Evidence map›Paper›PMID 40826445›Full record

ArticleBMC genomics2025

Bioinformatic insights into five Chinese population substructures inferred from the East Asian-specific AISNP panel.

Jing Chen, Yuguo Huang, Jie Zhong, Mengge Wang, Guanglin He, Jiangwei Yan

Abstract read
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Article in BMC genomics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Jing ChenSchool of Forensic Medicine, Shanxi Medical University, Jinzhong, 030600, China.
Yuguo HuangInstitute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610000, China.
Jie ZhongInstitute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610000, China.
Mengge WangInstitute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610000, China. Menggewang2021@163.com.
Guanglin HeInstitute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610000, China. guanglinhescu@163.com.
Jiangwei YanSchool of Forensic Medicine, Shanxi Medical University, Jinzhong, 030600, China. yanjw@sxmu.edu.cn.

Funding

the Center for Archaeological Science of Sichuan University 23SASA01the Major Project of the National Social Science Foundation of China 23&ZD203the National Natural Science Foundation of China 82030058the National Natural Science Foundation of China 82202078the National Natural Science Foundation of China 82402203the Open Project of the Key Laboratory of Forensic Genetics of the Ministry of Public Security 2022FGKFKT05the Shanxi Province Graduate Education Innovation Program Project 2023KY369the Sichuan Science and Technology Program 2024NSFSC1518
6 · The paper itself

Abstract

backgroundRecent advances in population-specific high-quality reference databases have significantly improved the performance of forensic panel development for personal identification, parentage testing, and biogeographical ancestry inference. However, the discriminative power of previously developed AISNP panels remains limited in applications involving regional Chinese population substructures.

resultsWe used the high-quality Chinese population-specific genetic resource to develop six nested C5ClusterTag-50/100/250/500/1000/2000 ancestry-informative SNP panels focused on inferring population stratification among geographically and genetically distinct Chinese populations. We used comprehensive bioinformatics approaches and machine learning to validate the effectiveness of these panels in both the testing and training datasets. A total of 2,772 individuals were screened across different AISNP panels based on the I

conclusionsThese panels can differentiate ethnolinguistic Chinese populations into five subgroups based on geographical divisions or linguistic affiliations, achieving a high average accuracy rate in machine learning models. This work not only developed a robust ancestry inference panel and new tools for predicting the ancestry of ethnolinguistic Chinese populations but also created a comprehensive reference dataset and machine learning model applicable to population and forensic uses globally.

Indexed as

Computational BiologyEast Asian PeopleGenetics, PopulationPolymorphism, Single NucleotideChinaHumansMachine LearningPrincipal Component AnalysisAncestry-informative SNPsBiogeographic ancestryChinese population substructuresForensic geneticsMachine learning

Identifiers

PMID40826445
PMCPMC12359956

What Socratic holds

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LicenceCC BY-NC-ND
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.