objective of population genetics. These processes include demographic effects such as past changes in effective population size or gene flow between structured populations. Furthermore, genomic variation is affected by selection on nonneutral genetic variants, for example, through the adaptation of beneficial alleles or balancing selection that maintains genetic variation. In this article, we discuss the characterization of these processes using population genetic models, and we review methods developed on the basis of these models to unravel the underlying processes from modern population genomic data sets. We briefly discuss the conditions in which these approaches can be used to infer demography or identify specific nonneutral genetic variants and cases in which caution is warranted. Moreover, we summarize the challenges of jointly inferring demography and selective processes that affect neutral variation genome-wide.
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Affiliation(s)
- Xiaoheng Cheng
- Department of Ecology and Evolution, University of Chicago, Chicago, Illinois, USA;
| | - Matthias Steinrücken
- Department of Human Genetics, University of Chicago, Chicago, Illinois, USA
- Department of Ecology and Evolution, University of Chicago, Chicago, Illinois, USA;
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10
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Crossman CA, Fontaine MC, Frasier TR. A comparison of genomic diversity and demographic history of the North Atlantic and Southwest Atlantic southern right whales. Mol Ecol 2024; 33:e17099. [PMID: 37577945 DOI: 10.1111/mec.17099] [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: 01/13/2023] [Revised: 07/25/2023] [Accepted: 07/31/2023] [Indexed: 08/15/2023]
Abstract
Right whales (genus Eubalaena) were among the first, and most extensively pursued, targets of commercial whaling. However, understanding the impacts of this persecution requires knowledge of the demographic histories of these species prior to exploitation. We used deep whole genome sequencing (~40×) of 12 North Atlantic (E. glacialis) and 10 Southwest Atlantic southern (E. australis) right whales to quantify contemporary levels of genetic diversity and infer their demographic histories over time. Using coalescent- and identity-by-descent-based modelling to estimate ancestral effective population sizes from genomic data, we demonstrate that North Atlantic right whales have lived with smaller effective population sizes (Ne) than southern right whales in the Southwest Atlantic since their divergence and describe the decline in both populations around the time of whaling. North Atlantic right whales exhibit reduced genetic diversity and longer runs of homozygosity leading to higher inbreeding coefficients compared to the sampled population of southern right whales. This study represents the first comprehensive assessment of genome-wide diversity of right whales in the western Atlantic and underscores the benefits of high coverage, genome-wide datasets to help resolve long-standing questions about how historical changes in effective population size over different time scales shape contemporary diversity estimates. This knowledge is crucial to improve our understanding of the right whales' history and inform our approaches to address contemporary conservation issues. Understanding and quantifying the cumulative impact of long-term small Ne, low levels of diversity and recent inbreeding on North Atlantic right whale recovery will be important next steps.
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Affiliation(s)
- Carla A Crossman
- Biology Department, Saint Mary's University, Halifax, Nova Scotia, Canada
| | - Michael C Fontaine
- Laboratoire MIVEGEC (Université de Montpellier, CNRS 5290, IRD 224), Montpellier, France
- Groningen Institute for Evolutionary Life Sciences (GELIFES), University of Groningen, Groningen, The Netherlands
| | - Timothy R Frasier
- Biology Department, Saint Mary's University, Halifax, Nova Scotia, Canada
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11
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Mackintosh A, Setter D. Genealogical asymmetry under the IM model and a two-taxon test for gene flow. Genetics 2024; 228:iyae157. [PMID: 39344660 PMCID: PMC11631468 DOI: 10.1093/genetics/iyae157] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2024] [Accepted: 09/26/2024] [Indexed: 10/01/2024] Open
Abstract
Methods for detecting gene flow between populations often rely on asymmetry in the average length of particular genealogical branches, with the ABBA-BABA test being a well known example. Currently, asymmetry-based methods cannot be applied to a pair of populations and such analyses are instead performed using model-based methods. Here we investigate genealogical asymmetry under a two-population Isolation with Migration model. We focus on genealogies where the first coalescence event is between lineages sampled from different populations, as the external branches of these genealogies have equal expected length as long as there is no post-divergence gene flow. We show that unidirectional gene flow breaks this symmetry and results in the recipient population having longer external branches. We derive expectations for the probability of this genealogical asymmetry and propose a simple statistic (Am) to detect it from genome sequence data. Am provides a two-taxon test for gene flow that only requires a single unphased diploid genome from each population, with no outgroup information. We use analytic expectations and simulations to explore how recombination, unequal effective population sizes, bidirectional gene flow and background selection influence Am and find that the statistic provides unambiguous evidence for gene flow under a continent-island history. We estimate Am for genome sequence data from Heliconius butterflies and Odocoileus deer, generating results consistent with previous model-based analyses. Our work highlights a signal of gene flow overlooked to date and provides a method that complements existing approaches for investigating the demographic history of recently diverged populations.
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Affiliation(s)
- Alexander Mackintosh
- Department of Ecology and Genetics, Uppsala University, Norbyvägen 18D, Uppsala 75236, Sweden
- Institute of Ecology and Evolution, Ashworth Laboratories, University of Edinburgh, Charlotte Auerbach Road, Edinburgh EH9 3FL, UK
| | - Derek Setter
- Institute of Ecology and Evolution, Ashworth Laboratories, University of Edinburgh, Charlotte Auerbach Road, Edinburgh EH9 3FL, UK
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12
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Williams MP, Flegontov P, Maier R, Huber CD. Testing times: disentangling admixture histories in recent and complex demographies using ancient DNA. Genetics 2024; 228:iyae110. [PMID: 39013011 PMCID: PMC11373510 DOI: 10.1093/genetics/iyae110] [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: 04/08/2024] [Revised: 04/08/2024] [Accepted: 06/11/2024] [Indexed: 07/18/2024] Open
Abstract
Our knowledge of human evolutionary history has been greatly advanced by paleogenomics. Since the 2020s, the study of ancient DNA has increasingly focused on reconstructing the recent past. However, the accuracy of paleogenomic methods in resolving questions of historical and archaeological importance amidst the increased demographic complexity and decreased genetic differentiation remains an open question. We evaluated the performance and behavior of two commonly used methods, qpAdm and the f3-statistic, on admixture inference under a diversity of demographic models and data conditions. We performed two complementary simulation approaches-firstly exploring a wide demographic parameter space under four simple demographic models of varying complexities and configurations using branch-length data from two chromosomes-and secondly, we analyzed a model of Eurasian history composed of 59 populations using whole-genome data modified with ancient DNA conditions such as SNP ascertainment, data missingness, and pseudohaploidization. We observe that population differentiation is the primary factor driving qpAdm performance. Notably, while complex gene flow histories influence which models are classified as plausible, they do not reduce overall performance. Under conditions reflective of the historical period, qpAdm most frequently identifies the true model as plausible among a small candidate set of closely related populations. To increase the utility for resolving fine-scaled hypotheses, we provide a heuristic for further distinguishing between candidate models that incorporates qpAdm model P-values and f3-statistics. Finally, we demonstrate a significant performance increase for qpAdm using whole-genome branch-length f2-statistics, highlighting the potential for improved demographic inference that could be achieved with future advancements in f-statistic estimations.
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Affiliation(s)
- Matthew P Williams
- Department of Biology, Pennsylvania State University, University Park, PA 16802, USA
| | - Pavel Flegontov
- Department of Biology and Ecology, University of Ostrava, Ostrava 701 03, Czechia
- Department of Human Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA
| | - Robert Maier
- Department of Human Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA
| | - Christian D Huber
- Department of Biology, Pennsylvania State University, University Park, PA 16802, USA
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13
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Cádiz MI, Tengstedt ANB, Sørensen IH, Pedersen ES, Fox AD, Hansen MM. Demographic History and Inbreeding in Two Declining Sea Duck Species Inferred From Whole-Genome Sequence Data. Evol Appl 2024; 17:e70008. [PMID: 39257569 PMCID: PMC11386304 DOI: 10.1111/eva.70008] [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: 05/11/2024] [Revised: 08/16/2024] [Accepted: 08/19/2024] [Indexed: 09/12/2024] Open
Abstract
Anthropogenic impact has transitioned from threatening already rare species to causing significant declines in once numerous organisms. Long-tailed duck (Clangula hyemalis) and velvet scoter (Melanitta fusca) were once important quarry sea duck species in NW Europe, but recent declines resulted in their reclassification as vulnerable on the IUCN Red List. We sequenced and assembled genomes for both species and resequenced 15 individuals of each. Using analyses based on site frequency spectra and sequential Markovian coalescence, we found C. hyemalis to show more historical demographic stability, whereas M. fusca was affected particularly by the Last (Weichselian) Glaciation. This likely reflects C. hyemalis breeding continuously across the Arctic, with cycles of glaciation primarily shifting breeding areas south or north without major population declines, whereas the more restricted southern range of M. fusca would lead to significant range contraction during glaciations. Both species showed evidence of declines over the past thousands of years, potentially reflecting anthropogenic pressures with the recent decline indicating an accelerated process. Analysis of runs of homozygosity (ROH) showed low but nontrivial inbreeding, with F ROH from 0.012 to 0.063 in C. hyemalis and ranging from 0 to 0.047 in M. fusca. Lengths of ROH suggested that this was due to ongoing background inbreeding rather than recent declines. Overall, despite demographically important declines, this has not yet led to strong inbreeding and genetic erosion, and the most pressing conservation concern may be the risk of density-dependent (Allee) effects. We recommend monitoring of inbreeding using ROH analysis as a cost-efficient method to track future developments to support effective conservation of these species.
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Affiliation(s)
- María I Cádiz
- Department of Biology Aarhus University Aarhus Denmark
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14
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Diamantidis D, Fan WTL, Birkner M, Wakeley J. Bursts of coalescence within population pedigrees whenever big families occur. Genetics 2024; 227:iyae030. [PMID: 38408329 DOI: 10.1093/genetics/iyae030] [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: 01/23/2024] [Revised: 01/23/2024] [Accepted: 02/18/2024] [Indexed: 02/28/2024] Open
Abstract
We consider a simple diploid population-genetic model with potentially high variability of offspring numbers among individuals. Specifically, against a backdrop of Wright-Fisher reproduction and no selection, there is an additional probability that a big family occurs, meaning that a pair of individuals has a number of offspring on the order of the population size. We study how the pedigree of the population generated under this model affects the ancestral genetic process of a sample of size two at a single autosomal locus without recombination. Our population model is of the type for which multiple-merger coalescent processes have been described. We prove that the conditional distribution of the pairwise coalescence time given the random pedigree converges to a limit law as the population size tends to infinity. This limit law may or may not be the usual exponential distribution of the Kingman coalescent, depending on the frequency of big families. But because it includes the number and times of big families, it differs from the usual multiple-merger coalescent models. The usual multiple-merger coalescent models are seen as describing the ancestral process marginal to, or averaging over, the pedigree. In the limiting ancestral process conditional on the pedigree, the intervals between big families can be modeled using the Kingman coalescent but each big family causes a discrete jump in the probability of coalescence. Analogous results should hold for larger samples and other population models. We illustrate these results with simulations and additional analysis, highlighting their implications for inference and understanding of multilocus data.
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Affiliation(s)
| | - Wai-Tong Louis Fan
- Department of Mathematics, Indiana University, Bloomington, IN 47405, USA
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA
| | - Matthias Birkner
- Institut für Mathematik, Johannes-Gutenberg-Universität, 55099 Mainz, Germany
| | - John Wakeley
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA
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15
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Tengstedt ANB, Liu S, Jacobsen MW, Gundlund C, Møller PR, Berg S, Bekkevold D, Hansen MM. Genomic insights on conservation priorities for North Sea houting and European lake whitefish (Coregonus spp.). Mol Ecol 2024:e17367. [PMID: 38686435 DOI: 10.1111/mec.17367] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2024] [Revised: 04/08/2024] [Accepted: 04/12/2024] [Indexed: 05/02/2024]
Abstract
Population genomics analysis holds great potential for informing conservation of endangered populations. We focused on a controversial case of European whitefish (Coregonus spp.) populations. The endangered North Sea houting is the only coregonid fish that tolerates oceanic salinities and was previously considered a species (C. oxyrhinchus) distinct from European lake whitefish (C. lavaretus). However, no firm evidence for genetic-based salinity adaptation has been available. Also, studies based on microsatellite and mitogenome data suggested surprisingly recent divergence (c. 2500 years bp) between houting and lake whitefish. These data types furthermore have provided no evidence for possible inbreeding. Finally, a controversial taxonomic revision recently classified all whitefish in the region as C. maraena, calling conservation priorities of houting into question. We used whole-genome and ddRAD sequencing to analyse six lake whitefish populations and the only extant indigenous houting population. Demographic inference indicated post-glacial expansion and divergence between lake whitefish and houting occurring not long after the Last Glaciation, implying deeper population histories than previous analyses. Runs of homozygosity analysis suggested not only high inbreeding (FROH up to 30.6%) in some freshwater populations but also FROH up to 10.6% in the houting prompting conservation concerns. Finally, outlier scans provided evidence for adaptation to high salinities in the houting. Applying a framework for defining conservation units based on current and historical reproductive isolation and adaptive divergence led us to recommend that the houting be treated as a separate conservation unit regardless of species status. In total, the results underscore the potential of genomics to inform conservation practices, in this case clarifying conservation units and highlighting populations of concern.
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Affiliation(s)
| | - Shenglin Liu
- Department of Biology, Aarhus University, Aarhus C, Denmark
| | - Magnus W Jacobsen
- National Institute of Aquatic Resources, Technical University of Denmark, Silkeborg, Denmark
| | | | - Peter Rask Møller
- Natural History Museum of Denmark, University of Copenhagen, Copenhagen, Denmark
| | - Søren Berg
- National Institute of Aquatic Resources, Technical University of Denmark, Silkeborg, Denmark
| | - Dorte Bekkevold
- National Institute of Aquatic Resources, Technical University of Denmark, Silkeborg, Denmark
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16
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Luo CS, Li TT, Jiang XL, Song Y, Fan TT, Shen XB, Yi R, Ao XP, Xu GB, Deng M. High-quality haplotype-resolved genome assembly for ring-cup oak (Quercus glauca) provides insight into oaks demographic dynamics. Mol Ecol Resour 2024; 24:e13914. [PMID: 38108568 DOI: 10.1111/1755-0998.13914] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Revised: 11/15/2023] [Accepted: 12/05/2023] [Indexed: 12/19/2023]
Abstract
Quercus section Cyclobalanopsis represents a dominant woody lineage in East Asian evergreen broadleaved forests. Regardless of its ecological and economic importance, little is known about the genomes of species in this unique oak lineage. Quercus glauca is one of the most widespread tree species in the section Cyclobalanopsis. In this study, a high-quality haplotype-resolved reference genome was assembled for Q. glauca from PacBio HiFi and Hi-C reads. The genome size, contig N50, and scaffold N50 measured 902.88, 7.60, and 69.28 Mb, respectively, for haplotype1, and 913.28, 7.20, and 71.53 Mb, respectively, for haplotype2. A total of 37,457 and 38,311 protein-coding genes were predicted in haplotype1 and haplotype2, respectively. Homologous chromosomes in the Q. glauca genome had excellent gene pair collinearity. The number of R-genes in Q. glauca was similar to most East Asian oaks but less than oak species from Europe and America. Abundant structural variation in the Q. glauca genome could contribute to environmental stress tolerance in Q. glauca. Sections Cyclobalanopsis and Cerris diverged in the Oligocene, in agreement with fossil records for section Cyclobalanopsis, which document its presence in East Asia since the early Miocene. The demographic dynamics of closely related oak species were largely similar. The high-quality reference genome provided here for the most widespread species in section Cyclobalanopsis will serve as an essential genomic resource for evolutionary studies of key oak lineages while also supporting studies of interspecific introgression, local adaptation, and speciation in oaks.
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Affiliation(s)
- Chang-Sha Luo
- The Laboratory of Forestry Genetics, Central South University of Forestry and Technology, Changsha, Hunan, China
| | - Tian-Tian Li
- The Laboratory of Forestry Genetics, Central South University of Forestry and Technology, Changsha, Hunan, China
| | - Xiao-Long Jiang
- The Laboratory of Forestry Genetics, Central South University of Forestry and Technology, Changsha, Hunan, China
| | - Ying Song
- The Laboratory of Forestry Genetics, Central South University of Forestry and Technology, Changsha, Hunan, China
| | - Ting-Ting Fan
- The Laboratory of Forestry Genetics, Central South University of Forestry and Technology, Changsha, Hunan, China
| | - Xiang-Bao Shen
- The Laboratory of Forestry Genetics, Central South University of Forestry and Technology, Changsha, Hunan, China
| | - Rong Yi
- The Laboratory of Forestry Genetics, Central South University of Forestry and Technology, Changsha, Hunan, China
| | - Xiao-Ping Ao
- The Laboratory of Forestry Genetics, Central South University of Forestry and Technology, Changsha, Hunan, China
| | - Gang-Biao Xu
- The Laboratory of Forestry Genetics, Central South University of Forestry and Technology, Changsha, Hunan, China
| | - Min Deng
- School of Ecology and Environmental Science, Yunnan University, Kunming, Yunnan, China
- Yunnan Key Laboratory of Plant Reproductive Adaptation and Evolutionary Ecology and Institute of Biodiversity, Yunnan University, Kunming, Yunnan, China
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17
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Gao Y, Zhang X, Chen H, Lu Y, Ma S, Yang Y, Zhang M, Xu S. Reconstructing the ancestral gene pool to uncover the origins and genetic links of Hmong-Mien speakers. BMC Biol 2024; 22:59. [PMID: 38475771 PMCID: PMC10935854 DOI: 10.1186/s12915-024-01838-9] [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: 10/10/2023] [Accepted: 02/01/2024] [Indexed: 03/14/2024] Open
Abstract
BACKGROUND Hmong-Mien (HM) speakers are linguistically related and live primarily in China, but little is known about their ancestral origins or the evolutionary mechanism shaping their genomic diversity. In particular, the lack of whole-genome sequencing data on the Yao population has prevented a full investigation of the origins and evolutionary history of HM speakers. As such, their origins are debatable. RESULTS Here, we made a deep sequencing effort of 80 Yao genomes, and our analysis together with 28 East Asian populations and 968 ancient Asian genomes suggested that there is a strong genetic basis for the formation of the HM language family. We estimated that the most recent common ancestor dates to 5800 years ago, while the genetic divergence between the HM and Tai-Kadai speakers was estimated to be 8200 years ago. We proposed that HM speakers originated from the Yangtze River Basin and spread with agricultural civilization. We identified highly differentiated variants between HM and Han Chinese, in particular, a deafness-related missense variant (rs72474224) in the GJB2 gene is in a higher frequency in HM speakers than in others. CONCLUSIONS Our results indicated complex gene flow and medically relevant variants involved in the HM speakers' evolution history.
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Affiliation(s)
- Yang Gao
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
- School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Xiaoxi Zhang
- School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Hao Chen
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Yan Lu
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Sen Ma
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Yajun Yang
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, Fudan University, Shanghai, China
| | - Menghan Zhang
- Institute of Modern Languages and Linguistics, and Ministry of Education Key Laboratory of Contemporary Anthropology, School of Life Sciences, Fudan University, Shanghai, 200433, China
| | - Shuhua Xu
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
- School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China.
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China.
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, Fudan University, Shanghai, China.
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18
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Kessler C, Shafer ABA. Genomic Analyses Capture the Human-Induced Demographic Collapse and Recovery in a Wide-Ranging Cervid. Mol Biol Evol 2024; 41:msae038. [PMID: 38378172 PMCID: PMC10917209 DOI: 10.1093/molbev/msae038] [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] [Revised: 02/08/2024] [Accepted: 02/14/2024] [Indexed: 02/22/2024] Open
Abstract
The glacial cycles of the Quaternary heavily impacted species through successions of population contractions and expansions. Similarly, populations have been intensely shaped by human pressures such as unregulated hunting and land use changes. White-tailed and mule deer survived in different refugia through the Last Glacial Maximum, and their populations were severely reduced after the European colonization. Here, we analyzed 73 resequenced deer genomes from across their North American range to understand the consequences of climatic and anthropogenic pressures on deer demographic and adaptive history. We found strong signals of climate-induced vicariance and demographic decline; notably, multiple sequentially Markovian coalescent recovers a severe decline in mainland white-tailed deer effective population size (Ne) at the end of the Last Glacial Maximum. We found robust evidence for colonial overharvest in the form of a recent and dramatic drop in Ne in all analyzed populations. Historical census size and restocking data show a clear parallel to historical Ne estimates, and temporal Ne/Nc ratio shows patterns of conservation concern for mule deer. Signatures of selection highlight genes related to temperature, including a cold receptor previously highlighted in woolly mammoth. We also detected immune genes that we surmise reflect the changing land use patterns in North America. Our study provides a detailed picture of anthropogenic and climatic-induced decline in deer diversity and clues to understanding the conservation concerns of mule deer and the successful demographic recovery of white-tailed deer.
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Affiliation(s)
- Camille Kessler
- Environmental and Life Sciences Graduate Program, Trent University, Peterborough, Ontario, Canada
| | - Aaron B A Shafer
- Environmental and Life Sciences Graduate Program, Trent University, Peterborough, Ontario, Canada
- Department of Forensic Science, Trent University, Peterborough, Ontario, Canada
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19
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Padilla-Iglesias C, Derkx I. Hunter-gatherer genetics research: Importance and avenues. EVOLUTIONARY HUMAN SCIENCES 2024; 6:e15. [PMID: 38516374 PMCID: PMC10955370 DOI: 10.1017/ehs.2024.7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2023] [Revised: 01/17/2024] [Accepted: 02/02/2024] [Indexed: 03/23/2024] Open
Abstract
Major developments in the field of genetics in the past few decades have revolutionised notions of what it means to be human. Although currently only a few populations around the world practise a hunting and gathering lifestyle, this mode of subsistence has characterised members of our species since its very origins and allowed us to migrate across the planet. Therefore, the geographical distribution of hunter-gatherer populations, dependence on local ecosystems and connections to past populations and neighbouring groups have provided unique insights into our evolutionary origins. However, given the vulnerable status of hunter-gatherers worldwide, the development of the field of anthropological genetics requires that we reevaluate how we conduct research with these communities. Here, we review how the inclusion of hunter-gatherer populations in genetics studies has advanced our understanding of human origins, ancient population migrations and interactions as well as phenotypic adaptations and adaptability to different environments, and the important scientific and medical applications of these advancements. At the same time, we highlight the necessity to address yet unresolved questions and identify areas in which the field may benefit from improvements.
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Affiliation(s)
| | - Inez Derkx
- Department of Evolutionary Anthropology, University of Zurich, Zurich, Switzerland
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20
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Lescroart J, Bonilla-Sánchez A, Napolitano C, Buitrago-Torres DL, Ramírez-Chaves HE, Pulido-Santacruz P, Murphy WJ, Svardal H, Eizirik E. Extensive Phylogenomic Discordance and the Complex Evolutionary History of the Neotropical Cat Genus Leopardus. Mol Biol Evol 2023; 40:msad255. [PMID: 37987559 PMCID: PMC10701098 DOI: 10.1093/molbev/msad255] [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: 08/31/2023] [Revised: 11/07/2023] [Accepted: 11/13/2023] [Indexed: 11/22/2023] Open
Abstract
Even in the genomics era, the phylogeny of Neotropical small felids comprised in the genus Leopardus remains contentious. We used whole-genome resequencing data to construct a time-calibrated consensus phylogeny of this group, quantify phylogenomic discordance, test for interspecies introgression, and assess patterns of genetic diversity and demographic history. We infer that the Leopardus radiation started in the Early Pliocene as an initial speciation burst, followed by another in its subgenus Oncifelis during the Early Pleistocene. Our findings challenge the long-held notion that ocelot (Leopardus pardalis) and margay (L. wiedii) are sister species and instead indicate that margay is most closely related to the enigmatic Andean cat (L. jacobita), whose whole-genome data are reported here for the first time. In addition, we found that the newly sampled Andean tiger cat (L. tigrinus pardinoides) population from Colombia associates closely with Central American tiger cats (L. tigrinus oncilla). Genealogical discordance was largely attributable to incomplete lineage sorting, yet was augmented by strong gene flow between ocelot and the ancestral branch of Oncifelis, as well as between Geoffroy's cat (L. geoffroyi) and southern tiger cat (L. guttulus). Contrasting demographic trajectories have led to disparate levels of current genomic diversity, with a nearly tenfold difference in heterozygosity between Andean cat and ocelot, spanning the entire range of variability found in extant felids. Our analyses improved our understanding of the speciation history and diversity patterns in this felid radiation, and highlight the benefits to phylogenomic inference of embracing the many heterogeneous signals scattered across the genome.
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Affiliation(s)
- Jonas Lescroart
- Department of Biology, University of Antwerp, Antwerp, Belgium
- School of Health and Life Sciences, Pontifical Catholic University of Rio Grande do Sul, Porto Alegre, Brazil
| | - Alejandra Bonilla-Sánchez
- School of Health and Life Sciences, Pontifical Catholic University of Rio Grande do Sul, Porto Alegre, Brazil
- Faculty of Exact and Natural Sciences, University of Antioquia, Medellín, Colombia
| | - Constanza Napolitano
- Department of Biological Sciences and Biodiversity, University of Los Lagos, Osorno, Chile
- Institute of Ecology and Biodiversity, Concepción, Chile
- Cape Horn International Center, Puerto Williams, Chile
- Andean Cat Alliance, Villa Carlos Paz, Argentina
| | - Diana L Buitrago-Torres
- School of Health and Life Sciences, Pontifical Catholic University of Rio Grande do Sul, Porto Alegre, Brazil
| | - Héctor E Ramírez-Chaves
- Department of Biological Sciences, University of Caldas, Manizales, Colombia
- Centro de Museos, Museo de Historia Natural, University of Caldas, Manizales, Colombia
| | | | - William J Murphy
- Veterinary Integrative Biosciences, Texas A&M University, College Station, TX, USA
- Interdisciplinary Program in Genetics & Genomics, Texas A&M University, College Station, TX, USA
| | - Hannes Svardal
- Department of Biology, University of Antwerp, Antwerp, Belgium
- Naturalis Biodiversity Center, Leiden, Netherlands
| | - Eduardo Eizirik
- School of Health and Life Sciences, Pontifical Catholic University of Rio Grande do Sul, Porto Alegre, Brazil
- Instituto Pró-Carnívoros, Atibaia, Brazil
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21
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Kusuma P, Cox MP, Barker G, Sudoyo H, Lansing JS, Jacobs GS. Deep ancestry of Bornean hunter-gatherers supports long-term local ancestry dynamics. Cell Rep 2023; 42:113346. [PMID: 37917587 DOI: 10.1016/j.celrep.2023.113346] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Revised: 06/30/2023] [Accepted: 10/10/2023] [Indexed: 11/04/2023] Open
Abstract
Borneo was a crossroad of ancient dispersals, with some of the earliest Southeast Asian human remains and rock art. The island is home to traditionally hunter-gatherer Punan communities, whose origins, whether of subsistence reversion or long-term foraging, are unclear. The connection between its past and present-day agriculturalist inhabitants, who currently speak Austronesian languages and have composite and complex genetic ancestry, is equally opaque. Here, we analyze the genetic ancestry of the northeastern Bornean Punan Batu (who still practice some mobile hunting and gathering), Tubu, and Aput. We find deep ancestry connections, with a shared Asian signal outgrouping modern and ancient Austronesian-ancestry proxies, suggesting a time depth of more than 7,500 years. They also largely lack the mainland Southeast Asian signals of agricultural Borneans, who are themselves genetically heterogeneous. Our results support long-term inhabitation of Borneo by some Punan ancestors and reveal unexpected complexity in the origins and dispersal of Austronesian-expansion-related ancestry.
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Affiliation(s)
- Pradiptajati Kusuma
- Division of Genome Diversity and Diseases, Mochtar Riady Institute for Nanotechnology, Banten, Indonesia.
| | - Murray P Cox
- Department of Statistics, University of Auckland, Auckland, New Zealand; School of Natural Sciences, Massey University, Palmerston North, New Zealand
| | - Graeme Barker
- Department of Archaeology, University of Cambridge, Cambridge, UK
| | - Herawati Sudoyo
- Division of Genome Diversity and Diseases, Mochtar Riady Institute for Nanotechnology, Banten, Indonesia
| | - J Stephen Lansing
- Santa Fe Institute, Santa Fe, NM, USA; Complexity Science Hub Vienna, Vienna, Austria
| | - Guy S Jacobs
- Department of Archaeology, University of Cambridge, Cambridge, UK.
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22
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Williams MP, Flegontov P, Maier R, Huber CD. Testing Times: Challenges in Disentangling Admixture Histories in Recent and Complex Demographies. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.13.566841. [PMID: 38014190 PMCID: PMC10680674 DOI: 10.1101/2023.11.13.566841] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/29/2023]
Abstract
Paleogenomics has expanded our knowledge of human evolutionary history. Since the 2020s, the study of ancient DNA has increased its focus on reconstructing the recent past. However, the accuracy of paleogenomic methods in answering questions of historical and archaeological importance amidst the increased demographic complexity and decreased genetic differentiation within the historical period remains an open question. We used two simulation approaches to evaluate the limitations and behavior of commonly used methods, qpAdm and the f3-statistic, on admixture inference. The first is based on branch-length data simulated from four simple demographic models of varying complexities and configurations. The second, an analysis of Eurasian history composed of 59 populations using whole-genome data modified with ancient DNA conditions such as SNP ascertainment, data missingness, and pseudo-haploidization. We show that under conditions resembling historical populations, qpAdm can identify a small candidate set of true sources and populations closely related to them. However, in typical ancient DNA conditions, qpAdm is unable to further distinguish between them, limiting its utility for resolving fine-scaled hypotheses. Notably, we find that complex gene-flow histories generally lead to improvements in the performance of qpAdm and observe no bias in the estimation of admixture weights. We offer a heuristic for admixture inference that incorporates admixture weight estimate and P-values of qpAdm models, and f3-statistics to enhance the power to distinguish between multiple plausible candidates. Finally, we highlight the future potential of qpAdm through whole-genome branch-length f2-statistics, demonstrating the improved demographic inference that could be achieved with advancements in f-statistic estimations.
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Affiliation(s)
- Matthew P. Williams
- Pennsylvania State University, Department of Biology, University Park, PA 16802, USA
| | - Pavel Flegontov
- Department of Biology and Ecology, Faculty of Science, University of Ostrava, Ostrava, Czechia
- Department of Human Evolutionary Biology, Harvard University, Cambridge, MA, USA
| | - Robert Maier
- Department of Human Evolutionary Biology, Harvard University, Cambridge, MA, USA
| | - Christian D. Huber
- Pennsylvania State University, Department of Biology, University Park, PA 16802, USA
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23
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Peng MS, Liu YH, Shen QK, Zhang XH, Dong J, Li JX, Zhao H, Zhang H, Zhang X, He Y, Shi H, Cui C, Ouzhuluobu, Wu TY, Liu SM, Gonggalanzi, Baimakangzhuo, Bai C, Duojizhuoma, Liu T, Dai SS, Murphy RW, Qi XB, Dong G, Su B, Zhang YP. Genetic and cultural adaptations underlie the establishment of dairy pastoralism in the Tibetan Plateau. BMC Biol 2023; 21:208. [PMID: 37798721 PMCID: PMC10557253 DOI: 10.1186/s12915-023-01707-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Accepted: 09/20/2023] [Indexed: 10/07/2023] Open
Abstract
BACKGROUND Domestication and introduction of dairy animals facilitated the permanent human occupation of the Tibetan Plateau. Yet the history of dairy pastoralism in the Tibetan Plateau remains poorly understood. Little is known how Tibetans adapted to milk and dairy products. RESULTS We integrated archeological evidence and genetic analysis to show the picture that the dairy ruminants, together with dogs, were introduced from West Eurasia into the Tibetan Plateau since ~ 3600 years ago. The genetic admixture between the exotic and indigenous dogs enriched the candidate lactase persistence (LP) allele 10974A > G of West Eurasian origin in Tibetan dogs. In vitro experiments demonstrate that - 13838G > A functions as a LP allele in Tibetans. Unlike multiple LP alleles presenting selective signatures in West Eurasians and South Asians, the de novo origin of Tibetan-specific LP allele - 13838G > A with low frequency (~ 6-7%) and absence of selection corresponds - 13910C > T in pastoralists across eastern Eurasia steppe. CONCLUSIONS Results depict a novel scenario of genetic and cultural adaptations to diet and expand current understanding of the establishment of dairy pastoralism in the Tibetan Plateau.
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Affiliation(s)
- Min-Sheng Peng
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
- Yunnan Key Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
- KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Yan-Hu Liu
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
- Yunnan Key Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
- KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Quan-Kuan Shen
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
- Yunnan Key Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
- KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Xiao-Hua Zhang
- State Key Laboratory for Conservation and Utilization of Bio-Resources, Yunnan University, Kunming, 650091, China
- Institute of Medical Biology, Chinese Academy of Medical Science, Peking Union Medical College, Kunming, 650118, China
| | - Jiajia Dong
- Key Laboratory of Western China's Environmental Systems (Ministry of Education), College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, 730000, China
| | - Jin-Xiu Li
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
- Yunnan Key Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
| | - Hui Zhao
- State Key Laboratory for Conservation and Utilization of Bio-Resources, Yunnan University, Kunming, 650091, China
| | - Hui Zhang
- State Key Laboratory of Primate Biomedical Research (LPBR), School of Primate Translational Medicine, Kunming University of Science and Technology (KUST), Kunming, 650000, China
| | - Xiaoming Zhang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Yaoxi He
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Hong Shi
- State Key Laboratory of Primate Biomedical Research (LPBR), School of Primate Translational Medicine, Kunming University of Science and Technology (KUST), Kunming, 650000, China
| | - Chaoying Cui
- High Altitude Medical Research Center, School of Medicine, Tibetan University, Lhasa, 850000, China
| | - Ouzhuluobu
- High Altitude Medical Research Center, School of Medicine, Tibetan University, Lhasa, 850000, China
| | - Tian-Yi Wu
- National Key Laboratory of High Altitude Medicine, High Altitude Medical Research Institute, Xining, 810000, China
| | - Shi-Ming Liu
- National Key Laboratory of High Altitude Medicine, High Altitude Medical Research Institute, Xining, 810000, China
| | - Gonggalanzi
- High Altitude Medical Research Center, School of Medicine, Tibetan University, Lhasa, 850000, China
| | - Baimakangzhuo
- High Altitude Medical Research Center, School of Medicine, Tibetan University, Lhasa, 850000, China
| | - Caijuan Bai
- The First People's Hospital of Gansu Province, Lanzhou, 730000, China
| | - Duojizhuoma
- High Altitude Medical Research Center, School of Medicine, Tibetan University, Lhasa, 850000, China
| | - Ti Liu
- State Key Laboratory for Conservation and Utilization of Bio-Resources, Yunnan University, Kunming, 650091, China
| | - Shan-Shan Dai
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
- Yunnan Key Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
- KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Robert W Murphy
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
- Centre for Biodiversity and Conservation Biology, Royal Ontario Museum, Toronto, ON, M5S 2C6, Canada
| | - Xue-Bin Qi
- State Key Laboratory of Primate Biomedical Research (LPBR), School of Primate Translational Medicine, Kunming University of Science and Technology (KUST), Kunming, 650000, China.
- Tibetan Fukang Hospital, Lhasa, 850000, China.
| | - Guanghui Dong
- Key Laboratory of Western China's Environmental Systems (Ministry of Education), College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, 730000, China.
| | - Bing Su
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
| | - Ya-Ping Zhang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China.
- Yunnan Key Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China.
- KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- State Key Laboratory for Conservation and Utilization of Bio-Resources, Yunnan University, Kunming, 650091, China.
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24
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Martchenko D, Shafer ABA. Contrasting whole-genome and reduced representation sequencing for population demographic and adaptive inference: an alpine mammal case study. Heredity (Edinb) 2023; 131:273-281. [PMID: 37532838 PMCID: PMC10539292 DOI: 10.1038/s41437-023-00643-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2022] [Revised: 07/22/2023] [Accepted: 07/22/2023] [Indexed: 08/04/2023] Open
Abstract
Genomes capture the adaptive and demographic history of a species, but the choice of sequencing strategy and sample size can impact such inferences. We compared whole genome and reduced representation sequencing approaches to study the population demographic and adaptive signals of the North American mountain goat (Oreamnos americanus). We applied the restriction site-associated DNA sequencing (RADseq) approach to 254 individuals and whole genome resequencing (WGS) approach to 35 individuals across the species range at mid-level coverage (9X) and to 5 individuals at high coverage (30X). We used ANGSD to estimate the genotype likelihoods and estimated the effective population size (Ne), population structure, and explicitly modelled the demographic history with δaδi and MSMC2. The data sets were overall concordant in supporting a glacial induced vicariance and extremely low Ne in mountain goats. We evaluated a set of climatic variables and geographic location as predictors of genetic diversity using redundancy analysis. A moderate proportion of total variance (36% for WGS and 21% for RADseq data sets) was explained by geography and climate variables; both data sets support a large impact of drift and some degree of local adaptation. The empirical similarities of WGS and RADseq presented herein reassuringly suggest that both approaches will recover large demographic and adaptive signals in a population; however, WGS offers several advantages over RADseq, such as inferring adaptive processes and calculating runs-of-homozygosity estimates. Considering the predicted climate-induced changes in alpine environments and the genetically depauperate mountain goat, the long-term adaptive capabilities of this enigmatic species are questionable.
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Affiliation(s)
- Daria Martchenko
- Environmental and Life Sciences Graduate Program, Trent University, 2140 East Bank Drive, Peterborough, ON, K9J 7B8, Canada.
| | - Aaron B A Shafer
- Environmental and Life Sciences Graduate Program, Trent University, 2140 East Bank Drive, Peterborough, ON, K9J 7B8, Canada
- Department of Forensics & Environmental and Life Sciences Graduate Program, Trent University, 2140 East Bank Drive, Peterborough, ON, K9J 7B8, Canada
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25
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Schweiger R, Durbin R. Ultrafast genome-wide inference of pairwise coalescence times. Genome Res 2023; 33:1023-1031. [PMID: 37562965 PMCID: PMC10538485 DOI: 10.1101/gr.277665.123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Accepted: 06/21/2023] [Indexed: 08/12/2023]
Abstract
The pairwise sequentially Markovian coalescent (PSMC) algorithm and its extensions infer the coalescence time of two homologous chromosomes at each genomic position. This inference is used in reconstructing demographic histories, detecting selection signatures, studying genome-wide associations, constructing ancestral recombination graphs, and more. Inference of coalescence times between each pair of haplotypes in a large data set is of great interest, as they may provide rich information about the population structure and history of the sample. Here, we introduce a new method, Gamma-SMC, which is more than 10 times faster than current methods. To obtain this speed-up, we represent the posterior coalescence time distributions succinctly as a gamma distribution with just two parameters; in contrast, PSMC and its extensions hold these in a vector over discrete intervals of time. Thus, Gamma-SMC has constant time-complexity per site, without dependence on the number of discrete time states. Additionally, because of this continuous representation, our method is able to infer times spanning many orders of magnitude and, as such, is robust to parameter misspecification. We describe how this approach works, show its performance on simulated and real data, and illustrate its use in studying recent positive selection in the 1000 Genomes Project data set.
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Affiliation(s)
- Regev Schweiger
- Department of Genetics, University of Cambridge, Cambridge CB2 1TN, United Kingdom
| | - Richard Durbin
- Department of Genetics, University of Cambridge, Cambridge CB2 1TN, United Kingdom
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26
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Witt KE, Funk A, Añorve-Garibay V, Fang LL, Huerta-Sánchez E. The Impact of Modern Admixture on Archaic Human Ancestry in Human Populations. Genome Biol Evol 2023; 15:evad066. [PMID: 37103242 PMCID: PMC10194819 DOI: 10.1093/gbe/evad066] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Revised: 03/07/2023] [Accepted: 04/17/2023] [Indexed: 04/28/2023] Open
Abstract
Admixture, the genetic merging of parental populations resulting in mixed ancestry, has occurred frequently throughout the course of human history. Numerous admixture events have occurred between human populations across the world, which have shaped genetic ancestry in modern humans. For example, populations in the Americas are often mosaics of different ancestries due to recent admixture events as part of European colonization. Admixed individuals also often have introgressed DNA from Neanderthals and Denisovans that may have come from multiple ancestral populations, which may affect how archaic ancestry is distributed across an admixed genome. In this study, we analyzed admixed populations from the Americas to assess whether the proportion and location of admixed segments due to recent admixture impact an individual's archaic ancestry. We identified a positive correlation between non-African ancestry and archaic alleles, as well as a slight increase of Denisovan alleles in Indigenous American segments relative to European segments in admixed genomes. We also identify several genes as candidates for adaptive introgression, based on archaic alleles present at high frequency in admixed American populations but low frequency in East Asian populations. These results provide insights into how recent admixture events between modern humans redistributed archaic ancestry in admixed genomes.
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Affiliation(s)
- Kelsey E Witt
- Ecology, Evolution, and Organismal Biology, Brown University, Providence, Rhode Island
- Center for Computational Molecular Biology, Brown University, Providence, Rhode Island
| | - Alyssa Funk
- Center for Computational Molecular Biology, Brown University, Providence, Rhode Island
- Molecular Biology, Cell Biology, & Biochemistry, Brown University, Providence, Rhode Island
| | - Valeria Añorve-Garibay
- Center for Computational Molecular Biology, Brown University, Providence, Rhode Island
- Licenciatura en Ciencias Genómicas, Escuela Nacional de Estudios Superiores Unidad Juriquilla, Universidad Nacional Autónoma de México, Querétaro, Mexico
- Laboratorio Internacional de Investigación sobre el Genoma Humano, Universidad Nacional Autónoma de México, Querétaro, Mexico
| | - Lesly Lopez Fang
- Department of Life & Environmental Sciences, University of California, Merced, California, United States of America
| | - Emilia Huerta-Sánchez
- Ecology, Evolution, and Organismal Biology, Brown University, Providence, Rhode Island
- Center for Computational Molecular Biology, Brown University, Providence, Rhode Island
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27
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Scerri EML, Will M. The revolution that still isn't: The origins of behavioral complexity in Homo sapiens. J Hum Evol 2023; 179:103358. [PMID: 37058868 DOI: 10.1016/j.jhevol.2023.103358] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Revised: 03/13/2023] [Accepted: 03/14/2023] [Indexed: 04/16/2023]
Abstract
The behavioral origins of Homo sapiens can be traced back to the first material culture produced by our species in Africa, the Middle Stone Age (MSA). Beyond this broad consensus, the origins, patterns, and causes of behavioral complexity in modern humans remain debated. Here, we consider whether recent findings continue to support popular scenarios of: (1) a modern human 'package,' (2) a gradual and 'pan-African' emergence of behavioral complexity, and (3) a direct connection to changes in the human brain. Our geographically structured review shows that decades of scientific research have continuously failed to find a discrete threshold for a complete 'modernity package' and that the concept is theoretically obsolete. Instead of a continent-wide, gradual accumulation of complex material culture, the record exhibits a predominantly asynchronous presence and duration of many innovations across different regions of Africa. The emerging pattern of behavioral complexity from the MSA conforms to an intricate mosaic characterized by spatially discrete, temporally variable, and historically contingent trajectories. This archaeological record bears no direct relation to a simplistic shift in the human brain but rather reflects similar cognitive capacities that are variably manifested. The interaction of multiple causal factors constitutes the most parsimonious explanation driving the variable expression of complex behaviors, with demographic processes such as population structure, size, and connectivity playing a key role. While much emphasis has been given to innovation and variability in the MSA record, long periods of stasis and a lack of cumulative developments argue further against a strictly gradualistic nature in the record. Instead, we are confronted with humanity's deep, variegated roots in Africa, and a dynamic metapopulation that took many millennia to reach the critical mass capable of producing the ratchet effect commonly used to define contemporary human culture. Finally, we note a weakening link between 'modern' human biology and behavior from around 300 ka ago.
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Affiliation(s)
- Eleanor M L Scerri
- Pan-African Evolution Research Group, Max Planck Institute for Geoanthropology, Kahlaische Str. 10, 07749, Jena, Germany; Department of Classics and Archaeology, University of Malta, Msida, MSD 2080, Malta; Department of Prehistory, University of Cologne, 50931, Cologne, Germany.
| | - Manuel Will
- Department of Early Prehistory and Quaternary Ecology, University of Tübingen, Schloss Hohentübingen, Burgsteige 11, 72070, Tübingen, Germany
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28
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Pfennig A, Petersen LN, Kachambwa P, Lachance J. Evolutionary Genetics and Admixture in African Populations. Genome Biol Evol 2023; 15:evad054. [PMID: 36987563 PMCID: PMC10118306 DOI: 10.1093/gbe/evad054] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2023] [Revised: 03/15/2023] [Accepted: 03/22/2023] [Indexed: 03/30/2023] Open
Abstract
As the ancestral homeland of our species, Africa contains elevated levels of genetic diversity and substantial population structure. Importantly, African genomes are heterogeneous: They contain mixtures of multiple ancestries, each of which have experienced different evolutionary histories. In this review, we view population genetics through the lens of admixture, highlighting how multiple demographic events have shaped African genomes. Each of these historical vignettes paints a recurring picture of population divergence followed by secondary contact. First, we give a brief overview of genetic variation in Africa and examine deep population structure within Africa, including the evidence of ancient introgression from archaic "ghost" populations. Second, we describe the genetic legacies of admixture events that have occurred during the past 10,000 years. This includes gene flow between different click-speaking Khoe-San populations, the stepwise spread of pastoralism from eastern to southern Africa, multiple migrations of Bantu speakers across the continent, as well as admixture from the Middle East and Europe into the Sahel region and North Africa. Furthermore, the genomic signatures of more recent admixture can be found in the Cape Peninsula and throughout the African diaspora. Third, we highlight how natural selection has shaped patterns of genetic variation across the continent, noting that gene flow provides a potent source of adaptive variation and that selective pressures vary across Africa. Finally, we explore the biomedical implications of population structure in Africa on health and disease and call for more ethically conducted studies of genetic variation in Africa.
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Affiliation(s)
- Aaron Pfennig
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, Georgia
| | | | | | - Joseph Lachance
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, Georgia
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29
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Reboud EL, Nabholz B, Chevalier E, Tilak MK, Bito D, Condamine FL. Genomics, Population Divergence, and Historical Demography of the World's Largest and Endangered Butterfly, The Queen Alexandra's Birdwing. Genome Biol Evol 2023; 15:evad040. [PMID: 36896590 PMCID: PMC10101050 DOI: 10.1093/gbe/evad040] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Accepted: 02/24/2023] [Indexed: 03/11/2023] Open
Abstract
The world's largest butterfly is the microendemic Papua New Guinean Ornithoptera alexandrae. Despite years of conservation efforts to protect its habitat and breed this up-to-28-cm butterfly, this species still figures as endangered in the IUCN Red List and is only known from two allopatric populations occupying a total of only ∼140 km². Here we aim at assembling reference genomes for this species to investigate its genomic diversity, historical demography and determine whether the population is structured, which could provide guidance for conservation programs attempting to (inter)breed the two populations. Using a combination of long and short DNA reads and RNA sequencing, we assembled six reference genomes of the tribe Troidini, with four annotated genomes of O. alexandrae and two genomes of related species Ornithoptera priamus and Troides oblongomaculatus. We estimated the genomic diversity of the three species, and we proposed scenarios for the historical population demography using two polymorphism-based methods taking into account the characteristics of low-polymorphic invertebrates. Indeed, chromosome-scale assemblies reveal very low levels of nuclear heterozygosity across Troidini, which appears to be exceptionally low for O. alexandrae (lower than 0.01%). Demographic analyses demonstrate low and steadily declining Ne throughout O. alexandrae history, with a divergence into two distinct populations about 10,000 years ago. These results suggest that O. alexandrae distribution has been microendemic for a long time. It should also make local conservation programs aware of the genomic divergence of the two populations, which should not be ignored if any attempt is made to cross the two populations.
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Affiliation(s)
- Eliette L Reboud
- Institut des Sciences de l’Evolution de Montpellier, Université Montpellier, CNRS, IRD, EPHE, Montpellier, France
| | - Benoit Nabholz
- Institut des Sciences de l’Evolution de Montpellier, Université Montpellier, CNRS, IRD, EPHE, Montpellier, France
- Institut Universitaire de France (IUF), Paris, France
| | - Emmanuelle Chevalier
- Institut des Sciences de l’Evolution de Montpellier, Université Montpellier, CNRS, IRD, EPHE, Montpellier, France
| | - Marie-ka Tilak
- Institut des Sciences de l’Evolution de Montpellier, Université Montpellier, CNRS, IRD, EPHE, Montpellier, France
| | - Darren Bito
- Pacific Adventist University, Private Mail Bag, BOROKO 111, National Capital District, Port Moresby, Papua New Guinea
| | - Fabien L Condamine
- Institut des Sciences de l’Evolution de Montpellier, Université Montpellier, CNRS, IRD, EPHE, Montpellier, France
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30
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Vilaça ST, Donaldson ME, Benazzo A, Wheeldon TJ, Vizzari MT, Bertorelle G, Patterson BR, Kyle CJ. Tracing Eastern Wolf Origins From Whole-Genome Data in Context of Extensive Hybridization. Mol Biol Evol 2023; 40:msad055. [PMID: 37046402 PMCID: PMC10098045 DOI: 10.1093/molbev/msad055] [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] [Indexed: 04/14/2023] Open
Abstract
Southeastern Canada is inhabited by an amalgam of hybridizing wolf-like canids, raising fundamental questions regarding their taxonomy, origins, and timing of hybridization events. Eastern wolves (Canis lycaon), specifically, have been the subject of significant controversy, being viewed as either a distinct taxonomic entity of conservation concern or a recent hybrid of coyotes (C. latrans) and grey wolves (C. lupus). Mitochondrial DNA analyses show some evidence of eastern wolves being North American evolved canids. In contrast, nuclear genome studies indicate eastern wolves are best described as a hybrid entity, but with unclear timing of hybridization events. To test hypotheses related to these competing findings we sequenced whole genomes of 25 individuals, representative of extant Canadian wolf-like canid types of known origin and levels of contemporary hybridization. Here we present data describing eastern wolves as a distinct taxonomic entity that evolved separately from grey wolves for the past ∼67,000 years with an admixture event with coyotes ∼37,000 years ago. We show that Great Lakes wolves originated as a product of admixture between grey wolves and eastern wolves after the last glaciation (∼8,000 years ago) while eastern coyotes originated as a product of admixture between "western" coyotes and eastern wolves during the last century. Eastern wolf nuclear genomes appear shaped by historical and contemporary gene flow with grey wolves and coyotes, yet evolutionary uniqueness remains among eastern wolves currently inhabiting a restricted range in southeastern Canada.
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Affiliation(s)
- Sibelle T Vilaça
- Environmental and Life Sciences Graduate Program, Trent University, Ontario, Canada
- Department of Life Sciences and Biotechnology, University of Ferrara, Ferrara, Italy
| | - Michael E Donaldson
- Environmental and Life Sciences Graduate Program, Trent University, Ontario, Canada
| | - Andrea Benazzo
- Department of Life Sciences and Biotechnology, University of Ferrara, Ferrara, Italy
| | - Tyler J Wheeldon
- Ontario Ministry of Natural Resources and Forestry, Wildlife Research and Monitoring Section, Trent University, Ontario, Canada
| | - Maria Teresa Vizzari
- Department of Life Sciences and Biotechnology, University of Ferrara, Ferrara, Italy
| | - Giorgio Bertorelle
- Department of Life Sciences and Biotechnology, University of Ferrara, Ferrara, Italy
| | - Brent R Patterson
- Ontario Ministry of Natural Resources and Forestry, Wildlife Research and Monitoring Section, Trent University, Ontario, Canada
| | - Christopher J Kyle
- Environmental and Life Sciences Graduate Program, Trent University, Ontario, Canada
- Forensic Science Department, Trent University, Ontario, Canada
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31
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Rose NH, Badolo A, Sylla M, Akorli J, Otoo S, Gloria-Soria A, Powell JR, White BJ, Crawford JE, McBride CS. Dating the origin and spread of specialization on human hosts in Aedes aegypti mosquitoes. eLife 2023; 12:e83524. [PMID: 36897062 PMCID: PMC10038657 DOI: 10.7554/elife.83524] [Citation(s) in RCA: 27] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2022] [Accepted: 03/10/2023] [Indexed: 03/11/2023] Open
Abstract
The globally invasive mosquito subspecies Aedes aegypti aegypti is an effective vector of human arboviruses, in part because it specializes in biting humans and breeding in human habitats. Recent work suggests that specialization first arose as an adaptation to long, hot dry seasons in the West African Sahel, where Ae. aegypti relies on human-stored water for breeding. Here, we use whole-genome cross-coalescent analysis to date the emergence of human-specialist populationsand thus further probe the climate hypothesis. Importantly, we take advantage of the known migration of specialists out of Africa during the Atlantic Slave Trade to calibrate the coalescent clock and thus obtain a more precise estimate of the older evolutionary event than would otherwise be possible. We find that human-specialist mosquitoes diverged rapidly from ecological generalists approximately 5000 years ago, at the end of the African Humid Period-a time when the Sahara dried and water stored by humans became a uniquely stable, aquatic niche in the Sahel. We also use population genomic analyses to date a previously observed influx of human-specialist alleles into major West African cities. The characteristic length of tracts of human-specialist ancestry present on a generalist genetic background in Kumasi and Ouagadougou suggests the change in behavior occurred during rapid urbanization over the last 20-40 years. Taken together, we show that the timing and ecological context of two previously observed shifts towards human biting in Ae. aegypti differ; climate was likely the original driver, but urbanization has become increasingly important in recent decades.
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Affiliation(s)
- Noah H Rose
- Department of Ecology and Evolutionary Biology, Princeton UniversityPrincetonUnited States
- Princeton Neuroscience Institute, Princeton UniversityPrincetonUnited States
| | - Athanase Badolo
- Laboratory of Fundamental and Applied Entomology, Université Joseph Ki-ZerboOuagadougouBurkina Faso
| | - Massamba Sylla
- Department of Livestock Sciences and Techniques, Sine Saloum University El Hadji Ibrahima NIASSKaffrineSenegal
| | - Jewelna Akorli
- Department of Parasitology, Noguchi Memorial Institute for Medical Research, University of GhanaAccraGhana
| | - Sampson Otoo
- Department of Parasitology, Noguchi Memorial Institute for Medical Research, University of GhanaAccraGhana
| | - Andrea Gloria-Soria
- Department of Entomology. Center for Vector Biology & Zoonotic Diseases. The Connecticut Agricultural Experiment StationNew HavenUnited States
| | | | | | | | - Carolyn S McBride
- Department of Ecology and Evolutionary Biology, Princeton UniversityPrincetonUnited States
- Princeton Neuroscience Institute, Princeton UniversityPrincetonUnited States
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32
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Wei K, Silva-Arias GA, Tellier A. Selective sweeps linked to the colonization of novel habitats and climatic changes in a wild tomato species. THE NEW PHYTOLOGIST 2023; 237:1908-1921. [PMID: 36419182 DOI: 10.1111/nph.18634] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Accepted: 11/16/2022] [Indexed: 06/16/2023]
Abstract
Positive selection is the driving force underpinning local adaptation and leaves footprints of selective sweeps on the underlying major genes. Quantifying the timing of selection and revealing the genetic bases of adaptation in plant species occurring in steep and varying environmental gradients are crucial to predict a species' ability to colonize new niches. We use whole-genome sequence data from six populations across three different habitats of the wild tomato species Solanum chilense to infer the past demographic history and search for genes under strong positive selection. We then correlate current and past climatic projections with the demographic history, allele frequencies, the age of selection events and distribution shifts. Several selective sweeps occur at regulatory networks involved in root-hair development in low altitude and response to photoperiod and vernalization in high-altitude populations. These sweeps appear to occur in a concerted fashion in a given regulatory gene network at particular periods of substantial climatic change. Using a unique combination of genome scans and modelling of past climatic data, we quantify the timing of selection at genes likely underpinning local adaptation to semiarid habitats.
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Affiliation(s)
- Kai Wei
- Population Genetics, Department of Life Science Systems, School of Life Sciences, Technical University of Munich, Liesel-Beckmann Strasse 2, 85354, Freising, Germany
| | - Gustavo A Silva-Arias
- Population Genetics, Department of Life Science Systems, School of Life Sciences, Technical University of Munich, Liesel-Beckmann Strasse 2, 85354, Freising, Germany
| | - Aurélien Tellier
- Population Genetics, Department of Life Science Systems, School of Life Sciences, Technical University of Munich, Liesel-Beckmann Strasse 2, 85354, Freising, Germany
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33
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Kessler C, Wootton E, Shafer ABA. Speciation without gene-flow in hybridizing deer. Mol Ecol 2023; 32:1117-1132. [PMID: 36516402 DOI: 10.1111/mec.16824] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Revised: 12/01/2022] [Accepted: 12/05/2022] [Indexed: 12/15/2022]
Abstract
Under the ecological speciation model, divergent selection acts on ecological differences between populations, gradually creating barriers to gene flow and ultimately leading to reproductive isolation. Hybridisation is part of this continuum and can both promote and inhibit the speciation process. Here, we used white-tailed (Odocoileus virginianus) and mule deer (O. hemionus) to investigate patterns of speciation in hybridizing sister species. We quantified genome-wide historical introgression and performed genome scans to look for signatures of four different selection scenarios. Despite ample modern evidence of hybridisation, we found negligible patterns of ancestral introgression and no signatures of divergence with gene flow, rather localized patterns of allopatric and balancing selection were detected across the genome. Genes under balancing selection were related to immunity, MHC and sensory perception of smell, the latter of which is consistent with deer biology. The deficiency of historical gene-flow suggests that white-tailed and mule deer were spatially separated during the glaciation cycles of the Pleistocene and genome wide differentiation accrued via genetic drift. Dobzhansky-Muller incompatibilities and selection against hybrids are hypothesised to be acting, and diversity correlations to recombination rates suggests these sister species are far along the speciation continuum.
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Affiliation(s)
- Camille Kessler
- Environmental and Life Sciences Graduate Program, Trent University, Peterborough, Ontario, Canada
| | - Eric Wootton
- Biochemistry & Molecular Biology, Trent University, Peterborough, Ontario, Canada
| | - Aaron B A Shafer
- Environmental and Life Sciences Graduate Program, Trent University, Peterborough, Ontario, Canada
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34
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Prehistoric human migration between Sundaland and South Asia was driven by sea-level rise. Commun Biol 2023; 6:150. [PMID: 36739308 PMCID: PMC9899273 DOI: 10.1038/s42003-023-04510-0] [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: 02/05/2022] [Accepted: 01/20/2023] [Indexed: 02/06/2023] Open
Abstract
Rapid sea-level rise between the Last Glacial Maximum (LGM) and the mid-Holocene transformed the Southeast Asian coastal landscape, but the impact on human demography remains unclear. Here, we create a paleogeographic map, focusing on sea-level changes during the period spanning the LGM to the present-day and infer the human population history in Southeast and South Asia using 763 high-coverage whole-genome sequencing datasets from 59 ethnic groups. We show that sea-level rise, in particular meltwater pulses 1 A (MWP1A, ~14,500-14,000 years ago) and 1B (MWP1B, ~11,500-11,000 years ago), reduced land area by over 50% since the LGM, resulting in segregation of local human populations. Following periods of rapid sea-level rises, population pressure drove the migration of Malaysian Negritos into South Asia. Integrated paleogeographic and population genomic analysis demonstrates the earliest documented instance of forced human migration driven by sea-level rise.
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35
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The impact of modern admixture on archaic human ancestry in human populations. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.16.524232. [PMID: 36711776 PMCID: PMC9882123 DOI: 10.1101/2023.01.16.524232] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
Admixture, the genetic merging of parental populations resulting in mixed ancestry, has occurred frequently throughout the course of human history. Numerous admixture events have occurred between human populations across the world, as well as introgression between humans and archaic humans, Neanderthals and Denisovans. One example are genomes from populations in the Americas, as these are often mosaics of different ancestries due to recent admixture events as part of European colonization. In this study, we analyzed admixed populations from the Americas to assess whether the proportion and location of admixed segments due to recent admixture impact an individual’s archaic ancestry. We identified a positive correlation between non-African ancestry and archaic alleles, as well as a slight enrichment of Denisovan alleles in Indigenous American segments relative to European segments in admixed genomes. We also identify several genes as candidates for adaptive introgression, based on archaic alleles present at high frequency in admixed American populations but low frequency in East Asian populations. These results provide insights into how recent admixture events between modern humans redistributed archaic ancestry in admixed genomes.
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36
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Puckett EE, Davis IS, Harper DC, Wakamatsu K, Battu G, Belant JL, Beyer DE, Carpenter C, Crupi AP, Davidson M, DePerno CS, Forman N, Fowler NL, Garshelis DL, Gould N, Gunther K, Haroldson M, Ito S, Kocka D, Lackey C, Leahy R, Lee-Roney C, Lewis T, Lutto A, McGowan K, Olfenbuttel C, Orlando M, Platt A, Pollard MD, Ramaker M, Reich H, Sajecki JL, Sell SK, Strules J, Thompson S, van Manen F, Whitman C, Williamson R, Winslow F, Kaelin CB, Marks MS, Barsh GS. Genetic architecture and evolution of color variation in American black bears. Curr Biol 2023; 33:86-97.e10. [PMID: 36528024 PMCID: PMC10039708 DOI: 10.1016/j.cub.2022.11.042] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Revised: 11/08/2022] [Accepted: 11/18/2022] [Indexed: 12/23/2022]
Abstract
Color variation is a frequent evolutionary substrate for camouflage in small mammals, but the underlying genetics and evolutionary forces that drive color variation in natural populations of large mammals are mostly unexplained. The American black bear, Ursus americanus (U. americanus), exhibits a range of colors including the cinnamon morph, which has a similar color to the brown bear, U. arctos, and is found at high frequency in the American southwest. Reflectance and chemical melanin measurements showed little distinction between U. arctos and cinnamon U. americanus individuals. We used a genome-wide association for hair color as a quantitative trait in 151 U. americanus individuals and identified a single major locus (p < 10-13). Additional genomic and functional studies identified a missense alteration (R153C) in Tyrosinase-related protein 1 (TYRP1) that likely affects binding of the zinc cofactor, impairs protein localization, and results in decreased pigment production. Population genetic analyses and demographic modeling indicated that the R153C variant arose 9.36 kya in a southwestern population where it likely provided a selective advantage, spreading both northwards and eastwards by gene flow. A different TYRP1 allele, R114C, contributes to the characteristic brown color of U. arctos but is not fixed across the range.
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Affiliation(s)
- Emily E Puckett
- Department of Biological Sciences, University of Memphis, Memphis, TN 38152, USA.
| | - Isis S Davis
- Department of Biological Sciences, University of Memphis, Memphis, TN 38152, USA
| | - Dawn C Harper
- Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Kazumasa Wakamatsu
- Institute for Melanin Chemistry, Fujita Health University, Toyoake, Japan
| | - Gopal Battu
- HudsonAlpha Institute for Biotechnology, Huntsville, AL 35806, USA
| | - Jerrold L Belant
- Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI 48824, USA
| | - Dean E Beyer
- Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI 48824, USA
| | - Colin Carpenter
- West Virginia Division of Natural Resources, Beckley, WV 25801, USA
| | - Anthony P Crupi
- Division of Wildlife Conservation, Alaska Department of Fish and Game, Douglas, Juneau, AK 99824, USA
| | - Maria Davidson
- The Louisiana Department of Wildlife and Fisheries, Baton Rouge, LA 70898, USA
| | - Christopher S DePerno
- Department of Forestry and Environmental Resources, North Carolina State University, Raleigh, NC 27695-7646, USA
| | - Nicholas Forman
- New Mexico Department of Game and Fish, Santa Fe, NM 87507, USA
| | - Nicholas L Fowler
- Division of Wildlife Conservation, Alaska Department of Fish and Game, Douglas, Juneau, AK 99824, USA
| | - David L Garshelis
- Minnesota Department of Natural Resources, Grand Rapids, MN 55744, USA; IUCN SSC Bear Specialist Group
| | - Nicholas Gould
- Department of Forestry and Environmental Resources, North Carolina State University, Raleigh, NC 27695-7646, USA
| | - Kerry Gunther
- National Park Service, Yellowstone National Park, WY 82190-0168, USA
| | - Mark Haroldson
- U.S. Geological Survey, Northern Rocky Mountain Science Center, Interagency Grizzly Bear Study Team, Bozeman, MT 59715, USA
| | - Shosuke Ito
- Institute for Melanin Chemistry, Fujita Health University, Toyoake, Japan
| | - David Kocka
- Virginia Department of Wildlife Resources, Verona, VA 24482, USA
| | - Carl Lackey
- Nevada Department of Wildlife, Reno, NV 89512, USA
| | - Ryan Leahy
- National Park Service, Yosemite National Park Wildlife Management, Yosemite, CA 95389, USA
| | - Caitlin Lee-Roney
- National Park Service, Yosemite National Park Wildlife Management, Yosemite, CA 95389, USA
| | - Tania Lewis
- National Park Service, Glacier Bay National Park, Gustavus, AK 99826, USA
| | - Ashley Lutto
- U.S. Fish and Wildlife Service, Kenai National Wildlife Refuge, Soldotna, AK 99669, USA
| | - Kelly McGowan
- Department of Genetics, School of Medicine, Stanford University, Stanford, CA 94305, USA
| | | | - Mike Orlando
- Florida Fish and Wildlife Conservation Commission, Tallahassee, FL 32399, USA
| | - Alexander Platt
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Matthew D Pollard
- Department of Biological Sciences, University of Memphis, Memphis, TN 38152, USA
| | - Megan Ramaker
- HudsonAlpha Institute for Biotechnology, Huntsville, AL 35806, USA
| | | | - Jaime L Sajecki
- Virginia Department of Wildlife Resources, Verona, VA 24482, USA
| | - Stephanie K Sell
- Division of Wildlife Conservation, Alaska Department of Fish and Game, Douglas, Juneau, AK 99824, USA
| | - Jennifer Strules
- Department of Forestry and Environmental Resources, North Carolina State University, Raleigh, NC 27695-7646, USA
| | - Seth Thompson
- Virginia Department of Wildlife Resources, Verona, VA 24482, USA
| | - Frank van Manen
- U.S. Geological Survey, Northern Rocky Mountain Science Center, Interagency Grizzly Bear Study Team, Bozeman, MT 59715, USA
| | - Craig Whitman
- U.S. Geological Survey, Northern Rocky Mountain Science Center, Interagency Grizzly Bear Study Team, Bozeman, MT 59715, USA
| | - Ryan Williamson
- National Park Service, Great Smoky Mountains National Park, Gatlinburg, TN 37738, USA
| | | | - Christopher B Kaelin
- Department of Genetics, School of Medicine, Stanford University, Stanford, CA 94305, USA
| | - Michael S Marks
- Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Departments of Pathology and Laboratory Medicine and of Physiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Gregory S Barsh
- HudsonAlpha Institute for Biotechnology, Huntsville, AL 35806, USA; Department of Genetics, School of Medicine, Stanford University, Stanford, CA 94305, USA
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37
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Mooney JA, Marsden CD, Yohannes A, Wayne RK, Lohmueller KE. Long-term Small Population Size, Deleterious Variation, and Altitude Adaptation in the Ethiopian Wolf, a Severely Endangered Canid. Mol Biol Evol 2023; 40:msac277. [PMID: 36585842 PMCID: PMC9847632 DOI: 10.1093/molbev/msac277] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Revised: 11/07/2022] [Accepted: 12/22/2022] [Indexed: 01/01/2023] Open
Abstract
Ethiopian wolves, a canid species endemic to the Ethiopian Highlands, have been steadily declining in numbers for decades. Currently, out of 35 extant species, it is now one of the world's most endangered canids. Most conservation efforts have focused on preventing disease, monitoring movements and behavior, and assessing the geographic ranges of sub-populations. Here, we add an essential layer by determining the Ethiopian wolf's demographic and evolutionary history using high-coverage (∼40×) whole-genome sequencing from 10 Ethiopian wolves from the Bale Mountains. We observe exceptionally low diversity and enrichment of weakly deleterious variants in the Ethiopian wolves in comparison with two North American gray wolf populations and four dog breeds. These patterns are consequences of long-term small population size, rather than recent inbreeding. We infer the demographic history of the Ethiopian wolf and find it to be concordant with historic records and previous genetic analyses, suggesting Ethiopian wolves experienced a series of both ancient and recent bottlenecks, resulting in a census population size of fewer than 500 individuals and an estimated effective population size of approximately 100 individuals. Additionally, long-term small population size may have limited the accumulation of strongly deleterious recessive mutations. Finally, as the Ethiopian wolves have inhabited high-altitude areas for thousands of years, we searched for evidence of high-altitude adaptation, finding evidence of positive selection at a transcription factor in a hypoxia-response pathway [CREB-binding protein (CREBBP)]. Our findings are pertinent to continuing conservation efforts and understanding how demography influences the persistence of deleterious variation in small populations.
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Affiliation(s)
- Jazlyn A Mooney
- Department of Human Genetics, University of California Los Angeles, Los Angeles, CA 90095, USA
- Department of Biology, Stanford University, Stanford, CA, USA
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA
| | - Clare D Marsden
- Department of Ecology & Evolutionary Biology, University of California Los Angeles, Los Angeles, CA, USA
| | - Abigail Yohannes
- Department of Chemistry and Biochemistry, University of California Los Angeles, Los Angeles, CA, USA
| | - Robert K Wayne
- Department of Ecology & Evolutionary Biology, University of California Los Angeles, Los Angeles, CA, USA
| | - Kirk E Lohmueller
- Department of Human Genetics, University of California Los Angeles, Los Angeles, CA 90095, USA
- Department of Ecology & Evolutionary Biology, University of California Los Angeles, Los Angeles, CA, USA
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38
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Harvati K, Ackermann RR. Merging morphological and genetic evidence to assess hybridization in Western Eurasian late Pleistocene hominins. Nat Ecol Evol 2022; 6:1573-1585. [PMID: 36064759 DOI: 10.1038/s41559-022-01875-z] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2019] [Accepted: 08/08/2022] [Indexed: 11/09/2022]
Abstract
Previous scientific consensus saw human evolution as defined by adaptive differences (behavioural and/or biological) and the emergence of Homo sapiens as the ultimate replacement of non-modern groups by a modern, adaptively more competitive group. However, recent research has shown that the process underlying our origins was considerably more complex. While archaeological and fossil evidence suggests that behavioural complexity may not be confined to the modern human lineage, recent palaeogenomic work shows that gene flow between distinct lineages (for example, Neanderthals, Denisovans, early H. sapiens) occurred repeatedly in the late Pleistocene, probably contributing elements to our genetic make-up that might have been crucial to our success as a diverse, adaptable species. Following these advances, the prevailing human origins model has shifted from one of near-complete replacement to a more nuanced view of partial replacement with considerable reticulation. Here we provide a brief introduction to the current genetic evidence for hybridization among hominins, its prevalence in, and effects on, comparative mammal groups, and especially how it manifests in the skull. We then explore the degree to which cranial variation seen in the fossil record of late Pleistocene hominins from Western Eurasia corresponds with our current genetic and comparative data. We are especially interested in understanding the degree to which skeletal data can reflect admixture. Our findings indicate some correspondence between these different lines of evidence, flag individual fossils as possibly admixed, and suggest that different cranial regions may preserve hybridization signals differentially. We urge further studies of the phenotype to expand our ability to detect the ways in which migration, interaction and genetic exchange have shaped the human past, beyond what is currently visible with the lens of ancient DNA.
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Affiliation(s)
- K Harvati
- Paleoanthropology section, Senckenberg Centre for Human Evolution and Palaeoenvironment, Institute for Archaeological Sciences, Eberhard Karls Universität Tübingen, Tübingen, Germany.
- DFG Centre for Advanced Studies 'Words, Bones, Genes, Tools', Eberhard Karls Universität Tübingen, Tübingen, Germany.
| | - R R Ackermann
- Human Evolution Research Institute, University of Cape Town, Cape Town, South Africa.
- Department of Archaeology, University of Cape Town, Cape Town, South Africa.
- DFG Centre for Advanced Studies 'Words, Bones, Genes, Tools', Eberhard Karls Universität Tübingen, Tübingen, Germany.
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39
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Upadhya G, Steinrücken M. Robust inference of population size histories from genomic sequencing data. PLoS Comput Biol 2022; 18:e1010419. [PMID: 36112715 PMCID: PMC9518926 DOI: 10.1371/journal.pcbi.1010419] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2021] [Revised: 09/28/2022] [Accepted: 07/21/2022] [Indexed: 02/08/2023] Open
Abstract
Unraveling the complex demographic histories of natural populations is a central problem in population genetics. Understanding past demographic events is of general anthropological interest, but is also an important step in establishing accurate null models when identifying adaptive or disease-associated genetic variation. An important class of tools for inferring past population size changes from genomic sequence data are Coalescent Hidden Markov Models (CHMMs). These models make efficient use of the linkage information in population genomic datasets by using the local genealogies relating sampled individuals as latent states that evolve along the chromosome in an HMM framework. Extending these models to large sample sizes is challenging, since the number of possible latent states increases rapidly. Here, we present our method CHIMP (CHMM History-Inference Maximum-Likelihood Procedure), a novel CHMM method for inferring the size history of a population. It can be applied to large samples (hundreds of haplotypes) and only requires unphased genomes as input. The two implementations of CHIMP that we present here use either the height of the genealogical tree (TMRCA) or the total branch length, respectively, as the latent variable at each position in the genome. The requisite transition and emission probabilities are obtained by numerically solving certain systems of differential equations derived from the ancestral process with recombination. The parameters of the population size history are subsequently inferred using an Expectation-Maximization algorithm. In addition, we implement a composite likelihood scheme to allow the method to scale to large sample sizes. We demonstrate the efficiency and accuracy of our method in a variety of benchmark tests using simulated data and present comparisons to other state-of-the-art methods. Specifically, our implementation using TMRCA as the latent variable shows comparable performance and provides accurate estimates of effective population sizes in intermediate and ancient times. Our method is agnostic to the phasing of the data, which makes it a promising alternative in scenarios where high quality data is not available, and has potential applications for pseudo-haploid data.
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Affiliation(s)
- Gautam Upadhya
- Department of Physics, University of Chicago, Chicago, Illinois, United States of America
| | - Matthias Steinrücken
- Department of Ecology and Evolution, University of Chicago, Chicago, Illinois, United States of America
- Department of Human Genetics, University of Chicago, Chicago, Illinois, United States of America
- * E-mail:
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40
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Bergström A, Stanton DWG, Taron UH, Frantz L, Sinding MHS, Ersmark E, Pfrengle S, Cassatt-Johnstone M, Lebrasseur O, Girdland-Flink L, Fernandes DM, Ollivier M, Speidel L, Gopalakrishnan S, Westbury MV, Ramos-Madrigal J, Feuerborn TR, Reiter E, Gretzinger J, Münzel SC, Swali P, Conard NJ, Carøe C, Haile J, Linderholm A, Androsov S, Barnes I, Baumann C, Benecke N, Bocherens H, Brace S, Carden RF, Drucker DG, Fedorov S, Gasparik M, Germonpré M, Grigoriev S, Groves P, Hertwig ST, Ivanova VV, Janssens L, Jennings RP, Kasparov AK, Kirillova IV, Kurmaniyazov I, Kuzmin YV, Kosintsev PA, Lázničková-Galetová M, Leduc C, Nikolskiy P, Nussbaumer M, O'Drisceoil C, Orlando L, Outram A, Pavlova EY, Perri AR, Pilot M, Pitulko VV, Plotnikov VV, Protopopov AV, Rehazek A, Sablin M, Seguin-Orlando A, Storå J, Verjux C, Zaibert VF, Zazula G, Crombé P, Hansen AJ, Willerslev E, Leonard JA, Götherström A, Pinhasi R, Schuenemann VJ, Hofreiter M, Gilbert MTP, Shapiro B, Larson G, Krause J, Dalén L, Skoglund P. Grey wolf genomic history reveals a dual ancestry of dogs. Nature 2022; 607:313-320. [PMID: 35768506 PMCID: PMC9279150 DOI: 10.1038/s41586-022-04824-9] [Citation(s) in RCA: 63] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Accepted: 04/28/2022] [Indexed: 01/01/2023]
Abstract
The grey wolf (Canis lupus) was the first species to give rise to a domestic population, and they remained widespread throughout the last Ice Age when many other large mammal species went extinct. Little is known, however, about the history and possible extinction of past wolf populations or when and where the wolf progenitors of the present-day dog lineage (Canis familiaris) lived1–8. Here we analysed 72 ancient wolf genomes spanning the last 100,000 years from Europe, Siberia and North America. We found that wolf populations were highly connected throughout the Late Pleistocene, with levels of differentiation an order of magnitude lower than they are today. This population connectivity allowed us to detect natural selection across the time series, including rapid fixation of mutations in the gene IFT88 40,000–30,000 years ago. We show that dogs are overall more closely related to ancient wolves from eastern Eurasia than to those from western Eurasia, suggesting a domestication process in the east. However, we also found that dogs in the Near East and Africa derive up to half of their ancestry from a distinct population related to modern southwest Eurasian wolves, reflecting either an independent domestication process or admixture from local wolves. None of the analysed ancient wolf genomes is a direct match for either of these dog ancestries, meaning that the exact progenitor populations remain to be located. DNA from ancient wolves spanning 100,000 years sheds light on wolves’ evolutionary history and the genomic origin of dogs.
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Affiliation(s)
- Anders Bergström
- Ancient Genomics Laboratory, The Francis Crick Institute, London, UK.
| | - David W G Stanton
- Department of Bioinformatics and Genetics, Swedish Museum of Natural History, Stockholm, Sweden.,Centre for Palaeogenetics, Stockholm, Sweden.,School of Biological and Behavioural Sciences, Queen Mary University of London, London, UK
| | - Ulrike H Taron
- Evolutionary Adaptive Genomics, Institute of Biochemistry and Biology, University of Potsdam, Potsdam, Germany
| | - Laurent Frantz
- School of Biological and Behavioural Sciences, Queen Mary University of London, London, UK.,Palaeogenomics Group, Department of Veterinary Sciences, Ludwig Maximilian University, Munich, Germany
| | - Mikkel-Holger S Sinding
- The GLOBE Institute, University of Copenhagen, Copenhagen, Denmark.,Smurfit Institute of Genetics, Trinity College Dublin, Dublin, Ireland.,The Qimmeq Project, University of Greenland, Nuuk, Greenland.,Greenland Institute of Natural Resources, Nuuk, Greenland
| | - Erik Ersmark
- Department of Bioinformatics and Genetics, Swedish Museum of Natural History, Stockholm, Sweden.,Centre for Palaeogenetics, Stockholm, Sweden
| | - Saskia Pfrengle
- Institute for Archaeological Sciences, University of Tübingen, Tübingen, Germany.,Institute of Evolutionary Medicine, University of Zurich, Zurich, Switzerland
| | - Molly Cassatt-Johnstone
- Department of Ecology and Evolutionary Biology, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Ophélie Lebrasseur
- The Palaeogenomics & Bio-Archaeology Research Network, Research Laboratory for Archaeology and History of Art, University of Oxford, Oxford, UK
| | - Linus Girdland-Flink
- Department of Archaeology, School of Geosciences, University of Aberdeen, Aberdeen, UK.,School of Biological and Environmental Sciences, Liverpool John Moores University, Liverpool, UK
| | - Daniel M Fernandes
- Department of Evolutionary Anthropology, University of Vienna, Vienna, Austria.,CIAS, Department of Life Sciences, University of Coimbra, Coimbra, Portugal
| | - Morgane Ollivier
- University of Rennes, CNRS, ECOBIO (Ecosystèmes, biodiversité, évolution)-UMR 6553, Rennes, France
| | - Leo Speidel
- Ancient Genomics Laboratory, The Francis Crick Institute, London, UK.,Genetics Institute, University College London, London, UK
| | | | - Michael V Westbury
- Evolutionary Adaptive Genomics, Institute of Biochemistry and Biology, University of Potsdam, Potsdam, Germany.,The GLOBE Institute, University of Copenhagen, Copenhagen, Denmark
| | | | - Tatiana R Feuerborn
- The GLOBE Institute, University of Copenhagen, Copenhagen, Denmark.,The Qimmeq Project, University of Greenland, Nuuk, Greenland.,Institute for Archaeological Sciences, University of Tübingen, Tübingen, Germany
| | - Ella Reiter
- Institute for Archaeological Sciences, University of Tübingen, Tübingen, Germany
| | - Joscha Gretzinger
- Institute for Archaeological Sciences, University of Tübingen, Tübingen, Germany.,Max Planck Institute for the Science of Human History, Jena, Germany
| | - Susanne C Münzel
- Institute for Archaeological Sciences, University of Tübingen, Tübingen, Germany
| | - Pooja Swali
- Ancient Genomics Laboratory, The Francis Crick Institute, London, UK
| | - Nicholas J Conard
- Department of Early Prehistory and Quaternary Ecology, University of Tübingen, Tübingen, Germany.,Senckenberg Centre for Human Evolution and Palaeoenvironment, University of Tübingen, Tübingen, Germany
| | - Christian Carøe
- The GLOBE Institute, University of Copenhagen, Copenhagen, Denmark
| | - James Haile
- The Palaeogenomics & Bio-Archaeology Research Network, Research Laboratory for Archaeology and History of Art, University of Oxford, Oxford, UK
| | - Anna Linderholm
- Centre for Palaeogenetics, Stockholm, Sweden.,The Palaeogenomics & Bio-Archaeology Research Network, Research Laboratory for Archaeology and History of Art, University of Oxford, Oxford, UK.,Texas A&M University, College Station, TX, USA.,Department of Geological Sciences, Stockholm University, Stockholm, Sweden
| | | | - Ian Barnes
- Department of Earth Sciences, Natural History Museum, London, UK
| | - Chris Baumann
- Senckenberg Centre for Human Evolution and Palaeoenvironment, University of Tübingen, Tübingen, Germany.,Department of Geosciences and Geography, Faculty of Science, University of Helsinki, Helsinki, Finland
| | | | - Hervé Bocherens
- Senckenberg Centre for Human Evolution and Palaeoenvironment, University of Tübingen, Tübingen, Germany.,Biogeology, Department of Geosciences, University of Tübingen, Tübingen, Germany
| | - Selina Brace
- Department of Earth Sciences, Natural History Museum, London, UK
| | - Ruth F Carden
- School of Archaeology, University College Dublin, Dublin, Ireland
| | - Dorothée G Drucker
- Senckenberg Centre for Human Evolution and Palaeoenvironment, University of Tübingen, Tübingen, Germany
| | - Sergey Fedorov
- North-Eastern Federal University, Yakutsk, Russian Federation
| | | | | | | | - Pam Groves
- University of Alaska, Fairbanks, AK, USA
| | - Stefan T Hertwig
- Naturhistorisches Museum Bern, Bern, Switzerland.,Institute of Ecology and Evolution, University of Bern, Bern, Switzerland
| | | | | | - Richard P Jennings
- School of Biological and Environmental Sciences, Liverpool John Moores University, Liverpool, UK
| | - Aleksei K Kasparov
- Institute for the History of Material Culture, Russian Academy of Sciences, St Petersburg, Russian Federation
| | - Irina V Kirillova
- Ice Age Museum, Shidlovskiy National Alliance 'Ice Age', Moscow, Russian Federation
| | - Islam Kurmaniyazov
- Department of Archaeology, Ethnology and Museology, Al-Farabi Kazakh State University, Almaty, Kazakhstan
| | - Yaroslav V Kuzmin
- Sobolev Institute of Geology and Mineralogy, Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russian Federation
| | | | | | | | - Pavel Nikolskiy
- Geological Institute, Russian Academy of Sciences, Moscow, Russian Federation
| | | | - Cóilín O'Drisceoil
- National Monuments Service, Department of Housing, Local Government and Heritage, Dublin, Ireland
| | - Ludovic Orlando
- Centre d'Anthropobiologie et de Génomique de Toulouse UMR 5288, CNRS, Faculté de Médecine Purpan, Université Paul Sabatier, Toulouse, France
| | - Alan Outram
- Department of Archaeology, University of Exeter, Exeter, UK
| | - Elena Y Pavlova
- Arctic & Antarctic Research Institute, St Petersburg, Russian Federation
| | - Angela R Perri
- PaleoWest, Henderson, NV, USA.,Department of Anthropology, University of Nevada, Las Vegas, Las Vegas, NV, USA
| | - Małgorzata Pilot
- Museum & Institute of Zoology, Polish Academy of Sciences, Gdańsk, Poland
| | - Vladimir V Pitulko
- Institute for the History of Material Culture, Russian Academy of Sciences, St Petersburg, Russian Federation
| | | | | | | | - Mikhail Sablin
- Zoological Institute of the Russian Academy of Sciences, St. Petersburg, Russian Federation
| | - Andaine Seguin-Orlando
- Centre d'Anthropobiologie et de Génomique de Toulouse UMR 5288, CNRS, Faculté de Médecine Purpan, Université Paul Sabatier, Toulouse, France
| | - Jan Storå
- Stockholm University, Stockholm, Sweden
| | | | - Victor F Zaibert
- Institute of Archaeology and Steppe Civilizations, Al-Farabi Kazakh National University, Almaty, Kazakhstan
| | - Grant Zazula
- Yukon Palaeontology Program, Whitehorse, Yukon Territories, Canada.,Collections and Research, Canadian Museum of Nature, Ottawa, Ontario, Canada
| | | | - Anders J Hansen
- The GLOBE Institute, University of Copenhagen, Copenhagen, Denmark
| | - Eske Willerslev
- The GLOBE Institute, University of Copenhagen, Copenhagen, Denmark.,Department of Zoology, University of Cambridge, Cambridge, UK
| | | | - Anders Götherström
- Centre for Palaeogenetics, Stockholm, Sweden.,Stockholm University, Stockholm, Sweden
| | - Ron Pinhasi
- Department of Evolutionary Anthropology, University of Vienna, Vienna, Austria.,Human Evolution and Archaeological Sciences, University of Vienna, Vienna, Austria
| | - Verena J Schuenemann
- Institute for Archaeological Sciences, University of Tübingen, Tübingen, Germany.,Institute of Evolutionary Medicine, University of Zurich, Zurich, Switzerland.,Department of Evolutionary Anthropology, University of Vienna, Vienna, Austria
| | - Michael Hofreiter
- Evolutionary Adaptive Genomics, Institute of Biochemistry and Biology, University of Potsdam, Potsdam, Germany
| | - M Thomas P Gilbert
- The GLOBE Institute, University of Copenhagen, Copenhagen, Denmark.,University Museum, NTNU, Trondheim, Norway
| | - Beth Shapiro
- Department of Ecology and Evolutionary Biology, University of California, Santa Cruz, Santa Cruz, CA, USA.,Howard Hughes Medical Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Greger Larson
- The Palaeogenomics & Bio-Archaeology Research Network, Research Laboratory for Archaeology and History of Art, University of Oxford, Oxford, UK
| | - Johannes Krause
- Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
| | - Love Dalén
- Department of Bioinformatics and Genetics, Swedish Museum of Natural History, Stockholm, Sweden.,Centre for Palaeogenetics, Stockholm, Sweden
| | - Pontus Skoglund
- Ancient Genomics Laboratory, The Francis Crick Institute, London, UK.
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41
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Wang MS, Murray GGR, Mann D, Groves P, Vershinina AO, Supple MA, Kapp JD, Corbett-Detig R, Crump SE, Stirling I, Laidre KL, Kunz M, Dalén L, Green RE, Shapiro B. A polar bear paleogenome reveals extensive ancient gene flow from polar bears into brown bears. Nat Ecol Evol 2022; 6:936-944. [PMID: 35711062 DOI: 10.1038/s41559-022-01753-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Accepted: 03/30/2022] [Indexed: 11/09/2022]
Abstract
Polar bears (Ursus maritimus) and brown bears (Ursus arctos) are sister species possessing distinct physiological and behavioural adaptations that evolved over the last 500,000 years. However, comparative and population genomics analyses have revealed that several extant and extinct brown bear populations have relatively recent polar bear ancestry, probably as the result of geographically localized instances of gene flow from polar bears into brown bears. Here, we generate and analyse an approximate 20X paleogenome from an approximately 100,000-year-old polar bear that reveals a massive prehistoric admixture event, which is evident in the genomes of all living brown bears. This ancient admixture event was not visible from genomic data derived from living polar bears. Like more recent events, this massive admixture event mainly involved unidirectional gene flow from polar bears into brown bears and occurred as climate changes caused overlap in the ranges of the two species. These findings highlight the complex reticulate paths that evolution can take within a regime of radically shifting climate.
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Affiliation(s)
- Ming-Shan Wang
- Howard Hughes Medical Institute, University of California Santa Cruz, Santa Cruz, CA, USA.,Department of Ecology and Evolutionary Biology, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Gemma G R Murray
- Department of Veterinary Medicine, University of Cambridge, Cambridge, UK
| | - Daniel Mann
- Department of Geosciences, University of Alaska, Fairbanks, AK, USA.,Institute of Arctic Biology, University of Alaska, Fairbanks, AK, USA
| | - Pamela Groves
- Institute of Arctic Biology, University of Alaska, Fairbanks, AK, USA
| | - Alisa O Vershinina
- Department of Ecology and Evolutionary Biology, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Megan A Supple
- Howard Hughes Medical Institute, University of California Santa Cruz, Santa Cruz, CA, USA.,Department of Ecology and Evolutionary Biology, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Joshua D Kapp
- Department of Ecology and Evolutionary Biology, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Russell Corbett-Detig
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Sarah E Crump
- Department of Ecology and Evolutionary Biology, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Ian Stirling
- Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada.,Wildlife Research Division, Environment and Climate Change Canada Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada
| | - Kristin L Laidre
- Polar Science Center, Applied Physics Laboratory, University of Washington, Seattle, WA, USA
| | - Michael Kunz
- University of Alaska Museum of the North, Fairbanks, AK, USA
| | - Love Dalén
- Department of Bioinformatics and Genetics, Swedish Museum of Natural History, Stockholm, Sweden.,Centre for Palaeogenetics, Stockholm, Sweden
| | - Richard E Green
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Beth Shapiro
- Howard Hughes Medical Institute, University of California Santa Cruz, Santa Cruz, CA, USA. .,Department of Ecology and Evolutionary Biology, University of California Santa Cruz, Santa Cruz, CA, USA.
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42
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Popadin K, Gunbin K, Peshkin L, Annis S, Fleischmann Z, Franco M, Kraytsberg Y, Markuzon N, Ackermann RR, Khrapko K. Mitochondrial Pseudogenes Suggest Repeated Inter-Species Hybridization among Direct Human Ancestors. Genes (Basel) 2022; 13:810. [PMID: 35627195 PMCID: PMC9140377 DOI: 10.3390/genes13050810] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Revised: 04/12/2022] [Accepted: 04/16/2022] [Indexed: 12/02/2022] Open
Abstract
The hypothesis that the evolution of humans involves hybridization between diverged species has been actively debated in recent years. We present the following novel evidence in support of this hypothesis: the analysis of nuclear pseudogenes of mtDNA ("NUMTs"). NUMTs are considered "mtDNA fossils" as they preserve sequences of ancient mtDNA and thus carry unique information about ancestral populations. Our comparison of a NUMT sequence shared by humans, chimpanzees, and gorillas with their mtDNAs implies that, around the time of divergence between humans and chimpanzees, our evolutionary history involved the interbreeding of individuals whose mtDNA had diverged as much as ~4.5 Myr prior. This large divergence suggests a distant interspecies hybridization. Additionally, analysis of two other NUMTs suggests that such events occur repeatedly. Our findings suggest a complex pattern of speciation in primate/human ancestors and provide one potential explanation for the mosaic nature of fossil morphology found at the emergence of the hominin lineage. A preliminary version of this manuscript was uploaded to the preprint server BioRxiv in 2017 (10.1101/134502).
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Affiliation(s)
- Konstantin Popadin
- School of Life Sciences, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland;
- Center for Mitochondrial Functional Genomics, Institute of Living Systems, Immanuel Kant Baltic Federal University, 236040 Kaliningrad, Russia
- Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
| | | | - Leonid Peshkin
- Department of Genetics, Harvard Medical School, Boston, MA 02115, USA;
| | - Sofia Annis
- Department of Biology, Northeastern University, Boston, MA 02115, USA; (S.A.); (Z.F.); (M.F.)
| | - Zoe Fleischmann
- Department of Biology, Northeastern University, Boston, MA 02115, USA; (S.A.); (Z.F.); (M.F.)
| | - Melissa Franco
- Department of Biology, Northeastern University, Boston, MA 02115, USA; (S.A.); (Z.F.); (M.F.)
| | | | | | - Rebecca R. Ackermann
- Human Evolution Research Institute, Department of Archaeology, University of Cape Town, Cape Town 7700, South Africa;
| | - Konstantin Khrapko
- Department of Biology, Northeastern University, Boston, MA 02115, USA; (S.A.); (Z.F.); (M.F.)
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43
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Witt KE, Villanea F, Loughran E, Zhang X, Huerta-Sanchez E. Apportioning archaic variants among modern populations. Philos Trans R Soc Lond B Biol Sci 2022; 377:20200411. [PMID: 35430882 PMCID: PMC9014186 DOI: 10.1098/rstb.2020.0411] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/30/2023] Open
Abstract
The apportionment of human genetic diversity within and between populations has been measured to understand human relatedness and demographic history. Likewise, the distribution of archaic ancestry in modern populations can be leveraged to better understand the interaction between our species and its archaic relatives. Resolving the interactions between modern and archaic human populations can be difficult, as archaic variants in modern populations have been shaped by genetic drift, bottlenecks and gene flow. Here, we investigate the distribution of archaic variation in Eurasian populations. We find that archaic ancestry coverage at the individual- and population-level present distinct patterns in modern human populations: South Asians have nearly twice the number of population-unique archaic alleles compared with Europeans or East Asians, indicating that these populations experienced differing demographic and archaic admixture events. We confirm previous observations that East Asian individuals have more Neanderthal ancestry than European individuals, but surprisingly, when we compare the number of single nucleotide polymorphisms with archaic alleles found across a population, Europeans have more Neanderthal ancestry than East Asians. We compare these results to simulated models and conclude that these patterns are consistent with multiple admixture events between modern humans and Neanderthals. This article is part of the theme issue ‘Celebrating 50 years since Lewontin's apportionment of human diversity’.
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Affiliation(s)
- Kelsey E. Witt
- Ecology, Evolution, and Organismal Biology, Brown University, Providence, RI 02912, USA
- Center for Computational Molecular Biology, Brown University, Providence, RI 02912, USA
| | - Fernando Villanea
- Department of Anthropology, University of Colorado Boulder, Boulder, CO, USA
| | - Elle Loughran
- Smurfit Institute of Genetics, Trinity College Dublin, Dublin, Republic of Ireland
| | - Xinjun Zhang
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, CA, USA
| | - Emilia Huerta-Sanchez
- Ecology, Evolution, and Organismal Biology, Brown University, Providence, RI 02912, USA
- Center for Computational Molecular Biology, Brown University, Providence, RI 02912, USA
- Smurfit Institute of Genetics, Trinity College Dublin, Dublin, Republic of Ireland
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44
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Baumdicker F, Bisschop G, Goldstein D, Gower G, Ragsdale AP, Tsambos G, Zhu S, Eldon B, Ellerman EC, Galloway JG, Gladstein AL, Gorjanc G, Guo B, Jeffery B, Kretzschumar WW, Lohse K, Matschiner M, Nelson D, Pope NS, Quinto-Cortés CD, Rodrigues MF, Saunack K, Sellinger T, Thornton K, van Kemenade H, Wohns AW, Wong Y, Gravel S, Kern AD, Koskela J, Ralph PL, Kelleher J. Efficient ancestry and mutation simulation with msprime 1.0. Genetics 2022; 220:iyab229. [PMID: 34897427 PMCID: PMC9176297 DOI: 10.1093/genetics/iyab229] [Citation(s) in RCA: 167] [Impact Index Per Article: 55.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Accepted: 12/03/2021] [Indexed: 11/13/2022] Open
Abstract
Stochastic simulation is a key tool in population genetics, since the models involved are often analytically intractable and simulation is usually the only way of obtaining ground-truth data to evaluate inferences. Because of this, a large number of specialized simulation programs have been developed, each filling a particular niche, but with largely overlapping functionality and a substantial duplication of effort. Here, we introduce msprime version 1.0, which efficiently implements ancestry and mutation simulations based on the succinct tree sequence data structure and the tskit library. We summarize msprime's many features, and show that its performance is excellent, often many times faster and more memory efficient than specialized alternatives. These high-performance features have been thoroughly tested and validated, and built using a collaborative, open source development model, which reduces duplication of effort and promotes software quality via community engagement.
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Affiliation(s)
- Franz Baumdicker
- Cluster of Excellence “Controlling Microbes to Fight Infections”, Mathematical and Computational Population Genetics, University of Tübingen, 72076 Tübingen, Germany
| | - Gertjan Bisschop
- Institute of Evolutionary Biology, The University of Edinburgh, Edinburgh EH9 3FL, UK
| | - Daniel Goldstein
- Khoury College of Computer Sciences, Northeastern University, Boston, MA 02115, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Graham Gower
- Lundbeck GeoGenetics Centre, Globe Institute, University of Copenhagen, 1350 Copenhagen K, Denmark
| | - Aaron P Ragsdale
- Department of Integrative Biology, University of Wisconsin–Madison, Madison, WI 53706, USA
| | - Georgia Tsambos
- Melbourne Integrative Genomics, School of Mathematics and Statistics, University of Melbourne, Parkville, VIC 3010, Australia
| | - Sha Zhu
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, UK
| | - Bjarki Eldon
- Leibniz Institute for Evolution and Biodiversity Science, Museum für Naturkunde, Berlin 10115, Germany
| | | | - Jared G Galloway
- Department of Biology, Institute of Ecology and Evolution, University of Oregon, Eugene, OR 97403-5289, USA
- Computational Biology Program, Fred Hutchinson Cancer Research Center, Seattle, WA 98102, USA
| | - Ariella L Gladstein
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599-7264, USA
- Embark Veterinary, Inc., Boston, MA 02111, USA
| | - Gregor Gorjanc
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh EH25 9RG, UK
| | - Bing Guo
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD 21201, USA
| | - Ben Jeffery
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, UK
| | - Warren W Kretzschumar
- Center for Hematology and Regenerative Medicine, Karolinska Institute, 141 83 Huddinge, Sweden
| | - Konrad Lohse
- Institute of Evolutionary Biology, The University of Edinburgh, Edinburgh EH9 3FL, UK
| | | | - Dominic Nelson
- Department of Human Genetics, McGill University, Montréal, QC H3A 0C7, Canada
| | - Nathaniel S Pope
- Department of Entomology, Pennsylvania State University, State College, PA 16802, USA
| | - Consuelo D Quinto-Cortés
- National Laboratory of Genomics for Biodiversity (LANGEBIO), Unit of Advanced Genomics, CINVESTAV, Irapuato, Mexico
| | - Murillo F Rodrigues
- Department of Biology, Institute of Ecology and Evolution, University of Oregon, Eugene, OR 97403-5289, USA
| | | | - Thibaut Sellinger
- Professorship for Population Genetics, Department of Life Science Systems, Technical University of Munich, 85354 Freising, Germany
| | - Kevin Thornton
- Department of Ecology and Evolutionary Biology, University of California, Irvine, CA 92697, USA
| | | | - Anthony W Wohns
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, UK
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Yan Wong
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, UK
| | - Simon Gravel
- Department of Human Genetics, McGill University, Montréal, QC H3A 0C7, Canada
| | - Andrew D Kern
- Department of Biology, Institute of Ecology and Evolution, University of Oregon, Eugene, OR 97403-5289, USA
| | - Jere Koskela
- Department of Statistics, University of Warwick, Coventry CV4 7AL, UK
| | - Peter L Ralph
- Department of Biology, Institute of Ecology and Evolution, University of Oregon, Eugene, OR 97403-5289, USA
- Department of Mathematics, University of Oregon, Eugene, OR 97403-5289, USA
| | - Jerome Kelleher
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, UK
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45
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Manthey JD, Bourgeois Y, Meheretu Y, Boissinot S. Varied diversification patterns and distinct demographic trajectories in Ethiopian montane forest bird (Aves: Passeriformes) populations separated by the Great Rift Valley. Mol Ecol 2022; 31:2664-2678. [PMID: 35239243 DOI: 10.1111/mec.16417] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2020] [Revised: 02/16/2022] [Accepted: 02/21/2022] [Indexed: 11/30/2022]
Abstract
Taxon-specific characteristics and extrinsic climatic and geological forces may both shape population differentiation and speciation. In geographically and taxonomically focused investigations, differentiation may occur synchronously as species respond to the same external conditions. Conversely, when evolution is investigated in taxa with largely varying traits, population differentiation and speciation is complex and shaped by interactions of Earth's template and species-specific traits. As such, it is important to characterize evolutionary histories broadly across the tree of life, especially in geographic regions that are exceptionally diverse and under pressures from human activities such as in biodiversity hotspots. Here, using whole-genome sequencing data, we characterize genomic variation in populations of six Ethiopian Highlands forest bird species separated by a lowland biogeographic barrier, the Great Rift Valley (GRV). In all six species, populations on either side of the GRV exhibited significant but varying levels of genetic differentiation. Species' dispersal ability was negatively correlated with levels of population differentiation. Isolation with migration models indicated varied patterns of population differentiation and connectivity among populations of the focal species. We found that demographic histories-estimated for each individual-varied by both species and population but were consistent between individuals of the same species and sampling region. We found that genomic diversity varied by half an order of magnitude across species, and that this variation could largely be explained by the harmonic mean of effective population size over the past 200,000 years. Overall, we found that even in highly dispersive species like birds, the GRV acts as a substantial biogeographic barrier.
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46
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Zhang M, Yang Q, Ai H, Huang L. Revisiting the Evolutionary History of Pigs via De Novo Mutation Rate Estimation in A Three-generation Pedigree. GENOMICS, PROTEOMICS & BIOINFORMATICS 2022; 20:1040-1052. [PMID: 35181533 DOI: 10.1016/j.gpb.2022.02.001] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/25/2021] [Revised: 12/20/2021] [Accepted: 02/09/2022] [Indexed: 12/30/2022]
Abstract
The mutation rate used in the previous analyses of pig evolution and demographics was cursory and hence invited potential bias in inferring evolutionary history. Herein, we estimated the de novo mutation rate of pigs as 3.6 × 10-9 per base per generation using high-quality whole-genome sequencing data from nine individuals in a three-generation pedigree through stringent filtering and validation. Using this mutation rate, we re-investigated the evolutionary history of pigs. The estimated divergence time of ∼ 10 kiloyears ago (KYA) between European wild and domesticated pigs was consistent with the domestication time of European pigs based on archaeological evidence. However, other divergence events inferred here were not as ancient as previously described. Our estimates suggested that Sus speciation occurred ∼ 1.36 million years ago (MYA); European wild pigs split from Asian wild pigs only ∼ 219 KYA; and south and north Chinese wild pigs split ∼ 25 KYA. Meanwhile, our results showed that the most recent divergence event between Chinese wild and domesticated pigs occurred in the Hetao plain, North China, approximately 20 KYA, supporting the possibly independent domestication in North China along the middle Yellow River. We also found that the maximum effective population size of pigs was ∼ 6 times larger than the previous estimate. An archaic migration from other Sus species originating ∼ 2 MYA to European pigs was detected during western colonization of pigs; this interfered with the previous demographic inference. Our de novo mutation rate estimation and its consequences for demographic history inference reasonably provide a new vision regarding the evolutionary history of pigs.
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Affiliation(s)
- Mingpeng Zhang
- State Key Laboratory for Swine Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang 330045, China
| | - Qiang Yang
- State Key Laboratory for Swine Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang 330045, China
| | - Huashui Ai
- State Key Laboratory for Swine Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang 330045, China.
| | - Lusheng Huang
- State Key Laboratory for Swine Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang 330045, China.
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47
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Speidel L, Cassidy L, Davies RW, Hellenthal G, Skoglund P, Myers SR. Inferring Population Histories for Ancient Genomes Using Genome-Wide Genealogies. Mol Biol Evol 2021; 38:3497-3511. [PMID: 34129037 PMCID: PMC8383901 DOI: 10.1093/molbev/msab174] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
Ancient genomes anchor genealogies in directly observed historical genetic variation and contextualize ancestral lineages with archaeological insights into their geography and cultural associations. However, the majority of ancient genomes are of lower coverage and cannot be directly built into genealogies. Here, we present a fast and scalable method, Colate, the first approach for inferring ancestral relationships through time between low-coverage genomes without requiring phasing or imputation. Our approach leverages sharing patterns of mutations dated using a genealogy to infer coalescence rates. For deeply sequenced ancient genomes, we additionally introduce an extension of the Relate algorithm for joint inference of genealogies incorporating such genomes. Application to 278 present-day and 430 ancient DNA samples of >0.5x mean coverage allows us to identify dynamic population structure and directional gene flow between early farmer and European hunter-gatherer groups. We further show that the previously reported, but still unexplained, increase in the TCC/TTC mutation rate, which is strongest in West Eurasia today, was already present at similar strength and widespread in the Late Glacial Period ~10k-15k years ago, but is not observed in samples >30k years old. It is strongest in Neolithic farmers, and highly correlated with recent coalescence rates between other genomes and a 10,000-year-old Anatolian hunter-gatherer. This suggests gene-flow among ancient peoples postdating the last glacial maximum as widespread and localizes the driver of this mutational signal in both time and geography in that region. Our approach should be widely applicable in future for addressing other evolutionary questions, and in other species.
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Affiliation(s)
- Leo Speidel
- Francis Crick Institute, London, United Kingdom
- Genetics Institute, University College London, London, United Kingdom
| | - Lara Cassidy
- Smurfit Institute of Genetics, Trinity College Dublin, Dublin, Republic of Ireland
| | - Robert W Davies
- Department of Statistics, University of Oxford, Oxford, United Kingdom
| | | | | | - Simon R Myers
- Department of Statistics, University of Oxford, Oxford, United Kingdom
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
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48
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Almarri MA, Haber M, Lootah RA, Hallast P, Al Turki S, Martin HC, Xue Y, Tyler-Smith C. The genomic history of the Middle East. Cell 2021; 184:4612-4625.e14. [PMID: 34352227 PMCID: PMC8445022 DOI: 10.1016/j.cell.2021.07.013] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2021] [Revised: 05/17/2021] [Accepted: 07/09/2021] [Indexed: 11/22/2022]
Abstract
The Middle East region is important to understand human evolution and migrations but is underrepresented in genomic studies. Here, we generated 137 high-coverage physically phased genome sequences from eight Middle Eastern populations using linked-read sequencing. We found no genetic traces of early expansions out-of-Africa in present-day populations but found Arabians have elevated Basal Eurasian ancestry that dilutes their Neanderthal ancestry. Population sizes within the region started diverging 15–20 kya, when Levantines expanded while Arabians maintained smaller populations that derived ancestry from local hunter-gatherers. Arabians suffered a population bottleneck around the aridification of Arabia 6 kya, while Levantines had a distinct bottleneck overlapping the 4.2 kya aridification event. We found an association between movement and admixture of populations in the region and the spread of Semitic languages. Finally, we identify variants that show evidence of selection, including polygenic selection. Our results provide detailed insights into the genomic and selective histories of the Middle East. Middle Easterners do not have ancestry from an early out-of-Africa expansion Basal Eurasian and African ancestry in Arabians deplete their Neanderthal ancestry Populations experienced bottlenecks overlapping aridification events Identification of recent single and polygenic signals of selection in Arabia
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Affiliation(s)
- Mohamed A Almarri
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton CB10 1SA, UK; Department of Forensic Science and Criminology, Dubai Police GHQ, Dubai, United Arab Emirates.
| | - Marc Haber
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham B15 2TT, UK; Centre for Computational Biology, University of Birmingham, Birmingham B15 2TT, UK.
| | - Reem A Lootah
- Department of Forensic Science and Criminology, Dubai Police GHQ, Dubai, United Arab Emirates
| | - Pille Hallast
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton CB10 1SA, UK; Institute of Biomedicine and Translational Medicine, University of Tartu, Tartu 50411, Estonia
| | - Saeed Al Turki
- Translational Pathology, Department of Pathology and Laboratory Medicine, King Abdulaziz Medical City, Ministry of National Guard-Health Affairs, Riyadh, Saudi Arabia; Department of Genetics & Genomics, College of Medicine and Health Sciences, United Arab Emirates University, Al Ain, United Arab Emirates
| | - Hilary C Martin
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton CB10 1SA, UK
| | - Yali Xue
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton CB10 1SA, UK
| | - Chris Tyler-Smith
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton CB10 1SA, UK
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49
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Ahlquist KD, Bañuelos MM, Funk A, Lai J, Rong S, Villanea FA, Witt KE. Our Tangled Family Tree: New Genomic Methods Offer Insight into the Legacy of Archaic Admixture. Genome Biol Evol 2021; 13:evab115. [PMID: 34028527 PMCID: PMC8480178 DOI: 10.1093/gbe/evab115] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Revised: 05/07/2021] [Accepted: 05/22/2021] [Indexed: 11/30/2022] Open
Abstract
The archaic ancestry present in the human genome has captured the imagination of both scientists and the wider public in recent years. This excitement is the result of new studies pushing the envelope of what we can learn from the archaic genetic information that has survived for over 50,000 years in the human genome. Here, we review the most recent ten years of literature on the topic of archaic introgression, including the current state of knowledge on Neanderthal and Denisovan introgression, as well as introgression from other as-yet unidentified archaic populations. We focus this review on four topics: 1) a reimagining of human demographic history, including evidence for multiple admixture events between modern humans, Neanderthals, Denisovans, and other archaic populations; 2) state-of-the-art methods for detecting archaic ancestry in population-level genomic data; 3) how these novel methods can detect archaic introgression in modern African populations; and 4) the functional consequences of archaic gene variants, including how those variants were co-opted into novel function in modern human populations. The goal of this review is to provide a simple-to-access reference for the relevant methods and novel data, which has changed our understanding of the relationship between our species and its siblings. This body of literature reveals the large degree to which the genetic legacy of these extinct hominins has been integrated into the human populations of today.
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Affiliation(s)
- K D Ahlquist
- Center for Computational Molecular Biology, Brown University, Providence, Rhode Island, USA
- Department of Molecular Biology, Cell Biology, and Biochemistry, Brown University, Providence, Rhode Island, USA
| | - Mayra M Bañuelos
- Center for Computational Molecular Biology, Brown University, Providence, Rhode Island, USA
- Department of Molecular Biology, Cell Biology, and Biochemistry, Brown University, Providence, Rhode Island, USA
| | - Alyssa Funk
- Center for Computational Molecular Biology, Brown University, Providence, Rhode Island, USA
- Department of Molecular Biology, Cell Biology, and Biochemistry, Brown University, Providence, Rhode Island, USA
| | - Jiaying Lai
- Center for Computational Molecular Biology, Brown University, Providence, Rhode Island, USA
- Brown Center for Biomedical Informatics, Brown University, Providence, Rhode Island, USA
| | - Stephen Rong
- Center for Computational Molecular Biology, Brown University, Providence, Rhode Island, USA
- Department of Molecular Biology, Cell Biology, and Biochemistry, Brown University, Providence, Rhode Island, USA
| | - Fernando A Villanea
- Center for Computational Molecular Biology, Brown University, Providence, Rhode Island, USA
- Department of Anthropology, University of Colorado Boulder, Colorado, USA
| | - Kelsey E Witt
- Center for Computational Molecular Biology, Brown University, Providence, Rhode Island, USA
- Department of Ecology and Evolutionary Biology, Brown University, Providence, Rhode Island, USA
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Sellinger TPP, Abu-Awad D, Tellier A. Limits and convergence properties of the sequentially Markovian coalescent. Mol Ecol Resour 2021; 21:2231-2248. [PMID: 33978324 DOI: 10.1111/1755-0998.13416] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2020] [Revised: 04/19/2021] [Accepted: 04/29/2021] [Indexed: 02/07/2023]
Abstract
Several methods based on the sequentially Markovian coalescent (SMC) make use of full genome sequence data from samples to infer population demographic history including past changes in population size, admixture, migration events and population structure. More recently, the original theoretical framework has been extended to allow the simultaneous estimation of population size changes along with other life history traits such as selfing or seed banking. The latter developments enhance the applicability of SMC methods to nonmodel species. Although convergence proofs have been given using simulated data in a few specific cases, an in-depth investigation of the limitations of SMC methods is lacking. In order to explore such limits, we first develop a tool inferring the best case convergence of SMC methods assuming the true underlying coalescent genealogies are known. This tool can be used to quantify the amount and type of information that can be confidently retrieved from given data sets prior to the analysis of the real data. Second, we assess the inference accuracy when the assumptions of SMC approaches are violated due to departures from the model, namely the presence of transposable elements, variable recombination and mutation rates along the sequence, and SNP calling errors. Third, we deliver a new interpretation of SMC methods by highlighting the importance of the transition matrix, which we argue can be used as a set of summary statistics in other statistical inference methods, uncoupling the SMC from hidden Markov models (HMMs). We finally offer recommendations to better apply SMC methods and build adequate data sets under budget constraints.
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Affiliation(s)
| | - Diala Abu-Awad
- Department of Life Science Systems, Technical University of Munich, Munchen, Germany
| | - Aurélien Tellier
- Department of Life Science Systems, Technical University of Munich, Munchen, Germany
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