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Large-scale lexical and genetic alignment supports a hybrid model of Han Chinese demic and cultural diffusions

Nature Human Behaviour (2024)Cite this article

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Abstract

The Han Chinese history is shaped by substantial demographic activities and sociocultural transmissions. However, it remains challenging to assess the contributions of demic and cultural diffusion to Han culture and language, primarily due to the lack of rigorous examination of genetic–linguistic congruence. Here we digitized a large-scale linguistic inventory comprising 1,018 lexical traits across 926 dialect varieties. Using phylogenetic analysis and admixture inference, we revealed a north–south gradient of lexical differences that probably resulted from historical migrations. Furthermore, we quantified extensive horizontal language transfers and pinpointed central China as a dialectal melting pot. Integrating genetic data from 30,408 Han Chinese individuals, we compared the lexical and genetic landscapes across 26 provinces. Our results support a hybrid model where demic diffusion predominantly impacts central China, while cultural diffusion and language assimilation occur in southwestern and coastal regions, respectively. This interdisciplinary study sheds light on the complex social-genetic history of the Han Chinese.

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Fig. 1: Geographic characteristics of Chinese dialects.
Fig. 2: Manhattan plot of outlier lexical traits.
Fig. 3: Internal structure of Chinese dialects.
Fig. 4: Admixture patterns of Chinese dialects.
Fig. 5: Correlation between the genetic component of Northern Han populations and the linguistic component of northern language (Mandarin) in China.

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Data availability

The lexical inventory of Chinese dialects and other necessary datasets to reproduce the results in the paper are available in the Supplementary Tables. The allele frequency data of genetic variants used in this study are available via PGG.Han website at https://www.biosino.org/pgghan/data/variant. The pairwise FST for any two provincial populations and the inferred ancestry composition for each of the provincial populations are available in GitHub at https://github.com/Shuhua-Group/Genetic-characteristics-of-the-Han100K-initiative or via Zenodo at https://doi.org/10.5281/zenodo.10816923 (ref. 112). The use of genetic data in this work is approved by The National Health Commission of the People’s Republic of China (No. 2024BAT00503). Release of the summary statistics of genetic data in this work is recorded by the National Health Commission (NHC) of the People’s Republic of China at Open Archive for Miscellaneous Data (OMIX) with accession number OMIX004518. All data generated or analysed during this study are included in this Article, its Supplementary Information and publicly available repositories.

Code availability

The codes required to transform the data into the statistics and outputs reported in the paper are available in Supplementary Information and have been deposited in GitHub at https://github.com/JoshuaThieriot/Chinese-dialect-project and in Zenodo at https://doi.org/10.5281/zenodo.10867759 (ref. 113).

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Acknowledgements

This research was supported by the National Natural Science Foundation of China (T2122007, 32288101, 32070577 and 32030020), National Key R&D Program of China (2023YFC2605400, 2020YFE0201600), National Social Science Foundation (23&ZD317 and 20&ZD301), the Shanghai Science and Technology Commission Program (23JS1410100), the Office of Global Partnerships (Key Projects Development Fund), and the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (Grant Agreement No. 883700 TRAM). This work was also sponsored by the ‘Shuguang Program’ supported by the Shanghai Education Development Foundation and Shanghai Municipal Education Commission (20SG06), and by the Fundamental Research Funds for the Central Universities (2022ECNU-XWK-XK005). The computational work in this study was supported by the CFFF Computing Platform and the Human Phenome Data Center of Fudan University. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

Author information

Author notes

  1. These authors contributed equally: Chengkun Yang, Xiaoxi Zhang.

Authors and Affiliations

  1. State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, School of Life Science, Fudan University, Shanghai, China

    Chengkun Yang, Sizhe Yang, Baihui Wu, Li Jin & Shuhua Xu

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

    Xiaoxi Zhang & Shuhua Xu

  3. Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China

    Xiaoxi Zhang & Shuhua Xu

  4. School of Ethnology and Sociology, Minzu University of China, Beijing, China

    Shi Yan

  5. Department of Chinese Language and Literature, Fudan University, Shanghai, China

    Fengshuo You & Zhiyi Wang

  6. Department of Cultural Heritage and Museology, Fudan University, Shanghai, China

    Yue Cui

  7. Department of Linguistics and Modern Languages, The Chinese University of Hong Kong, Hong Kong, China

    Ni Xie

  8. Institute of Modern Languages and Linguistics, Fudan University, Shanghai, China

    Menghan Zhang

  9. Research Institute of Intelligent Complex Systems, Fudan University, Shanghai, China

    Menghan Zhang

  10. Ministry of Education Key Laboratory of Contemporary Anthropology, Fudan University, Shanghai, China

    Menghan Zhang

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Contributions

C.Y., S. Yan, L.J., S.X. and M.Z. designed the research. C.Y., F.Y., Y.C., N.X., Z.W. and M.Z. collated the linguistic data of the Chinese dialects. X.Z. and S.X. assembled the genetic data of the Han Chinese and performed genetic data analysis. C.Y., S. Yang, B.W. and M.Z. performed the linguistic analyses and interdisciplinary alignment. C.Y., S. Yan, L.J., S.X. and M.Z. discussed the results. C.Y., X.Z., S.X. and M.Z. wrote and revised the paper. All authors approved the final version of the manuscript.

Corresponding authors

Correspondence to Li Jin, Shuhua Xu or Menghan Zhang.

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Nature Human Behaviour thanks Randy J. Lapolla and Chuang-Chao Wang for their contribution to the peer review of this work. Peer reviewer reports are available.

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Lexical inventory, datasets generated from statistical analysis, and other relevant analytical results.

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Yang, C., Zhang, X., Yan, S. et al. Large-scale lexical and genetic alignment supports a hybrid model of Han Chinese demic and cultural diffusions. Nat Hum Behav (2024). https://doi.org/10.1038/s41562-024-01886-9

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