1
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Liu J, Bitsue HK, Yang Z. Skin colour: A window into human phenotypic evolution and environmental adaptation. Mol Ecol 2024; 33:e17369. [PMID: 38713101 DOI: 10.1111/mec.17369] [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: 01/31/2024] [Revised: 04/13/2024] [Accepted: 04/17/2024] [Indexed: 05/08/2024]
Abstract
As modern humans ventured out of Africa and dispersed around the world, they faced novel environmental challenges that led to geographic adaptations including skin colour. Over the long history of human evolution, skin colour has changed dramatically, showing tremendous diversity across different geographical regions, for example, the majority of individuals from the expansive lands of Africa have darker skin, whereas the majority of people from Eurasia exhibit lighter skin. What adaptations did lighter skin confer upon modern humans as they migrated from Africa to Eurasia? What genetic mechanisms underlie the diversity of skin colour observed in different populations? In recent years, scientists have gradually gained a deeper understanding of the interactions between pigmentation gene and skin colour through population-based genomic studies of different groups around the world, particularly in East Asia and Africa. In this review, we summarize our current understanding of 26 skin colour-related pigmentation genes and 48 SNPs that influence skin colour. Important pigmentation genes across three major populations are described in detail: MFSD12, SLC24A5, PDPK1 and DDB1/CYB561A3/TMEM138 influence skin colour in African populations; OCA2, KITLG, SLC24A2, GNPAT and PAH are key to the evolution of skin pigmentation in East Asian populations; and SLC24A5, SLC45A2, TYR, TYRP1, ASIP, MC1R and IRF4 significantly contribute to the lightening of skin colour in European populations. We summarized recent findings in genomic studies of skin colour in populations that implicate diverse geographic environments, local adaptation among populations, gene flow and multi-gene interactions as factors influencing skin colour diversity.
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Affiliation(s)
- Jiuming Liu
- Tianjian Laboratory of Advanced Biomedical Sciences, Academy of Medical Sciences, Zhengzhou University, Zhengzhou, China
| | - Habtom K Bitsue
- Tianjian Laboratory of Advanced Biomedical Sciences, Academy of Medical Sciences, Zhengzhou University, Zhengzhou, China
| | - Zhaohui Yang
- Tianjian Laboratory of Advanced Biomedical Sciences, Academy of Medical Sciences, Zhengzhou University, Zhengzhou, China
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2
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Li G, Liu Y, Feng X, Diao S, Zhong Z, Li B, Teng J, Zhang W, Zeng H, Cai X, Gao Y, Liu X, Yuan X, Li J, Zhang Z. Integrating Multiple Database Resources to Elucidate the Gene Flow in Southeast Asian Pig Populations. Int J Mol Sci 2024; 25:5689. [PMID: 38891877 PMCID: PMC11171535 DOI: 10.3390/ijms25115689] [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: 04/17/2024] [Revised: 05/16/2024] [Accepted: 05/18/2024] [Indexed: 06/21/2024] Open
Abstract
The domestic pig (Sus scrofa) and its subfamilies have experienced long-term and extensive gene flow, particularly in Southeast Asia. Here, we analyzed 236 pigs, focusing on Yunnan indigenous, European commercial, East Asian, and Southeast Asian breeds, using the Pig Genomics Reference Panel (PGRP v1) of Pig Genotype-Tissue Expression (PigGTEx) to investigate gene flow and associated complex traits by integrating multiple database resources. In this study, we discovered evidence of admixtures from European pigs into the genome of Yunnan indigenous pigs. Additionally, we hypothesized that a potential conceptual gene flow route that may have contributed to the genetic composition of the Diannan small-ear pig is a gene exchange from the Vietnamese pig. Based on the most stringent gene introgression scan using the fd statistic, we identified three specific loci on chromosome 8, ranging from 51.65 to 52.45 Mb, which exhibited strong signatures of selection and harbored the NAF1, NPY1R, and NPY5R genes. These genes are associated with complex traits, such as fat mass, immunity, and litter weight, in pigs, as supported by multiple bio-functionalization databases. We utilized multiple databases to explore the potential dynamics of genetic exchange in Southeast Asian pig populations and elucidated specific gene functionalities.
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Affiliation(s)
- Guangzhen Li
- National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (G.L.); (Y.L.); (X.F.); (S.D.); (Z.Z.); (B.L.); (J.T.); (W.Z.); (H.Z.); (X.C.); (Y.G.); (X.Y.)
| | - Yuqiang Liu
- National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (G.L.); (Y.L.); (X.F.); (S.D.); (Z.Z.); (B.L.); (J.T.); (W.Z.); (H.Z.); (X.C.); (Y.G.); (X.Y.)
| | - Xueyan Feng
- National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (G.L.); (Y.L.); (X.F.); (S.D.); (Z.Z.); (B.L.); (J.T.); (W.Z.); (H.Z.); (X.C.); (Y.G.); (X.Y.)
| | - Shuqi Diao
- National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (G.L.); (Y.L.); (X.F.); (S.D.); (Z.Z.); (B.L.); (J.T.); (W.Z.); (H.Z.); (X.C.); (Y.G.); (X.Y.)
| | - Zhanming Zhong
- National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (G.L.); (Y.L.); (X.F.); (S.D.); (Z.Z.); (B.L.); (J.T.); (W.Z.); (H.Z.); (X.C.); (Y.G.); (X.Y.)
| | - Bolang Li
- National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (G.L.); (Y.L.); (X.F.); (S.D.); (Z.Z.); (B.L.); (J.T.); (W.Z.); (H.Z.); (X.C.); (Y.G.); (X.Y.)
| | - Jinyan Teng
- National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (G.L.); (Y.L.); (X.F.); (S.D.); (Z.Z.); (B.L.); (J.T.); (W.Z.); (H.Z.); (X.C.); (Y.G.); (X.Y.)
| | - Wenjing Zhang
- National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (G.L.); (Y.L.); (X.F.); (S.D.); (Z.Z.); (B.L.); (J.T.); (W.Z.); (H.Z.); (X.C.); (Y.G.); (X.Y.)
| | - Haonan Zeng
- National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (G.L.); (Y.L.); (X.F.); (S.D.); (Z.Z.); (B.L.); (J.T.); (W.Z.); (H.Z.); (X.C.); (Y.G.); (X.Y.)
| | - Xiaodian Cai
- National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (G.L.); (Y.L.); (X.F.); (S.D.); (Z.Z.); (B.L.); (J.T.); (W.Z.); (H.Z.); (X.C.); (Y.G.); (X.Y.)
| | - Yahui Gao
- National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (G.L.); (Y.L.); (X.F.); (S.D.); (Z.Z.); (B.L.); (J.T.); (W.Z.); (H.Z.); (X.C.); (Y.G.); (X.Y.)
| | - Xiaohong Liu
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou 510275, China;
| | - Xiaolong Yuan
- National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (G.L.); (Y.L.); (X.F.); (S.D.); (Z.Z.); (B.L.); (J.T.); (W.Z.); (H.Z.); (X.C.); (Y.G.); (X.Y.)
| | - Jiaqi Li
- National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (G.L.); (Y.L.); (X.F.); (S.D.); (Z.Z.); (B.L.); (J.T.); (W.Z.); (H.Z.); (X.C.); (Y.G.); (X.Y.)
| | - Zhe Zhang
- National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (G.L.); (Y.L.); (X.F.); (S.D.); (Z.Z.); (B.L.); (J.T.); (W.Z.); (H.Z.); (X.C.); (Y.G.); (X.Y.)
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Bennett EA, Fu Q. Ancient genomes and the evolutionary path of modern humans. Cell 2024; 187:1042-1046. [PMID: 38428387 DOI: 10.1016/j.cell.2024.01.047] [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: 10/19/2023] [Revised: 12/21/2023] [Accepted: 01/29/2024] [Indexed: 03/03/2024]
Abstract
Growing evidence from archaic and early modern human genomes brings new insights to the emergence of modern humans. We recount recent information collected from ancient DNA studies that inform us about the evolutionary pathway to modern humanity. These findings point to both individual- and population-level advantages underlying modern human expansion.
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Affiliation(s)
- E Andrew Bennett
- Key Laboratory of Vertebrate Evolution and Human Origins, Institute of Vertebrate Paleontology and Paleoanthropology, Chinese Academy of Sciences, Beijing, China.
| | - Qiaomei Fu
- Key Laboratory of Vertebrate Evolution and Human Origins, Institute of Vertebrate Paleontology and Paleoanthropology, Chinese Academy of Sciences, Beijing, China; University of the Chinese Academy of Sciences, Beijing 100049, China.
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4
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Barouch A, Mathov Y, Meshorer E, Yakir B, Carmel L. Reconstructing DNA methylation maps of ancient populations. Nucleic Acids Res 2024; 52:1602-1612. [PMID: 38261973 PMCID: PMC10939417 DOI: 10.1093/nar/gkad1232] [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: 01/11/2023] [Revised: 12/09/2023] [Accepted: 01/19/2024] [Indexed: 01/25/2024] Open
Abstract
Studying premortem DNA methylation from ancient DNA (aDNA) provides a proxy for ancient gene activity patterns, and hence valuable information on evolutionary changes in gene regulation. Due to statistical limitations, current methods to reconstruct aDNA methylation maps are constrained to high-coverage shotgun samples, which comprise a small minority of available ancient samples. Most samples are sequenced using in-situ hybridization capture sequencing which targets a predefined set of genomic positions. Here, we develop methods to reconstruct aDNA methylation maps of samples that were not sequenced using high-coverage shotgun sequencing, by way of pooling together individuals to obtain a DNA methylation map that is characteristic of a population. We show that the resulting DNA methylation maps capture meaningful biological information and allow for the detection of differential methylation across populations. We offer guidelines on how to carry out comparative studies involving ancient populations, and how to control the rate of falsely discovered differentially methylated regions. The ability to reconstruct DNA methylation maps of past populations allows for the development of a whole new frontier in paleoepigenetic research, tracing DNA methylation changes throughout human history, using data from thousands of ancient samples.
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Affiliation(s)
- Arielle Barouch
- Department of Genetics, The Alexander Silberman Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem 9190401, Israel
- School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem 9190401, Israel
| | - Yoav Mathov
- Department of Genetics, The Alexander Silberman Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem 9190401, Israel
- Edmond and Lily Safra Center for Brain Sciences (ELSC), The Hebrew University of Jerusalem, Jerusalem 9190401, Israel
| | - Eran Meshorer
- Department of Genetics, The Alexander Silberman Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem 9190401, Israel
- Edmond and Lily Safra Center for Brain Sciences (ELSC), The Hebrew University of Jerusalem, Jerusalem 9190401, Israel
| | - Benjamin Yakir
- Department of Statistics and Data Science, The Hebrew University of Jerusalem, Jerusalem 9190500, Israel
| | - Liran Carmel
- Department of Genetics, The Alexander Silberman Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem 9190401, Israel
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5
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Lei H, Li J, Zhao B, Kou SH, Xiao F, Chen T, Wang SM. Evolutionary origin of germline pathogenic variants in human DNA mismatch repair genes. Hum Genomics 2024; 18:5. [PMID: 38287404 PMCID: PMC10823654 DOI: 10.1186/s40246-024-00573-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2023] [Accepted: 01/17/2024] [Indexed: 01/31/2024] Open
Abstract
BACKGROUND Mismatch repair (MMR) system is evolutionarily conserved for genome stability maintenance. Germline pathogenic variants (PVs) in MMR genes that lead to MMR functional deficiency are associated with high cancer risk. Knowing the evolutionary origin of germline PVs in human MMR genes will facilitate understanding the biological base of MMR deficiency in cancer. However, systematic knowledge is lacking to address the issue. In this study, we performed a comprehensive analysis to know the evolutionary origin of human MMR PVs. METHODS We retrieved MMR gene variants from the ClinVar database. The genomes of 100 vertebrates were collected from the UCSC genome browser and ancient human sequencing data were obtained through comprehensive data mining. Cross-species conservation analysis was performed based on the phylogenetic relationship among 100 vertebrates. Rescaled ancient sequencing data were used to perform variant calling for archeological analysis. RESULTS Using the phylogenetic approach, we traced the 3369 MMR PVs identified in modern humans in 99 non-human vertebrate genomes but found no evidence for cross-species conservation as the source for human MMR PVs. Using the archeological approach, we searched the human MMR PVs in over 5000 ancient human genomes dated from 45,045 to 100 years before present and identified a group of MMR PVs shared between modern and ancient humans mostly within 10,000 years with similar quantitative patterns. CONCLUSION Our study reveals that MMR PVs in modern humans were arisen within the recent human evolutionary history.
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Affiliation(s)
- Huijun Lei
- Ministry of Education Frontiers Science Center for Precision Oncology, Cancer Centre and Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Taipa, Macau SAR, 999078, China
- Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, 310018, Zhejiang, China
- Department of Cancer Prevention, Zhejiang Cancer Hospital, Hangzhou, 310022, Zhejiang, China
| | - Jiaheng Li
- Ministry of Education Frontiers Science Center for Precision Oncology, Cancer Centre and Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Taipa, Macau SAR, 999078, China
| | - Bojin Zhao
- Ministry of Education Frontiers Science Center for Precision Oncology, Cancer Centre and Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Taipa, Macau SAR, 999078, China
| | - Si Hoi Kou
- Ministry of Education Frontiers Science Center for Precision Oncology, Cancer Centre and Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Taipa, Macau SAR, 999078, China
| | - Fengxia Xiao
- Ministry of Education Frontiers Science Center for Precision Oncology, Cancer Centre and Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Taipa, Macau SAR, 999078, China
| | - Tianhui Chen
- Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, 310018, Zhejiang, China.
- Department of Cancer Prevention, Zhejiang Cancer Hospital, Hangzhou, 310022, Zhejiang, China.
| | - San Ming Wang
- Ministry of Education Frontiers Science Center for Precision Oncology, Cancer Centre and Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Taipa, Macau SAR, 999078, China.
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6
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Yang S, Sun X, Jin L, Zhang M. Inferring language dispersal patterns with velocity field estimation. Nat Commun 2024; 15:190. [PMID: 38167834 PMCID: PMC10761963 DOI: 10.1038/s41467-023-44430-5] [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: 06/05/2023] [Accepted: 12/11/2023] [Indexed: 01/05/2024] Open
Abstract
Reconstructing the spatial evolution of languages can deepen our understanding of the demic diffusion and cultural spread. However, the phylogeographic approach that is frequently used to infer language dispersal patterns has limitations, primarily because the phylogenetic tree cannot fully explain the language evolution induced by the horizontal contact among languages, such as borrowing and areal diffusion. Here, we introduce the language velocity field estimation, which does not rely on the phylogenetic tree, to infer language dispersal trajectories and centre. Its effectiveness and robustness are verified through both simulated and empirical validations. Using language velocity field estimation, we infer the dispersal patterns of four agricultural language families and groups, encompassing approximately 700 language samples. Our results show that the dispersal trajectories of these languages are primarily compatible with population movement routes inferred from ancient DNA and archaeological materials, and their dispersal centres are geographically proximate to ancient homelands of agricultural or Neolithic cultures. Our findings highlight that the agricultural languages dispersed alongside the demic diffusions and cultural spreads during the past 10,000 years. We expect that language velocity field estimation could aid the spatial analysis of language evolution and further branch out into the studies of demographic and cultural dynamics.
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Affiliation(s)
- Sizhe Yang
- State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, and Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai, 200438, China
| | - Xiaoru Sun
- Human Phenome Institute, Fudan University, Shanghai, 200438, China
- Ministry of Education Key Laboratory of Contemporary Anthropology, Department of Anthropology and Human Genetics, School of Life Sciences, Fudan University, Shanghai, 200438, China
| | - Li Jin
- State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, and Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai, 200438, China.
- Human Phenome Institute, Fudan University, Shanghai, 200438, China.
| | - Menghan Zhang
- Institute of Modern Languages and Linguistics, Fudan University, Shanghai, 200433, China.
- Research Institute of Intelligent Complex Systems, Fudan University, Shanghai, 200433, China.
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7
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Lee SK, Kim SH, Ahnn J. Beethoven, Infected with Hepatitis B, Inspired the "Beethoven Virus.". Mol Cells 2023; 46:743-745. [PMID: 38052489 PMCID: PMC10701304 DOI: 10.14348/molcells.2023.0132] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2023] [Revised: 08/22/2023] [Accepted: 08/24/2023] [Indexed: 12/07/2023] Open
Affiliation(s)
- Sun-Kyung Lee
- Department of Life Sciences, Research Institute for Natural Sciences, Research Institute for Convergence of Basic Science, College of Natural Sciences, Hanyang University, Seoul 04763, Korea
| | - Seung Hyun Kim
- Department of Life Sciences, Research Institute for Natural Sciences, Research Institute for Convergence of Basic Science, College of Natural Sciences, Hanyang University, Seoul 04763, Korea
| | - Joohong Ahnn
- Department of Life Sciences, Research Institute for Natural Sciences, Research Institute for Convergence of Basic Science, College of Natural Sciences, Hanyang University, Seoul 04763, Korea
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8
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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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9
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Guevara E, Gopalan S, Massey DJ, Adegboyega M, Zhou W, Solis A, Anaya AD, Churchill SE, Feldblum J, Lawler RR. Getting it right: Teaching undergraduate biology to undermine racial essentialism. Biol Methods Protoc 2023; 8:bpad032. [PMID: 38023347 PMCID: PMC10674104 DOI: 10.1093/biomethods/bpad032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2023] [Revised: 11/03/2023] [Accepted: 11/10/2023] [Indexed: 12/01/2023] Open
Abstract
How we teach human genetics matters for social equity. The biology curriculum appears to be a crucial locus of intervention for either reinforcing or undermining students' racial essentialist views. The Mendelian genetic models dominating textbooks, particularly in combination with racially inflected language sometimes used when teaching about monogenic disorders, can increase middle and high school students' racial essentialism and opposition to policies to increase equity. These findings are of particular concern given the increasing spread of racist misinformation online and the misappropriation of human genomics research by white supremacists, who take advantage of low levels of genetics literacy in the general public. Encouragingly, however, teaching updated information about the geographical distribution of human genetic variation and the complex, multifactorial basis of most human traits, reduces students' endorsement of racial essentialism. The genetics curriculum is therefore a key tool in combating misinformation and scientific racism. Here, we describe a framework and example teaching materials for teaching students key concepts in genetics, human evolutionary history, and human phenotypic variation at the undergraduate level. This framework can be flexibly applied in biology and anthropology classes and adjusted based on time availability. Our goal is to provide undergraduate-level instructors with varying levels of expertise with a set of evidence-informed tools for teaching human genetics to combat scientific racism, including an evolving set of instructional resources, as well as learning goals and pedagogical approaches. Resources can be found at https://noto.li/YIlhZ5. Additionally, we hope to generate conversation about integrating modern genetics into the undergraduate curriculum, in light of recent findings about the risks and opportunities associated with teaching genetics.
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Affiliation(s)
- Elaine Guevara
- Department of Evolutionary Anthropology, Duke University, Durham, NC 27713, United States
| | - Shyamalika Gopalan
- Department of Evolutionary Anthropology, Duke University, Durham, NC 27713, United States
| | - Dashiell J Massey
- Department of Evolutionary Anthropology, Duke University, Durham, NC 27713, United States
| | - Mayowa Adegboyega
- Department of Evolutionary Anthropology, Duke University, Durham, NC 27713, United States
| | - Wen Zhou
- Department of Evolutionary Anthropology, Duke University, Durham, NC 27713, United States
- Department of Evolutionary Anthropology, Duke Kunshan University, Kunshan, Jiangsu 215316, China
| | - Alma Solis
- Department of Evolutionary Anthropology, Duke University, Durham, NC 27713, United States
| | - Alisha D Anaya
- Department of Evolutionary Anthropology, Duke University, Durham, NC 27713, United States
| | - Steven E Churchill
- Department of Evolutionary Anthropology, Duke University, Durham, NC 27713, United States
| | - Joseph Feldblum
- Department of Evolutionary Anthropology, Duke University, Durham, NC 27713, United States
| | - Richard R Lawler
- Department of Sociology and Anthropology, James Madison University, Harrisonburg, Virginia 22807, United States
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10
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Ávila-Arcos MC, Raghavan M, Schlebusch C. Going local with ancient DNA: A review of human histories from regional perspectives. Science 2023; 382:53-58. [PMID: 37797024 DOI: 10.1126/science.adh8140] [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: 05/27/2023] [Accepted: 09/05/2023] [Indexed: 10/07/2023]
Abstract
Ancient DNA (aDNA) has added a wealth of information about our species' history, including insights on genetic origins, migrations and gene flow, genetic admixture, and health and disease. Much early work has focused on continental-level questions, leaving many regional questions, especially those relevant to the Global South, comparatively underexplored. A few success stories of aDNA studies from smaller laboratories involve more local aspects of human histories and health in the Americas, Africa, Asia, and Oceania. In this Review, we cover some of these contributions by synthesizing finer-scale questions of importance to the archaeogenetics field, as well as to Indigenous and Descendant communities. We further highlight the potential of aDNA to uncover past histories in regions where colonialism has neglected the oral histories of oppressed peoples.
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Affiliation(s)
- María C Ávila-Arcos
- International Laboratory for Human Genome Research, Universidad Nacional Autónoma de México, Querétaro, Mexico
| | - Maanasa Raghavan
- Department of Human Genetics, University of Chicago, Chicago, IL, USA
| | - Carina Schlebusch
- Human Evolution, Department of Organismal Biology, Uppsala University, Uppsala, Sweden
- Palaeo-Research Institute, University of Johannesburg, Johannesburg, South Africa
- SciLifeLab, Uppsala, Sweden
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11
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Chen N, Nedoluzhko A. Ancient DNA: the past for the future. BMC Genomics 2023; 24:309. [PMID: 37291482 DOI: 10.1186/s12864-023-09396-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2023] [Accepted: 05/21/2023] [Indexed: 06/10/2023] Open
Abstract
The last decade has seen advancements in sequencing technologies and laboratory preparation protocols for ancient DNA (aDNA) that have rapidly been applied in multiple research areas thus enabling large-scale scientific research. Future research could also refine our understanding of the evolution of humans, non-human animals, plants, invertebrate specimens, and microorganisms.
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Affiliation(s)
- Ningbo Chen
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, 712100, China.
| | - Artem Nedoluzhko
- Paleogenomics Laboratory, European University at St. Petersburg, 6/1A Gagarinskaya Street, St. Petersburg, 191187, Russia.
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12
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Sørensen EF, Harris RA, Zhang L, Raveendran M, Kuderna LFK, Walker JA, Storer JM, Kuhlwilm M, Fontsere C, Seshadri L, Bergey CM, Burrell AS, Bergman J, Phillips-Conroy JE, Shiferaw F, Chiou KL, Chuma IS, Keyyu JD, Fischer J, Gingras MC, Salvi S, Doddapaneni H, Schierup MH, Batzer MA, Jolly CJ, Knauf S, Zinner D, Farh KKH, Marques-Bonet T, Munch K, Roos C, Rogers J. Genome-wide coancestry reveals details of ancient and recent male-driven reticulation in baboons. Science 2023; 380:eabn8153. [PMID: 37262153 DOI: 10.1126/science.abn8153] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2021] [Accepted: 09/27/2022] [Indexed: 06/03/2023]
Abstract
Baboons (genus Papio) are a morphologically and behaviorally diverse clade of catarrhine monkeys that have experienced hybridization between phenotypically and genetically distinct phylogenetic species. We used high-coverage whole-genome sequences from 225 wild baboons representing 19 geographic localities to investigate population genomics and interspecies gene flow. Our analyses provide an expanded picture of evolutionary reticulation among species and reveal patterns of population structure within and among species, including differential admixture among conspecific populations. We describe the first example of a baboon population with a genetic composition that is derived from three distinct lineages. The results reveal processes, both ancient and recent, that produced the observed mismatch between phylogenetic relationships based on matrilineal, patrilineal, and biparental inheritance. We also identified several candidate genes that may contribute to species-specific phenotypes.
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Affiliation(s)
- Erik F Sørensen
- Bioinformatics Research Centre, Aarhus University, 8000 Aarhus, Denmark
| | - R Alan Harris
- Human Genome Sequencing Center and Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Liye Zhang
- Primate Genetics Laboratory, German Primate Center, Leibniz Institute for Primate Research, 37077 Göttingen, Germany
| | - Muthuswamy Raveendran
- Human Genome Sequencing Center and Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Lukas F K Kuderna
- Institute of Evolutionary Biology (UPF-CSIC), PRBB, Dr. Aiguader 88, 08003 Barcelona, Spain
- Artificial Intelligence Lab, Illumina Inc., San Diego, CA 92122, USA
| | - Jerilyn A Walker
- Department of Biological Sciences, Louisiana State University, Baton Rouge, LA 70803, USA
| | | | - Martin Kuhlwilm
- Institute of Evolutionary Biology (UPF-CSIC), PRBB, Dr. Aiguader 88, 08003 Barcelona, Spain
- Department of Evolutionary Anthropology, University of Vienna, 1030 Vienna, Austria
- Human Evolution and Archaeological Sciences (HEAS), University of Vienna, 1030 Vienna, Austria
| | - Claudia Fontsere
- Institute of Evolutionary Biology (UPF-CSIC), PRBB, Dr. Aiguader 88, 08003 Barcelona, Spain
| | - Lakshmi Seshadri
- Primate Genetics Laboratory, German Primate Center, Leibniz Institute for Primate Research, 37077 Göttingen, Germany
| | - Christina M Bergey
- Department of Genetics, Human Genetics Institute of New Jersey, Rutgers University, Piscataway, NJ 08854, USA
| | - Andrew S Burrell
- Department of Anthropology, New York University, New York, NY 10003, USA
| | - Juraj Bergman
- Bioinformatics Research Centre, Aarhus University, 8000 Aarhus, Denmark
- Section for Ecoinformatics and Biodiversity, Department of Biology, Aarhus University, 8000 Aarhus C, Denmark
| | - Jane E Phillips-Conroy
- Department of Neuroscience, Washington University School of Medicine in St. Louis, St. Louis, MO 63110, USA
- Department of Anthropology, Washington University in St. Louis, St. Louis, MO 63130, USA
| | | | - Kenneth L Chiou
- Center for Evolution and Medicine, Arizona State University, Tempe, AZ 85281, USA
- School of Life Sciences, Arizona State University, Tempe, AZ 85281, USA
| | | | | | - Julia Fischer
- Cognitive Ethology Laboratory, German Primate Center, Leibniz Institute for Primate Research, 37077 Göttingen, Germany
- Department of Primate Cognition, Georg-August-Universität Göttingen, 37077 Göttingen, Germany
- Leibniz ScienceCampus Primate Cognition, 37077 Göttingen, Germany
| | - Marie-Claude Gingras
- Human Genome Sequencing Center and Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Sejal Salvi
- Human Genome Sequencing Center and Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Harshavardhan Doddapaneni
- Human Genome Sequencing Center and Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Mikkel H Schierup
- Bioinformatics Research Centre, Aarhus University, 8000 Aarhus, Denmark
| | - Mark A Batzer
- Department of Biological Sciences, Louisiana State University, Baton Rouge, LA 70803, USA
| | - Clifford J Jolly
- Department of Anthropology, New York University, New York, NY 10003, USA
| | - Sascha Knauf
- Institute of International Animal Health/One Health, Friedrich-Loeffler-Institut, Federal Research Institute for Animal Health, 17493 Greifswald-Insel Riems, Germany
| | - Dietmar Zinner
- Cognitive Ethology Laboratory, German Primate Center, Leibniz Institute for Primate Research, 37077 Göttingen, Germany
- Department of Primate Cognition, Georg-August-Universität Göttingen, 37077 Göttingen, Germany
- Leibniz ScienceCampus Primate Cognition, 37077 Göttingen, Germany
| | - Kyle K-H Farh
- Artificial Intelligence Lab, Illumina Inc., San Diego, CA 92122, USA
| | - Tomas Marques-Bonet
- Institute of Evolutionary Biology (UPF-CSIC), PRBB, Dr. Aiguader 88, 08003 Barcelona, Spain
- Catalan Institution of Research and Advanced Studies (ICREA), Passeig de Lluis Companys, 23, 08010 Barcelona, Spain
- CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology, Baldiri i Reixac 4, 08028 Barcelona, Spain
- Institut Catala de Paleontologia Miquel Crusafont, Universitat Autonoma de Barcelona, Edifici ICTA-ICP, cl Columnes s/n, 08193 Cerdanyola del Valles, Barcelona, Spain
| | - Kasper Munch
- Bioinformatics Research Centre, Aarhus University, 8000 Aarhus, Denmark
| | - Christian Roos
- Primate Genetics Laboratory, German Primate Center, Leibniz Institute for Primate Research, 37077 Göttingen, Germany
- Gene Bank of Primates, German Primate Center, Leibniz Institute for Primate Research, 37077 Göttingen, Germany
| | - Jeffrey Rogers
- Human Genome Sequencing Center and Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
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13
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Abstract
Autoimmune diseases display a high degree of comorbidity within individuals and families, suggesting shared risk factors. Over the past 15 years, genome-wide association studies have established the polygenic basis of these common conditions and revealed widespread sharing of genetic effects, indicative of a shared immunopathology. Despite ongoing challenges in determining the precise genes and molecular consequences of these risk variants, functional experiments and integration with multimodal genomic data are providing valuable insights into key immune cells and pathways driving these diseases, with potential therapeutic implications. Moreover, genetic studies of ancient populations are shedding light on the contribution of pathogen-driven selection pressures to the increased prevalence of autoimmune disease. This Review summarizes the current understanding of autoimmune disease genetics, including shared effects, mechanisms, and evolutionary origins.
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Affiliation(s)
- Adil Harroud
- Department of Neurology and Neurosurgery, McGill University, Montréal, Quebec, Canada
- Department of Human Genetics, McGill University, Montréal, Quebec, Canada
- The Neuro (Montreal Neurological Institute and Hospital), McGill University, Montréal, Quebec, Canada
| | - David A Hafler
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
- Department of Immunobiology, Yale School of Medicine, New Haven, CT, USA
- Broad Institute of MIT and Harvard University, Cambridge, MA, USA
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14
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Kopp GH, Sithaldeen R, Trede F, Grathwol F, Roos C, Zinner D. A Comprehensive Overview of Baboon Phylogenetic History. Genes (Basel) 2023; 14:genes14030614. [PMID: 36980887 PMCID: PMC10048742 DOI: 10.3390/genes14030614] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2023] [Revised: 02/13/2023] [Accepted: 02/17/2023] [Indexed: 03/05/2023] Open
Abstract
Baboons (genus Papio) are an intriguing study system to investigate complex evolutionary processes and the evolution of social systems. An increasing number of studies over the last 20 years has shown that considerable incongruences exist between phylogenies based on morphology, mitochondrial, and nuclear sequence data of modern baboons, and hybridization and introgression have been suggested as the main drivers of these patterns. Baboons, therefore, present an excellent opportunity to study these phenomena and their impact on speciation. Advances both in geographic and genomic coverage provide increasing details on the complexity of the phylogeography of baboons. Here, we compile the georeferenced genetic data of baboons and review the current knowledge on baboon phylogeny, discuss the evolutionary processes that may have shaped the patterns that we observe today, and propose future avenues for research.
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Affiliation(s)
- Gisela H. Kopp
- Zukunftskolleg, University of Konstanz, 78457 Konstanz, Germany
- Department of Biology, University of Konstanz, 78457 Konstanz, Germany
- Centre for the Advanced Study of Collective Behaviour, University of Konstanz, 78457 Konstanz, Germany
- Department of Migration, Max Planck Institute of Animal Behavior, 78315 Radolfzell, Germany
- Correspondence:
| | - Riashna Sithaldeen
- Academic Development Programme, Centre for Higher Education and Development, University of Cape Town, Cape Town 7700, South Africa
| | - Franziska Trede
- Cognitive Ethology Laboratory, German Primate Center, Leibniz Institute for Primate Research, 37077 Göttingen, Germany
| | - Franziska Grathwol
- Department of Biology, University of Konstanz, 78457 Konstanz, Germany
- Department of Migration, Max Planck Institute of Animal Behavior, 78315 Radolfzell, Germany
| | - Christian Roos
- Gene Bank of Primates and Primate Genetics Laboratory, German Primate Center, Leibniz Institute for Primate Research, 37077 Göttingen, Germany
| | - Dietmar Zinner
- Cognitive Ethology Laboratory, German Primate Center, Leibniz Institute for Primate Research, 37077 Göttingen, Germany
- Department of Primate Cognition, Georg-August-University, 37073 Göttingen, Germany
- Leibniz-ScienceCampus Primate Cognition, 37077 Göttingen, Germany
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15
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Montgomery LM, Supernant K. Archaeology in 2021: Repatriation, reclamation, and reckoning with historical trauma. AMERICAN ANTHROPOLOGIST 2022. [DOI: 10.1111/aman.13778] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/01/2022]
Affiliation(s)
- Lindsay M. Montgomery
- Department of Anthropology and Centre for Indigenous Studies University of Toronto Canada
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16
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Collen EJ, Johar AS, Teixeira JC, Llamas B. The immunogenetic impact of European colonization in the Americas. Front Genet 2022; 13:918227. [PMID: 35991555 PMCID: PMC9388791 DOI: 10.3389/fgene.2022.918227] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Accepted: 07/07/2022] [Indexed: 11/13/2022] Open
Abstract
The introduction of pathogens originating from Eurasia into the Americas during early European contact has been associated with high mortality rates among Indigenous peoples, likely contributing to their historical and precipitous population decline. However, the biological impacts of imported infectious diseases and resulting epidemics, especially in terms of pathogenic effects on the Indigenous immunity, remain poorly understood and highly contentious to this day. Here, we examine multidisciplinary evidence underpinning colonization-related immune genetic change, providing contextualization from anthropological studies, paleomicrobiological evidence of contrasting host-pathogen coevolutionary histories, and the timings of disease emergence. We further summarize current studies examining genetic signals reflecting post-contact Indigenous population bottlenecks, admixture with European and other populations, and the putative effects of natural selection, with a focus on ancient DNA studies and immunity-related findings. Considering current genetic evidence, together with a population genetics theoretical approach, we show that post-contact Indigenous immune adaptation, possibly influenced by selection exerted by introduced pathogens, is highly complex and likely to be affected by multifactorial causes. Disentangling putative adaptive signals from those of genetic drift thus remains a significant challenge, highlighting the need for the implementation of population genetic approaches that model the short time spans and complex demographic histories under consideration. This review adds to current understandings of post-contact immunity evolution in Indigenous peoples of America, with important implications for bettering our understanding of human adaptation in the face of emerging infectious diseases.
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Affiliation(s)
- Evelyn Jane Collen
- Australian Centre for Ancient DNA, School of Biological Sciences, University of Adelaide, Adelaide, SA, Australia
- *Correspondence: Evelyn Jane Collen, ; Bastien Llamas,
| | - Angad Singh Johar
- Australian Centre for Ancient DNA, School of Biological Sciences, University of Adelaide, Adelaide, SA, Australia
- School of Mathematics and Statistics, The University of Melbourne, Parkville, VIC, Australia
| | - João C. Teixeira
- Australian Centre for Ancient DNA, School of Biological Sciences, University of Adelaide, Adelaide, SA, Australia
- School of Culture History and Language, The Australian National University, Canberra, ACT, Australia
- Centre of Excellence for Australian Biodiversity and Heritage (CABAH), School of Biological Sciences, University of Adelaide, Adelaide, SA, Australia
| | - Bastien Llamas
- Australian Centre for Ancient DNA, School of Biological Sciences, University of Adelaide, Adelaide, SA, Australia
- Centre of Excellence for Australian Biodiversity and Heritage (CABAH), School of Biological Sciences, University of Adelaide, Adelaide, SA, Australia
- National Centre for Indigenous Genomics, Australian National University, Canberra, ACT, Australia
- Telethon Kids Institute, Indigenous Genomics Research Group, Adelaide, SA, Australia
- *Correspondence: Evelyn Jane Collen, ; Bastien Llamas,
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17
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Fu Q. Insights into evolutionary dynamics of East Asians through Ancient DNA. CHINESE SCIENCE BULLETIN-CHINESE 2022. [DOI: 10.1360/tb-2022-0569] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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18
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Liu Y, Bennett EA, Fu Q. Evolving ancient DNA techniques and the future of human history. Cell 2022; 185:2632-2635. [PMID: 35868268 DOI: 10.1016/j.cell.2022.06.009] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Revised: 05/31/2022] [Accepted: 06/06/2022] [Indexed: 11/28/2022]
Abstract
Ancient DNA (aDNA) techniques applied to human genomics have significantly advanced in the past decade, enabling large-scale aDNA research, sometimes independent of human remains. This commentary reviews the major milestones of aDNA techniques and explores future directions to expand the scope of aDNA research and insights into present-day human health.
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Affiliation(s)
- Yichen Liu
- Key Laboratory of Vertebrate Evolution and Human Origins, Institute of Vertebrate Paleontology and Paleoanthropology, Center for Excellence in Life and Paleoenvironment, Chinese Academy of Sciences, Beijing 100044, China; Shanghai Qi Zhi Institute, Shanghai 200232, China
| | - E Andrew Bennett
- Key Laboratory of Vertebrate Evolution and Human Origins, Institute of Vertebrate Paleontology and Paleoanthropology, Center for Excellence in Life and Paleoenvironment, Chinese Academy of Sciences, Beijing 100044, China; Shanghai Qi Zhi Institute, Shanghai 200232, China
| | - Qiaomei Fu
- Key Laboratory of Vertebrate Evolution and Human Origins, Institute of Vertebrate Paleontology and Paleoanthropology, Center for Excellence in Life and Paleoenvironment, Chinese Academy of Sciences, Beijing 100044, China; Shanghai Qi Zhi Institute, Shanghai 200232, China; University of Chinese Academy of Sciences, Beijing 100049, China.
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19
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Polygenic score accuracy in ancient samples: Quantifying the effects of allelic turnover. PLoS Genet 2022; 18:e1010170. [PMID: 35522704 PMCID: PMC9116686 DOI: 10.1371/journal.pgen.1010170] [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: 09/29/2021] [Revised: 05/18/2022] [Accepted: 03/26/2022] [Indexed: 11/19/2022] Open
Abstract
Polygenic scores link the genotypes of ancient individuals to their phenotypes, which are often unobservable, offering a tantalizing opportunity to reconstruct complex trait evolution. In practice, however, interpretation of ancient polygenic scores is subject to numerous assumptions. For one, the genome-wide association (GWA) studies from which polygenic scores are derived, can only estimate effect sizes for loci segregating in contemporary populations. Therefore, a GWA study may not correctly identify all loci relevant to trait variation in the ancient population. In addition, the frequencies of trait-associated loci may have changed in the intervening years. Here, we devise a theoretical framework to quantify the effect of this allelic turnover on the statistical properties of polygenic scores as functions of population genetic dynamics, trait architecture, power to detect significant loci, and the age of the ancient sample. We model the allele frequencies of loci underlying trait variation using the Wright-Fisher diffusion, and employ the spectral representation of its transition density to find analytical expressions for several error metrics, including the expected sample correlation between the polygenic scores of ancient individuals and their true phenotypes, referred to as polygenic score accuracy. Our theory also applies to a two-population scenario and demonstrates that allelic turnover alone may explain a substantial percentage of the reduced accuracy observed in cross-population predictions, akin to those performed in human genetics. Finally, we use simulations to explore the effects of recent directional selection, a bias-inducing process, on the statistics of interest. We find that even in the presence of bias, weak selection induces minimal deviations from our neutral expectations for the decay of polygenic score accuracy. By quantifying the limitations of polygenic scores in an explicit evolutionary context, our work lays the foundation for the development of more sophisticated statistical procedures to analyze both temporally and geographically resolved polygenic scores.
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20
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Heraclides A, Fernández-Domínguez E. Mitochondrial DNA Consensus Calling and Quality Filtering for Constructing Ancient Human Mitogenomes: Comparison of Two Widely Applied Methods. Int J Mol Sci 2022; 23:4651. [PMID: 35563041 PMCID: PMC9104972 DOI: 10.3390/ijms23094651] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Revised: 04/18/2022] [Accepted: 04/19/2022] [Indexed: 02/05/2023] Open
Abstract
Retrieving high-quality endogenous ancient DNA (aDNA) poses several challenges, including low molecular copy number, high rates of fragmentation, damage at read termini, and potential presence of exogenous contaminant DNA. All these factors complicate a reliable reconstruction of consensus aDNA sequences in reads from high-throughput sequencing platforms. Here, we report findings from a thorough evaluation of two alternative tools (ANGSD and schmutzi) aimed at overcoming these issues and constructing high-quality ancient mitogenomes. Raw genomic data (BAM/FASTQ) from a total of 17 previously published whole ancient human genomes ranging from the 14th to the 7th millennium BCE were retrieved and mitochondrial consensus sequences were reconstructed using different quality filters, with their accuracy measured and compared. Moreover, the influence of different sequence parameters (number of reads, sequenced bases, mean coverage, and rate of deamination and contamination) as predictors of derived sequence quality was evaluated. Complete mitogenomes were successfully reconstructed for all ancient samples, and for the majority of them, filtering substantially improved mtDNA consensus calling and haplogroup prediction. Overall, the schmutzi pipeline, which estimates and takes into consideration exogenous contamination, appeared to have the edge over the much faster and user-friendly alternative method (ANGSD) in moderate to high coverage samples (>1,000,000 reads). ANGSD, however, through its read termini trimming filter, showed better capabilities in calling the consensus sequence from low-quality samples. Among all the predictors of overall sample quality examined, the strongest correlation was found for the available number of sequence reads and bases. In the process, we report a previously unassigned haplogroup (U3b) for an Early Chalcolithic individual from Southern Anatolia/Northern Levant.
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Affiliation(s)
- Alexandros Heraclides
- Department of Health Sciences, European University Cyprus, Diogenis Str. 6, Nicosia 2404, Cyprus
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21
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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: 0] [Impact Index Per Article: 0] [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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22
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Fischer CE, Pemonge MH, Ducoussau I, Arzelier A, Rivollat M, Santos F, Barrand Emam H, Bertaud A, Beylier A, Ciesielski E, Dedet B, Desenne S, Duday H, Chenal F, Gailledrat E, Goepfert S, Gorgé O, Gorgues A, Kuhnle G, Lambach F, Lefort A, Mauduit A, Maziere F, Oudry S, Paresys C, Pinard E, Plouin S, Richard I, Roth-Zehner M, Roure R, Thevenet C, Thomas Y, Rottier S, Deguilloux MF, Pruvost M. Origin and mobility of Iron Age Gaulish groups in present-day France revealed through archaeogenomics. iScience 2022; 25:104094. [PMID: 35402880 PMCID: PMC8983337 DOI: 10.1016/j.isci.2022.104094] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Revised: 02/17/2022] [Accepted: 03/13/2022] [Indexed: 11/17/2022] Open
Abstract
The Iron Age period occupies an important place in French history because the Gauls are regularly presented as the direct ancestors of the extant French population. We documented here the genomic diversity of Iron Age communities originating from six French regions. The 49 acquired genomes permitted us to highlight an absence of discontinuity between Bronze Age and Iron Age groups in France, lending support to a cultural transition linked to progressive local economic changes rather than to a massive influx of allochthone groups. Genomic analyses revealed strong genetic homogeneity among the regional groups associated with distinct archaeological cultures. This genomic homogenization appears to be linked to individuals' mobility between regions and gene flow with neighbouring groups from England and Spain. Thus, the results globally support a common genomic legacy for the Iron Age population of modern-day France that could be linked to recurrent gene flow between culturally differentiated communities.
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Affiliation(s)
- Claire-Elise Fischer
- UMR 5199 PACEA, CNRS, Université de Bordeaux, 33615 Pessac, France
- Corresponding author
| | | | - Isaure Ducoussau
- UMR 5199 PACEA, CNRS, Université de Bordeaux, 33615 Pessac, France
| | - Ana Arzelier
- UMR 5199 PACEA, CNRS, Université de Bordeaux, 33615 Pessac, France
| | - Maïté Rivollat
- UMR 5199 PACEA, CNRS, Université de Bordeaux, 33615 Pessac, France
- Department of Archaeogenetics, Max Planck Institue for Evolutionary Anthropology, Deutscher Platz 6, 04103 Leipzig, Germany
| | - Frederic Santos
- UMR 5199 PACEA, CNRS, Université de Bordeaux, 33615 Pessac, France
| | - Hélène Barrand Emam
- ANTEA-Archéologie, Habsheim, France
- UMR7044 Archimède, CNRS Université de Strasbourg et Université de Haute-Alsace, Strasbourg et Mulhouse, France
| | - Alexandre Bertaud
- UMR-5607 Ausonius, Université Bordeaux Montaigne, Maison de l’Archéologie, 8 Esplanade des Antilles, 33600 Pessac, France
| | - Alexandre Beylier
- Service Archéologie Sète Agglopôle Mediterranée, 34110 Frontignan, France
- UMR 5140 - ASM, Université Paul Valéry Montpellier 3, CNRS, Ministère de la Culture, Inrap, 34000 Montpellier, France
| | - Elsa Ciesielski
- UMR 5140 - ASM, Université Paul Valéry Montpellier 3, CNRS, Ministère de la Culture, Inrap, 34000 Montpellier, France
| | - Bernard Dedet
- UMR 5140 - ASM, Université Paul Valéry Montpellier 3, CNRS, Ministère de la Culture, Inrap, 34000 Montpellier, France
| | - Sophie Desenne
- INRAP, Institut National de Recherche Archéologiques Préventives, 75685 Paris Cedex 14, France
- UMR 8215 Trajectoires, CNRS, Université Paris 1 Pantheon Sorbonne, 92023 Nanterre, France
| | - Henri Duday
- UMR 5199 PACEA, CNRS, Université de Bordeaux, 33615 Pessac, France
| | - Fanny Chenal
- UMR7044 Archimède, CNRS Université de Strasbourg et Université de Haute-Alsace, Strasbourg et Mulhouse, France
- INRAP, Institut National de Recherche Archéologiques Préventives, 75685 Paris Cedex 14, France
| | - Eric Gailledrat
- UMR 5140 - ASM, Université Paul Valéry Montpellier 3, CNRS, Ministère de la Culture, Inrap, 34000 Montpellier, France
| | - Sébastien Goepfert
- ANTEA-Archéologie, Habsheim, France
- UMR7044 Archimède, CNRS Université de Strasbourg et Université de Haute-Alsace, Strasbourg et Mulhouse, France
| | - Olivier Gorgé
- Institut de Recherche Biomédicale des Armées, Place Général Valérie André, 91220 Brétigny-sur-Orge, France
| | - Alexis Gorgues
- UMR-5607 Ausonius, Université Bordeaux Montaigne, Maison de l’Archéologie, 8 Esplanade des Antilles, 33600 Pessac, France
| | - Gertrud Kuhnle
- Landesamt für Denkmalpflege im Regierungspräsidium Stuttgart Referat 84.2, Operative Archäologie Dienstsitz Freiburg Günterstalstraße 67, 79100 Freiburg im Breisgau, Germany
| | - François Lambach
- UMR 5199 PACEA, CNRS, Université de Bordeaux, 33615 Pessac, France
| | - Anthony Lefort
- INRAP, Institut National de Recherche Archéologiques Préventives, 75685 Paris Cedex 14, France
| | | | - Florent Maziere
- UMR 5140 - ASM, Université Paul Valéry Montpellier 3, CNRS, Ministère de la Culture, Inrap, 34000 Montpellier, France
- INRAP, Institut National de Recherche Archéologiques Préventives, 75685 Paris Cedex 14, France
| | - Sophie Oudry
- INRAP, Institut National de Recherche Archéologiques Préventives, 75685 Paris Cedex 14, France
- UMR-7268 ADES, CNRS, Université Aix-Marseille, EFS, 13015 Marseille, France
| | - Cécile Paresys
- INRAP, Institut National de Recherche Archéologiques Préventives, 75685 Paris Cedex 14, France
- UMR 7264 CEPAM, CNRS Université Nice Sophia Antipolis, 06357 Nice Cedex 4, France
| | - Estelle Pinard
- INRAP, Institut National de Recherche Archéologiques Préventives, 75685 Paris Cedex 14, France
- UMR 8215 Trajectoires, CNRS, Université Paris 1 Pantheon Sorbonne, 92023 Nanterre, France
| | - Suzanne Plouin
- UMR7044 Archimède, CNRS Université de Strasbourg et Université de Haute-Alsace, Strasbourg et Mulhouse, France
| | - Isabelle Richard
- INRAP, Institut National de Recherche Archéologiques Préventives, 75685 Paris Cedex 14, France
- UMR 7264 CEPAM, CNRS Université Nice Sophia Antipolis, 06357 Nice Cedex 4, France
| | - Muriel Roth-Zehner
- UMR7044 Archimède, CNRS Université de Strasbourg et Université de Haute-Alsace, Strasbourg et Mulhouse, France
- Archéologie Alsace, 11 Rue Champollion, 67600 Sélestat, France
| | - Réjane Roure
- UMR 5140 - ASM, Université Paul Valéry Montpellier 3, CNRS, Ministère de la Culture, Inrap, 34000 Montpellier, France
| | - Corinne Thevenet
- INRAP, Institut National de Recherche Archéologiques Préventives, 75685 Paris Cedex 14, France
- UMR 8215 Trajectoires, CNRS, Université Paris 1 Pantheon Sorbonne, 92023 Nanterre, France
| | - Yohann Thomas
- UMR7044 Archimède, CNRS Université de Strasbourg et Université de Haute-Alsace, Strasbourg et Mulhouse, France
- INRAP, Institut National de Recherche Archéologiques Préventives, 75685 Paris Cedex 14, France
| | - Stéphane Rottier
- UMR 5199 PACEA, CNRS, Université de Bordeaux, 33615 Pessac, France
| | | | - Mélanie Pruvost
- UMR 5199 PACEA, CNRS, Université de Bordeaux, 33615 Pessac, France
- Corresponding author
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23
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Menéndez LP, Paul KS, de la Fuente C, Almeida T, Delgado M, Figueiro G, Jorgensen K, Kuzminsky S, López-Sosa MC, Nichols J, Roksandic M, Scott GR, O'Rourke D, Hubbe M. Towards an interdisciplinary perspective for the study of human expansions and biocultural diversity in the Americas. Evol Anthropol 2022; 31:62-68. [PMID: 35043498 DOI: 10.1002/evan.21937] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Revised: 12/20/2021] [Accepted: 12/28/2021] [Indexed: 11/06/2022]
Affiliation(s)
- Lumila P Menéndez
- Department of Anthropology of the Americas, University of Bonn, Bonn, Germany.,Theoretical Biology Unit, Department of Evolutionary Biology, University of Vienna, Vienna, Austria
| | - Kathleen S Paul
- Department of Anthropology, University of Arkansas, Fayetteville, Arkansas, USA
| | | | - Tatiana Almeida
- Clinical Laboratory & BigData and Analytics, Hospital Israelita Albert Einstein, São Paulo, Brazil.,Laboratório de Estudos em Antropologia Biológica, Bioarqueologia e Evolução Humana, Universidade Federal do Rio Grande, Rio Grande, Brazil
| | - Miguel Delgado
- Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), República Argentina (CONICET), División Antropología, Facultad de Ciencias Naturales y Museo, Universidad Nacional de La Plata, La Plata, República Argentina.,Ministry of Education Key Laboratory of Contemporary Anthropology Collaborative Innovation Center of Genetics and Development, School of Life Sciences and Human Phenome Institute Fudan University, Shanghai, China
| | - Gonzalo Figueiro
- Departamento de Antropología Biológica, Universidad de la República, Montevideo, Uruguay
| | - Kelsey Jorgensen
- Department of Anthropology, Wayne State University, Detroit, Michigan, USA
| | - Susan Kuzminsky
- Department of Anthropology and Applied Archaeology, Eastern New Mexico University, Portales, New Mexico, USA.,Anthropology Department, University of California, Santa Cruz, California, USA
| | | | - Johanna Nichols
- Department of Slavic Languages and Literatures, University of California, Berkeley, California, USA
| | - Mirjana Roksandic
- Department of Anthropology, University of Winnipeg, Winnipeg, Manitoba, Canada
| | | | - Dennis O'Rourke
- Department of Anthropology, University of Kansas, Lawrence, Kansas, USA
| | - Mark Hubbe
- Department of Anthropology, Ohio State University, Columbus, Ohio, USA.,Instituto de Arqueología y Antropología, Universidad Católica del Norte, Antofagasta, Chile
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24
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Wang H, Chen M, Chen C, Fang Y, Cui W, Lei F, Zhu B. Genetic Background of Kirgiz Ethnic Group From Northwest China Revealed by Mitochondrial DNA Control Region Sequences on Massively Parallel Sequencing. Front Genet 2022; 13:729514. [PMID: 35281833 PMCID: PMC8906502 DOI: 10.3389/fgene.2022.729514] [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: 06/23/2021] [Accepted: 01/24/2022] [Indexed: 11/23/2022] Open
Abstract
The mitochondrial DNA (mtDNA) has been used to trace population evolution and apply to forensic identification due to the characteristics including lack of recombination, higher copy number and matrilineal inheritance comparing with nuclear genome DNA. In this study, mtDNA control region sequences of 91 Kirgiz individuals from the Northwest region of China were sequenced to identify genetic polymorphisms and gain insight into the genetic background of the Kirgiz ethnic group. MtDNA control region sequences of Kirgiz individuals presented relatively high genetic polymorphisms. The 1,122 bp sequences of mtDNA control region could differ among unrelated Kirgiz individuals, which suggested the mtDNA control region sequences have a good maternal pedigree tracing capability among different Kirgiz individuals. The neutrality test, mismatch distribution, Bayesian phylogenetic inference, Bayesian skyline analysis, and the median network analyses showed that the Kirgiz group might occurred population expansion, and the expansion could be observed at about ∼53.41 kilo years ago (kya) when ancestries of modern humans began to thrive in Eurasia. The pairwise population comparisons, principal component analyses, and median network analyses were performed based on haplogroup frequencies or mtDNA control region sequences of 5,886 individuals from the Kirgiz group and the 48 reference populations all over the world. And the most homologous haplotypes were found between Kirgiz individuals and the East Asian individuals, which indicated that the Kirgiz group might have gene exchanges with the East Asian populations.
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Affiliation(s)
- Hongdan Wang
- Key Laboratory of Shaanxi Province for Craniofacial Precision Medicine Research, College of Stomatology, Xi'an Jiaotong University, Xi'an, China.,Medical Genetic Institute of Henan Province, Henan Provincial People's Hospital, Zhengzhou University People's Hospital, Zhengzhou, China
| | - Man Chen
- Guangzhou Key Laboratory of Forensic Multi-Omics for Precision Identification, School of Forensic Medicine, Southern Medical University, Guangzhou, China.,Multi-Omics Innovative Research Center of Forensic Identification, Department of Forensic Genetics, School of Forensic Medicine, Southern Medical University, Guangzhou, China
| | - Chong Chen
- Key Laboratory of Shaanxi Province for Craniofacial Precision Medicine Research, College of Stomatology, Xi'an Jiaotong University, Xi'an, China.,College of Forensic Medicine, Xi'an Jiaotong University, Xi'an, China
| | - Yating Fang
- Guangzhou Key Laboratory of Forensic Multi-Omics for Precision Identification, School of Forensic Medicine, Southern Medical University, Guangzhou, China.,Multi-Omics Innovative Research Center of Forensic Identification, Department of Forensic Genetics, School of Forensic Medicine, Southern Medical University, Guangzhou, China
| | - Wei Cui
- Guangzhou Key Laboratory of Forensic Multi-Omics for Precision Identification, School of Forensic Medicine, Southern Medical University, Guangzhou, China.,Multi-Omics Innovative Research Center of Forensic Identification, Department of Forensic Genetics, School of Forensic Medicine, Southern Medical University, Guangzhou, China
| | - Fanzhang Lei
- Guangzhou Key Laboratory of Forensic Multi-Omics for Precision Identification, School of Forensic Medicine, Southern Medical University, Guangzhou, China.,Multi-Omics Innovative Research Center of Forensic Identification, Department of Forensic Genetics, School of Forensic Medicine, Southern Medical University, Guangzhou, China
| | - Bofeng Zhu
- Key Laboratory of Shaanxi Province for Craniofacial Precision Medicine Research, College of Stomatology, Xi'an Jiaotong University, Xi'an, China.,Guangzhou Key Laboratory of Forensic Multi-Omics for Precision Identification, School of Forensic Medicine, Southern Medical University, Guangzhou, China.,Multi-Omics Innovative Research Center of Forensic Identification, Department of Forensic Genetics, School of Forensic Medicine, Southern Medical University, Guangzhou, China.,College of Forensic Medicine, Xi'an Jiaotong University, Xi'an, China
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25
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Liu Y, Xie J, Wang M, Liu C, Zhu J, Zou X, Li W, Wang L, Leng C, Xu Q, Yeh HY, Wang CC, Wen X, Liu C, He G. Genomic Insights Into the Population History and Biological Adaptation of Southwestern Chinese Hmong-Mien People. Front Genet 2022; 12:815160. [PMID: 35047024 PMCID: PMC8762323 DOI: 10.3389/fgene.2021.815160] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Accepted: 12/03/2021] [Indexed: 01/19/2023] Open
Abstract
Hmong-Mien (HM) -speaking populations, widely distributed in South China, the north of Thailand, Laos, and Vietnam, have experienced different settlement environments, dietary habits, and pathogenic exposure. However, their specific biological adaptation remained largely uncharacterized, which is important in the population evolutionary genetics and Trans-Omics for regional Precision Medicine. Besides, the origin and genetic diversity of HM people and their phylogenetic relationship with surrounding modern and ancient populations are also unknown. Here, we reported genome-wide SNPs in 52 representative Miao people and combined them with 144 HM people from 13 geographically representative populations to characterize the full genetic admixture and adaptive landscape of HM speakers. We found that obvious genetic substructures existed in geographically different HM populations; one localized in the HM clines, and others possessed affinity with Han Chinese. We also identified one new ancestral lineage specifically existed in HM people, which spatially distributed from Sichuan and Guizhou in the north to Thailand in the south. The sharing patterns of the newly identified homogenous ancestry component combined the estimated admixture times via the decay of linkage disequilibrium and haplotype sharing in GLOBETROTTER suggested that the modern HM-speaking populations originated from Southwest China and migrated southward in the historic period, which is consistent with the reconstructed phenomena of linguistic and archeological documents. Additionally, we identified specific adaptive signatures associated with several important human nervous system biological functions. Our pilot work emphasized the importance of anthropologically informed sampling and deeply genetic structure reconstruction via whole-genome sequencing in the next step in the deep Chinese Population Genomic Diversity Project (CPGDP), especially in the regions with rich ethnolinguistic diversity.
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Affiliation(s)
- Yan Liu
- School of Basic Medical Sciences, North Sichuan Medical College, Nanchong, China.,Medical Imaging Key Laboratory of Sichuan Province, North Sichuan Medical College, Nanchong, China
| | - Jie Xie
- School of Basic Medical Sciences, North Sichuan Medical College, Nanchong, China
| | - Mengge Wang
- Guangzhou Forensic Science Institute, Guangzhou, China.,Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
| | - Changhui Liu
- Guangzhou Forensic Science Institute, Guangzhou, China
| | - Jingrong Zhu
- Department of Anthropology and Ethnology, Xiamen University, Xiamen, China
| | - Xing Zou
- College of Medicine, Chongqing University, Chongqing, China
| | - Wenshan Li
- College of Medical Imaging, North Sichuan Medical College, Nanchong, China
| | - Lin Wang
- College of Clinical Medicine, North Sichuan Medical College, Nanchong, China
| | - Cuo Leng
- College of Medical Imaging, North Sichuan Medical College, Nanchong, China
| | - Quyi Xu
- Guangzhou Forensic Science Institute, Guangzhou, China
| | - Hui-Yuan Yeh
- School of Humanities, Nanyang Technological University, Singapore, Singapore
| | - Chuan-Chao Wang
- State Key Laboratory of Cellular Stress Biology, National Institute for Data Science in Health and Medicine, School of Life Sciences, Xiamen University, Xiamen, China.,Department of Anthropology and Ethnology, Institute of Anthropology, School of Sociology and Anthropology, Xiamen University, Xiamen, China.,State Key Laboratory of Marine Environmental Science, Xiamen University, Xiamen, China
| | - Xiaohong Wen
- School of Basic Medical Sciences, North Sichuan Medical College, Nanchong, China
| | - Chao Liu
- Guangzhou Forensic Science Institute, Guangzhou, China.,Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
| | - Guanglin He
- School of Humanities, Nanyang Technological University, Singapore, Singapore.,State Key Laboratory of Cellular Stress Biology, National Institute for Data Science in Health and Medicine, School of Life Sciences, Xiamen University, Xiamen, China.,Department of Anthropology and Ethnology, Institute of Anthropology, School of Sociology and Anthropology, Xiamen University, Xiamen, China.,State Key Laboratory of Marine Environmental Science, Xiamen University, Xiamen, China
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