1
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Moriano J, Leonardi O, Vitriolo A, Testa G, Boeckx C. A multi-layered integrative analysis reveals a cholesterol metabolic program in outer radial glia with implications for human brain evolution. Development 2024; 151:dev202390. [PMID: 39114968 DOI: 10.1242/dev.202390] [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: 10/01/2023] [Accepted: 07/18/2024] [Indexed: 08/28/2024]
Abstract
The definition of molecular and cellular mechanisms contributing to brain ontogenetic trajectories is essential to investigate the evolution of our species. Yet their functional dissection at an appropriate level of granularity remains challenging. Capitalizing on recent efforts that have extensively profiled neural stem cells from the developing human cortex, we develop an integrative computational framework to perform trajectory inference and gene regulatory network reconstruction, (pseudo)time-informed non-negative matrix factorization for learning the dynamics of gene expression programs, and paleogenomic analysis for a higher-resolution mapping of derived regulatory variants in our species in comparison with our closest relatives. We provide evidence for cell type-specific regulation of gene expression programs during indirect neurogenesis. In particular, our analysis uncovers a key role for a cholesterol program in outer radial glia, regulated by zinc-finger transcription factor KLF6. A cartography of the regulatory landscape impacted by Homo sapiens-derived variants reveals signals of selection clustering around regulatory regions associated with GLI3, a well-known regulator of radial glial cell cycle, and impacting KLF6 regulation. Our study contributes to the evidence of significant changes in metabolic pathways in recent human brain evolution.
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Affiliation(s)
- Juan Moriano
- Department of General Linguistics, University of Barcelona, 08007 Barcelona, Spain
- University of Barcelona Institute of Complex Systems, 08007 Barcelona, Spain
| | | | - Alessandro Vitriolo
- Human Technopole, Viale Rita Levi-Montalcini 1, 20157 Milan, Italy
- Department of Oncology and Hemato-Oncology, University of Milan, Via Santa Sofia 9, 20122 Milan, Italy
| | - Giuseppe Testa
- Human Technopole, Viale Rita Levi-Montalcini 1, 20157 Milan, Italy
- Department of Oncology and Hemato-Oncology, University of Milan, Via Santa Sofia 9, 20122 Milan, Italy
| | - Cedric Boeckx
- Department of General Linguistics, University of Barcelona, 08007 Barcelona, Spain
- University of Barcelona Institute of Complex Systems, 08007 Barcelona, Spain
- University of Barcelona Institute of Neurosciences, 08007 Barcelona, Spain
- Catalan Institute for Research and Advanced Studies (ICREA), 08007 Barcelona, Spain
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2
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González-Buenfil R, Vieyra-Sánchez S, Quinto-Cortés CD, Oppenheimer SJ, Pomat W, Laman M, Cervantes-Hernández MC, Barberena-Jonas C, Auckland K, Allen A, Allen S, Phipps ME, Huerta-Sanchez E, Ioannidis AG, Mentzer AJ, Moreno-Estrada A. Genetic Signatures of Positive Selection in Human Populations Adapted to High Altitude in Papua New Guinea. Genome Biol Evol 2024; 16:evae161. [PMID: 39173139 PMCID: PMC11339866 DOI: 10.1093/gbe/evae161] [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] [Accepted: 07/09/2024] [Indexed: 08/24/2024] Open
Abstract
Papua New Guinea (PNG) hosts distinct environments mainly represented by the ecoregions of the Highlands and Lowlands that display increased altitude and a predominance of pathogens, respectively. Since its initial peopling approximately 50,000 years ago, inhabitants of these ecoregions might have differentially adapted to the environmental pressures exerted by each of them. However, the genetic basis of adaptation in populations from these areas remains understudied. Here, we investigated signals of positive selection in 62 highlanders and 43 lowlanders across 14 locations in the main island of PNG using whole-genome genotype data from the Oceanian Genome Variation Project (OGVP) and searched for signals of positive selection through population differentiation and haplotype-based selection scans. Additionally, we performed archaic ancestry estimation to detect selection signals in highlanders within introgressed regions of the genome. Among highland populations we identified candidate genes representing known biomarkers for mountain sickness (SAA4, SAA1, PRDX1, LDHA) as well as candidate genes of the Notch signaling pathway (PSEN1, NUMB, RBPJ, MAML3), a novel proposed pathway for high altitude adaptation in multiple organisms. We also identified candidate genes involved in oxidative stress, inflammation, and angiogenesis, processes inducible by hypoxia, as well as in components of the eye lens and the immune response. In contrast, candidate genes in the lowlands are mainly related to the immune response (HLA-DQB1, HLA-DQA2, TAAR6, TAAR9, TAAR8, RNASE4, RNASE6, ANG). Moreover, we find two candidate regions to be also enriched with archaic introgressed segments, suggesting that archaic admixture has played a role in the local adaptation of PNG populations.
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Affiliation(s)
- Ram González-Buenfil
- Advanced Genomics Unit (UGA), Center for Research and Advanced Studies of the National Polytechnic Institute (Cinvestav), Irapuato, Guanajuato, Mexico
| | - Sofía Vieyra-Sánchez
- Advanced Genomics Unit (UGA), Center for Research and Advanced Studies of the National Polytechnic Institute (Cinvestav), Irapuato, Guanajuato, Mexico
| | - Consuelo D Quinto-Cortés
- Advanced Genomics Unit (UGA), Center for Research and Advanced Studies of the National Polytechnic Institute (Cinvestav), Irapuato, Guanajuato, Mexico
| | | | - William Pomat
- Vector-Borne Diseases Unit, Papua New Guinea Institute of Medical Research, Madang, Papua New Guinea
| | - Moses Laman
- Vector-Borne Diseases Unit, Papua New Guinea Institute of Medical Research, Madang, Papua New Guinea
| | - Mayté C Cervantes-Hernández
- Advanced Genomics Unit (UGA), Center for Research and Advanced Studies of the National Polytechnic Institute (Cinvestav), Irapuato, Guanajuato, Mexico
| | - Carmina Barberena-Jonas
- Advanced Genomics Unit (UGA), Center for Research and Advanced Studies of the National Polytechnic Institute (Cinvestav), Irapuato, Guanajuato, Mexico
| | | | - Angela Allen
- Department of Molecular Haematology, MRC Weatherall Institute of Molecular Medicine, Headley Way, Headington, Oxford, OX3 9DS, UK
| | - Stephen Allen
- Department of Clinical Sciences,Liverpool School of Tropical Medicine, Pembroke Place, Liverpool, L3 5QA, UK
| | - Maude E Phipps
- Jeffrey Cheah School of Medicine and Health Sciences, Monash University Malaysia, Subang Jaya 47500, Selangor, Malaysia
| | - Emilia Huerta-Sanchez
- Center for Computational Molecular Biology, Brown University, Providence, RI 02912, USA
- Department of Ecology, Evolution and Organismal Biology, Brown University, Providence, RI 02912, USA
| | - Alexander G Ioannidis
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA, USA
- Department of Biomedical Data Science, Stanford Medical School, Stanford, CA, USA
| | | | - Andrés Moreno-Estrada
- Advanced Genomics Unit (UGA), Center for Research and Advanced Studies of the National Polytechnic Institute (Cinvestav), Irapuato, Guanajuato, Mexico
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3
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Li L, Comi TJ, Bierman RF, Akey JM. Recurrent gene flow between Neanderthals and modern humans over the past 200,000 years. Science 2024; 385:eadi1768. [PMID: 38991054 DOI: 10.1126/science.adi1768] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Accepted: 05/14/2024] [Indexed: 07/13/2024]
Abstract
Although it is well known that the ancestors of modern humans and Neanderthals admixed, the effects of gene flow on the Neanderthal genome are not well understood. We develop methods to estimate the amount of human-introgressed sequences in Neanderthals and apply it to whole-genome sequence data from 2000 modern humans and three Neanderthals. We estimate that Neanderthals have 2.5 to 3.7% human ancestry, and we leverage human-introgressed sequences in Neanderthals to revise estimates of Neanderthal ancestry in modern humans, show that Neanderthal population sizes were significantly smaller than previously estimated, and identify two distinct waves of modern human gene flow into Neanderthals. Our data provide insights into the genetic legacy of recurrent gene flow between modern humans and Neanderthals.
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Affiliation(s)
- Liming Li
- Department of Medical Genetics and Developmental Biology, School of Medicine, The Key Laboratory of Developmental Genes and Human Diseases, Ministry of Education, Southeast University, Nanjing 210009, China
- The Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08540, USA
| | - Troy J Comi
- The Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08540, USA
| | - Rob F Bierman
- The Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08540, USA
| | - Joshua M Akey
- The Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08540, USA
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4
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Iasi LNM, Chintalapati M, Skov L, Mesa AB, Hajdinjak M, Peter BM, Moorjani P. Neandertal ancestry through time: Insights from genomes of ancient and present-day humans. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.13.593955. [PMID: 38798350 PMCID: PMC11118355 DOI: 10.1101/2024.05.13.593955] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/29/2024]
Abstract
Gene flow from Neandertals has shaped the landscape of genetic and phenotypic variation in modern humans. We identify the location and size of introgressed Neandertal ancestry segments in more than 300 genomes spanning the last 50,000 years. We study how Neandertal ancestry is shared among individuals to infer the time and duration of the Neandertal gene flow. We find the correlation of Neandertal segment locations across individuals and their divergence to sequenced Neandertals, both support a model of single major Neandertal gene flow. Our catalog of introgressed segments through time confirms that most natural selection-positive and negative-on Neandertal ancestry variants occurred immediately after the gene flow, and provides new insights into how the contact with Neandertals shaped human origins and adaptation.
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Affiliation(s)
- Leonardo N. M. Iasi
- Department for Evolutionary Genetics, Max-Planck-Institute for Evolutionary Anthropology; Leipzig, 04301, Germany
| | - Manjusha Chintalapati
- Department of Molecular and Cell Biology, University of California Berkeley; Berkeley, CA 94720, USA
| | - Laurits Skov
- Department of Molecular and Cell Biology, University of California Berkeley; Berkeley, CA 94720, USA
| | - Alba Bossoms Mesa
- Department for Evolutionary Genetics, Max-Planck-Institute for Evolutionary Anthropology; Leipzig, 04301, Germany
| | - Mateja Hajdinjak
- Department for Evolutionary Genetics, Max-Planck-Institute for Evolutionary Anthropology; Leipzig, 04301, Germany
- The Francis Crick Institute; London, NW1 1AT, UK
| | - Benjamin M. Peter
- Department for Evolutionary Genetics, Max-Planck-Institute for Evolutionary Anthropology; Leipzig, 04301, Germany
- Department of Biology, University of Rochester; Rochester NY, 14620,USA
| | - Priya Moorjani
- Department of Molecular and Cell Biology, University of California Berkeley; Berkeley, CA 94720, USA
- Center for Computational Biology, University of California Berkeley; Berkeley, CA 94720, USA
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5
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Carrión-Castillo A, Boeckx C. Insights into the genetic architecture of cerebellar lobules derived from the UK Biobank. Sci Rep 2024; 14:9488. [PMID: 38664414 DOI: 10.1038/s41598-024-59699-9] [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: 11/07/2023] [Accepted: 04/15/2024] [Indexed: 06/19/2024] Open
Abstract
In this work we endeavor to further understand the genetic architecture of the cerebellum by examining the genetic underpinnings of the different cerebellar lob(ul)es, identifying their genetic relation to cortical and subcortical regions, as well as to psychiatric disorders, as well as traces of their evolutionary trajectories. We confirm the moderate heritability of cerebellar volumes, and reveal genetic clustering and variability across their different substructures, which warranted a detailed analysis using this higher structural resolution. We replicated known genetic correlations with several subcortical volumes, and report new cortico-cerebellar genetic correlations, including negative genetic correlations between anterior cerebellar lobules and cingulate, and positive ones between lateral Crus I and lobule VI with cortical measures in the fusiform region. Heritability partitioning for evolutionary annotations highlighted that the vermis of Crus II has depleted heritability in genomic regions of "archaic introgression deserts", but no enrichment/depletion of heritability in any other cerebellar regions. Taken together, these findings reveal novel insights into the genetic underpinnings of the different cerebellar lobules.
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Affiliation(s)
- Amaia Carrión-Castillo
- Basque Center on Cognition, Brain and Language (BCBL), Donostia-San Sebastián, Spain.
- Ikerbasque, Basque Foundation for Science, Bilbao, Spain.
| | - Cedric Boeckx
- Universitat de Barcelona, Barcelona, Spain.
- Universitat de Barcelona Institute of Complex Systems, Barcelona, Spain.
- Universitat de Barcelona Institute of Neurosciences, Barcelona, Spain.
- Catalan Institute for Research and Advanced Studies (ICREA), Barcelona, Spain.
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6
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Liu X, Koyama S, Tomizuka K, Takata S, Ishikawa Y, Ito S, Kosugi S, Suzuki K, Hikino K, Koido M, Koike Y, Horikoshi M, Gakuhari T, Ikegawa S, Matsuda K, Momozawa Y, Ito K, Kamatani Y, Terao C. Decoding triancestral origins, archaic introgression, and natural selection in the Japanese population by whole-genome sequencing. SCIENCE ADVANCES 2024; 10:eadi8419. [PMID: 38630824 PMCID: PMC11023554 DOI: 10.1126/sciadv.adi8419] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/21/2023] [Accepted: 03/07/2024] [Indexed: 04/19/2024]
Abstract
We generated Japanese Encyclopedia of Whole-Genome/Exome Sequencing Library (JEWEL), a high-depth whole-genome sequencing dataset comprising 3256 individuals from across Japan. Analysis of JEWEL revealed genetic characteristics of the Japanese population that were not discernible using microarray data. First, rare variant-based analysis revealed an unprecedented fine-scale genetic structure. Together with population genetics analysis, the present-day Japanese can be decomposed into three ancestral components. Second, we identified unreported loss-of-function (LoF) variants and observed that for specific genes, LoF variants appeared to be restricted to a more limited set of transcripts than would be expected by chance, with PTPRD as a notable example. Third, we identified 44 archaic segments linked to complex traits, including a Denisovan-derived segment at NKX6-1 associated with type 2 diabetes. Most of these segments are specific to East Asians. Fourth, we identified candidate genetic loci under recent natural selection. Overall, our work provided insights into genetic characteristics of the Japanese population.
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Affiliation(s)
- Xiaoxi Liu
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Clinical Research Center, Shizuoka General Hospital, Shizuoka, Japan
| | - Satoshi Koyama
- Laboratory for Cardiovascular Genomics and Informatics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of Harvard and MIT, Boston, MA, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
| | - Kohei Tomizuka
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Sadaaki Takata
- Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Yuki Ishikawa
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Shuji Ito
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Laboratory for Bone and Joint Diseases, RIKEN Center for Medical Sciences, Tokyo, Japan
- Department of Orthopedic Surgery, Faculty of Medicine, Shimane University, Izumo, Japan
| | - Shunichi Kosugi
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Kunihiko Suzuki
- Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Keiko Hikino
- Laboratory for Pharmacogenomics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Masaru Koido
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Laboratory of Complex Trait Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Yoshinao Koike
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Laboratory for Bone and Joint Diseases, RIKEN Center for Medical Sciences, Tokyo, Japan
- Department of Orthopedic Surgery, Hokkaido University Graduate School of Medicine, Sapporo, Japan
| | - Momoko Horikoshi
- Laboratory for Genomics of Diabetes and Metabolism, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Takashi Gakuhari
- Institute for the Study of Ancient Civilizations and Cultural Resources, College of Human and Social Sciences, Kanazawa University, Kanazawa, Japan
| | - Shiro Ikegawa
- Laboratory for Bone and Joint Diseases, RIKEN Center for Medical Sciences, Tokyo, Japan
| | - Kochi Matsuda
- Laboratory of Genome Technology, Human Genome Center, Institute of Medical Science, The University of Tokyo, Tokyo, Japan
- Laboratory of Clinical Genome Sequencing, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Yukihide Momozawa
- Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Kaoru Ito
- Laboratory for Cardiovascular Genomics and Informatics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Yoichiro Kamatani
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Laboratory of Complex Trait Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Chikashi Terao
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Clinical Research Center, Shizuoka General Hospital, Shizuoka, Japan
- The Department of Applied Genetics, The School of Pharmaceutical Sciences, University of Shizuoka, Shizuoka, Japan
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7
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Ferreira RC, Rodrigues CR, Broach JR, Briones MRS. Convergent Mutations and Single Nucleotide Variants in Mitochondrial Genomes of Modern Humans and Neanderthals. Int J Mol Sci 2024; 25:3785. [PMID: 38612593 PMCID: PMC11012180 DOI: 10.3390/ijms25073785] [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: 01/25/2024] [Revised: 03/12/2024] [Accepted: 03/13/2024] [Indexed: 04/14/2024] Open
Abstract
The genetic contributions of Neanderthals to the modern human genome have been evidenced by the comparison of present-day human genomes with paleogenomes. Neanderthal signatures in extant human genomes are attributed to intercrosses between Neanderthals and archaic anatomically modern humans (AMHs). Although Neanderthal signatures are well documented in the nuclear genome, it has been proposed that there is no contribution of Neanderthal mitochondrial DNA to contemporary human genomes. Here we show that modern human mitochondrial genomes contain 66 potential Neanderthal signatures, or Neanderthal single nucleotide variants (N-SNVs), of which 36 lie in coding regions and 7 result in nonsynonymous changes. Seven N-SNVs are associated with traits such as cycling vomiting syndrome, Alzheimer's disease and Parkinson's disease, and two N-SNVs are associated with intelligence quotient. Based on recombination tests, principal component analysis (PCA) and the complete absence of these N-SNVs in 41 archaic AMH mitogenomes, we conclude that convergent evolution, and not recombination, explains the presence of N-SNVs in present-day human mitogenomes.
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Affiliation(s)
- Renata C. Ferreira
- Center for Medical Bioinformatics, Federal University of São Paulo, São Paulo 04039032, SP, Brazil;
| | - Camila R. Rodrigues
- Graduate Program in Microbiology and Immunology, Federal University of São Paulo, São Paulo 04039032, SP, Brazil;
| | - James R. Broach
- Department of Biochemistry, Institute for Personalized Medicine, Pennsylvania State University College of Medicine, 500 University Drive, Hershey, PA 17033, USA;
| | - Marcelo R. S. Briones
- Center for Medical Bioinformatics, Federal University of São Paulo, São Paulo 04039032, SP, Brazil;
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8
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Zeberg H, Jakobsson M, Pääbo S. The genetic changes that shaped Neandertals, Denisovans, and modern humans. Cell 2024; 187:1047-1058. [PMID: 38367615 DOI: 10.1016/j.cell.2023.12.029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Revised: 11/20/2023] [Accepted: 12/20/2023] [Indexed: 02/19/2024]
Abstract
Modern human ancestors diverged from the ancestors of Neandertals and Denisovans about 600,000 years ago. Until about 40,000 years ago, these three groups existed in parallel, occasionally met, and exchanged genes. A critical question is why modern humans, and not the other two groups, survived, became numerous, and developed complex cultures. Here, we discuss genetic differences among the groups and some of their functional consequences. As more present-day genome sequences become available from diverse groups, we predict that very few, if any, differences will distinguish all modern humans from all Neandertals and Denisovans. We propose that the genetic basis of what constitutes a modern human is best thought of as a combination of genetic features, where perhaps none of them is present in each and every present-day individual.
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Affiliation(s)
- Hugo Zeberg
- Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, 04103 Leipzig, Germany; Department of Physiology and Pharmacology, Karolinska Institutet, 17165 Stockholm, Sweden.
| | - Mattias Jakobsson
- Department of Organismal Biology, Uppsala University, 75236 Uppsala, Sweden
| | - Svante Pääbo
- Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, 04103 Leipzig, Germany; Okinawa Institute of Science and Technology, Onnason 904-0495, Okinawa, Japan.
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9
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Ray DD, Flagel L, Schrider DR. IntroUNET: Identifying introgressed alleles via semantic segmentation. PLoS Genet 2024; 20:e1010657. [PMID: 38377104 PMCID: PMC10906877 DOI: 10.1371/journal.pgen.1010657] [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: 02/06/2023] [Revised: 03/01/2024] [Accepted: 01/29/2024] [Indexed: 02/22/2024] Open
Abstract
A growing body of evidence suggests that gene flow between closely related species is a widespread phenomenon. Alleles that introgress from one species into a close relative are typically neutral or deleterious, but sometimes confer a significant fitness advantage. Given the potential relevance to speciation and adaptation, numerous methods have therefore been devised to identify regions of the genome that have experienced introgression. Recently, supervised machine learning approaches have been shown to be highly effective for detecting introgression. One especially promising approach is to treat population genetic inference as an image classification problem, and feed an image representation of a population genetic alignment as input to a deep neural network that distinguishes among evolutionary models (i.e. introgression or no introgression). However, if we wish to investigate the full extent and fitness effects of introgression, merely identifying genomic regions in a population genetic alignment that harbor introgressed loci is insufficient-ideally we would be able to infer precisely which individuals have introgressed material and at which positions in the genome. Here we adapt a deep learning algorithm for semantic segmentation, the task of correctly identifying the type of object to which each individual pixel in an image belongs, to the task of identifying introgressed alleles. Our trained neural network is thus able to infer, for each individual in a two-population alignment, which of those individual's alleles were introgressed from the other population. We use simulated data to show that this approach is highly accurate, and that it can be readily extended to identify alleles that are introgressed from an unsampled "ghost" population, performing comparably to a supervised learning method tailored specifically to that task. Finally, we apply this method to data from Drosophila, showing that it is able to accurately recover introgressed haplotypes from real data. This analysis reveals that introgressed alleles are typically confined to lower frequencies within genic regions, suggestive of purifying selection, but are found at much higher frequencies in a region previously shown to be affected by adaptive introgression. Our method's success in recovering introgressed haplotypes in challenging real-world scenarios underscores the utility of deep learning approaches for making richer evolutionary inferences from genomic data.
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Affiliation(s)
- Dylan D. Ray
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Lex Flagel
- Division of Data Science, Gencove Inc., New York, New York, United States of America
- Department of Plant and Microbial Biology, University of Minnesota, Saint Paul, Minnesota, United States of America
| | - Daniel R. Schrider
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
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10
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Marchi N, Kapopoulou A, Excoffier L. Demogenomic inference from spatially and temporally heterogeneous samples. Mol Ecol Resour 2024; 24:e13877. [PMID: 37819677 DOI: 10.1111/1755-0998.13877] [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: 04/24/2023] [Revised: 09/15/2023] [Accepted: 09/27/2023] [Indexed: 10/13/2023]
Abstract
Modern and ancient genomes are not necessarily drawn from homogeneous populations, as they may have been collected from different places and at different times. This heterogeneous sampling can be an issue for demographic inferences and results in biased demographic parameters and incorrect model choice if not properly considered. When explicitly accounted for, it can result in very complex models and high data dimensionality that are difficult to analyse. In this paper, we formally study the impact of such spatial and temporal sampling heterogeneity on demographic inference, and we introduce a way to circumvent this problem. To deal with structured samples without increasing the dimensionality of the site frequency spectrum (SFS), we introduce a new structured approach to the existing program fastsimcoal2. We assess the efficiency and relevance of this methodological update with simulated and modern human genomic data. We particularly focus on spatial and temporal heterogeneities to evidence the interest of this new SFS-based approach, which can be especially useful when handling scattered and ancient DNA samples, as in conservation genetics or archaeogenetics.
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Affiliation(s)
- Nina Marchi
- CMPG, Institute for Ecology and Evolution, University of Berne, Berne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Adamandia Kapopoulou
- CMPG, Institute for Ecology and Evolution, University of Berne, Berne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Laurent Excoffier
- CMPG, Institute for Ecology and Evolution, University of Berne, Berne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
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11
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Di Santo LN, Quilodrán CS, Currat M. Temporal Variation in Introgressed Segments' Length Statistics Computed from a Limited Number of Ancient Genomes Sheds Light on Past Admixture Pulses. Mol Biol Evol 2023; 40:msad252. [PMID: 37992125 PMCID: PMC10715198 DOI: 10.1093/molbev/msad252] [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: 04/18/2023] [Revised: 10/16/2023] [Accepted: 11/09/2023] [Indexed: 11/24/2023] Open
Abstract
Hybridization is recognized as an important evolutionary force, but identifying and timing admixture events between divergent lineages remain a major aim of evolutionary biology. While this has traditionally been done using inferential tools on contemporary genomes, the latest advances in paleogenomics have provided a growing wealth of temporally distributed genomic data. Here, we used individual-based simulations to generate chromosome-level genomic data for a 2-population system and described temporal neutral introgression patterns under a single- and 2-pulse admixture model. We computed 6 summary statistics aiming to inform the timing and number of admixture pulses between interbreeding entities: lengths of introgressed sequences and their variance within genomes, as well as genome-wide introgression proportions and related measures. The first 2 statistics could confidently be used to infer interlineage hybridization history, peaking at the beginning and shortly after an admixture pulse. Temporal variation in introgression proportions and related statistics provided more limited insights, particularly when considering their application to ancient genomes still scant in number. Lastly, we computed these statistics on Homo sapiens paleogenomes and successfully inferred the hybridization pulse from Neanderthal that occurred approximately 40 to 60 kya. The scarce number of genomes dating from this period prevented more precise inferences, but the accumulation of paleogenomic data opens promising perspectives as our approach only requires a limited number of ancient genomes.
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Affiliation(s)
- Lionel N Di Santo
- Department of Genetics and Evolution, University of Geneva, Geneva CH-1205
| | | | - Mathias Currat
- Department of Genetics and Evolution, University of Geneva, Geneva CH-1205
- Institute of Genetics and Genomics in Geneva (IGE3), University of Geneva, Geneva CH-1205
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12
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Ragsdale AP. Human evolution: Neanderthal footprints in African genomes. Curr Biol 2023; 33:R1197-R1200. [PMID: 37989099 DOI: 10.1016/j.cub.2023.10.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2023]
Abstract
Human and Neanderthal populations met and mixed on multiple occasions over evolutionary time, resulting in the exchange of genetic material. New genomic analyses of diverse African populations reveal a history of bidirectional gene flow and selection acting on introgressed alleles.
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Affiliation(s)
- Aaron P Ragsdale
- Department of Integrative Biology, University of Wisconsin-Madison, Madison, WI 53706, USA.
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13
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Harris DN, Platt A, Hansen MEB, Fan S, McQuillan MA, Nyambo T, Mpoloka SW, Mokone GG, Belay G, Fokunang C, Njamnshi AK, Tishkoff SA. Diverse African genomes reveal selection on ancient modern human introgressions in Neanderthals. Curr Biol 2023; 33:4905-4916.e5. [PMID: 37837965 PMCID: PMC10841429 DOI: 10.1016/j.cub.2023.09.066] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Revised: 07/18/2023] [Accepted: 09/26/2023] [Indexed: 10/16/2023]
Abstract
Comparisons of Neanderthal genomes to anatomically modern human (AMH) genomes show a history of Neanderthal-to-AMH introgression stemming from interbreeding after the migration of AMHs from Africa to Eurasia. All non-sub-Saharan African AMHs have genomic regions genetically similar to Neanderthals that descend from this introgression. Regions of the genome with Neanderthal similarities have also been identified in sub-Saharan African populations, but their origins have been unclear. To better understand how these regions are distributed across sub-Saharan Africa, the source of their origin, and what their distribution within the genome tells us about early AMH and Neanderthal evolution, we analyzed a dataset of high-coverage, whole-genome sequences from 180 individuals from 12 diverse sub-Saharan African populations. In sub-Saharan African populations with non-sub-Saharan African ancestry, as much as 1% of their genomes can be attributed to Neanderthal sequence introduced by recent migration, and subsequent admixture, of AMH populations originating from the Levant and North Africa. However, most Neanderthal homologous regions in sub-Saharan African populations originate from migration of AMH populations from Africa to Eurasia ∼250 kya, and subsequent admixture with Neanderthals, resulting in ∼6% AMH ancestry in Neanderthals. These results indicate that there have been multiple migration events of AMHs out of Africa and that Neanderthal and AMH gene flow has been bi-directional. Observing that genomic regions where AMHs show a depletion of Neanderthal introgression are also regions where Neanderthal genomes show a depletion of AMH introgression points to deleterious interactions between introgressed variants and background genomes in both groups-a hallmark of incipient speciation.
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Affiliation(s)
- Daniel N Harris
- Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Alexander Platt
- Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Matthew E B Hansen
- Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Shaohua Fan
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, School of Life Science, Fudan University, Shanghai 200438, China
| | - Michael A McQuillan
- Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Thomas Nyambo
- Department of Biochemistry and Molecular Biology, Hubert Kairuki Memorial University, Dar es Salaam, Tanzania
| | - Sununguko Wata Mpoloka
- Department of Biological Sciences, Faculty of Science, University of Botswana, Private Bag UB 0022, Gaborone, Botswana
| | - Gaonyadiwe George Mokone
- Department of Biomedical Sciences, Faculty of Medicine, University of Botswana, Private Bag UB 0022, Gaborone, Botswana
| | - Gurja Belay
- Department of Microbial Cellular and Molecular Biology, Addis Ababa University, P.O. Box 1176, Addis Ababa, Ethiopia
| | - Charles Fokunang
- Department of Pharmacotoxicology and Pharmacokinetics, Faculty of Medicine and Biomedical Sciences, The University of Yaoundé I, P.O. Box 337, Yaoundé, Cameroon
| | - Alfred K Njamnshi
- Brain Research Africa Initiative (BRAIN), P.O. Box 25625, Yaoundé, Cameroon; Neuroscience Lab, Faculty of Medicine and Biomedical Sciences, The University of Yaoundé I, Yaoundé, Cameroon
| | - Sarah A Tishkoff
- Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA.
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14
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Zhang Y, Zhu Q, Shao Y, Jiang Y, Ouyang Y, Zhang L, Zhang W. Inferring Historical Introgression with Deep Learning. Syst Biol 2023; 72:1013-1038. [PMID: 37257491 DOI: 10.1093/sysbio/syad033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Revised: 05/28/2023] [Accepted: 05/30/2023] [Indexed: 06/02/2023] Open
Abstract
Resolving phylogenetic relationships among taxa remains a challenge in the era of big data due to the presence of genetic admixture in a wide range of organisms. Rapidly developing sequencing technologies and statistical tests enable evolutionary relationships to be disentangled at a genome-wide level, yet many of these tests are computationally intensive and rely on phased genotypes, large sample sizes, restricted phylogenetic topologies, or hypothesis testing. To overcome these difficulties, we developed a deep learning-based approach, named ERICA, for inferring genome-wide evolutionary relationships and local introgressed regions from sequence data. ERICA accepts sequence alignments of both population genomic data and multiple genome assemblies, and efficiently identifies discordant genealogy patterns and exchanged regions across genomes when compared with other methods. We further tested ERICA using real population genomic data from Heliconius butterflies that have undergone adaptive radiation and frequent hybridization. Finally, we applied ERICA to characterize hybridization and introgression in wild and cultivated rice, revealing the important role of introgression in rice domestication and adaptation. Taken together, our findings demonstrate that ERICA provides an effective method for teasing apart evolutionary relationships using whole genome data, which can ultimately facilitate evolutionary studies on hybridization and introgression.
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Affiliation(s)
- Yubo Zhang
- State Key Laboratory of Protein and Plant Gene Research, Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
| | - Qingjie Zhu
- Chinese Institute for Brain Research, Beijing 102206, China
| | - Yi Shao
- Chinese Institute for Brain Research, Beijing 102206, China
| | - Yanchen Jiang
- State Key Laboratory of Protein and Plant Gene Research, Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
- State Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Peking University, Beijing 100871, China
| | - Yidan Ouyang
- National Key Laboratory of Crop Genetic Improvement and National Centre of Plant Gene Research (Wuhan), Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China
| | - Li Zhang
- Chinese Institute for Brain Research, Beijing 102206, China
| | - Wei Zhang
- State Key Laboratory of Protein and Plant Gene Research, Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
- State Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Peking University, Beijing 100871, China
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15
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Quilodrán CS, Rio J, Tsoupas A, Currat M. Past human expansions shaped the spatial pattern of Neanderthal ancestry. SCIENCE ADVANCES 2023; 9:eadg9817. [PMID: 37851812 PMCID: PMC10584333 DOI: 10.1126/sciadv.adg9817] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Accepted: 09/11/2023] [Indexed: 10/20/2023]
Abstract
The worldwide expansion of modern humans (Homo sapiens) started before the extinction of Neanderthals (Homo neanderthalensis). Both species coexisted and interbred, leading to slightly higher introgression in East Asians than in Europeans. This distinct ancestry level has been argued to result from selection, but range expansions of modern humans could provide an alternative explanation. This hypothesis would lead to spatial introgression gradients, increasing with distance from the expansion source. We investigate the presence of Neanderthal introgression gradients after past human expansions by analyzing Eurasian paleogenomes. We show that the out-of-Africa expansion resulted in spatial gradients of Neanderthal ancestry that persisted through time. While keeping the same gradient orientation, the expansion of early Neolithic farmers contributed decisively to reducing the Neanderthal introgression in European populations compared to Asian populations. This is because Neolithic farmers carried less Neanderthal DNA than preceding Paleolithic hunter-gatherers. This study shows that inferences about past human population dynamics can be made from the spatiotemporal variation in archaic introgression.
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Affiliation(s)
| | - Jérémy Rio
- Department of Genetics and Evolution, University of Geneva, Geneva, Switzerland
| | - Alexandros Tsoupas
- Department of Genetics and Evolution, University of Geneva, Geneva, Switzerland
| | - Mathias Currat
- Department of Genetics and Evolution, University of Geneva, Geneva, Switzerland
- Institute of Genetics and Genomics in Geneva (IGE3), University of Geneva, Geneva, Switzerland
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16
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Roca-Umbert A, Garcia-Calleja J, Vogel-González M, Fierro-Villegas A, Ill-Raga G, Herrera-Fernández V, Bosnjak A, Muntané G, Gutiérrez E, Campelo F, Vicente R, Bosch E. Human genetic adaptation related to cellular zinc homeostasis. PLoS Genet 2023; 19:e1010950. [PMID: 37747921 PMCID: PMC10553801 DOI: 10.1371/journal.pgen.1010950] [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: 02/28/2023] [Revised: 10/05/2023] [Accepted: 08/31/2023] [Indexed: 09/27/2023] Open
Abstract
SLC30A9 encodes a ubiquitously zinc transporter (ZnT9) and has been consistently suggested as a candidate for positive selection in humans. However, no direct adaptive molecular phenotype has been demonstrated. Our results provide evidence for directional selection operating in two major complementary haplotypes in Africa and East Asia. These haplotypes are associated with differential gene expression but also differ in the Met50Val substitution (rs1047626) in ZnT9, which we show is found in homozygosis in the Denisovan genome and displays accompanying signatures suggestive of archaic introgression. Although we found no significant differences in systemic zinc content between individuals with different rs1047626 genotypes, we demonstrate that the expression of the derived isoform (ZnT9 50Val) in HEK293 cells shows a gain of function when compared with the ancestral (ZnT9 50Met) variant. Notably, the ZnT9 50Val variant was found associated with differences in zinc handling by the mitochondria and endoplasmic reticulum, with an impact on mitochondrial metabolism. Given the essential role of the mitochondria in skeletal muscle and since the derived allele at rs1047626 is known to be associated with greater susceptibility to several neuropsychiatric traits, we propose that adaptation to cold may have driven this selection event, while also impacting predisposition to neuropsychiatric disorders in modern humans.
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Affiliation(s)
- Ana Roca-Umbert
- Institut de Biologia Evolutiva (UPF-CSIC), Departament de Medicina i Ciències de la Vida, Universitat Pompeu Fabra, Parc de Recerca Biomèdica de Barcelona, Barcelona, Spain
| | - Jorge Garcia-Calleja
- Institut de Biologia Evolutiva (UPF-CSIC), Departament de Medicina i Ciències de la Vida, Universitat Pompeu Fabra, Parc de Recerca Biomèdica de Barcelona, Barcelona, Spain
| | - Marina Vogel-González
- Laboratory of Molecular Physiology, Department of Medicine and Life Sciences (MELIS), Universitat Pompeu Fabra, Barcelona, Spain
| | - Alejandro Fierro-Villegas
- Laboratory of Molecular Physiology, Department of Medicine and Life Sciences (MELIS), Universitat Pompeu Fabra, Barcelona, Spain
| | - Gerard Ill-Raga
- Laboratory of Molecular Physiology, Department of Medicine and Life Sciences (MELIS), Universitat Pompeu Fabra, Barcelona, Spain
| | - Víctor Herrera-Fernández
- Laboratory of Molecular Physiology, Department of Medicine and Life Sciences (MELIS), Universitat Pompeu Fabra, Barcelona, Spain
| | - Anja Bosnjak
- Laboratory of Molecular Physiology, Department of Medicine and Life Sciences (MELIS), Universitat Pompeu Fabra, Barcelona, Spain
| | - Gerard Muntané
- Institut de Biologia Evolutiva (UPF-CSIC), Departament de Medicina i Ciències de la Vida, Universitat Pompeu Fabra, Parc de Recerca Biomèdica de Barcelona, Barcelona, Spain
- Hospital Universitari Institut Pere Mata, IISPV, Universitat Rovira i Virgili, Reus, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Madrid, Spain
| | - Esteban Gutiérrez
- Laboratory of Molecular Physiology, Department of Medicine and Life Sciences (MELIS), Universitat Pompeu Fabra, Barcelona, Spain
| | - Felix Campelo
- ICFO-Institut de Ciencies Fotoniques, The Barcelona Institute of Science and Technology, Barcelona, Spain
| | - Rubén Vicente
- Laboratory of Molecular Physiology, Department of Medicine and Life Sciences (MELIS), Universitat Pompeu Fabra, Barcelona, Spain
| | - Elena Bosch
- Institut de Biologia Evolutiva (UPF-CSIC), Departament de Medicina i Ciències de la Vida, Universitat Pompeu Fabra, Parc de Recerca Biomèdica de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Madrid, Spain
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17
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Flegontov P, Işıldak U, Maier R, Yüncü E, Changmai P, Reich D. Modeling of African population history using f-statistics is biased when applying all previously proposed SNP ascertainment schemes. PLoS Genet 2023; 19:e1010931. [PMID: 37676865 PMCID: PMC10508636 DOI: 10.1371/journal.pgen.1010931] [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: 01/22/2023] [Revised: 09/19/2023] [Accepted: 08/21/2023] [Indexed: 09/09/2023] Open
Abstract
f-statistics have emerged as a first line of analysis for making inferences about demographic history from genome-wide data. Not only are they guaranteed to allow robust tests of the fits of proposed models of population history to data when analyzing full genome sequencing data-that is, all single nucleotide polymorphisms (SNPs) in the individuals being analyzed-but they are also guaranteed to allow robust tests of models for SNPs ascertained as polymorphic in a population that is an outgroup in a phylogenetic sense to all groups being analyzed. True "outgroup ascertainment" is in practice impossible in humans because our species has arisen from a substructured ancestral population that does not descend from a homogeneous ancestral population going back many hundreds of thousands of years into the past. However, initial studies suggested that non-outgroup-ascertainment schemes might produce robust enough results using f-statistics, and that motivated widespread fitting of models to data using non-outgroup-ascertained SNP panels such as the "Affymetrix Human Origins array" which has been genotyped on thousands of modern individuals from hundreds of populations, or the "1240k" in-solution enrichment reagent which has been the source of about 70% of published genome-wide data for ancient humans. In this study, we show that while analyses of population history using such panels work well for studies of relationships among non-African populations and one African outgroup, when co-modeling more than one sub-Saharan African and/or archaic human groups (Neanderthals and Denisovans), fitting of f-statistics to such SNP sets is expected to frequently lead to false rejection of true demographic histories, and failure to reject incorrect models. Analyzing panels of SNPs polymorphic in archaic humans, which has been suggested as a solution for the ascertainment problem, has limited statistical power and retains important biases. However, by carrying out simulations of diverse demographic histories, we show that bias in inferences based on f-statistics can be minimized by ascertaining on variants common in a union of diverse African groups; such ascertainment retains high statistical power while allowing co-analysis of archaic and modern groups.
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Affiliation(s)
- Pavel Flegontov
- Department of Human Evolutionary Biology, Harvard University, Cambridge, Massachusetts, United States of America
- Department of Biology and Ecology, Faculty of Science, University of Ostrava, Ostrava, Czechia
- Kalmyk Research Center of the Russian Academy of Sciences, Elista, Russia
| | - Ulaş Işıldak
- Department of Biology and Ecology, Faculty of Science, University of Ostrava, Ostrava, Czechia
| | - Robert Maier
- Department of Human Evolutionary Biology, Harvard University, Cambridge, Massachusetts, United States of America
| | - Eren Yüncü
- Department of Biology and Ecology, Faculty of Science, University of Ostrava, Ostrava, Czechia
| | - Piya Changmai
- Department of Biology and Ecology, Faculty of Science, University of Ostrava, Ostrava, Czechia
| | - David Reich
- Department of Human Evolutionary Biology, Harvard University, Cambridge, Massachusetts, United States of America
- Department of Genetics, Harvard Medical School, Boston, Massachusetts, United States of America
- Howard Hughes Medical Institute, Harvard Medical School, Boston, Massachusetts, United States of America
- Broad Institute of Harvard and MIT, Cambridge, Massachusetts, United States of America
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18
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Piccardi M, Gentiluomo M, Bertoncini S, Pezzilli R, Erőss B, Bunduc S, Uzunoglu FG, Talar-Wojnarowska R, Vanagas T, Sperti C, Oliverius M, Aoki MN, Ermini S, Hussein T, Boggi U, Jamroziak K, Maiello E, Morelli L, Vodickova L, Di Franco G, Landi S, Szentesi A, Lovecek M, Puzzono M, Tavano F, van Laarhoven HWM, Zerbi A, Mohelnikova-Duchonova B, Stocker H, Costello E, Capurso G, Ginocchi L, Lawlor RT, Vanella G, Bazzocchi F, Izbicki JR, Latiano A, Bueno-de-Mesquita B, Ponz de Leon Pisani R, Schöttker B, Soucek P, Hegyi P, Gazouli M, Hackert T, Kupcinskas J, Poskiene L, Tacelli M, Roth S, Carrara S, Perri F, Hlavac V, Theodoropoulos GE, Busch OR, Mambrini A, van Eijck CHJ, Arcidiacono P, Scarpa A, Pasquali C, Basso D, Lucchesi M, Milanetto AC, Neoptolemos JP, Cavestro GM, Janciauskas D, Chen X, Chammas R, Goetz M, Brenner H, Archibugi L, Dannemann M, Canzian F, Tofanelli S, Campa D. Exploring the Neandertal legacy of pancreatic ductal adenocarcinoma risk in Eurasians. Biol Res 2023; 56:46. [PMID: 37574541 PMCID: PMC10424372 DOI: 10.1186/s40659-023-00457-y] [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: 06/30/2022] [Accepted: 07/20/2023] [Indexed: 08/15/2023] Open
Abstract
BACKGROUND The genomes of present-day non-Africans are composed of 1-3% of Neandertal-derived DNA as a consequence of admixture events between Neandertals and anatomically modern humans about 50-60 thousand years ago. Neandertal-introgressed single nucleotide polymorphisms (aSNPs) have been associated with modern human disease-related traits, which are risk factors for pancreatic ductal adenocarcinoma (PDAC), such as obesity, type 2 diabetes, and inflammation. In this study, we aimed at investigating the role of aSNPs in PDAC in three Eurasian populations. RESULTS The high-coverage Vindija Neandertal genome was used to select aSNPs in non-African populations from 1000 Genomes project phase 3 data. Then, the association between aSNPs and PDAC risk was tested independently in Europeans and East Asians, using existing GWAS data on more than 200 000 individuals. We did not find any significant associations between aSNPs and PDAC in samples of European descent, whereas, in East Asians, we observed that the Chr10p12.1-rs117585753-T allele (MAF = 10%) increased the risk to develop PDAC (OR = 1.35, 95%CI 1.19-1.54, P = 3.59 × 10-6), with a P-value close to a threshold that takes into account multiple testing. CONCLUSIONS Our results show only a minimal contribution of Neandertal SNPs to PDAC risk.
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Affiliation(s)
- Margherita Piccardi
- Department of Biology, Unit of Genetics, University of Pisa, Via Derna 1, 56126, Pisa, Italy
| | - Manuel Gentiluomo
- Department of Biology, Unit of Genetics, University of Pisa, Via Derna 1, 56126, Pisa, Italy
| | - Stefania Bertoncini
- Department of Biology, Unit of Zoology and Anthropology, University of Pisa, Pisa, Italy
| | | | - Bálint Erőss
- Institute for Translational Medicine, Medical School, University of Pécs, Pécs, Hungary
| | - Stefania Bunduc
- Institute for Translational Medicine, Medical School, University of Pécs, Pécs, Hungary
- Center for Translational Medicine, Semmelweis University, Budapest, Hungary
- Division of Pancreatic Diseases, Heart and Vascular Center, Semmelweis University, Budapest, Hungary
- Carol Davila University of Medicine and Pharmacy, Bucharest, Romania
| | - Faik G Uzunoglu
- Department of General, Visceral and Thoracic Surgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | | | - Tomas Vanagas
- Department of Surgery, Lithuanian University of Health Sciences, Kaunas, Lithuania
| | - Cosimo Sperti
- Department DISCOG, Chirurgia Generale 1, University of Padova, Padua, Italy
| | - Martin Oliverius
- Department of Surgery, Third Faculty of Medicine, University Hospital Kralovske Vinohrady, Charles University, Prague, Czech Republic
| | - Mateus Nóbrega Aoki
- Laboratory for Applied Science and Technology in Health, Carlos Chagas Institute, Curitiba, Brazil
| | - Stefano Ermini
- Blood Transfusion Service, Azienda Ospedaliero-Universitaria Meyer, Children's Hospital, Florence, Italy
| | - Tamás Hussein
- Institute for Translational Medicine, Medical School, University of Pécs, Pécs, Hungary
| | - Ugo Boggi
- Division of General and Transplantation Surgery, University of Pisa, Pisa, Italy
| | - Krzysztof Jamroziak
- Department of Hematology, Transplantation and Internal Medicine, University of Warsaw, Warsaw, Poland
| | - Evaristo Maiello
- Department of Oncology, Fondazione IRCCS "Casa Sollievo Della Sofferenza" Hospital, San Giovanni Rotondo, Foggia, Italy
| | - Luca Morelli
- Department of Translational Research and New Technologies in Medicine and Surgery, General Surgery Unit, University of Pisa, Pisa, Italy
| | - Ludmila Vodickova
- Department of Molecular Biology of Cancer, Institute of Experimental Medicine of the Czech Academy of Sciences, Prague, Czech Republic
- Biomedical Center, Faculty of Medicine in Pilsen, Charles University, Pilsen, Czech Republic
- Institute of Biology and Medical Genetics, First Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Gregorio Di Franco
- Department of Translational Research and New Technologies in Medicine and Surgery, General Surgery Unit, University of Pisa, Pisa, Italy
| | - Stefano Landi
- Department of Biology, Unit of Genetics, University of Pisa, Via Derna 1, 56126, Pisa, Italy
| | - Andrea Szentesi
- Institute for Translational Medicine, Medical School, University of Pécs, Pécs, Hungary
- Center for Translational Medicine, Semmelweis University, Budapest, Hungary
- János Szentágothai Research Center, University of Pécs, Pécs, Hungary
| | - Martin Lovecek
- Department of Surgery I, University Hospital Olomouc, Olomouc, Czech Republic
| | - Marta Puzzono
- Gastroenterology and Gastrointestinal Endoscopy Unit, Vita-Salute San Raffaele University, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Francesca Tavano
- Division of Gastroenterology and Research Laboratory, Fondazione IRCCS "Casa Sollievo Della Sofferenza" Hospital, San Giovanni Rotondo, Foggia, Italy
| | - Hanneke W M van Laarhoven
- Department of Medical Oncology, Amsterdam UMC, Cancer Center Amsterdam, University of Amsterdam, Amsterdam, The Netherlands
| | - Alessandro Zerbi
- Pancreatic Unit, IRCCS Humanitas Research Hospital, Milan, Italy
- Department of Biomedical Sciences, Humanitas University, Milan, Italy
| | | | - Hannah Stocker
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Network Aging Research (NAR), Heidelberg University, Heidelberg, Germany
| | - Eithne Costello
- Department of Molecular & Clinical Cancer Medicine, University of Liverpool, Liverpool, UK
| | - Gabriele Capurso
- Digestive and Liver Disease Unit, S Andrea Hospital, Rome, Italy
- Pancreas Translational and Clinical Research Center, Pancreato-Biliary Endoscopy and Endoscopic Ultrasound, San Raffaele Scientific Institute IRCCS, Milan, Italy
| | - Laura Ginocchi
- Oncological Department, Oncology of Massa Carrara, ASL Toscana Nord Ovest, Massa Carrara, Italy
| | - Rita T Lawlor
- ARC-NET Research Centre and Department of Diagnostics and Public Health, Section of Pathology, University of Verona, Verona, Italy
| | - Giuseppe Vanella
- Digestive and Liver Disease Unit, S Andrea Hospital, Rome, Italy
- Pancreas Translational and Clinical Research Center, Pancreato-Biliary Endoscopy and Endoscopic Ultrasound, San Raffaele Scientific Institute IRCCS, Milan, Italy
| | - Francesca Bazzocchi
- Department of Surgery, Fondazione IRCCS "Casa Sollievo Della Sofferenza" Hospital, San Giovanni Rotondo, Foggia, Italy
| | - Jakob R Izbicki
- Department of General, Visceral and Thoracic Surgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Anna Latiano
- Division of Gastroenterology and Research Laboratory, Fondazione IRCCS "Casa Sollievo Della Sofferenza" Hospital, San Giovanni Rotondo, Foggia, Italy
| | - Bas Bueno-de-Mesquita
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
| | - Ruggero Ponz de Leon Pisani
- Pancreato-Biliary Endoscopy and Endoscopic Ultrasound, Pancreas Translational and Clinical Research Center, San Raffaele Scientific Institute IRCCS, Milan, Italy
| | - Ben Schöttker
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Network Aging Research (NAR), Heidelberg University, Heidelberg, Germany
| | - Pavel Soucek
- Biomedical Center, Faculty of Medicine in Pilsen, Charles University, Pilsen, Czech Republic
| | - Péter Hegyi
- Institute for Translational Medicine, Medical School, University of Pécs, Pécs, Hungary
- Center for Translational Medicine, Semmelweis University, Budapest, Hungary
- Division of Pancreatic Diseases, Heart and Vascular Center, Semmelweis University, Budapest, Hungary
- János Szentágothai Research Center, University of Pécs, Pécs, Hungary
| | - Maria Gazouli
- Laboratory of Biology, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Thilo Hackert
- Department of General, Visceral, and Transplantation Surgery, University of Heidelberg, Heidelberg, Germany
| | - Juozas Kupcinskas
- Department of Gastroenterology and Institute for Digestive Research, Lithuanian University of Health Sciences, Kaunas, Lithuania
| | - Lina Poskiene
- Department of Pathology, Lithuanian University of Health Sciences, Kaunas, Lithuania
| | - Matteo Tacelli
- Pancreato-Biliary Endoscopy and Endoscopic Ultrasound, Pancreas Translational and Clinical Research Center, San Raffaele Scientific Institute IRCCS, Milan, Italy
| | - Susanne Roth
- Department of General, Visceral, and Transplantation Surgery, University of Heidelberg, Heidelberg, Germany
| | - Silvia Carrara
- Department of Gastroenterology, Endoscopic Unit, IRCCS Humanitas Research Hospital, Milan, Italy
| | - Francesco Perri
- Division of Gastroenterology and Research Laboratory, Fondazione IRCCS "Casa Sollievo Della Sofferenza" Hospital, San Giovanni Rotondo, Foggia, Italy
| | - Viktor Hlavac
- Biomedical Center, Faculty of Medicine in Pilsen, Charles University, Pilsen, Czech Republic
| | - George E Theodoropoulos
- First Department of Propaedeutic Surgery, Hippocration General Hospital, National and Kapodistrian University of Athens, Athens, Greece
| | - Olivier R Busch
- Department of Surgery, Amsterdam UMC, Cancer Center Amsterdam, University of Amsterdam, Amsterdam, the Netherlands
| | - Andrea Mambrini
- Oncological Department, Oncology of Massa Carrara, ASL Toscana Nord Ovest, Massa Carrara, Italy
| | - Casper H J van Eijck
- Department of Surgery, Erasmus MC University Medical Center, Rotterdam, the Netherlands
| | - Paolo Arcidiacono
- Pancreato-Biliary Endoscopy and Endoscopic Ultrasound, Pancreas Translational and Clinical Research Center, San Raffaele Scientific Institute IRCCS, Milan, Italy
| | - Aldo Scarpa
- ARC-NET Research Centre and Department of Diagnostics and Public Health, Section of Pathology, University of Verona, Verona, Italy
| | - Claudio Pasquali
- Department DISCOG, Chirurgia Generale 3, University of Padova, Padua, Italy
| | - Daniela Basso
- Department DIMED, Laboratory Medicine, University of Padova, Padua, Italy
| | - Maurizio Lucchesi
- Oncological Department, Oncology of Massa Carrara, ASL Toscana Nord Ovest, Massa Carrara, Italy
| | | | - John P Neoptolemos
- Department of General, Visceral, and Transplantation Surgery, University of Heidelberg, Heidelberg, Germany
| | - Giulia Martina Cavestro
- Gastroenterology and Gastrointestinal Endoscopy Unit, Vita-Salute San Raffaele University, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Dainius Janciauskas
- Department of Pathology, Lithuanian University of Health Sciences, Kaunas, Lithuania
| | - Xuechen Chen
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Medical Faculty Heidelberg, Heidelberg University, Heidelberg, Germany
| | - Roger Chammas
- Department of Radiology and Oncology, Institute of Cancer of São Paulo (ICESP) São Paulo, Sao Paulo, Brazil
- Faculty of Medicine, University of São Paulo, São Paulo, Brazil
| | - Mara Goetz
- Department of General, Visceral and Thoracic Surgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Division of Preventive Oncology, German Cancer Research Center (DKFZ) and National Center for Tumor Diseases (NCT), Heidelberg, Germany
- German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Livia Archibugi
- Digestive and Liver Disease Unit, S Andrea Hospital, Rome, Italy
- Pancreas Translational and Clinical Research Center, Pancreato-Biliary Endoscopy and Endoscopic Ultrasound, San Raffaele Scientific Institute IRCCS, Milan, Italy
| | - Michael Dannemann
- Estonian Biocentre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Federico Canzian
- Genomic Epidemiology Group, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Sergio Tofanelli
- Department of Biology, Unit of Zoology and Anthropology, University of Pisa, Pisa, Italy
| | - Daniele Campa
- Department of Biology, Unit of Genetics, University of Pisa, Via Derna 1, 56126, Pisa, Italy.
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19
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Vaill M, Kawanishi K, Varki N, Gagneux P, Varki A. Comparative physiological anthropogeny: exploring molecular underpinnings of distinctly human phenotypes. Physiol Rev 2023; 103:2171-2229. [PMID: 36603157 PMCID: PMC10151058 DOI: 10.1152/physrev.00040.2021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Revised: 12/26/2022] [Accepted: 12/28/2022] [Indexed: 01/06/2023] Open
Abstract
Anthropogeny is a classic term encompassing transdisciplinary investigations of the origins of the human species. Comparative anthropogeny is a systematic comparison of humans and other living nonhuman hominids (so-called "great apes"), aiming to identify distinctly human features in health and disease, with the overall goal of explaining human origins. We begin with a historical perspective, briefly describing how the field progressed from the earliest evolutionary insights to the current emphasis on in-depth molecular and genomic investigations of "human-specific" biology and an increased appreciation for cultural impacts on human biology. While many such genetic differences between humans and other hominids have been revealed over the last two decades, this information remains insufficient to explain the most distinctive phenotypic traits distinguishing humans from other living hominids. Here we undertake a complementary approach of "comparative physiological anthropogeny," along the lines of the preclinical medical curriculum, i.e., beginning with anatomy and considering each physiological system and in each case considering genetic and molecular components that are relevant. What is ultimately needed is a systematic comparative approach at all levels from molecular to physiological to sociocultural, building networks of related information, drawing inferences, and generating testable hypotheses. The concluding section will touch on distinctive considerations in the study of human evolution, including the importance of gene-culture interactions.
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Affiliation(s)
- Michael Vaill
- Center for Academic Research and Training in Anthropogeny, University of California, San Diego, La Jolla, California
- Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, California
- Glycobiology Research and Training Center, University of California, San Diego, La Jolla, California
| | - Kunio Kawanishi
- Center for Academic Research and Training in Anthropogeny, University of California, San Diego, La Jolla, California
- Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, California
- Department of Experimental Pathology, Faculty of Medicine, University of Tsukuba, Tsukuba, Japan
| | - Nissi Varki
- Center for Academic Research and Training in Anthropogeny, University of California, San Diego, La Jolla, California
- Glycobiology Research and Training Center, University of California, San Diego, La Jolla, California
- Department of Pathology, University of California, San Diego, La Jolla, California
| | - Pascal Gagneux
- Center for Academic Research and Training in Anthropogeny, University of California, San Diego, La Jolla, California
- Glycobiology Research and Training Center, University of California, San Diego, La Jolla, California
- Department of Pathology, University of California, San Diego, La Jolla, California
| | - Ajit Varki
- Center for Academic Research and Training in Anthropogeny, University of California, San Diego, La Jolla, California
- Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, California
- Glycobiology Research and Training Center, University of California, San Diego, La Jolla, California
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20
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Ågren R, Patil S, Zhou X, Sahlholm K, Pääbo S, Zeberg H. Major Genetic Risk Factors for Dupuytren's Disease Are Inherited From Neandertals. Mol Biol Evol 2023; 40:msad130. [PMID: 37315093 DOI: 10.1093/molbev/msad130] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/16/2023] Open
Abstract
Dupuytren's disease is characterized by fingers becoming permanently bent in a flexed position. Whereas people of African ancestry are rarely afflicted by Dupuytren's disease, up to ∼30% of men over 60 years suffer from this condition in northern Europe. Here, we meta-analyze 3 biobanks comprising 7,871 cases and 645,880 controls and find 61 genome-wide significant variants associated with Dupuytren's disease. We show that 3 of the 61 loci harbor alleles of Neandertal origin, including the second and third most strongly associated ones (P = 6.4 × 10-132 and P = 9.2 × 10-69, respectively). For the most strongly associated Neandertal variant, we identify EPDR1 as the causal gene. Dupuytren's disease is an example of how admixture with Neandertals has shaped regional differences in disease prevalence.
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Affiliation(s)
- Richard Ågren
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
| | - Snehal Patil
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
| | - Xiang Zhou
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
| | - Kristoffer Sahlholm
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
- Department of Integrative Medical Biology, Wallenberg Centre for Molecular Medicine, Umeå University, Umeå, Sweden
| | - Svante Pääbo
- Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
- Human Evolutionary Genomics Unit, Okinawa Institute of Science and Technology, Okinawa, Japan
| | - Hugo Zeberg
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
- Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
- Human Evolutionary Genomics Unit, Okinawa Institute of Science and Technology, Okinawa, Japan
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21
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Petersen J, Englmaier L, Artemov AV, Poverennaya I, Mahmoud R, Bouderlique T, Tesarova M, Deviatiiarov R, Szilvásy-Szabó A, Akkuratov EE, Pajuelo Reguera D, Zeberg H, Kaucka M, Kastriti ME, Krivanek J, Radaszkiewicz T, Gömöryová K, Knauth S, Potesil D, Zdrahal Z, Ganji RS, Grabowski A, Buhl ME, Zikmund T, Kavkova M, Axelson H, Lindgren D, Kramann R, Kuppe C, Erdélyi F, Máté Z, Szabó G, Koehne T, Harkany T, Fried K, Kaiser J, Boor P, Fekete C, Rozman J, Kasparek P, Prochazka J, Sedlacek R, Bryja V, Gusev O, Adameyko I. A previously uncharacterized Factor Associated with Metabolism and Energy (FAME/C14orf105/CCDC198/1700011H14Rik) is related to evolutionary adaptation, energy balance, and kidney physiology. Nat Commun 2023; 14:3092. [PMID: 37248239 DOI: 10.1038/s41467-023-38663-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Accepted: 05/11/2023] [Indexed: 05/31/2023] Open
Abstract
In this study we use comparative genomics to uncover a gene with uncharacterized function (1700011H14Rik/C14orf105/CCDC198), which we hereby name FAME (Factor Associated with Metabolism and Energy). We observe that FAME shows an unusually high evolutionary divergence in birds and mammals. Through the comparison of single nucleotide polymorphisms, we identify gene flow of FAME from Neandertals into modern humans. We conduct knockout experiments on animals and observe altered body weight and decreased energy expenditure in Fame knockout animals, corresponding to genome-wide association studies linking FAME with higher body mass index in humans. Gene expression and subcellular localization analyses reveal that FAME is a membrane-bound protein enriched in the kidneys. Although the gene knockout results in structurally normal kidneys, we detect higher albumin in urine and lowered ferritin in the blood. Through experimental validation, we confirm interactions between FAME and ferritin and show co-localization in vesicular and plasma membranes.
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Affiliation(s)
- Julian Petersen
- Department of Orthodontics, University Leipzig Medical Center, Leipzig, Germany.
| | - Lukas Englmaier
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, 1090, Vienna, Austria
- Ludwig Boltzmann Institute for Rare and Undiagnosed Diseases, 1090, Vienna, Austria
| | - Artem V Artemov
- Department of Neuroimmunology, Center for Brain Research, Medical University Vienna, Vienna, Austria
| | - Irina Poverennaya
- Department of Neuroimmunology, Center for Brain Research, Medical University Vienna, Vienna, Austria
| | - Ruba Mahmoud
- Department of Orthodontics, University Leipzig Medical Center, Leipzig, Germany
| | - Thibault Bouderlique
- Department of Neuroimmunology, Center for Brain Research, Medical University Vienna, Vienna, Austria
| | - Marketa Tesarova
- Central European Institute of Technology, Brno University of Technology, Brno, Czech Republic
| | - Ruslan Deviatiiarov
- Regulatory Genomics Research Center, Institute of Fundamental Medicine and Biology, Kazan Federal University, Kazan, Russia
- Endocrinology Research Center, Moscow, Russia
| | - Anett Szilvásy-Szabó
- Laboratory of Integrative Neuroendocrinology, Institute of Experimental Medicine, 1083, Budapest, Hungary
| | - Evgeny E Akkuratov
- Department of Applied Physics, Royal Institute of Technology, Science for Life Laboratory, 171 65, Stockholm, Sweden
- University of Oxford, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, Oxford, OX3 9DS, UK
| | - David Pajuelo Reguera
- Institute of Molecular Genetics of the Czech Academy of Science, Czech Centre for Phenogenomics, Vestec, Czech Republic
| | - Hugo Zeberg
- Department of Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
| | - Marketa Kaucka
- Max Planck Institute for Evolutionary Biology, Plön, 24306, Germany
| | - Maria Eleni Kastriti
- Department of Neuroimmunology, Center for Brain Research, Medical University Vienna, Vienna, Austria
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
| | - Jan Krivanek
- Department of Histology and Embryology, Faculty of Medicine, Masaryk University, Brno, Czech Republic
| | - Tomasz Radaszkiewicz
- Institute of Experimental Biology, Faculty of Science, Masaryk University, Brno, Czech Republic
| | - Kristína Gömöryová
- Institute of Experimental Biology, Faculty of Science, Masaryk University, Brno, Czech Republic
| | - Sarah Knauth
- Department of Orthodontics, University Leipzig Medical Center, Leipzig, Germany
| | - David Potesil
- Central European Institute of Technology, Masaryk University, Brno, Czech Republic
| | - Zbynek Zdrahal
- Central European Institute of Technology, Masaryk University, Brno, Czech Republic
| | - Ranjani Sri Ganji
- Central European Institute of Technology, Masaryk University, Brno, Czech Republic
| | - Anna Grabowski
- Department of Neuroimmunology, Center for Brain Research, Medical University Vienna, Vienna, Austria
| | - Miriam E Buhl
- Institute of Pathology & Electron Microscopy Facility, RWTH Aachen University Hospital, Aachen, Germany
| | - Tomas Zikmund
- Central European Institute of Technology, Brno University of Technology, Brno, Czech Republic
| | - Michaela Kavkova
- Central European Institute of Technology, Brno University of Technology, Brno, Czech Republic
- Department of Histology and Embryology, Faculty of Medicine, Masaryk University, Brno, Czech Republic
| | - Håkan Axelson
- Translational Cancer Research, Department of Laboratory Medicine, Lund University, Medicon Village, Scheelevägen 2, Lund, Sweden
| | - David Lindgren
- Translational Cancer Research, Department of Laboratory Medicine, Lund University, Medicon Village, Scheelevägen 2, Lund, Sweden
| | - Rafael Kramann
- Institute of Experimental Medicine and Systems Biology, RWTH Aachen University, Aachen, Germany
| | - Christoph Kuppe
- Institute of Experimental Medicine and Systems Biology, RWTH Aachen University, Aachen, Germany
| | - Ferenc Erdélyi
- Medical Gene Technology Unit, Institute of Experimental Medicine, Budapest, Hungary
| | - Zoltán Máté
- Medical Gene Technology Unit, Institute of Experimental Medicine, Budapest, Hungary
| | - Gábor Szabó
- Medical Gene Technology Unit, Institute of Experimental Medicine, Budapest, Hungary
| | - Till Koehne
- Department of Orthodontics, University Leipzig Medical Center, Leipzig, Germany
| | - Tibor Harkany
- Department of Molecular Neurosciences, Center for Brain Research, Medical University Vienna, Vienna, Austria
| | - Kaj Fried
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
| | - Jozef Kaiser
- Central European Institute of Technology, Brno University of Technology, Brno, Czech Republic
| | - Peter Boor
- Institute of Pathology & Electron Microscopy Facility, RWTH Aachen University Hospital, Aachen, Germany
| | - Csaba Fekete
- Laboratory of Integrative Neuroendocrinology, Institute of Experimental Medicine, 1083, Budapest, Hungary
| | - Jan Rozman
- Institute of Molecular Genetics of the Czech Academy of Science, Czech Centre for Phenogenomics, Vestec, Czech Republic
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, 6, avenue du Swing, 4367, Belvaux, Luxembourg
| | - Petr Kasparek
- Institute of Molecular Genetics of the Czech Academy of Science, Czech Centre for Phenogenomics, Vestec, Czech Republic
| | - Jan Prochazka
- Institute of Molecular Genetics of the Czech Academy of Science, Czech Centre for Phenogenomics, Vestec, Czech Republic
| | - Radislav Sedlacek
- Institute of Molecular Genetics of the Czech Academy of Science, Czech Centre for Phenogenomics, Vestec, Czech Republic
| | - Vitezslav Bryja
- Institute of Experimental Biology, Faculty of Science, Masaryk University, Brno, Czech Republic
| | - Oleg Gusev
- Endocrinology Research Center, Moscow, Russia
- Intractable Disease Research Center, Graduate School of Medicine, Juntendo University, Tokyo, Japan
- Center for Integrative Medical Sciences, RIKEN, Yokohama City, Kanagawa, Japan
| | - Igor Adameyko
- Department of Neuroimmunology, Center for Brain Research, Medical University Vienna, Vienna, Austria.
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden.
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22
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Rong S, Neil CR, Welch A, Duan C, Maguire S, Meremikwu IC, Meyerson M, Evans BJ, Fairbrother WG. Large-scale functional screen identifies genetic variants with splicing effects in modern and archaic humans. Proc Natl Acad Sci U S A 2023; 120:e2218308120. [PMID: 37192163 PMCID: PMC10214146 DOI: 10.1073/pnas.2218308120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Accepted: 04/12/2023] [Indexed: 05/18/2023] Open
Abstract
Humans coexisted and interbred with other hominins which later became extinct. These archaic hominins are known to us only through fossil records and for two cases, genome sequences. Here, we engineer Neanderthal and Denisovan sequences into thousands of artificial genes to reconstruct the pre-mRNA processing patterns of these extinct populations. Of the 5,169 alleles tested in this massively parallel splicing reporter assay (MaPSy), we report 962 exonic splicing mutations that correspond to differences in exon recognition between extant and extinct hominins. Using MaPSy splicing variants, predicted splicing variants, and splicing quantitative trait loci, we show that splice-disrupting variants experienced greater purifying selection in anatomically modern humans than that in Neanderthals. Adaptively introgressed variants were enriched for moderate-effect splicing variants, consistent with positive selection for alternative spliced alleles following introgression. As particularly compelling examples, we characterized a unique tissue-specific alternative splicing variant at the adaptively introgressed innate immunity gene TLR1, as well as a unique Neanderthal introgressed alternative splicing variant in the gene HSPG2 that encodes perlecan. We further identified potentially pathogenic splicing variants found only in Neanderthals and Denisovans in genes related to sperm maturation and immunity. Finally, we found splicing variants that may contribute to variation among modern humans in total bilirubin, balding, hemoglobin levels, and lung capacity. Our findings provide unique insights into natural selection acting on splicing in human evolution and demonstrate how functional assays can be used to identify candidate causal variants underlying differences in gene regulation and phenotype.
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Affiliation(s)
- Stephen Rong
- Center for Computational Molecular Biology, Brown University, Providence, RI02912
- Department of Molecular Biology, Cell Biology, and Biochemistry, Brown University, Providence, RI02912
| | - Christopher R. Neil
- Department of Molecular Biology, Cell Biology, and Biochemistry, Brown University, Providence, RI02912
| | - Anastasia Welch
- Department of Molecular Biology, Cell Biology, and Biochemistry, Brown University, Providence, RI02912
| | - Chaorui Duan
- Department of Molecular Biology, Cell Biology, and Biochemistry, Brown University, Providence, RI02912
| | - Samantha Maguire
- Department of Molecular Biology, Cell Biology, and Biochemistry, Brown University, Providence, RI02912
| | - Ijeoma C. Meremikwu
- Department of Molecular Biology, Cell Biology, and Biochemistry, Brown University, Providence, RI02912
| | - Malcolm Meyerson
- Department of Molecular Biology, Cell Biology, and Biochemistry, Brown University, Providence, RI02912
| | - Ben J. Evans
- Department of Biology, McMaster University, Hamilton, ONL8S 4K1, Canada
| | - William G. Fairbrother
- Center for Computational Molecular Biology, Brown University, Providence, RI02912
- Department of Molecular Biology, Cell Biology, and Biochemistry, Brown University, Providence, RI02912
- Hassenfeld Child Health Innovation Institute of Brown University, Providence, RI02912
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23
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Boeckx C. What made us "hunter-gatherers of words". Front Neurosci 2023; 17:1080861. [PMID: 36845441 PMCID: PMC9947416 DOI: 10.3389/fnins.2023.1080861] [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: 10/26/2022] [Accepted: 01/19/2023] [Indexed: 02/11/2023] Open
Abstract
This paper makes three interconnected claims: (i) the "human condition" cannot be captured by evolutionary narratives that reduce it to a recent 'cognitive modernity', nor by narratives that eliminates all cognitive differences between us and out closest extinct relatives, (ii) signals from paleogenomics, especially coming from deserts of introgression but also from signatures of positive selection, point to the importance of mutations that impact neurodevelopment, plausibly leading to temperamental differences, which may impact cultural evolutionary trajectories in specific ways, and (iii) these trajectories are expected to affect the language phenotypes, modifying what is being learned and how it is put to use. In particular, I hypothesize that these different trajectories influence the development of symbolic systems, the flexible ways in which symbols combine, and the size and configurations of the communities in which these systems are put to use.
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Affiliation(s)
- Cedric Boeckx
- Section of General Linguistics, Universitat de Barcelona, Barcelona, Spain
- Institute of Complex Systems, Universitat de Barcelona, Barcelona, Spain
- Catalan Institute for Research and Advanced Studies (ICREA), Barcelona, Spain
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24
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Gontier N, Sukhoverkhov A. Reticulate evolution underlies synergistic trait formation in human communities. Evol Anthropol 2023; 32:26-38. [PMID: 36205197 DOI: 10.1002/evan.21962] [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: 09/05/2021] [Revised: 04/19/2022] [Accepted: 09/18/2022] [Indexed: 11/11/2022]
Abstract
This paper investigates how reticulate evolution contributes to a better understanding of human sociocultural evolution in general, and community formation in particular. Reticulate evolution is evolution as it occurs by means of symbiosis, symbiogenesis, lateral gene transfer, infective heredity, and hybridization. From these mechanisms and processes, we mainly zoom in on symbiosis and we investigate how it underlies the rise of (1) human, plant, animal, and machine interactions typical of agriculture, animal husbandry, farming, and industrialization; (2) diet-microbiome relationships; and (3) host-virome and other pathogen interactions that underlie human health and disease. We demonstrate that reticulate evolution necessitates an understanding of behavioral and cultural evolution at a community level, where reticulate causal processes underlie the rise of synergistic organizational traits.
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Affiliation(s)
- Nathalie Gontier
- Applied Evolutionary Epistemology Lab, Centro de Filosofia das Ciências, Departamento de História e Filosofia das Ciências, Faculdade de Ciências, Universidade de Lisboa, Lisboa, Portugal
| | - Anton Sukhoverkhov
- Department of Philosophy, Kuban State Agrarian University, Krasnodar, Russia
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25
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Schroeder L, Ackermann RR. Moving beyond the adaptationist paradigm for human evolution, and why it matters. J Hum Evol 2023; 174:103296. [PMID: 36527977 DOI: 10.1016/j.jhevol.2022.103296] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Revised: 11/12/2022] [Accepted: 11/12/2022] [Indexed: 12/23/2022]
Abstract
The Journal of Human Evolution (JHE) was founded 50 years ago when much of the foundation for how we think about human evolution was in place or being put in place, providing the main framework for how we consider our origins today. Here, we will explore historical developments, including early JHE outputs, as they relate to our understanding of the relationship between phenotypic variation and evolutionary process, and use that as a springboard for considering our current understanding of these links as applied to human evolution. We will focus specifically on how the study of variation itself has shifted us away from taxonomic and adaptationist perspectives toward a richer understanding of the processes shaping human evolutionary history, using literature searches and specific test cases to highlight this. We argue that natural selection, gene exchange, genetic drift, and mutation should not be considered individually when considering the production of hominin diversity. In this context, we offer suggestions for future research directions and reflect on this more complex understanding of human evolution and its broader relevance to society. Finally, we end by considering authorship demographics and practices in the last 50 years within JHE and how a shift in these demographics has the potential to reshape the science of human evolution going forward.
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Affiliation(s)
- Lauren Schroeder
- Department of Anthropology, University of Toronto Mississauga, Mississauga, ON, L5L 1C6, Canada; Human Evolution Research Institute, University of Cape Town, Rondebosch, 7701, South Africa.
| | - Rebecca Rogers Ackermann
- Human Evolution Research Institute, University of Cape Town, Rondebosch, 7701, South Africa; Department of Archaeology, University of Cape Town, Rondebosch, 7701, South Africa.
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26
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Wang Y, Zhao Z, Miao X, Wang Y, Qian X, Chen L, Wang C, Li S. eSMC: a statistical model to infer admixture events from individual genomics data. BMC Genomics 2022; 23:827. [PMCID: PMC9748406 DOI: 10.1186/s12864-022-09033-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Accepted: 11/21/2022] [Indexed: 12/15/2022] Open
Abstract
Abstract
Background
Inferring historical population admixture events yield essential insights in understanding a species demographic history. Methods are available to infer admixture events in demographic history with extant genetic data from multiple sources. Due to the deficiency in ancient population genetic data, there lacks a method for admixture inference from a single source. Pairwise Sequentially Markovian Coalescent (PSMC) estimates the historical effective population size from lineage genomes of a single individual, based on the distribution of the most recent common ancestor between the diploid’s alleles. However, PSMC does not infer the admixture event.
Results
Here, we proposed eSMC, an extended PSMC model for admixture inference from a single source. We evaluated our model’s performance on both in silico data and real data. We simulated population admixture events at an admixture time range from 5 kya to 100 kya (5 years/generation) with population admix ratio at 1:1, 2:1, 3:1, and 4:1, respectively. The root means the square error is $$\pm 7.61$$
±
7.61
kya for all experiments. Then we implemented our method to infer the historical admixture events in human, donkey and goat populations. The estimated admixture time for both Han and Tibetan individuals range from 60 kya to 80 kya (25 years/generation), while the estimated admixture time for the domesticated donkeys and the goats ranged from 40 kya to 60 kya (8 years/generation) and 40 kya to 100 kya (6 years/generation), respectively. The estimated admixture times were concordance to the time that domestication occurred in human history.
Conclusion
Our eSMC effectively infers the time of the most recent admixture event in history from a single individual’s genomics data. The source code of eSMC is hosted at https://github.com/zachary-zzc/eSMC.
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27
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Harvati K, Reyes-Centeno H. Evolution of Homo in the Middle and Late Pleistocene. J Hum Evol 2022; 173:103279. [PMID: 36375244 PMCID: PMC9703123 DOI: 10.1016/j.jhevol.2022.103279] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Revised: 10/10/2022] [Accepted: 10/10/2022] [Indexed: 11/13/2022]
Abstract
The Middle and Late Pleistocene is arguably the most interesting period in human evolution. This broad period witnessed the evolution of our own lineage, as well as that of our sister taxon, the Neanderthals, and related Denisovans. It is exceptionally rich in both fossil and archaeological remains, and uniquely benefits from insights gained through molecular approaches, such as paleogenetics and paleoproteomics, that are currently not widely applicable in earlier contexts. This wealth of information paints a highly complex picture, often described as 'the Muddle in the Middle,' defying the common adage that 'more evidence is needed' to resolve it. Here we review competing phylogenetic scenarios and the historical and theoretical developments that shaped our approaches to the fossil record, as well as some of the many remaining open questions associated with this period. We propose that advancing our understanding of this critical time requires more than the addition of data and will necessitate a major shift in our conceptual and theoretical framework.
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Affiliation(s)
- Katerina Harvati
- Paleoanthropology, Institute for Archaeological Sciences and Senckenberg Centre for Human Evolution and Palaeoenvironment, Eberhard Karls University of Tübingen, Rümelinstrasse 19-23, Tübingen 72070, Germany; DFG Centre for Advanced Studies 'Words, Bones, Genes, Tools: Tracking Linguistic, Cultural and Biological Trajectories of the Human Past', Rümelinstrasse 19-23, Tübingen 72070, Germany.
| | - Hugo Reyes-Centeno
- Department of Anthropology, University of Kentucky, 211 Lafferty Hall, Lexington, KY 40506, USA; William S. Webb Museum of Anthropology, University of Kentucky, 1020 Export St, Lexington, KY 40504, USA
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Campelo dos Santos AL, Owings A, Sullasi HSL, Gokcumen O, DeGiorgio M, Lindo J. Genomic evidence for ancient human migration routes along South America's Atlantic coast. Proc Biol Sci 2022; 289:20221078. [PMID: 36322514 PMCID: PMC9629774 DOI: 10.1098/rspb.2022.1078] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
An increasing body of archaeological and genomic evidence has hinted at a complex settlement process of the Americas by humans. This is especially true for South America, where unexpected ancestral signals have raised perplexing scenarios for the early migrations into different regions of the continent. Here, we present ancient human genomes from the archaeologically rich Northeast Brazil and compare them to ancient and present-day genomic data. We find a distinct relationship between ancient genomes from Northeast Brazil, Lagoa Santa, Uruguay and Panama, representing evidence for ancient migration routes along South America's Atlantic coast. To further add to the existing complexity, we also detect greater Denisovan than Neanderthal ancestry in ancient Uruguay and Panama individuals. Moreover, we find a strong Australasian signal in an ancient genome from Panama. This work sheds light on the deep demographic history of eastern South America and presents a starting point for future fine-scale investigations on the regional level.
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Affiliation(s)
- Andre Luiz Campelo dos Santos
- Department of Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, FL 33431, USA,Department of Archaeology, Federal University of Pernambuco, Recife, Pernambuco 50670-901, Brazil
| | - Amanda Owings
- Department of Anthropology, Emory University, Atlanta, GA 30322, USA
| | | | - Omer Gokcumen
- Department of Biological Sciences, State University of New York at Buffalo, Buffalo, NY 14260, USA
| | - Michael DeGiorgio
- Department of Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, FL 33431, USA
| | - John Lindo
- Department of Anthropology, Emory University, Atlanta, GA 30322, USA
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29
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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: 0] [Impact Index Per Article: 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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30
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Reilly PF, Tjahjadi A, Miller SL, Akey JM, Tucci S. The contribution of Neanderthal introgression to modern human traits. Curr Biol 2022; 32:R970-R983. [PMID: 36167050 PMCID: PMC9741939 DOI: 10.1016/j.cub.2022.08.027] [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] [Indexed: 12/13/2022]
Abstract
Neanderthals, our closest extinct relatives, lived in western Eurasia from 400,000 years ago until they went extinct around 40,000 years ago. DNA retrieved from ancient specimens revealed that Neanderthals mated with modern human contemporaries. As a consequence, introgressed Neanderthal DNA survives scattered across the human genome such that 1-4% of the genome of present-day people outside Africa are inherited from Neanderthal ancestors. Patterns of Neanderthal introgressed genomic sequences suggest that Neanderthal alleles had distinct fates in the modern human genetic background. Some Neanderthal alleles facilitated human adaptation to new environments such as novel climate conditions, UV exposure levels and pathogens, while others had deleterious consequences. Here, we review the body of work on Neanderthal introgression over the past decade. We describe how evolutionary forces shaped the genomic landscape of Neanderthal introgression and highlight the impact of introgressed alleles on human biology and phenotypic variation.
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Affiliation(s)
| | - Audrey Tjahjadi
- Department of Anthropology, Yale University, New Haven, CT, USA
| | | | - Joshua M Akey
- Lewis Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA.
| | - Serena Tucci
- Department of Anthropology, Yale University, New Haven, CT, USA; Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT, USA.
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31
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Behnamian S, Esposito U, Holland G, Alshehab G, Dobre AM, Pirooznia M, Brimacombe CS, Elhaik E. Temporal population structure, a genetic dating method for ancient Eurasian genomes from the past 10,000 years. CELL REPORTS METHODS 2022; 2:100270. [PMID: 36046618 PMCID: PMC9421539 DOI: 10.1016/j.crmeth.2022.100270] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Revised: 06/17/2022] [Accepted: 07/19/2022] [Indexed: 11/21/2022]
Abstract
Radiocarbon dating is the gold standard in archeology to estimate the age of skeletons, a key to studying their origins. Many published ancient genomes lack reliable and direct dates, which results in obscure and contradictory reports. We developed the temporal population structure (TPS), a DNA-based dating method for genomes ranging from the Late Mesolithic to today, and applied it to 3,591 ancient and 1,307 modern Eurasians. TPS predictions aligned with the known dates and correctly accounted for kin relationships. TPS dating of poorly dated Eurasian samples resolved conflicting reports in the literature, as illustrated by one test case. We also demonstrated how TPS improved the ability to study phenotypic traits over time. TPS can be used when radiocarbon dating is unfeasible or uncertain or to develop alternative hypotheses for samples younger than 10,000 years ago, a limitation that may be resolved over time as ancient data accumulate.
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Affiliation(s)
- Sara Behnamian
- Department of Biology, Lund University, 22362 Lund, Sweden
| | - Umberto Esposito
- Department of Animal and Plant Sciences, University of Sheffield, Sheffield S10 2TN, UK
| | - Grace Holland
- Department of Animal and Plant Sciences, University of Sheffield, Sheffield S10 2TN, UK
| | - Ghadeer Alshehab
- Department of Automatic Control and Systems Engineering, University of Sheffield, Sheffield S1 3JD, UK
| | - Ann M. Dobre
- Department of Animal and Plant Sciences, University of Sheffield, Sheffield S10 2TN, UK
| | - Mehdi Pirooznia
- National Heart, Lung, and Blood Institute (NHLBI), Bethesda, MD 20892, USA
| | - Conrad S. Brimacombe
- Department of Animal and Plant Sciences, University of Sheffield, Sheffield S10 2TN, UK
- Department of Anthropology and Archaeology, University of Bristol, Bristol BS8 1TH, UK
| | - Eran Elhaik
- Department of Biology, Lund University, 22362 Lund, Sweden
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32
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Vilgalys TP, Fogel AS, Anderson JA, Mututua RS, Warutere JK, Siodi IL, Kim SY, Voyles TN, Robinson JA, Wall JD, Archie EA, Alberts SC, Tung J. Selection against admixture and gene regulatory divergence in a long-term primate field study. Science 2022; 377:635-641. [PMID: 35926022 PMCID: PMC9682493 DOI: 10.1126/science.abm4917] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Genetic admixture is central to primate evolution. We combined 50 years of field observations of immigration and group demography with genomic data from ~9 generations of hybrid baboons to investigate the consequences of admixture in the wild. Despite no obvious fitness costs to hybrids, we found signatures of selection against admixture similar to those described for archaic hominins. These patterns were concentrated near genes where ancestry is strongly associated with gene expression. Our analyses also show that introgression is partially predictable across the genome. This study demonstrates the value of integrating genomic and field data for revealing how "genomic signatures of selection" (e.g., reduced introgression in low-recombination regions) manifest in nature; moreover, it underscores the importance of other primates as living models for human evolution.
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Affiliation(s)
- Tauras P. Vilgalys
- Department of Evolutionary Anthropology, Duke University, Durham, NC, USA,Section of Genetic Medicine, University of Chicago, Chicago, IL, USA
| | - Arielle S. Fogel
- Department of Evolutionary Anthropology, Duke University, Durham, NC, USA,University Program in Genetics and Genomics, Duke University, Durham, NC, USA
| | - Jordan A. Anderson
- Department of Evolutionary Anthropology, Duke University, Durham, NC, USA
| | | | | | | | - Sang Yoon Kim
- Department of Evolutionary Anthropology, Duke University, Durham, NC, USA
| | - Tawni N. Voyles
- Department of Evolutionary Anthropology, Duke University, Durham, NC, USA
| | | | - Jeffrey D. Wall
- Institute for Human Genetics, University of California, San Francisco, CA, USA
| | - Elizabeth A. Archie
- Department of Biological Sciences, University of Notre Dame, Notre Dame, IN, USA
| | - Susan C. Alberts
- Department of Evolutionary Anthropology, Duke University, Durham, NC, USA,Department of Biology, Duke University, Durham, NC, USA,Duke University Population Research Institute, Duke University, Durham, NC, USA
| | - Jenny Tung
- Department of Evolutionary Anthropology, Duke University, Durham, NC, USA,Department of Biology, Duke University, Durham, NC, USA,Duke University Population Research Institute, Duke University, Durham, NC, USA,Canadian Institute for Advanced Research, Toronto, Canada,Department of Primate Behavior and Evolution, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany,Corresponding author
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33
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Brucato N, André M, Hudjashov G, Mondal M, Cox MP, Leavesley M, Ricaut FX. Chronology of natural selection in Oceanian genomes. iScience 2022; 25:104583. [PMID: 35880026 PMCID: PMC9308150 DOI: 10.1016/j.isci.2022.104583] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Revised: 05/11/2022] [Accepted: 06/07/2022] [Indexed: 11/30/2022] Open
Abstract
As human populations left Asia to first settle in Oceania around 50,000 years ago, they entered a territory ecologically separated from the Old World for millions of years. We analyzed genomic data of 239 modern Oceanian individuals to detect and date signals of selection specific to this region. Combining both relative and absolute dating approaches, we identified a strong selection pattern between 52,000 and 54,000 years ago in the genomes of descendants of the first settlers of Sahul. This strikingly corresponds to the dates of initial settlement as inferred from archaeological evidence. Loci under selection during this period, some showing enrichment in Denisovan ancestry, overlap genes involved in the immune response and diet, especially based on plants. Pathogens and natural resources, especially from endemic plants, therefore appear to have acted as strong selective pressures on the genomes of the first settlers of Sahul. 239 human genomes from both sides of the Wallacean ecogeographical barriers Signals of selection are dated between -54,000 to -52,000 in modern Oceanian genomes Genes related to immunity and diet were under strong selection Denisovan introgressions participated to the genetic adaptations present in Oceanians
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Affiliation(s)
- Nicolas Brucato
- Laboratoire Évolution et Diversité Biologique (EDB UMR 5174), Université de Toulouse Midi-Pyrénées, CNRS, IRD, UPS. 118 route de Narbonne, Bat 4R1, 31062 cedex 9 Toulouse, France
| | - Mathilde André
- Laboratoire Évolution et Diversité Biologique (EDB UMR 5174), Université de Toulouse Midi-Pyrénées, CNRS, IRD, UPS. 118 route de Narbonne, Bat 4R1, 31062 cedex 9 Toulouse, France.,Institute of Genomics, University of Tartu, Tartu, 51010 Tartumaa, Estonia
| | - Georgi Hudjashov
- Institute of Genomics, University of Tartu, Tartu, 51010 Tartumaa, Estonia
| | - Mayukh Mondal
- Institute of Genomics, University of Tartu, Tartu, 51010 Tartumaa, Estonia
| | - Murray P Cox
- School of Natural Sciences, Massey University, Palmerston North 4442, New Zealand
| | - Matthew Leavesley
- Strand of Anthropology, Sociology and Archaeology, School of Humanities and Social Sciences, University of Papua New Guinea, PO Box 320, National Capital District 134, Papua New Guinea.,College of Arts, Society and Education, James Cook University, P.O. Box 6811, Cairns, QLD 4870, Australia.,ARC Centre of Excellence for Australian Biodiversity and Heritage, University of Wollongong, Wollongong, NSW 2522, Australia
| | - François-Xavier Ricaut
- Laboratoire Évolution et Diversité Biologique (EDB UMR 5174), Université de Toulouse Midi-Pyrénées, CNRS, IRD, UPS. 118 route de Narbonne, Bat 4R1, 31062 cedex 9 Toulouse, France
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34
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Haeggström S, Ingelman-Sundberg M, Pääbo S, Zeberg H. The clinically relevant CYP2C8*3 and CYP2C9*2 haplotype is inherited from Neandertals. THE PHARMACOGENOMICS JOURNAL 2022; 22:247-249. [PMID: 35780191 PMCID: PMC9363273 DOI: 10.1038/s41397-022-00284-6] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Revised: 05/13/2022] [Accepted: 06/10/2022] [Indexed: 11/23/2022]
Abstract
Genetic variation in genes encoding cytochrome P450 enzymes influences the metabolism of drugs and endogenous compounds. The locus containing the cytochrome genes CYP2C8 and CYP2C9 on chromosome 10 exhibits linkage disequilibrium between the CYP2C8*3 and CYP2C9*2 alleles, forming a haplotype of ~300 kilobases. This haplotype is associated with altered metabolism of several drugs, most notably reduced metabolism of warfarin and phenytoin, leading to toxicity at otherwise therapeutic doses. Here we show that this haplotype is inherited from Neandertals.
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35
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African mitochondrial haplogroup L7: a 100,000-year-old maternal human lineage discovered through reassessment and new sequencing. Sci Rep 2022; 12:10747. [PMID: 35750688 PMCID: PMC9232647 DOI: 10.1038/s41598-022-13856-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Accepted: 05/30/2022] [Indexed: 11/17/2022] Open
Abstract
Archaeological and genomic evidence suggest that modern Homo sapiens have roamed the planet for some 300–500 thousand years. In contrast, global human mitochondrial (mtDNA) diversity coalesces to one African female ancestor (“Mitochondrial Eve”) some 145 thousand years ago, owing to the ¼ gene pool size of our matrilineally inherited haploid genome. Therefore, most of human prehistory was spent in Africa where early ancestors of Southern African Khoisan and Central African rainforest hunter-gatherers (RFHGs) segregated into smaller groups. Their subdivisions followed climatic oscillations, new modes of subsistence, local adaptations, and cultural-linguistic differences, all prior to their exodus out of Africa. Seven African mtDNA haplogroups (L0–L6) traditionally captured this ancient structure—these L haplogroups have formed the backbone of the mtDNA tree for nearly two decades. Here we describe L7, an eighth haplogroup that we estimate to be ~ 100 thousand years old and which has been previously misclassified in the literature. In addition, L7 has a phylogenetic sublineage L7a*, the oldest singleton branch in the human mtDNA tree (~ 80 thousand years). We found that L7 and its sister group L5 are both low-frequency relics centered around East Africa, but in different populations (L7: Sandawe; L5: Mbuti). Although three small subclades of African foragers hint at the population origins of L5'7, the majority of subclades are divided into Afro-Asiatic and eastern Bantu groups, indicative of more recent admixture. A regular re-estimation of the entire mtDNA haplotype tree is needed to ensure correct cladistic placement of new samples in the future.
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36
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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: 3.5] [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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37
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Temporal mapping of derived high-frequency gene variants supports the mosaic nature of the evolution of Homo sapiens. Sci Rep 2022; 12:9937. [PMID: 35705575 PMCID: PMC9200848 DOI: 10.1038/s41598-022-13589-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Accepted: 05/25/2022] [Indexed: 11/25/2022] Open
Abstract
Large-scale estimations of the time of emergence of variants are essential to examine hypotheses concerning human evolution with precision. Using an open repository of genetic variant age estimations, we offer here a temporal evaluation of various evolutionarily relevant datasets, such as Homo sapiens-specific variants, high-frequency variants found in genetic windows under positive selection, introgressed variants from extinct human species, as well as putative regulatory variants specific to various brain regions. We find a recurrent bimodal distribution of high-frequency variants, but also evidence for specific enrichments of gene categories in distinct time windows, pointing to different periods of phenotypic changes, resulting in a mosaic. With a temporal classification of genetic mutations in hand, we then applied a machine learning tool to predict what genes have changed more in certain time windows, and which tissues these genes may have impacted more. Overall, we provide a fine-grained temporal mapping of derived variants in Homo sapiens that helps to illuminate the intricate evolutionary history of our species.
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38
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Zhang R, Yuan K, Xu S. Detecting archaic introgression and modeling multiple-wave admixture with ArchaicSeeker 2.0. STAR Protoc 2022; 3:101314. [PMID: 35496797 PMCID: PMC9038769 DOI: 10.1016/j.xpro.2022.101314] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
Abstract
ArchaicSeeker 2.0 is designed to identify the sequences derived from known or unknown archaic hominins and to further model the multiple-wave gene flows. The main functional modules involve seeking introgressed sequences, determining corresponding ancestries, and reconstructing the admixture history. The protocol below describes the analytic steps for the application of ArchaicSeeker 2.0 into analysis of example data of the Han Chinese population. For complete details on the use and execution of this protocol, please refer to Yuan et al. (2021). ArchaicSeeker 2.0 can identify introgressed sequences from archaic hominins Modeling complex introgression history without massive computer simulation Overcomes the limitations of existing methods in inferring multiple introgression
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39
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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: 2.0] [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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40
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Buisan R, Moriano J, Andirkó A, Boeckx C. A Brain Region-Specific Expression Profile for Genes Within Large Introgression Deserts and Under Positive Selection in Homo sapiens. Front Cell Dev Biol 2022; 10:824740. [PMID: 35557944 PMCID: PMC9086289 DOI: 10.3389/fcell.2022.824740] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Accepted: 04/04/2022] [Indexed: 11/13/2022] Open
Abstract
Analyses of ancient DNA from extinct hominins have provided unique insights into the complex evolutionary history of Homo sapiens, intricately related to that of the Neanderthals and the Denisovans as revealed by several instances of admixture events. These analyses have also allowed the identification of introgression deserts: genomic regions in our species that are depleted of "archaic" haplotypes. The presence of genes like FOXP2 in these deserts has been taken to be suggestive of brain-related functional differences between Homo species. Here, we seek a deeper characterization of these regions and the specific expression trajectories of genes within them, taking into account signals of positive selection in our lineage. Analyzing publicly available transcriptomic data from the human brain at different developmental stages, we found that structures outside the cerebral neocortex, in particular the cerebellum, the striatum and the mediodorsal nucleus of the thalamus show the most divergent transcriptomic profiles when considering genes within large introgression deserts and under positive selection.
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Affiliation(s)
| | - Juan Moriano
- Universitat de Barcelona, Barcelona, Spain
- Universitat de Barcelona Institute of Complex Systems, Barcelona, Spain
| | - Alejandro Andirkó
- Universitat de Barcelona, Barcelona, Spain
- Universitat de Barcelona Institute of Complex Systems, Barcelona, Spain
| | - Cedric Boeckx
- Universitat de Barcelona, Barcelona, Spain
- Universitat de Barcelona Institute of Complex Systems, Barcelona, Spain
- Catalan Institute for Research and Advanced Studies (ICREA), Barcelona, Spain
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41
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Brand CM, Colbran LL, Capra JA. Predicting Archaic Hominin Phenotypes from Genomic Data. Annu Rev Genomics Hum Genet 2022; 23:591-612. [PMID: 35440148 DOI: 10.1146/annurev-genom-111521-121903] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Ancient DNA provides a powerful window into the biology of extant and extinct species, including humans' closest relatives: Denisovans and Neanderthals. Here, we review what is known about archaic hominin phenotypes from genomic data and how those inferences have been made. We contend that understanding the influence of variants on lower-level molecular phenotypes-such as gene expression and protein function-is a promising approach to using ancient DNA to learn about archaic hominin traits. Molecular phenotypes have simpler genetic architectures than organism-level complex phenotypes, and this approach enables moving beyond association studies by proposing hypotheses about the effects of archaic variants that are testable in model systems. The major challenge to understanding archaic hominin phenotypes is broadening our ability to accurately map genotypes to phenotypes, but ongoing advances ensure that there will be much more to learn about archaic hominin phenotypes from their genomes. Expected final online publication date for the Annual Review of Genomics and Human Genetics, Volume 23 is October 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
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Affiliation(s)
- Colin M Brand
- Department of Epidemiology and Biostatistics, University of California, San Francisco, California, USA; , .,Bakar Computational Health Sciences Institute, University of California, San Francisco, California, USA
| | - Laura L Colbran
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - John A Capra
- Department of Epidemiology and Biostatistics, University of California, San Francisco, California, USA; , .,Bakar Computational Health Sciences Institute, University of California, San Francisco, California, USA
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42
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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: 5] [Impact Index Per Article: 2.5] [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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43
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Vallini L, Marciani G, Aneli S, Bortolini E, Benazzi S, Pievani T, Pagani L. Genetics and Material Culture Support Repeated Expansions into Paleolithic Eurasia from a Population Hub Out of Africa. Genome Biol Evol 2022; 14:evac045. [PMID: 35445261 PMCID: PMC9021735 DOI: 10.1093/gbe/evac045] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/21/2022] [Indexed: 11/14/2022] Open
Abstract
The population dynamics that followed the Out of Africa (OoA) expansion and the whereabouts of the early migrants before the differentiation that ultimately led to the formation of Oceanian, West and East Eurasian macropopulations have long been debated. Shedding light on these events may, in turn, provide clues to better understand the cultural evolution in Eurasia between 50 and 35 ka. Here, we analyze Eurasian Paleolithic DNA evidence to provide a comprehensive population model and validate it in light of available material culture. Leveraging on our integrated approach we propose the existence of a Eurasian population Hub, where Homo sapiens lived between the OoA and the broader colonization of Eurasia, which was characterized by multiple events of expansion and local extinction. A major population wave out of Hub, of which Ust'Ishim, Bacho Kiro, and Tianyuan are unadmixed representatives, is broadly associated with Initial Upper Paleolithic lithics and populated West and East Eurasia before or around 45 ka, before getting largely extinct in Europe. In this light, we suggest a parsimonious placement of Oase1 as an individual related to Bacho Kiro who experienced additional Neanderthal introgression. Another expansion, started before 38 ka, is broadly associated with Upper Paleolithic industries and repopulated Europe with sporadic admixtures with the previous wave (GoyetQ116-1) and more systematic ones, whereas moving through Siberia (Yana, Mal'ta). Before these events, we also confirm Zlatý Kůň as the most basal human lineage sequenced to date OoA, potentially representing an earlier wave of expansion out of the Hub.
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Affiliation(s)
| | - Giulia Marciani
- Department of Cultural Heritage, University of Bologna, Ravenna, Italy
- Department of Physical Sciences, Earth and Environment, University of Siena, Italy
| | - Serena Aneli
- Department of Biology, University of Padova, Italy
- Department of Public Health Sciences and Pediatrics, University of Turin, Italy
| | - Eugenio Bortolini
- Department of Cultural Heritage, University of Bologna, Ravenna, Italy
| | - Stefano Benazzi
- Department of Cultural Heritage, University of Bologna, Ravenna, Italy
- Department of Human Evolution, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
| | | | - Luca Pagani
- Department of Biology, University of Padova, Italy
- Institute of Genomics, University of Tartu, Estonia
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44
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Aganezov S, Yan SM, Soto DC, Kirsche M, Zarate S, Avdeyev P, Taylor DJ, Shafin K, Shumate A, Xiao C, Wagner J, McDaniel J, Olson ND, Sauria MEG, Vollger MR, Rhie A, Meredith M, Martin S, Lee J, Koren S, Rosenfeld JA, Paten B, Layer R, Chin CS, Sedlazeck FJ, Hansen NF, Miller DE, Phillippy AM, Miga KH, McCoy RC, Dennis MY, Zook JM, Schatz MC. A complete reference genome improves analysis of human genetic variation. Science 2022; 376:eabl3533. [PMID: 35357935 DOI: 10.1126/science.abl3533] [Citation(s) in RCA: 123] [Impact Index Per Article: 61.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Compared to its predecessors, the Telomere-to-Telomere CHM13 genome adds nearly 200 million base pairs of sequence, corrects thousands of structural errors, and unlocks the most complex regions of the human genome for clinical and functional study. We show how this reference universally improves read mapping and variant calling for 3202 and 17 globally diverse samples sequenced with short and long reads, respectively. We identify hundreds of thousands of variants per sample in previously unresolved regions, showcasing the promise of the T2T-CHM13 reference for evolutionary and biomedical discovery. Simultaneously, this reference eliminates tens of thousands of spurious variants per sample, including reduction of false positives in 269 medically relevant genes by up to a factor of 12. Because of these improvements in variant discovery coupled with population and functional genomic resources, T2T-CHM13 is positioned to replace GRCh38 as the prevailing reference for human genetics.
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Affiliation(s)
- Sergey Aganezov
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | - Stephanie M Yan
- Department of Biology, Johns Hopkins University, Baltimore, MD, USA
| | - Daniela C Soto
- Department of Biochemistry and Molecular Medicine, Genome Center, MIND Institute, University of California, Davis, CA, USA
| | - Melanie Kirsche
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | - Samantha Zarate
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | - Pavel Avdeyev
- Genome Informatics Section, National Human Genome Research Institute, Bethesda, MD, USA
| | - Dylan J Taylor
- Department of Biology, Johns Hopkins University, Baltimore, MD, USA
| | - Kishwar Shafin
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, CA, USA
| | - Alaina Shumate
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Chunlin Xiao
- National Center for Biotechnology Information, National Library of Medicine, Bethesda, MD, USA
| | - Justin Wagner
- National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Jennifer McDaniel
- National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Nathan D Olson
- National Institute of Standards and Technology, Gaithersburg, MD, USA
| | | | - Mitchell R Vollger
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Arang Rhie
- Genome Informatics Section, National Human Genome Research Institute, Bethesda, MD, USA
| | - Melissa Meredith
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, CA, USA
| | - Skylar Martin
- Department of Computer Science and Biofrontiers Institute, University of Colorado, Boulder, CO, USA
| | - Joyce Lee
- Bionano Genomics, San Diego, CA, USA
| | - Sergey Koren
- Genome Informatics Section, National Human Genome Research Institute, Bethesda, MD, USA
| | | | - Benedict Paten
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, CA, USA
| | - Ryan Layer
- Department of Computer Science and Biofrontiers Institute, University of Colorado, Boulder, CO, USA
| | | | - Fritz J Sedlazeck
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Nancy F Hansen
- Comparative Genomics Analysis Unit, National Human Genome Research Institute, Rockville, MD, USA
| | - Danny E Miller
- Department of Genome Sciences, University of Washington, Seattle, WA, USA.,Department of Pediatrics, Division of Genetic Medicine, University of Washington and Seattle Children's Hospital, Seattle, WA, USA
| | - Adam M Phillippy
- Genome Informatics Section, National Human Genome Research Institute, Bethesda, MD, USA
| | - Karen H Miga
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, CA, USA
| | - Rajiv C McCoy
- Department of Biology, Johns Hopkins University, Baltimore, MD, USA
| | - Megan Y Dennis
- Department of Biochemistry and Molecular Medicine, Genome Center, MIND Institute, University of California, Davis, CA, USA
| | - Justin M Zook
- National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Michael C Schatz
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA.,Department of Biology, Johns Hopkins University, Baltimore, MD, USA.,Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
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45
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Nurk S, Koren S, Rhie A, Rautiainen M, Bzikadze AV, Mikheenko A, Vollger MR, Altemose N, Uralsky L, Gershman A, Aganezov S, Hoyt SJ, Diekhans M, Logsdon GA, Alonge M, Antonarakis SE, Borchers M, Bouffard GG, Brooks SY, Caldas GV, Chen NC, Cheng H, Chin CS, Chow W, de Lima LG, Dishuck PC, Durbin R, Dvorkina T, Fiddes IT, Formenti G, Fulton RS, Fungtammasan A, Garrison E, Grady PG, Graves-Lindsay TA, Hall IM, Hansen NF, Hartley GA, Haukness M, Howe K, Hunkapiller MW, Jain C, Jain M, Jarvis ED, Kerpedjiev P, Kirsche M, Kolmogorov M, Korlach J, Kremitzki M, Li H, Maduro VV, Marschall T, McCartney AM, McDaniel J, Miller DE, Mullikin JC, Myers EW, Olson ND, Paten B, Peluso P, Pevzner PA, Porubsky D, Potapova T, Rogaev EI, Rosenfeld JA, Salzberg SL, Schneider VA, Sedlazeck FJ, Shafin K, Shew CJ, Shumate A, Sims Y, Smit AFA, Soto DC, Sović I, Storer JM, Streets A, Sullivan BA, Thibaud-Nissen F, Torrance J, Wagner J, Walenz BP, Wenger A, Wood JMD, Xiao C, Yan SM, Young AC, Zarate S, Surti U, McCoy RC, Dennis MY, Alexandrov IA, Gerton JL, O’Neill RJ, Timp W, Zook JM, Schatz MC, Eichler EE, Miga KH, Phillippy AM. The complete sequence of a human genome. Science 2022; 376:44-53. [PMID: 35357919 PMCID: PMC9186530 DOI: 10.1126/science.abj6987] [Citation(s) in RCA: 1078] [Impact Index Per Article: 539.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Since its initial release in 2000, the human reference genome has covered only the euchromatic fraction of the genome, leaving important heterochromatic regions unfinished. Addressing the remaining 8% of the genome, the Telomere-to-Telomere (T2T) Consortium presents a complete 3.055 billion-base pair sequence of a human genome, T2T-CHM13, that includes gapless assemblies for all chromosomes except Y, corrects errors in the prior references, and introduces nearly 200 million base pairs of sequence containing 1956 gene predictions, 99 of which are predicted to be protein coding. The completed regions include all centromeric satellite arrays, recent segmental duplications, and the short arms of all five acrocentric chromosomes, unlocking these complex regions of the genome to variational and functional studies.
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Affiliation(s)
- Sergey Nurk
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD USA
| | - Sergey Koren
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD USA
| | - Arang Rhie
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD USA
| | - Mikko Rautiainen
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD USA
| | - Andrey V. Bzikadze
- Graduate Program in Bioinformatics and Systems Biology, University of California, San Diego; La Jolla, CA, USA
| | - Alla Mikheenko
- Center for Algorithmic Biotechnology, Institute of Translational Biomedicine, Saint Petersburg State University; Saint Petersburg, Russia
| | - Mitchell R. Vollger
- Department of Genome Sciences, University of Washington School of Medicine; Seattle, WA, USA
| | - Nicolas Altemose
- Department of Bioengineering, University of California, Berkeley; Berkeley, CA, USA
| | - Lev Uralsky
- Sirius University of Science and Technology; Sochi, Russia
- Vavilov Institute of General Genetics; Moscow, Russia
| | - Ariel Gershman
- Department of Molecular Biology and Genetics, Johns Hopkins University; Baltimore, MD, USA
| | - Sergey Aganezov
- Department of Computer Science, Johns Hopkins University; Baltimore, MD, USA
| | - Savannah J. Hoyt
- Institute for Systems Genomics and Department of Molecular and Cell Biology, University of Connecticut; Storrs, CT, USA
| | - Mark Diekhans
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz; Santa Cruz, CA, USA
| | - Glennis A. Logsdon
- Department of Genome Sciences, University of Washington School of Medicine; Seattle, WA, USA
| | - Michael Alonge
- Department of Computer Science, Johns Hopkins University; Baltimore, MD, USA
| | | | | | - Gerard G. Bouffard
- NIH Intramural Sequencing Center, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD, USA
| | - Shelise Y. Brooks
- NIH Intramural Sequencing Center, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD, USA
| | - Gina V. Caldas
- Department of Molecular and Cell Biology, University of California, Berkeley; Berkeley, CA, USA
| | - Nae-Chyun Chen
- Department of Computer Science, Johns Hopkins University; Baltimore, MD, USA
| | - Haoyu Cheng
- Department of Data Sciences, Dana-Farber Cancer Institute; Boston, MA
- Department of Biomedical Informatics, Harvard Medical School; Boston, MA
| | | | | | | | - Philip C. Dishuck
- Department of Genome Sciences, University of Washington School of Medicine; Seattle, WA, USA
| | - Richard Durbin
- Wellcome Sanger Institute; Cambridge, UK
- Department of Genetics, University of Cambridge; Cambridge, UK
| | - Tatiana Dvorkina
- Center for Algorithmic Biotechnology, Institute of Translational Biomedicine, Saint Petersburg State University; Saint Petersburg, Russia
| | | | - Giulio Formenti
- Laboratory of Neurogenetics of Language and The Vertebrate Genome Lab, The Rockefeller University; New York, NY, USA
- Howard Hughes Medical Institute; Chevy Chase, MD, USA
| | - Robert S. Fulton
- Department of Genetics, Washington University School of Medicine; St. Louis, MO, USA
| | | | - Erik Garrison
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz; Santa Cruz, CA, USA
- University of Tennessee Health Science Center; Memphis, TN, USA
| | - Patrick G.S. Grady
- Institute for Systems Genomics and Department of Molecular and Cell Biology, University of Connecticut; Storrs, CT, USA
| | | | - Ira M. Hall
- Department of Genetics, Yale University School of Medicine; New Haven, CT, USA
| | - Nancy F. Hansen
- Comparative Genomics Analysis Unit, Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD, USA
| | - Gabrielle A. Hartley
- Institute for Systems Genomics and Department of Molecular and Cell Biology, University of Connecticut; Storrs, CT, USA
| | - Marina Haukness
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz; Santa Cruz, CA, USA
| | | | | | - Chirag Jain
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD USA
- Department of Computational and Data Sciences, Indian Institute of Science; Bangalore KA, India
| | - Miten Jain
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz; Santa Cruz, CA, USA
| | - Erich D. Jarvis
- Laboratory of Neurogenetics of Language and The Vertebrate Genome Lab, The Rockefeller University; New York, NY, USA
- Howard Hughes Medical Institute; Chevy Chase, MD, USA
| | | | - Melanie Kirsche
- Department of Computer Science, Johns Hopkins University; Baltimore, MD, USA
| | - Mikhail Kolmogorov
- Department of Computer Science and Engineering, University of California, San Diego; San Diego, CA, USA
| | | | - Milinn Kremitzki
- McDonnell Genome Institute, Washington University in St. Louis; St. Louis, MO, USA
| | - Heng Li
- Department of Data Sciences, Dana-Farber Cancer Institute; Boston, MA
- Department of Biomedical Informatics, Harvard Medical School; Boston, MA
| | - Valerie V. Maduro
- Undiagnosed Diseases Program, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD, USA
| | - Tobias Marschall
- Heinrich Heine University Düsseldorf, Medical Faculty, Institute for Medical Biometry and Bioinformatics; Düsseldorf, Germany
| | - Ann M. McCartney
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD USA
| | - Jennifer McDaniel
- Biosystems and Biomaterials Division, National Institute of Standards and Technology; Gaithersburg, MD, USA
| | - Danny E. Miller
- Department of Genome Sciences, University of Washington School of Medicine; Seattle, WA, USA
- Department of Pediatrics, Division of Genetic Medicine, University of Washington and Seattle Children’s Hospital; Seattle, WA, USA
| | - James C. Mullikin
- NIH Intramural Sequencing Center, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD, USA
- Comparative Genomics Analysis Unit, Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD, USA
| | - Eugene W. Myers
- Max-Planck Institute of Molecular Cell Biology and Genetics; Dresden, Germany
| | - Nathan D. Olson
- Biosystems and Biomaterials Division, National Institute of Standards and Technology; Gaithersburg, MD, USA
| | - Benedict Paten
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz; Santa Cruz, CA, USA
| | | | - Pavel A. Pevzner
- Department of Computer Science and Engineering, University of California, San Diego; San Diego, CA, USA
| | - David Porubsky
- Department of Genome Sciences, University of Washington School of Medicine; Seattle, WA, USA
| | - Tamara Potapova
- Stowers Institute for Medical Research; Kansas City, MO, USA
| | - Evgeny I. Rogaev
- Sirius University of Science and Technology; Sochi, Russia
- Vavilov Institute of General Genetics; Moscow, Russia
- Department of Psychiatry, University of Massachusetts Medical School; Worcester, MA, USA
- Faculty of Biology, Lomonosov Moscow State University; Moscow, Russia
| | | | - Steven L. Salzberg
- Department of Computer Science, Johns Hopkins University; Baltimore, MD, USA
- Department of Biomedical Engineering, Johns Hopkins University; Baltimore, MD, USA
| | - Valerie A. Schneider
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health; Bethesda, MD, USA
| | - Fritz J. Sedlazeck
- Human Genome Sequencing Center, Baylor College of Medicine; Houston TX, USA
| | - Kishwar Shafin
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz; Santa Cruz, CA, USA
| | - Colin J. Shew
- Genome Center, MIND Institute, Department of Biochemistry and Molecular Medicine, University of California, Davis; CA, USA
| | - Alaina Shumate
- Department of Biomedical Engineering, Johns Hopkins University; Baltimore, MD, USA
| | - Ying Sims
- Wellcome Sanger Institute; Cambridge, UK
| | | | - Daniela C. Soto
- Genome Center, MIND Institute, Department of Biochemistry and Molecular Medicine, University of California, Davis; CA, USA
| | - Ivan Sović
- Pacific Biosciences; Menlo Park, CA, USA
- Digital BioLogic d.o.o.; Ivanić-Grad, Croatia
| | | | - Aaron Streets
- Department of Bioengineering, University of California, Berkeley; Berkeley, CA, USA
- Chan Zuckerberg Biohub; San Francisco, CA, USA
| | - Beth A. Sullivan
- Department of Molecular Genetics and Microbiology, Duke University School of Medicine; Durham, NC, USA
| | - Françoise Thibaud-Nissen
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health; Bethesda, MD, USA
| | | | - Justin Wagner
- Biosystems and Biomaterials Division, National Institute of Standards and Technology; Gaithersburg, MD, USA
| | - Brian P. Walenz
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD USA
| | | | | | - Chunlin Xiao
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health; Bethesda, MD, USA
| | - Stephanie M. Yan
- Department of Biology, Johns Hopkins University; Baltimore, MD, USA
| | - Alice C. Young
- NIH Intramural Sequencing Center, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD, USA
| | - Samantha Zarate
- Department of Computer Science, Johns Hopkins University; Baltimore, MD, USA
| | - Urvashi Surti
- Department of Pathology, University of Pittsburgh; Pittsburgh, PA, USA
| | - Rajiv C. McCoy
- Department of Biology, Johns Hopkins University; Baltimore, MD, USA
| | - Megan Y. Dennis
- Genome Center, MIND Institute, Department of Biochemistry and Molecular Medicine, University of California, Davis; CA, USA
| | - Ivan A. Alexandrov
- Center for Algorithmic Biotechnology, Institute of Translational Biomedicine, Saint Petersburg State University; Saint Petersburg, Russia
- Vavilov Institute of General Genetics; Moscow, Russia
- Research Center of Biotechnology of the Russian Academy of Sciences; Moscow, Russia
| | - Jennifer L. Gerton
- Stowers Institute for Medical Research; Kansas City, MO, USA
- Department of Biochemistry and Molecular Biology, University of Kansas Medical School; Kansas City, MO, USA
| | - Rachel J. O’Neill
- Institute for Systems Genomics and Department of Molecular and Cell Biology, University of Connecticut; Storrs, CT, USA
| | - Winston Timp
- Department of Molecular Biology and Genetics, Johns Hopkins University; Baltimore, MD, USA
- Department of Biomedical Engineering, Johns Hopkins University; Baltimore, MD, USA
| | - Justin M. Zook
- Biosystems and Biomaterials Division, National Institute of Standards and Technology; Gaithersburg, MD, USA
| | - Michael C. Schatz
- Department of Computer Science, Johns Hopkins University; Baltimore, MD, USA
- Department of Biology, Johns Hopkins University; Baltimore, MD, USA
| | - Evan E. Eichler
- Department of Genome Sciences, University of Washington School of Medicine; Seattle, WA, USA
- Howard Hughes Medical Institute; Chevy Chase, MD, USA
| | - Karen H. Miga
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz; Santa Cruz, CA, USA
- Department of Biomolecular Engineering, University of California Santa Cruz, CA, USA
| | - Adam M. Phillippy
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD USA
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46
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Weasel L. How Neanderthals became White: The introgression of race into contemporary human evolutionary genomics. Am Nat 2022; 200:129-139. [DOI: 10.1086/720130] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
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47
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Wohns AW, Wong Y, Jeffery B, Akbari A, Mallick S, Pinhasi R, Patterson N, Reich D, Kelleher J, McVean G. A unified genealogy of modern and ancient genomes. Science 2022; 375:eabi8264. [PMID: 35201891 PMCID: PMC10027547 DOI: 10.1126/science.abi8264] [Citation(s) in RCA: 40] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
The sequencing of modern and ancient genomes from around the world has revolutionized our understanding of human history and evolution. However, the problem of how best to characterize ancestral relationships from the totality of human genomic variation remains unsolved. Here, we address this challenge with nonparametric methods that enable us to infer a unified genealogy of modern and ancient humans. This compact representation of multiple datasets explores the challenges of missing and erroneous data and uses ancient samples to constrain and date relationships. We demonstrate the power of the method to recover relationships between individuals and populations as well as to identify descendants of ancient samples. Finally, we introduce a simple nonparametric estimator of the geographical location of ancestors that recapitulates key events in human history.
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Affiliation(s)
- Anthony Wilder Wohns
- Broad Institute of MIT and Harvard; Cambridge, MA 02142, USA
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford; Oxford OX3 7LF, UK
| | - Yan Wong
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford; Oxford OX3 7LF, UK
| | - Ben Jeffery
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford; Oxford OX3 7LF, UK
| | - Ali Akbari
- Broad Institute of MIT and Harvard; Cambridge, MA 02142, USA
- Department of Human Evolutionary Biology, Harvard University; Cambridge, MA 02138, USA
- Department of Genetics, Harvard Medical School; Boston, MA 02115, USA
| | - Swapan Mallick
- Broad Institute of MIT and Harvard; Cambridge, MA 02142, USA
- Howard Hughes Medical Institute; Boston, MA 02115, USA
| | - Ron Pinhasi
- Department of Evolutionary Anthropology, University of Vienna; 1090 Vienna, Austria
| | - Nick Patterson
- Broad Institute of MIT and Harvard; Cambridge, MA 02142, USA
- Department of Human Evolutionary Biology, Harvard University; Cambridge, MA 02138, USA
- Howard Hughes Medical Institute; Boston, MA 02115, USA
- Department of Genetics, Harvard Medical School; Boston, MA 02115, USA
| | - David Reich
- Broad Institute of MIT and Harvard; Cambridge, MA 02142, USA
- Department of Human Evolutionary Biology, Harvard University; Cambridge, MA 02138, USA
- Howard Hughes Medical Institute; Boston, MA 02115, USA
- Department of Genetics, Harvard Medical School; Boston, MA 02115, USA
| | - Jerome Kelleher
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford; Oxford OX3 7LF, UK
| | - Gil McVean
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford; Oxford OX3 7LF, UK
- Corresponding author.
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48
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Huffman JE, Butler-Laporte G, Khan A, Pairo-Castineira E, Drivas TG, Peloso GM, Nakanishi T, Ganna A, Verma A, Baillie JK, Kiryluk K, Richards JB, Zeberg H. Multi-ancestry fine mapping implicates OAS1 splicing in risk of severe COVID-19. Nat Genet 2022; 54:125-127. [PMID: 35027740 PMCID: PMC8837537 DOI: 10.1038/s41588-021-00996-8] [Citation(s) in RCA: 62] [Impact Index Per Article: 31.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2021] [Accepted: 11/29/2021] [Indexed: 01/18/2023]
Abstract
The OAS1/2/3 cluster has been identified as a risk locus for severe COVID-19 among individuals of European ancestry, with a protective haplotype of approximately 75 kilobases (kb) derived from Neanderthals in the chromosomal region 12q24.13. This haplotype contains a splice variant of OAS1, which occurs in people of African ancestry independently of gene flow from Neanderthals. Using trans-ancestry fine-mapping approaches in 20,779 hospitalized cases, we demonstrate that this splice variant is likely to be the SNP responsible for the association at this locus, thus strongly implicating OAS1 as an effector gene influencing COVID-19 severity.
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Affiliation(s)
- Jennifer E Huffman
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston, MA, USA
| | - Guillaume Butler-Laporte
- Departments of Medicine, Human Genetics, Epidemiology, Biostatistics and Occupational Health, McGill University, Lady Davis Institute, Jewish General Hospital, Montréal, Québec, Canada
| | - Atlas Khan
- Division of Nephrology, Department of Medicine, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY, USA
| | - Erola Pairo-Castineira
- Roslin Institute, University of Edinburgh, Edinburgh, UK
- Medical Research Council Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | - Theodore G Drivas
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania,, Philadelphia, PA, USA
- Division of Human Genetics, Department of Pediatrics, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Division of Translational Medicine and Human Genetics, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Gina M Peloso
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Tomoko Nakanishi
- Department of Human Genetics, McGill University, Montréal, Québec, Canada
- Lady Davis Institute, Jewish General Hospital, McGill University, Montréal, Québec, Canada
- Kyoto-McGill International Collaborative School in Genomic Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
- Japan Society for the Promotion of Science, Tokyo, Japan
| | - Andrea Ganna
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Anurag Verma
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania,, Philadelphia, PA, USA
- Division of Translational Medicine and Human Genetics, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Corporal Michael Crescenz VA Medical Center, Philadelphia, PA, USA
| | - J Kenneth Baillie
- Roslin Institute, University of Edinburgh, Edinburgh, UK
- Medical Research Council Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | - Krzysztof Kiryluk
- Division of Nephrology, Department of Medicine, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY, USA
- Institute for Genomic Medicine, Columbia University, New York, NY, USA
| | - J Brent Richards
- Departments of Medicine, Human Genetics, Epidemiology, Biostatistics and Occupational Health, McGill University, Lady Davis Institute, Jewish General Hospital, Montréal, Québec, Canada
- Department of Twin Research, King's College London, London, UK
| | - Hugo Zeberg
- Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany.
- Department of Neuroscience, Karolinska Institutet, Stockholm, Sweden.
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49
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Zhang C, Hansen MEB, Tishkoff SA. Advances in integrative African genomics. Trends Genet 2022; 38:152-168. [PMID: 34740451 PMCID: PMC8752515 DOI: 10.1016/j.tig.2021.09.013] [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: 07/16/2021] [Revised: 09/16/2021] [Accepted: 09/28/2021] [Indexed: 12/16/2022]
Abstract
There has been a rapid increase in human genome sequencing in the past two decades, resulting in the identification of millions of previously unknown genetic variants. However, African populations are under-represented in sequencing efforts. Additional sequencing from diverse African populations and the construction of African-specific reference genomes is needed to better characterize the full spectrum of variation in humans. However, sequencing alone is insufficient to address the molecular and cellular mechanisms underlying variable phenotypes and disease risks. Determining functional consequences of genetic variation using multi-omics approaches is a fundamental post-genomic challenge. We discuss approaches to close the knowledge gaps about African genomic diversity and review advances in African integrative genomic studies and their implications for precision medicine.
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Affiliation(s)
- Chao Zhang
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Matthew E B Hansen
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Sarah A Tishkoff
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA.
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50
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Hayakawa T, Terahara M, Fujito NT, Matsunaga T, Teshima KM, Hane M, Kitajima K, Sato C, Takahata N, Satta Y. Lower promoter activity of the ST8SIA2 gene has been favored in evolving human collective brains. PLoS One 2021; 16:e0259897. [PMID: 34914745 PMCID: PMC8675693 DOI: 10.1371/journal.pone.0259897] [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: 05/24/2021] [Accepted: 10/28/2021] [Indexed: 11/18/2022] Open
Abstract
ST8SIA2 is an important molecule regulating expression of the phenotype involved in schizophrenia. Lowered promoter activity of the ST8SIA2 gene is considered to be protective against schizophrenia by conferring tolerance to psychosocial stress. Here, we examined the promoter-type composition of anatomically modern humans (AMHs) and archaic humans (AHs; Neanderthals and Denisovans), and compared the promoter activity at the population level (population promoter activity; PPA) between them. In AMHs, the TCT-type, showing the second lowest promoter activity, was most prevalent in the ancestral population of non-Africans. However, the detection of only the CGT-type from AH samples and recombination tracts in AH sequences showed that the CGT- and TGT-types, exhibiting the two highest promoter activities, were common in AH populations. Furthermore, interspecies gene flow occurred into AMHs from AHs and into Denisovans from Neanderthals, influencing promoter-type compositions independently in both AMHs and AHs. The difference of promoter-type composition makes PPA unique in each population. East and Southeast Asian populations show the lowest PPA. This results from the selective increase of the CGC-type, showing the lowest promoter activity, in these populations. Every non-African population shows significantly lower PPA than African populations, resulting from the TCT-type having the highest prevalence in the ancestral population of non-Africans. In addition, PPA reduction is also found among subpopulations within Africa via a slight increase of the TCT-type. These findings indicate a trend toward lower PPA in the spread of AMHs, interpreted as a continuous adaptation to psychosocial stress arising in migration. This trend is considered as genetic tuning for the evolution of collective brains. The inferred promoter-type composition of AHs differed markedly from that of AMHs, resulting in higher PPA in AHs than in AMHs. This suggests that the trend toward lower PPA is a unique feature in AMH spread.
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Affiliation(s)
- Toshiyuki Hayakawa
- Graduate School of Systems Life Sciences, Kyushu University, Fukuoka, Japan
- Faculty of Arts and Science, Kyushu University, Fukuoka, Japan
- * E-mail:
| | - Masahiro Terahara
- Graduate School of Systems Life Sciences, Kyushu University, Fukuoka, Japan
| | - Naoko T. Fujito
- School of Advanced Sciences, SOKENDAI (The Graduate University for Advanced Studies), Hayama, Kanagawa, Japan
| | - Takumi Matsunaga
- Graduate School of Systems Life Sciences, Kyushu University, Fukuoka, Japan
| | | | - Masaya Hane
- Bioscience and Biotechnology Center, Nagoya University, Nagoya, Aichi, Japan
| | - Ken Kitajima
- Institute for Glyco-core Research (iGCORE), Nagoya University, Nagoya, Aichi, Japan
| | - Chihiro Sato
- Institute for Glyco-core Research (iGCORE), Nagoya University, Nagoya, Aichi, Japan
| | - Naoyuki Takahata
- School of Advanced Sciences, SOKENDAI (The Graduate University for Advanced Studies), Hayama, Kanagawa, Japan
| | - Yoko Satta
- School of Advanced Sciences, SOKENDAI (The Graduate University for Advanced Studies), Hayama, Kanagawa, Japan
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