Human genetic history on the Tibetan Plateau in the past 5100 years

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Abstract

Using genome-wide data of 89 ancient individuals dated to 5100 to 100 years before the present (B.P.) from 29 sites across the Tibetan Plateau, we found plateau-specific ancestry across plateau populations, with substantial genetic structure indicating high differentiation before 2500 B.P. Northeastern plateau populations rapidly showed admixture associated with millet farmers by 4700 B.P. in the Gonghe Basin. High genetic similarity on the southern and southwestern plateau showed population expansion along the Yarlung Tsangpo River since 3400 years ago. Central and southeastern plateau populations revealed extensive genetic admixture within the plateau historically, with substantial ancestry related to that found in southern and southwestern plateau populations. Over the past ~700 years, substantial gene flow from lowland East Asia further shaped the genetic landscape of present-day plateau populations. The high-altitude adaptive EPAS1 allele was found in plateau populations as early as in a 5100-year-old individual and showed a sharp increase over the past 2800 years.

Abstract

Ancient human DNA from the last 5,100 years provides insight into Tibetan ancestry and population dynamics on the plateau.

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Fast and accurate short read alignment with Burrows–Wheeler transform

Heng Li, Richard Durbin (2009)

Motivation: The enormous amount of short reads generated by the new DNA sequencing technologies call for the development of fast and accurate read alignment programs. A first generation of hash table-based methods has been developed, including MAQ, which is accurate, feature rich and fast enough to align short reads from a single individual. However, MAQ does not support gapped alignment for single-end reads, which makes it unsuitable for alignment of longer reads where indels may occur frequently. The speed of MAQ is also a concern when the alignment is scaled up to the resequencing of hundreds of individuals. Results: We implemented Burrows-Wheeler Alignment tool (BWA), a new read alignment package that is based on backward search with Burrows–Wheeler Transform (BWT), to efficiently align short sequencing reads against a large reference sequence such as the human genome, allowing mismatches and gaps. BWA supports both base space reads, e.g. from Illumina sequencing machines, and color space reads from AB SOLiD machines. Evaluations on both simulated and real data suggest that BWA is ∼10–20× faster than MAQ, while achieving similar accuracy. In addition, BWA outputs alignment in the new standard SAM (Sequence Alignment/Map) format. Variant calling and other downstream analyses after the alignment can be achieved with the open source SAMtools software package. Availability: http://maq.sourceforge.net Contact: rd@sanger.ac.uk

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PLINK: a tool set for whole-genome association and population-based linkage analyses.

Shaun Purcell, Benjamin M. Neale, Kathe Todd-Brown … (2007)

Whole-genome association studies (WGAS) bring new computational, as well as analytic, challenges to researchers. Many existing genetic-analysis tools are not designed to handle such large data sets in a convenient manner and do not necessarily exploit the new opportunities that whole-genome data bring. To address these issues, we developed PLINK, an open-source C/C++ WGAS tool set. With PLINK, large data sets comprising hundreds of thousands of markers genotyped for thousands of individuals can be rapidly manipulated and analyzed in their entirety. As well as providing tools to make the basic analytic steps computationally efficient, PLINK also supports some novel approaches to whole-genome data that take advantage of whole-genome coverage. We introduce PLINK and describe the five main domains of function: data management, summary statistics, population stratification, association analysis, and identity-by-descent estimation. In particular, we focus on the estimation and use of identity-by-state and identity-by-descent information in the context of population-based whole-genome studies. This information can be used to detect and correct for population stratification and to identify extended chromosomal segments that are shared identical by descent between very distantly related individuals. Analysis of the patterns of segmental sharing has the potential to map disease loci that contain multiple rare variants in a population-based linkage analysis.

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Fast model-based estimation of ancestry in unrelated individuals.

David H. Alexander, John Novembre, Kenneth Lange (2009)

Population stratification has long been recognized as a confounding factor in genetic association studies. Estimated ancestries, derived from multi-locus genotype data, can be used to perform a statistical correction for population stratification. One popular technique for estimation of ancestry is the model-based approach embodied by the widely applied program structure. Another approach, implemented in the program EIGENSTRAT, relies on Principal Component Analysis rather than model-based estimation and does not directly deliver admixture fractions. EIGENSTRAT has gained in popularity in part owing to its remarkable speed in comparison to structure. We present a new algorithm and a program, ADMIXTURE, for model-based estimation of ancestry in unrelated individuals. ADMIXTURE adopts the likelihood model embedded in structure. However, ADMIXTURE runs considerably faster, solving problems in minutes that take structure hours. In many of our experiments, we have found that ADMIXTURE is almost as fast as EIGENSTRAT. The runtime improvements of ADMIXTURE rely on a fast block relaxation scheme using sequential quadratic programming for block updates, coupled with a novel quasi-Newton acceleration of convergence. Our algorithm also runs faster and with greater accuracy than the implementation of an Expectation-Maximization (EM) algorithm incorporated in the program FRAPPE. Our simulations show that ADMIXTURE's maximum likelihood estimates of the underlying admixture coefficients and ancestral allele frequencies are as accurate as structure's Bayesian estimates. On real-world data sets, ADMIXTURE's estimates are directly comparable to those from structure and EIGENSTRAT. Taken together, our results show that ADMIXTURE's computational speed opens up the possibility of using a much larger set of markers in model-based ancestry estimation and that its estimates are suitable for use in correcting for population stratification in association studies.

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Author and article information

Contributors

Hongru Wang:

ORCID: https://orcid.org/0000-0001-8305-5231

Role: ConceptualizationRole: Formal analysisRole: InvestigationRole: MethodologyRole: SoftwareRole: ValidationRole: VisualizationRole: Writing - original draftRole: Writing - review & editing

Melinda A. Yang:

ORCID: https://orcid.org/0000-0001-9004-7563

Role: Formal analysisRole: InvestigationRole: VisualizationRole: Writing - original draftRole: Writing - review & editing

Shargan Wangdue:

ORCID: https://orcid.org/0000-0002-4215-3959

Role: ConceptualizationRole: Project administrationRole: ResourcesRole: Writing - review & editing

Hongliang Lu: Role: ConceptualizationRole: Data curationRole: Funding acquisitionRole: Project administrationRole: ResourcesRole: SupervisionRole: VisualizationRole: Writing - original draftRole: Writing - review & editing

Honghai Chen: Role: InvestigationRole: ResourcesRole: Writing - review & editing

Linhui Li: Role: Resources

Guanghui Dong: Role: Resources

Tinley Tsring: Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SoftwareRole: SupervisionRole: ValidationRole: VisualizationRole: Writing - original draftRole: Writing - review & editing

Haibing Yuan:

ORCID: https://orcid.org/0000-0002-3155-6760

Role: ConceptualizationRole: InvestigationRole: ResourcesRole: Writing - original draft

Wei He:

ORCID: https://orcid.org/0000-0001-6597-5990

Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SoftwareRole: SupervisionRole: ValidationRole: VisualizationRole: Writing - original draftRole: Writing - review & editing

Manyu Ding: Role: Formal analysisRole: Visualization

Xiaohong Wu:

ORCID: https://orcid.org/0000-0002-3819-0829

Role: Resources

Shuai Li: Role: Resources

Norbu Tashi: Role: Resources

Tsho Yang: Role: Resources

Feng Yang: Role: Resources

Yan Tong: Role: Formal analysisRole: InvestigationRole: ResourcesRole: ValidationRole: Visualization

Zujun Chen: Role: Resources

Yuanhong He:

ORCID: https://orcid.org/0000-0003-4311-6751

Role: Resources

Peng Cao: Role: Resources

Qingyan Dai: Role: Resources

Feng Liu: Role: Resources

Xiaotian Feng: Role: Resources

Tianyi Wang:

ORCID: https://orcid.org/0000-0002-4790-7668

Role: Resources

Ruowei Yang: Role: Resources

Wanjing Ping:

ORCID: https://orcid.org/0000-0003-4318-0673

Role: Resources

Zhaoxia Zhang: Role: Formal analysisRole: Resources

Yang Gao:

ORCID: https://orcid.org/0000-0001-7057-1413

Role: Resources

Ming Zhang: Role: InvestigationRole: Writing - review & editing

Xiaoji Wang: Role: Data curationRole: Formal analysisRole: ResourcesRole: Validation

Chao Zhang:

ORCID: https://orcid.org/0000-0002-0687-9058

Role: Resources

Kai Yuan:

ORCID: https://orcid.org/0000-0002-8460-6581

Role: Investigation

Albert Min-Shan Ko: Role: Writing - original draft

Mark Aldenderfer:

ORCID: https://orcid.org/0000-0002-7033-4319

Role: ConceptualizationRole: Writing - review & editing

Xing Gao:

ORCID: https://orcid.org/0000-0001-5295-3629

Role: ConceptualizationRole: Funding acquisitionRole: InvestigationRole: Project administrationRole: ResourcesRole: SupervisionRole: ValidationRole: Writing - review & editing

Shuhua Xu:

ORCID: https://orcid.org/0000-0002-1975-1002

Qiaomei Fu:

ORCID: https://orcid.org/0000-0002-7141-0002

Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: Project administrationRole: SoftwareRole: SupervisionRole: ValidationRole: VisualizationRole: Writing - original draftRole: Writing - review & editing

Journal

Journal ID (nlm-ta): Sci Adv

Journal ID (iso-abbrev): Sci Adv

Journal ID (publisher-id): sciadv

Journal ID (hwp): advances

Title: Science Advances

Publisher: American Association for the Advancement of Science

ISSN (Electronic): 2375-2548

Publication date Collection: March 2023

Publication date (Electronic, pub): 17 March 2023

Volume: 9

Issue: 11

Electronic Location Identifier: eadd5582

Affiliations

[ ¹ ]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.

[ ² ]Department of Biology, University of Richmond, Richmond, VA 23173, USA.

[ ³ ]Tibet Institute for Conservation and Research of Cultural Relics, Lhasa 850000, China.

[ ⁴ ]School of Archaeology and Museology, Sichuan University, Chengdu 610064, China.

[ ⁵ ]Center for Archaeological Science, Sichuan University, Chengdu 610064, China.

[ ⁶ ]School of Cultural Heritage, Northwest University, Xi’an 710069, China.

[ ⁷ ]Key Laboratory of Western China’s Environmental Systems (Ministry of Education), College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China.

[ ⁸ ]University of the Chinese Academy of Sciences, Beijing 100049, China.

[ ⁹ ]School of Archaeology and Museology, Peking University, Beijing 100871, China.

[ ¹⁰ ]State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, Collaborative Innovation Center of Genetics and Development, School of Life Sciences, Fudan University, Shanghai 200438, China.

[ ¹¹ ]Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China.

[ ¹² ]Department of Anthropology and Heritage Studies, University of California, Merced, Merced, CA 95343, USA.

[ ¹³ ]Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai 200032, China.

[ ¹⁴ ]Human Phenome Institute, Zhangjiang Fudan International Innovation Center, and Ministry of Education Key Laboratory of Contemporary Anthropology, Fudan University, Shanghai 201203, China.

[ ¹⁵ ]Shanghai Qi Zhi Institute, Shanghai 200232, China.

Author notes

[* ]Corresponding author. Email: fuqiaomei@ 123456ivpp.ac.cn

[†]

These authors contributed equally to this work.

[‡]

Present address: Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China.

Author information

Hongru Wang https://orcid.org/0000-0001-8305-5231

Melinda A. Yang https://orcid.org/0000-0001-9004-7563

Shargan Wangdue https://orcid.org/0000-0002-4215-3959

Haibing Yuan https://orcid.org/0000-0002-3155-6760

Wei He https://orcid.org/0000-0001-6597-5990

Xiaohong Wu https://orcid.org/0000-0002-3819-0829

Yuanhong He https://orcid.org/0000-0003-4311-6751

Tianyi Wang https://orcid.org/0000-0002-4790-7668

Wanjing Ping https://orcid.org/0000-0003-4318-0673

Yang Gao https://orcid.org/0000-0001-7057-1413

Chao Zhang https://orcid.org/0000-0002-0687-9058

Kai Yuan https://orcid.org/0000-0002-8460-6581

Mark Aldenderfer https://orcid.org/0000-0002-7033-4319

Xing Gao https://orcid.org/0000-0001-5295-3629

Shuhua Xu https://orcid.org/0000-0002-1975-1002

Qiaomei Fu https://orcid.org/0000-0002-7141-0002

Article

Publisher ID: add5582

DOI: 10.1126/sciadv.add5582

PMC ID: 10022901

PubMed ID: 36930720

SO-VID: a1702536-333f-4ab6-b5ed-e91452fd9721

Copyright © Copyright © 2023 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution License 4.0 (CC BY).

License:

This is an open-access article distributed under the terms of the Creative Commons Attribution license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

History

Date received : 18 June 2022

Date accepted : 13 February 2023

Funding

Funded by: FundRef http://dx.doi.org/10.13039/100000011, Howard Hughes Medical Institute;

Award ID: 55008731

Funded by: FundRef http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;

Award ID: 41925009

Funded by: FundRef http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;

Award ID: 32030020

Funded by: National key R&D program of China;

Award ID: 2021YFC1523600

Funded by: Shanghai Municipal Science and Technology Major Project;

Award ID: 2017SHZDZX01

Funded by: Chinese Academy of Sciences (CAS) and the Ministry of Finance of the People’s Republic of China;

Award ID: YSBR-019

Funded by: Chinese Academy of Sciences (CAS) and the Ministry of Finance of the People’s Republic of China;

Award ID: XDB26000000

Funded by: Key National Social Science Foundation of China;

Award ID: 16ZDA144

Funded by: “Research on the roots of Chinese civilization” of Zhengzhou University;

Award ID: XKZDJC202006

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Human genetic history on the Tibetan Plateau in the past 5100 years

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50 years of ROAPE

Most cited references 109

Fast and accurate short read alignment with Burrows–Wheeler transform

PLINK: a tool set for whole-genome association and population-based linkage analyses.

Fast model-based estimation of ancestry in unrelated individuals.

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Cited by 13

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