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Wang Z, Wang M, Hu L, He G, Nie S. Evolutionary profiles and complex admixture landscape in East Asia: New insights from modern and ancient Y chromosome variation perspectives. Heliyon 2024; 10:e30067. [PMID: 38756579 PMCID: PMC11096704 DOI: 10.1016/j.heliyon.2024.e30067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Revised: 04/08/2024] [Accepted: 04/18/2024] [Indexed: 05/18/2024] Open
Abstract
Human Y-chromosomes are characterized by nonrecombination and uniparental inheritance, carrying traces of human history evolution and admixture. Large-scale population-specific genomic sources based on advanced sequencing technologies have revolutionized our understanding of human Y chromosome diversity and its anthropological and forensic applications. Here, we reviewed and meta-analyzed the Y chromosome genetic diversity of modern and ancient people from China and summarized the patterns of founding lineages of spatiotemporally different populations associated with their origin, expansion, and admixture. We emphasized the strong association between our identified founding lineages and language-related human dispersal events correlated with the Sino-Tibetan, Altaic, and southern Chinese multiple-language families related to the Hmong-Mien, Tai-Kadai, Austronesian, and Austro-Asiatic languages. We subsequently summarize the recent advances in translational applications in forensic and anthropological science, including paternal biogeographical ancestry inference (PBGAI), surname investigation, and paternal history reconstruction. Whole-Y sequencing or high-resolution panels with high coverage of terminal Y chromosome lineages are essential for capturing the genomic diversity of ethnolinguistically diverse East Asians. Generally, we emphasized the importance of including more ethnolinguistically diverse, underrepresented modern and spatiotemporally different ancient East Asians in human genetic research for a comprehensive understanding of the paternal genetic landscape of East Asians with a detailed time series and for the reconstruction of a reference database in the PBGAI, even including new technology innovations of Telomere-to-Telomere (T2T) for new genetic variation discovery.
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Affiliation(s)
- Zhiyong Wang
- School of Forensic Medicine, Kunming Medical University, Kunming, 650500, China
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610000, China
- Center for Archaeological Science, Sichuan University, Chengdu, 610000, China
| | - Mengge Wang
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610000, China
- Center for Archaeological Science, Sichuan University, Chengdu, 610000, China
- Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510275, China
| | - Liping Hu
- School of Forensic Medicine, Kunming Medical University, Kunming, 650500, China
| | - Guanglin He
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610000, China
- Center for Archaeological Science, Sichuan University, Chengdu, 610000, China
| | - Shengjie Nie
- School of Forensic Medicine, Kunming Medical University, Kunming, 650500, China
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Zhou J, Zhang X, Li X, Sui J, Zhang S, Zhong H, Zhang Q, Zhang X, Huang H, Wen Y. Genetic structure and demographic history of Northern Han people in Liaoning Province inferred from genome-wide array data. Front Ecol Evol 2022. [DOI: 10.3389/fevo.2022.1014024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Abstract
In this study, we used typical and advanced population genetic analysis methods [principal component analysis (PCA), ADMIXTURE, FST, f3-statistics, f4-statistics, qpAdm/qpWave, qpGraph, ALDER (Admixture-induced Linkage Disequilibrium for Evolutionary Relationships) and TreeMix] to explore the genetic structure of 80 Han individuals from four different cities in Liaoning Province and reconstruct their demographic history based on the newly generated genome-wide data. We found that Liaoning Han people have genetic similarities with other northern Han people (Shandong, Henan, and Shanxi) and Liaoning Manchu people. Millet farmers in the Yellow River Basin (YRB) and the West Liao River Basin (WLRB) (57–98%) and hunter-gatherers in the Mongolian Plateau (MP) and the Amur River Basin (ARB) (40–43%) are the main ancestral sources of the Liaoning Han people. Our study further supports the “northern origin hypothesis”; YRB-related ancestry accounts for 83–98% of the genetic makeup of the Liaoning Han population. There are clear genetic influences of northern East Asian populations in the Liaoning Han people, ancient Northeast Asian-related ancestry is another dominant ancestral component, and large-scale population admixture has happened between Tungusic Manchu people and Han people. There are genetic differences among the Liaoning Han people, and we found that these differences are associated with different migration routes of Hans during the “Chuang Guandong” period in historical records.
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Wang CZ, Yu XE, Shi MS, Li H, Ma SH. Whole mitochondrial genome analysis of the Daur ethnic minority from Hulunbuir in the Inner Mongolia Autonomous Region of China. BMC Ecol Evol 2022; 22:66. [PMID: 35585500 PMCID: PMC9118598 DOI: 10.1186/s12862-022-02019-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Accepted: 04/27/2022] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND Mitochondrial DNA (mtDNA) variations are often associated with bioenergetics, disease, and speciation and can be used to track the history of women. Although advances in massively parallel sequencing (MPS) technology have greatly promoted our understanding of the population's history (especially genome-wide data and whole Y chromosome sequencing), the whole mtDNA sequence of many important groups has not been fully studied. In this study, we employed whole mitogenomes of 209 healthy and unrelated individuals from the Daur group, a Mongolic-speaking representative population of the indigenous groups in the Heilongjiang River basin (also known as the Amur River basin). RESULTS The dataset presented 127 distinct mtDNA haplotypes, resulting in a haplotype diversity of 0.9933. Most of haplotypes were assigned to eastern Eurasian-specific lineages, such as D4 (19.62%), B4 (9.09%), D5 (7.66%) and M7 (4.78%). Population comparisons showed that the Daurians do have certain connections with the ancient populations in the Heilongjiang River basin but the matrilineal genetic composition of the Daur group was also greatly influenced by other non-Mongolic groups from neighboring areas. CONCLUSIONS Collectively, the whole mtDNA data generated in the present study will augment the existing mtDNA database. Our study provides genetic links between the Daur population and the aborigine peoples from Siberia and the Amur-Ussuri Region. But on the whole, compared with other Mongolic-speaking groups, the modern Daur population is closer to the East Asian ancestry group.
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Affiliation(s)
- Chi-Zao Wang
- Department of Radiology, The First Affiliated Hospital of Shantou University Medical College, Shantou, 515041, China
- Shantou University Medical College, Shantou, 515041, Guangdong, China
- Laboratory of Medical Molecular Imaging, The First Affiliated Hospital of Shantou University Medical College, No. 57 Changping Road, Shantou, 515041, Guangdong, China
| | - Xue-Er Yu
- MOE Key Laboratory of Contemporary Anthropology, School of Life Sciences, Fudan University, 200438, Shanghai, China
| | - Mei-Sen Shi
- Criminal Justice College of China University of Political Science and Law, Beijing, 100088, People's Republic of China
| | - Hui Li
- MOE Key Laboratory of Contemporary Anthropology, School of Life Sciences, Fudan University, 200438, Shanghai, China
- Shanxi Academy of Advanced Research and Innovation, Fudan-Datong Institute of Chinese Origin, Datong, 037006, China
| | - Shu-Hua Ma
- Department of Radiology, The First Affiliated Hospital of Shantou University Medical College, Shantou, 515041, China
- Shantou University Medical College, Shantou, 515041, Guangdong, China
- Laboratory of Medical Molecular Imaging, The First Affiliated Hospital of Shantou University Medical College, No. 57 Changping Road, Shantou, 515041, Guangdong, China
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Improving the regional Y-STR haplotype resolution utilizing haplogroup-determining Y-SNPs and the application of machine learning in Y-SNP haplogroup prediction in a forensic Y-STR database: A pilot study on male Chinese Yunnan Zhaoyang Han population. Forensic Sci Int Genet 2021; 57:102659. [PMID: 35007855 DOI: 10.1016/j.fsigen.2021.102659] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2021] [Revised: 12/14/2021] [Accepted: 12/27/2021] [Indexed: 11/23/2022]
Abstract
Improving the resolution of the current widely used Y-chromosomal short tandem repeat (Y-STR) dataset is of great importance for forensic investigators, and the current approach is limited, except for the addition of more Y-STR loci. In this research, a regional Y-DNA database was investigated to improve the Y-STR haplotype resolution utilizing a Y-SNP Pedigree Tagging System that includes 24 Y-chromosomal single nucleotide polymorphism (Y-SNP) loci. This pilot study was conducted in the Chinese Yunnan Zhaoyang Han population, and 3473 unrelated male individuals were enrolled. Based on data on the male haplogroups under different panels, the matched or near-matching (NM) Y-STR haplotype pairs from different haplogroups indicated the critical roles of haplogroups in improving the regional Y-STR haplotype resolution. A classic median-joining network analysis was performed using Y-STR or Y-STR/Y-SNP data to reconstruct population substructures, which revealed the ability of Y-SNPs to correct misclassifications from Y-STRs. Additionally, population substructures were reconstructed using multiple unsupervised or supervised dimensionality reduction methods, which indicated the potential of Y-STR haplotypes in predicting Y-SNP haplogroups. Haplogroup prediction models were built based on nine publicly accessible machine-learning (ML) approaches. The results showed that the best prediction accuracy score could reach 99.71% for major haplogroups and 98.54% for detailed haplogroups. Potential influences on prediction accuracy were assessed by adjusting the Y-STR locus numbers, selecting Y-STR loci with various mutabilities, and performing data processing. ML-based predictors generally presented a better prediction accuracy than two available predictors (Nevgen and EA-YPredictor). Three tree models were developed based on the Yfiler Plus panel with unprocessed input data, which showed their strong generalization ability in classifying various Chinese Han subgroups (validation dataset). In conclusion, this study revealed the significance and application prospects of Y-SNP haplogroups in improving regional Y-STR databases. Y-SNP haplogroups can be used to discriminate NM Y-STR haplotype pairs, and it is important for forensic Y-STR databases to develop haplogroup prediction tools to improve the accuracy of biogeographic ancestry inferences.
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Zhang X, He G, Li W, Wang Y, Li X, Chen Y, Qu Q, Wang Y, Xi H, Wang CC, Wen Y. Genomic Insight Into the Population Admixture History of Tungusic-Speaking Manchu People in Northeast China. Front Genet 2021; 12:754492. [PMID: 34659368 PMCID: PMC8515022 DOI: 10.3389/fgene.2021.754492] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2021] [Accepted: 08/30/2021] [Indexed: 11/13/2022] Open
Abstract
Manchu is the third-largest ethnic minority in China and has the largest population size among the Tungusic-speaking groups. However, the genetic origin and admixture history of the Manchu people are far from clear due to the sparse sampling and a limited number of markers genotyped. Here, we provided the first batch of genome-wide data of genotyping approximate 700,000 single-nucleotide polymorphisms (SNPs) in 93 Manchu individuals collected from northeast China. We merged the newly generated data with data of publicly available modern and ancient East Asians to comprehensively characterize the genetic diversity and fine-scale population structure, as well as explore the genetic origin and admixture history of northern Chinese Manchus. We applied both descriptive methods of ADMIXTURE, fineSTRUCTURE, F ST , TreeMix, identity by decedent (IBD), principal component analysis (PCA), and qualitative f-statistics (f 3, f 4, qpAdm, and qpWave). We found that Liaoning Manchus have a close genetic relationship and significant admixture signal with northern Han Chinese, which is in line with the cluster patterns in the haplotype-based results. Additionally, the qpAdm-based admixture models showed that modern Manchu people were formed as major ancestry related to Yellow River farmers and minor ancestry linked to ancient populations from Amur River Bain, or others. In summary, the northeastern Chinese Manchu people in Liaoning were an exception to the coherent genetic structure of Tungusic-speaking populations, probably due to the large-scale population migrations and genetic admixtures in the past few hundred years.
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Affiliation(s)
- Xianpeng Zhang
- Institute of Biological Anthropology, Jinzhou Medical University, Jinzhou, China
| | - Guanglin He
- 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
- School of Humanities, Nanyang Technological University, Singapore, Singapore
| | - Wenhui Li
- Institute of Biological Anthropology, Jinzhou Medical University, Jinzhou, China
| | - Yunfeng Wang
- Xinbin Manchu Autonomous County People’s Hospital, Fushun, China
| | - Xin Li
- Institute of Biological Anthropology, Jinzhou Medical University, Jinzhou, China
| | - Ying Chen
- Institute of Biological Anthropology, Jinzhou Medical University, Jinzhou, China
| | - Quanying Qu
- Institute of Biological Anthropology, Jinzhou Medical University, Jinzhou, China
| | - Ying Wang
- Institute of Biological Anthropology, Jinzhou Medical University, Jinzhou, China
| | - Huanjiu Xi
- Institute of Biological Anthropology, Jinzhou Medical University, Jinzhou, China
| | - 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
| | - Youfeng Wen
- Institute of Biological Anthropology, Jinzhou Medical University, Jinzhou, China
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