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Liu J, Ye SY, Xu XD, Liu Q, Ma F, Yu X, Luo YH, Chen LL, Zeng X. Multiomics analysis reveals the genetic and metabolic characteristics associated with the low prevalence of dental caries. J Oral Microbiol 2023; 15:2277271. [PMID: 37928602 PMCID: PMC10623897 DOI: 10.1080/20002297.2023.2277271] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Accepted: 10/25/2023] [Indexed: 11/07/2023] Open
Abstract
Background Despite poor oral hygiene, the Baiku Yao (BKY) ethnic group in China presents a low prevalence of dental caries, which may be related to genetic susceptibility. Due to strict intra-ethnic marriage rule, this ethnic has an advantage in studying the interaction between genetic factors and other regulatory factors related to dental caries. Methods Peripheral blood from a caries-free adult male was used for whole genome sequencing, and the BKY assembled genome was compared to the Han Chinese genome. Oral saliva samples were collected from 51 subjects for metabolomic and metagenomic analysis. Multiomics data were integrated for combined analysis using bioinformatics approaches. Results Comparative genomic analysis revealed the presence of structural variations in several genes associated with dental caries. Metabolomic and metagenomic sequencing demonstrated the caries-free group had significantly higher concentration of antimicrobials and higher abundance of core oral health-related microbiota. The functional analysis indicated that cationic antimicrobial peptide resistance and the lipopolysaccharide biosynthesis pathway were enriched in the caries-free group. Conclusions Our study provided new insights into the specific regulatory mechanisms that contribute to the low prevalence of dental caries in the specific population and may provide new evidence for the genetic diagnosis and control of dental caries.
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Affiliation(s)
- Jinshen Liu
- College of Stomatology, Hospital of Stomatology, Guangxi Medical University, Nanning, China
| | - Si-Ying Ye
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, College of Life Science and Technology, Guangxi University, Nanning, China
| | - Xin-Dong Xu
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, College of Life Science and Technology, Guangxi University, Nanning, China
| | - Qiulin Liu
- College of Stomatology, Hospital of Stomatology, Guangxi Medical University, Nanning, China
| | - Fei Ma
- College of Stomatology, Hospital of Stomatology, Guangxi Medical University, Nanning, China
| | - Xueting Yu
- College of Stomatology, Hospital of Stomatology, Guangxi Medical University, Nanning, China
| | - Yu-Hong Luo
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, College of Life Science and Technology, Guangxi University, Nanning, China
| | - Ling-Ling Chen
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, College of Life Science and Technology, Guangxi University, Nanning, China
| | - Xiaojuan Zeng
- College of Stomatology, Hospital of Stomatology, Guangxi Medical University, Nanning, China
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2
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Xia X, Zhang F, Li S, Luo X, Peng L, Dong Z, Pausch H, Leonard AS, Crysnanto D, Wang S, Tong B, Lenstra JA, Han J, Li F, Xu T, Gu L, Jin L, Dang R, Huang Y, Lan X, Ren G, Wang Y, Gao Y, Ma Z, Cheng H, Ma Y, Chen H, Pang W, Lei C, Chen N. Structural variation and introgression from wild populations in East Asian cattle genomes confer adaptation to local environment. Genome Biol 2023; 24:211. [PMID: 37723525 PMCID: PMC10507960 DOI: 10.1186/s13059-023-03052-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Accepted: 09/07/2023] [Indexed: 09/20/2023] Open
Abstract
BACKGROUND Structural variations (SVs) in individual genomes are major determinants of complex traits, including adaptability to environmental variables. The Mongolian and Hainan cattle breeds in East Asia are of taurine and indicine origins that have evolved to adapt to cold and hot environments, respectively. However, few studies have investigated SVs in East Asian cattle genomes and their roles in environmental adaptation, and little is known about adaptively introgressed SVs in East Asian cattle. RESULTS In this study, we examine the roles of SVs in the climate adaptation of these two cattle lineages by generating highly contiguous chromosome-scale genome assemblies. Comparison of the two assemblies along with 18 Mongolian and Hainan cattle genomes obtained by long-read sequencing data provides a catalog of 123,898 nonredundant SVs. Several SVs detected from long reads are in exons of genes associated with epidermal differentiation, skin barrier, and bovine tuberculosis resistance. Functional investigations show that a 108-bp exonic insertion in SPN may affect the uptake of Mycobacterium tuberculosis by macrophages, which might contribute to the low susceptibility of Hainan cattle to bovine tuberculosis. Genotyping of 373 whole genomes from 39 breeds identifies 2610 SVs that are differentiated along a "north-south" gradient in China and overlap with 862 related genes that are enriched in pathways related to environmental adaptation. We identify 1457 Chinese indicine-stratified SVs that possibly originate from banteng and are frequent in Chinese indicine cattle. CONCLUSIONS Our findings highlight the unique contribution of SVs in East Asian cattle to environmental adaptation and disease resistance.
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Affiliation(s)
- Xiaoting Xia
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Xianyang, China
| | - Fengwei Zhang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Xianyang, China
| | - Shuang Li
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Xianyang, China
| | - Xiaoyu Luo
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Xianyang, China
| | - Lixin Peng
- National Engineering Research Center for Non-Food Biorefinery, Guangxi Academy of Sciences, 98 Daling Road, Nanning, China
| | - Zheng Dong
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Xianyang, China
| | - Hubert Pausch
- Animal Genomics, ETH Zurich, Universitaetstrasse 2, 8006, Zurich, Switzerland
| | - Alexander S Leonard
- Animal Genomics, ETH Zurich, Universitaetstrasse 2, 8006, Zurich, Switzerland
| | - Danang Crysnanto
- Animal Genomics, ETH Zurich, Universitaetstrasse 2, 8006, Zurich, Switzerland
| | - Shikang Wang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Xianyang, China
| | - Bin Tong
- The State Key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock, School of Life Sciences, Inner Mongolia University, Hohhot, China
| | - Johannes A Lenstra
- Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands
| | - Jianlin Han
- Livestock Genetics Program, International Livestock Research Institute (ILRI), Nairobi, Kenya
- CAAS-ILRI Joint Laboratory On Livestock and Forage Genetic Resources, Institute of Animal Science, Chinese Academy of Agriculture Sciences (CAAS), Beijing, China
| | - Fuyong Li
- Department of Infectious Diseases and Public Health, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Kowloon, Hong Kong SAR, China
| | - Tieshan Xu
- Tropical Crops Genetic Resources Institute, Chinese Academy of Tropical Agricultural Sciences, Haikou, China
| | - Lihong Gu
- Institute of Animal Science & Veterinary Medicine, Hainan Academy of Agricultural Sciences, Haikou, China
| | - Liangliang Jin
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Xianyang, China
| | - Ruihua Dang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Xianyang, China
| | - Yongzhen Huang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Xianyang, China
| | - Xianyong Lan
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Xianyang, China
| | - Gang Ren
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Xianyang, China
| | - Yu Wang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Xianyang, China
| | - Yuanpeng Gao
- College of Veterinary Medicine, Northwest A&F University, Xianyang, Yangling, China
| | - Zhijie Ma
- Qinghai Academy of Animal Science and Veterinary Medicine, Qinghai University, Xining, China
| | - Haijian Cheng
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Xianyang, China
- Institute of Animal Science and Veterinary Medicine, Shandong Academy of Agricultural Sciences, Shandong Key Lab of Animal Disease Control and Breeding, Jinan, China
| | - Yun Ma
- Key Laboratory of Ruminant Molecular and Cellular Breeding of Ningxia Hui Autonomous Region, School of Agriculture, Ningxia University, Yinchuan, China
| | - Hong Chen
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Xianyang, China
| | - Weijun Pang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Xianyang, China.
| | - Chuzhao Lei
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Xianyang, China.
| | - Ningbo Chen
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Xianyang, China.
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A pangenome reference representative of 36 minority Chinese ethnic groups. Nature 2023:10.1038/d41586-023-01675-w. [PMID: 37316594 DOI: 10.1038/d41586-023-01675-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
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Gao Y, Yang X, Chen H, Tan X, Yang Z, Deng L, Wang B, Kong S, Li S, Cui Y, Lei C, Wang Y, Pan Y, Ma S, Sun H, Zhao X, Shi Y, Yang Z, Wu D, Wu S, Zhao X, Shi B, Jin L, Hu Z, Lu Y, Chu J, Ye K, Xu S. A pangenome reference of 36 Chinese populations. Nature 2023:10.1038/s41586-023-06173-7. [PMID: 37316654 PMCID: PMC10322713 DOI: 10.1038/s41586-023-06173-7] [Citation(s) in RCA: 27] [Impact Index Per Article: 27.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2022] [Accepted: 05/05/2023] [Indexed: 06/16/2023]
Abstract
Human genomics is witnessing an ongoing paradigm shift from a single reference sequence to a pangenome form, but populations of Asian ancestry are underrepresented. Here we present data from the first phase of the Chinese Pangenome Consortium, including a collection of 116 high-quality and haplotype-phased de novo assemblies based on 58 core samples representing 36 minority Chinese ethnic groups. With an average 30.65× high-fidelity long-read sequence coverage, an average contiguity N50 of more than 35.63 megabases and an average total size of 3.01 gigabases, the CPC core assemblies add 189 million base pairs of euchromatic polymorphic sequences and 1,367 protein-coding gene duplications to GRCh38. We identified 15.9 million small variants and 78,072 structural variants, of which 5.9 million small variants and 34,223 structural variants were not reported in a recently released pangenome reference1. The Chinese Pangenome Consortium data demonstrate a remarkable increase in the discovery of novel and missing sequences when individuals are included from underrepresented minority ethnic groups. The missing reference sequences were enriched with archaic-derived alleles and genes that confer essential functions related to keratinization, response to ultraviolet radiation, DNA repair, immunological responses and lifespan, implying great potential for shedding new light on human evolution and recovering missing heritability in complex disease mapping.
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Affiliation(s)
- Yang Gao
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, School of Life Sciences, Fudan University, Shanghai, China
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, Fudan University, Shanghai, China
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
- School of Life Science and Technology, ShanghaiTech University, Shanghai, 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
- Genome Institute, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Hao Chen
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Xinjiang Tan
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Zhaoqing Yang
- Department of Medical Genetics, Institute of Medical Biology, Chinese Academy of Medical Sciences, Kunming, China
| | - Lian Deng
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, School of Life Sciences, Fudan University, Shanghai, China
| | - Baonan Wang
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, Fudan University, Shanghai, China
| | - Shuang Kong
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, Fudan University, Shanghai, China
| | - Songyang Li
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, Fudan University, Shanghai, China
| | - Yuhang Cui
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, Fudan University, Shanghai, China
| | - Chang Lei
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, School of Life Sciences, Fudan University, Shanghai, China
| | - Yimin Wang
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Yuwen Pan
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Sen Ma
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Hao Sun
- Department of Medical Genetics, Institute of Medical Biology, Chinese Academy of Medical Sciences, Kunming, China
| | - Xiaohan Zhao
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, Fudan University, Shanghai, China
| | - Yingbing Shi
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, School of Life Sciences, Fudan University, Shanghai, China
| | - Ziyi Yang
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, School of Life Sciences, Fudan University, Shanghai, China
| | - Dongdong Wu
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Shaoyuan Wu
- Jiangsu Key Laboratory of Phylogenomics & Comparative Genomics, International Joint Center of Genomics of Jiangsu Province School of Life Sciences, Jiangsu Normal University, Xuzhou, China
| | - Xingming Zhao
- Institute of Science and Technology for Brain-Inspired Intelligence, Ministry of Education Key (MOE) Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, MOE Frontiers Center for Brain Science Fudan University, Shanghai, China
| | - Binyin Shi
- Department of Endocrinology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Li Jin
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, School of Life Sciences, Fudan University, Shanghai, China
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, Fudan University, Shanghai, China
| | - Zhibin Hu
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Yan Lu
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, School of Life Sciences, Fudan University, Shanghai, China.
| | - Jiayou Chu
- Department of Medical Genetics, Institute of Medical Biology, Chinese Academy of Medical Sciences, Kunming, China.
| | - Kai Ye
- 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.
- School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China.
| | - Shuhua Xu
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, School of Life Sciences, Fudan University, Shanghai, China.
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, Fudan University, Shanghai, China.
- School of Life Science and Technology, ShanghaiTech University, Shanghai, China.
- Jiangsu Key Laboratory of Phylogenomics & Comparative Genomics, International Joint Center of Genomics of Jiangsu Province School of Life Sciences, Jiangsu Normal University, Xuzhou, China.
- Department of Liver Surgery and Transplantation Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China.
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, China.
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5
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Chao KH, Zimin AV, Pertea M, Salzberg SL. The first gapless, reference-quality, fully annotated genome from a Southern Han Chinese individual. G3 (BETHESDA, MD.) 2023; 13:jkac321. [PMID: 36630290 PMCID: PMC9997556 DOI: 10.1093/g3journal/jkac321] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Revised: 10/27/2022] [Accepted: 11/03/2022] [Indexed: 01/12/2023]
Abstract
We used long-read DNA sequencing to assemble the genome of a Southern Han Chinese male. We organized the sequence into chromosomes and filled in gaps using the recently completed T2T-CHM13 genome as a guide, yielding a gap-free genome, Han1, containing 3,099,707,698 bases. Using the T2T-CHM13 annotation as a reference, we mapped all genes onto the Han1 genome and identified additional gene copies, generating a total of 60,708 putative genes, of which 20,003 are protein-coding. A comprehensive comparison between the genes revealed that 235 protein-coding genes were substantially different between the individuals, with frameshifts or truncations affecting the protein-coding sequence. Most of these were heterozygous variants in which one gene copy was unaffected. This represents the first gene-level comparison between two finished, annotated individual human genomes.
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Affiliation(s)
- Kuan-Hao Chao
- Department of Computer Science, Johns Hopkins University, Baltimore, MD 21218, USA
- Center for Computational Biology, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Aleksey V Zimin
- Center for Computational Biology, Johns Hopkins University, Baltimore, MD 21218, USA
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Mihaela Pertea
- Center for Computational Biology, Johns Hopkins University, Baltimore, MD 21218, USA
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Steven L Salzberg
- Department of Computer Science, Johns Hopkins University, Baltimore, MD 21218, USA
- Center for Computational Biology, Johns Hopkins University, Baltimore, MD 21218, USA
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
- Department of Biostatistics, Johns Hopkins University, Baltimore, MD 21211, USA
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6
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Xu H, Zhao M, Mei S, Zhang Y, Cai M, Lei F, Zhu B. Allelic and haplotypic polymorphisms and paternal genetic analysis of Chinese Shaanxi Han population utilizing a multiplex Y-STR set. Ann Hum Biol 2022; 49:361-366. [PMID: 36437608 DOI: 10.1080/03014460.2022.2152487] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
BACKGROUND The analysis of Y chromosomal genetic markers is of great significance in human genetic fields related to male individuals. The Han nationality is the most populous ethnic group. It is critical to investigate the Y-chromosome short tandem repeat (Y-STR) genetic informativeness of Han nationalities in different Chinese regions in order to gain a comprehensive understanding of their paternal genetic relationships and origin. AIM To assess the allelic and haplotypic polymorphisms of the novel AGCU Y SUPP STR amplification system containing seven Y-STRs in the maximal dataset of the Y-STR Haplotype Reference Database (YHRD) and 17 newly included Y-STRs, and explore the genetic relationships among the Shaanxi Han population and 12 reference populations from China. SUBJECTS AND METHODS A total sample of 220 Han male subjects were obtained from the Shaanxi Province, China, and genotyped by the novel AGCU Y SUPP STR amplification system. Multiplex population genetic analyses derived from the same 16 Y-STR loci were carried out among the Shaanxi Han population and 12 reference populations from China. RESULTS The gene diversities (GD) ranged from the maximum value of 0.9609 (DYS385a,b) to the minimum value of 0.5441 (DYS531). Besides, 217 distinct haplotypes were detected wholly in 220 individuals, of which 214 (98.62%) were exclusive. The entire haplotype diversity (HD) and discrimination capacity (DC) were 0.9999 and 0.9864, respectively, while the haplotype match probability (HMP) was 0.0045. Among the reference populations, the obtained results of population genetic analyses revealed that the Shaanxi Han population had the largest genetic distance with the Guangxi Yao group, but the smallest genetic distance with the Hunan Tujia group. CONCLUSIONS These Y-STR loci in the AGCU Y SUPP STR amplification system were of high genetic polymorphisms and the amplification system could be used as a prospective complementary tool for forensic application and paternal genetics in the Shaanxi Han population.
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Affiliation(s)
- Hui Xu
- Guangzhou Key Laboratory of Forensic Multi-Omics for Precision Identification, School of Forensic Medicine, Southern Medical University, Guangzhou, China
| | - Ming Zhao
- Guangzhou Key Laboratory of Forensic Multi-Omics for Precision Identification, School of Forensic Medicine, Southern Medical University, Guangzhou, China
| | - Shuyan Mei
- Guangzhou Key Laboratory of Forensic Multi-Omics for Precision Identification, School of Forensic Medicine, Southern Medical University, Guangzhou, China
| | - Yunying Zhang
- Guangzhou Key Laboratory of Forensic Multi-Omics for Precision Identification, School of Forensic Medicine, Southern Medical University, Guangzhou, China
| | - Meiming Cai
- Guangzhou Key Laboratory of Forensic Multi-Omics for Precision Identification, School of Forensic Medicine, Southern Medical University, Guangzhou, China
| | - Fanzhang Lei
- Guangzhou Key Laboratory of Forensic Multi-Omics for Precision Identification, School of Forensic Medicine, Southern Medical University, Guangzhou, China
| | - Bofeng Zhu
- Guangzhou Key Laboratory of Forensic Multi-Omics for Precision Identification, School of Forensic Medicine, Southern Medical University, Guangzhou, China.,Clinical Research Center of Shaanxi Province for Dental and Maxillofacial Diseases, College of Stomatology, Xi'an Jiaotong University, Xi'an, China
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7
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Deng L, Xie B, Wang Y, Zhang X, Xu S. A protocol for applying a population-specific reference genome assembly to population genetics and medical studies. STAR Protoc 2022; 3:101440. [PMID: 35664259 PMCID: PMC9157554 DOI: 10.1016/j.xpro.2022.101440] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
Abstract
With a growing number of available de novo sequenced genomes, protocols for their applications to population genetics will benefit our understanding of the human genome. Here we detail analytic steps to apply an example de novo reference genome to map and detect variants of short-read sequences from corresponding populations and to discover variants of disease-relevant genes. Using this protocol, we can improve variant discovery, better investigate population-specific genome properties, and evaluate the potential of sequenced genomes in medical studies. For complete details on the use and execution of this protocol, please refer to Lou et al. (2022). Protocol for mapping and variants detection of short-read sequences Advantages of using a population-specific reference genome in population genomic studies Analytic steps to discover potential variants of disease-relevant genes
Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.
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Affiliation(s)
- Lian Deng
- State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, Collaborative Innovation Center of Genetics and Development, School of Life Sciences, Fudan University, Shanghai 200438, China
| | - Bo Xie
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Yimin Wang
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Xiaoxi Zhang
- School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China
| | - Shuhua Xu
- State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, Collaborative Innovation Center of Genetics and Development, School of Life Sciences, Fudan University, Shanghai 200438, China
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
- School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China
- Human Phenome Institute, Zhangjiang Fudan International Innovation Center, and Ministry of Education Key Laboratory of Contemporary Anthropology, Fudan University, Shanghai 201203, China
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming 650223, China
- Corresponding author
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8
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Evaluation of Lou et al.: Proposed benefits of a population-specific genome reference. Cell Syst 2022; 13:265-267. [PMID: 35447075 DOI: 10.1016/j.cels.2022.03.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
One snapshot of the peer review process for "Haplo-type-resolved de novo assembly of a Tujia genome suggests the necessity for high-quality population-specific genome references" (Lou et al., 2022).
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