1
|
Guran SH, Yousefi M, Kafash A, Ghasidian E. Reconstructing contact and a potential interbreeding geographical zone between Neanderthals and anatomically modern humans. Sci Rep 2024; 14:20475. [PMID: 39227643 PMCID: PMC11372063 DOI: 10.1038/s41598-024-70206-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: 04/20/2024] [Accepted: 08/13/2024] [Indexed: 09/05/2024] Open
Abstract
While the interbreeding of Homo neanderthalensis (hereafter Neanderthal) and Anatomically modern human (AMH) has been proven, owing to the shortage of fossils and absence of appropriate DNA, the timing and geography of their interbreeding are not clearly known. In this study, we applied ecological niche modelling (maximum entropy approach) and GIS to reconstruct the palaeodistribution of Neanderthals and AMHs in Southwest Asia and Southeast Europe and identify their contact and potential interbreeding zone during marine isotope stage 5 (MIS 5), when the second wave of interbreeding occurred. We used climatic variables characterizing the environmental conditions of MIS 5 ca. 120 to 80 kyr (averaged value) along with the topography and coordinates of Neanderthal and modern human archaeological sites to characterize the palaeodistribution of each species. Overlapping the models revealed that the Zagros Mountains were a contact and potential interbreeding zone for the two human species. We believe that the Zagros Mountains acted as a corridor connecting the Palearctic/Afrotropical realms, facilitating northwards dispersal of AMHs and southwards dispersal of Neanderthals during MIS 5. Our analyses are comparable with archaeological and genetic evidence collected during recent decades.
Collapse
Affiliation(s)
- Saman H Guran
- Institute for Prehistoric Archaeology, University of Cologne, Cologne, Germany.
- DiyarMehr Institute for Palaeolithic Research, Kermanshah, Iran.
| | - Masoud Yousefi
- Stiftung Neanderthal Museum, Mettmann, Germany
- Department of Biology, Hakim Sabzevari University, Sabzevar, Iran
| | - Anooshe Kafash
- School of Culture and Society, Department of Archaeology and Heritage Studies, Aarhus University, Aarhus, Denmark
| | - Elham Ghasidian
- DiyarMehr Institute for Palaeolithic Research, Kermanshah, Iran
- Stiftung Neanderthal Museum, Mettmann, Germany
| |
Collapse
|
2
|
Langdon QK, Groh JS, Aguillon SM, Powell DL, Gunn T, Payne C, Baczenas JJ, Donny A, Dodge TO, Du K, Schartl M, Ríos-Cárdenas O, Gutiérrez-Rodríguez C, Morris M, Schumer M. Swordtail fish hybrids reveal that genome evolution is surprisingly predictable after initial hybridization. PLoS Biol 2024; 22:e3002742. [PMID: 39186811 PMCID: PMC11379403 DOI: 10.1371/journal.pbio.3002742] [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: 12/30/2023] [Revised: 09/06/2024] [Accepted: 07/09/2024] [Indexed: 08/28/2024] Open
Abstract
Over the past 2 decades, biologists have come to appreciate that hybridization, or genetic exchange between distinct lineages, is remarkably common-not just in particular lineages but in taxonomic groups across the tree of life. As a result, the genomes of many modern species harbor regions inherited from related species. This observation has raised fundamental questions about the degree to which the genomic outcomes of hybridization are repeatable and the degree to which natural selection drives such repeatability. However, a lack of appropriate systems to answer these questions has limited empirical progress in this area. Here, we leverage independently formed hybrid populations between the swordtail fish Xiphophorus birchmanni and X. cortezi to address this fundamental question. We find that local ancestry in one hybrid population is remarkably predictive of local ancestry in another, demographically independent hybrid population. Applying newly developed methods, we can attribute much of this repeatability to strong selection in the earliest generations after initial hybridization. We complement these analyses with time-series data that demonstrates that ancestry at regions under selection has remained stable over the past approximately 40 generations of evolution. Finally, we compare our results to the well-studied X. birchmanni × X. malinche hybrid populations and conclude that deeper evolutionary divergence has resulted in stronger selection and higher repeatability in patterns of local ancestry in hybrids between X. birchmanni and X. cortezi.
Collapse
Affiliation(s)
- Quinn K. Langdon
- Department of Biology, Stanford University, Stanford, California, United States of America
- Centro de Investigaciones Científicas de las Huastecas “Aguazarca”, A.C., Calnali, Hidalgo, Mexico
| | - Jeffrey S. Groh
- Center for Population Biology and Department of Evolution and Ecology, University of California, Davis, Davis, California, United States of America
| | - Stepfanie M. Aguillon
- Department of Biology, Stanford University, Stanford, California, United States of America
- Centro de Investigaciones Científicas de las Huastecas “Aguazarca”, A.C., Calnali, Hidalgo, Mexico
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, Los Angeles, United States of America
| | - Daniel L. Powell
- Department of Biology, Stanford University, Stanford, California, United States of America
- Centro de Investigaciones Científicas de las Huastecas “Aguazarca”, A.C., Calnali, Hidalgo, Mexico
- Department of Biological Sciences, Louisiana State University, Baton Rouge, Louisiana, United States of America
| | - Theresa Gunn
- Department of Biology, Stanford University, Stanford, California, United States of America
- Centro de Investigaciones Científicas de las Huastecas “Aguazarca”, A.C., Calnali, Hidalgo, Mexico
| | - Cheyenne Payne
- Department of Biology, Stanford University, Stanford, California, United States of America
- Centro de Investigaciones Científicas de las Huastecas “Aguazarca”, A.C., Calnali, Hidalgo, Mexico
| | - John J. Baczenas
- Department of Biology, Stanford University, Stanford, California, United States of America
| | - Alex Donny
- Department of Biology, Stanford University, Stanford, California, United States of America
- Centro de Investigaciones Científicas de las Huastecas “Aguazarca”, A.C., Calnali, Hidalgo, Mexico
| | - Tristram O. Dodge
- Department of Biology, Stanford University, Stanford, California, United States of America
- Centro de Investigaciones Científicas de las Huastecas “Aguazarca”, A.C., Calnali, Hidalgo, Mexico
| | - Kang Du
- Xiphophorus Genetic Stock Center, Texas State University San Marcos, San Marcos, United States of America
| | - Manfred Schartl
- Xiphophorus Genetic Stock Center, Texas State University San Marcos, San Marcos, United States of America
- Developmental Biochemistry, Biocenter, University of Würzburg, Würzburg, Germany
| | - Oscar Ríos-Cárdenas
- Red de Biología Evolutiva, Instituto de Ecología, A.C., Xalapa, Veracruz, Mexico
| | | | - Molly Morris
- Department of Biological Sciences, Ohio University, Athens, Ohio, United States of America
| | - Molly Schumer
- Department of Biology, Stanford University, Stanford, California, United States of America
- Centro de Investigaciones Científicas de las Huastecas “Aguazarca”, A.C., Calnali, Hidalgo, Mexico
- Freeman Hrabowski Fellow, Howard Hughes Medical Institute, Stanford, California, United States of America
| |
Collapse
|
3
|
Ma X, Lu Y, Xu S. Adaptive Evolution of Two Distinct Adaptive Haplotypes of Neanderthal Origin at the Immunoglobulin Heavy-chain Locus in East Asian and European Populations. Mol Biol Evol 2024; 41:msae147. [PMID: 39011558 DOI: 10.1093/molbev/msae147] [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: 11/21/2023] [Revised: 07/05/2024] [Accepted: 07/11/2024] [Indexed: 07/17/2024] Open
Abstract
Immunoglobulins (Igs) have a crucial role in humoral immunity. Two recent studies have reported a high-frequency Neanderthal-introgressed haplotype throughout Eurasia and a high-frequency Neanderthal-introgressed haplotype specific to southern East Asia at the immunoglobulin heavy-chain (IGH) gene locus on chromosome 14q32.33. Surprisingly, we found the previously reported high-frequency Neanderthal-introgressed haplotype does not exist throughout Eurasia. Instead, our study identified two distinct high-frequency haplotypes of putative Neanderthal origin in East Asia and Europe, although they shared introgressed alleles. Notably, the alleles of putative Neanderthal origin reduced the expression of IGHG1 and increased the expression of IGHG2 and IGHG3 in various tissues. These putatively introgressed alleles also affected the production of IgG1 upon antigen stimulation and increased the risk of systemic lupus erythematosus. Additionally, the greatest genetic differentiation across the whole genome between southern and northern East Asians was observed for the East Asian haplotype of putative Neanderthal origin. The frequency decreased from southern to northern East Asia and correlated positively with the genome-wide proportion of southern East Asian ancestry, indicating that this putative positive selection likely occurred in the common ancestor of southern East Asian populations before the admixture with northern East Asian populations.
Collapse
Affiliation(s)
- Xixian Ma
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
- Institute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen 518055, China
| | - Yan Lu
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, School of Life Sciences, Department of Liver Surgery and Transplantation Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China
- Ministry of Education Key Laboratory of Contemporary Anthropology, Fudan University, Shanghai China
| | - Shuhua Xu
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, School of Life Sciences, Department of Liver Surgery and Transplantation Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China
| |
Collapse
|
4
|
Chen S, Tang D, Deng L, Xu S. Asian-European differentiation of schizophrenia-associated genes driven by admixture and natural selection. iScience 2024; 27:109560. [PMID: 38638564 PMCID: PMC11024917 DOI: 10.1016/j.isci.2024.109560] [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: 08/22/2023] [Revised: 12/29/2023] [Accepted: 03/22/2024] [Indexed: 04/20/2024] Open
Abstract
The European-centered genome-wide association studies of schizophrenia (SCZ) may not be well applied to non-European populations. We analyzed 1,592 reported SCZ-associated genes using the public genome data and found an overall higher Asian-European differentiation on the SCZ-associated variants than at the genome-wide level. Notable examples included 15 missense variants, a regulatory variant SLC5A10-rs1624825, and a damaging variant TSPAN18-rs1001292. Independent local adaptations in recent 25,000 years, after the Asian-European divergence, could have contributed to such genetic differentiation, as were identified at a missense mutation LTN1-rs57646126-A in Asians, and a non-risk allele ZSWIM6-rs72761442-G in Europeans. Altai-Neanderthal-derived alleles may have opposite effects on SCZ susceptibility between ancestries. Furthermore, adaptive introgression was detected on the non-risk haplotype at 1q21.2 in Europeans, while in Asians it was observed on the SCZ risk haplotype at 3p21.31 which is also potentially ultra-violet protective. This study emphasizes the importance of including more representative Asian samples in future SCZ studies.
Collapse
Affiliation(s)
- Sihan Chen
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, School of Life Sciences, Department of Liver Surgery and Transplantation Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Die Tang
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, School of Life Sciences, Department of Liver Surgery and Transplantation Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Lian Deng
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, School of Life Sciences, Department of Liver Surgery and Transplantation Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai 200032, China
- Ministry of Education Key Laboratory of Contemporary Anthropology, School of Life Sciences, Fudan University, Shanghai 200438, China
| | - Shuhua Xu
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, School of Life Sciences, Department of Liver Surgery and Transplantation Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai 200032, China
- Ministry of Education Key Laboratory of Contemporary Anthropology, School of Life Sciences, Fudan University, Shanghai 200438, China
| |
Collapse
|
5
|
Ge J, Xing S, Grün R, Deng C, Jiang Y, Jiang T, Yang S, Zhao K, Gao X, Yang H, Guo Z, Petraglia MD, Shao Q. New Late Pleistocene age for the Homo sapiens skeleton from Liujiang southern China. Nat Commun 2024; 15:3611. [PMID: 38684677 PMCID: PMC11058812 DOI: 10.1038/s41467-024-47787-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Accepted: 04/12/2024] [Indexed: 05/02/2024] Open
Abstract
The emergence of Homo sapiens in Eastern Asia is a topic of significant research interest. However, well-preserved human fossils in secure, dateable contexts in this region are extremely rare, and often the subject of intense debate owing to stratigraphic and geochronological problems. Tongtianyan cave, in Liujiang District of Liuzhou City, southern China is one of the most important fossils finds of H. sapiens, though its age has been debated, with chronometric dates ranging from the late Middle Pleistocene to the early Late Pleistocene. Here we provide new age estimates and revised provenience information for the Liujiang human fossils, which represent one of the most complete fossil skeletons of H. sapiens in China. U-series dating on the human fossils and radiocarbon and optically stimulated luminescence dating on the fossil-bearing sediments provided ages ranging from ~33,000 to 23,000 years ago (ka). The revised age estimates correspond with the dates of other human fossils in northern China, at Tianyuan Cave (~40.8-38.1 ka) and Zhoukoudian Upper Cave (39.0-36.3 ka), indicating the geographically widespread presence of H. sapiens across Eastern Asia in the Late Pleistocene, which is significant for better understanding human dispersals and adaptations in the region.
Collapse
Affiliation(s)
- Junyi Ge
- Key Laboratory of Vertebrate Evolution and Human Origins, Institute of Vertebrate Paleontology and Paleoanthropology, Chinese Academy of Sciences, Beijing, 100044, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Song Xing
- Key Laboratory of Vertebrate Evolution and Human Origins, Institute of Vertebrate Paleontology and Paleoanthropology, Chinese Academy of Sciences, Beijing, 100044, China
- Centro Nacional de Investigación sobre la Evolución Humana, Paseo de la Sierra de Atapuerca s/n, Burgos, Spain
| | - Rainer Grün
- Research School of Earth Sciences, The Australian National University, Canberra, ACT, Australia
- Australian Research Centre for Human Evolution, Griffith University, Brisbane, QD, 4111, Australia
- School of Geography, Nanjing Normal University, Nanjing, 210023, China
| | - Chenglong Deng
- University of Chinese Academy of Sciences, Beijing, 100049, China
- State Key Laboratory of Lithospheric Evolution, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing, 100029, China
| | | | - Tingyun Jiang
- School of Geography, Nanjing Normal University, Nanjing, 210023, China
| | - Shixia Yang
- Key Laboratory of Vertebrate Evolution and Human Origins, Institute of Vertebrate Paleontology and Paleoanthropology, Chinese Academy of Sciences, Beijing, 100044, China
| | - Keliang Zhao
- Key Laboratory of Vertebrate Evolution and Human Origins, Institute of Vertebrate Paleontology and Paleoanthropology, Chinese Academy of Sciences, Beijing, 100044, China
| | - Xing Gao
- Key Laboratory of Vertebrate Evolution and Human Origins, Institute of Vertebrate Paleontology and Paleoanthropology, Chinese Academy of Sciences, Beijing, 100044, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Huili Yang
- State Key Laboratory of Earthquake Dynamics, Institute of Geology, China Earthquake Administration, Beijing, 100029, China
| | - Zhengtang Guo
- Key Laboratory of Cenozoic Geology and Environment, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing, 100029, China
| | - Michael D Petraglia
- Australian Research Centre for Human Evolution, Griffith University, Brisbane, QD, 4111, Australia.
- Human Origins Program, National Museum of Natural History, Smithsonian Institution, Washington, DC, 20560, USA.
- School of Social Science, The University of Queensland, Brisbane, QD, 4072, Australia.
| | - Qingfeng Shao
- School of Geography, Nanjing Normal University, Nanjing, 210023, China.
- Key Laboratory of Virtual Geographic Environment, Ministry of Education, Nanjing Normal University, Nanjing, 210023, China.
| |
Collapse
|
6
|
Gao Y, Zhang X, Chen H, Lu Y, Ma S, Yang Y, Zhang M, Xu S. Reconstructing the ancestral gene pool to uncover the origins and genetic links of Hmong-Mien speakers. BMC Biol 2024; 22:59. [PMID: 38475771 PMCID: PMC10935854 DOI: 10.1186/s12915-024-01838-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Accepted: 02/01/2024] [Indexed: 03/14/2024] Open
Abstract
BACKGROUND Hmong-Mien (HM) speakers are linguistically related and live primarily in China, but little is known about their ancestral origins or the evolutionary mechanism shaping their genomic diversity. In particular, the lack of whole-genome sequencing data on the Yao population has prevented a full investigation of the origins and evolutionary history of HM speakers. As such, their origins are debatable. RESULTS Here, we made a deep sequencing effort of 80 Yao genomes, and our analysis together with 28 East Asian populations and 968 ancient Asian genomes suggested that there is a strong genetic basis for the formation of the HM language family. We estimated that the most recent common ancestor dates to 5800 years ago, while the genetic divergence between the HM and Tai-Kadai speakers was estimated to be 8200 years ago. We proposed that HM speakers originated from the Yangtze River Basin and spread with agricultural civilization. We identified highly differentiated variants between HM and Han Chinese, in particular, a deafness-related missense variant (rs72474224) in the GJB2 gene is in a higher frequency in HM speakers than in others. CONCLUSIONS Our results indicated complex gene flow and medically relevant variants involved in the HM speakers' evolution history.
Collapse
Affiliation(s)
- Yang Gao
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
- School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Xiaoxi Zhang
- School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Hao Chen
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Yan Lu
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Sen Ma
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Yajun Yang
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, Fudan University, Shanghai, China
| | - Menghan Zhang
- Institute of Modern Languages and Linguistics, and Ministry of Education Key Laboratory of Contemporary Anthropology, School of Life Sciences, Fudan University, Shanghai, 200433, China
| | - Shuhua Xu
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
- School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China.
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China.
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, Fudan University, Shanghai, China.
| |
Collapse
|
7
|
Liu S, Luo H, Zhang P, Li Y, Hao D, Zhang S, Song T, Xu T, He S. Adaptive Selection of Cis-regulatory Elements in the Han Chinese. Mol Biol Evol 2024; 41:msae034. [PMID: 38377343 PMCID: PMC10917166 DOI: 10.1093/molbev/msae034] [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: 10/02/2023] [Revised: 01/18/2024] [Accepted: 02/05/2024] [Indexed: 02/22/2024] Open
Abstract
Cis-regulatory elements have an important role in human adaptation to the living environment. However, the lag in population genomic cohort studies and epigenomic studies, hinders the research in the adaptive analysis of cis-regulatory elements in human populations. In this study, we collected 4,013 unrelated individuals and performed a comprehensive analysis of adaptive selection of genome-wide cis-regulatory elements in the Han Chinese. In total, 12.34% of genomic regions are under the influence of adaptive selection, where 1.00% of enhancers and 2.06% of promoters are under positive selection, and 0.06% of enhancers and 0.02% of promoters are under balancing selection. Gene ontology enrichment analysis of these cis-regulatory elements under adaptive selection reveals that many positive selections in the Han Chinese occur in pathways involved in cell-cell adhesion processes, and many balancing selections are related to immune processes. Two classes of adaptive cis-regulatory elements related to cell adhesion were in-depth analyzed, one is the adaptive enhancers derived from neanderthal introgression, leads to lower hyaluronidase level in skin, and brings better performance on UV-radiation resistance to the Han Chinese. Another one is the cis-regulatory elements regulating wound healing, and the results suggest the positive selection inhibits coagulation and promotes angiogenesis and wound healing in the Han Chinese. Finally, we found that many pathogenic alleles, such as risky alleles of type 2 diabetes or schizophrenia, remain in the population due to the hitchhiking effect of positive selections. Our findings will help deepen our understanding of the adaptive evolution of genome regulation in the Han Chinese.
Collapse
Affiliation(s)
- Shuai Liu
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Huaxia Luo
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Peng Zhang
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Yanyan Li
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Di Hao
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Sijia Zhang
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Tingrui Song
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Tao Xu
- National Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
- Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan 250117, Shandong, China
| | - Shunmin He
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| |
Collapse
|
8
|
Zhang S, Zhang R, Yuan K, Yang L, Liu C, Liu Y, Ni X, Xu S. Reconstructing complex admixture history using a hierarchical model. Brief Bioinform 2024; 25:bbad540. [PMID: 38261339 PMCID: PMC10805183 DOI: 10.1093/bib/bbad540] [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: 10/20/2023] [Revised: 12/04/2023] [Accepted: 12/22/2023] [Indexed: 01/24/2024] Open
Abstract
Various methods have been proposed to reconstruct admixture histories by analyzing the length of ancestral chromosomal tracts, such as estimating the admixture time and number of admixture events. However, available methods do not explicitly consider the complex admixture structure, which characterizes the joining and mixing patterns of different ancestral populations during the admixture process, and instead assume a simplified one-by-one sequential admixture model. In this study, we proposed a novel approach that considers the non-sequential admixture structure to reconstruct admixture histories. Specifically, we introduced a hierarchical admixture model that incorporated four ancestral populations and developed a new method, called HierarchyMix, which uses the length of ancestral tracts and the number of ancestry switches along genomes to reconstruct the four-way admixture history. By automatically selecting the optimal admixture model using the Bayesian information criterion principles, HierarchyMix effectively estimates the corresponding admixture parameters. Simulation studies confirmed the effectiveness and robustness of HierarchyMix. We also applied HierarchyMix to Uyghurs and Kazakhs, enabling us to reconstruct the admixture histories of Central Asians. Our results highlight the importance of considering complex admixture structures and demonstrate that HierarchyMix is a useful tool for analyzing complex admixture events.
Collapse
Affiliation(s)
- Shi Zhang
- School of Mathematics and Statistics, Beijing Jiaotong University, Beijing, 100044, China
| | - Rui Zhang
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Kai Yuan
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Lu Yang
- School of Mathematics and Statistics, Beijing Jiaotong University, Beijing, 100044, China
| | - Chang Liu
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Yuting Liu
- School of Mathematics and Statistics, Beijing Jiaotong University, Beijing, 100044, China
| | - Xumin Ni
- School of Mathematics and Statistics, Beijing Jiaotong University, Beijing, 100044, China
| | - Shuhua Xu
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, School of Life Sciences, Department of Liver Surgery and Transplantation Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai 200032 , China
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, Fudan University, Shanghai 201203, China
- School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China
| |
Collapse
|
9
|
Langdon QK, Groh JS, Aguillon SM, Powell DL, Gunn T, Payne C, Baczenas JJ, Donny A, Dodge TO, Du K, Schartl M, Ríos-Cárdenas O, Gutierrez-Rodríguez C, Morris M, Schumer M. Genome evolution is surprisingly predictable after initial hybridization. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.21.572897. [PMID: 38187753 PMCID: PMC10769416 DOI: 10.1101/2023.12.21.572897] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/09/2024]
Abstract
Over the past two decades, evolutionary biologists have come to appreciate that hybridization, or genetic exchange between distinct lineages, is remarkably common - not just in particular lineages but in taxonomic groups across the tree of life. As a result, the genomes of many modern species harbor regions inherited from related species. This observation has raised fundamental questions about the degree to which the genomic outcomes of hybridization are repeatable and the degree to which natural selection drives such repeatability. However, a lack of appropriate systems to answer these questions has limited empirical progress in this area. Here, we leverage independently formed hybrid populations between the swordtail fish Xiphophorus birchmanni and X. cortezi to address this fundamental question. We find that local ancestry in one hybrid population is remarkably predictive of local ancestry in another, demographically independent hybrid population. Applying newly developed methods, we can attribute much of this repeatability to strong selection in the earliest generations after initial hybridization. We complement these analyses with time-series data that demonstrates that ancestry at regions under selection has remained stable over the past ~40 generations of evolution. Finally, we compare our results to the well-studied X. birchmanni×X. malinche hybrid populations and conclude that deeper evolutionary divergence has resulted in stronger selection and higher repeatability in patterns of local ancestry in hybrids between X. birchmanni and X. cortezi.
Collapse
Affiliation(s)
- Quinn K. Langdon
- Department of Biology, Stanford University
- Centro de Investigaciones Científicas de las Huastecas “Aguazarca”, A.C
- Gladstone Institute of Virology, Gladstone Institutes, San Francisco, California
| | - Jeffrey S. Groh
- Center for Population Biology and Department of Evolution and Ecology, University of California, Davis
| | - Stepfanie M. Aguillon
- Department of Biology, Stanford University
- Centro de Investigaciones Científicas de las Huastecas “Aguazarca”, A.C
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles
| | - Daniel L. Powell
- Department of Biology, Stanford University
- Centro de Investigaciones Científicas de las Huastecas “Aguazarca”, A.C
| | - Theresa Gunn
- Department of Biology, Stanford University
- Centro de Investigaciones Científicas de las Huastecas “Aguazarca”, A.C
| | - Cheyenne Payne
- Department of Biology, Stanford University
- Centro de Investigaciones Científicas de las Huastecas “Aguazarca”, A.C
| | | | - Alex Donny
- Department of Biology, Stanford University
- Centro de Investigaciones Científicas de las Huastecas “Aguazarca”, A.C
| | - Tristram O. Dodge
- Department of Biology, Stanford University
- Centro de Investigaciones Científicas de las Huastecas “Aguazarca”, A.C
| | - Kang Du
- Xiphophorus Genetic Stock Center, Texas State University San Marcos
| | - Manfred Schartl
- Xiphophorus Genetic Stock Center, Texas State University San Marcos
- Developmental Biochemistry, Biocenter, University of Würzburg
| | | | | | | | - Molly Schumer
- Department of Biology, Stanford University
- Centro de Investigaciones Científicas de las Huastecas “Aguazarca”, A.C
- Freeman Hrabowski Fellow, Howard Hughes Medical Institute
| |
Collapse
|
10
|
Ge X, Lu Y, Chen S, Gao Y, Ma L, Liu L, Liu J, Ma X, Kang L, Xu S. Genetic Origins and Adaptive Evolution of the Deng People on the Tibetan Plateau. Mol Biol Evol 2023; 40:msad205. [PMID: 37713634 PMCID: PMC10584363 DOI: 10.1093/molbev/msad205] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 07/01/2023] [Accepted: 08/30/2023] [Indexed: 09/17/2023] Open
Abstract
The Tibetan Plateau is populated by diverse ethnic groups, but most of them are underrepresented in genomics studies compared with the Tibetans (TIB). Here, to gain further insight into the genetic diversity and evolutionary history of the people living in the Tibetan Plateau, we sequenced 54 whole genomes of the Deng people with high coverage (30-60×) and analyzed the data together with that of TIB and Sherpas, as well as 968 ancient Asian genomes and available archaic and modern human data. We identified 17.74 million novel single-nucleotide variants from the newly sequenced genomes, although the Deng people showed reduced genomic diversity and a relatively small effective population size. Compared with the other Tibetan highlander groups which are highly admixed, the Deng people are dominated by a sole ancestry that could be traced to some ancient northern East Asian populations. The divergence between Deng and Tibetan people (∼4,700-7,200 years) was more recent than that between highlanders and the Han Chinese (Deng-HAN, ∼9,000-14,000 years; TIB-HAN, 7,200-10,000 years). Adaptive genetic variants (AGVs) identified in the Deng are only partially shared with those previously reported in the TIB like HLA-DQB1, whereas others like KLHL12 were not reported in TIB. In contrast, the top candidate genes harboring AGVs as previously identified in TIB, like EPAS1 and EGLN1, do not show strong positive selection signals in Deng. Interestingly, Deng also showed a different archaic introgression scenario from that observed in the TIB. Our results suggest that convergent adaptation might be prevalent on the Tibetan Plateau.
Collapse
Affiliation(s)
- Xueling Ge
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Yan Lu
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, School of Life Sciences, Fudan University, Shanghai, China
| | - Shuanghui Chen
- School of Life Science and Technology, ShanghaiTech University, Shanghai, China
| | - Yang Gao
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, School of Life Sciences, Fudan University, Shanghai, China
| | - Lifeng Ma
- Key Laboratory of High-Altitude Environment and Genes Related to Disease of Tibet Ministry of Education, Xizang Minzu University, Xianyang, Shaanxi, China
- Research Center for Tibetan Social Governance, Key Research Institute of Humanities and Social Sciences in Xizang Minzu University, State Ethnic Affairs Commission, Xizang Minzu University, Xianyang, Shaanxi, China
| | - Lijun Liu
- Key Laboratory of High-Altitude Environment and Genes Related to Disease of Tibet Ministry of Education, Xizang Minzu University, Xianyang, Shaanxi, China
- Research Center for Tibetan Social Governance, Key Research Institute of Humanities and Social Sciences in Xizang Minzu University, State Ethnic Affairs Commission, Xizang Minzu University, Xianyang, Shaanxi, China
| | - Jiaojiao Liu
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, School of Life Sciences, Fudan University, Shanghai, China
| | - Xixian Ma
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Longli Kang
- Key Laboratory of High-Altitude Environment and Genes Related to Disease of Tibet Ministry of Education, Xizang Minzu University, Xianyang, Shaanxi, China
- Research Center for Tibetan Social Governance, Key Research Institute of Humanities and Social Sciences in Xizang Minzu University, State Ethnic Affairs Commission, Xizang Minzu University, Xianyang, Shaanxi, China
| | - Shuhua Xu
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, School of Life Sciences, Fudan University, Shanghai, China
- School of Life Science and Technology, ShanghaiTech University, Shanghai, China
- Department of Liver Surgery and Transplantation Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, Fudan University, Shanghai, China
| |
Collapse
|
11
|
Gao Y, Yang X, Chen H, Tan X, Yang Z, Deng L, Wang B, Kong S, Li S, Cui Y, Lei C, Wang Y, Pan Y, Ma S, Sun H, Zhao X, Shi Y, Yang Z, Wu D, Wu S, Zhao X, Shi B, Jin L, Hu Z, Lu Y, Chu J, Ye K, Xu S. A pangenome reference of 36 Chinese populations. Nature 2023; 619:112-121. [PMID: 37316654 PMCID: PMC10322713 DOI: 10.1038/s41586-023-06173-7] [Citation(s) in RCA: 34] [Impact Index Per Article: 34.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2022] [Accepted: 05/05/2023] [Indexed: 06/16/2023]
Abstract
Human genomics is witnessing an ongoing paradigm shift from a single reference sequence to a pangenome form, but populations of Asian ancestry are underrepresented. Here we present data from the first phase of the Chinese Pangenome Consortium, including a collection of 116 high-quality and haplotype-phased de novo assemblies based on 58 core samples representing 36 minority Chinese ethnic groups. With an average 30.65× high-fidelity long-read sequence coverage, an average contiguity N50 of more than 35.63 megabases and an average total size of 3.01 gigabases, the CPC core assemblies add 189 million base pairs of euchromatic polymorphic sequences and 1,367 protein-coding gene duplications to GRCh38. We identified 15.9 million small variants and 78,072 structural variants, of which 5.9 million small variants and 34,223 structural variants were not reported in a recently released pangenome reference1. The Chinese Pangenome Consortium data demonstrate a remarkable increase in the discovery of novel and missing sequences when individuals are included from underrepresented minority ethnic groups. The missing reference sequences were enriched with archaic-derived alleles and genes that confer essential functions related to keratinization, response to ultraviolet radiation, DNA repair, immunological responses and lifespan, implying great potential for shedding new light on human evolution and recovering missing heritability in complex disease mapping.
Collapse
Affiliation(s)
- Yang Gao
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, School of Life Sciences, Fudan University, Shanghai, China
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, Fudan University, Shanghai, China
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
- School of Life Science and Technology, ShanghaiTech University, Shanghai, China
| | - Xiaofei Yang
- School of Computer Science and Technology, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China
- MOE Key Lab for Intelligent Networks & Networks Security, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China
- Genome Institute, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Hao Chen
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Xinjiang Tan
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Zhaoqing Yang
- Department of Medical Genetics, Institute of Medical Biology, Chinese Academy of Medical Sciences, Kunming, China
| | - Lian Deng
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, School of Life Sciences, Fudan University, Shanghai, China
| | - Baonan Wang
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, Fudan University, Shanghai, China
| | - Shuang Kong
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, Fudan University, Shanghai, China
| | - Songyang Li
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, Fudan University, Shanghai, China
| | - Yuhang Cui
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, Fudan University, Shanghai, China
| | - Chang Lei
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, School of Life Sciences, Fudan University, Shanghai, China
| | - Yimin Wang
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Yuwen Pan
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Sen Ma
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Hao Sun
- Department of Medical Genetics, Institute of Medical Biology, Chinese Academy of Medical Sciences, Kunming, China
| | - Xiaohan Zhao
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, Fudan University, Shanghai, China
| | - Yingbing Shi
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, School of Life Sciences, Fudan University, Shanghai, China
| | - Ziyi Yang
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, School of Life Sciences, Fudan University, Shanghai, China
| | - Dongdong Wu
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Shaoyuan Wu
- Jiangsu Key Laboratory of Phylogenomics & Comparative Genomics, International Joint Center of Genomics of Jiangsu Province School of Life Sciences, Jiangsu Normal University, Xuzhou, China
| | - Xingming Zhao
- Institute of Science and Technology for Brain-Inspired Intelligence, Ministry of Education Key (MOE) Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, MOE Frontiers Center for Brain Science Fudan University, Shanghai, China
| | - Binyin Shi
- Department of Endocrinology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Li Jin
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, School of Life Sciences, Fudan University, Shanghai, China
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, Fudan University, Shanghai, China
| | - Zhibin Hu
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Yan Lu
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, School of Life Sciences, Fudan University, Shanghai, China.
| | - Jiayou Chu
- Department of Medical Genetics, Institute of Medical Biology, Chinese Academy of Medical Sciences, Kunming, China.
| | - Kai Ye
- MOE Key Lab for Intelligent Networks & Networks Security, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China.
- School of Automation Science and Engineering, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China.
- School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China.
| | - Shuhua Xu
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, School of Life Sciences, Fudan University, Shanghai, China.
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, Fudan University, Shanghai, China.
- School of Life Science and Technology, ShanghaiTech University, Shanghai, China.
- Jiangsu Key Laboratory of Phylogenomics & Comparative Genomics, International Joint Center of Genomics of Jiangsu Province School of Life Sciences, Jiangsu Normal University, Xuzhou, China.
- Department of Liver Surgery and Transplantation Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China.
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, China.
| |
Collapse
|
12
|
Zhang X, Kim B, Singh A, Sankararaman S, Durvasula A, Lohmueller KE. MaLAdapt Reveals Novel Targets of Adaptive Introgression From Neanderthals and Denisovans in Worldwide Human Populations. Mol Biol Evol 2023; 40:msad001. [PMID: 36617238 PMCID: PMC9887621 DOI: 10.1093/molbev/msad001] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Revised: 12/25/2022] [Accepted: 12/28/2022] [Indexed: 01/09/2023] Open
Abstract
Adaptive introgression (AI) facilitates local adaptation in a wide range of species. Many state-of-the-art methods detect AI with ad-hoc approaches that identify summary statistic outliers or intersect scans for positive selection with scans for introgressed genomic regions. Although widely used, approaches intersecting outliers are vulnerable to a high false-negative rate as the power of different methods varies, especially for complex introgression events. Moreover, population genetic processes unrelated to AI, such as background selection or heterosis, may create similar genomic signals to AI, compromising the reliability of methods that rely on neutral null distributions. In recent years, machine learning (ML) methods have been increasingly applied to population genetic questions. Here, we present a ML-based method called MaLAdapt for identifying AI loci from genome-wide sequencing data. Using an Extra-Trees Classifier algorithm, our method combines information from a large number of biologically meaningful summary statistics to capture a powerful composite signature of AI across the genome. In contrast to existing methods, MaLAdapt is especially well-powered to detect AI with mild beneficial effects, including selection on standing archaic variation, and is robust to non-AI selective sweeps, heterosis from deleterious mutations, and demographic misspecification. Furthermore, MaLAdapt outperforms existing methods for detecting AI based on the analysis of simulated data and the validation of empirical signals through visual inspection of haplotype patterns. We apply MaLAdapt to the 1000 Genomes Project human genomic data and discover novel AI candidate regions in non-African populations, including genes that are enriched in functionally important biological pathways regulating metabolism and immune responses.
Collapse
Affiliation(s)
- Xinjun Zhang
- Department of Ecology and Evolutionary Biology, UCLA, Los Angeles, CA
| | - Bernard Kim
- Department of Biology, Stanford University, Palo Alto, CA
| | - Armaan Singh
- Department of Computer Science, UCLA, Los Angeles, CA
| | - Sriram Sankararaman
- Department of Computer Science, UCLA, Los Angeles, CA
- Department of Computational Medicine, UCLA, Los Angeles, CA
- Department of Human Genetics, David Geffen School of Medicine, UCLA, Los Angeles, CA
| | - Arun Durvasula
- Department of Genetics, Harvard Medical School, Boston, MA
| | - Kirk E Lohmueller
- Department of Ecology and Evolutionary Biology, UCLA, Los Angeles, CA
- Department of Human Genetics, David Geffen School of Medicine, UCLA, Los Angeles, CA
| |
Collapse
|
13
|
Chen H, Lin R, Lu Y, Zhang R, Gao Y, He Y, Xu S. Tracing Bai-Yue Ancestry in Aboriginal Li People on Hainan Island. Mol Biol Evol 2022; 39:6731089. [PMID: 36173765 PMCID: PMC9585476 DOI: 10.1093/molbev/msac210] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
As the most prevalent aboriginal group on Hainan Island located between South China and the mainland of Southeast Asia, the Li people are believed to preserve some unique genetic information due to their isolated circumstances, although this has been largely uninvestigated. We performed the first whole-genome sequencing of 55 Hainan Li (HNL) individuals with high coverage (∼30-50×) to gain insight into their genetic history and potential adaptations. We identified the ancestry enriched in HNL (∼85%) is well preserved in present-day Tai-Kadai speakers residing in South China and North Vietnam, that is, Bai-Yue populations. A lack of admixture signature due to the geographical restriction exacerbated the bottleneck in the present-day HNL. The genetic divergence among Bai-Yue populations began ∼4,000-3,000 years ago when the proto-HNL underwent migration and the settling of Hainan Island. Finally, we identified signatures of positive selection in the HNL, some outstanding examples included FADS1 and FADS2 related to a diet rich in polyunsaturated fatty acids. In addition, we observed that malaria-driven selection had occurred in the HNL, with population-specific variants of malaria-related genes (e.g., CR1) present. Interestingly, HNL harbors a high prevalence of malaria leveraged gene variants related to hematopoietic function (e.g., CD3G) that may explain the high incidence of blood disorders such as B-cell lymphomas in the present-day HNL. The results have advanced our understanding of the genetic history of the Bai-Yue populations and have provided new insights into the adaptive scenarios of the Li people.
Collapse
Affiliation(s)
| | | | - Yan Lu
- State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai 200438, China,Human Phenome Institute, Zhangjiang Fudan International Innovation Center, and Ministry of Education Key Laboratory of Contemporary Anthropology, Fudan University, Shanghai 201203, China
| | - Rui Zhang
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Yang Gao
- Human Phenome Institute, Zhangjiang Fudan International Innovation Center, and Ministry of Education Key Laboratory of Contemporary Anthropology, Fudan University, Shanghai 201203, China
| | | | | |
Collapse
|
14
|
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
Collapse
|
15
|
Deng L, Pan Y, Wang Y, Chen H, Yuan K, Chen S, Lu D, Lu Y, Mokhtar SS, Rahman TA, Hoh BP, Xu S. Genetic Connections and Convergent Evolution of Tropical Indigenous Peoples in Asia. Mol Biol Evol 2022; 39:msab361. [PMID: 34940850 PMCID: PMC8826522 DOI: 10.1093/molbev/msab361] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Tropical indigenous peoples in Asia (TIA) attract much attention for their unique appearance, whereas their genetic history and adaptive evolution remain mysteries. We conducted a comprehensive study to characterize the genetic distinction and connection of broad geographical TIAs. Despite the diverse genetic makeup and large interarea genetic differentiation between the TIA groups, we identified a basal Asian ancestry (bASN) specifically shared by these populations. The bASN ancestry was relatively enriched in ancient Asian human genomes dated as early as ∼50,000 years before the present and diminished in more recent history. Notably, the bASN ancestry is unlikely to be derived from archaic hominins. Instead, we suggest it may be better modeled as a survived lineage of the initial peopling of Asia. Shared adaptations inherited from the ancient Asian ancestry were detected among the TIA groups (e.g., LIMS1 for hair morphology, and COL24A1 for bone formation), and they are enriched in neurological functions either at an identical locus (e.g., NKAIN3), or different loci in an identical gene (e.g., TENM4). The bASN ancestry could also have formed the substrate of the genetic architecture of the dark pigmentation observed in the TIA peoples. We hypothesize that phenotypic convergence of the dark pigmentation in TIAs could have resulted from parallel (e.g., DDB1/DAK) or genetic convergence driven by admixture (e.g., MTHFD1 and RAD18), new mutations (e.g., STK11), or notably purifying selection (e.g., MC1R). Our results provide new insights into the initial peopling of Asia and an advanced understanding of the phenotypic convergence of the TIA peoples.
Collapse
Affiliation(s)
- Lian Deng
- State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai, China
| | - Yuwen Pan
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Yinan Wang
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
- Department of Liver Surgery and Transplantation Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Hao Chen
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Kai Yuan
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Sihan Chen
- Ministry of Education Key Laboratory of Contemporary Anthropology, School of Life Sciences, Human Phenome Institute, Fudan University, Shanghai, China
| | - Dongsheng Lu
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Yan Lu
- State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai, China
| | - Siti Shuhada Mokhtar
- Institute of Medical Molecular Biotechnology, Faculty of Medicine, Universiti Teknologi MARA, Sungai Buloh Campus, Sungai Buloh, Selangor, Malaysia
| | - Thuhairah Abdul Rahman
- Clinical Pathology Diagnostic Centre Research Laboratory, Faculty of Medicine, Universiti Teknologi MARA, Sungai Buloh Campus, Sungai Buloh, Selangor, Malaysia
| | - Boon-Peng Hoh
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
- Faculty of Medicine and Health Sciences, UCSI University, Cheras, Kuala Lumpur, Malaysia
| | - Shuhua Xu
- State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai, China
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
- Department of Liver Surgery and Transplantation Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China
- Ministry of Education Key Laboratory of Contemporary Anthropology, School of Life Sciences, Human Phenome Institute, Fudan University, Shanghai, China
- School of Life Science and Technology, ShanghaiTech University, Shanghai, China
- Jiangsu Key Laboratory of Phylogenomics and Comparative Genomics, School of Life Sciences, Jiangsu Normal University, Xuzhou, China
- Henan Institute of Medical and Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, China
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, China
| |
Collapse
|