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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, Qi X, 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: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [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
| | - 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.
| | - 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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Terefe E, Belay G, Han J, Hanotte O, Tijjani A. Genomic adaptation of Ethiopian indigenous cattle to high altitude. Front Genet 2022; 13:960234. [PMID: 36568400 PMCID: PMC9780680 DOI: 10.3389/fgene.2022.960234] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Accepted: 11/22/2022] [Indexed: 12/13/2022] Open
Abstract
The mountainous areas of Ethiopia represent one of the most extreme environmental challenges in Africa faced by humans and other inhabitants. Selection for high-altitude adaptation is expected to have imprinted the genomes of livestock living in these areas. Here we assess the genomic signatures of positive selection for high altitude adaptation in three cattle populations from the Ethiopian mountainous areas (Semien, Choke, and Bale mountains) compared to three Ethiopian lowland cattle populations (Afar, Ogaden, and Boran), using whole-genome resequencing and three genome scan approaches for signature of selection (iHS, XP-CLR, and PBS). We identified several candidate selection signature regions and several high-altitude adaptation genes. These include genes such as ITPR2, MB, and ARNT previously reported in the human population inhabiting the Ethiopian highlands. Furthermore, we present evidence of strong selection and high divergence between Ethiopian high- and low-altitude cattle populations at three new candidate genes (CLCA2, SLC26A2, and CBFA2T3), putatively linked to high-altitude adaptation in cattle. Our findings provide possible examples of convergent selection between cattle and humans as well as unique African cattle signature to the challenges of living in the Ethiopian mountainous regions.
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Affiliation(s)
- Endashaw Terefe
- Department of Microbial Cellular and Molecular Biology (MCMB), College of Natural and Computational Science, Addis Ababa University, Addis Ababa, Ethiopia,International Livestock Research Institute (ILRI), Addis Ababa, Ethiopia,Department of Animal Science, College of Agriculture and Environmental Science, Arsi University, Asella, Ethiopia,*Correspondence: Endashaw Terefe, Abdulfatai Tijjani,
| | - Gurja Belay
- Department of Microbial Cellular and Molecular Biology (MCMB), College of Natural and Computational Science, Addis Ababa University, Addis Ababa, Ethiopia
| | - Jianlin Han
- Livestock Genetics Program, International Livestock Research Institute (ILRI), Nairobi, Kenya,CAAS-ILRI Joint Laboratory on Livestock and Forage Genetic Resources, Institute of Animal Science, Chinese Academy of Agricultural Sciences (CAAS), Beijing, China
| | - Olivier Hanotte
- International Livestock Research Institute (ILRI), Addis Ababa, Ethiopia,Centre for Tropical Livestock Genetics and Health (CTLGH), The Roslin Institute, The University of Edinburgh, Midlothian, United Kingdom,School of Life Sciences, University of Nottingham, Nottingham, United Kingdom
| | - Abdulfatai Tijjani
- International Livestock Research Institute (ILRI), Addis Ababa, Ethiopia,Centre for Tropical Livestock Genetics and Health (CTLGH), The Roslin Institute, The University of Edinburgh, Midlothian, United Kingdom,*Correspondence: Endashaw Terefe, Abdulfatai Tijjani,
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3
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Tashi QZ, Tsering SB, Zhou NN, Zhang Y, Huang YJ, Jia J, Li TJ. A Study on the Molecular Mechanism of High Altitude Heart Disease in Children. Pharmgenomics Pers Med 2022; 15:721-731. [PMID: 35903087 PMCID: PMC9316483 DOI: 10.2147/pgpm.s356206] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2021] [Accepted: 04/08/2022] [Indexed: 12/22/2022] Open
Abstract
Objective High altitude heart disease (HAHD) is a common pediatric disease in high altitude areas. It usually occurs in people who have lived for a long time or have lived for more than 2500m above sea level. Its common inducement is respiratory tract infection. The clinical differential diagnosis is difficult because the symptoms of HAHD are similar to those of congenital heart disease; Due to the limitation of medical conditions, many patients are in the state of losing follow-up or not seeking medical treatment, resulting in poor prognosis of HAHD and becoming a high-altitude disease with high mortality. Clarifying the molecular mechanism of HAHD, developing early molecular screening technology and accurate treatment methods of HAHD are the key to improve the ability of prevention and treatment of HAHD. Methods First, the literature in the PubMed and CNKI databases were screened based on keywords and abstracts. Then, the literature for the study was identified based on the fitness between the content of the literature, the research objectives, and the timeliness of the literature. Finally, a systematic molecular mechanism of HAHD was established by investigating the literature and sorting out the genetic adaptations of Tibetan populations compared with low-altitude populations that migrated to the plateau. Results With the investigation of the 48 papers screened, it was found that genes capable of enhancing the hypoxic ventilatory response and resistance to pulmonary hypertension were all correlated with the hypoxia-inducible factor (HIF) pathway, consisting mainly of three pathways, HIF-1α, HIF-2α, and NO. Conclusion The low prevalence of HAHD in Tibetan aboriginal children was mainly due to the genetic adaptation of the Tibetan population to the high altitude environment, which coordinated the cellular response to hypoxia by regulating the downstream hypoxia control genes in the HIF pathway.
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Affiliation(s)
- Qu-Zhen Tashi
- Department of Pediatrics, Shigatse Peopel's Hospital, Shigatse, Tibet, 857000, People’s Republic of China
| | - Sang-Bu Tsering
- Department of Pediatrics, Shigatse Peopel's Hospital, Shigatse, Tibet, 857000, People’s Republic of China
| | - Na-Ni Zhou
- Fujungenetics Technologies Inc. Shanghai, Shanghai, 200333, People’s Republic of China
| | - Yi Zhang
- Fujungenetics Technologies Inc. Shanghai, Shanghai, 200333, People’s Republic of China
| | - Yu-Juan Huang
- Department of Emergency, Children’s Hospital of Shanghai, Shanghai, 200062, People’s Republic of China
| | - Jia Jia
- Fujungenetics Technologies Inc. Shanghai, Shanghai, 200333, People’s Republic of China
- Jia Jia, Fulgent Technologies Inc, No. 70 of Tongchuan Road, Putuo District, Shanghai, 200333, People’s Republic of China, Tel +86 18658176000, Email
| | - Ting-Jun Li
- Department of Emergency, Children’s Hospital of Shanghai, Shanghai, 200062, People’s Republic of China
- Correspondence: Ting-Jun Li, Department of Emergency, Children’s Hospital of Shanghai, No. 355 of Huding Road, Putuo District, Shanghai, 200062, People’s Republic of China, Tel +86 18930590701, Email
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4
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Colbran LL, Johnson MR, Mathieson I, Capra JA. Tracing the Evolution of Human Gene Regulation and Its Association with Shifts in Environment. Genome Biol Evol 2021; 13:evab237. [PMID: 34718543 PMCID: PMC8576593 DOI: 10.1093/gbe/evab237] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/16/2021] [Indexed: 12/16/2022] Open
Abstract
As humans populated the world, they adapted to many varying environmental factors, including climate, diet, and pathogens. Because many of these adaptations were mediated by multiple noncoding variants with small effects on gene regulation, it has been difficult to link genomic signals of selection to specific genes, and to describe the regulatory response to selection. To overcome this challenge, we adapted PrediXcan, a machine learning method for imputing gene regulation from genotype data, to analyze low-coverage ancient human DNA (aDNA). First, we used simulated genomes to benchmark strategies for adapting PrediXcan to increase robustness to incomplete data. Applying the resulting models to 490 ancient Eurasians, we found that genes with the strongest divergent regulation among ancient populations with hunter-gatherer, pastoralist, and agricultural lifestyles are enriched for metabolic and immune functions. Next, we explored the contribution of divergent gene regulation to two traits with strong evidence of recent adaptation: dietary metabolism and skin pigmentation. We found enrichment for divergent regulation among genes proposed to be involved in diet-related local adaptation, and the predicted effects on regulation often suggest explanations for known signals of selection, for example, at FADS1, GPX1, and LEPR. In contrast, skin pigmentation genes show little regulatory change over a 38,000-year time series of 2,999 ancient Europeans, suggesting that adaptation mainly involved large-effect coding variants. This work demonstrates that combining aDNA with present-day genomes is informative about the biological differences among ancient populations, the role of gene regulation in adaptation, and the relationship between genetic diversity and complex traits.
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Affiliation(s)
- Laura L Colbran
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, USA
| | - Maya R Johnson
- School for Science and Math at Vanderbilt, Vanderbilt University, USA
- Department of Computer Science, Bryn Mawr College, Pennsylvania, USA
| | - Iain Mathieson
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, USA
| | - John A Capra
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, USA
- Department of Biological Sciences, Vanderbilt University, USA
- Department of Biomedical Informatics, Vanderbilt University, USA
- Bakar Computational Health Sciences Institute, University of California, San Francisco, USA
- Department of Epidemiology and Biostatistics, University of California, San Francisco, USA
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5
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Padmasekar M, Savai R, Seeger W, Pullamsetti SS. Exposomes to Exosomes: Exosomes as Tools to Study Epigenetic Adaptive Mechanisms in High-Altitude Humans. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:8280. [PMID: 34444030 PMCID: PMC8392481 DOI: 10.3390/ijerph18168280] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Revised: 07/30/2021] [Accepted: 07/31/2021] [Indexed: 12/29/2022]
Abstract
Humans on earth inhabit a wide range of environmental conditions and some environments are more challenging for human survival than others. However, many living beings, including humans, have developed adaptive mechanisms to live in such inhospitable, harsh environments. Among different difficult environments, high-altitude living is especially demanding because of diminished partial pressure of oxygen and resulting chronic hypobaric hypoxia. This results in poor blood oxygenation and reduces aerobic oxidative respiration in the mitochondria, leading to increased reactive oxygen species generation and activation of hypoxia-inducible gene expression. Genetic mechanisms in the adaptation to high altitude is well-studied, but there are only limited studies regarding the role of epigenetic mechanisms. The purpose of this review is to understand the epigenetic mechanisms behind high-altitude adaptive and maladaptive phenotypes. Hypobaric hypoxia is a form of cellular hypoxia, which is similar to the one suffered by critically-ill hypoxemia patients. Thus, understanding the adaptive epigenetic signals operating in in high-altitude adjusted indigenous populations may help in therapeutically modulating signaling pathways in hypoxemia patients by copying the most successful epigenotype. In addition, we have summarized the current information about exosomes in hypoxia research and prospects to use them as diagnostic tools to study the epigenome of high-altitude adapted healthy or maladapted individuals.
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Affiliation(s)
- Manju Padmasekar
- Max-Planck Institute for Heart and Lung Research, Member of the German Center for Lung Research (DZL), Member of the Cardio-Pulmonary Institute (CPI), 61231 Bad Nauheim, Germany; (M.P.); (R.S.); (W.S.)
| | - Rajkumar Savai
- Max-Planck Institute for Heart and Lung Research, Member of the German Center for Lung Research (DZL), Member of the Cardio-Pulmonary Institute (CPI), 61231 Bad Nauheim, Germany; (M.P.); (R.S.); (W.S.)
- Institute for Lung Health (ILH), Justus Liebig University, 35392 Giessen, Germany
- Department of Internal Medicine, Justus-Liebig University Giessen, Member of the DZL, Member of CPI, 35392 Giessen, Germany
- Frankfurt Cancer Institute (FCI), Goethe University, 60438 Frankfurt am Main, Germany
| | - Werner Seeger
- Max-Planck Institute for Heart and Lung Research, Member of the German Center for Lung Research (DZL), Member of the Cardio-Pulmonary Institute (CPI), 61231 Bad Nauheim, Germany; (M.P.); (R.S.); (W.S.)
- Institute for Lung Health (ILH), Justus Liebig University, 35392 Giessen, Germany
- Department of Internal Medicine, Justus-Liebig University Giessen, Member of the DZL, Member of CPI, 35392 Giessen, Germany
| | - Soni Savai Pullamsetti
- Max-Planck Institute for Heart and Lung Research, Member of the German Center for Lung Research (DZL), Member of the Cardio-Pulmonary Institute (CPI), 61231 Bad Nauheim, Germany; (M.P.); (R.S.); (W.S.)
- Institute for Lung Health (ILH), Justus Liebig University, 35392 Giessen, Germany
- Department of Internal Medicine, Justus-Liebig University Giessen, Member of the DZL, Member of CPI, 35392 Giessen, Germany
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6
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Deng L, Zhang C, Yuan K, Gao Y, Pan Y, Ge X, He Y, Yuan Y, Lu Y, Zhang X, Chen H, Lou H, Wang X, Lu D, Liu J, Tian L, Feng Q, Khan A, Yang Y, Jin ZB, Yang J, Lu F, Qu J, Kang L, Su B, Xu S. Prioritizing natural-selection signals from the deep-sequencing genomic data suggests multi-variant adaptation in Tibetan highlanders. Natl Sci Rev 2019; 6:1201-1222. [PMID: 34691999 PMCID: PMC8291452 DOI: 10.1093/nsr/nwz108] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2019] [Revised: 06/17/2019] [Accepted: 06/18/2019] [Indexed: 12/13/2022] Open
Abstract
Human genetic adaptation to high altitudes (>2500 m) has been extensively studied over the last few years, but few functional adaptive genetic variants have been identified, largely owing to the lack of deep-genome sequencing data available to previous studies. Here, we build a list of putative adaptive variants, including 63 missense, 7 loss-of-function, 1,298 evolutionarily conserved variants and 509 expression quantitative traits loci. Notably, the top signal of selection is located in TMEM247, a transmembrane protein-coding gene. The Tibetan version of TMEM247 harbors one high-frequency (76.3%) missense variant, rs116983452 (c.248C > T; p.Ala83Val), with the T allele derived from archaic ancestry and carried by >94% of Tibetans but absent or in low frequencies (<3%) in non-Tibetan populations. The rs116983452-T is strongly and positively correlated with altitude and significantly associated with reduced hemoglobin concentration (p = 5.78 × 10-5), red blood cell count (p = 5.72 × 10-7) and hematocrit (p = 2.57 × 10-6). In particular, TMEM247-rs116983452 shows greater effect size and better predicts the phenotypic outcome than any EPAS1 variants in association with adaptive traits in Tibetans. Modeling the interaction between TMEM247-rs116983452 and EPAS1 variants indicates weak but statistically significant epistatic effects. Our results support that multiple variants may jointly deliver the fitness of the Tibetans on the plateau, where a complex model is needed to elucidate the adaptive evolution mechanism.
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Affiliation(s)
- Lian Deng
- Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nu-trition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Chao Zhang
- Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nu-trition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Kai Yuan
- Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nu-trition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Yang Gao
- Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nu-trition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
- School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China
| | - Yuwen Pan
- Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nu-trition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Xueling Ge
- Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nu-trition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Yaoxi He
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
| | - Yuan Yuan
- Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nu-trition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Yan Lu
- Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nu-trition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Xiaoxi Zhang
- Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nu-trition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
- School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China
| | - Hao Chen
- Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nu-trition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Haiyi Lou
- Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nu-trition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Xiaoji Wang
- Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nu-trition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Dongsheng Lu
- Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nu-trition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Jiaojiao Liu
- Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nu-trition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
- School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China
| | - Lei Tian
- Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nu-trition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Qidi Feng
- Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nu-trition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Asifullah Khan
- Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nu-trition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Yajun Yang
- State Key Laboratory of Genetic Engineering and Ministry of Education (MOE) Key Laboratory of Contemporary Anthropology, School of Life Sciences, Fudan University, Shanghai 200433, China
| | - Zi-Bing Jin
- The Eye Hospital, School of Ophthalmology & Optometry, Wenzhou Medical University, China National Center for International Research in Regenerative Medicine and Neurogenetics, State Key Laboratory of Ophthalmology, Optometry and Visual Science, Wenzhou 325027, China
| | - Jian Yang
- The Eye Hospital, School of Ophthalmology & Optometry, Wenzhou Medical University, China National Center for International Research in Regenerative Medicine and Neurogenetics, State Key Laboratory of Ophthalmology, Optometry and Visual Science, Wenzhou 325027, China
- Institute for Molecular Bioscience, Queensland Brain Institute, The University of Queensland, Brisbane, QLD 4072, Australia
| | - Fan Lu
- The Eye Hospital, School of Ophthalmology & Optometry, Wenzhou Medical University, China National Center for International Research in Regenerative Medicine and Neurogenetics, State Key Laboratory of Ophthalmology, Optometry and Visual Science, Wenzhou 325027, China
| | - Jia Qu
- The Eye Hospital, School of Ophthalmology & Optometry, Wenzhou Medical University, China National Center for International Research in Regenerative Medicine and Neurogenetics, State Key Laboratory of Ophthalmology, Optometry and Visual Science, Wenzhou 325027, China
| | - Longli Kang
- Key Laboratory for Molecular Genetic Mechanisms and Intervention Research on High Altitude Disease of Tibet Autonomous Region, School of Medicine, Xizang Minzu University, Xianyang 712082, 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
| | - Shuhua Xu
- Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nu-trition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
- School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming 650223, China
- Collaborative Innovation Center of Genetics and Development, Shanghai 200438, China
- Human Phenome Institute, Fudan University, Shanghai 201203, China
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7
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Bemanian V, Noone JC, Sauer T, Touma J, Vetvik K, Søderberg-Naucler C, Lindstrøm JC, Bukholm IR, Kristensen VN, Geisler J. Somatic EP300-G211S mutations are associated with overall somatic mutational patterns and breast cancer specific survival in triple-negative breast cancer. Breast Cancer Res Treat 2018; 172:339-351. [PMID: 30132219 DOI: 10.1007/s10549-018-4927-3] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2018] [Accepted: 08/17/2018] [Indexed: 10/28/2022]
Abstract
PURPOSE We have compared the mutational profiles of human breast cancer tumor samples belonging to all major subgroups with special emphasis on triple-negative breast cancer (TNBC). Our major goal was to identify specific mutations that could be potentially used for clinical decision making in TNBC patients. PATIENTS AND METHODS Primary tumor specimens from 149 Norwegian breast cancer patients were available. We analyzed the tissue samples for somatic mutations in 44 relevant breast cancer genes by targeted next-generation sequencing. As a second confirmatory technique, we performed pyrosequencing on selected samples. RESULTS We observed a distinct subgroup of TNBC patients, characterized by an almost completely lack of pathogenic somatic mutations. A point mutation in the adenoviral E1A binding protein p300 (EP300-G211S) was significantly correlated to this TNBC subgroup. The EP300-G211S mutation was exclusively found in the TNBC patients and its presence reduced the chance for other pathological somatic mutations in typical breast cancer genes investigated in our gene panel by 94.9% (P < 0.005). Interestingly, the EP300-G211S mutation also predicted a lower risk for relapses and decreased breast cancer-specific mortality during long-term follow-up of the patients. CONCLUSION Next-generation sequencing revealed specific mutations in EP300 to be associated with the mutational patterns in typical breast cancer genes and long-term outcome of triple-negative breast cancer patients.
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Affiliation(s)
- Vahid Bemanian
- Section of Gene Technology, Akershus University Hospital, 1478, Lørenskog, Norway
| | | | - Torill Sauer
- Department of Pathology, Akershus University Hospital, 1478, Lørenskog, Norway.,Institute of Clinical Medicine, University of Oslo, Campus at Akershus University Hospital, 1478, Lørenskog, Norway
| | - Joel Touma
- Department of Breast and Endocrine Surgery, Akershus University Hospital, 1478, Lørenskog, Norway.,Department of Oncology, Akershus University Hospital, 1478, Lørenskog, Norway
| | - Katja Vetvik
- Institute of Clinical Medicine, University of Oslo, Campus at Akershus University Hospital, 1478, Lørenskog, Norway.,Department of Breast and Endocrine Surgery, Akershus University Hospital, 1478, Lørenskog, Norway
| | - Cecilia Søderberg-Naucler
- Department of Medicine at Solna, Experimental Cardiovascular Research Unit and Departments of Medicine and Neurology, Center for Molecular Medicine, Karolinska Institute, 17176, Stockholm, Sweden
| | - Jonas Christoffer Lindstrøm
- Institute of Clinical Medicine, University of Oslo, Campus at Akershus University Hospital, 1478, Lørenskog, Norway.,Health Services Research Unit, Akershus University Hospital, 1478, Lørenskog, Norway
| | - Ida Rashida Bukholm
- Department of Breast and Endocrine Surgery, Akershus University Hospital, 1478, Lørenskog, Norway.,Norwegian System of Compensation to Patients, Oslo, Norway.,The Norwegian University of Life Sciences, Ås, Norway
| | - Vessela N Kristensen
- Institute of Clinical Medicine, University of Oslo, Campus at Akershus University Hospital, 1478, Lørenskog, Norway.,Clinical Molecular Biology (EPIGEN), Akershus University Hospital, 1478, Lørenskog, Norway
| | - Jürgen Geisler
- Institute of Clinical Medicine, University of Oslo, Campus at Akershus University Hospital, 1478, Lørenskog, Norway. .,Department of Oncology, Akershus University Hospital, 1478, Lørenskog, Norway.
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Jablonski NG. Genes for the high life: New genetic variants point to positive selection for high altitude hypoxia in Tibetans. Zool Res 2018; 38:117. [PMID: 28585434 PMCID: PMC5460079 DOI: 10.24272/j.issn.2095-8137.2017.031] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023] Open
Affiliation(s)
- Nina G Jablonski
- The Pennsylvania State University, University Park, PA 16902, USA.
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