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Models, methods and tools for ancestry inference and admixture analysis

Quantitative Biology volume 5, pages 236–250 (2017)Cite this article

Abstract

Background

Genetic admixture refers to the process or consequence of interbreeding between two or more previously isolated populations within a species. Compared to many other evolutionary driving forces such as mutations, genetic drift, and natural selection, genetic admixture is a quick mechanism for shaping population genomic diversity. In particular, admixture results in “recombination” of genetic variants that have been fixed in different populations, which has many evolutionary and medical implications.

Results

However, it is challenging to accurately reconstruct population admixture history and to understand of population admixture dynamics. In this review, we provide an overview of models, methods, and tools for ancestry inference and admixture analysis.

Conclusions

Many methods and tools used for admixture analysis were originally developed to analyze human data, but these methods can also be directly applied and/or slightly modified to study non-human species as well.

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Acknowledgments

S.X. acknowledges financial support from the National Natural Science Foundation of China (NSFC) grant (Nos. 91331204 and 31711530221), the Strategic Priority Research Program (No. XDB13040100) and Key Research Program of Frontier Sciences (No. QYZDJ-SSW-SYS009) of the Chinese Academy of Sciences (CAS), the National Science Fund for Distinguished Young Scholars (No. 31525014), and the Program of Shanghai Academic Research Leader (No. 16XD1404700); S.X. is Max- Planck Independent Research Group Leader and member of CAS Youth Innovation Promotion Association. S.X. also gratefully acknowledges the support of the National Program for Top-notch Young Innovative Talents of The “Wanren Jihua” Project. We thank LetPub (www.letpub.com) for its linguistic assistance during the preparation of this manuscript. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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  1. These authors contributed equally to this work.

Authors and Affiliations

  1. CAS Key Laboratory of Computational Biology, Max Planck Independent Research Group on Population Genomics, CAS-MPG Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, CAS, Shanghai, 200031, China

    Kai Yuan, Ying Zhou, Yuchen Wang, Chang Liu & Shuhua Xu

  2. University of Chinese Academy of Sciences, Beijing, 100049, China

    Kai Yuan, Ying Zhou, Yuchen Wang, Chang Liu & Shuhua Xu

  3. Department of Mathematics, School of Science, Beijing Jiaotong University, Beijing, 100044, China

    Xumin Ni

  4. School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China

    Shuhua Xu

  5. Collaborative Innovation Center of Genetics and Development, Shanghai, 200438, China

    Shuhua Xu

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  1. Kai Yuan
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  2. Ying Zhou
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  3. Xumin Ni
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  4. Yuchen Wang
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  5. Chang Liu
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  6. Shuhua Xu
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Correspondence to Shuhua Xu.

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Yuan, K., Zhou, Y., Ni, X. et al. Models, methods and tools for ancestry inference and admixture analysis. Quant Biol 5, 236–250 (2017). https://doi.org/10.1007/s40484-017-0117-2

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  • DOI: https://doi.org/10.1007/s40484-017-0117-2

Keywords

  • genetic admixture
  • ancestry
  • population structures
  • demographic history
  • archaic introgression
  • incomplete lineage sorting