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He Y, Zhang X, Peng MS, Li YC, Liu K, Zhang Y, Mao L, Guo Y, Ma Y, Zhou B, Zheng W, Yue T, Liao Y, Liang SA, Chen L, Zhang W, Chen X, Tang B, Yang X, Ye K, Gao S, Lu Y, Wang Y, Wan S, Hao R, Wang X, Mao Y, Dai S, Gao Z, Yang LQ, Guo J, Li J, Liu C, Wang J, Sovannary T, Bunnath L, Kampuansai J, Inta A, Srikummool M, Kutanan W, Ho HQ, Pham KD, Singthong S, Sochampa S, Kyaing UW, Pongamornkul W, Morlaeku C, Rattanakrajangsri K, Kong QP, Zhang YP, Su B. Genome diversity and signatures of natural selection in mainland Southeast Asia. Nature 2025:10.1038/s41586-025-08998-w. [PMID: 40369069 DOI: 10.1038/s41586-025-08998-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2024] [Accepted: 04/09/2025] [Indexed: 05/16/2025]
Abstract
Mainland Southeast Asia (MSEA) has rich ethnic and cultural diversity with a population of nearly 300 million1,2. However, people from MSEA are underrepresented in the current human genomic databases. Here we present the SEA3K genome dataset (phase I), generated by deep short-read whole-genome sequencing of 3,023 individuals from 30 MSEA populations, and long-read whole-genome sequencing of 37 representative individuals. We identified 79.59 million small variants and 96,384 structural variants, among which 22.83 million small variants and 24,622 structural variants are unique to this dataset. We observed a high genetic heterogeneity across MSEA populations, reflected by the varied combinations of genetic components. We identified 44 genomic regions with strong signatures of Darwinian positive selection, covering 89 genes involved in varied physiological systems such as physical traits and immune response. Furthermore, we observed varied patterns of archaic Denisovan introgression in MSEA populations, supporting the proposal of at least two distinct instances of Denisovan admixture into modern humans in Asia3. We also detected genomic regions that suggest adaptive archaic introgressions in MSEA populations. The large number of novel genomic variants in MSEA populations highlight the necessity of studying regional populations that can help answer key questions related to prehistory, genetic adaptation and complex diseases.
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Affiliation(s)
- Yaoxi He
- State Key Laboratory of Genetic Evolution and Animal Models, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
- Yunnan Key Laboratory of Integrative Anthropology, Kunming, China
| | - Xiaoming Zhang
- State Key Laboratory of Genetic Evolution and Animal Models, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
- Yunnan Key Laboratory of Integrative Anthropology, Kunming, China
| | - Min-Sheng Peng
- State Key Laboratory of Genetic Evolution and Animal Models, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
- KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Yu-Chun Li
- State Key Laboratory of Genetic Evolution and Animal Models, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
- KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming, China
- Kunming Key Laboratory of Healthy Aging Study, Kunming, China
| | - Kai Liu
- State Key Laboratory of Genetic Evolution and Animal Models, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Yu Zhang
- State Key Laboratory of Genetic Evolution and Animal Models, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Leyan Mao
- State Key Laboratory of Genetic Evolution and Animal Models, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Yongbo Guo
- State Key Laboratory of Genetic Evolution and Animal Models, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Yujie Ma
- State Key Laboratory of Genetic Evolution and Animal Models, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Bin Zhou
- State Key Laboratory of Genetic Evolution and Animal Models, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Wangshan Zheng
- State Key Laboratory of Genetic Evolution and Animal Models, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Tian Yue
- State Key Laboratory of Genetic Evolution and Animal Models, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Yuwen Liao
- State Key Laboratory of Genetic Evolution and Animal Models, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Shen-Ao Liang
- State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, School of Life Science, Fudan University, Shanghai, China
| | - Lu Chen
- State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, School of Life Science, Fudan University, Shanghai, China
| | - Weijie Zhang
- State Key Laboratory of Genetic Evolution and Animal Models, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Xiaoning Chen
- National Genomics Data Center, China National Center for Bioinformation, Beijing, China
| | - Bixia Tang
- National Genomics Data Center, China National Center for Bioinformation, Beijing, China
| | - Xiaofei Yang
- School of Computer Science and Technology, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China
- MOE Key Lab for Intelligent Networks & Networks Security, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China
- Center for Mathematical Medical, the First Affiliated Hospital, Xi'an Jiaotong University, Xi'an, China
| | - Kai Ye
- MOE Key Lab for Intelligent Networks & Networks Security, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China
- Center for Mathematical Medical, the First Affiliated Hospital, Xi'an Jiaotong University, Xi'an, China
- School of Automation Science and Engineering, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China
- Genome Institute, the First Affiliated Hospital, Xi'an Jiaotong University, Xi'an, China
- School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China
- Faculty of Science, Leiden University, Leiden, The Netherlands
| | - Shenghan Gao
- School of Computer Science and Technology, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China
- MOE Key Lab for Intelligent Networks & Networks Security, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China
- School of Automation Science and Engineering, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China
| | - Yurun Lu
- CEMS, NCMIS, HCMS, MADIS, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China
| | - Yong Wang
- CEMS, NCMIS, HCMS, MADIS, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China
| | - Shijie Wan
- School of Computer Science and Technology, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China
| | - Rushan Hao
- School of Medicine, Yunnan University, Kunming, China
| | - Xuankai Wang
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Yafei Mao
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
- Center for Genomic Research, International Institutes of Medicine, The Fourth Affiliated Hospital, Zhejiang University, Yiwu, China
| | - Shanshan Dai
- State Key Laboratory of Genetic Evolution and Animal Models, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Zongliang Gao
- State Key Laboratory of Genetic Evolution and Animal Models, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
- KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming, China
- University of Chinese Academy of Sciences, Beijing, China
- Kunming Key Laboratory of Healthy Aging Study, Kunming, China
| | - Li-Qin Yang
- State Key Laboratory of Genetic Evolution and Animal Models, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
- Yunnan Key Laboratory of Integrative Anthropology, Kunming, China
- Kunming Key Laboratory of Healthy Aging Study, Kunming, China
| | - Jianxin Guo
- State Key Laboratory of Genetic Evolution and Animal Models, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Jiangguo Li
- State Key Laboratory of Genetic Evolution and Animal Models, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Chao Liu
- Laboratory Animal Center, Kunming Institute of Zoology, the Chinese Academy of Sciences, Kunming, China
- National Resource Center for Non-Human Primates, Kunming, China
| | - Jianhua Wang
- Department of Anthropology, School of Sociology, Yunnan Minzu University, Kunming, China
| | - Tuot Sovannary
- Department of Geography and Land Management, Royal University of Phnom Penh, Phnom Penh, Cambodia
| | - Long Bunnath
- Department of Geography and Land Management, Royal University of Phnom Penh, Phnom Penh, Cambodia
| | - Jatupol Kampuansai
- Department of Biology, Faculty of Science, Chiang Mai University, Chiang Mai, Thailand
| | - Angkhana Inta
- Department of Biology, Faculty of Science, Chiang Mai University, Chiang Mai, Thailand
| | - Metawee Srikummool
- Department of Biochemistry, Faculty of Medical Science, Naresuan University, Phitsanulok, Thailand
| | - Wibhu Kutanan
- Department of Biology, Faculty of Science, Naresuan University, Phitsanulok, Thailand
| | - Huy Quang Ho
- Department of Immunology, Ha Noi Medical University, Ha Noi, Vietnam
| | - Khoa Dang Pham
- Department of Immunology, Ha Noi Medical University, Ha Noi, Vietnam
| | | | | | - U Win Kyaing
- Field School of Archaeology, Paukkhaung, Myanmar
| | - Wittaya Pongamornkul
- Queen Sirikit Botanic Garden (QSBG), The Botanical Garden Organization, Chiang Mai, Thailand
| | - Chutima Morlaeku
- Inter Mountain Peoples Education and Culture in Thailand Association (IMPECT), Sansai, Thailand
| | | | - Qing-Peng Kong
- State Key Laboratory of Genetic Evolution and Animal Models, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China.
- KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming, China.
- Kunming Key Laboratory of Healthy Aging Study, Kunming, China.
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, China.
| | - Ya-Ping Zhang
- State Key Laboratory of Genetic Evolution and Animal Models, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China.
- KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming, China.
- University of Chinese Academy of Sciences, Beijing, China.
- State Key Laboratory for Conservation and Utilization of Bio-Resources in Yunnan, School of Life Sciences, Yunnan University, Kunming, China.
| | - Bing Su
- State Key Laboratory of Genetic Evolution and Animal Models, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China.
- Yunnan Key Laboratory of Integrative Anthropology, Kunming, China.
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, China.
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2
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Shou W, Zhang C, Wang Y, Wang H, Guo L, Li L, Zhang T, Huang W, Shi J. Contrastive sequence signatures between the both sides of a recombination spot reveal an adaptation at PPARD locus from standing variation for pleiotropy since out-of-Africa dispersal. BMC Genomics 2025; 26:427. [PMID: 40307732 PMCID: PMC12042533 DOI: 10.1186/s12864-025-11620-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2025] [Accepted: 04/21/2025] [Indexed: 05/02/2025] Open
Abstract
BACKGROUND Drug metabolism and transporter genes are a specialized class of genes involved in absorption, distribution, metabolism and excretion. They easily present distinct genetic population differentiation and are vulnerable to natural selection. RESULTS We initiated a study using a special panel of informative genetic markers in such genes and dissected the genetic structure in representative Chinese and worldwide populations. A distinctive sub-population stratification was discovered in extensive Eurasians and resulted from divergence at the PPARD locus. The contrastive sequence signatures between the both sides of a recombination spot prove a selective sweep on this locus for genetic hitchhiking effect. A genealogy-based framework demonstrates the positive selection acting from standing variation exerted a moderate pressure in Eurasians, and drove the adaptive allele up to a high frequency. The timing and tempo estimations for the genetic adaptation indicate its onset coincided with the early out-of-Africa migration of modern humans and it lasted over a prolonged evolutionary history. A phenome-wide association analysis reveals an extended cis-regulation on the local gene expression and the pleiotropy implicated in a variety of complex traits. The colocalization analyses between the genetic associations from cis-acting gene expression and complex traits signify the most likely selective pressure from physical capacity, energy metabolism, and immune-related involvement, and provide prioritization for the effective genes and casual variants. CONCLUSIONS This work has laid a foundation for following efforts to make full sense of the biological mechanisms underlying the genetic adaptation.
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Affiliation(s)
- Weihua Shou
- Yunnan Key Laboratory of Children's Major Disease Research, Yunnan Institute of Pediatrics, Kunming Children's Hospital, 288 Qianxing Road, Kunming, Yunnan, 650228, P.R. China.
- Shanghai-MOST Key Laboratory of Health and Disease Genomics, Shanghai Institute for Biomedical and Pharmaceutical Technologies (SIBPT), 2140 Xietu Road, Shanghai, 200032, P.R. China.
| | - Chenhui Zhang
- Shanghai-MOST Key Laboratory of Health and Disease Genomics, Shanghai Institute for Biomedical and Pharmaceutical Technologies (SIBPT), 2140 Xietu Road, Shanghai, 200032, P.R. China
| | - Ying Wang
- Shanghai-MOST Key Laboratory of Health and Disease Genomics, Shanghai Institute for Biomedical and Pharmaceutical Technologies (SIBPT), 2140 Xietu Road, Shanghai, 200032, P.R. China
| | - Haifeng Wang
- Shanghai-MOST Key Laboratory of Health and Disease Genomics, Shanghai Institute for Biomedical and Pharmaceutical Technologies (SIBPT), 2140 Xietu Road, Shanghai, 200032, P.R. China
| | - Lei Guo
- Yunnan Key Laboratory of Children's Major Disease Research, Yunnan Institute of Pediatrics, Kunming Children's Hospital, 288 Qianxing Road, Kunming, Yunnan, 650228, P.R. China
| | - Li Li
- Yunnan Key Laboratory of Children's Major Disease Research, Yunnan Institute of Pediatrics, Kunming Children's Hospital, 288 Qianxing Road, Kunming, Yunnan, 650228, P.R. China
| | - Tiesong Zhang
- Yunnan Key Laboratory of Children's Major Disease Research, Yunnan Institute of Pediatrics, Kunming Children's Hospital, 288 Qianxing Road, Kunming, Yunnan, 650228, P.R. China.
| | - Wei Huang
- Shanghai-MOST Key Laboratory of Health and Disease Genomics, Shanghai Institute for Biomedical and Pharmaceutical Technologies (SIBPT), 2140 Xietu Road, Shanghai, 200032, P.R. China
| | - Jinxiu Shi
- Shanghai-MOST Key Laboratory of Health and Disease Genomics, Shanghai Institute for Biomedical and Pharmaceutical Technologies (SIBPT), 2140 Xietu Road, Shanghai, 200032, P.R. China.
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3
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Qiao X, Shi J, Xu H, Liu K, Pu Y, Xue X, Zheng W, Guo Y, Ma H, Wang CC, Bitsue HK, Xu X, Wang S, Zhao J, Guo X, Hou X, Wang X, Peng L, Qiu Z, Su B, Tang W, He Y, Guo J, Yang Z. Genetic diversity and dietary adaptations of the Central Plains Han Chinese population in East Asia. Commun Biol 2025; 8:291. [PMID: 39987348 PMCID: PMC11846999 DOI: 10.1038/s42003-025-07760-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2024] [Accepted: 02/17/2025] [Indexed: 02/24/2025] Open
Abstract
The Central Plains Han Chinese (CPHC) is the typical agricultural population of East Asia. Investigating the genome of the CPHC is crucial to understanding the genetic structure and adaptation of the modern humans in East Asia. Here, we perform whole genome sequencing of 492 CPHC individuals and obtained 22.65 million SNPs, 4.26 million INDELs and 41,959 SVs. We found the CPHC has a higher level of genetic diversity and the glycolipid metabolic genes show strong selection signals, e.g. LONP2, FADS2, FGF21 and SLC19A2. Ancient DNA analyses suggest that the domestication of crops, which drove the emergence of the candidate mutations. Notably, East Asian-specific SVs, e.g., DEL_21699 (LINC01749) and DEL_38406 (FAM102A) may be associated with the high prevalence of esophageal squamous carcinoma and primary angle-closure glaucoma. Our results provide an important genetic resource and show that dietary adaptations play an important role in phenotypic evolution in East Asian populations.
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Affiliation(s)
- Xiaoyang Qiao
- Tianjian Laboratory of Advanced Biomedical Sciences, Academy of Medical Science, Zhengzhou University, Zhengzhou, China
| | - Jianxiang Shi
- Tianjian Laboratory of Advanced Biomedical Sciences, Academy of Medical Science, Zhengzhou University, Zhengzhou, China
| | - Hongen Xu
- Tianjian Laboratory of Advanced Biomedical Sciences, Academy of Medical Science, Zhengzhou University, Zhengzhou, China
| | - Kai Liu
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Youwei Pu
- Tianjian Laboratory of Advanced Biomedical Sciences, Academy of Medical Science, Zhengzhou University, Zhengzhou, China
| | - Xia Xue
- Tianjian Laboratory of Advanced Biomedical Sciences, Academy of Medical Science, Zhengzhou University, Zhengzhou, China
| | - Wangshan Zheng
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Yongbo Guo
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Hao Ma
- State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Xiamen University, Xiamen, China
| | - Chuan-Chao Wang
- State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Xiamen University, Xiamen, China
| | - Habtom K Bitsue
- Tianjian Laboratory of Advanced Biomedical Sciences, Academy of Medical Science, Zhengzhou University, Zhengzhou, China
| | - Xiaoyu Xu
- Tianjian Laboratory of Advanced Biomedical Sciences, Academy of Medical Science, Zhengzhou University, Zhengzhou, China
| | - Shanshan Wang
- Tianjian Laboratory of Advanced Biomedical Sciences, Academy of Medical Science, Zhengzhou University, Zhengzhou, China
| | - Jingru Zhao
- Tianjian Laboratory of Advanced Biomedical Sciences, Academy of Medical Science, Zhengzhou University, Zhengzhou, China
| | - Xiangqian Guo
- Zhongyuan Intelligent Medical Laboratory, School of Basic Medical Sciences, Henan University, Kaifeng, China
| | - Xinyue Hou
- Tianjian Laboratory of Advanced Biomedical Sciences, Academy of Medical Science, Zhengzhou University, Zhengzhou, China
| | - Xinwei Wang
- Tianjian Laboratory of Advanced Biomedical Sciences, Academy of Medical Science, Zhengzhou University, Zhengzhou, China
| | - Lei Peng
- Tianjian Laboratory of Advanced Biomedical Sciences, Academy of Medical Science, Zhengzhou University, Zhengzhou, China
| | - Zan Qiu
- Tianjian Laboratory of Advanced Biomedical Sciences, Academy of Medical Science, Zhengzhou University, Zhengzhou, China
| | - Bing Su
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Wenxue Tang
- The Research and Application Center of Precision Medicine, Departments of Otolaryngology, The Second Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
| | - Yaoxi He
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China.
| | - Jiancheng Guo
- The Research and Application Center of Precision Medicine, The Second Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
| | - Zhaohui Yang
- Tianjian Laboratory of Advanced Biomedical Sciences, Academy of Medical Science, Zhengzhou University, Zhengzhou, China.
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4
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Zhu BY, Liu ZC, Zhao ZX, Huang HP, Zhang N, Xia J, Chen WW. Pharmacological Mechanism of Chinese Medicine in Systemic Lupus Erythematosus: A Narrative Review. Chin J Integr Med 2025; 31:157-169. [PMID: 39240290 DOI: 10.1007/s11655-024-3762-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/24/2024] [Indexed: 09/07/2024]
Abstract
Systemic lupus erythematosus (SLE) is a chronic autoimmune disorder affecting multiple systems, characterized by the development of harmful autoantibodies and immune complexes that lead to damage in organs and tissues. Chinese medicine (CM) plays a role in mitigating complications, enhancing treatment effectiveness, and reducing toxicity of concurrent medications, and ensuring a safe pregnancy. However, CM mainly solves the disease comprehensively through multi-target and multi-channel regulation process, therefore, its treatment mechanism is often complicated, involving many molecular links. This review introduces the research progress of pathogenesis of SLE from the aspects of genetics, epigenetics, innate immunity and acquired immunity, and then discusses the molecular mechanism and target of single Chinese herbal medicine and prescription that are commonly used and effective in clinic to treat SLE.
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Affiliation(s)
- Bo-Yu Zhu
- Department of Rheumatology, Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, 200071, China
| | - Zhi-Chao Liu
- Department of Rheumatology, Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, 200071, China
| | - Zhen-Xi Zhao
- Department of Rheumatology, Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, 200071, China
| | - Hui-Ping Huang
- Department of Rheumatology, Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, 200071, China
| | - Na Zhang
- Department of Rheumatology, Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, 200071, China
| | - Jia Xia
- Department of Rheumatology, Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, 200071, China
| | - Wei-Wei Chen
- Department of Rheumatology, Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, 200071, China.
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5
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Jiang T, Guo H, Liu Y, Li G, Cui Z, Cui X, Liu Y, Li Y, Zhang A, Cao S, Zhao T, Juan L, Kong W, Chen M, Liu D, Liu H, Zhang Y, Xu K, Wang Y, He M, Guo J, Lu M, Chen J, Zhao X, Zhao G, Dang S, Chen C, Wu X, Qin Q, Li Y, Shen H, Jin L, Liu B, Chen X, Zhao Y, Wang Y. A comprehensive genetic variant reference for the Chinese population. Sci Bull (Beijing) 2024; 69:3820-3825. [PMID: 38945749 DOI: 10.1016/j.scib.2024.06.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Revised: 03/07/2024] [Accepted: 04/28/2024] [Indexed: 07/02/2024]
Affiliation(s)
- Tao Jiang
- Faculty of Computing, Harbin Institute of Technology, Harbin 150001, China; Zhengzhou Research Institute, Harbin Institute of Technology, Zhengzhou 450000, China
| | - Hongzhe Guo
- Faculty of Computing, Harbin Institute of Technology, Harbin 150001, China; Zhengzhou Research Institute, Harbin Institute of Technology, Zhengzhou 450000, China
| | - Yadong Liu
- Faculty of Computing, Harbin Institute of Technology, Harbin 150001, China; Zhengzhou Research Institute, Harbin Institute of Technology, Zhengzhou 450000, China
| | - Gaoyang Li
- Faculty of Computing, Harbin Institute of Technology, Harbin 150001, China
| | - Zhe Cui
- Harbin Nebula Bioinformatics Technology Company, Harbin 150001, China
| | - Xinran Cui
- Faculty of Computing, Harbin Institute of Technology, Harbin 150001, China
| | - Yue Liu
- Faculty of Computing, Harbin Institute of Technology, Harbin 150001, China
| | - Yang Li
- Faculty of Computing, Harbin Institute of Technology, Harbin 150001, China
| | - Anqi Zhang
- Faculty of Computing, Harbin Institute of Technology, Harbin 150001, China
| | - Shuqi Cao
- Faculty of Computing, Harbin Institute of Technology, Harbin 150001, China
| | - Tianyi Zhao
- Zhengzhou Research Institute, Harbin Institute of Technology, Zhengzhou 450000, China; School of Medicine and Health, Harbin Institute of Technology, Harbin 150001, China
| | - Liran Juan
- School of Medicine and Health, Harbin Institute of Technology, Harbin 150001, China
| | - Weize Kong
- Faculty of Computing, Harbin Institute of Technology, Harbin 150001, China
| | - Ming Chen
- Harbin Nebula Bioinformatics Technology Company, Harbin 150001, China
| | - Dianming Liu
- Harbin Nebula Bioinformatics Technology Company, Harbin 150001, China
| | - Hongri Liu
- Harbin Nebula Bioinformatics Technology Company, Harbin 150001, China
| | - Yixiao Zhang
- Department of Urology Surgery, Key Laboratory of Precision Medical Research on Major Chronic Disease, Liaoning Province, Shengjing Hospital of China Medical University, Shenyang 110004, China
| | - Kelin Xu
- Fudan University Taizhou Institute of Health Sciences, Taizhou 200438, China; Department of Biostatistics, School of Public Health, Fudan University, Shanghai 200433, China
| | - Yongjun Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China; China National Clinical Research Center for Neurological Diseases, Beijing 100070, China
| | - Meian He
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Jiancheng Guo
- Henan Research Center for Genomic Sequencing and Translational Medicine, Zhengzhou University, Zhengzhou 450001, China; The Second Affiliated Hospital of Zhengzhou University, Zhengzhou 450014, China
| | - Ming Lu
- Clinical Epidemiology Unit, Qilu Hospital of Shandong University, Jinan 250012, China
| | - Jun Chen
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou 350001, China
| | - Xing Zhao
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu 610041, China
| | - Genming Zhao
- School of Public Health, Fudan University, Shanghai 200433, China
| | - Shaonong Dang
- School of Public Health, Xi'an Jiaotong University, Xi'an 710061, China
| | - Chao Chen
- Center for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, and Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha 410083, China
| | - Xiaojian Wu
- Department of Colorectal Surgery, the Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou 510655, China; Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, Sun Yat-sen University, Guangzhou 510655, China
| | - Qiyuan Qin
- Department of Colorectal Surgery, the Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou 510655, China; Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, Sun Yat-sen University, Guangzhou 510655, China
| | - Yixue Li
- Guangzhou Laboratory, Guangzhou 510005, China
| | - Hongbing Shen
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Li Jin
- Fudan University Taizhou Institute of Health Sciences, Taizhou 200438, China; State Key Laboratory of Genetic Engineering, Human Phenome Institute, and School of Life Sciences, Fudan University, Shanghai 200433, China
| | - Bo Liu
- Faculty of Computing, Harbin Institute of Technology, Harbin 150001, China; Zhengzhou Research Institute, Harbin Institute of Technology, Zhengzhou 450000, China.
| | - Xingdong Chen
- Fudan University Taizhou Institute of Health Sciences, Taizhou 200438, China; State Key Laboratory of Genetic Engineering, Human Phenome Institute, and School of Life Sciences, Fudan University, Shanghai 200433, China.
| | - Yuhong Zhao
- Department of Clinical Epidemiology, Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang 110004, China.
| | - Yadong Wang
- Faculty of Computing, Harbin Institute of Technology, Harbin 150001, China; Zhengzhou Research Institute, Harbin Institute of Technology, Zhengzhou 450000, China; School of Medicine and Health, Harbin Institute of Technology, Harbin 150001, China.
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Song T, Shi Y, Li Y, Hao D, Zhan K, Xu T, Chen R, He S. TOAnnoPriDB: an integrative database for trans-omic annotation and prioritization of non-coding variants across human genome. Sci Bull (Beijing) 2024:S2095-9273(24)00937-X. [PMID: 39736494 DOI: 10.1016/j.scib.2024.12.030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2024] [Revised: 10/28/2024] [Accepted: 12/09/2024] [Indexed: 01/01/2025]
Affiliation(s)
- Tingrui Song
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Yirong Shi
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yanyan Li
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Di Hao
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Kaixin Zhan
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Tao Xu
- National Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China; Shandong First Medical University & Shandong Academy of Medical Sciences, Taian 271016, China.
| | - Runsheng Chen
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China.
| | - Shunmin He
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China.
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Zhang S, Song Q, Zhang P, Wang X, Guo R, Li Y, Liu S, Yan X, Zhang J, Niu Y, Shi Y, Song T, Xu T, He S. Genome-wide investigation of VNTR motif polymorphisms in 8,222 genomes: Implications for biological regulation and human traits. CELL GENOMICS 2024; 4:100699. [PMID: 39609246 DOI: 10.1016/j.xgen.2024.100699] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/08/2024] [Revised: 08/31/2024] [Accepted: 11/01/2024] [Indexed: 11/30/2024]
Abstract
Variable number tandem repeat (VNTR) is a pervasive and highly mutable genetic feature that varies in both length and repeat sequence. Despite the well-studied copy-number variants, the functional impacts of repeat motif polymorphisms remain unknown. Here, we present the largest genome-wide VNTR polymorphism map to date, with over 2.5 million VNTR length polymorphisms (VNTR-LPs) and over 11 million VNTR motif polymorphisms (VNTR-MPs) detected in 8,222 high-coverage genomes. Leveraging the large-scale NyuWa cohort, we identified 2,982,456 (31.8%) NyuWa-specific VNTR-MPs, of which 95.3% were rare. Moreover, we found 1,937 out of 38,685 VNTRs that were associated with gene expression through VNTR-MPs in lymphoblastoid cell lines. Specifically, we clarified that the expansion of a likely causal motif could upregulate gene expression by improving the binding concentration of PU.1. We also explored the potential impacts of VNTR polymorphisms on phenotypic differentiation and disease susceptibility. This study expands our knowledge of VNTR-MPs and their functional implications.
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Affiliation(s)
- Sijia Zhang
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China; College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China; Department of Scientific Research, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
| | - Qiao Song
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Peng Zhang
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Xiaona Wang
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Rong Guo
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Yanyan Li
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Shuai Liu
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Xiaoyu Yan
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Jingjing Zhang
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Yiwei Niu
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Yirong Shi
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Tingrui Song
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Tao Xu
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China; National Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China; Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, Shandong 250117, China.
| | - Shunmin He
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China; College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China.
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8
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Shi L, Zhang P, Liu Q, Liu C, Cheng L, Yu B, Chen H. Genome-Wide Analysis of Genetic Diversity and Selection Signatures in Zaobei Beef Cattle. Animals (Basel) 2024; 14:2447. [PMID: 39199980 PMCID: PMC11350888 DOI: 10.3390/ani14162447] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2024] [Revised: 08/17/2024] [Accepted: 08/21/2024] [Indexed: 09/01/2024] Open
Abstract
This investigation provides a comprehensive analysis of genomic diversity and selection signatures in Zaobei beef cattle, an indigenous breed known for its adaptation to hot and humid climates and superior meat quality. Whole-genome resequencing was conducted on 23 Zaobei cattle, compared with 46 Simmental cattle to highlight genetic distinctions. Population structure analysis confirmed the genetic uniqueness of Zaobei cattle. Using methods such as DASDC v1.01, XPEHH, and θπ ratio, we identified 230, 232, and 221 genes through DASDC, including hard sweeps, soft sweeps, and linkage sweeps, respectively. Coincidentally, 109 genes were identified when using XPEHH and θπ ratio methods. Together, these analyses revealed eight positive selection genes (ARHGAP15, ZNF618, USH2A, PDZRN4, SPATA6, ROR2, KCNIP3, and VWA3B), which are linked to critical traits such as heat stress adaptation, fertility, and meat quality. Moreover, functional enrichment analyses showed pathways related to autophagy, immune response, energy metabolism, and muscle development. The comprehensive genomic insights gained from this study provide valuable knowledge for breeding programs aimed at enhancing the beneficial traits in Zaobei cattle.
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Affiliation(s)
- Liangyu Shi
- Laboratory of Genetic Breeding, Reproduction and Precision Livestock Farming & Hubei Provincial Center of Technology Innovation for Domestic Animal Breeding, School of Animal Science and Nutritional Engineering, Wuhan Polytechnic University, Wuhan 430023, China; (L.S.); (P.Z.); (Q.L.)
| | - Pu Zhang
- Laboratory of Genetic Breeding, Reproduction and Precision Livestock Farming & Hubei Provincial Center of Technology Innovation for Domestic Animal Breeding, School of Animal Science and Nutritional Engineering, Wuhan Polytechnic University, Wuhan 430023, China; (L.S.); (P.Z.); (Q.L.)
| | - Qing Liu
- Laboratory of Genetic Breeding, Reproduction and Precision Livestock Farming & Hubei Provincial Center of Technology Innovation for Domestic Animal Breeding, School of Animal Science and Nutritional Engineering, Wuhan Polytechnic University, Wuhan 430023, China; (L.S.); (P.Z.); (Q.L.)
| | - Chenhui Liu
- Institute of Animal Science and Veterinary Medicine, Wuhan Academy of Agricultural Sciences, Wuhan 430208, China; (C.L.); (L.C.)
| | - Lei Cheng
- Institute of Animal Science and Veterinary Medicine, Wuhan Academy of Agricultural Sciences, Wuhan 430208, China; (C.L.); (L.C.)
| | - Bo Yu
- Laboratory of Genetic Breeding, Reproduction and Precision Livestock Farming & Hubei Provincial Center of Technology Innovation for Domestic Animal Breeding, School of Animal Science and Nutritional Engineering, Wuhan Polytechnic University, Wuhan 430023, China; (L.S.); (P.Z.); (Q.L.)
| | - Hongbo Chen
- Laboratory of Genetic Breeding, Reproduction and Precision Livestock Farming & Hubei Provincial Center of Technology Innovation for Domestic Animal Breeding, School of Animal Science and Nutritional Engineering, Wuhan Polytechnic University, Wuhan 430023, China; (L.S.); (P.Z.); (Q.L.)
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9
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Ma Y, Gao K, Sun X, Wang J, Yang Y, Wu J, Chai A, Yao L, Liu N, Yu H, Su Y, Lu T, Wang L, Yue W, Zhang X, Xu L, Zhang D, Li J. STON2 variations are involved in synaptic dysfunction and schizophrenia-like behaviors by regulating Syt1 trafficking. Sci Bull (Beijing) 2024; 69:1458-1471. [PMID: 38402028 DOI: 10.1016/j.scib.2024.02.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2023] [Revised: 11/13/2023] [Accepted: 02/06/2024] [Indexed: 02/26/2024]
Abstract
Synaptic dysfunction is a core component of the pathophysiology of schizophrenia. However, the genetic risk factors and molecular mechanisms related to synaptic dysfunction are still not fully understood. The Stonin 2 (STON2) gene encodes a major adaptor for clathrin-mediated endocytosis (CME) of synaptic vesicles. In this study, we showed that the C-C (307Pro-851Ala) haplotype of STON2 increases the susceptibility to schizophrenia and examined whether STON2 variations cause schizophrenia-like behaviors through the regulation of CME. We found that schizophrenia-related STON2 variations led to protein dephosphorylation, which affected its interaction with synaptotagmin 1 (Syt1), a calcium sensor protein located in the presynaptic membrane that is critical for CME. STON2307Pro851Ala knockin mice exhibited deficits in synaptic transmission, short-term plasticity, and schizophrenia-like behaviors. Moreover, among seven antipsychotic drugs, patients with the C-C (307Pro-851Ala) haplotype responded better to haloperidol than did the T-A (307Ser-851Ser) carriers. The recovery of deficits in Syt1 sorting and synaptic transmission by acute administration of haloperidol effectively improved schizophrenia-like behaviors in STON2307Pro851Ala knockin mice. Our findings demonstrated the effect of schizophrenia-related STON2 variations on synaptic dysfunction through the regulation of CME, which might be attractive therapeutic targets for treating schizophrenia-like phenotypes.
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Affiliation(s)
- Yuanlin Ma
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Key Laboratory of Mental Health, Chinese Academy of Medical Sciences, Beijing 100191, China; The First Affiliated Hospital, Chongqing Medical University, Chongqing Key Laboratory of Neurology, Chongqing 400016, China
| | - Kai Gao
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Key Laboratory of Mental Health, Chinese Academy of Medical Sciences, Beijing 100191, China; Changping Laboratory, Beijing 102206, China
| | - Xiaoxuan Sun
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Key Laboratory of Mental Health, Chinese Academy of Medical Sciences, Beijing 100191, China
| | - Jinxin Wang
- Chinese Institute for Brain Research, Beijing 102206, China
| | - Yang Yang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Key Laboratory of Mental Health, Chinese Academy of Medical Sciences, Beijing 100191, China
| | - Jianying Wu
- Chinese Institute for Brain Research, Beijing 102206, China
| | - Anping Chai
- Laboratory of Learning and Memory, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650201, China; Shenzhen Key Laboratory of Translational Research for Brain Diseases, The Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen 518055, China
| | - Li Yao
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Nan Liu
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Hao Yu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Key Laboratory of Mental Health, Chinese Academy of Medical Sciences, Beijing 100191, China
| | - Yi Su
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Key Laboratory of Mental Health, Chinese Academy of Medical Sciences, Beijing 100191, China
| | - Tianlan Lu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Key Laboratory of Mental Health, Chinese Academy of Medical Sciences, Beijing 100191, China
| | - Lifang Wang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Key Laboratory of Mental Health, Chinese Academy of Medical Sciences, Beijing 100191, China
| | - Weihua Yue
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Key Laboratory of Mental Health, Chinese Academy of Medical Sciences, Beijing 100191, China; PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing 100871, China
| | - Xiaohui Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Lin Xu
- Laboratory of Learning and Memory, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650201, China
| | - Dai Zhang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Key Laboratory of Mental Health, Chinese Academy of Medical Sciences, Beijing 100191, China; Changping Laboratory, Beijing 102206, China
| | - Jun Li
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Key Laboratory of Mental Health, Chinese Academy of Medical Sciences, Beijing 100191, China; Changping Laboratory, Beijing 102206, China.
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10
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Chen Z, Finnell RH, Lei Y, Wang H. Progress and clinical prospect of genomic structural variants investigation. Sci Bull (Beijing) 2024; 69:705-708. [PMID: 38310047 DOI: 10.1016/j.scib.2024.01.035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2024]
Affiliation(s)
- Zhongzhong Chen
- Obstetrics and Gynecology Hospital, State Key Laboratory of Genetic Engineering, Institute of Reproduction and Development, Fudan University, Shanghai 200011, China; Shanghai Children's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200062, China
| | - Richard H Finnell
- Center for Precision Environmental Health, Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston 77030, USA; Departments of Molecular and Human Genetics and Medicine, Baylor College of Medicine, One Baylor Plaza, Houston 77030, USA
| | - Yunping Lei
- Center for Precision Environmental Health, Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston 77030, USA.
| | - Hongyan Wang
- Obstetrics and Gynecology Hospital, State Key Laboratory of Genetic Engineering, Institute of Reproduction and Development, Fudan University, Shanghai 200011, China; Shanghai Key Laboratory of Metabolic Remodelling and Health, Institute of Metabolism and Integrative Biology, Fudan University, Shanghai 200438, China; Children's Hospital of Fudan University, Shanghai 201102, China.
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11
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Liu S, Luo H, Zhang P, Li Y, Hao D, Zhang S, Song T, Xu T, He S. Adaptive Selection of Cis-regulatory Elements in the Han Chinese. Mol Biol Evol 2024; 41:msae034. [PMID: 38377343 PMCID: PMC10917166 DOI: 10.1093/molbev/msae034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2023] [Revised: 01/18/2024] [Accepted: 02/05/2024] [Indexed: 02/22/2024] Open
Abstract
Cis-regulatory elements have an important role in human adaptation to the living environment. However, the lag in population genomic cohort studies and epigenomic studies, hinders the research in the adaptive analysis of cis-regulatory elements in human populations. In this study, we collected 4,013 unrelated individuals and performed a comprehensive analysis of adaptive selection of genome-wide cis-regulatory elements in the Han Chinese. In total, 12.34% of genomic regions are under the influence of adaptive selection, where 1.00% of enhancers and 2.06% of promoters are under positive selection, and 0.06% of enhancers and 0.02% of promoters are under balancing selection. Gene ontology enrichment analysis of these cis-regulatory elements under adaptive selection reveals that many positive selections in the Han Chinese occur in pathways involved in cell-cell adhesion processes, and many balancing selections are related to immune processes. Two classes of adaptive cis-regulatory elements related to cell adhesion were in-depth analyzed, one is the adaptive enhancers derived from neanderthal introgression, leads to lower hyaluronidase level in skin, and brings better performance on UV-radiation resistance to the Han Chinese. Another one is the cis-regulatory elements regulating wound healing, and the results suggest the positive selection inhibits coagulation and promotes angiogenesis and wound healing in the Han Chinese. Finally, we found that many pathogenic alleles, such as risky alleles of type 2 diabetes or schizophrenia, remain in the population due to the hitchhiking effect of positive selections. Our findings will help deepen our understanding of the adaptive evolution of genome regulation in the Han Chinese.
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Affiliation(s)
- Shuai Liu
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Huaxia Luo
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Peng Zhang
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Yanyan Li
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Di Hao
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Sijia Zhang
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Tingrui Song
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Tao Xu
- National Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
- Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan 250117, Shandong, China
| | - Shunmin He
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
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12
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Takashima S, Tokiya M, Izui K, Miyamoto H, Matsumoto A. Asian flush is a potential protective factor against COVID-19: a web-based retrospective survey in Japan. Environ Health Prev Med 2024; 29:14. [PMID: 38462476 PMCID: PMC10937249 DOI: 10.1265/ehpm.23-00361] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Accepted: 02/10/2024] [Indexed: 03/12/2024] Open
Abstract
BACKGROUND Coronavirus disease 2019 (COVID-19), first reported in December 2019, spread worldwide in a short period, resulting in numerous cases and associated deaths; however, the toll was relatively low in East Asia. A genetic polymorphism unique to East Asians, Aldehyde dehydrogenase 2 rs671, has been reported to confer protection against infections. METHOD We retrospectively investigated the association between the surrogate marker of the rs671 variant, the skin flushing phenomenon after alcohol consumption, and the timing of COVID-19 incidence using a web-based survey tool to test any protective effects of rs671 against COVID-19. RESULTS A total of 807 valid responses were received from 362 non-flushers and 445 flushers. During the 42 months, from 12/1/2019 to 5/31/2023, 40.6% of non-flushers and 35.7% of flushers experienced COVID-19. Flushers tended to have a later onset (Spearman's partial rank correlation test, p = 0.057, adjusted for sex and age). Similarly, 2.5% of non-flushers and 0.5% of flushers were hospitalized because of COVID-19. Survival analysis estimated lower risks of COVID-19 and associated hospitalization among flushers (p = 0.03 and <0.01, respectively; generalized Wilcoxon test). With the Cox proportional hazards model covering 21 months till 8/31/2021, when approximately half of the Japanese population had received two doses of COVID-19 vaccine, the hazard ratio (95% confidence interval) of COVID-19 incidence was estimated to be 0.21 (0.10-0.46) for flusher versus non-flusher, with adjustment for sex, age, steroid use, and area of residence. CONCLUSIONS Our study suggests an association between the flushing phenomenon after drinking and a decreased risk of COVID-19 morbidity and hospitalization, suggesting that the rs671 variant is a protective factor. This study provides valuable information for infection control and helps understand the unique constitutional diversity of East Asians.
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Affiliation(s)
- Satoshi Takashima
- Department of Social and Environmental Medicine, Saga University, 5-1-1 Nabeshima, Saga 849-8501, Japan
- Plant Products Safety Division, Food Safety and Consumer Affairs Bureau, Ministry of Agriculture, Forestry and Fisheries, 1-2-1 Kasumigaseki, Chiyodaku, Tokyo 100-8950, Japan
| | - Mikiko Tokiya
- Department of Social and Environmental Medicine, Saga University, 5-1-1 Nabeshima, Saga 849-8501, Japan
| | - Katsura Izui
- Graduate School of Biostudies, Kyoto University, Oiwake-cho, Kitashirakawa, Sakyo-ku, Kyoto 606-8502, Japan
| | - Hiroshi Miyamoto
- Department of Pathology and Microbiology, Faculty of Medicine, Saga University, 5-1-1 Nabeshima, Saga 849-8501, Japan
| | - Akiko Matsumoto
- Department of Social and Environmental Medicine, Saga University, 5-1-1 Nabeshima, Saga 849-8501, Japan
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