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Cooke NP, Murray M, Cassidy LM, Mattiangeli V, Okazaki K, Kasai K, Gakuhari T, Bradley DG, Nakagome S. Genomic imputation of ancient Asian populations contrasts local adaptation in pre- and post-agricultural Japan. iScience 2024; 27:110050. [PMID: 38883821 PMCID: PMC11176660 DOI: 10.1016/j.isci.2024.110050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2023] [Revised: 03/25/2024] [Accepted: 05/17/2024] [Indexed: 06/18/2024] Open
Abstract
Early modern humans lived as hunter-gatherers for millennia before agriculture, yet the genetic adaptations of these populations remain a mystery. Here, we investigate selection in the ancient hunter-gatherer-fisher Jomon and contrast pre- and post-agricultural adaptation in the Japanese archipelago. Building on the successful validation of imputation with ancient Asian genomes, we identify selection signatures in the Jomon, particularly robust signals from KITLG variants, which may have influenced dark pigmentation evolution. The Jomon lacks well-known adaptive variants (EDAR, ADH1B, and ALDH2), marking their emergence after the advent of farming in the archipelago. Notably, the EDAR and ADH1B variants were prevalent in the archipelago 1,300 years ago, whereas the ALDH2 variant could have emerged later due to its absence in other ancient genomes. Overall, our study underpins local adaptation unique to the Jomon population, which in turn sheds light on post-farming selection that continues to shape contemporary Asian populations.
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Affiliation(s)
- Niall P Cooke
- School of Medicine, Trinity College Dublin, Dublin, Ireland
| | | | - Lara M Cassidy
- Smurfit Institute of Genetics, Trinity College Dublin, Dublin, Ireland
| | | | - Kenji Okazaki
- Department of Anatomy, Faculty of Medicine, Tottori University, Yonago, Japan
| | - Kenji Kasai
- Toyama Prefectural Center for Archaeological Operations, Toyama, Japan
| | - Takashi Gakuhari
- Institute for the Study of Ancient Civilizations and Cultural Resources, Kanazawa University, Kanazawa, Japan
| | - Daniel G Bradley
- Smurfit Institute of Genetics, Trinity College Dublin, Dublin, Ireland
| | - Shigeki Nakagome
- School of Medicine, Trinity College Dublin, Dublin, Ireland
- Institute for the Study of Ancient Civilizations and Cultural Resources, Kanazawa University, Kanazawa, Japan
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2
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Su H, Wang M, Li X, Duan S, Sun Q, Sun Y, Wang Z, Yang Q, Huang Y, Zhong J, Chen J, Jiang X, Ma J, Yang T, Liu Y, Luo L, Liu Y, Yang J, Chen G, Liu C, Cai Y, He G. Population genetic admixture and evolutionary history in the Shandong Peninsula inferred from integrative modern and ancient genomic resources. BMC Genomics 2024; 25:611. [PMID: 38890579 PMCID: PMC11184692 DOI: 10.1186/s12864-024-10514-9] [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: 03/15/2024] [Accepted: 06/11/2024] [Indexed: 06/20/2024] Open
Abstract
BACKGROUND Ancient northern East Asians (ANEA) from the Yellow River region, who pioneered millet cultivation, play a crucial role in understanding the origins of ethnolinguistically diverse populations in modern China and the entire landscape of deep genetic structure and variation discovery in modern East Asians. However, the direct links between ANEA and geographically proximate modern populations, as well as the biological adaptive processes involved, remain poorly understood. RESULTS Here, we generated genome-wide SNP data for 264 individuals from geographically different Han populations in Shandong. An integrated genomic resource encompassing both modern and ancient East Asians was compiled to examine fine-scale population admixture scenarios and adaptive traits. The reconstruction of demographic history and hierarchical clustering patterns revealed that individuals from the Shandong Peninsula share a close genetic affinity with ANEA, indicating long-term genetic continuity and mobility in the lower Yellow River basin since the early Neolithic period. Biological adaptive signatures, including those related to immune and metabolic pathways, were identified through analyses of haplotype homozygosity and allele frequency spectra. These signatures are linked to complex traits such as height and body mass index, which may be associated with adaptations to cold environments, dietary practices, and pathogen exposure. Additionally, allele frequency trajectories over time and a haplotype network of two highly differentiated genes, ABCC11 and SLC10A1, were delineated. These genes, which are associated with axillary odor and bilirubin metabolism, respectively, illustrate how local adaptations can influence the diversification of traits in East Asians. CONCLUSIONS Our findings provide a comprehensive genomic dataset that elucidates the fine-scale genetic history and evolutionary trajectory of natural selection signals and disease susceptibility in Han Chinese populations. This study serves as a paradigm for integrating spatiotemporally diverse ancient genomes in the era of population genomic medicine.
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Affiliation(s)
- Haoran Su
- Genetic and Prenatal Diagnosis Center, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637007, Sichuan, China
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610000, China
- School of Laboratory Medicine, North Sichuan Medical College, Nanchong, 637007, Sichuan, China
| | - Mengge Wang
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610000, China.
- Center for Archaeological Science, Sichuan University, Chengdu, 610000, China.
- Research Center for Genomic Medicine, North Sichuan Medical College, Nanchong, 637100, China.
| | - Xiangping Li
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610000, China
- School of Forensic Medicine, Kunming Medical University, Kunming, 650500, China
| | - Shuhan Duan
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610000, China
- Research Center for Genomic Medicine, North Sichuan Medical College, Nanchong, 637100, China
- Institute of Basic Medicine and Forensic Medicine, North Sichuan Medical College and Genetic and Prenatal Diagnosis Center, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637007, Sichuan, China
| | - Qiuxia Sun
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610000, China
- Department of Forensic Medicine, College of Basic Medicine, Chongqing Medical University, Chongqing, 400331, China
| | - Yuntao Sun
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610000, China
- West China School of Basic Science & Forensic Medicine, Sichuan University, Chengdu, 610041, China
| | - Zhiyong Wang
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610000, China
- School of Forensic Medicine, Kunming Medical University, Kunming, 650500, China
| | - Qingxin Yang
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610000, China
- School of Forensic Medicine, Kunming Medical University, Kunming, 650500, China
| | - Yuguo Huang
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610000, China
| | - Jie Zhong
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610000, China
| | - Jing Chen
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610000, China
- School of Forensic Medicine, Shanxi Medical University, Jinzhong, 030001, China
| | - Xiucheng Jiang
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610000, China
- Research Center for Genomic Medicine, North Sichuan Medical College, Nanchong, 637100, China
- Institute of Basic Medicine and Forensic Medicine, North Sichuan Medical College and Genetic and Prenatal Diagnosis Center, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637007, Sichuan, China
| | - Jinyue Ma
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610000, China
- Research Center for Genomic Medicine, North Sichuan Medical College, Nanchong, 637100, China
- Institute of Basic Medicine and Forensic Medicine, North Sichuan Medical College and Genetic and Prenatal Diagnosis Center, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637007, Sichuan, China
| | - Ting Yang
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610000, China
- School of Forensic Medicine, Kunming Medical University, Kunming, 650500, China
| | - Yunhui Liu
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610000, China
- Department of Forensic Medicine, College of Basic Medicine, Chongqing Medical University, Chongqing, 400331, China
| | - Lintao Luo
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610000, China
- Department of Forensic Medicine, College of Basic Medicine, Chongqing Medical University, Chongqing, 400331, China
| | - Yan Liu
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610000, China
- Research Center for Genomic Medicine, North Sichuan Medical College, Nanchong, 637100, China
- Institute of Basic Medicine and Forensic Medicine, North Sichuan Medical College and Genetic and Prenatal Diagnosis Center, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637007, Sichuan, China
| | - Junbao Yang
- Research Center for Genomic Medicine, North Sichuan Medical College, Nanchong, 637100, China
- Institute of Basic Medicine and Forensic Medicine, North Sichuan Medical College and Genetic and Prenatal Diagnosis Center, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637007, Sichuan, China
| | - Gang Chen
- Hunan Key Laboratory of Bioinformatics, School of Computer Science and Engineering, Central South University, Changsha, 410075, China
| | - Chao Liu
- Anti-Drug Technology Center of Guangdong Province, Guangzhou, 510230, China.
| | - Yan Cai
- Genetic and Prenatal Diagnosis Center, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637007, Sichuan, China.
| | - Guanglin He
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610000, China.
- Center for Archaeological Science, Sichuan University, Chengdu, 610000, China.
- Research Center for Genomic Medicine, North Sichuan Medical College, Nanchong, 637100, China.
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Liang B, Bai T, Zhao Y, Han J, He X, Pu Y, Wang C, Liu W, Ma Q, Tian K, Zheng W, Liu N, Liu J, Ma Y, Jiang L. Two mutations at KRT74 and EDAR synergistically drive the fine-wool production in Chinese sheep. J Adv Res 2024; 57:1-13. [PMID: 37137429 PMCID: PMC10918353 DOI: 10.1016/j.jare.2023.04.012] [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: 11/02/2022] [Revised: 04/13/2023] [Accepted: 04/14/2023] [Indexed: 05/05/2023] Open
Abstract
INTRODUCTION Fine-wool sheep are the most common breed used by the wool industry worldwide. Fine-wool sheep have over a three-fold higher follicle density and a 50% smaller fiber diameter than coarse-wool sheep. OBJECTIVES This study aims to clarify the underlying genetic basis for the denser and finer wool phenotype in fine-wool breeds. METHOD Whole-genome sequences of 140 samples, Ovine HD630K SNP array data of 385 samples, including fine, semi-fine, and coarse wool sheep, as well as skin transcriptomes of nine samples were integrated for genomic selection signature analysis. RESULTS Two loci at keratin 74 (KRT74) and ectodysplasin receptor (EDAR) were revealed. Fine-scale analysis in 250 fine/semi-fine and 198 coarse wool sheep narrowed this association to one C/A missense variant of KRT74 (OAR3:133,486,008, P = 1.02E-67) and one T/C SNP in the regulatory region upstream of EDAR (OAR3:61,927,840, P = 2.50E-43). Cellular over-expression and ovine skin section staining assays confirmed that C-KRT74 activated the KRT74 protein and specifically enlarged cell size at the Huxley's layer of the inner root sheath (P < 0.01). This structure enhancement shapes the growing hair shaft into the finer wool than the wild type. Luciferase assays validated that the C-to-T mutation upregulated EDAR mRNA expression via a newly created SOX2 binding site and potentially led to the formation of more hair placodes. CONCLUSIONS Two functional mutations driving finer and denser wool production were characterized and offered new targets for genetic breeding during wool sheep selection. This study not only provides a theoretical basis for future selection of fine wool sheep breeds but also contributes to improving the value of wool commodities.
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Affiliation(s)
- Benmeng Liang
- National Germplasm Center of Domestic Animal Resources, Ministry of Technology, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing, China; National Engineering Laboratory for Animal Breeding and MOA Key Laboratory of Animal Genetics and Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China; Key Laboratory of Livestock and Poultry Resources (Cattle) Evaluation and Utilization, Ministry of Agriculture and Rural Affairs, China
| | - Tianyou Bai
- National Germplasm Center of Domestic Animal Resources, Ministry of Technology, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing, China; Key Laboratory of Livestock and Poultry Resources (Cattle) Evaluation and Utilization, Ministry of Agriculture and Rural Affairs, China
| | - Yuhetian Zhao
- National Germplasm Center of Domestic Animal Resources, Ministry of Technology, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing, China; Key Laboratory of Livestock and Poultry Resources (Cattle) Evaluation and Utilization, Ministry of Agriculture and Rural Affairs, China
| | - Jiangang Han
- National Germplasm Center of Domestic Animal Resources, Ministry of Technology, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing, China; Key Laboratory of Livestock and Poultry Resources (Cattle) Evaluation and Utilization, Ministry of Agriculture and Rural Affairs, China; Animal Genomics Laboratory, UCD School of Agriculture and Food Science, UCD College of Health and Agricultural Sciences, University College Dublin, Belfield, Dublin D04 V1W8, Ireland
| | - Xiaohong He
- National Germplasm Center of Domestic Animal Resources, Ministry of Technology, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing, China; Key Laboratory of Livestock and Poultry Resources (Cattle) Evaluation and Utilization, Ministry of Agriculture and Rural Affairs, China
| | - Yabin Pu
- National Germplasm Center of Domestic Animal Resources, Ministry of Technology, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing, China; Key Laboratory of Livestock and Poultry Resources (Cattle) Evaluation and Utilization, Ministry of Agriculture and Rural Affairs, China
| | - Chunxin Wang
- Institute of Animal Sciences, Jilin Academy of Agricultural Sciences, Gongzhuling 136100, China
| | - Wujun Liu
- College of Animal Science, Xinjiang Agriculture University, Urumqi, Xinjiang, China
| | - Qing Ma
- Institute of Animal Science, Ningxia Academy of Agriculture and Forestry Sciences, Yinchuan 75002, Ningxia, China
| | - Kechuan Tian
- Institute of Animal Science and Veterinary Medicine, Shandong Academy of Agricultural Sciences, Jinan, China; Xinjiang Academy of Animal Science, China
| | | | - Nan Liu
- College of Animal Science and Technology, Qingdao Agricultural University, China
| | - Jianfeng Liu
- National Engineering Laboratory for Animal Breeding and MOA Key Laboratory of Animal Genetics and Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China.
| | - Yuehui Ma
- National Germplasm Center of Domestic Animal Resources, Ministry of Technology, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing, China; Key Laboratory of Livestock and Poultry Resources (Cattle) Evaluation and Utilization, Ministry of Agriculture and Rural Affairs, China.
| | - Lin Jiang
- National Germplasm Center of Domestic Animal Resources, Ministry of Technology, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing, China; Key Laboratory of Livestock and Poultry Resources (Cattle) Evaluation and Utilization, Ministry of Agriculture and Rural Affairs, China.
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4
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Liu X, Matsunami M, Horikoshi M, Ito S, Ishikawa Y, Suzuki K, Momozawa Y, Niida S, Kimura R, Ozaki K, Maeda S, Imamura M, Terao C. Natural Selection Signatures in the Hondo and Ryukyu Japanese Subpopulations. Mol Biol Evol 2023; 40:msad231. [PMID: 37903429 PMCID: PMC10615566 DOI: 10.1093/molbev/msad231] [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: 03/27/2023] [Revised: 09/20/2023] [Accepted: 10/06/2023] [Indexed: 11/01/2023] Open
Abstract
Natural selection signatures across Japanese subpopulations are under-explored. Here we conducted genome-wide selection scans with 622,926 single nucleotide polymorphisms for 20,366 Japanese individuals, who were recruited from the main-islands of Japanese Archipelago (Hondo) and the Ryukyu Archipelago (Ryukyu), representing two major Japanese subpopulations. The integrated haplotype score (iHS) analysis identified several signals in one or both subpopulations. We found a novel candidate locus at IKZF2, especially in Ryukyu. Significant signals were observed in the major histocompatibility complex region in both subpopulations. The lead variants differed and demonstrated substantial allele frequency differences between Hondo and Ryukyu. The lead variant in Hondo tags HLA-A*33:03-C*14:03-B*44:03-DRB1*13:02-DQB1*06:04-DPB1*04:01, a haplotype specific to Japanese and Korean. While in Ryukyu, the lead variant tags DRB1*15:01-DQB1*06:02, which had been recognized as a genetic risk factor for narcolepsy. In contrast, it is reported to confer protective effects against type 1 diabetes and human T lymphotropic virus type 1-associated myelopathy/tropical spastic paraparesis. The FastSMC analysis identified 8 loci potentially affected by selection within the past 20-150 generations, including 2 novel candidate loci. The analysis also showed differences in selection patterns of ALDH2 between Hondo and Ryukyu, a gene recognized to be specifically targeted by selection in East Asian. In summary, our study provided insights into the selection signatures within the Japanese and nominated potential sources of selection pressure.
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Affiliation(s)
- Xiaoxi Liu
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Clinical Research Center, Shizuoka General Hospital, Shizuoka, Japan
| | - Masatoshi Matsunami
- Department of Advanced Genomic and Laboratory Medicine, Graduate School of Medicine, University of the Ryukyus, Nishihara-Cho, Japan
| | - Momoko Horikoshi
- Laboratory for Genomics of Diabetes and Metabolism, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Shuji Ito
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Yuki Ishikawa
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Kunihiko Suzuki
- Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Yukihide Momozawa
- Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Shumpei Niida
- Core Facility Administration, Research Institute, National Center for Geriatrics and Gerontology, Obu, Japan
| | - Ryosuke Kimura
- Department of Human Biology and Anatomy, Graduate School of Medicine, University of the Ryukyus, Nishihara-Cho, Japan
| | - Kouichi Ozaki
- Medical Genome Center, Research Institute, National Center for Geriatrics and Gerontology, Obu, Japan
| | - Shiro Maeda
- Department of Advanced Genomic and Laboratory Medicine, Graduate School of Medicine, University of the Ryukyus, Nishihara-Cho, Japan
- Division of Clinical Laboratory and Blood Transfusion, University of the Ryukyus Hospital, Okinawa, Japan
| | - Minako Imamura
- Department of Advanced Genomic and Laboratory Medicine, Graduate School of Medicine, University of the Ryukyus, Nishihara-Cho, Japan
- Division of Clinical Laboratory and Blood Transfusion, University of the Ryukyus Hospital, Okinawa, Japan
| | - Chikashi Terao
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Clinical Research Center, Shizuoka General Hospital, Shizuoka, Japan
- The Department of Applied Genetics, School of Pharmaceutical Sciences, University of Shizuoka, Shizuoka, Japan
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5
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Li Y, Xiong Z, Zhang M, Hysi PG, Qian Y, Adhikari K, Weng J, Wu S, Du S, Gonzalez-Jose R, Schuler-Faccini L, Bortolini MC, Acuna-Alonzo V, Canizales-Quinteros S, Gallo C, Poletti G, Bedoya G, Rothhammer F, Wang J, Tan J, Yuan Z, Jin L, Uitterlinden AG, Ghanbari M, Ikram MA, Nijsten T, Zhu X, Lei Z, Jia P, Ruiz-Linares A, Spector TD, Wang S, Kayser M, Liu F. Combined genome-wide association study of 136 quantitative ear morphology traits in multiple populations reveal 8 novel loci. PLoS Genet 2023; 19:e1010786. [PMID: 37459304 PMCID: PMC10351707 DOI: 10.1371/journal.pgen.1010786] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2022] [Accepted: 05/16/2023] [Indexed: 07/20/2023] Open
Abstract
Human ear morphology, a complex anatomical structure represented by a multidimensional set of correlated and heritable phenotypes, has a poorly understood genetic architecture. In this study, we quantitatively assessed 136 ear morphology traits using deep learning analysis of digital face images in 14,921 individuals from five different cohorts in Europe, Asia, and Latin America. Through GWAS meta-analysis and C-GWASs, a recently introduced method to effectively combine GWASs of many traits, we identified 16 genetic loci involved in various ear phenotypes, eight of which have not been previously associated with human ear features. Our findings suggest that ear morphology shares genetic determinants with other surface ectoderm-derived traits such as facial variation, mono eyebrow, and male pattern baldness. Our results enhance the genetic understanding of human ear morphology and shed light on the shared genetic contributors of different surface ectoderm-derived phenotypes. Additionally, gene editing experiments in mice have demonstrated that knocking out the newly ear-associated gene (Intu) and a previously ear-associated gene (Tbx15) causes deviating mouse ear morphology.
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Affiliation(s)
- Yi Li
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, China
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, China
| | - Ziyi Xiong
- Department of Genetic Identification, Erasmus MC, University Medical Center, the Netherlands
- Department of Epidemiology, Erasmus MC, University Medical Center, the Netherlands
| | - Manfei Zhang
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, China
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Fudan University, China
| | - Pirro G. Hysi
- Department of Twin Research and Genetic Epidemiology, King’s College London, United Kingdom
| | - Yu Qian
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, China
- Beijing No.8 High School, Beijing, China
| | - Kaustubh Adhikari
- Department of Genetics, Evolution and Environment, and UCL Genetics Institute, University College London, United Kingdom
- School of Mathematics and Statistics, Faculty of Science, Technology, Engineering and Mathematics, The Open University, United Kingdom
| | - Jun Weng
- Center for Biometrics and Security Research & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, China
| | - Sijie Wu
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, China
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Fudan University, China
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, China
| | - Siyuan Du
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, China
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
- University of Chinese Academy of Sciences, China
| | - Rolando Gonzalez-Jose
- Instituto Patagonico de Ciencias Sociales y Humanas, Centro Nacional Patagonico, CONICET, Argentina
| | | | | | - Victor Acuna-Alonzo
- Molecular Genetics Laboratory, National School of Anthropology and History, Mexico
| | - Samuel Canizales-Quinteros
- Unidad de Genomica de Poblaciones Aplicada a la Salud, Facultad de Quimica, UNAM-Instituto Nacional de Medicina Genomica, Mexico
| | - Carla Gallo
- Laboratorios de Investigacion y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Peru
| | - Giovanni Poletti
- Laboratorios de Investigacion y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Peru
| | - Gabriel Bedoya
- GENMOL (Genetica Molecular), Universidad de Antioquia, Medellin, Colombia
| | | | - Jiucun Wang
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Fudan University, China
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, China
| | - Jingze Tan
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, China
| | - Ziyu Yuan
- Fudan-Taizhou Institute of Health Sciences, China
| | - Li Jin
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, China
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Fudan University, China
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, China
- Fudan-Taizhou Institute of Health Sciences, China
| | - André G. Uitterlinden
- Department of Epidemiology, Erasmus MC, University Medical Center, the Netherlands
- Department of Internal Medicine, Erasmus MC, University Medical Center, the Netherlands
| | - Mohsen Ghanbari
- Department of Epidemiology, Erasmus MC, University Medical Center, the Netherlands
| | - M. Arfan Ikram
- Department of Epidemiology, Erasmus MC, University Medical Center, the Netherlands
| | - Tamar Nijsten
- Department of Dermatology, Erasmus MC, University Medical Center, the Netherlands
| | - Xiangyu Zhu
- Center for Biometrics and Security Research & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, China
| | - Zhen Lei
- Center for Biometrics and Security Research & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, China
| | - Peilin Jia
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, China
| | - Andres Ruiz-Linares
- Department of Genetics, Evolution and Environment, and UCL Genetics Institute, University College London, United Kingdom
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, China
- Aix-Marseille Universite, CNRS, EFS, ADES, France
| | - Timothy D. Spector
- Department of Twin Research and Genetic Epidemiology, King’s College London, United Kingdom
| | - Sijia Wang
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, China
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, China
| | - Manfred Kayser
- Department of Genetic Identification, Erasmus MC, University Medical Center, the Netherlands
| | - Fan Liu
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, China
- Department of Genetic Identification, Erasmus MC, University Medical Center, the Netherlands
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6
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Gu L, Xia C, Yang S, Yang G. The adaptive evolution of cancer driver genes. BMC Genomics 2023; 24:215. [PMID: 37098512 PMCID: PMC10131384 DOI: 10.1186/s12864-023-09301-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2022] [Accepted: 04/08/2023] [Indexed: 04/27/2023] Open
Abstract
BACKGROUND Cancer is a life-threatening disease in humans; yet, cancer genes are frequently reported to be under positive selection. This suggests an evolutionary-genetic paradox in which cancer evolves as a secondary product of selection in human beings. However, systematic investigation of the evolution of cancer driver genes is sparse. RESULTS Using comparative genomics analysis, population genetics analysis and computational molecular evolutionary analysis, the evolution of 568 cancer driver genes of 66 cancer types were evaluated at two levels, selection on the early evolution of humans (long timescale selection in the human lineage during primate evolution, i.e., millions of years), and recent selection in modern human populations (~ 100,000 years). Results showed that eight cancer genes covering 11 cancer types were under positive selection in the human lineage (long timescale selection). And 35 cancer genes covering 47 cancer types were under positive selection in modern human populations (recent selection). Moreover, SNPs associated with thyroid cancer in three thyroid cancer driver genes (CUX1, HERC2 and RGPD3) were under positive selection in East Asian and European populations, consistent with the high incidence of thyroid cancer in these populations. CONCLUSIONS These findings suggest that cancer can be evolved, in part, as a by-product of adaptive changes in humans. Different SNPs at the same locus can be under different selection pressures in different populations, and thus should be under consideration during precision medicine, especially for targeted medicine in specific populations.
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Affiliation(s)
- Langyu Gu
- State Key Laboratory for Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, Guangdong, 510275, China.
| | - Canwei Xia
- Ministry of Education Key Laboratory for Biodiversity and Ecological Engineering, College of Life Sciences, Beijing Normal University, Beijing, 100875, China
| | - Shiyu Yang
- The Affiliated Brain Hospital, Guangzhou Medical University, Guangzhou, 510180, Guangdong, China
| | - Guofen Yang
- Department of Gynecology, First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, 510060, Guangdong, China.
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7
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Elkins KM, Garloff AT, Zeller CB. Additional predictions for forensic DNA phenotyping of externally visible characteristics using the ForenSeq and Imagen kits. J Forensic Sci 2023; 68:608-613. [PMID: 36762775 DOI: 10.1111/1556-4029.15215] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Revised: 01/15/2023] [Accepted: 01/24/2023] [Indexed: 02/11/2023]
Abstract
Multiplex DNA typing methods using massively parallel sequencing can be used to predict externally visible characteristics (EVCs) in forensic DNA phenotyping through the analysis of single-nucleotide polymorphisms. The focus of EVC determination has focused on hair color, eye color, and skin tone as well as visible biogeographical ancestry features. In this study, we researched off-label applications beyond what is currently marketed by the manufacturer of the Verogen ForenSeq kit primer set B and Imagen primer set E SNP loci. We investigated additional EVC predictions by examining published genome wide sequencing studies and reported allele-specific gene expression and predictive values. We have identified 15 SNPs included in the ForenSeq kit panel and Imagen kits that have additional EVC prediction capabilities beyond what is published in the Verogen manuals. The additional EVCs that can be predicted include hair graying, ephelides hyperpigmented spots, dermatoheliosis, facial pigmented spots, standing height, pattern balding, helix-rolling ear morphology, hair shape, hair thickness, facial morphology, eyebrow thickness, sarcoidosis, obesity, vitiligo, and tanning propensity. The loci can be used to augment and refine phenotype predictions with software such as MetaHuman for missing persons, cold case, and historic case investigations.
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Affiliation(s)
- Kelly M Elkins
- TU Human Remains Identification Laboratory (THRIL), Chemistry Department, Forensic Science Program, Towson University, Towson, Maryland, USA
| | - Alexis T Garloff
- TU Human Remains Identification Laboratory (THRIL), Chemistry Department, Forensic Science Program, Towson University, Towson, Maryland, USA
| | - Cynthia B Zeller
- TU Human Remains Identification Laboratory (THRIL), Chemistry Department, Forensic Science Program, Towson University, Towson, Maryland, USA
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8
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Kataria S, Dabas P, Saraswathy KN, Sachdeva MP, Jain S. Investigating the morphology and genetics of scalp and facial hair characteristics for phenotype prediction. Sci Justice 2023; 63:135-148. [PMID: 36631178 DOI: 10.1016/j.scijus.2022.12.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Revised: 12/11/2022] [Accepted: 12/12/2022] [Indexed: 12/23/2022]
Abstract
Microscopic traits and ultrastructure of hair such as cross-sectional shape, pigmentation, curvature, and internal structure help determine the level of variations between and across human populations. Apart from cosmetics and anthropological applications, such as determining species, somatic origin (body area), and biogeographic ancestry, the evidential value of hair has increased with rapid progression in the area of forensic DNA phenotyping (FDP). Individuals differ in the features of their scalp hair (greying, shape, colour, balding, thickness, and density) and facial hair (eyebrow thickness, monobrow, and beard thickness) features. Scalp and facial hair characteristics are genetically controlled and lead to visible inter-individual variations within and among populations of various ethnic origins. Hence, these characteristics can be exploited and made more inclusive in FDP, thereby leading to more comprehensive, accurate, and robust prediction models for forensic purposes. The present article focuses on understanding the genetics of scalp and facial hair characteristics with the goal to develop a more inclusive approach to better understand hair biology by integrating hair microscopy with genetics for genotype-phenotype correlation research.
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Affiliation(s)
- Suraj Kataria
- Department of Anthropology, University of Delhi, India.
| | - Prashita Dabas
- Amity Institute of Forensic Sciences, Amity University, Noida, Uttar Pradesh, India.
| | | | - M P Sachdeva
- Department of Anthropology, University of Delhi, India.
| | - Sonal Jain
- Department of Anthropology, University of Delhi, India.
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9
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Cong PK, Bai WY, Li JC, Yang MY, Khederzadeh S, Gai SR, Li N, Liu YH, Yu SH, Zhao WW, Liu JQ, Sun Y, Zhu XW, Zhao PP, Xia JW, Guan PL, Qian Y, Tao JG, Xu L, Tian G, Wang PY, Xie SY, Qiu MC, Liu KQ, Tang BS, Zheng HF. Genomic analyses of 10,376 individuals in the Westlake BioBank for Chinese (WBBC) pilot project. Nat Commun 2022; 13:2939. [PMID: 35618720 PMCID: PMC9135724 DOI: 10.1038/s41467-022-30526-x] [Citation(s) in RCA: 28] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2021] [Accepted: 05/05/2022] [Indexed: 01/04/2023] Open
Abstract
We initiate the Westlake BioBank for Chinese (WBBC) pilot project with 4,535 whole-genome sequencing (WGS) individuals and 5,841 high-density genotyping individuals, and identify 81.5 million SNPs and INDELs, of which 38.5% are absent in dbSNP Build 151. We provide a population-specific reference panel and an online imputation server ( https://wbbc.westlake.edu.cn/ ) which could yield substantial improvement of imputation performance in Chinese population, especially for low-frequency and rare variants. By analyzing the singleton density of the WGS data, we find selection signatures in SNX29, DNAH1 and WDR1 genes, and the derived alleles of the alcohol metabolism genes (ADH1A and ADH1B) emerge around 7,000 years ago and tend to be more common from 4,000 years ago in East Asia. Genetic evidence supports the corresponding geographical boundaries of the Qinling-Huaihe Line and Nanling Mountains, which separate the Han Chinese into subgroups, and we reveal that North Han was more homogeneous than South Han.
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Affiliation(s)
- Pei-Kuan Cong
- Diseases & Population (DaP) Geninfo Lab, School of Life Sciences, Westlake University, Hangzhou, Zhejiang, China
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang, China
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang, China
| | - Wei-Yang Bai
- Diseases & Population (DaP) Geninfo Lab, School of Life Sciences, Westlake University, Hangzhou, Zhejiang, China
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang, China
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang, China
| | - Jin-Chen Li
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China
- National Clinical Research Center for Geriatric Disorders, Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan, China
- Center for Medical Genetics & Hunan Key Laboratory, School of Life Sciences, Central South University, Changsha, Hunan, China
| | - Meng-Yuan Yang
- Diseases & Population (DaP) Geninfo Lab, School of Life Sciences, Westlake University, Hangzhou, Zhejiang, China
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang, China
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang, China
| | - Saber Khederzadeh
- Diseases & Population (DaP) Geninfo Lab, School of Life Sciences, Westlake University, Hangzhou, Zhejiang, China
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang, China
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang, China
| | - Si-Rui Gai
- Diseases & Population (DaP) Geninfo Lab, School of Life Sciences, Westlake University, Hangzhou, Zhejiang, China
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang, China
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang, China
| | - Nan Li
- The High-Performance Computing Center, Westlake University, Hangzhou, Zhejiang, China
| | - Yu-Heng Liu
- The High-Performance Computing Center, Westlake University, Hangzhou, Zhejiang, China
| | - Shi-Hui Yu
- Clinical Genome Center, KingMed Diagnostics, Co., Ltd., Guangzhou, Guangdong, China
| | - Wei-Wei Zhao
- Clinical Genome Center, KingMed Diagnostics, Co., Ltd., Guangzhou, Guangdong, China
| | - Jun-Quan Liu
- Clinical Genome Center, KingMed Diagnostics, Co., Ltd., Guangzhou, Guangdong, China
| | - Yi Sun
- Clinical Genome Center, KingMed Diagnostics, Co., Ltd., Guangzhou, Guangdong, China
| | - Xiao-Wei Zhu
- Diseases & Population (DaP) Geninfo Lab, School of Life Sciences, Westlake University, Hangzhou, Zhejiang, China
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang, China
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang, China
| | - Pian-Pian Zhao
- Diseases & Population (DaP) Geninfo Lab, School of Life Sciences, Westlake University, Hangzhou, Zhejiang, China
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang, China
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang, China
| | - Jiang-Wei Xia
- Diseases & Population (DaP) Geninfo Lab, School of Life Sciences, Westlake University, Hangzhou, Zhejiang, China
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang, China
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang, China
| | - Peng-Lin Guan
- Diseases & Population (DaP) Geninfo Lab, School of Life Sciences, Westlake University, Hangzhou, Zhejiang, China
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang, China
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang, China
| | - Yu Qian
- Diseases & Population (DaP) Geninfo Lab, School of Life Sciences, Westlake University, Hangzhou, Zhejiang, China
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang, China
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang, China
| | - Jian-Guo Tao
- Diseases & Population (DaP) Geninfo Lab, School of Life Sciences, Westlake University, Hangzhou, Zhejiang, China
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang, China
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang, China
| | - Lin Xu
- WBBC Shandong Center, Binzhou Medical University, Yantai, Shandong, China
| | - Geng Tian
- WBBC Shandong Center, Binzhou Medical University, Yantai, Shandong, China
| | - Ping-Yu Wang
- WBBC Shandong Center, Binzhou Medical University, Yantai, Shandong, China
| | - Shu-Yang Xie
- WBBC Shandong Center, Binzhou Medical University, Yantai, Shandong, China
| | - Mo-Chang Qiu
- WBBC Jiangxi Center, Jiangxi Medical College, Shangrao, Jiangxi, China
| | - Ke-Qi Liu
- WBBC Jiangxi Center, Jiangxi Medical College, Shangrao, Jiangxi, China
| | - Bei-Sha Tang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China.
- National Clinical Research Center for Geriatric Disorders, Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan, China.
| | - Hou-Feng Zheng
- Diseases & Population (DaP) Geninfo Lab, School of Life Sciences, Westlake University, Hangzhou, Zhejiang, China.
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang, China.
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang, China.
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10
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Font-Porterias N, McNelis MG, Comas D, Hlusko LJ. Evidence of selection in the ectodysplasin pathway among endangered aquatic mammals. Integr Org Biol 2022; 4:obac018. [PMID: 35874492 PMCID: PMC9299678 DOI: 10.1093/iob/obac018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Revised: 05/06/2022] [Accepted: 05/21/2022] [Indexed: 11/13/2022] Open
Abstract
Synopsis The ectodysplasin pathway has been a target of evolution repeatedly. Genetic variation in the key genes of this pathway (EDA, EDAR, and EDARADD) results in a rich source of pleiotropic effects across ectodermally-derived structures, including teeth, hair, sweat glands, and mammary glands. In addition, a non-canonical Wnt pathway has a very similar functional role, making variation in the WNT10A gene also of evolutionary significance. The adaptation of mammals to aquatic environments has occurred independently in at least 4 orders, whose species occupy a wide geographic range (from equatorial to polar regions) and exhibit great phenotypic variation in ectodermally-derived structures, including the presence or absence of fur and extreme lactational strategies. The role of the ectodysplasin pathway in the adaptation to aquatic environments has been never explored in mammalian species. In the present study, we analyze the genetic variation in orthologous coding sequences from EDA, EDAR, EDARADD, and WNT10A genes together with ectodermally-derived phenotypic variation from 34 aquatic and non-aquatic mammalian species to assess signals of positive selection, gene-trait coevolution, and genetic convergence. Our study reveals strong evidence of positive selection in a proportion of coding sites in EDA and EDAR genes in 3 endangered aquatic mammals (the Hawaiian monk seal, the Yangtze finless porpoise, and the sea otter). We hypothesize functional implications potentially related to the adaptation to the low-latitude aquatic environment in the Hawaiian monk seal and the freshwater in the Yangtze finless porpoise. The signal in the sea otter is likely the result of an increased genetic drift after an intense bottleneck and reduction of genetic diversity. Besides positive selection, we have not detected robust signals of gene-trait coevolution or convergent amino acid shifts in the ectodysplasin pathway associated with shared phenotypic traits among aquatic mammals. This study provides new evidence of the evolutionary role of the ectodysplasin pathway and encourages further investigation, including functional studies, to fully resolve its relationship with mammalian aquatic adaptation. Spanish La vía de la ectodisplasina ha sido objeto de la evolución repetidamente. La variación genética en los principales genes de esta vía (EDA, EDAR y EDARADD) da como resultado una gran diversidad de efectos pleiotrópicos en las estructuras derivadas del ectodermo, incluidos los dientes, el cabello, las glándulas sudoríparas y las glándulas mamarias. Además, una vía wnt no canónica tiene un papel funcional muy similar, por lo que la variación en el gen WNT10A también tiene importancia evolutiva. La adaptación de los mamíferos a los entornes acuáticos se ha producido de forma independiente en al menos cuatro órdenes, cuyas especies ocupan un amplio rango geográfico (desde regiones ecuatoriales a polares) y presentan una gran variación fenotípica en las estructuras derivadas del ectodermo, incluyendo la presencia o ausencia de pelaje y estrategias de lactancia muy diferentes. El papel de la vía de la ectodisplasina en la adaptación a entornos acuáticos no se ha explorado nunca en especies de mamíferos. En este estudio, analizamos la variación genética en las secuencias codificantes ortólogas de los genes EDA, EDAR, EDARADD y WNT10A junto con la variación fenotípica derivada del ectodermo de 34 especies de mamíferos acuáticos y no acuáticos para evaluar señales de selección positiva, coevolución gen-rasgo y convergencia genética. Nuestro estudio revela señales de selección positiva en regiones de las secuencias codificantes de los genes EDA y EDAR en tres mamíferos acuáticos en peligro de extinción (la foca monje de Hawái, la marsopa lisa y la nutria marina). Estas señales podrían tener implicaciones funcionales potencialmente relacionadas con la adaptación al entorno acuático de baja latitud en la foca monje de Hawái y el agua dulce en la marsopa lisa. La señal en la nutria marina es probablemente el resultado de una mayor deriva genética tras un intenso un cuello de botella y una reducción de la diversidad genética. A parte de selección positiva, no hemos detectado señales sólidas de coevolución gen-rasgo o cambios convergentes de aminoácidos en la vía de la ectodisplasina asociados a rasgos fenotípicos compartidos entre mamíferos acuáticos. Este estudio proporciona nuevas evidencias del papel evolutivo de la vía de la ectodisplasina y quiere promover futuras investigaciones con estudios funcionales para acabar de resolver la relación de esta vía con la adaptación acuática de los mamíferos.
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Affiliation(s)
- Neus Font-Porterias
- Departament de Ciències Experimentals i de la Salut, Universitat Pompeu Fabra, Institut de Biologia Evolutiva (UPF-CSIC) , Barcelona , Spain
| | - Madeline G McNelis
- Department of Integrative Biology, University of California Berkeley , California , USA
| | - David Comas
- Departament de Ciències Experimentals i de la Salut, Universitat Pompeu Fabra, Institut de Biologia Evolutiva (UPF-CSIC) , Barcelona , Spain
| | - Leslea J Hlusko
- Department of Integrative Biology, University of California Berkeley , California , USA
- National Research Center on Human Evolution (CENIEH) , Burgos , Spain
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11
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The genomic origins of the world's first farmers. Cell 2022; 185:1842-1859.e18. [PMID: 35561686 PMCID: PMC9166250 DOI: 10.1016/j.cell.2022.04.008] [Citation(s) in RCA: 31] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Revised: 03/04/2022] [Accepted: 04/06/2022] [Indexed: 11/24/2022]
Abstract
The precise genetic origins of the first Neolithic farming populations in Europe and Southwest Asia, as well as the processes and the timing of their differentiation, remain largely unknown. Demogenomic modeling of high-quality ancient genomes reveals that the early farmers of Anatolia and Europe emerged from a multiphase mixing of a Southwest Asian population with a strongly bottlenecked western hunter-gatherer population after the last glacial maximum. Moreover, the ancestors of the first farmers of Europe and Anatolia went through a period of extreme genetic drift during their westward range expansion, contributing highly to their genetic distinctiveness. This modeling elucidates the demographic processes at the root of the Neolithic transition and leads to a spatial interpretation of the population history of Southwest Asia and Europe during the late Pleistocene and early Holocene.
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12
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Pośpiech E, Karłowska-Pik J, Kukla-Bartoszek M, Woźniak A, Boroń M, Zubańska M, Jarosz A, Bronikowska A, Grzybowski T, Płoski R, Spólnicka M, Branicki W. Overlapping association signals in the genetics of hair-related phenotypes in humans and their relevance to predictive DNA analysis. Forensic Sci Int Genet 2022; 59:102693. [DOI: 10.1016/j.fsigen.2022.102693] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Revised: 02/25/2022] [Accepted: 03/22/2022] [Indexed: 01/02/2023]
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13
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Pośpiech E, Teisseyre P, Mielniczuk J, Branicki W. Predicting Physical Appearance from DNA Data-Towards Genomic Solutions. Genes (Basel) 2022; 13:genes13010121. [PMID: 35052461 PMCID: PMC8774670 DOI: 10.3390/genes13010121] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Revised: 01/03/2022] [Accepted: 01/04/2022] [Indexed: 02/04/2023] Open
Abstract
The idea of forensic DNA intelligence is to extract from genomic data any information that can help guide the investigation. The clues to the externally visible phenotype are of particular practical importance. The high heritability of the physical phenotype suggests that genetic data can be easily predicted, but this has only become possible with less polygenic traits. The forensic community has developed DNA-based predictive tools by employing a limited number of the most important markers analysed with targeted massive parallel sequencing. The complexity of the genetics of many other appearance phenotypes requires big data coupled with sophisticated machine learning methods to develop accurate genomic predictors. A significant challenge in developing universal genomic predictive methods will be the collection of sufficiently large data sets. These should be created using whole-genome sequencing technology to enable the identification of rare DNA variants implicated in phenotype determination. It is worth noting that the correctness of the forensic sketch generated from the DNA data depends on the inclusion of an age factor. This, however, can be predicted by analysing epigenetic data. An important limitation preventing whole-genome approaches from being commonly used in forensics is the slow progress in the development and implementation of high-throughput, low DNA input sequencing technologies. The example of palaeoanthropology suggests that such methods may possibly be developed in forensics.
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Affiliation(s)
- Ewelina Pośpiech
- Malopolska Centre of Biotechnology, Jagiellonian University, 30-387 Kraków, Poland;
| | - Paweł Teisseyre
- Institute of Computer Science, Polish Academy of Sciences, 01-248 Warsaw, Poland; (P.T.); (J.M.)
- Faculty of Mathematics and Information Science, Warsaw University of Technology, 00-662 Warsaw, Poland
| | - Jan Mielniczuk
- Institute of Computer Science, Polish Academy of Sciences, 01-248 Warsaw, Poland; (P.T.); (J.M.)
- Faculty of Mathematics and Information Science, Warsaw University of Technology, 00-662 Warsaw, Poland
| | - Wojciech Branicki
- Malopolska Centre of Biotechnology, Jagiellonian University, 30-387 Kraków, Poland;
- Central Forensic Laboratory of the Police, 00-583 Warsaw, Poland
- Correspondence: ; Tel.: +48-126-645-024
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14
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Colomer-Vilaplana A, Murga-Moreno J, Canalda-Baltrons A, Inserte C, Soto D, Coronado-Zamora M, Barbadilla A, Casillas S. PopHumanVar: an interactive application for the functional characterization and prioritization of adaptive genomic variants in humans. Nucleic Acids Res 2022; 50:D1069-D1076. [PMID: 34664660 PMCID: PMC8728255 DOI: 10.1093/nar/gkab925] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2021] [Revised: 09/17/2021] [Accepted: 09/28/2021] [Indexed: 12/22/2022] Open
Abstract
Adaptive challenges that humans faced as they expanded across the globe left specific molecular footprints that can be decoded in our today's genomes. Different sets of metrics are used to identify genomic regions that have undergone selection. However, there are fewer methods capable of pinpointing the allele ultimately responsible for this selection. Here, we present PopHumanVar, an interactive online application that is designed to facilitate the exploration and thorough analysis of candidate genomic regions by integrating both functional and population genomics data currently available. PopHumanVar generates useful summary reports of prioritized variants that are putatively causal of recent selective sweeps. It compiles data and graphically represents different layers of information, including natural selection statistics, as well as functional annotations and genealogical estimations of variant age, for biallelic single nucleotide variants (SNVs) of the 1000 Genomes Project phase 3. Specifically, PopHumanVar amasses SNV-based information from GEVA, SnpEFF, GWAS Catalog, ClinVar, RegulomeDB and DisGeNET databases, as well as accurate estimations of iHS, nSL and iSAFE statistics. Notably, PopHumanVar can successfully identify known causal variants of frequently reported candidate selection regions, including EDAR in East-Asians, ACKR1 (DARC) in Africans and LCT/MCM6 in Europeans. PopHumanVar is open and freely available at https://pophumanvar.uab.cat.
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Affiliation(s)
- Aina Colomer-Vilaplana
- Department of Genetics and Microbiology, Universitat Autònoma de Barcelona, Bellaterra, Barcelona 08193, Spain
| | - Jesús Murga-Moreno
- Department of Genetics and Microbiology, Universitat Autònoma de Barcelona, Bellaterra, Barcelona 08193, Spain
- Institute of Biotechnology and Biomedicine, Universitat Autònoma de Barcelona, Bellaterra, Barcelona 08193, Spain
| | - Aleix Canalda-Baltrons
- Department of Genetics and Microbiology, Universitat Autònoma de Barcelona, Bellaterra, Barcelona 08193, Spain
| | - Clara Inserte
- Institute of Biotechnology and Biomedicine, Universitat Autònoma de Barcelona, Bellaterra, Barcelona 08193, Spain
| | - Daniel Soto
- Department of Genetics and Microbiology, Universitat Autònoma de Barcelona, Bellaterra, Barcelona 08193, Spain
| | - Marta Coronado-Zamora
- Department of Genetics and Microbiology, Universitat Autònoma de Barcelona, Bellaterra, Barcelona 08193, Spain
- Institute of Biotechnology and Biomedicine, Universitat Autònoma de Barcelona, Bellaterra, Barcelona 08193, Spain
| | - Antonio Barbadilla
- Department of Genetics and Microbiology, Universitat Autònoma de Barcelona, Bellaterra, Barcelona 08193, Spain
- Institute of Biotechnology and Biomedicine, Universitat Autònoma de Barcelona, Bellaterra, Barcelona 08193, Spain
| | - Sònia Casillas
- Department of Genetics and Microbiology, Universitat Autònoma de Barcelona, Bellaterra, Barcelona 08193, Spain
- Institute of Biotechnology and Biomedicine, Universitat Autònoma de Barcelona, Bellaterra, Barcelona 08193, Spain
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15
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Qiu J, Zhou Q, Ye W, Chen Q, Bao YJ. SweepCluster: A SNP clustering tool for detecting gene-specific sweeps in prokaryotes. BMC Bioinformatics 2022; 23:19. [PMID: 34991447 PMCID: PMC8734265 DOI: 10.1186/s12859-021-04533-6] [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: 02/24/2021] [Accepted: 12/13/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND The gene-specific sweep is a selection process where an advantageous mutation along with the nearby neutral sites in a gene region increases the frequency in the population. It has been demonstrated to play important roles in ecological differentiation or phenotypic divergence in microbial populations. Therefore, identifying gene-specific sweeps in microorganisms will not only provide insights into the evolutionary mechanisms, but also unravel potential genetic markers associated with biological phenotypes. However, current methods were mainly developed for detecting selective sweeps in eukaryotic data of sparse genotypes and are not readily applicable to prokaryotic data. Furthermore, some challenges have not been sufficiently addressed by the methods, such as the low spatial resolution of sweep regions and lack of consideration of the spatial distribution of mutations. RESULTS We proposed a novel gene-centric and spatial-aware approach for identifying gene-specific sweeps in prokaryotes and implemented it in a python tool SweepCluster. Our method searches for gene regions with a high level of spatial clustering of pre-selected polymorphisms in genotype datasets assuming a null distribution model of neutral selection. The pre-selection of polymorphisms is based on their genetic signatures, such as elevated population subdivision, excessive linkage disequilibrium, or significant phenotype association. Performance evaluation using simulation data showed that the sensitivity and specificity of the clustering algorithm in SweepCluster is above 90%. The application of SweepCluster in two real datasets from the bacteria Streptococcus pyogenes and Streptococcus suis showed that the impact of pre-selection was dramatic and significantly reduced the uninformative signals. We validated our method using the genotype data from Vibrio cyclitrophicus, the only available dataset of gene-specific sweeps in bacteria, and obtained a concordance rate of 78%. We noted that the concordance rate could be underestimated due to distinct reference genomes and clustering strategies. The application to the human genotype datasets showed that SweepCluster is also applicable to eukaryotic data and is able to recover 80% of a catalog of known sweep regions. CONCLUSION SweepCluster is applicable to a broad category of datasets. It will be valuable for detecting gene-specific sweeps in diverse genotypic data and provide novel insights on adaptive evolution.
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Affiliation(s)
- Junhui Qiu
- State Key Laboratory of Biocatalysis and Enzyme Engineering, Hubei Collaborative Innovation Center for Green Transformation of Bio-Resources, Hubei Key Laboratory of Industrial Biotechnology, School of Life Sciences, Hubei University, Wuhan, 430062, China
| | - Qi Zhou
- State Key Laboratory of Biocatalysis and Enzyme Engineering, Hubei Collaborative Innovation Center for Green Transformation of Bio-Resources, Hubei Key Laboratory of Industrial Biotechnology, School of Life Sciences, Hubei University, Wuhan, 430062, China
| | - Weicai Ye
- School of Computer Science and Engineering, Guangdong Province Key Laboratory of Computational Science, and National Engineering Laboratory for Big Data Analysis and Application, Sun Yat-Sen University, Guangzhou, 510275, China
| | - Qianjun Chen
- State Key Laboratory of Biocatalysis and Enzyme Engineering, Hubei Collaborative Innovation Center for Green Transformation of Bio-Resources, Hubei Key Laboratory of Industrial Biotechnology, School of Life Sciences, Hubei University, Wuhan, 430062, China.
| | - Yun-Juan Bao
- State Key Laboratory of Biocatalysis and Enzyme Engineering, Hubei Collaborative Innovation Center for Green Transformation of Bio-Resources, Hubei Key Laboratory of Industrial Biotechnology, School of Life Sciences, Hubei University, Wuhan, 430062, China.
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16
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Abdel Hay R, Sayed KS, Hegazi SA, Nada A, Amer MA. Trichoscopic features of hair and scalp in noncomplaining individuals: A descriptive study. J Cosmet Dermatol 2021; 21:3934-3942. [PMID: 34932866 DOI: 10.1111/jocd.14694] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Revised: 11/09/2021] [Accepted: 12/08/2021] [Indexed: 10/19/2022]
Abstract
BACKGROUND Trichoscopy is a simple noninvasive tool that is used in calculating different hair parameters and the diagnosis of different hair/scalp diseases at variable magnifications. OBJECTIVE The aim of this work is to describe the features and parameters of hair and scalp in a healthy sample of Egyptian population using videodermoscopy. This may help to provide standard range of measurements of normal hair in both males and females. METHODS A nonrandomized, observational study for features and parameters of hair structure, performed on 368 healthy Egyptian subjects with no hair/scalp complaint. RESULTS Each scalp area has its own vascular pattern. Male subjects showed different values regarding their hair parameters from the female subjects. No significant difference was seen after application of hair dye, except for few values. In both genders, there was a change in hair parameters with age. Smoking had a negative influence on hair parameters. CONCLUSION Hair features and parameters observed in our population are different from those reported by other populations. Smoking affects hair thickness and density. Dyed hair has greater thickness mostly due to the protective effect of hair conditioners.
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Affiliation(s)
- Rania Abdel Hay
- Dermatology Department, Faculty of Medicine, Cairo University, Cairo, Egypt
| | - Khadiga S Sayed
- Dermatology Department, Faculty of Medicine, Cairo University, Cairo, Egypt
| | - Soha Ahmad Hegazi
- Dermatology Department, Faculty of Medicine, Cairo University, Cairo, Egypt
| | - Ahmed Nada
- Dermatology Department, Faculty of Medicine, Cairo University, Cairo, Egypt
| | - Marwa Ahmed Amer
- Dermatology Department, Faculty of Medicine, Cairo University, Cairo, Egypt
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17
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Wahyudi F, Aghakhanian F, Rahman S, Teo YY, Szpak M, Dhaliwal J, Ayub Q. Prioritising positively selected variants in whole-genome sequencing data using FineMAV. BMC Bioinformatics 2021; 22:604. [PMID: 34922440 PMCID: PMC8684245 DOI: 10.1186/s12859-021-04506-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2021] [Accepted: 11/30/2021] [Indexed: 11/17/2022] Open
Abstract
Background In population genomics, polymorphisms that are highly differentiated between geographically separated populations are often suggestive of Darwinian positive selection. Genomic scans have highlighted several such regions in African and non-African populations, but only a handful of these have functional data that clearly associates candidate variations driving the selection process. Fine-Mapping of Adaptive Variation (FineMAV) was developed to address this in a high-throughput manner using population based whole-genome sequences generated by the 1000 Genomes Project. It pinpoints positively selected genetic variants in sequencing data by prioritizing high frequency, population-specific and functional derived alleles. Results We developed a stand-alone software that implements the FineMAV statistic. To graphically visualise the FineMAV scores, it outputs the statistics as bigWig files, which is a common file format supported by many genome browsers. It is available as a command-line and graphical user interface. The software was tested by replicating the FineMAV scores obtained using 1000 Genomes Project African, European, East and South Asian populations and subsequently applied to whole-genome sequencing datasets from Singapore and China to highlight population specific variants that can be subsequently modelled. The software tool is publicly available at https://github.com/fadilla-wahyudi/finemav. Conclusions The software tool described here determines genome-wide FineMAV scores, using low or high-coverage whole-genome sequencing datasets, that can be used to prioritize a list of population specific, highly differentiated candidate variants for in vitro or in vivo functional screens. The tool displays these scores on the human genome browsers for easy visualisation, annotation and comparison between different genomic regions in worldwide human populations. Supplementary Information The online version contains supplementary material available at 10.1186/s12859-021-04506-9.
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Affiliation(s)
- Fadilla Wahyudi
- School of Science, Monash University Malaysia, 47500, Bandar Sunway, Selangor Darul Ehsan, Malaysia
| | - Farhang Aghakhanian
- Monash University Malaysia Genomics Facility, 47500, Bandar Sunway, Selangor Darul Ehsan, Malaysia.,Genes and Human Disease Research Program, Oklahoma Medical Research Foundation,, Oklahoma City, OK, 73104, USA
| | - Sadequr Rahman
- School of Science, Monash University Malaysia, 47500, Bandar Sunway, Selangor Darul Ehsan, Malaysia.,Tropical Medicine and Biology Multidisciplinary Platform, Monash University Malaysia, 47500, Bandar Sunway, Selangor Darul Ehsan, Malaysia
| | - Yik-Ying Teo
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | - Michał Szpak
- European Bioinformatics Institute, Hinxton, CB10 1SA, UK.,Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, CB10 1SA, UK
| | - Jasbir Dhaliwal
- School of Information Technology, Monash University Malaysia, 47500, Bandar Sunway, Selangor Darul Ehsan, Malaysia.
| | - Qasim Ayub
- School of Science, Monash University Malaysia, 47500, Bandar Sunway, Selangor Darul Ehsan, Malaysia. .,Monash University Malaysia Genomics Facility, 47500, Bandar Sunway, Selangor Darul Ehsan, Malaysia. .,Tropical Medicine and Biology Multidisciplinary Platform, Monash University Malaysia, 47500, Bandar Sunway, Selangor Darul Ehsan, Malaysia.
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18
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Nishikawa Y, Ishida T. Genetic lineage of the Amami islanders inferred from classical genetic markers. Meta Gene 2021. [DOI: 10.1016/j.mgene.2021.100956] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022] Open
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19
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Weisz NA, Roberts KA, Hardy WR. Reliability of phenotype estimation and extended classification of ancestry using decedent samples. Int J Legal Med 2021; 135:2221-2233. [PMID: 34436656 DOI: 10.1007/s00414-021-02631-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2020] [Accepted: 06/04/2021] [Indexed: 11/30/2022]
Abstract
The Illumina® MiSeq FGx™, in conjunction with the ForenSeq™ DNA Signature Prep kit, produces genotypes of the CODIS-required short tandem repeats and provides phenotype and biogeographical ancestry estimations via phenotype-informative and ancestry-informative markers, respectively. Although both markers have been validated for use in forensic biology, there is little data to determine the practical utility of these estimations to assist in identifying missing persons using decedent casework samples. The accuracy and utility of phenotypic and ancestral estimations were investigated for 300 samples received by the Los Angeles County Department of Medical Examiner-Coroner. piSNP genotypes were translated into hair and eye colors using the Forenseq™ Universal Analysis Software (UAS) on the MiSeq FGx™ and the HIrisPlex System, and statistical accuracy was evaluated in context with the reported decedent characteristics. Similarly, estimates of each decedent's biogeographical ancestry were compared to assess the efficacy of these markers to predict ancestry correctly. The average UAS and the HIrisPlex system prediction accuracy for brown and blue eyes were 95.3% and 96.2%, respectively. Intermediate eye color could not be predicted with high accuracy using either system. Other than the black hair phenotype reporting an accuracy that exceeded 90% using either system, hair color was also too variable to be predicted with high accuracy. The FROG-kb database distinguishes decedents adequately beyond the Asian, African, European, and Admixed American global ancestries provided by the MiSeq FGx™ UAS PCA plots. FROG-kb correctly identified Middle Eastern, Pacific Islander, Latin American, or Jewish ancestries with accuracies of 70.0%, 81.8%, 73.8%, and 86.7%, respectively.
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Affiliation(s)
- Naomi A Weisz
- School of Criminal Justice and Criminalistics, California State University, Los Angeles, 1800 Paseo Rancho Castilla, Los Angeles, CA, 90032, USA
| | - Katherine A Roberts
- School of Criminal Justice and Criminalistics, California State University, Los Angeles, 1800 Paseo Rancho Castilla, Los Angeles, CA, 90032, USA. .,California Forensic Science Institute, California State University, Los Angeles, 5151 State University Drive, Los Angeles, CA, 90032, USA.
| | - W Reef Hardy
- Human Genomics Unit, Los Angeles County Department of Medical Examiner-Coroner, 1104 N Mission Road, Los Angeles, CA, 90033, USA
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20
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Lasisi T, Zaidi AA, Webster TH, Stephens NB, Routch K, Jablonski NG, Shriver MD. High-throughput phenotyping methods for quantifying hair fiber morphology. Sci Rep 2021; 11:11535. [PMID: 34075066 PMCID: PMC8169905 DOI: 10.1038/s41598-021-90409-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Accepted: 05/10/2021] [Indexed: 11/18/2022] Open
Abstract
Quantifying the continuous variation in human scalp hair morphology is of interest to anthropologists, geneticists, dermatologists and forensic scientists, but existing methods for studying hair form are time-consuming and not widely used. Here, we present a high-throughput sample preparation protocol for the imaging of both longitudinal (curvature) and cross-sectional scalp hair morphology. Additionally, we describe and validate a new Python package designed to process longitudinal and cross-sectional hair images, segment them, and provide measurements of interest. Lastly, we apply our methods to an admixed African-European sample (n = 140), demonstrating the benefit of quantifying hair morphology over classification, and providing evidence that the relationship between cross-sectional morphology and curvature may be an artefact of population stratification rather than a causal link.
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Affiliation(s)
- Tina Lasisi
- Department of Anthropology, Pennsylvania State University, Philadelphia, USA.
| | - Arslan A Zaidi
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| | | | - Nicholas B Stephens
- Department of Anthropology, Pennsylvania State University, Philadelphia, USA
| | - Kendall Routch
- Department of Anthropology, Pennsylvania State University, Philadelphia, USA
| | - Nina G Jablonski
- Department of Anthropology, Pennsylvania State University, Philadelphia, USA
| | - Mark D Shriver
- Department of Anthropology, Pennsylvania State University, Philadelphia, USA
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21
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Bourrat P. Measuring Causal Invariance Formally. ENTROPY 2021; 23:e23060690. [PMID: 34070711 PMCID: PMC8228138 DOI: 10.3390/e23060690] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/14/2021] [Revised: 05/25/2021] [Accepted: 05/25/2021] [Indexed: 11/16/2022]
Abstract
Invariance is one of several dimensions of causal relationships within the interventionist account. The more invariant a relationship between two variables, the more the relationship should be considered paradigmatically causal. In this paper, I propose two formal measures to estimate invariance, illustrated by a simple example. I then discuss the notion of invariance for causal relationships between non-nominal (i.e., ordinal and quantitative) variables, for which Information theory, and hence the formalism proposed here, is not well suited. Finally, I propose how invariance could be qualified for such variables.
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Affiliation(s)
- Pierrick Bourrat
- Department of Philosophy, Macquarie University, Balaclava Road, North Ryde, NSW 2109, Australia;
- Department of Philosophy & Charles Perkins Centre, The University of Sydney, Camperdown, NSW 2006, Australia
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22
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Yasumizu Y, Sakaue S, Konuma T, Suzuki K, Matsuda K, Murakami Y, Kubo M, Palamara PF, Kamatani Y, Okada Y. Genome-Wide Natural Selection Signatures Are Linked to Genetic Risk of Modern Phenotypes in the Japanese Population. Mol Biol Evol 2021; 37:1306-1316. [PMID: 31957793 PMCID: PMC7182208 DOI: 10.1093/molbev/msaa005] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
Elucidation of natural selection signatures and relationships with phenotype spectra is important to understand adaptive evolution of modern humans. Here, we conducted a genome-wide scan of selection signatures of the Japanese population by estimating locus-specific time to the most recent common ancestor using the ascertained sequentially Markovian coalescent (ASMC), from the biobank-based large-scale genome-wide association study data of 170,882 subjects. We identified 29 genetic loci with selection signatures satisfying the genome-wide significance. The signatures were most evident at the alcohol dehydrogenase (ADH) gene cluster locus at 4q23 (PASMC = 2.2 × 10−36), followed by relatively strong selection at the FAM96A (15q22), MYOF (10q23), 13q21, GRIA2 (4q32), and ASAP2 (2p25) loci (PASMC < 1.0 × 10−10). The additional analysis interrogating extended haplotypes (integrated haplotype score) showed robust concordance of the detected signatures, contributing to fine-mapping of the genes, and provided allelic directional insights into selection pressure (e.g., positive selection for ADH1B-Arg48His and HLA-DPB1*04:01). The phenome-wide selection enrichment analysis with the trait-associated variants identified a variety of the modern human phenotypes involved in the adaptation of Japanese. We observed population-specific evidence of enrichment with the alcohol-related phenotypes, anthropometric and biochemical clinical measurements, and immune-related diseases, differently from the findings in Europeans using the UK Biobank resource. Our study demonstrated population-specific features of the selection signatures in Japanese, highlighting a value of the natural selection study using the nation-wide biobank-scale genome and phenotype data.
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Affiliation(s)
| | - Saori Sakaue
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan.,Department of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.,Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Takahiro Konuma
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
| | - Ken Suzuki
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
| | - Koichi Matsuda
- Department of Computational Biology and Medical Science, Graduate school of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Yoshinori Murakami
- Division of Molecular Pathology, The Institute of Medical Sciences, The University of Tokyo, Tokyo, Japan
| | - Michiaki Kubo
- RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | | | - Yoichiro Kamatani
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan.,Laboratory of Complex Trait Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Yukinori Okada
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan.,Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Suita, Japan.,Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives, Osaka University, Suita, Japan
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23
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Lasisi T. The constraints of racialization: How classification and valuation hinder scientific research on human variation. AMERICAN JOURNAL OF PHYSICAL ANTHROPOLOGY 2021; 175:376-386. [PMID: 33675042 DOI: 10.1002/ajpa.24264] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/28/2020] [Revised: 02/15/2021] [Accepted: 02/17/2021] [Indexed: 12/18/2022]
Abstract
Human biological variation has historically been studied through the lens of racialization. Despite a general shift away from the use of overt racial terminologies, the underlying racialized frameworks used to describe and understand human variation still remain. Even in relatively recent anthropological and biomedical work, we can observe clear manifestations of such racial thinking. This paper shows how classification and valuation are two specific processes which facilitate racialization and hinder attempts to move beyond such frameworks. The bias induced by classification distorts descriptions of phenotypic variation in a way that erroneously portrays European populations as more variable than others. Implicit valuation occurs in tandem with classification and produces narratives of superiority/inferiority for certain phenotypic variants without an objective biological basis. The bias of racialization is a persistent impediment stemming from the inheritance of scientific knowledge developed under explicitly racial paradigms. It is also an internalized cognitive distortion cultivated through socialization in a world where racialization is inescapable. Though undeniably challenging, this does not present an insurmountable barrier, and this bias can be mitigated through the critical evaluation of past work, the active inclusion of marginalized perspectives, and the direct confrontation of institutional structures enforcing racialized paradigms.
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Affiliation(s)
- Tina Lasisi
- Department of Anthropology, Pennsylvania State University, State College, Pennsylvania, USA
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24
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Kataoka K, Fujita H, Isa M, Gotoh S, Arasaki A, Ishida H, Kimura R. The human EDAR 370V/A polymorphism affects tooth root morphology potentially through the modification of a reaction-diffusion system. Sci Rep 2021; 11:5143. [PMID: 33664401 PMCID: PMC7933414 DOI: 10.1038/s41598-021-84653-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2020] [Accepted: 02/15/2021] [Indexed: 01/31/2023] Open
Abstract
Morphological variations in human teeth have long been recognized and, in particular, the spatial and temporal distribution of two patterns of dental features in Asia, i.e., Sinodonty and Sundadonty, have contributed to our understanding of the human migration history. However, the molecular mechanisms underlying such dental variations have not yet been completely elucidated. Recent studies have clarified that a nonsynonymous variant in the ectodysplasin A receptor gene (EDAR 370V/A; rs3827760) contributes to crown traits related to Sinodonty. In this study, we examined the association between the EDAR polymorphism and tooth root traits by using computed tomography images and identified that the effects of the EDAR variant on the number and shape of roots differed depending on the tooth type. In addition, to better understand tooth root morphogenesis, a computational analysis for patterns of tooth roots was performed, assuming a reaction-diffusion system. The computational study suggested that the complicated effects of the EDAR polymorphism could be explained when it is considered that EDAR modifies the syntheses of multiple related molecules working in the reaction-diffusion dynamics. In this study, we shed light on the molecular mechanisms of tooth root morphogenesis, which are less understood in comparison to those of tooth crown morphogenesis.
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Affiliation(s)
- Keiichi Kataoka
- Department of Human Biology and Anatomy, Graduate School of Medicine, University of the Ryukyus, Okinawa, 903-0215, Japan
- Department of Oral and Maxillofacial Functional Rehabilitation, Graduate School of Medicine, University of the Ryukyus, Okinawa, Japan
| | - Hironori Fujita
- Astrobiology Center, National Institutes of Natural Sciences, Tokyo, Japan
- National Institute for Basic Biology, National Institutes of Natural Sciences, Aichi, Japan
- Department of Basic Biology, School of Life Science, SOKENDAI (The Graduate School for Advanced Studies), Aichi, Japan
| | - Mutsumi Isa
- Department of Human Biology and Anatomy, Graduate School of Medicine, University of the Ryukyus, Okinawa, 903-0215, Japan
| | - Shimpei Gotoh
- Department of Human Biology and Anatomy, Graduate School of Medicine, University of the Ryukyus, Okinawa, 903-0215, Japan
- Department of Oral and Maxillofacial Functional Rehabilitation, Graduate School of Medicine, University of the Ryukyus, Okinawa, Japan
| | - Akira Arasaki
- Department of Oral and Maxillofacial Functional Rehabilitation, Graduate School of Medicine, University of the Ryukyus, Okinawa, Japan
| | - Hajime Ishida
- Department of Human Biology and Anatomy, Graduate School of Medicine, University of the Ryukyus, Okinawa, 903-0215, Japan
| | - Ryosuke Kimura
- Department of Human Biology and Anatomy, Graduate School of Medicine, University of the Ryukyus, Okinawa, 903-0215, Japan.
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25
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Wu Z, Wang Y, Han W, Yang K, Hai E, Ma R, Di Z, Shang F, Su R, Wang R, Wang Z, Zhang Y, Li J. EDA and EDAR expression at different stages of hair follicle development in cashmere goats and effects on expression of related genes. Arch Anim Breed 2020; 63:461-470. [PMID: 33473371 PMCID: PMC7810227 DOI: 10.5194/aab-63-461-2020] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2020] [Accepted: 10/16/2020] [Indexed: 11/25/2022] Open
Abstract
This study is focused on the detection of ectodysplasin A (EDA) and ectodysplasin A receptor
(EDAR) mRNA expression levels and protein positions in seven stages of
cashmere goat fetus development (45, 55, 65, 75 95, 115, and 135 d), with the main goal of
investigating the effect of EDA and EDAR on genes related to hair follicle
development.
Quantitative real-time polymerase chain reaction (RT-qPCR) was used to
measure EDA and EDAR expression levels in seven stages of cashmere goat
fetus development. Immunohistochemistry (IHC) was used to locate EDA and EDAR
in the critical stage of fetal hair follicle development (45–135 d). EDA and EDAR expression in fetal fibroblasts and epithelial cells was
interfered with by short hairpin RNA (sh-RNA). The results indicated that
EDA and EDAR were both expressed in the skin tissue in the seven cashmere
goat embryo stages. Moreover, EDA and EDAR play an important role in the
formation of embryonic placode (Pc). After interfering with EDA and EDAR,
the expression of BMP2, BMP4, noggin, β-catenin, TGF-β2,
Wnt-10b, and NOTCH1 in fibroblasts and epithelial cells changed
significantly.
This study provides a theoretical and
experimental basis for further studying the molecular regulation mechanism
of hair follicle development.
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Affiliation(s)
- Zhihong Wu
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, Inner Mongolia Autonomous Region 010018, China
| | - Yu Wang
- College of Veterinary Medicine, Inner Mongolia Agricultural University, Hohhot, Inner Mongolia Autonomous Region 010018, China
| | - Wenjing Han
- College of Chemistry and Life Science, Chifeng University, Chifeng, Inner Mongolia Autonomous Region 024000, China
| | - Kun Yang
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, Inner Mongolia Autonomous Region 010018, China
| | - Erhan Hai
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, Inner Mongolia Autonomous Region 010018, China
| | - Rong Ma
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, Inner Mongolia Autonomous Region 010018, China
| | - Zhengyang Di
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, Inner Mongolia Autonomous Region 010018, China
| | - Fangzheng Shang
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, Inner Mongolia Autonomous Region 010018, China
| | - Rui Su
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, Inner Mongolia Autonomous Region 010018, China
| | - Ruijun Wang
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, Inner Mongolia Autonomous Region 010018, China
| | - Zhiying Wang
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, Inner Mongolia Autonomous Region 010018, China
| | - Yanjun Zhang
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, Inner Mongolia Autonomous Region 010018, China
| | - Jinquan Li
- Key Laboratory of Animal Genetics, Breeding and Reproduction in Inner Mongolia Autonomous Region, Hohhot, Inner Mongolia Autonomous Region 010018, China.,Engineering Research Center for Goat Genetics and Breeding, Inner Mongolia Autonomous Region, Hohhot, Inner Mongolia Autonomous Region 010018, China.,Key Laboratory of Mutton Sheep Genetics and Breeding, Ministry of Agriculture, Hohhot, Inner Mongolia Autonomous Region 010018, China
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26
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Comparison of Genome-Wide Association Scans for Quantitative and Observational Measures of Human Hair Curvature. Twin Res Hum Genet 2020; 23:271-277. [PMID: 33190678 DOI: 10.1017/thg.2020.78] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
Previous genetic studies on hair morphology focused on the overall morphology of the hair using data collected by self-report or researcher observation. Here, we present the first genome-wide association study (GWAS) of a micro-level quantitative measure of hair curvature. We compare these results to GWAS results obtained using a macro-level classification of observable hair curvature performed in the same sample of twins and siblings of European descent. Observational data were collected by trained observers, while quantitative data were acquired using an Optical Fibre Diameter Analyser (OFDA). The GWAS for both the observational and quantitative measures of hair curvature resulted in genome-wide significant signals at chromosome 1q21.3 close to the trichohyalin (TCHH) gene, previously shown to harbor variants associated with straight hair morphology in Europeans. All genetic variants reaching genome-wide significance for both GWAS (quantitative measure lead single-nucleotide polymorphism [SNP] rs12130862, p = 9.5 × 10-09; observational measure lead SNP rs11803731, p = 2.1 × 10-17) were in moderate to very high linkage disequilibrium (LD) with each other (minimum r2 = .45), indicating they represent the same genetic locus. Conditional analyses confirmed the presence of only one signal associated with each measure at this locus. Results from the quantitative measures reconfirmed the accuracy of observational measures.
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Koch SL, Liebowitz C, Shriver MD, Jablonski NG. Microscopical discrimination of human head hairs sharing a mitochondrial haplogroup. J Forensic Sci 2020; 66:56-71. [PMID: 32956521 DOI: 10.1111/1556-4029.14560] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2020] [Revised: 07/14/2020] [Accepted: 08/10/2020] [Indexed: 11/30/2022]
Abstract
In forensic analyses, determining the level of consensus among examiners for hair comparison conclusions and ancestry identifications is important for assessing the scientific validity of microscopical hair examinations. Here, we present data from an interlaboratory study on the accuracy of microscopical hair comparisons among a subset of experienced hair examiners currently analyzing hair in forensic laboratories across the United States. We examined how well microscopical analysis of hair can reliably be used to differentiate hair samples, many of which were macroscopically similar. Using cut hair samples, many sharing similar macroscopic and microscopic features, collected from individuals who share the same mitochondrial haplogroup as an indication of genetic relatedness, we tested multiple aspects that could impact hair comparisons. This research tested the extent to which morphological features related to ancestry and hair length influence conclusions. Microscopical hair examinations yielded accurate assessments of inclusion/exclusion relative to the reference samples among 85% of the pairwise comparisons. We found shorter hairs had reduced levels of accuracy and hairs from populations examiners were not familiar with may have impacted their ability to resolve features. The reliability of ancestry determinations is not yet clear, but we found indications that the existing categories are only somewhat related to current ethnic and genetic variation. Our results provide support for the continued utility of microscopical comparison of hairs within forensic laboratories and to advocate for a combined analytical approach using both microscopical analysis and mtDNA data on all forensic analyses of hair.
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Affiliation(s)
- Sandra L Koch
- McCrone Associates, Westmont, IL, USA.,Anthropology Department, Pennsylvania State University, University Park, PA, USA
| | - Corey Liebowitz
- Anthropology Department, Pennsylvania State University, University Park, PA, USA
| | - Mark D Shriver
- Anthropology Department, Pennsylvania State University, University Park, PA, USA
| | - Nina G Jablonski
- Anthropology Department, Pennsylvania State University, University Park, PA, USA
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Whole genome sequence analysis reveals genetic structure and X-chromosome haplotype structure in indigenous Chinese pigs. Sci Rep 2020; 10:9433. [PMID: 32523001 PMCID: PMC7286894 DOI: 10.1038/s41598-020-66061-2] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2019] [Accepted: 05/14/2020] [Indexed: 12/05/2022] Open
Abstract
Chinese indigenous pigs exhibit considerable phenotypic diversity, but their population structure and the genetic basis of agriculturally important traits need further exploration. Here, we sequenced the whole genomes of 24 individual pigs representing 22 breeds distributed throughout China. For comparison with European and commercial breeds (one pig per breed), we included seven published pig genomes with our new genomes for analyses. Our results showed that breeds grouped together based on morphological classifications are not necessarily more genetically similar to each other than to breeds from other groups. We found that genetic material from European pigs likely introgressed into five Chinese breeds. We have identified two new subpopulations of domestic pigs that encompass morphology-based criteria in China. The Southern Chinese subpopulation comprises the classical South Chinese Type and part of the Central China Type. In contrast, the Northern Chinese subpopulation comprises the North China Type, the Lower Yangtze River Basin Type, the Southwest Type, the Plateau Type, and the remainder of the Central China Type. Eight haplotypes and two recombination sites were identified within a conserved 40.09 Mb linkage-disequilibrium (LD) block on the X chromosome. Potential candidate genes (LEPR, FANCC, COL1A1, and PCCA) influencing body size were identified. Our findings provide insights into the phylogeny of Chinese indigenous pig breeds and benefit gene mining efforts to improve major economic traits.
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Battey CJ, Ralph PL, Kern AD. Predicting geographic location from genetic variation with deep neural networks. eLife 2020; 9:e54507. [PMID: 32511092 PMCID: PMC7324158 DOI: 10.7554/elife.54507] [Citation(s) in RCA: 45] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2019] [Accepted: 06/03/2020] [Indexed: 12/12/2022] Open
Abstract
Most organisms are more closely related to nearby than distant members of their species, creating spatial autocorrelations in genetic data. This allows us to predict the location of origin of a genetic sample by comparing it to a set of samples of known geographic origin. Here, we describe a deep learning method, which we call Locator, to accomplish this task faster and more accurately than existing approaches. In simulations, Locator infers sample location to within 4.1 generations of dispersal and runs at least an order of magnitude faster than a recent model-based approach. We leverage Locator's computational efficiency to predict locations separately in windows across the genome, which allows us to both quantify uncertainty and describe the mosaic ancestry and patterns of geographic mixing that characterize many populations. Applied to whole-genome sequence data from Plasmodium parasites, Anopheles mosquitoes, and global human populations, this approach yields median test errors of 16.9km, 5.7km, and 85km, respectively.
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Affiliation(s)
- CJ Battey
- University of Oregon, Institute of Ecology and EvolutionEugeneUnited States
| | - Peter L Ralph
- University of Oregon, Institute of Ecology and EvolutionEugeneUnited States
| | - Andrew D Kern
- University of Oregon, Institute of Ecology and EvolutionEugeneUnited States
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Characterisation of a second gain of function EDAR variant, encoding EDAR380R, in East Asia. Eur J Hum Genet 2020; 28:1694-1702. [PMID: 32499598 DOI: 10.1038/s41431-020-0660-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2019] [Revised: 04/07/2020] [Accepted: 05/12/2020] [Indexed: 11/08/2022] Open
Abstract
Ectodysplasin A1 receptor (EDAR) is a TNF receptor family member with roles in the development and growth of hair, teeth and glands. A derived allele of EDAR, single-nucleotide variant rs3827760, encodes EDAR:p.(Val370Ala), a receptor with more potent signalling effects than the ancestral EDAR370Val. This allele of rs3827760 is at very high frequency in modern East Asian and Native American populations as a result of ancient positive selection and has been associated with straighter, thicker hair fibres, alteration of tooth and ear shape, reduced chin protrusion and increased fingertip sweat gland density. Here we report the characterisation of another SNV in EDAR, rs146567337, encoding EDAR:p.(Ser380Arg). The derived allele of this SNV is at its highest global frequency, of up to 5%, in populations of southern China, Vietnam, the Philippines, Malaysia and Indonesia. Using haplotype analyses, we find that the rs3827760 and rs146567337 SNVs arose on distinct haplotypes and that rs146567337 does not show the same signs of positive selection as rs3827760. From functional studies in cultured cells, we find that EDAR:p.(Ser380Arg) displays increased EDAR signalling output, at a similar level to that of EDAR:p.(Val370Ala). The existence of a second SNV with partly overlapping geographic distribution, the same in vitro functional effect and similar evolutionary age as the derived allele of rs3827760, but of independent origin and not exhibiting the same signs of strong selection, suggests a northern focus of positive selection on EDAR function in East Asia.
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31
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Leerunyakul K, Suchonwanit P. Asian Hair: A Review of Structures, Properties, and Distinctive Disorders. Clin Cosmet Investig Dermatol 2020; 13:309-318. [PMID: 32425573 PMCID: PMC7187942 DOI: 10.2147/ccid.s247390] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2020] [Accepted: 04/08/2020] [Indexed: 11/23/2022]
Abstract
Asian hair is known for its straightness, dark pigmentation, and large diameter. The cuticle layer in Asians is thicker with more compact cuticle cells than that in Caucasians. Asian hair generally exhibits the strongest mechanical properties, and its cross-sectional area is determined greatly by genetic variations, particularly from the ectodysplasin A receptor gene. However, knowledge on Asian hair remains unclear with limited studies. This article aimed to review and summarize the characteristics and properties of Asian hair. It also aimed to discuss hair disorders including linear lupus panniculitis and pseudocyst of the scalp that occur distinctively in Asian populations.
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Affiliation(s)
- Kanchana Leerunyakul
- Division of Dermatology, Department of Medicine, Faculty of Medicine, Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
| | - Poonkiat Suchonwanit
- Division of Dermatology, Department of Medicine, Faculty of Medicine, Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
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32
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Seidualy M, Blazyte A, Jeon S, Bhak Y, Jeon Y, Kim J, Eriksson A, Bolser D, Yoon C, Manica A, Lee S, Bhak J. Decoding a highly mixed Kazakh genome. Hum Genet 2020; 139:557-568. [PMID: 32076829 PMCID: PMC7170836 DOI: 10.1007/s00439-020-02132-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2019] [Accepted: 02/05/2020] [Indexed: 01/22/2023]
Abstract
We provide a Kazakh whole genome sequence (MJS) and analyses with the largest comparative Kazakh genomic data available to date. We found 102,240 novel SNVs and a high level of heterozygosity. ADMIXTURE analysis confirmed a significant proportion of variations in this individual coming from all continents except Africa and Oceania. A principal component analysis showed neighboring Kalmyk, Uzbek, and Kyrgyz populations to have the strongest resemblance to the MJS genome which reflects fairly recent Kazakh history. MJS's mitochondrial haplogroup, J1c2, probably represents an early European and Near Eastern influence to Central Asia. This was also supported by the heterozygous SNPs associated with European phenotypic features and strikingly similar Kazakh ancestral composition inferred by ADMIXTURE. Admixture (f3) analysis showed that MJS's genomic signature is best described as a cross between the Neolithic East Asian (Devil's Gate1) and the Bronze Age European (Halberstadt_LBA1) components rather than a contemporary admixture.
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Affiliation(s)
- Madina Seidualy
- Korean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST), Ulsan, 44919 Republic of Korea
| | - Asta Blazyte
- Korean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST), Ulsan, 44919 Republic of Korea
| | - Sungwon Jeon
- Korean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST), Ulsan, 44919 Republic of Korea
- Department of Biomedical Engineering, School of Life Sciences, Ulsan National Institute of Science and Technology (UNIST), Ulsan, 44919 Republic of Korea
| | - Youngjune Bhak
- Korean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST), Ulsan, 44919 Republic of Korea
- Department of Biomedical Engineering, School of Life Sciences, Ulsan National Institute of Science and Technology (UNIST), Ulsan, 44919 Republic of Korea
| | - Yeonsu Jeon
- Korean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST), Ulsan, 44919 Republic of Korea
- Department of Biomedical Engineering, School of Life Sciences, Ulsan National Institute of Science and Technology (UNIST), Ulsan, 44919 Republic of Korea
| | - Jungeun Kim
- Personal Genomics Institute (PGI), Genome Research Foundation, Cheongju, 28160 Republic of Korea
| | - Anders Eriksson
- Department of Medical and Molecular Genetics, King’s College London, London, SE1 9RT UK
- cGEM, Institute of Genomics, University of Tartu, Riia 23b, 51010 Tartu, Estonia
| | - Dan Bolser
- Geromics Ltd, Office 261, 23 Kings Street, Cambridge, CB1 1AH UK
| | - Changhan Yoon
- Korean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST), Ulsan, 44919 Republic of Korea
- Department of Biomedical Engineering, School of Life Sciences, Ulsan National Institute of Science and Technology (UNIST), Ulsan, 44919 Republic of Korea
| | - Andrea Manica
- Department of Zoology, University of Cambridge, Downing Street, Cambridge, CB2 3EJ UK
| | - Semin Lee
- Korean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST), Ulsan, 44919 Republic of Korea
- Department of Biomedical Engineering, School of Life Sciences, Ulsan National Institute of Science and Technology (UNIST), Ulsan, 44919 Republic of Korea
| | - Jong Bhak
- Korean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST), Ulsan, 44919 Republic of Korea
- Department of Biomedical Engineering, School of Life Sciences, Ulsan National Institute of Science and Technology (UNIST), Ulsan, 44919 Republic of Korea
- Personal Genomics Institute (PGI), Genome Research Foundation, Cheongju, 28160 Republic of Korea
- Clinomics LTD, Ulsan National Institute of Science and Technology (UNIST), Ulsan, 44919 Republic of Korea
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33
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Evaluation of Hair Density and Hair Diameter in the Adult Thai Population Using Quantitative Trichoscopic Analysis. BIOMED RESEARCH INTERNATIONAL 2020; 2020:2476890. [PMID: 32104683 PMCID: PMC7035527 DOI: 10.1155/2020/2476890] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/28/2019] [Accepted: 01/06/2020] [Indexed: 11/29/2022]
Abstract
The data of hair density and hair diameter in the Asian population, especially in Thais, are limited. We aimed to evaluate hair density and hair diameter of members of the Thai population at different scalp sites and to determine the effect of sex and aging as well as to compare the results with those in groups of other ethnicities. Healthy Thais whose hair examination findings were normal were evaluated. Two hundred and thirty-nine subjects participated in this study, of whom 79 were male and 160 were female. Hair density and hair diameter were analyzed at four different scalp sites using quantitative trichoscopic analysis. The highest hair density in Thais was observed in the vertex area. Hair densities at four different scalp sites were significantly different from one another; only hair density at the vertex site showed no significant difference from that in the occipital area. In contrast, hair diameter did not show any statistically significant differences for the different sites. We observed decreased mean hair density with increasing age and found statistically significant differences between participants in their 20s and those in their 60s, while hair diameter remained consistent. Comparing our results with a previous study in other ethnicities, the hair densities in Asians are generally lower. In conclusion, hair density in the Thai population varies at different scalp sites. Aging is a factor in declining hair density. Asians have a lower hair density compared to Caucasian and African populations.
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34
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Rehman AU, Iqbal J, Shakeel A, Qamar ZU, Rana P. Hardy-Weinberg equilibrium study of six morphogenetic characters in a population of Punjab, Pakistan. ALL LIFE 2020. [DOI: 10.1080/26895293.2020.1750491] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022] Open
Affiliation(s)
- Aneeq-ur- Rehman
- Department of Plant Breeding and Genetics, University of Agriculture Faisalabad, Faisalabad, Pakistan
| | - Junaid Iqbal
- Department of Plant Breeding and Genetics, University of Agriculture Faisalabad, Faisalabad, Pakistan
| | - Amir Shakeel
- Department of Plant Breeding and Genetics, University of Agriculture Faisalabad, Faisalabad, Pakistan
| | - Zia ul Qamar
- Nuclear Institute for Agriculture and Biology, Faisalabad, Pakistan
| | - Poonum Rana
- Department of Zoology, University of Agriculture Faisalabad, Faisalabad, Pakistan
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35
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Satta Y, Zheng W, Nishiyama KV, Iwasaki RL, Hayakawa T, Fujito NT, Takahata N. Two-dimensional site frequency spectrum for detecting, classifying and dating incomplete selective sweeps. Genes Genet Syst 2019; 94:283-300. [DOI: 10.1266/ggs.19-00012] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Affiliation(s)
- Yoko Satta
- School of Advanced Sciences, SOKENDAI (The Graduate University for Advanced Studies)
| | - Wanjing Zheng
- School of Advanced Sciences, SOKENDAI (The Graduate University for Advanced Studies)
| | - Kumiko V. Nishiyama
- School of Advanced Sciences, SOKENDAI (The Graduate University for Advanced Studies)
| | - Risa L. Iwasaki
- School of Advanced Sciences, SOKENDAI (The Graduate University for Advanced Studies)
| | - Toshiyuki Hayakawa
- Graduate School of Systems Life Sciences and Faculty of Arts and Science, Kyushu University
| | - Naoko T. Fujito
- Institute for Human Genetics and Department of Epidemiology and Biostatistics, University of California
| | - Naoyuki Takahata
- School of Advanced Sciences, SOKENDAI (The Graduate University for Advanced Studies)
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36
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Glueck C, Wilson JA. RETRACTED: Is photoshop with Qualitative Image Analysis a valid technique for measuring hair morphology? A test using wires of known dimensions. JOURNAL OF VERTEBRATE BIOLOGY 2019. [DOI: 10.25225/fozo.012.2019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Affiliation(s)
- Christopher Glueck
- Department of Biology, University of Nebraska at Omaha, 6001 Dodge Street, Omaha, NE 68182-0040, USA; e-mail:
| | - James A. Wilson
- Department of Biology, University of Nebraska at Omaha, 6001 Dodge Street, Omaha, NE 68182-0040, USA; e-mail:
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37
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Koch SL, Tridico SR, Bernard BA, Shriver MD, Jablonski NG. The biology of human hair: A multidisciplinary review. Am J Hum Biol 2019; 32:e23316. [DOI: 10.1002/ajhb.23316] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2018] [Revised: 07/21/2019] [Accepted: 08/17/2019] [Indexed: 12/22/2022] Open
Affiliation(s)
- Sandra L. Koch
- Department of AnthropologyPennsylvania State University State College Pennsylvania
| | | | | | - Mark D. Shriver
- Department of AnthropologyPennsylvania State University State College Pennsylvania
| | - Nina G. Jablonski
- Department of AnthropologyPennsylvania State University State College Pennsylvania
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38
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Szpak M, Xue Y, Ayub Q, Tyler‐Smith C. How well do we understand the basis of classic selective sweeps in humans? FEBS Lett 2019; 593:1431-1448. [DOI: 10.1002/1873-3468.13447] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2019] [Revised: 04/29/2019] [Accepted: 05/17/2019] [Indexed: 12/14/2022]
Affiliation(s)
| | - Yali Xue
- The Wellcome Sanger Institute Hinxton UK
| | - Qasim Ayub
- School of Science Monash University Malaysia Bandar Sunway Malaysia
- Tropical Medicine and Biology Multidisciplinary Platform Monash University Malaysia Genomics Facility Bandar Sunway Malaysia
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39
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Koganebuchi K, Kimura R. Biomedical and genetic characteristics of the Ryukyuans: demographic history, diseases and physical and physiological traits. Ann Hum Biol 2019; 46:354-366. [PMID: 31116031 DOI: 10.1080/03014460.2019.1582699] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Context: The Ryukyu Islands stretch across a southwestern area of the Japanese Archipelago. Because of their unique geographical and historical backgrounds, Ryukyuans have their own genetic and phenotypic characteristics, which have been disclosed in previous anthropological and biomedical studies. Objective: The history, peopling and biomedical and genetic characteristics of Ryukyuans are reviewed and future research directions are discussed. Conclusion: Morphological and genetic studies have suggested the complex demographic history of Ryukyuans and their relationships with other Asian populations. Knowledge of population formation processes is important to understand the distribution of pathogens. In viral infectious diseases, some strains that may be associated with disease symptoms are specific to Ryukyuans. Dramatic changes in diet have played an important role among Ryukyuans in terms of increases in lifestyle-related diseases and mortality risks. To achieve a better understanding of pathogenic disease factors, further integration of findings regarding the genetic and biomedical characteristics of the Ryukyuans is needed.
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Affiliation(s)
- Kae Koganebuchi
- Department of Human Biology and Anatomy, Graduate School of Medicine, University of the Ryukyus , Okinawa , Japan
| | - Ryosuke Kimura
- Department of Human Biology and Anatomy, Graduate School of Medicine, University of the Ryukyus , Okinawa , Japan
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40
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Li Y, Zhao W, Li D, Tao X, Xiong Z, Liu J, Zhang W, Ji A, Tang K, Liu F, Li C. EDAR, LYPLAL1, PRDM16, PAX3, DKK1, TNFSF12, CACNA2D3, and SUPT3H gene variants influence facial morphology in a Eurasian population. Hum Genet 2019; 138:681-689. [PMID: 31025105 DOI: 10.1007/s00439-019-02023-7] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2019] [Accepted: 04/20/2019] [Indexed: 12/19/2022]
Abstract
In human society, the facial surface is visible and recognizable based on the facial shape variation which represents a set of highly polygenic and correlated complex traits. Understanding the genetic basis underlying facial shape traits has important implications in population genetics, developmental biology, and forensic science. A number of single nucleotide polymorphisms (SNPs) are associated with human facial shape variation, mostly in European populations. To bridge the gap between European and Asian populations in term of the genetic basis of facial shape variation, we examined the effect of these SNPs in a European-Asian admixed Eurasian population which included a total of 612 individuals. The coordinates of 17 facial landmarks were derived from high resolution 3dMD facial images, and 136 Euclidean distances between all pairs of landmarks were quantitatively derived. DNA samples were genotyped using the Illumina Infinium Global Screening Array and imputed using the 1000 Genomes reference panel. Genetic association between 125 previously reported facial shape-associated SNPs and 136 facial shape phenotypes was tested using linear regression. As a result, a total of eight SNPs from different loci demonstrated significant association with one or more facial shape traits after adjusting for multiple testing (significance threshold p < 1.28 × 10-3), together explaining up to 6.47% of sex-, age-, and BMI-adjusted facial phenotype variance. These included EDAR rs3827760, LYPLAL1 rs5781117, PRDM16 rs4648379, PAX3 rs7559271, DKK1 rs1194708, TNFSF12 rs80067372, CACNA2D3 rs56063440, and SUPT3H rs227833. Notably, the EDAR rs3827760 and LYPLAL1 rs5781117 SNPs displayed significant association with eight and seven facial phenotypes, respectively (2.39 × 10-5 < p < 1.28 × 10-3). The majority of these SNPs showed a distinct allele frequency between European and East Asian reference panels from the 1000 Genomes Project. These results showed the details of above eight genes influence facial shape variation in a Eurasian population.
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Affiliation(s)
- Yi Li
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Beijing, China
| | - Wenting Zhao
- Key Laboratory of Forensic Genetics, National Engineering Laboratory for Forensic Science, Institute of Forensic Science, Beijing, China
| | - Dan Li
- CAS-MPG Partner Institute and Key Laboratory for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Xianming Tao
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Beijing, China
| | - Ziyi Xiong
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Beijing, China
| | - Jing Liu
- Key Laboratory of Forensic Genetics, National Engineering Laboratory for Forensic Science, Institute of Forensic Science, Beijing, China
| | - Wei Zhang
- Key Laboratory of Forensic Genetics, National Engineering Laboratory for Forensic Science, Institute of Forensic Science, Beijing, China
| | - Anquan Ji
- Key Laboratory of Forensic Genetics, National Engineering Laboratory for Forensic Science, Institute of Forensic Science, Beijing, China
| | - Kun Tang
- CAS-MPG Partner Institute and Key Laboratory for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Fan Liu
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Beijing, China.
- Department of Genetic Identification, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands.
| | - Caixia Li
- Key Laboratory of Forensic Genetics, National Engineering Laboratory for Forensic Science, Institute of Forensic Science, Beijing, China.
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41
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An Integrated Analysis of Cashmere Fineness lncRNAs in Cashmere Goats. Genes (Basel) 2019; 10:genes10040266. [PMID: 30987022 PMCID: PMC6523453 DOI: 10.3390/genes10040266] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2019] [Revised: 03/23/2019] [Accepted: 03/28/2019] [Indexed: 02/06/2023] Open
Abstract
Animal growth and development are regulated by long non-coding RNAs (lncRNAs). However, the functions of lncRNAs in regulating cashmere fineness are poorly understood. To identify the key lncRNAs that are related to cashmere fineness in skin, we have collected skin samples of Liaoning cashmere goats (LCG) and Inner Mongolia cashmere goats (MCG) in the anagen phase, and have performed RNA sequencing (RNA-seq) approach on these samples. The high-throughput sequencing and bioinformatics analyses identified 437 novel lncRNAs, including 93 differentially expressed lncRNAs. We also identified 3084 differentially expressed messenger RNAs (mRNAs) out of 27,947 mRNAs. Gene ontology (GO) analyses of lncRNAs and target genes in cis show a predominant enrichment of targets that are related to intermediate filament and intermediate filament cytoskeleton. According to the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, sphingolipid metabolism is a significant pathway for lncRNA targets. In addition, this is the first report to reveal the possible lncRNA–mRNA regulatory network for cashmere fineness in cashmere goats. We also found that lncRNA XLOC_008679 and its target gene, KRT35, may be related to cashmere fineness in the anagen phase. The characterization and expression analyses of lncRNAs will facilitate future studies on the potential value of fiber development in LCG.
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42
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Wang J, Cui K, Yang Z, Li T, Hua G, Han D, Yao Y, Chen J, Deng X, Yang X, Deng X. Transcriptome Analysis of Improved Wool Production in Skin-Specific Transgenic Sheep Overexpressing Ovine β-Catenin. Int J Mol Sci 2019; 20:ijms20030620. [PMID: 30709037 PMCID: PMC6387261 DOI: 10.3390/ijms20030620] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2018] [Revised: 01/21/2019] [Accepted: 01/24/2019] [Indexed: 12/16/2022] Open
Abstract
β-Catenin is an evolutionarily conserved molecule in the canonical Wnt signaling pathway, which controls decisive steps in embryogenesis and functions as a crucial effector in the development of hair follicles. However, the molecular mechanisms underlying wool production have not been fully elucidated. In this study, we investigated the effects of ovine β-catenin on wool follicles of transgenic sheep produced by pronuclear microinjection with a skin-specific promoter of human keratin14 (k14). Both polymerase chain reaction and Southern blot analysis showed that the sheep carried the ovine β-catenin gene and that the β-catenin gene could be stably inherited. To study the molecular responses to high expression of β-catenin, high-throughput RNA-seq technology was employed using three transgenic sheep and their wild-type siblings. These findings suggest that β-catenin normally plays an important role in wool follicle development by activating the downstream genes of the Wnt pathway and enhancing the expression of keratin protein genes and keratin-associated protein genes.
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Affiliation(s)
- Jiankui Wang
- Key Laboratory of Animal Genetics, Breeding, and Reproduction of the Ministry of Agriculture & Beijing Key Laboratory of Animal Genetic Improvement, China Agricultural University, Beijing 100193, China.
| | - Kai Cui
- Key Laboratory of Animal Genetics, Breeding, and Reproduction of the Ministry of Agriculture & Beijing Key Laboratory of Animal Genetic Improvement, China Agricultural University, Beijing 100193, China.
| | - Zu Yang
- Key Laboratory of Animal Genetics, Breeding, and Reproduction of the Ministry of Agriculture & Beijing Key Laboratory of Animal Genetic Improvement, China Agricultural University, Beijing 100193, China.
| | - Tun Li
- Key Laboratory of Animal Genetics, Breeding, and Reproduction of the Ministry of Agriculture & Beijing Key Laboratory of Animal Genetic Improvement, China Agricultural University, Beijing 100193, China.
| | - Guoying Hua
- Key Laboratory of Animal Genetics, Breeding, and Reproduction of the Ministry of Agriculture & Beijing Key Laboratory of Animal Genetic Improvement, China Agricultural University, Beijing 100193, China.
| | - Deping Han
- Key Laboratory of Animal Genetics, Breeding, and Reproduction of the Ministry of Agriculture & Beijing Key Laboratory of Animal Genetic Improvement, China Agricultural University, Beijing 100193, China.
| | - Yanzhu Yao
- Key Laboratory of Animal Genetics, Breeding, and Reproduction of the Ministry of Agriculture & Beijing Key Laboratory of Animal Genetic Improvement, China Agricultural University, Beijing 100193, China.
| | - Jianfei Chen
- Key Laboratory of Animal Genetics, Breeding, and Reproduction of the Ministry of Agriculture & Beijing Key Laboratory of Animal Genetic Improvement, China Agricultural University, Beijing 100193, China.
| | - Xiaotian Deng
- Key Laboratory of Animal Genetics, Breeding, and Reproduction of the Ministry of Agriculture & Beijing Key Laboratory of Animal Genetic Improvement, China Agricultural University, Beijing 100193, China.
| | - Xue Yang
- Key Laboratory of Animal Genetics, Breeding, and Reproduction of the Ministry of Agriculture & Beijing Key Laboratory of Animal Genetic Improvement, China Agricultural University, Beijing 100193, China.
| | - Xuemei Deng
- Key Laboratory of Animal Genetics, Breeding, and Reproduction of the Ministry of Agriculture & Beijing Key Laboratory of Animal Genetic Improvement, China Agricultural University, Beijing 100193, China.
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Liu F, Chen Y, Zhu G, Hysi PG, Wu S, Adhikari K, Breslin K, Pospiech E, Hamer MA, Peng F, Muralidharan C, Acuna-Alonzo V, Canizales-Quinteros S, Bedoya G, Gallo C, Poletti G, Rothhammer F, Bortolini MC, Gonzalez-Jose R, Zeng C, Xu S, Jin L, Uitterlinden AG, Ikram MA, van Duijn CM, Nijsten T, Walsh S, Branicki W, Wang S, Ruiz-Linares A, Spector TD, Martin NG, Medland SE, Kayser M. Meta-analysis of genome-wide association studies identifies 8 novel loci involved in shape variation of human head hair. Hum Mol Genet 2019; 27:559-575. [PMID: 29220522 PMCID: PMC5886212 DOI: 10.1093/hmg/ddx416] [Citation(s) in RCA: 43] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2017] [Accepted: 11/29/2017] [Indexed: 01/18/2023] Open
Abstract
Shape variation of human head hair shows striking variation within and between human populations, while its genetic basis is far from being understood. We performed a series of genome-wide association studies (GWASs) and replication studies in a total of 28 964 subjects from 9 cohorts from multiple geographic origins. A meta-analysis of three European GWASs identified 8 novel loci (1p36.23 ERRFI1/SLC45A1, 1p36.22 PEX14, 1p36.13 PADI3, 2p13.3 TGFA, 11p14.1 LGR4, 12q13.13 HOXC13, 17q21.2 KRTAP, and 20q13.33 PTK6), and confirmed 4 previously known ones (1q21.3 TCHH/TCHHL1/LCE3E, 2q35 WNT10A, 4q21.21 FRAS1, and 10p14 LINC00708/GATA3), all showing genome-wide significant association with hair shape (P < 5e-8). All except one (1p36.22 PEX14) were replicated with nominal significance in at least one of the 6 additional cohorts of European, Native American and East Asian origins. Three additional previously known genes (EDAR, OFCC1, and PRSS53) were confirmed at the nominal significance level. A multivariable regression model revealed that 14 SNPs from different genes significantly and independently contribute to hair shape variation, reaching a cross-validated AUC value of 0.66 (95% CI: 0.62–0.70) and an AUC value of 0.64 in an independent validation cohort, providing an improved accuracy compared with a previous model. Prediction outcomes of 2504 individuals from a multiethnic sample were largely consistent with general knowledge on the global distribution of hair shape variation. Our study thus delivers target genes and DNA variants for future functional studies to further evaluate the molecular basis of hair shape in humans.
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Affiliation(s)
- Fan Liu
- Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China.,Department of Genetic Identification, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands.,University of Chinese Academy of Sciences, Beijing, China
| | - Yan Chen
- Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China.,University of Chinese Academy of Sciences, Beijing, China
| | - Gu Zhu
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Pirro G Hysi
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Sijie Wu
- University of Chinese Academy of Sciences, Beijing, China.,Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute for Biological Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Kaustubh Adhikari
- Department of Genetics, Evolution, and Environment, University College London, London WC1E 6BT, UK
| | - Krystal Breslin
- Department of Biology, Indiana-University-Purdue-University-Indianapolis (IUPUI), Indianapolis, IN, USA
| | - Ewelina Pospiech
- Institute of Zoology and Biomedical Research, Faculty of Biology and Earth Sciences, Jagiellonian University, Kraków, Poland.,Malopolska Centre of Biotechnology, Jagiellonian University, Kraków, Poland
| | - Merel A Hamer
- Department of Dermatology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Fuduan Peng
- Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China.,University of Chinese Academy of Sciences, Beijing, China
| | - Charanya Muralidharan
- Department of Biology, Indiana-University-Purdue-University-Indianapolis (IUPUI), Indianapolis, IN, USA
| | - Victor Acuna-Alonzo
- Laboratorio de Genética Molecular, Escuela Nacional de Antropologia e Historia, México City, México
| | - Samuel Canizales-Quinteros
- Unidad de Genómica de Poblaciones Aplicada a la Salud, Facultad de Química, UNAM-Instituto Nacional de Medicina Genómica, México City, México
| | - Gabriel Bedoya
- GENMOL (Genética Molecular), Universidad de Antioquia, Medellín, Colombia
| | - Carla Gallo
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Perú
| | - Giovanni Poletti
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Perú
| | | | - Maria Catira Bortolini
- Departamento de Genética, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brasil
| | - Rolando Gonzalez-Jose
- Instituto Patagónico de Ciencias Sociales y Humanas, CENPAT-CONICET, Puerto Madryn, Argentina
| | - Changqing Zeng
- Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China
| | - Shuhua Xu
- University of Chinese Academy of Sciences, Beijing, China.,Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute for Biological Sciences, Chinese Academy of Sciences, Shanghai, China.,State Key Laboratory of Genetic Engineering and Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai, China.,School of Life Science and Technology, Shanghai Tech University, Shanghai, China
| | - Li Jin
- University of Chinese Academy of Sciences, Beijing, China.,State Key Laboratory of Genetic Engineering and Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai, China
| | - André G Uitterlinden
- Department of Internal Medicine, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands.,Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - M Arfan Ikram
- Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Cornelia M van Duijn
- Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Tamar Nijsten
- Department of Dermatology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Susan Walsh
- Department of Biology, Indiana-University-Purdue-University-Indianapolis (IUPUI), Indianapolis, IN, USA
| | - Wojciech Branicki
- Malopolska Centre of Biotechnology, Jagiellonian University, Kraków, Poland.,Central Forensic Laboratory of the Police, Warsaw, Poland
| | - Sijia Wang
- University of Chinese Academy of Sciences, Beijing, China.,Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute for Biological Sciences, Chinese Academy of Sciences, Shanghai, China.,State Key Laboratory of Genetic Engineering and Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai, China
| | - Andrés Ruiz-Linares
- Department of Genetics, Evolution, and Environment, University College London, London WC1E 6BT, UK.,Ministry of Education Key Laboratory of Contemporary Anthropology and Collaborative Innovation Center of Genetics and Development, Fudan University, Shanghai, China.,Laboratory of Biocultural Anthropology, Law, Ethics, and Health (Centre National de la Recherche Scientifique and Etablissement Français du Sang), Aix-Marseille Université, Marseille, France
| | - Timothy D Spector
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Nicholas G Martin
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Sarah E Medland
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Manfred Kayser
- Department of Genetic Identification, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
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KANZAWA-KIRIYAMA HIDEAKI, JINAM TIMOTHYA, KAWAI YOSUKE, SATO TAKEHIRO, HOSOMICHI KAZUYOSHI, TAJIMA ATSUSHI, ADACHI NOBORU, MATSUMURA HIROFUMI, KRYUKOV KIRILL, SAITOU NARUYA, SHINODA KENICHI. Late Jomon male and female genome sequences from the Funadomari site in Hokkaido, Japan. ANTHROPOL SCI 2019. [DOI: 10.1537/ase.190415] [Citation(s) in RCA: 42] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/01/2022]
Affiliation(s)
| | - TIMOTHY A. JINAM
- Division of Population Genetics, National Institute of Genetics, Mishima
| | - YOSUKE KAWAI
- Department of Human Genetics, Graduate School of Medicine, The University of Tokyo, Tokyo
| | - TAKEHIRO SATO
- Department of Bioinformatics and Genomics, Graduate School of Medical Sciences, Kanazawa University, Kanazawa
| | - KAZUYOSHI HOSOMICHI
- Department of Bioinformatics and Genomics, Graduate School of Medical Sciences, Kanazawa University, Kanazawa
| | - ATSUSHI TAJIMA
- Department of Bioinformatics and Genomics, Graduate School of Medical Sciences, Kanazawa University, Kanazawa
| | - NOBORU ADACHI
- Department of Legal Medicine, Interdisciplinary Graduate School of Medicine and Engineering, University of Yamanashi, Chuo
| | - HIROFUMI MATSUMURA
- Second Division of Physical Therapy, School of Health Sciences, Sapporo Medical University, Sapporo
| | - KIRILL KRYUKOV
- Department of Molecular Life Science, School of Medicine, Tokai University, Isehara
| | - NARUYA SAITOU
- Division of Population Genetics, National Institute of Genetics, Mishima
| | - KEN-ICHI SHINODA
- Department of Anthropology, National Museum of Nature and Science, Tsukuba
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45
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Koch SL, Shriver MD, Jablonski NG. Variation in human hair ultrastructure among three biogeographic populations. J Struct Biol 2019; 205:60-66. [DOI: 10.1016/j.jsb.2018.11.008] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2018] [Revised: 11/11/2018] [Accepted: 11/21/2018] [Indexed: 11/30/2022]
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46
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Detection and Classification of Hard and Soft Sweeps from Unphased Genotypes by Multilocus Genotype Identity. Genetics 2018; 210:1429-1452. [PMID: 30315068 DOI: 10.1534/genetics.118.301502] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2018] [Accepted: 10/08/2018] [Indexed: 11/18/2022] Open
Abstract
Positive natural selection can lead to a decrease in genomic diversity at the selected site and at linked sites, producing a characteristic signature of elevated expected haplotype homozygosity. These selective sweeps can be hard or soft. In the case of a hard selective sweep, a single adaptive haplotype rises to high population frequency, whereas multiple adaptive haplotypes sweep through the population simultaneously in a soft sweep, producing distinct patterns of genetic variation in the vicinity of the selected site. Measures of expected haplotype homozygosity have previously been used to detect sweeps in multiple study systems. However, these methods are formulated for phased haplotype data, typically unavailable for nonmodel organisms, and some may have reduced power to detect soft sweeps due to their increased genetic diversity relative to hard sweeps. To address these limitations, we applied the H12 and H2/H1 statistics proposed in 2015 by Garud et al., which have power to detect both hard and soft sweeps, to unphased multilocus genotypes, denoting them as G12 and G2/G1. G12 (and the more direct expected homozygosity analog to H12, denoted G123) has comparable power to H12 for detecting both hard and soft sweeps. G2/G1 can be used to classify hard and soft sweeps analogously to H2/H1, conditional on a genomic region having high G12 or G123 values. The reason for this power is that, under random mating, the most frequent haplotypes will yield the most frequent multilocus genotypes. Simulations based on parameters compatible with our recent understanding of human demographic history suggest that expected homozygosity methods are best suited for detecting recent sweeps, and increase in power under recent population expansions. Finally, we find candidates for selective sweeps within the 1000 Genomes CEU, YRI, GIH, and CHB populations, which corroborate and complement existing studies.
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47
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Pośpiech E, Chen Y, Kukla-Bartoszek M, Breslin K, Aliferi A, Andersen JD, Ballard D, Chaitanya L, Freire-Aradas A, van der Gaag KJ, Girón-Santamaría L, Gross TE, Gysi M, Huber G, Mosquera-Miguel A, Muralidharan C, Skowron M, Carracedo Á, Haas C, Morling N, Parson W, Phillips C, Schneider PM, Sijen T, Syndercombe-Court D, Vennemann M, Wu S, Xu S, Jin L, Wang S, Zhu G, Martin NG, Medland SE, Branicki W, Walsh S, Liu F, Kayser M. Towards broadening Forensic DNA Phenotyping beyond pigmentation: Improving the prediction of head hair shape from DNA. Forensic Sci Int Genet 2018; 37:241-251. [PMID: 30268682 DOI: 10.1016/j.fsigen.2018.08.017] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2018] [Revised: 07/18/2018] [Accepted: 08/27/2018] [Indexed: 10/28/2022]
Abstract
Human head hair shape, commonly classified as straight, wavy, curly or frizzy, is an attractive target for Forensic DNA Phenotyping and other applications of human appearance prediction from DNA such as in paleogenetics. The genetic knowledge underlying head hair shape variation was recently improved by the outcome of a series of genome-wide association and replication studies in a total of 26,964 subjects, highlighting 12 loci of which 8 were novel and introducing a prediction model for Europeans based on 14 SNPs. In the present study, we evaluated the capacity of DNA-based head hair shape prediction by investigating an extended set of candidate SNP predictors and by using an independent set of samples for model validation. Prediction model building was carried out in 9674 subjects (6068 from Europe, 2899 from Asia and 707 of admixed European and Asian ancestries), used previously, by considering a novel list of 90 candidate SNPs. For model validation, genotype and phenotype data were newly collected in 2415 independent subjects (2138 Europeans and 277 non-Europeans) by applying two targeted massively parallel sequencing platforms, Ion Torrent PGM and MiSeq, or the MassARRAY platform. A binomial model was developed to predict straight vs. non-straight hair based on 32 SNPs from 26 genetic loci we identified as significantly contributing to the model. This model achieved prediction accuracies, expressed as AUC, of 0.664 in Europeans and 0.789 in non-Europeans; the statistically significant difference was explained mostly by the effect of one EDAR SNP in non-Europeans. Considering sex and age, in addition to the SNPs, slightly and insignificantly increased the prediction accuracies (AUC of 0.680 and 0.800, respectively). Based on the sample size and candidate DNA markers investigated, this study provides the most robust, validated, and accurate statistical prediction models and SNP predictor marker sets currently available for predicting head hair shape from DNA, providing the next step towards broadening Forensic DNA Phenotyping beyond pigmentation traits.
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Affiliation(s)
- Ewelina Pośpiech
- Institute of Zoology and Biomedical Research, Faculty of Biology, Jagiellonian University, Gronostajowa st. 9, 30-387, Kraków, Poland; Malopolska Centre of Biotechnology, Jagiellonian University, Gronostajowa st. 7A, 30-387, Kraków, Poland
| | - Yan Chen
- Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beichen West Road 1-104, Chaoyang, Beijing, 100101, PR China; University of Chinese Academy of Sciences, 19 Yuquan Road, Shijingshan, Beijing, 100049, PR China
| | - Magdalena Kukla-Bartoszek
- Faculty of Biochemistry, Biophysics and Biotechnology, Jagiellonian University, Gronostajowa st. 7, 30-387, Kraków, Poland
| | - Krystal Breslin
- Department of Biology, Indiana University Purdue University Indianapolis (IUPUI), IN, USA
| | - Anastasia Aliferi
- King's Forensics, Faculty of Life Sciences and Medicine, King's College London, 150 Stamford Street, London, United Kingdom
| | - Jeppe D Andersen
- Section of Forensic Genetics, Department of Forensic Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Frederik V's Vej 11, DK-2100, Copenhagen, Denmark
| | - David Ballard
- King's Forensics, Faculty of Life Sciences and Medicine, King's College London, 150 Stamford Street, London, United Kingdom
| | - Lakshmi Chaitanya
- Department of Genetic Identification, Erasmus MC University Medical Center Rotterdam, P.O. Box 2040, 3000 CA, Rotterdam, Netherlands
| | - Ana Freire-Aradas
- Institute of Legal Medicine, Medical Faculty, University of Cologne, Melatengürtel 60/62, D-50823, Cologne, Germany; Forensic Genetics Unit, Institute of Forensic Sciences, R/ San Francisco s/n, Faculty of Medicine, 15782, University of Santiago de Compostela, Santiago de Compostela, Spain
| | - Kristiaan J van der Gaag
- Division of Biological Traces, Netherlands Forensic Institute, P.O. Box 24044, 2490 AA, The Hague, The Netherlands
| | - Lorena Girón-Santamaría
- Forensic Genetics Unit, Institute of Forensic Sciences, R/ San Francisco s/n, Faculty of Medicine, 15782, University of Santiago de Compostela, Santiago de Compostela, Spain
| | - Theresa E Gross
- Institute of Legal Medicine, Medical Faculty, University of Cologne, Melatengürtel 60/62, D-50823, Cologne, Germany
| | - Mario Gysi
- Zurich Institute of Forensic Medicine, University of Zurich, Winterthurerstrasse 190, 8057, Zurich, Switzerland
| | - Gabriela Huber
- Institute of Legal Medicine, Medical University of Innsbruck, Müllerstrasse 44, 6020, Innsbruck, Austria
| | - Ana Mosquera-Miguel
- Forensic Genetics Unit, Institute of Forensic Sciences, R/ San Francisco s/n, Faculty of Medicine, 15782, University of Santiago de Compostela, Santiago de Compostela, Spain
| | - Charanya Muralidharan
- Department of Biology, Indiana University Purdue University Indianapolis (IUPUI), IN, USA
| | - Małgorzata Skowron
- Department of Dermatology, Collegium Medicum of the Jagiellonian University, Skawińska st. 8, 31-066, Kraków, Poland
| | - Ángel Carracedo
- Forensic Genetics Unit, Institute of Forensic Sciences, R/ San Francisco s/n, Faculty of Medicine, 15782, University of Santiago de Compostela, Santiago de Compostela, Spain; Center of Excellence in Genomic Medicine Research, King Abdulaziz University, Jeddah, KSA, Saudi Arabia
| | - Cordula Haas
- Zurich Institute of Forensic Medicine, University of Zurich, Winterthurerstrasse 190, 8057, Zurich, Switzerland
| | - Niels Morling
- Section of Forensic Genetics, Department of Forensic Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Frederik V's Vej 11, DK-2100, Copenhagen, Denmark
| | - Walther Parson
- Institute of Legal Medicine, Medical University of Innsbruck, Müllerstrasse 44, 6020, Innsbruck, Austria; Forensic Science Program, The Pennsylvania State University, 13 Thomas Building, University Park, PA, 16802, USA
| | - Christopher Phillips
- Forensic Genetics Unit, Institute of Forensic Sciences, R/ San Francisco s/n, Faculty of Medicine, 15782, University of Santiago de Compostela, Santiago de Compostela, Spain
| | - Peter M Schneider
- Institute of Legal Medicine, Medical Faculty, University of Cologne, Melatengürtel 60/62, D-50823, Cologne, Germany
| | - Titia Sijen
- Division of Biological Traces, Netherlands Forensic Institute, P.O. Box 24044, 2490 AA, The Hague, The Netherlands
| | - Denise Syndercombe-Court
- King's Forensics, Faculty of Life Sciences and Medicine, King's College London, 150 Stamford Street, London, United Kingdom
| | - Marielle Vennemann
- Institute of Legal Medicine, University of Münster, Röntgenstr. 23, 48149, Münster, Germany
| | - Sijie Wu
- University of Chinese Academy of Sciences, 19 Yuquan Road, Shijingshan, Beijing, 100049, PR China; Chinese Academy of Sciences Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute for Biological Sciences, Chinese Academy of Sciences, 320 Yue Yang Road Shanghai, 200031, PR China
| | - Shuhua Xu
- University of Chinese Academy of Sciences, 19 Yuquan Road, Shijingshan, Beijing, 100049, PR China; Chinese Academy of Sciences Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute for Biological Sciences, Chinese Academy of Sciences, 320 Yue Yang Road Shanghai, 200031, PR China; State Key Laboratory of Genetic Engineering and Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, 2005 Song Hu Road Shanghai, 200438, PR China; School of Life Science and Technology, Shanghai-Tech University, 393 Middle Huaxia Road, Pudong, Shanghai, 201210, PR China
| | - Li Jin
- Chinese Academy of Sciences Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute for Biological Sciences, Chinese Academy of Sciences, 320 Yue Yang Road Shanghai, 200031, PR China; State Key Laboratory of Genetic Engineering and Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, 2005 Song Hu Road Shanghai, 200438, PR China
| | - Sijia Wang
- University of Chinese Academy of Sciences, 19 Yuquan Road, Shijingshan, Beijing, 100049, PR China; Chinese Academy of Sciences Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute for Biological Sciences, Chinese Academy of Sciences, 320 Yue Yang Road Shanghai, 200031, PR China; State Key Laboratory of Genetic Engineering and Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, 2005 Song Hu Road Shanghai, 200438, PR China
| | - Ghu Zhu
- Queensland Institute of Medical Research, Royal Brisbane Hospital, QLD 4029, Brisbane, Australia
| | - Nick G Martin
- Queensland Institute of Medical Research, Royal Brisbane Hospital, QLD 4029, Brisbane, Australia
| | - Sarah E Medland
- Queensland Institute of Medical Research, Royal Brisbane Hospital, QLD 4029, Brisbane, Australia
| | - Wojciech Branicki
- Malopolska Centre of Biotechnology, Jagiellonian University, Gronostajowa st. 7A, 30-387, Kraków, Poland
| | - Susan Walsh
- Department of Biology, Indiana University Purdue University Indianapolis (IUPUI), IN, USA
| | - Fan Liu
- Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beichen West Road 1-104, Chaoyang, Beijing, 100101, PR China; University of Chinese Academy of Sciences, 19 Yuquan Road, Shijingshan, Beijing, 100049, PR China; Department of Genetic Identification, Erasmus MC University Medical Center Rotterdam, P.O. Box 2040, 3000 CA, Rotterdam, Netherlands
| | - Manfred Kayser
- Department of Genetic Identification, Erasmus MC University Medical Center Rotterdam, P.O. Box 2040, 3000 CA, Rotterdam, Netherlands.
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Gonçalves GL, Maestri R, Moreira GRP, Jacobi MAM, Freitas TRO, Hoekstra HE. Divergent genetic mechanism leads to spiny hair in rodents. PLoS One 2018; 13:e0202219. [PMID: 30118524 PMCID: PMC6097693 DOI: 10.1371/journal.pone.0202219] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2018] [Accepted: 07/30/2018] [Indexed: 11/18/2022] Open
Abstract
Spines, or modified hairs, have evolved multiple times in mammals, particularly in rodents. In this study, we investigated the evolution of spines in six rodent families. We first measured and compared the morphology and physical properties of hairs between paired spiny and non-spiny sister lineages. We found two distinct hair morphologies had evolved repeatedly in spiny rodents: hairs with a grooved cross-section and a second near cylindrical form. Compared to the ancestral elliptical-shaped hairs, spiny hairs had higher tension and stiffness, and overall, hairs with similar morphology had similar functional properties. To examine the genetic basis of this convergent evolution, we tested whether a single amino acid change (V370A) in the Ectodysplasin A receptor (Edar) gene is associated with spiny hair, as this substitution causes thicker and straighter hair in East Asian human populations. We found that most mammals have the common amino acid valine at position 370, but two species, the kangaroo rat (non-spiny) and spiny pocket mouse (spiny), have an isoleucine. Importantly, none of the variants we identified are associated with differences in rodent hair morphology. Thus, the specific Edar mutation associated with variation in human hair does not seem to play a role in modifying hairs in wild rodents, suggesting that different mutations in Edar and/or other genes are responsible for variation in the spiny hair phenotypes we observed within rodents.
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Affiliation(s)
- Gislene L. Gonçalves
- Programa de Pós-Graduação em Genética e Biologia Molecular, Departamento de Genética, Instituto de Biociências, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
- Departamento de Recursos Ambientales, Facultad de Ciencias Agronómicas, Universidad de Tarapacá, Arica, Chile
| | - Renan Maestri
- Programa de Pós-Graduação em Biologia Animal, Departamento de Zoologia, Instituto de Biociências, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
- Departamento de Ecologia, Instituto de Biociências, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
| | - Gilson R. P. Moreira
- Programa de Pós-Graduação em Biologia Animal, Departamento de Zoologia, Instituto de Biociências, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
| | - Marly A. M. Jacobi
- Departamento de Química, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
| | - Thales R. O. Freitas
- Programa de Pós-Graduação em Genética e Biologia Molecular, Departamento de Genética, Instituto de Biociências, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
- Programa de Pós-Graduação em Biologia Animal, Departamento de Zoologia, Instituto de Biociências, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
| | - Hopi E. Hoekstra
- Department of Organismic & Evolutionary Biology, Department of Molecular & Cellular Biology, Museum of Comparative Zoology, Howard Hughes Medical Institute, Harvard University, Cambridge, MA, United States of America
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49
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Fujito NT, Satta Y, Hayakawa T, Takahata N. A new inference method for detecting an ongoing selective sweep. Genes Genet Syst 2018; 93:149-161. [DOI: 10.1266/ggs.18-00008] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Affiliation(s)
- Naoko T. Fujito
- School of Advanced Sciences, SOKENDAI (The Graduate University for Advanced Studies)
| | - Yoko Satta
- School of Advanced Sciences, SOKENDAI (The Graduate University for Advanced Studies)
| | - Toshiyuki Hayakawa
- Graduate School of Systems Life Sciences, Kyushu University
- Faculty of Arts and Science, Kyushu University
| | - Naoyuki Takahata
- School of Advanced Sciences, SOKENDAI (The Graduate University for Advanced Studies)
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Pośpiech E, Lee SD, Kukla-Bartoszek M, Karłowska-Pik J, Woźniak A, Boroń M, Zubańska M, Bronikowska A, Hong SR, Lee JH, Wojas-Pelc A, Lee HY, Spólnicka M, Branicki W. Variation in the RPTN gene may facilitate straight hair formation in Europeans and East Asians. J Dermatol Sci 2018; 91:331-334. [PMID: 29935789 DOI: 10.1016/j.jdermsci.2018.06.003] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2018] [Revised: 05/30/2018] [Accepted: 06/11/2018] [Indexed: 02/02/2023]
Affiliation(s)
- Ewelina Pośpiech
- Institute of Zoology and Biomedical Research, Faculty of Biology, Jagiellonian University, Gronostajowa St. 9, 30-387 Krakow, Poland; Malopolska Centre of Biotechnology of the Jagiellonian University, Gronostajowa St. 7A, 30-387 Krakow, Poland.
| | - Soong Deok Lee
- Department of Forensic Medicine, Seoul National University College of Medicine, 103 Daehak-ro (Yeongeon-dong), Jongno-gu, Seoul 03080, South Korea; Institute of Forensic Science, Seoul National University College of Medicine, 103 Daehak-ro (Yeongeon-dong), Jongno-gu, Seoul 03080, South Korea
| | - Magdalena Kukla-Bartoszek
- Faculty of Biochemistry, Biophysics and Biotechnology, Jagiellonian University, Gronostajowa St. 7, 30-387 Krakow, Poland
| | - Joanna Karłowska-Pik
- Faculty of Mathematics and Computer Science, Nicolaus Copernicus University, Chopina St. 12/18, 87-100 Torun, Poland
| | - Anna Woźniak
- Central Forensic Laboratory of the Police, Aleje Ujazdowskie 7, 00-583 Warsaw, Poland
| | - Michał Boroń
- Central Forensic Laboratory of the Police, Aleje Ujazdowskie 7, 00-583 Warsaw, Poland
| | - Magdalena Zubańska
- Unit of Forensic Sciences, Faculty of Internal Security, Police Academy, Marszałka Józefa Piłsudskiego St. 111, 12-100, Szczytno, Poland
| | - Agnieszka Bronikowska
- Department of Dermatology, Collegium Medicum of the Jagiellonian University, Skawinska St. 8, 31-066 Krakow, Poland
| | - Sae Rom Hong
- Department of Forensic Medicine, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul 03722, South Korea; Brain Korea 21 PLUS Project for Medical Science, Yonsei University, Seoul, South Korea
| | - Ji Hyun Lee
- Department of Forensic Medicine, Seoul National University College of Medicine, 103 Daehak-ro (Yeongeon-dong), Jongno-gu, Seoul 03080, South Korea
| | - Anna Wojas-Pelc
- Department of Dermatology, Collegium Medicum of the Jagiellonian University, Skawinska St. 8, 31-066 Krakow, Poland
| | - Hwan Young Lee
- Department of Forensic Medicine, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul 03722, South Korea
| | - Magdalena Spólnicka
- Central Forensic Laboratory of the Police, Aleje Ujazdowskie 7, 00-583 Warsaw, Poland
| | - Wojciech Branicki
- Malopolska Centre of Biotechnology of the Jagiellonian University, Gronostajowa St. 7A, 30-387, Krakow, Poland; Central Forensic Laboratory of the Police, Aleje Ujazdowskie 7, 00-583 Warsaw, Poland
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