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Lei C, Liu J, Zhang R, Pan Y, Lu Y, Gao Y, Ma X, Yang Y, Guan Y, Mamatyusupu D, Xu S. Ancestral Origins and Admixture History of Kazakhs. Mol Biol Evol 2024; 41:msae144. [PMID: 38995236 PMCID: PMC11272102 DOI: 10.1093/molbev/msae144] [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: 12/15/2023] [Revised: 04/29/2024] [Accepted: 07/02/2024] [Indexed: 07/13/2024] Open
Abstract
Kazakh people, like many other populations that settled in Central Asia, demonstrate an array of mixed anthropological features of East Eurasian (EEA) and West Eurasian (WEA) populations, indicating a possible scenario of biological admixture between already differentiated EEA and WEA populations. However, their complex biological origin, genomic makeup, and genetic interaction with surrounding populations are not well understood. To decipher their genetic structure and population history, we conducted, to our knowledge, the first whole-genome sequencing study of Kazakhs residing in Xinjiang (KZK). We demonstrated that KZK derived their ancestries from 4 ancestral source populations: East Asian (∼39.7%), West Asian (∼28.6%), Siberian (∼23.6%), and South Asian (∼8.1%). The recognizable interactions of EEA and WEA ancestries in Kazakhs were dated back to the 15th century BCE. Kazakhs were genetically distinctive from the Uyghurs in terms of their overall genomic makeup, although the 2 populations were closely related in genetics, and both showed a substantial admixture of western and eastern peoples. Notably, we identified a considerable sex-biased admixture, with an excess of western males and eastern females contributing to the KZK gene pool. We further identified a set of genes that showed remarkable differentiation in KZK from the surrounding populations, including those associated with skin color (SLC24A5, OCA2), essential hypertension (HLA-DQB1), hypertension (MTHFR, SLC35F3), and neuron development (CNTNAP2). These results advance our understanding of the complex history of contacts between Western and Eastern Eurasians, especially those living or along the old Silk Road.
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Affiliation(s)
- Chang Lei
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, School of Life Sciences, Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Jiaojiao Liu
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, School of Life Sciences, Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Rui Zhang
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Yuwen Pan
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Yan Lu
- Ministry of Education Key Laboratory of Contemporary Anthropology, Fudan University, Shanghai 201203, China
| | - Yang Gao
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, School of Life Sciences, Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Xixian Ma
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Yajun Yang
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, School of Life Sciences, Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Yaqun Guan
- Department of Biochemistry and Molecular Biology, Preclinical Medicine College, Xinjiang Medical University, Urumqi 830011, China
| | - Dolikun Mamatyusupu
- College of the Life Sciences and Technology, Xinjiang University, Urumqi 830046, China
| | - Shuhua Xu
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, School of Life Sciences, Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai 200032, China
- Ministry of Education Key Laboratory of Contemporary Anthropology, Fudan University, Shanghai 201203, China
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Feng Y, Xie N, Inoue F, Fan S, Saskin J, Zhang C, Zhang F, Hansen MEB, Nyambo T, Mpoloka SW, Mokone GG, Fokunang C, Belay G, Njamnshi AK, Marks MS, Oancea E, Ahituv N, Tishkoff SA. Integrative functional genomic analyses identify genetic variants influencing skin pigmentation in Africans. Nat Genet 2024; 56:258-272. [PMID: 38200130 PMCID: PMC11005318 DOI: 10.1038/s41588-023-01626-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Accepted: 11/28/2023] [Indexed: 01/12/2024]
Abstract
Skin color is highly variable in Africans, yet little is known about the underlying molecular mechanism. Here we applied massively parallel reporter assays to screen 1,157 candidate variants influencing skin pigmentation in Africans and identified 165 single-nucleotide polymorphisms showing differential regulatory activities between alleles. We combine Hi-C, genome editing and melanin assays to identify regulatory elements for MFSD12, HMG20B, OCA2, MITF, LEF1, TRPS1, BLOC1S6 and CYB561A3 that impact melanin levels in vitro and modulate human skin color. We found that independent mutations in an OCA2 enhancer contribute to the evolution of human skin color diversity and detect signals of local adaptation at enhancers of MITF, LEF1 and TRPS1, which may contribute to the light skin color of Khoesan-speaking populations from Southern Africa. Additionally, we identified CYB561A3 as a novel pigmentation regulator that impacts genes involved in oxidative phosphorylation and melanogenesis. These results provide insights into the mechanisms underlying human skin color diversity and adaptive evolution.
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Affiliation(s)
- Yuanqing Feng
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA
| | - Ning Xie
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA
| | - Fumitaka Inoue
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, USA
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA
- Institute for the Advanced Study of Human Biology (WPI-ASHBi), Kyoto University, Kyoto, Japan
| | - Shaohua Fan
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA
- Human Phenome Institute, School of Life Science, Fudan University, Shanghai, China
| | - Joshua Saskin
- Department of Neuroscience, Brown University, Providence, RI, USA
| | - Chao Zhang
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA
| | - Fang Zhang
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA
| | - Matthew E B Hansen
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA
| | - Thomas Nyambo
- Department of Biochemistry and Molecular Biology, Hubert Kairuki Memorial University, Dar es Salaam, Tanzania
| | - Sununguko Wata Mpoloka
- Department of Biological Sciences, Faculty of Sciences, University of Botswana, Gaborone, Botswana
| | | | - Charles Fokunang
- Department of Pharmacotoxicology and Pharmacokinetics, Faculty of Medicine and Biomedical Sciences, The University of Yaoundé I, Yaoundé, Cameroon
| | - Gurja Belay
- Department of Biology, Addis Ababa University, Addis Ababa, Ethiopia
| | - Alfred K Njamnshi
- Brain Research Africa Initiative (BRAIN); Neuroscience Lab, Faculty of Medicine and Biomedical Sciences, The University of Yaoundé I, Department of Neurology, Central Hospital Yaoundé, Yaoundé, Cameroon
| | - Michael S Marks
- Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia Research Institute, Philadelphia, PA, USA
| | - Elena Oancea
- Department of Neuroscience, Brown University, Providence, RI, USA
| | - Nadav Ahituv
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, USA
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA
| | - Sarah A Tishkoff
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Biology, University of Pennsylvania, Philadelphia, PA, USA.
- Center for Global Genomics and Health Equity, University of Pennsylvania, Philadelphia, PA, USA.
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Yang K, Zhang J, Zhao Y, Shao Y, Zhai M, Liu H, Zhang L. Whole Genome Resequencing Revealed the Genetic Relationship and Selected Regions among Baicheng-You, Beijing-You, and European-Origin Broilers. BIOLOGY 2023; 12:1397. [PMID: 37997996 PMCID: PMC10669838 DOI: 10.3390/biology12111397] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/30/2023] [Revised: 10/30/2023] [Accepted: 11/01/2023] [Indexed: 11/25/2023]
Abstract
As the only two You-chicken breeds in China, Baicheng-You (BCY) and Beijing-You (BJY) chickens are famous for their good meat quality. However, so far, the molecular basis of germplasm of the two You-chicken breeds is not yet clear. The genetic relationship among BCY, BJY, and European-origin broilers (BRs) was analyzed using whole genome resequencing data to contribute to this issue. A total of 18,852,372 single nucleotide polymorphisms (SNPs) were obtained in this study. After quality control, 8,207,242 SNPs were applied to subsequent analysis. The data indicated that BJY chickens possessed distant distance with BRs (genetic differentiation coefficient (FST) = 0.1681) and BCY (FST = 0.1231), respectively, while BCY and BRs had a closer relationship (FST = 0.0946). In addition, by using FST, cross-population extended haplotype homozygosity (XP-EHH), and cross-population composite likelihood ratio (XP-CLR) methods, we found 374 selected genes between BJY and BRs chickens and 279 selected genes between BCY and BJY chickens, respectively, which contained a number of important candidates or genetic variations associated with feather growth and fat deposition of BJY chickens and potential disease resistance of BCY chickens. Our study demonstrates a genome-wide view of genetic diversity and differentiation among BCY, BJY, and BRs. These results may provide useful information on a molecular basis related to the special characteristics of these broiler breeds, thus enabling us to better understand the formation mechanism of Chinese-You chickens.
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Affiliation(s)
- Kai Yang
- College of Animal Science and Technology, Nanjing Agricultural University, Nanjing 210095, China; (K.Y.); (Y.Z.)
| | - Jian Zhang
- Institute of Animal Husbandry and Veterinary Medicine, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China; (J.Z.); (H.L.)
| | - Yuelei Zhao
- College of Animal Science and Technology, Nanjing Agricultural University, Nanjing 210095, China; (K.Y.); (Y.Z.)
| | - Yonggang Shao
- College of Animal Science, Xinjiang Agricultural University, Urumqi 830052, China; (Y.S.); (M.Z.)
| | - Manjun Zhai
- College of Animal Science, Xinjiang Agricultural University, Urumqi 830052, China; (Y.S.); (M.Z.)
| | - Huagui Liu
- Institute of Animal Husbandry and Veterinary Medicine, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China; (J.Z.); (H.L.)
| | - Lifan Zhang
- College of Animal Science and Technology, Nanjing Agricultural University, Nanjing 210095, China; (K.Y.); (Y.Z.)
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Peng Q, Liu Y, Huels A, Zhang C, Yu Y, Qiu W, Cai X, Zhao Y, Schikowski T, Merches K, Liu Y, Yang Y, Wang J, Zhao Y, Jin L, Zhang L, Krutmann J, Wang S. Genetic Variants in Telomerase Reverse Transcriptase Contribute to Solar Lentigines. J Invest Dermatol 2023; 143:1062-1072.e25. [PMID: 36572090 DOI: 10.1016/j.jid.2022.11.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Revised: 10/01/2022] [Accepted: 11/11/2022] [Indexed: 12/26/2022]
Abstract
Solar lentigines (SLs) are a hallmark of human skin aging. They result from chronic exposure to sunlight and other environmental stressors. Recent studies also imply genetic factors, but findings are partially conflicting and lack of replication. Through a multi-trait based analysis strategy, we discovered that genetic variants in telomerase reverse transcriptase were significantly associated with non-facial SL in two East Asian (Taizhou longitudinal cohort, n = 2,964 and National Survey of Physical Traits, n = 2,954) and one Caucasian population (SALIA, n = 462), top SNP rs2853672 (P-value for Taizhou longitudinal cohort = 1.32 × 10‒28 and P-value for National Survey of Physical Traits = 3.66 × 10‒17 and P-value for SALIA = 0.0007 and Pmeta = 4.93 × 10‒44). The same variants were nominally associated with facial SL but not with other skin aging or skin pigmentation traits. The SL-enhanced allele/haplotype upregulated the transcription of the telomerase reverse transcriptase gene. Of note, well-known telomerase reverse transcriptase‒related aging markers such as leukocyte telomere length and intrinsic epigenetic age acceleration were not associated with SL. Our results indicate a previously unrecognized role of telomerase reverse transcriptase in skin aging‒related lentigines formation.
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Affiliation(s)
- Qianqian Peng
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Yu Liu
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Anke Huels
- IUF - Leibniz Research Institute for Environmental Medicine, Düsseldorf, Germany; Faculty of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, Georgia, USA
| | - Canfeng Zhang
- Scientific Research Center, The Seventh Affiliated Hospital, Sun Yat-Sen University, Shenzhen, China
| | - Yao Yu
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China; CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Wenqing Qiu
- MOE Key Laboratory of Metabolism and Molecular Medicine, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Fudan University, Shanghai, China
| | - Xiyang Cai
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Yuepu Zhao
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Tamara Schikowski
- IUF - Leibniz Research Institute for Environmental Medicine, Düsseldorf, Germany
| | - Katja Merches
- IUF - Leibniz Research Institute for Environmental Medicine, Düsseldorf, Germany
| | - Yun Liu
- MOE Key Laboratory of Metabolism and Molecular Medicine, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Fudan University, Shanghai, China
| | - Yajun Yang
- State Key Laboratory of Genetic Engineering, Collaborative Innovation Center for Genetics and Development, Human Phenome Institute, Fudan University, Shanghai, China; Ministry of Education Key Laboratory of Contemporary Anthropology, Department of Anthropology and Human Genetics, School of Life Sciences, Fudan University, Shanghai, China
| | - Jiucun Wang
- State Key Laboratory of Genetic Engineering, Collaborative Innovation Center for Genetics and Development, Human Phenome Institute, Fudan University, Shanghai, China; Ministry of Education Key Laboratory of Contemporary Anthropology, Department of Anthropology and Human Genetics, School of Life Sciences, Fudan University, Shanghai, China
| | - Yong Zhao
- Key Laboratory of Gene Engineering of the Ministry of Education, School of Life Sciences, Sun Yat-sen University, Guangzhou, China
| | - Li Jin
- State Key Laboratory of Genetic Engineering, Collaborative Innovation Center for Genetics and Development, Human Phenome Institute, Fudan University, Shanghai, China; Ministry of Education Key Laboratory of Contemporary Anthropology, Department of Anthropology and Human Genetics, School of Life Sciences, Fudan University, Shanghai, China
| | - Liang Zhang
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China; Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, China; Department of Plastic and Reconstructive Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jean Krutmann
- IUF - Leibniz Research Institute for Environmental Medicine, Düsseldorf, Germany; State Key Laboratory of Genetic Engineering, Collaborative Innovation Center for Genetics and Development, Human Phenome Institute, Fudan University, Shanghai, China; Medical Faculty, Heinrich-Heine-University, Düsseldorf, Germany
| | - Sijia Wang
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China; Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, China.
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5
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Zheng W, He Y, Guo Y, Yue T, Zhang H, Li J, Zhou B, Zeng X, Li L, Wang B, Cao J, Chen L, Li C, Li H, Cui C, Bai C, Baimakangzhuo, Qi X, Ouzhuluobu, Su B. Large-scale genome sequencing redefines the genetic footprints of high-altitude adaptation in Tibetans. Genome Biol 2023; 24:73. [PMID: 37055782 PMCID: PMC10099689 DOI: 10.1186/s13059-023-02912-1] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Accepted: 03/29/2023] [Indexed: 04/15/2023] Open
Abstract
BACKGROUND Tibetans are genetically adapted to high-altitude environments. Though many studies have been conducted, the genetic basis of the adaptation remains elusive due to the poor reproducibility for detecting selective signatures in the Tibetan genomes. RESULTS Here, we present whole-genome sequencing (WGS) data of 1001 indigenous Tibetans, covering the major populated areas of the Qinghai-Tibetan Plateau in China. We identify 35 million variants, and more than one-third of them are novel variants. Utilizing the large-scale WGS data, we construct a comprehensive map of allele frequency and linkage disequilibrium and provide a population-specific genome reference panel, referred to as 1KTGP. Moreover, with the use of a combined approach, we redefine the signatures of Darwinian-positive selection in the Tibetan genomes, and we characterize a high-confidence list of 4320 variants and 192 genes that have undergone selection in Tibetans. In particular, we discover four new genes, TMEM132C, ATP13A3, SANBR, and KHDRBS2, with strong signals of selection, and they may account for the adaptation of cardio-pulmonary functions in Tibetans. Functional annotation and enrichment analysis indicate that the 192 genes with selective signatures are likely involved in multiple organs and physiological systems, suggesting polygenic and pleiotropic effects. CONCLUSIONS Overall, the large-scale Tibetan WGS data and the identified adaptive variants/genes can serve as a valuable resource for future genetic and medical studies of high-altitude populations.
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Affiliation(s)
- Wangshan Zheng
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Beijing, 100101, China
| | - Yaoxi He
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
| | - Yongbo Guo
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Beijing, 100101, China
| | - Tian Yue
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Beijing, 100101, China
| | - Hui Zhang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
| | - Jun Li
- Fukang Obstetrics, Gynecology and Children Branch Hospital, Tibetan Fukang Hospital, Lhasa, 850000, China
| | - Bin Zhou
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Beijing, 100101, China
| | - Xuerui Zeng
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Beijing, 100101, China
| | - Liya Li
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
| | - Bin Wang
- Fukang Obstetrics, Gynecology and Children Branch Hospital, Tibetan Fukang Hospital, Lhasa, 850000, China
| | - Jingxin Cao
- Fukang Obstetrics, Gynecology and Children Branch Hospital, Tibetan Fukang Hospital, Lhasa, 850000, China
| | - Li Chen
- Fukang Obstetrics, Gynecology and Children Branch Hospital, Tibetan Fukang Hospital, Lhasa, 850000, China
| | - Chunxia Li
- Fukang Obstetrics, Gynecology and Children Branch Hospital, Tibetan Fukang Hospital, Lhasa, 850000, China
| | - Hongyan Li
- Fukang Obstetrics, Gynecology and Children Branch Hospital, Tibetan Fukang Hospital, Lhasa, 850000, China
| | - Chaoying Cui
- High Altitude Medical Research Center, School of Medicine, Tibetan University, Lhasa, 850000, China
| | - Caijuan Bai
- High Altitude Medical Research Center, School of Medicine, Tibetan University, Lhasa, 850000, China
| | - Baimakangzhuo
- High Altitude Medical Research Center, School of Medicine, Tibetan University, Lhasa, 850000, China
| | - Xuebin Qi
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China.
- Fukang Obstetrics, Gynecology and Children Branch Hospital, Tibetan Fukang Hospital, Lhasa, 850000, China.
| | - Ouzhuluobu
- Fukang Obstetrics, Gynecology and Children Branch Hospital, Tibetan Fukang Hospital, Lhasa, 850000, China.
- High Altitude Medical Research Center, School of Medicine, Tibetan University, Lhasa, 850000, China.
| | - Bing Su
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China.
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, 650223, China.
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6
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Amano S, Yoshikawa T, Ito C, Mabuchi I, Kikuchi K, Ooguri M, Yasuda C. Prediction and association analyses of skin phenotypes in Japanese females using genetic, environmental, and physical features. Skin Res Technol 2023; 29:e13231. [PMID: 36437544 PMCID: PMC9838785 DOI: 10.1111/srt.13231] [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: 01/19/2022] [Accepted: 10/15/2022] [Indexed: 11/29/2022]
Abstract
BACKGROUND Skin characteristics show great variation from person to person and are affected by multiple factors, including genetic, environmental, and physical factors, but details of the involvement and contributions of these factors remain unclear. OBJECTIVES We aimed to characterize genetic, environmental, and physical factors affecting 16 skin features by developing models to predict personal skin characteristics. METHODS We analyzed the associations of skin phenotypes with genetic, environmental, and physical features in 1472 Japanese females aged 20-80 years. We focused on 16 skin characteristics, including melanin, brightness/lightness, yellowness, pigmented spots, wrinkles, resilience, moisture, barrier function, texture, and sebum amount. As genetic factors, we selected 74 single-nucleotide polymorphisms of genes related to skin color, vitamin level, hormones, circulation, extracellular matrix (ECM) components and ECM-degrading enzymes, inflammation, and antioxidants. Histories of ultraviolet (UV) exposure and smoking as environmental factors and age, height, and weight as physical factors were acquired by means of a questionnaire. RESULTS A linear association with age was prominent for increase in the area of crow's feet, increase in number of pigmented spots, decrease in forehead sebum, and increase in VISIA wrinkle parameters. Associations were analyzed by constructing linear regression models for skin feature changes and logistic regression models to predict whether subjects show lower or higher skin measurement values in the same age groups. Multiple genetic factors, history of UV exposure and smoking, and body mass index were statistically selected for each skin characteristic. The most important association found for skin spots, such as lentigines and wrinkles, was adolescent sun exposure. CONCLUSION Genetic, environmental, and physical factors associated with interindividual differences of the selected skin features were identified. The developed models should be useful to predict the skin characteristics of individuals and their age-related changes.
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Affiliation(s)
- Satoshi Amano
- Shiseido Co. Ltd., MIRAI Technology Institute, Yokohama, Kanagawa, Japan
| | - Tatsuya Yoshikawa
- Shiseido Co. Ltd., MIRAI Technology Institute, Yokohama, Kanagawa, Japan
| | - Chiaki Ito
- DYNACOM Co. Ltd., World Business Garden, Mihama-ku, Chiba, Japan
| | - Ikumi Mabuchi
- DYNACOM Co. Ltd., World Business Garden, Mihama-ku, Chiba, Japan
| | - Kumiko Kikuchi
- Shiseido Co. Ltd., MIRAI Technology Institute, Yokohama, Kanagawa, Japan
| | - Motoki Ooguri
- Shiseido Co. Ltd., MIRAI Technology Institute, Yokohama, Kanagawa, Japan
| | - Chie Yasuda
- Shiseido Co. Ltd., MIRAI Technology Institute, Yokohama, Kanagawa, Japan
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7
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Pan Y, Zhang C, Lu Y, Ning Z, Lu D, Gao Y, Zhao X, Yang Y, Guan Y, Mamatyusupu D, Xu S. Genomic diversity and post-admixture adaptation in the Uyghurs. Natl Sci Rev 2022; 9:nwab124. [PMID: 35350227 PMCID: PMC8953455 DOI: 10.1093/nsr/nwab124] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2021] [Revised: 05/30/2021] [Accepted: 06/07/2021] [Indexed: 11/17/2022] Open
Abstract
Population admixture results in genome-wide combinations of genetic variants derived from different ancestral populations of distinct ancestry, thus providing a unique opportunity for understanding the genetic determinants of phenotypic variation in humans. Here, we used whole-genome sequencing of 92 individuals with high coverage (30–60×) to systematically investigate genomic diversity in the Uyghurs living in Xinjiang, China (XJU), an admixed population of both European-like and East-Asian-like ancestry. The XJU population shows greater genetic diversity, especially a higher proportion of rare variants, compared with their ancestral source populations, corresponding to greater phenotypic diversity of XJU. Admixture-induced functional variants in EDAR were associated with the diversity of facial morphology in XJU. Interestingly, the interaction of functional variants between SLC24A5 and OCA2 likely influences the diversity of skin pigmentation. Notably, selection has seemingly been relaxed or canceled in several genes with significantly biased ancestry, such as HERC2–OCA2. Moreover, signatures of post-admixture adaptation in XJU were identified, including genes related to metabolism (e.g. CYP2D6), digestion (e.g. COL11A1), olfactory perception (e.g. ANO2) and immunity (e.g. HLA). Our results demonstrated population admixture as a driving force, locally or globally, in shaping human genetic and phenotypic diversity as well as in adaptive evolution.
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Affiliation(s)
- Yuwen Pan
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences , Shanghai 200031, China
| | - Chao Zhang
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences , Shanghai 200031, China
| | - Yan Lu
- State Key Laboratory of Genetic Engineering and Ministry of Education (MOE) Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University , Shanghai 200438, China
| | - Zhilin Ning
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences , Shanghai 200031, China
| | - Dongsheng Lu
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences , Shanghai 200031, China
| | - Yang Gao
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences , Shanghai 200031, China
- School of Life Science and Technology, ShanghaiTech University , Shanghai 201210, China
| | - Xiaohan Zhao
- Human Phenome Institute, Fudan University , Shanghai 201203, China
| | - Yajun Yang
- State Key Laboratory of Genetic Engineering and Ministry of Education (MOE) Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University , Shanghai 200438, China
| | - Yaqun Guan
- Department of Biochemistry and Molecular Biology, Preclinical Medicine College, Xinjiang Medical University , Urumqi 830011, China
| | - Dolikun Mamatyusupu
- College of the Life Sciences and Technology, Xinjiang University , Urumqi 830046, China
| | - Shuhua Xu
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences , Shanghai 200031, China
- State Key Laboratory of Genetic Engineering and Ministry of Education (MOE) Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University , Shanghai 200438, China
- School of Life Science and Technology, ShanghaiTech University , Shanghai 201210, China
- Human Phenome Institute, Fudan University , Shanghai 201203, China
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences , Kunming 650223, China
- Henan Institute of Medical and Pharmaceutical Sciences, Zhengzhou University , Zhengzhou 450052, China
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8
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GWAS Identifies Multiple Genetic Loci for Skin Color in Korean Women. J Invest Dermatol 2021; 142:1077-1084. [PMID: 34648798 DOI: 10.1016/j.jid.2021.08.440] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2021] [Revised: 08/11/2021] [Accepted: 08/13/2021] [Indexed: 12/29/2022]
Abstract
Human skin color is largely determined by genetic factors. Recent GWASs have reported several genetic variants associated with skin color, mostly in European and African populations. In this study, we performed GWAS in 17,019 Korean women to identify genetic variants associated with facial skin color, quantitatively measured as CIELAB color index. We identified variants in three, one, and six genomic loci associated with facial skin color index L∗, a∗, and b∗ values, respectively, and replicated the associations (combined analysis P-value < 5.0 × 10-8). The significant loci included variants in known genes (OCA2 rs74653330, BNC2 rs16935073, rs72620727 near KITLG, and SLC6A17 rs6689641) and to our knowledge previously unreported genes (SCARB1 rs10846744, SYN2 rs12629034, and LINC00486 rs6543678). This is GWAS to elucidate genetic variants of facial skin color in a Korean female population. Further functional characterizations of the investigated genes are warranted to elucidate their contribution to skin pigmentation-related traits.
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9
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A Genome-Wide Scan on Individual Typology Angle Found Variants at SLC24A2 Associated with Skin Color Variation in Chinese Populations. J Invest Dermatol 2021; 142:1223-1227.e14. [PMID: 34570997 DOI: 10.1016/j.jid.2021.07.186] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2020] [Revised: 07/01/2021] [Accepted: 07/09/2021] [Indexed: 11/21/2022]
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10
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Wang F, Luo Q, Chen Y, Liu Y, Xu K, Adhikari K, Cai X, Liu J, Li Y, Liu X, Ramirez-Aristeguieta LM, Yuan Z, Zhou Y, Li FF, Jiang B, Jin L, Ruiz-Linares A, Yang Z, Liu F, Wang S. A Genome-Wide Scan on Individual Typology Angle Found Variants at SLC24A2 Associated with Skin Color Variation in Chinese Populations. J Invest Dermatol 2021. [DOI: https://doi.org/10.1016/j.jid.2021.07.186] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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11
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Palmal S, Adhikari K, Mendoza-Revilla J, Fuentes-Guajardo M, Silva de Cerqueira CC, Bonfante B, Chacón-Duque JC, Sohail A, Hurtado M, Villegas V, Granja V, Jaramillo C, Arias W, Lozano RB, Everardo-Martínez P, Gómez-Valdés J, Villamil-Ramírez H, Hünemeier T, Ramallo V, Parolin ML, Gonzalez-José R, Schüler-Faccini L, Bortolini MC, Acuña-Alonzo V, Canizales-Quinteros S, Gallo C, Poletti G, Bedoya G, Rothhammer F, Balding D, Faux P, Ruiz-Linares A. Prediction of eye, hair and skin colour in Latin Americans. Forensic Sci Int Genet 2021; 53:102517. [PMID: 33865096 DOI: 10.1016/j.fsigen.2021.102517] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Revised: 03/19/2021] [Accepted: 03/30/2021] [Indexed: 10/21/2022]
Abstract
Here we evaluate the accuracy of prediction for eye, hair and skin pigmentation in a dataset of > 6500 individuals from Mexico, Colombia, Peru, Chile and Brazil (including genome-wide SNP data and quantitative/categorical pigmentation phenotypes - the CANDELA dataset CAN). We evaluated accuracy in relation to different analytical methods and various phenotypic predictors. As expected from statistical principles, we observe that quantitative traits are more sensitive to changes in the prediction models than categorical traits. We find that Random Forest or Linear Regression are generally the best performing methods. We also compare the prediction accuracy of SNP sets defined in the CAN dataset (including 56, 101 and 120 SNPs for eye, hair and skin colour prediction, respectively) to the well-established HIrisPlex-S SNP set (including 6, 22 and 36 SNPs for eye, hair and skin colour prediction respectively). When training prediction models on the CAN data, we observe remarkably similar performances for HIrisPlex-S and the larger CAN SNP sets for the prediction of hair (categorical) and eye (both categorical and quantitative), while the CAN sets outperform HIrisPlex-S for quantitative, but not for categorical skin pigmentation prediction. The performance of HIrisPlex-S, when models are trained in a world-wide sample (although consisting of 80% Europeans, https://hirisplex.erasmusmc.nl), is lower relative to training in the CAN data (particularly for hair and skin colour). Altogether, our observations are consistent with common variation of eye and hair colour having a relatively simple genetic architecture, which is well captured by HIrisPlex-S, even in admixed Latin Americans (with partial European ancestry). By contrast, since skin pigmentation is a more polygenic trait, accuracy is more sensitive to prediction SNP set size, although here this effect was only apparent for a quantitative measure of skin pigmentation. Our results support the use of HIrisPlex-S in the prediction of categorical pigmentation traits for forensic purposes in Latin America, while illustrating the impact of training datasets on its accuracy.
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Affiliation(s)
- Sagnik Palmal
- UMR 7268 ADES, CNRS, Aix-Marseille Université, EFS, Faculté de Médecine Timone, Marseille 13005, France
| | - Kaustubh Adhikari
- School of Mathematics and Statistics, Faculty of Science, Technology, Engineering and Mathematics, The Open University, Milton Keynes MK7 6AA, UK; Department of Genetics, Evolution and Environment, and UCL Genetics Institute, University College London, London WC1E 6BT, UK
| | - Javier Mendoza-Revilla
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima 31, Perú; Unit of Human Evolutionary Genetics, Institut Pasteur, Paris 75015, France
| | - Macarena Fuentes-Guajardo
- Departamento de Tecnología Médica, Facultad de Ciencias de la Salud, Universidad de Tarapacá, Arica 1000000, Chile
| | | | - Betty Bonfante
- UMR 7268 ADES, CNRS, Aix-Marseille Université, EFS, Faculté de Médecine Timone, Marseille 13005, France
| | - Juan Camilo Chacón-Duque
- Division of Vertebrates and Anthropology, Department of Earth Sciences, Natural History Museum, London SW7 5BD, UK
| | - Anood Sohail
- Department of Biotechnology, Kinnaird College for Women, 93 - Jail Road, Lahore 54000, Pakistan
| | - Malena Hurtado
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima 31, Perú
| | - Valeria Villegas
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima 31, Perú
| | - Vanessa Granja
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima 31, Perú
| | - Claudia Jaramillo
- Department of Biotechnology, Kinnaird College for Women, 93 - Jail Road, Lahore 54000, Pakistan; GENMOL (Genética Molecular), Universidad de Antioquia, Medellín 5001000, Colombia
| | - William Arias
- GENMOL (Genética Molecular), Universidad de Antioquia, Medellín 5001000, Colombia
| | - Rodrigo Barquera Lozano
- National Institute of Anthropology and History, Mexico City 6600, Mexico; Department of Archaeogenetics, Max Planck Institute for the Science of Human History (MPI-SHH), Jena 07745, Germany
| | | | - Jorge Gómez-Valdés
- National Institute of Anthropology and History, Mexico City 6600, Mexico
| | - Hugo Villamil-Ramírez
- Unidad de Genomica de Poblaciones Aplicada a la Salud, Facultad de Química, UNAM-Instituto Nacional de Medicina Genómica, Mexico City 4510, Mexico
| | - Tábita Hünemeier
- Departamento de Genética e Biologia Evolutiva, Instituto de Biociências, Universidade de São Paulo, São Paulo, SP 05508-090, Brazil
| | - Virginia Ramallo
- Departamento de Genética, Universidade Federal do Rio Grande do Sul, Porto Alegre 90040-060, Brazil; Instituto Patagónico de Ciencias Sociales y Humanas, Centro Nacional Patagónico, CONICET, Puerto Madryn U9129ACD, Argentina
| | - Maria-Laura Parolin
- Instituto de Diversidad y Evolución Austral (IDEAus), Centro Nacional Patagónico, CONICET, Puerto Madryn, Argentina
| | - Rolando Gonzalez-José
- Instituto Patagónico de Ciencias Sociales y Humanas, Centro Nacional Patagónico, CONICET, Puerto Madryn U9129ACD, Argentina
| | - Lavinia Schüler-Faccini
- Departamento de Genética, Universidade Federal do Rio Grande do Sul, Porto Alegre 90040-060, Brazil
| | - Maria-Cátira Bortolini
- Departamento de Genética, Universidade Federal do Rio Grande do Sul, Porto Alegre 90040-060, Brazil
| | | | - Samuel Canizales-Quinteros
- Unidad de Genomica de Poblaciones Aplicada a la Salud, Facultad de Química, UNAM-Instituto Nacional de Medicina Genómica, Mexico City 4510, Mexico
| | - Carla Gallo
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima 31, Perú
| | - Giovanni Poletti
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima 31, Perú
| | - Gabriel Bedoya
- GENMOL (Genética Molecular), Universidad de Antioquia, Medellín 5001000, Colombia
| | - Francisco Rothhammer
- Instituto de Alta Investigación, Universidad de Tarapacá, Arica 1000000, Chile; Programa de Genetica Humana, ICBM, Facultad de Medicina, Universidad de Chile, Santiago, Arica 1000000, Chile
| | - David Balding
- Department of Genetics, Evolution and Environment, and UCL Genetics Institute, University College London, London WC1E 6BT, UK; Melbourne Integrative Genomics, Schools of BioSciences and Mathematics & Statistics, University of Melbourne, Melbourne, VIC 3010, Australia
| | - Pierre Faux
- UMR 7268 ADES, CNRS, Aix-Marseille Université, EFS, Faculté de Médecine Timone, Marseille 13005, France.
| | - Andrés Ruiz-Linares
- UMR 7268 ADES, CNRS, Aix-Marseille Université, EFS, Faculté de Médecine Timone, Marseille 13005, France; Department of Genetics, Evolution and Environment, and UCL Genetics Institute, University College London, London WC1E 6BT, UK; Ministry of Education Key Laboratory of Contemporary Anthropology and Collaborative Innovation Center of Genetics and Development, School of Life Sciences and Human Phenome Institute, Fudan University, Yangpu District, Shanghai, China.
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12
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Feng Z, Duren Z, Xiong Z, Wang S, Liu F, Wong WH, Wang Y. hReg-CNCC reconstructs a regulatory network in human cranial neural crest cells and annotates variants in a developmental context. Commun Biol 2021; 4:442. [PMID: 33824393 PMCID: PMC8024315 DOI: 10.1038/s42003-021-01970-0] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2020] [Accepted: 03/09/2021] [Indexed: 12/19/2022] Open
Abstract
Cranial Neural Crest Cells (CNCC) originate at the cephalic region from forebrain, midbrain and hindbrain, migrate into the developing craniofacial region, and subsequently differentiate into multiple cell types. The entire specification, delamination, migration, and differentiation process is highly regulated and abnormalities during this craniofacial development cause birth defects. To better understand the molecular networks underlying CNCC, we integrate paired gene expression & chromatin accessibility data and reconstruct the genome-wide human Regulatory network of CNCC (hReg-CNCC). Consensus optimization predicts high-quality regulations and reveals the architecture of upstream, core, and downstream transcription factors that are associated with functions of neural plate border, specification, and migration. hReg-CNCC allows us to annotate genetic variants of human facial GWAS and disease traits with associated cis-regulatory modules, transcription factors, and target genes. For example, we reveal the distal and combinatorial regulation of multiple SNPs to core TF ALX1 and associations to facial distances and cranial rare disease. In addition, hReg-CNCC connects the DNA sequence differences in evolution, such as ultra-conserved elements and human accelerated regions, with gene expression and phenotype. hReg-CNCC provides a valuable resource to interpret genetic variants as early as gastrulation during embryonic development. The network resources are available at https://github.com/AMSSwanglab/hReg-CNCC .
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Affiliation(s)
- Zhanying Feng
- CEMS, NCMIS, MDIS, Academy of Mathematics and Systems Science, National Center for Mathematics and Interdisciplinary Sciences, Chinese Academy of Sciences, Beijing, China.,School of Mathematics, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Beijing, China
| | - Zhana Duren
- Center for Human Genetics, Department of Genetics and Biochemistry, Clemson University, Greenwood, SC, USA.,Department of Statistics, Department of Biomedical Data Science, Bio-X Program, Stanford University, Stanford, CA, USA
| | - Ziyi Xiong
- Department of Genetic Identification, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands.,Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands.,CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China
| | - Sijia Wang
- Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China.,Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, China
| | - Fan Liu
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China. .,China National Center for Bioinformation, Chinese Academy of Sciences, Beijing, China.
| | - Wing Hung Wong
- Department of Statistics, Department of Biomedical Data Science, Bio-X Program, Stanford University, Stanford, CA, USA.
| | - Yong Wang
- CEMS, NCMIS, MDIS, Academy of Mathematics and Systems Science, National Center for Mathematics and Interdisciplinary Sciences, Chinese Academy of Sciences, Beijing, China. .,School of Mathematics, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Beijing, China. .,Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, China. .,Key Laboratory of Systems Biology, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Hangzhou, China.
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13
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Norton HL. The color of normal: How a Eurocentric focus erases pigmentation complexity. Am J Hum Biol 2020; 33:e23554. [PMID: 33337560 DOI: 10.1002/ajhb.23554] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2020] [Revised: 12/03/2020] [Accepted: 12/06/2020] [Indexed: 11/06/2022] Open
Abstract
OBJECTIVES Skin pigmentation is both a highly variable and highly visible human phenotypic trait. Investigations into the biology and origins of this variation have been the focus of research in the fields of dermatology, anthropology, and forensic science, among others. This manuscript explores how much of what we know about the biology, genetics, and evolutionary origins of pigmentation has been strongly influenced by investigations and applications that focus on lighter skin. METHODS I reviewed literature from the fields of dermatology, anthropology and evolutionary genetics, and forensic science to assess how perceptions of lighter skin as the "normal" state in humans can shape the ways that knowledge is gathered and applied in these fields. RESULTS This normalization of lighter skin has impacted common tools used in dermatology and shaped the framework of dermatological education. A strong Eurocentric bias has shaped our understanding of the genetic architecture of pigmentary traits, which influences the ways in we understand the evolutionary processes leading to modern pigmentation diversity. Finally, I discuss how these biases in pigmentation genetics work in combination with phenotypic systems that privilege predicting lighter pigmentation variation to impede accurate prediction of intermediate phenotypes, particularly in individuals with ancestry from multiple populations. This can lead to a disproportionate targeting of already over-policed populations with darker skin. CONCLUSIONS Potential changes to how we conceptualize clinical and basic pigmentation research may help to reduce existing health disparities and improve understanding of pigmentation genetic architecture and how this knowledge is applied in forensic contexts.
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Affiliation(s)
- Heather L Norton
- Department of Anthropology, University of Cincinnati, Cincinnati, Ohio, USA
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14
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Kidd KK, Pakstis AJ, Donnelly MP, Bulbul O, Cherni L, Gurkan C, Kang L, Li H, Yun L, Paschou P, Meiklejohn KA, Haigh E, Speed WC. The distinctive geographic patterns of common pigmentation variants at the OCA2 gene. Sci Rep 2020; 10:15433. [PMID: 32963319 PMCID: PMC7508881 DOI: 10.1038/s41598-020-72262-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2020] [Accepted: 08/17/2020] [Indexed: 11/25/2022] Open
Abstract
Oculocutaneous Albinism type 2 (OCA2) is a gene of great interest because of genetic variation affecting normal pigmentation variation in humans. The diverse geographic patterns for variant frequencies at OCA2 have been evident but have not been systematically investigated, especially outside of Europe. Here we examine population genetic variation in and near the OCA2 gene from a worldwide perspective. The very different patterns of genetic variation found across world regions suggest strong selection effects may have been at work over time. For example, analyses involving the variants that affect pigmentation of the iris argue that the derived allele of the rs1800407 single nucleotide polymorphism, which produces a hypomorphic protein, may have contributed to the previously demonstrated positive selection in Europe for the enhancer variant responsible for light eye color. More study is needed on the relationships of the genetic variation at OCA2 to variation in pigmentation in areas beyond Europe.
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Affiliation(s)
- Kenneth K Kidd
- Professor Emeritus, Department of Genetics, Yale University School of Medicine, P.O. Box 208005, New Haven, CT, 06520-8005, USA.
| | - Andrew J Pakstis
- Professor Emeritus, Department of Genetics, Yale University School of Medicine, P.O. Box 208005, New Haven, CT, 06520-8005, USA
| | - Michael P Donnelly
- Professor Emeritus, Department of Genetics, Yale University School of Medicine, P.O. Box 208005, New Haven, CT, 06520-8005, USA.,Biological and Environmental Sciences, Troy University, Dothan, AL, 36303, USA
| | - Ozlem Bulbul
- Institute of Forensic Science, Istanbul University-Cerrahpasa, Istanbul, 34500, Turkey
| | - Lotfi Cherni
- Laboratory of Genetics, Immunology and Human Pathologies, Faculty of Sciences of Tunis, University of Tunis El Manar, 2092, Tunis, Tunisia.,Higher Institute of Biotechnology of Monastir, Monastir University, 5000, Monastir, Tunisia
| | - Cemal Gurkan
- Turkish Cypriot DNA Laboratory, Committee on Missing Persons in Cyprus Turkish Cypriot Member Office, Nicosia, North Cyprus), Turkey.,Dr. Fazıl Küçük Faculty of Medicine, Eastern Mediterranean University, Famagusta (North Cyprus), Turkey
| | - Longli Kang
- Key Laboratory forMolecular GeneticMechanisms and Intervention Research On High Altitude Disease of Tibet Autonomous Region, School of Medicine, Xizang Minzu University, Xianyang, 712082, Shaanxi, China.,Key Laboratory of High Altitude Environment and Genes Related To Disease of Tibet Ministry of Education, School of Medicine, Xizang Minzu University, Xianyang, 712082, Shaanxi, China
| | - Hui Li
- MOE State Key Laboratory of Contemporary Anthropology, School of Life Sciences, Fudan University, Shanghai, China
| | - Libing Yun
- Institute of Forensic Medicine, West China College of Preclinical and Forensic Medicine, Sichuan University, No.16. Section 3. RenMin Nan Road, Chengdu, 610041, Sichuan, China
| | - Peristera Paschou
- Department of Biological Sciences, Purdue University, West Lafayette, IN, USA
| | - Kelly A Meiklejohn
- Department of Population Health and Pathobiology, North Carolina State University, 1060 William Moore Drive, Raleigh, NC, 27607, USA
| | - Eva Haigh
- Professor Emeritus, Department of Genetics, Yale University School of Medicine, P.O. Box 208005, New Haven, CT, 06520-8005, USA
| | - William C Speed
- Professor Emeritus, Department of Genetics, Yale University School of Medicine, P.O. Box 208005, New Haven, CT, 06520-8005, USA
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15
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Yang Z, Shi H, Ma P, Zhao S, Kong Q, Bian T, Gong C, Zhao Q, Liu Y, Qi X, Zhang X, Han Y, Liu J, Li Q, Chen H, Su B. Darwinian Positive Selection on the Pleiotropic Effects of KITLG Explain Skin Pigmentation and Winter Temperature Adaptation in Eurasians. Mol Biol Evol 2020; 35:2272-2283. [PMID: 29961894 DOI: 10.1093/molbev/msy136] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Human skin color diversity is considered an adaptation to environmental conditions such as UV radiation. Investigations into the genetic bases of such adaptation have identified a group of pigmentation genes contributing to skin color diversity in African and non-African populations. Here, we present a population analysis of the pigmentation gene KITLG with previously reported signal of Darwinian positive selection in both European and East Asian populations. We demonstrated that there had been recurrent selective events in the upstream and the downstream regions of KITLG in Eurasian populations. More importantly, besides the expected selection on the KITLG variants favoring light skin in coping with the weak UV radiation at high latitude, we observed a KITLG variant showing adaptation to winter temperature. In particular, compared with UV radiation, winter temperature showed a much stronger correlation with the prevalence of the presumably adaptive KITLG allele in Asian populations. This observation was further supported by the in vitro functional test at low temperature. Consequently, the pleiotropic effects of KITLG, that is, pigmentation and thermogenesis were both targeted by natural selection that acted on different KITLG sequence variants, contributing to the adaptation of Eurasians to both UV radiation and winter temperature at high latitude areas.
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Affiliation(s)
- Zhaohui Yang
- Yunnan Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, China.,State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China.,Yunnan Provincial Academy of Science and Technology, Kunming, China
| | - Hong Shi
- Yunnan Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, China.,Yunnan Provincial Academy of Science and Technology, Kunming, China
| | - Pengcheng Ma
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Shilei Zhao
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China
| | - Qinghong Kong
- Faculty of Life Science and Technology, Kunming University of Science and Technology, Kunming, China
| | - Tianhao Bian
- Yunnan Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, China.,Yunnan Provincial Academy of Science and Technology, Kunming, China
| | - Chao Gong
- Yunnan Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, China.,Yunnan Provincial Academy of Science and Technology, Kunming, China
| | - Qi Zhao
- Yunnan Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, China.,Yunnan Provincial Academy of Science and Technology, Kunming, China
| | - Yuan Liu
- Faculty of Life Science and Technology, Kunming University of Science and Technology, Kunming, China
| | - Xuebin Qi
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Xiaoming Zhang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Yinglun Han
- College of Life Science, Liaoning Normal University, Dalian, China
| | - Jiewei Liu
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Qingwei Li
- College of Life Science, Liaoning Normal University, Dalian, China
| | - Hua Chen
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China
| | - Bing Su
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China.,Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, China
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16
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Lona-Durazo F, Hernandez-Pacheco N, Fan S, Zhang T, Choi J, Kovacs MA, Loftus SK, Le P, Edwards M, Fortes-Lima CA, Eng C, Huntsman S, Hu D, Gómez-Cabezas EJ, Marín-Padrón LC, Grauholm J, Mors O, Burchard EG, Norton HL, Pavan WJ, Brown KM, Tishkoff S, Pino-Yanes M, Beleza S, Marcheco-Teruel B, Parra EJ. Meta-analysis of GWA studies provides new insights on the genetic architecture of skin pigmentation in recently admixed populations. BMC Genet 2019; 20:59. [PMID: 31315583 PMCID: PMC6637524 DOI: 10.1186/s12863-019-0765-5] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2019] [Accepted: 07/08/2019] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND Association studies in recently admixed populations are extremely useful to identify the genetic architecture of pigmentation, due to their high genotypic and phenotypic variation. However, to date only four Genome-Wide Association Studies (GWAS) have been carried out in these populations. RESULTS We present a GWAS of skin pigmentation in an admixed sample from Cuba (N = 762). Additionally, we conducted a meta-analysis including the Cuban sample, and admixed samples from Cape Verde, Puerto Rico and African-Americans from San Francisco. This meta-analysis is one of the largest efforts so far to characterize the genetic basis of skin pigmentation in admixed populations (N = 2,104). We identified five genome-wide significant regions in the meta-analysis, and explored if the markers observed in these regions are associated with the expression of relevant pigmentary genes in human melanocyte cultures. In three of the regions identified in the meta-analysis (SLC24A5, SLC45A2, and GRM5/TYR), the association seems to be driven by non-synonymous variants (rs1426654, rs16891982, and rs1042602, respectively). The rs16891982 polymorphism is strongly associated with the expression of the SLC45A2 gene. In the GRM5/TYR region, in addition to the rs1042602 non-synonymous SNP located on the TYR gene, variants located in the nearby GRM5 gene have an independent effect on pigmentation, possibly through regulation of gene expression of the TYR gene. We also replicated an association recently described near the MFSD12 gene on chromosome 19 (lead variant rs112332856). Additionally, our analyses support the presence of multiple signals in the OCA2/HERC2/APBA2 region on chromosome 15. A clear causal candidate is the HERC2 intronic variant rs12913832, which has a profound influence on OCA2 expression. This variant has pleiotropic effects on eye, hair, and skin pigmentation. However, conditional and haplotype-based analyses indicate the presence of other variants with independent effects on melanin levels in OCA2 and APBA2. Finally, a follow-up of genome-wide signals identified in a recent GWAS for tanning response indicates that there is a substantial overlap in the genetic factors influencing skin pigmentation and tanning response. CONCLUSIONS Our meta-analysis of skin pigmentation GWAS in recently admixed populations provides new insights about the genetic architecture of this complex trait.
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Affiliation(s)
- Frida Lona-Durazo
- Department of Anthropology, University of Toronto at Mississauga, Health Sciences Complex, room 352, Mississauga, Ontario L5L 1C6 Canada
| | - Natalia Hernandez-Pacheco
- Research Unit, Hospital Universitario N.S. de Candelaria, Universidad de La Laguna, Santa Cruz de Tenerife, Spain
- Genomics and Health Group, Department of Biochemistry, Microbiology, Cell Biology and Genetics, Universidad de La Laguna, La Laguna, Tenerife, Spain
| | - Shaohua Fan
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| | - Tongwu Zhang
- Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, USA
| | - Jiyeon Choi
- Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, USA
| | - Michael A. Kovacs
- Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, USA
| | - Stacie K. Loftus
- Genetic Disease Research Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, USA
| | - Phuong Le
- Department of Anthropology, University of Toronto at Mississauga, Health Sciences Complex, room 352, Mississauga, Ontario L5L 1C6 Canada
| | - Melissa Edwards
- Department of Anthropology, University of Toronto at Mississauga, Health Sciences Complex, room 352, Mississauga, Ontario L5L 1C6 Canada
| | - Cesar A. Fortes-Lima
- Evolutionary Anthropology Team, Laboratory Eco-Anthropology and Ethno-Biology UMR7206, CNRS-MNHN-University Paris Diderot, Musée de l’Homme, Paris, France
- Department of Organismal Biology, Evolutionary Biology Centre, Uppsala University, Uppsala, Sweden
| | - Celeste Eng
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA USA
| | - Scott Huntsman
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA USA
| | - Donglei Hu
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA USA
| | | | | | - Jonas Grauholm
- Department for Congenital Disorders, Statens Serum Institut, Copenhagen, Denmark
| | - Ole Mors
- Translational Neuropsychiatry Unit, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus University, Aarhus, Denmark
- Psychiatric Department, Aarhus University Hospital, Aarhus, Denmark
| | - Esteban G. Burchard
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA USA
| | - Heather L. Norton
- Department of Anthropology, University of Cincinnati, Cincinnati, USA
| | - William J. Pavan
- Genetic Disease Research Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, USA
| | - Kevin M. Brown
- Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, USA
| | - Sarah Tishkoff
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
- Department of Biology, School of Arts and Sciences, University of Pennsylvania, Philadelphia, PA USA
| | - Maria Pino-Yanes
- Genomics and Health Group, Department of Biochemistry, Microbiology, Cell Biology and Genetics, Universidad de La Laguna, La Laguna, Tenerife, Spain
- CIBER de Enfermedades Respiratorias, Instituto de Salud Carlos III, Madrid, Spain
- Instituto de Tecnologías Biomédicas (ITB), Universidad de La Laguna, Santa Cruz de Tenerife, Spain
| | - Sandra Beleza
- Department of Genetics and Genome Biology, College of Life Sciences, University of Leicester, Leicester, UK
| | | | - Esteban J. Parra
- Department of Anthropology, University of Toronto at Mississauga, Health Sciences Complex, room 352, Mississauga, Ontario L5L 1C6 Canada
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17
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Fritsche LG, Beesley LJ, VandeHaar P, Peng RB, Salvatore M, Zawistowski M, Gagliano Taliun SA, Das S, LeFaive J, Kaleba EO, Klumpner TT, Moser SE, Blanc VM, Brummett CM, Kheterpal S, Abecasis GR, Gruber SB, Mukherjee B. Exploring various polygenic risk scores for skin cancer in the phenomes of the Michigan genomics initiative and the UK Biobank with a visual catalog: PRSWeb. PLoS Genet 2019; 15:e1008202. [PMID: 31194742 PMCID: PMC6592565 DOI: 10.1371/journal.pgen.1008202] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2018] [Revised: 06/25/2019] [Accepted: 05/17/2019] [Indexed: 01/08/2023] Open
Abstract
Polygenic risk scores (PRS) are designed to serve as single summary measures that are easy to construct, condensing information from a large number of genetic variants associated with a disease. They have been used for stratification and prediction of disease risk. The primary focus of this paper is to demonstrate how we can combine PRS and electronic health records data to better understand the shared and unique genetic architecture and etiology of disease subtypes that may be both related and heterogeneous. PRS construction strategies often depend on the purpose of the study, the available data/summary estimates, and the underlying genetic architecture of a disease. We consider several choices for constructing a PRS using data obtained from various publicly-available sources including the UK Biobank and evaluate their abilities to predict not just the primary phenotype but also secondary phenotypes derived from electronic health records (EHR). This study was conducted using data from 30,702 unrelated, genotyped patients of recent European descent from the Michigan Genomics Initiative (MGI), a longitudinal biorepository effort within Michigan Medicine. We examine the three most common skin cancer subtypes in the USA: basal cell carcinoma, cutaneous squamous cell carcinoma, and melanoma. Using these PRS for various skin cancer subtypes, we conduct a phenome-wide association study (PheWAS) within the MGI data to evaluate PRS associations with secondary traits. PheWAS results are then replicated using population-based UK Biobank data and compared across various PRS construction methods. We develop an accompanying visual catalog called PRSweb that provides detailed PheWAS results and allows users to directly compare different PRS construction methods.
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Affiliation(s)
- Lars G. Fritsche
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, Michigan, United States of America
- Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, Michigan, United States of America
| | - Lauren J. Beesley
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, Michigan, United States of America
| | - Peter VandeHaar
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, Michigan, United States of America
- Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, Michigan, United States of America
| | - Robert B. Peng
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, Michigan, United States of America
| | - Maxwell Salvatore
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, Michigan, United States of America
| | - Matthew Zawistowski
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, Michigan, United States of America
- Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, Michigan, United States of America
| | - Sarah A. Gagliano Taliun
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, Michigan, United States of America
- Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, Michigan, United States of America
| | - Sayantan Das
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, Michigan, United States of America
- Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, Michigan, United States of America
| | - Jonathon LeFaive
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, Michigan, United States of America
- Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, Michigan, United States of America
| | - Erin O. Kaleba
- Division of Pain Medicine, Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, Michigan, United States of America
| | - Thomas T. Klumpner
- Division of Pain Medicine, Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, Michigan, United States of America
- Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Stephanie E. Moser
- Division of Pain Medicine, Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, Michigan, United States of America
| | - Victoria M. Blanc
- Central Biorepository, University of Michigan Medical School, Ann Arbor, Michigan, United States of America
| | - Chad M. Brummett
- Division of Pain Medicine, Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, Michigan, United States of America
- Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Sachin Kheterpal
- Division of Pain Medicine, Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, Michigan, United States of America
- Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Gonçalo R. Abecasis
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, Michigan, United States of America
- Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, Michigan, United States of America
| | - Stephen B. Gruber
- USC Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, California, United States of America
| | - Bhramar Mukherjee
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, Michigan, United States of America
- Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, Michigan, United States of America
- Michigan Institute for Data Science, University of Michigan, Ann Arbor, Michigan, United States of America
- Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, Michigan, United States of America
- University of Michigan Rogel Cancer Center, University of Michigan, Ann Arbor, Michigan, United States of America
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18
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Baxter LL, Watkins-Chow DE, Pavan WJ, Loftus SK. A curated gene list for expanding the horizons of pigmentation biology. Pigment Cell Melanoma Res 2019; 32:348-358. [PMID: 30339321 PMCID: PMC10413850 DOI: 10.1111/pcmr.12743] [Citation(s) in RCA: 76] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2018] [Revised: 09/01/2018] [Accepted: 09/29/2018] [Indexed: 12/27/2022]
Abstract
Over the past century, studies of human pigmentary disorders along with mouse and zebrafish models have shed light on the many cellular functions associated with visible pigment phenotypes. This has led to numerous genes annotated with the ontology term "pigmentation" in independent human, mouse, and zebrafish databases. Comparisons among these datasets revealed that each is individually incomplete in documenting all genes involved in integument-based pigmentation phenotypes. Additionally, each database contained inherent species-specific biases in data annotation, and the term "pigmentation" did not solely reflect integument pigmentation phenotypes. This review presents a comprehensive, cross-species list of 650 genes involved in pigmentation phenotypes that was compiled with extensive manual curation of genes annotated in OMIM, MGI, ZFIN, and GO. The resulting cross-species list of genes both intrinsic and extrinsic to integument pigment cells provides a valuable tool that can be used to expand our knowledge of complex, pigmentation-associated pathways.
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Affiliation(s)
- Laura L Baxter
- Genetic Disease Research Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland
| | - Dawn E Watkins-Chow
- Genetic Disease Research Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland
| | - William J Pavan
- Genetic Disease Research Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland
| | - Stacie K Loftus
- Genetic Disease Research Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland
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19
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Katsara MA, Nothnagel M. True colors: A literature review on the spatial distribution of eye and hair pigmentation. Forensic Sci Int Genet 2019; 39:109-118. [DOI: 10.1016/j.fsigen.2019.01.001] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2018] [Revised: 12/11/2018] [Accepted: 01/01/2019] [Indexed: 10/27/2022]
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20
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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: 7.0] [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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21
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Quillen EE, Norton HL, Parra EJ, Lona-Durazo F, Ang KC, Illiescu FM, Pearson LN, Shriver MD, Lasisi T, Gokcumen O, Starr I, Lin YL, Martin AR, Jablonski NG. Shades of complexity: New perspectives on the evolution and genetic architecture of human skin. AMERICAN JOURNAL OF PHYSICAL ANTHROPOLOGY 2018; 168 Suppl 67:4-26. [PMID: 30408154 DOI: 10.1002/ajpa.23737] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/02/2018] [Revised: 09/17/2018] [Accepted: 09/20/2018] [Indexed: 02/06/2023]
Abstract
Like many highly variable human traits, more than a dozen genes are known to contribute to the full range of skin color. However, the historical bias in favor of genetic studies in European and European-derived populations has blinded us to the magnitude of pigmentation's complexity. As deliberate efforts are being made to better characterize diverse global populations and new sequencing technologies, better measurement tools, functional assessments, predictive modeling, and ancient DNA analyses become more widely accessible, we are beginning to appreciate how limited our understanding of the genetic bases of human skin color have been. Novel variants in genes not previously linked to pigmentation have been identified and evidence is mounting that there are hundreds more variants yet to be found. Even for genes that have been exhaustively characterized in European populations like MC1R, OCA2, and SLC24A5, research in previously understudied groups is leading to a new appreciation of the degree to which genetic diversity, epistatic interactions, pleiotropy, admixture, global and local adaptation, and cultural practices operate in population-specific ways to shape the genetic architecture of skin color. Furthermore, we are coming to terms with how factors like tanning response and barrier function may also have influenced selection on skin throughout human history. By examining how our knowledge of pigmentation genetics has shifted in the last decade, we can better appreciate how far we have come in understanding human diversity and the still long road ahead for understanding many complex human traits.
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Affiliation(s)
- Ellen E Quillen
- Department of Internal Medicine, Section of Molecular Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina.,Center for Precision Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Heather L Norton
- Department of Anthropology, University of Cincinnati, Cincinnati, Ohio
| | - Esteban J Parra
- Department of Anthropology, University of Toronto - Mississauga, Mississauga, Ontario, Canada
| | - Frida Lona-Durazo
- Department of Anthropology, University of Toronto - Mississauga, Mississauga, Ontario, Canada
| | - Khai C Ang
- Department of Pathology and Jake Gittlen Laboratories for Cancer Research, Penn State College of Medicine, Hershey, Pennsylvania
| | - Florin Mircea Illiescu
- Department of Zoology, University of Cambridge, Cambridge, United Kingdom.,Centro de Estudios Interculturales e Indígenas - CIIR, P. Universidad Católica de Chile, Santiago, Chile
| | - Laurel N Pearson
- Department of Anthropology, Pennsylvania State University, University Park, Pennsylvania
| | - Mark D Shriver
- Department of Anthropology, Pennsylvania State University, University Park, Pennsylvania
| | - Tina Lasisi
- Department of Anthropology, Pennsylvania State University, University Park, Pennsylvania
| | - Omer Gokcumen
- Department of Biological Sciences, State University of New York at Buffalo, Buffalo, New York
| | - Izzy Starr
- Department of Biological Sciences, State University of New York at Buffalo, Buffalo, New York
| | - Yen-Lung Lin
- Department of Biological Sciences, State University of New York at Buffalo, Buffalo, New York
| | - Alicia R Martin
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts.,Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts.,Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, Massachusetts
| | - Nina G Jablonski
- Department of Anthropology, Pennsylvania State University, University Park, Pennsylvania
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22
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Iliescu FM, Chaplin G, Rai N, Jacobs GS, Basu Mallick C, Mishra A, Thangaraj K, Jablonski NG. The influences of genes, the environment, and social factors on the evolution of skin color diversity in India. Am J Hum Biol 2018; 30:e23170. [PMID: 30099804 DOI: 10.1002/ajhb.23170] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2018] [Revised: 06/18/2018] [Accepted: 07/09/2018] [Indexed: 12/21/2022] Open
Abstract
OBJECTIVES Skin color is a highly visible and variable trait across human populations. It is not yet clear how evolutionary forces interact to generate phenotypic diversity. Here, we sought to unravel through an integrative framework the role played by three factors-demography and migration, sexual selection, and natural selection-in driving skin color diversity in India. METHODS Skin reflectance data were collected from 10 diverse socio-cultural populations along the latitudinal expanse of India, including both sexes. We first looked at how skin color varies within and between these populations. Second, we compared patterns of sexual dimorphism in skin color. Third, we studied the influence of ultraviolet radiation on skin color throughout India. Finally, we attempted to disentangle the interactions between these factors in the context of available genetic data. RESULTS We found that the relative importance of these forces varied between populations. Social factors and population structure have played a stronger role than natural selection in shaping skin color diversity across India. Phenotypic overprinting resulted from additional genetic mutations overriding the skin lightening effect of variants such as the SLC24A5 rs1426654-A allele in some populations, in the context of the variable influence of sexual selection. Furthermore, specific genotypes are not associated reliably with specific skin color phenotypes. This result has relevance for DNA forensics and ancient DNA research. CONCLUSIONS India is a crucible of macro- and micro-evolutionary forces, and the complex interactions of physical and social forces are visible in the patterns of skin color seen today in the country.
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Affiliation(s)
- Florin Mircea Iliescu
- Department of Zoology, University of Cambridge, Cambridge, United Kingdom.,Centro de Estudios Interculturales e Indígenas - CIIR, P. Universidad Católica de Chile, Santiago, Chile
| | - George Chaplin
- Department of Anthropology, The Pennsylvania State University, University Park, State Park, Pennsylvania
| | - Niraj Rai
- CSIR-Centre for Cellular and Molecular Biology, Hyderabad, India.,Birbal Sahni Institute of Palaeosciences, Lucknow, India
| | - Guy S Jacobs
- Complexity Institute, Nanyang Technological University, Singapore
| | - Chandana Basu Mallick
- Estonian Biocentre, Tartu, Estonia.,The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh, United Kingdom
| | - Anshuman Mishra
- CSIR-Centre for Cellular and Molecular Biology, Hyderabad, India
| | | | - Nina G Jablonski
- Department of Anthropology, The Pennsylvania State University, University Park, State Park, Pennsylvania
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23
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Jo Hodonsky C, Schurmann C, Schick UM, Kocarnik J, Tao R, van Rooij FJ, Wassel C, Buyske S, Fornage M, Hindorff LA, Floyd JS, Ganesh SK, Lin DY, North KE, Reiner AP, Loos RJ, Kooperberg C, Avery CL. Generalization and fine mapping of red blood cell trait genetic associations to multi-ethnic populations: The PAGE Study. Am J Hematol 2018; 93:10.1002/ajh.25161. [PMID: 29905378 PMCID: PMC6300146 DOI: 10.1002/ajh.25161] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2018] [Revised: 05/29/2018] [Accepted: 05/29/2018] [Indexed: 12/17/2022]
Abstract
Red blood cell (RBC) traits provide insight into a wide range of physiological states and exhibit moderate to high heritability, making them excellent candidates for genetic studies to inform underlying biologic mechanisms. Previous RBC trait genome-wide association studies were performed primarily in European- or Asian-ancestry populations, missing opportunities to inform understanding of RBC genetic architecture in diverse populations and reduce intervals surrounding putative functional SNPs through fine-mapping. Here, we report the first fine-mapping of six correlated (Pearson's r range: |0.04 - 0.92|) RBC traits in up to 19,036 African Americans and 19,562 Hispanic/Latinos participants of the Population Architecture using Genomics and Epidemiology (PAGE) consortium. Trans-ethnic meta-analysis of race/ethnic- and study-specific estimates for approximately 11,000 SNPs flanking 13 previously identified association signals as well as 150,000 additional array-wide SNPs was performed using inverse-variance meta-analysis after adjusting for study and clinical covariates. Approximately half of previously reported index SNP-RBC trait associations generalized to the trans-ethnic study population (p<1.7x10-4 ); previously unreported independent association signals within the ABO region reinforce the potential for multiple functional variants affecting the same locus. Trans-ethnic fine-mapping did not reveal additional signals at the HFE locus independent of the known functional variants. Finally, we identified a potential novel association in the Hispanic/Latino study population at the HECTD4/RPL6 locus for RBC count (p=1.9x10-7 ). The identification of a previously unknown association, generalization of a large proportion of known association signals, and refinement of known association signals all exemplify the benefits of genetic studies in diverse populations. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Chani Jo Hodonsky
- Department of Epidemiology, University of North Carolina Gillings School of Public Health, Chapel Hill, NC
| | - Claudia Schurmann
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY
- The Genetics of Obesity and Related Metabolic Traits Program, The Icahn School of Medicine at Mount Sinai, New York, NY
| | - Ursula M Schick
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY
- The Genetics of Obesity and Related Metabolic Traits Program, The Icahn School of Medicine at Mount Sinai, New York, NY
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA
| | - Jonathan Kocarnik
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA
| | - Ran Tao
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN
| | - Frank Ja van Rooij
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, 3000, the Netherlands
| | - Christina Wassel
- Department of Pathology and Laboratory Medicine, College of Medicine, University of Vermont, Burlington, VT
| | - Steve Buyske
- Department of Statistics and Biostatistics, Hill Center, Rutgers, The State University of New Jersey, 110 Frelinghuysen Rd. Piscataway, NY
| | - Myriam Fornage
- Institute of Molecular Medicine and Human Genetics Center, University of Texas Health Science Center at Houston, Houston, TX
| | - Lucia A Hindorff
- Division of Genomic Medicine, National Human Genome Research Institute, National institutes of Health, Bethesda, MD
| | - James S Floyd
- Departments of Medicine, University of Washington, Seattle, WA
- Department of Epidemiology, University of Washington, Seattle, WA
| | - Santhi K Ganesh
- Department of Human Genetics, University of Michigan Medical School, Ann Arbor, MI
- Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, MI
| | - Dan-Yu Lin
- Department of Biostatistics, University of North Carolina, Chapel Hill, NC
| | - Kari E North
- Department of Epidemiology, University of North Carolina Gillings School of Public Health, Chapel Hill, NC
| | - Alex P Reiner
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA
- Department of Epidemiology, University of Washington, Seattle, WA
| | - Ruth Jf Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY
- The Genetics of Obesity and Related Metabolic Traits Program, The Icahn School of Medicine at Mount Sinai, New York, NY
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA
| | - Christy L Avery
- Department of Epidemiology, University of North Carolina Gillings School of Public Health, Chapel Hill, NC
- Carolina Population Center, University of North Carolina, Chapel Hill, NC
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