Ancient genomes illuminate the demographic history of Shandong over the past two millennia.

IF 6.6 2区 生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY Journal of Genetics and Genomics Pub Date : 2024-07-14 DOI:10.1016/j.jgg.2024.07.008
Qu Shen, Zhigang Wu, Jinguo Zan, Xiaomin Yang, Jianxin Guo, Zhi Ji, Baitong Wang, Yilan Liu, Xiaolu Mao, Xinyi Wang, Xinyue Zou, Hongming Zhou, Yanying Peng, Hao Ma, Haifeng He, Tianyou Bai, Mengting Xu, Shaoqing Wen, Li Jin, Qun Zhang, Chuan-Chao Wang
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Abstract

Shandong province, located in the Lower Yellow River, is one of the birthplaces of ancient Chinese civilization. However, the comprehensive genetic histories of this region have remained largely unknown until now due to a lack of ancient human genomes. Here, we present 21 ancient genomes from Shandong dating from the Warring States period to the Jin-Yuan Dynasties. Unlike the early Neolithic samples from Shandong, the historical samples are most closely related to post-Late Neolithic populations of the Middle Yellow River Basin, suggesting a population turnover in Shandong from the Neolithic Age to the Historical era. In addition, we detect a close genetic affinity between the historical samples in Shandong and present-day Han Chinese, showing long-term genetic stability in Han Chinese at least since the Warring States period.

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古代基因组揭示了山东两千年来的人口历史。
位于黄河下游的山东省是中国古代文明的发祥地之一。然而,由于缺乏古人类基因组,这一地区的综合遗传史至今仍不为人知。在这里,我们展示了 21 个山东地区的古人类基因组,年代可追溯到战国至金元时期。与山东新石器时代早期的样本不同,这些历史样本与黄河中游流域新石器时代晚期以后的人群关系最为密切,这表明从新石器时代到历史时代,山东的人群发生了更替。此外,我们还检测到山东历史样本与现今汉族之间存在着密切的遗传亲缘关系,这表明至少自战国时期以来,汉族的遗传具有长期的稳定性。
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来源期刊
Journal of Genetics and Genomics
Journal of Genetics and Genomics 生物-生化与分子生物学
CiteScore
8.20
自引率
3.40%
发文量
4756
审稿时长
14 days
期刊介绍: The Journal of Genetics and Genomics (JGG, formerly known as Acta Genetica Sinica ) is an international journal publishing peer-reviewed articles of novel and significant discoveries in the fields of genetics and genomics. Topics of particular interest include but are not limited to molecular genetics, developmental genetics, cytogenetics, epigenetics, medical genetics, population and evolutionary genetics, genomics and functional genomics as well as bioinformatics and computational biology.
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