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Wu T, Xu S. Understanding the contemporary high obesity rate from an evolutionary genetic perspective. Hereditas 2023; 160:5. [PMID: 36750916 PMCID: PMC9903520 DOI: 10.1186/s41065-023-00268-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Accepted: 01/31/2023] [Indexed: 02/09/2023] Open
Abstract
The topic of obesity is gaining increasing popularity globally. From an evolutionary genetic perspective, it is believed that the main cause of the high obesity rate is the mismatch between environment and genes after people have shifted toward a modern high-calorie diet. However, it has been debated for over 60 years about how obesity-related genes become prevalent all over the world. Here, we review the three most influential hypotheses or viewpoints, i.e., the thrifty gene hypothesis, the drifty gene hypothesis, and the maladaptation viewpoint. In particular, genome-wide association studies in the recent 10 years have provided rich findings and evidence to be considered for a better understanding of the evolutionary genetic mechanisms of obesity. We anticipate this brief review to direct further studies and inspire the future application of precision medicine in obesity treatment.
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Affiliation(s)
- Tong Wu
- grid.8547.e0000 0001 0125 2443State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, Collaborative Innovation Center of Genetics and Development, School of Life Sciences, Fudan University, Shanghai, 200438 China
| | - Shuhua Xu
- State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, Collaborative Innovation Center of Genetics and Development, School of Life Sciences, Fudan University, Shanghai, 200438, China. .,Human Phenome Institute, Zhangjiang Fudan International Innovation Center, and Ministry of Education Key Laboratory of Contemporary Anthropology, Fudan University, Shanghai, 201203, China. .,Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
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2
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Caliebe A, Tekola‐Ayele F, Darst BF, Wang X, Song YE, Gui J, Sebro RA, Balding DJ, Saad M, Dubé M. Including diverse and admixed populations in genetic epidemiology research. Genet Epidemiol 2022; 46:347-371. [PMID: 35842778 PMCID: PMC9452464 DOI: 10.1002/gepi.22492] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Revised: 05/31/2022] [Accepted: 06/06/2022] [Indexed: 11/25/2022]
Abstract
The inclusion of ancestrally diverse participants in genetic studies can lead to new discoveries and is important to ensure equitable health care benefit from research advances. Here, members of the Ethical, Legal, Social, Implications (ELSI) committee of the International Genetic Epidemiology Society (IGES) offer perspectives on methods and analysis tools for the conduct of inclusive genetic epidemiology research, with a focus on admixed and ancestrally diverse populations in support of reproducible research practices. We emphasize the importance of distinguishing socially defined population categorizations from genetic ancestry in the design, analysis, reporting, and interpretation of genetic epidemiology research findings. Finally, we discuss the current state of genomic resources used in genetic association studies, functional interpretation, and clinical and public health translation of genomic findings with respect to diverse populations.
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Affiliation(s)
- Amke Caliebe
- Institute of Medical Informatics and StatisticsKiel University and University Hospital Schleswig‐HolsteinKielGermany
| | - Fasil Tekola‐Ayele
- Epidemiology Branch, Division of Population Health Research, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institutes of HealthBethesdaMarylandUSA
| | - Burcu F. Darst
- Center for Genetic EpidemiologyUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
- Public Health Sciences DivisionFred Hutchinson Cancer Research CenterSeattleWashingtonUSA
| | - Xuexia Wang
- Department of MathematicsUniversity of North TexasDentonTexasUSA
| | - Yeunjoo E. Song
- Department of Population and Quantitative Health SciencesCase Western Reserve UniversityClevelandOhioUSA
| | - Jiang Gui
- Department of Biomedical Data Science, Geisel School of Medicine, Dartmouth CollegeOne Medical Center Dr.LebanonNew HampshireUSA
| | | | - David J. Balding
- Melbourne Integrative Genomics, Schools of BioSciences and of Mathematics & StatisticsUniversity of MelbourneMelbourneAustralia
| | - Mohamad Saad
- Qatar Computing Research InstituteHamad Bin Khalifa UniversityDohaQatar
- Neuroscience Research Center, Faculty of Medical SciencesLebanese UniversityBeirutLebanon
| | - Marie‐Pierre Dubé
- Department of Medicine, and Social and Preventive MedicineUniversité de MontréalMontréalQuébecCanada
- Beaulieu‐Saucier Pharmacogenomcis CentreMontreal Heart InstituteMontrealCanada
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Lo YH, Cheng HC, Hsiung CN, Yang SL, Wang HY, Peng CW, Chen CY, Lin KP, Kang ML, Chen CH, Chu HW, Lin CF, Lee MH, Liu Q, Satta Y, Lin CJ, Lin M, Chaw SM, Loo JH, Shen CY, Ko WY. Detecting Genetic Ancestry and Adaptation in the Taiwanese Han People. Mol Biol Evol 2021; 38:4149-4165. [PMID: 33170928 PMCID: PMC8476137 DOI: 10.1093/molbev/msaa276] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
The Taiwanese people are composed of diverse indigenous populations and the Taiwanese Han. About 95% of the Taiwanese identify themselves as Taiwanese Han, but this may not be a homogeneous population because they migrated to the island from various regions of continental East Asia over a period of 400 years. Little is known about the underlying patterns of genetic ancestry, population admixture, and evolutionary adaptation in the Taiwanese Han people. Here, we analyzed the whole-genome single-nucleotide polymorphism genotyping data from 14,401 individuals of Taiwanese Han collected by the Taiwan Biobank and the whole-genome sequencing data for a subset of 772 people. We detected four major genetic ancestries with distinct geographic distributions (i.e., Northern, Southeastern, Japonic, and Island Southeast Asian ancestries) and signatures of population mixture contributing to the genomes of Taiwanese Han. We further scanned for signatures of positive natural selection that caused unusually long-range haplotypes and elevations of hitchhiked variants. As a result, we identified 16 candidate loci in which selection signals can be unambiguously localized at five single genes: CTNNA2, LRP1B, CSNK1G3, ASTN2, and NEO1. Statistical associations were examined in 16 metabolic-related traits to further elucidate the functional effects of each candidate gene. All five genes appear to have pleiotropic connections to various types of disease susceptibility and significant associations with at least one metabolic-related trait. Together, our results provide critical insights for understanding the evolutionary history and adaption of the Taiwanese Han population.
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Affiliation(s)
- Yun-Hua Lo
- Faculty of Life Sciences and Institute of Genome Sciences, National Yang-Ming University, Taipei, Taiwan
| | - Hsueh-Chien Cheng
- Faculty of Life Sciences and Institute of Genome Sciences, National Yang-Ming University, Taipei, Taiwan
| | - Chia-Ni Hsiung
- Institute of Biomedical Sciences, Academia Sinica, Taipei City, Taiwan
| | - Show-Ling Yang
- Institute of Biomedical Sciences, Academia Sinica, Taipei City, Taiwan
| | - Han-Yu Wang
- Faculty of Life Sciences and Institute of Genome Sciences, National Yang-Ming University, Taipei, Taiwan
| | - Chia-Wei Peng
- Faculty of Life Sciences and Institute of Genome Sciences, National Yang-Ming University, Taipei, Taiwan
| | - Chun-Yu Chen
- Faculty of Life Sciences and Institute of Genome Sciences, National Yang-Ming University, Taipei, Taiwan
| | - Kung-Ping Lin
- Faculty of Life Sciences and Institute of Genome Sciences, National Yang-Ming University, Taipei, Taiwan
| | - Mei-Ling Kang
- Faculty of Life Sciences and Institute of Genome Sciences, National Yang-Ming University, Taipei, Taiwan
| | - Chien-Hsiun Chen
- Institute of Biomedical Sciences, Academia Sinica, Taipei City, Taiwan
| | - Hou-Wei Chu
- Institute of Biomedical Sciences, Academia Sinica, Taipei City, Taiwan
| | | | - Mei-Hsuan Lee
- Institute of Clinical Medicine, National Yang-Ming University, Taipei, Taiwan
| | - Quintin Liu
- Department of Evolutionary Studies of Biosystems, SOKENDAI (The Graduate University for Advanced Studies), Hayama, Japan
| | - Yoko Satta
- Department of Evolutionary Studies of Biosystems, SOKENDAI (The Graduate University for Advanced Studies), Hayama, Japan
| | - Cheng-Jui Lin
- Molecular Anthropology and Transfusion Medicine Research Laboratory, Mackay Memorial Hospital, Taipei, Taiwan
| | - Marie Lin
- Molecular Anthropology and Transfusion Medicine Research Laboratory, Mackay Memorial Hospital, Taipei, Taiwan
| | - Shu-Miaw Chaw
- Biodiversity Research Center, Academia Sinica, Taipei City, Taiwan
| | - Jun-Hun Loo
- Molecular Anthropology and Transfusion Medicine Research Laboratory, Mackay Memorial Hospital, Taipei, Taiwan
| | - Chen-Yang Shen
- Institute of Biomedical Sciences, Academia Sinica, Taipei City, Taiwan
| | - Wen-Ya Ko
- Faculty of Life Sciences and Institute of Genome Sciences, National Yang-Ming University, Taipei, Taiwan
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Abstract
Some of the genes responsible for the evolution of light skin pigmentation in Europeans show signals of positive selection in present-day populations. Recently, genome-wide association studies have highlighted the highly polygenic nature of skin pigmentation. It is unclear whether selection has operated on all of these genetic variants or just a subset. By studying variation in over a thousand ancient genomes from West Eurasia covering 40,000 y, we are able to study both the aggregate behavior of pigmentation-associated variants and the evolutionary history of individual variants. We find that the evolution of light skin pigmentation in Europeans was driven by frequency changes in a relatively small fraction of the genetic variants that are associated with variation in the trait today. Skin pigmentation is a classic example of a polygenic trait that has experienced directional selection in humans. Genome-wide association studies have identified well over a hundred pigmentation-associated loci, and genomic scans in present-day and ancient populations have identified selective sweeps for a small number of light pigmentation-associated alleles in Europeans. It is unclear whether selection has operated on all of the genetic variation associated with skin pigmentation as opposed to just a small number of large-effect variants. Here, we address this question using ancient DNA from 1,158 individuals from West Eurasia covering a period of 40,000 y combined with genome-wide association summary statistics from the UK Biobank. We find a robust signal of directional selection in ancient West Eurasians on 170 skin pigmentation-associated variants ascertained in the UK Biobank. However, we also show that this signal is driven by a limited number of large-effect variants. Consistent with this observation, we find that a polygenic selection test in present-day populations fails to detect selection with the full set of variants. Our data allow us to disentangle the effects of admixture and selection. Most notably, a large-effect variant at SLC24A5 was introduced to Western Europe by migrations of Neolithic farming populations but continued to be under selection post-admixture. This study shows that the response to selection for light skin pigmentation in West Eurasia was driven by a relatively small proportion of the variants that are associated with present-day phenotypic variation.
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Meeks KAC, Bentley AR, Adeyemo AA, Rotimi CN. Evolutionary forces in diabetes and hypertension pathogenesis in Africans. Hum Mol Genet 2021; 30:R110-R118. [PMID: 33734377 DOI: 10.1093/hmg/ddaa238] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2020] [Revised: 10/16/2020] [Accepted: 10/22/2020] [Indexed: 11/12/2022] Open
Abstract
Rates of type 2 diabetes (T2D) and hypertension are increasing rapidly in urbanizing sub-Saharan Africa (SSA). While lifestyle factors drive the increases in T2D and hypertension prevalence, evidence across populations shows that genetic variation, which is driven by evolutionary forces including a natural selection that shaped the human genome, also plays a role. Here we report the evidence for the effect of selection in African genomes on mechanisms underlying T2D and hypertension, including energy metabolism, adipose tissue biology, insulin action and salt retention. Selection effects found for variants in genes PPARA and TCF7L2 may have enabled Africans to respond to nutritional challenges by altering carbohydrate and lipid metabolism. Likewise, African-ancestry-specific characteristics of adipose tissue biology (low visceral adipose tissue [VAT], high intermuscular adipose tissue and a strong association between VAT and adiponectin) may have been selected for in response to nutritional and infectious disease challenges in the African environment. Evidence for selection effects on insulin action, including insulin resistance and secretion, has been found for several genes including MPHOSPH9, TMEM127, ZRANB3 and MC3R. These effects may have been historically adaptive in critical conditions, such as famine and inflammation. A strong correlation between hypertension susceptibility variants and latitude supports the hypothesis of selection for salt retention mechanisms in warm, humid climates. Nevertheless, adaptive genomics studies in African populations are scarce. More work is needed, particularly genomics studies covering the wide diversity of African populations in SSA and Africans in diaspora, as well as further functional assessment of established risk loci.
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Affiliation(s)
- Karlijn A C Meeks
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Amy R Bentley
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Adebowale A Adeyemo
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Charles N Rotimi
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
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Khrunin AV, Khvorykh GV, Fedorov AN, Limborska SA. Genomic landscape of the signals of positive natural selection in populations of Northern Eurasia: A view from Northern Russia. PLoS One 2020; 15:e0228778. [PMID: 32023328 PMCID: PMC7001972 DOI: 10.1371/journal.pone.0228778] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2019] [Accepted: 01/23/2020] [Indexed: 12/15/2022] Open
Abstract
Natural selection of beneficial genetic variants played a critical role in human adaptation to a wide range of environmental conditions. Northern Eurasia, despite its severe climate, is home to lots of ethnically diverse populations. The genetic variants associated with the survival of these populations have hardly been analyzed. We searched for the genomic signatures of positive selection in (1) the genome-wide microarray data of 432 people from eight different northern Russian populations and (2) the whole-genome sequences of 250 people from Northern Eurasia from a public repository through testing the extended haplotype homozigosity (EHH) and direct comparison of allele frequency, respectively. The 20 loci with the strongest selection signals were characterized in detail. Among the top EHH hits were the NRG3 and NBEA genes, which are involved in the development and functioning of the neural system, the PTPRM gene, which mediates cell-cell interactions and adhesion, and a region on chromosome 4 (chr4:28.7-28.9 Mb) that contained several loci affiliated with different classes of non-coding RNAs (RN7SL101P, MIR4275, MESTP3, and LINC02364). NBEA and the region on chromosome 4 were novel selection targets that were identified for the first time in Western Siberian populations. Cross-population comparisons of EHH profiles suggested a particular role for the chr4:28.7-28.9 Mb region in the local adaptation of Western Siberians. The strongest selection signal identified in Siberian sequenced genomes was formed by six SNPs on chromosome 11 (chr11:124.9-125.2 Mb). This region included well-known genes SLC37A2 and PKNOX2. SLC37A2 is most-highly expressed in the gut. Its expression is regulated by vitamin D, which is often deficient in northern regions. The PKNOX2 gene is a transcription factor of the homeobox family that is expressed in the brain and many other tissues. This gene is associated with alcohol addiction, which is widespread in many Northern Eurasian populations.
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Affiliation(s)
- Andrey V. Khrunin
- Department of Molecular Bases of Human Genetics, Institute of Molecular Genetics of Russian Academy of Sciences, Moscow, Russia
| | - Gennady V. Khvorykh
- Department of Molecular Bases of Human Genetics, Institute of Molecular Genetics of Russian Academy of Sciences, Moscow, Russia
| | - Alexei N. Fedorov
- Department of Molecular Bases of Human Genetics, Institute of Molecular Genetics of Russian Academy of Sciences, Moscow, Russia
- Department of Medicine, University of Toledo, Toledo, Ohio, United States of America
| | - Svetlana A. Limborska
- Department of Molecular Bases of Human Genetics, Institute of Molecular Genetics of Russian Academy of Sciences, Moscow, Russia
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Whole-Genome Sequencing Identifies the Egl Nine Homologue 3 (egln3/phd3) and Protein Phosphatase 1 Regulatory Inhibitor Subunit 2 (PPP1R2P1) Associated with High-Altitude Polycythemia in Tibetans at High Altitude. DISEASE MARKERS 2019; 2019:5946461. [PMID: 31827636 PMCID: PMC6881591 DOI: 10.1155/2019/5946461] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/18/2019] [Accepted: 09/06/2019] [Indexed: 01/29/2023]
Abstract
Background The hypoxic conditions at high altitudes are great threats to survival, causing pressure for adaptation. More and more high-altitude denizens are not adapted with the condition known as high-altitude polycythemia (HAPC) that featured excessive erythrocytosis. As a high-altitude sickness, the etiology of HAPC is still unclear. Methods In this study, we reported the whole-genome sequencing-based study of 10 native Tibetans with HAPC and 10 control subjects followed by genotyping of selected 21 variants from discovered single nucleotide variants (SNVs) in an independent cohort (232 cases and 266 controls). Results We discovered the egl nine homologue 3 (egln3/phd3) (14q13.1, rs1346902, P = 1.91 × 10−5) and PPP1R2P1 (Protein Phosphatase 1 Regulatory Inhibitor Subunit 2) gene (6p21.32, rs521539, P = 0.012). Our results indicated an unbiased framework to identify etiological mechanisms of HAPC and showed that egln3/phd3 and PPP1R2P1 may be associated with the susceptibility to HAPC. Egln3/phd3b is associated with hypoxia-inducible factor subunit α (HIFα). Protein Phosphatase 1 Regulatory Inhibitor is associated with reactive oxygen species (ROS) and oxidative stress. Conclusions Our genome sequencing conducted in Tibetan HAPC patients identified egln3/phd3 and PPP1R2P1 associated with HAPC.
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Fernandes V, Brucato N, Ferreira JC, Pedro N, Cavadas B, Ricaut FX, Alshamali F, Pereira L. Genome-Wide Characterization of Arabian Peninsula Populations: Shedding Light on the History of a Fundamental Bridge between Continents. Mol Biol Evol 2019; 36:575-586. [PMID: 30649405 DOI: 10.1093/molbev/msz005] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
The Arabian Peninsula (AP) was an important crossroad between Africa, Asia, and Europe, being the cradle of the structure defining these main human population groups, and a continuing path for their admixture. The screening of 741,000 variants in 420 Arabians and 80 Iranians allowed us to quantify the dominant sub-Saharan African admixture in the west of the peninsula, whereas South Asian and Levantine/European influence was stronger in the east, leading to a rift between western and eastern sides of the Peninsula. Dating of the admixture events indicated that Indian Ocean slave trade and Islamization periods were important moments in the genetic makeup of the region. The western-eastern axis was also observable in terms of positive selection of diversity conferring lactose tolerance, with the West AP developing local adaptation and the East AP acquiring the derived allele selected in European populations and existing in South Asia. African selected malaria resistance through the DARC gene was enriched in all Arabian genomes, especially in the western part. Clear European influences associated with skin and eye color were equally frequent across the Peninsula.
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Affiliation(s)
- Veronica Fernandes
- i3S - Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Porto, Portugal.,IPATIMUP - Instituto de Patologia e Imunologia Molecular da Universidade do Porto, Porto, Portugal
| | - Nicolas Brucato
- Laboratoire Évolution & Diversité Biologique (EDB UMR 5174), Université de Toulouse Midi-Pyrénées, CNRS, IRD, UPS. 118 route de Narbonne, Bat 4R1, 31062 Toulouse cedex 9, France
| | - Joana C Ferreira
- i3S - Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Porto, Portugal.,IPATIMUP - Instituto de Patologia e Imunologia Molecular da Universidade do Porto, Porto, Portugal.,Instituto de Ciências Biomédicas Abel Salazar (ICBAS), Universidade do Porto, Porto, Portugal
| | - Nicole Pedro
- i3S - Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Porto, Portugal.,IPATIMUP - Instituto de Patologia e Imunologia Molecular da Universidade do Porto, Porto, Portugal
| | - Bruno Cavadas
- i3S - Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Porto, Portugal.,IPATIMUP - Instituto de Patologia e Imunologia Molecular da Universidade do Porto, Porto, Portugal
| | - François-Xavier Ricaut
- Laboratoire Évolution & Diversité Biologique (EDB UMR 5174), Université de Toulouse Midi-Pyrénées, CNRS, IRD, UPS. 118 route de Narbonne, Bat 4R1, 31062 Toulouse cedex 9, France
| | - Farida Alshamali
- Department of Forensic Sciences and Criminology, Dubai Police General Headquarters, Dubai, United Arab Emirates
| | - Luisa Pereira
- i3S - Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Porto, Portugal.,IPATIMUP - Instituto de Patologia e Imunologia Molecular da Universidade do Porto, Porto, Portugal.,Faculdade de Medicina da Universidade do Porto, Porto, Portugal
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Voskarides K. Combination of 247 Genome-Wide Association Studies Reveals High Cancer Risk as a Result of Evolutionary Adaptation. Mol Biol Evol 2019; 35:473-485. [PMID: 29220501 PMCID: PMC5850495 DOI: 10.1093/molbev/msx305] [Citation(s) in RCA: 38] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
Analysis of GLOBOCAN-2012 data shows clearly here that cancer incidence worldwide is highly related with low average annual temperatures and extreme low temperatures. This applies for all cancers together or separately for many frequent or rare cancer types (all cancers P = 9.49×10-18). Supporting fact is that Inuit people, living at extreme low temperatures, have the highest cancer rates today. Hypothesizing an evolutionary explanation, 240 cancer genome-wide association studies, and seven genome-wide association studies for cold and high-altitude adaptation were combined. A list of 1,377 cancer-associated genes was created to initially investigate whether cold selected genes are enriched with cancer-associated genes. Among Native Americans, Inuit and Eskimos, the highest association was observed for Native Americans (P = 6.7×10-5). An overall or a meta-analysis approach confirmed further this result. Similar approach for three populations living at extreme high altitude, revealed high association for Andeans-Tibetans (P = 1.3×10-11). Overall analysis or a meta-analysis was also significant. A separate analysis showed special selection for tumor suppressor genes. These results can be viewed along with those of previous functional studies that showed that reduced apoptosis potential due to specific p53 variants (the most important tumor suppressor gene) is beneficial in high-altitude and cold environments. In conclusion, this study shows that genetic variants selected for adaptation at extreme environmental conditions can increase cancer risk later on age. This is in accordance with antagonistic pleiotropy hypothesis.
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Congenital and evolutionary modulations of hypoxia sensing and their erythroid phenotype. CURRENT OPINION IN PHYSIOLOGY 2019. [DOI: 10.1016/j.cophys.2018.12.001] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
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11
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Molinaro L, Pagani L. Human evolutionary history of Eastern Africa. Curr Opin Genet Dev 2018; 53:134-139. [DOI: 10.1016/j.gde.2018.10.002] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2018] [Revised: 08/31/2018] [Accepted: 10/08/2018] [Indexed: 01/16/2023]
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Jablonski NG, Chaplin G. The roles of vitamin D and cutaneous vitamin D production in human evolution and health. INTERNATIONAL JOURNAL OF PALEOPATHOLOGY 2018; 23:54-59. [PMID: 29606375 DOI: 10.1016/j.ijpp.2018.01.005] [Citation(s) in RCA: 39] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/01/2017] [Revised: 01/24/2018] [Accepted: 01/25/2018] [Indexed: 06/08/2023]
Abstract
Most of the vitamin D necessary for the maintenance of human health and successful reproduction is made in the skin under the influence of a narrow portion of the electromagnetic spectrum emitted from the sun, namely ultraviolet B radiation (UVB). During the course of human evolution, skin pigmentation has evolved to afford protection against high levels of UVR while still permitting cutaneous production of vitamin D. Similar pigmentation phenotypes evolved repeatedly as the result of independent genetic events when isolated human populations dispersed into habitats of extremely low or high UVB. The gradient of skin color seen in modern human populations is evidence of the operation of two clines, one favoring photoprotection near the equator, the other favoring vitamin D production nearer the poles. Through time, human adaptations to different solar regimes have become more cultural than biological. Rapid human migrations, increasing urbanization, and changes in lifestyle have created mismatches between skin pigmentation and environmental conditions leading to vitamin D deficiency. The prevalence and significance for health of vitamin D deficiencies, and the definition of optimal levels of vitamin D in the bloodstream are subjects of intense research and debate, but two of the causes of vitamin D deficiency - lack of sun exposure and abandonment of vitamin D rich foods in the diet - are traceable to changes in human lifestyles accompanying urbanization in prehistory.
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Affiliation(s)
- Nina G Jablonski
- Department of Anthropology, The Pennsylvania State University, 409 Carpenter Building, University Park, PA 16802, United States.
| | - George Chaplin
- Department of Anthropology, The Pennsylvania State University, 409 Carpenter Building, University Park, PA 16802, United States
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Zehra R, Abbasi AA. Homo sapiens-Specific Binding Site Variants within Brain Exclusive Enhancers Are Subject to Accelerated Divergence across Human Population. Genome Biol Evol 2018; 10:956-966. [PMID: 29608725 PMCID: PMC5952923 DOI: 10.1093/gbe/evy052] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/06/2018] [Indexed: 01/04/2023] Open
Abstract
Empirical assessments of human accelerated noncoding DNA frgaments have delineated presence of many cis-regulatory elements. Enhancers make up an important category of such accelerated cis-regulatory elements that efficiently control the spatiotemporal expression of many developmental genes. Establishing plausible reasons for accelerated enhancer sequence divergence in Homo sapiens has been termed significant in various previously published studies. This acceleration by including closely related primates and archaic human data has the potential to open up evolutionary avenues for deducing present-day brain structure. This study relied on empirically confirmed brain exclusive enhancers to avoid any misjudgments about their regulatory status and categorized among them a subset of enhancers with an exceptionally accelerated rate of lineage specific divergence in humans. In this assorted set, 13 distinct transcription factor binding sites were located that possessed unique existence in humans. Three of 13 such sites belonging to transcription factors SOX2, RUNX1/3, and FOS/JUND possessed single nucleotide variants that made them unique to H. sapiens upon comparisons with Neandertal and Denisovan orthologous sequences. These variants modifying the binding sites in modern human lineage were further substantiated as single nucleotide polymorphisms via exploiting 1000 Genomes Project Phase3 data. Long range haplotype based tests laid out evidence of positive selection to be governing in African population on two of the modern human motif modifying alleles with strongest results for SOX2 binding site. In sum, our study acknowledges acceleration in noncoding regulatory landscape of the genome and highlights functional parts within it to have undergone accelerated divergence in present-day human population.
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Affiliation(s)
| | - Amir Ali Abbasi
- National Center for Bioinformatics, Programme of Comparative and Evolutionary Genomics, Faculty of Biological Sciences, Quaid-i-Azam University, Islamabad, Pakistan
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Crawford NG, Kelly DE, Hansen MEB, Beltrame MH, Fan S, Bowman SL, Jewett E, Ranciaro A, Thompson S, Lo Y, Pfeifer SP, Jensen JD, Campbell MC, Beggs W, Hormozdiari F, Mpoloka SW, Mokone GG, Nyambo T, Meskel DW, Belay G, Haut J, Rothschild H, Zon L, Zhou Y, Kovacs MA, Xu M, Zhang T, Bishop K, Sinclair J, Rivas C, Elliot E, Choi J, Li SA, Hicks B, Burgess S, Abnet C, Watkins-Chow DE, Oceana E, Song YS, Eskin E, Brown KM, Marks MS, Loftus SK, Pavan WJ, Yeager M, Chanock S, Tishkoff SA. Loci associated with skin pigmentation identified in African populations. Science 2017; 358:eaan8433. [PMID: 29025994 PMCID: PMC5759959 DOI: 10.1126/science.aan8433] [Citation(s) in RCA: 198] [Impact Index Per Article: 28.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2017] [Accepted: 10/03/2017] [Indexed: 12/13/2022]
Abstract
Despite the wide range of skin pigmentation in humans, little is known about its genetic basis in global populations. Examining ethnically diverse African genomes, we identify variants in or near SLC24A5, MFSD12, DDB1, TMEM138, OCA2, and HERC2 that are significantly associated with skin pigmentation. Genetic evidence indicates that the light pigmentation variant at SLC24A5 was introduced into East Africa by gene flow from non-Africans. At all other loci, variants associated with dark pigmentation in Africans are identical by descent in South Asian and Australo-Melanesian populations. Functional analyses indicate that MFSD12 encodes a lysosomal protein that affects melanogenesis in zebrafish and mice, and that mutations in melanocyte-specific regulatory regions near DDB1/TMEM138 correlate with expression of ultraviolet response genes under selection in Eurasians.
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Affiliation(s)
- Nicholas G Crawford
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Derek E Kelly
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Genomics and Computational Biology Graduate Program, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Matthew E B Hansen
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Marcia H Beltrame
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Shaohua Fan
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Shanna L Bowman
- Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia Research Institute, Philadelphia, PA 19104, USA
- Department of Pathology and Laboratory Medicine and Department of Physiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Ethan Jewett
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley, CA 94704, USA
- Department of Statistics, University of California, Berkeley, Berkeley, CA 94704, USA
| | - Alessia Ranciaro
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Simon Thompson
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Yancy Lo
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Susanne P Pfeifer
- School of Life Sciences, Arizona State University, Tempe, AZ 85287, USA
| | - Jeffrey D Jensen
- School of Life Sciences, Arizona State University, Tempe, AZ 85287, USA
| | - Michael C Campbell
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Biology, Howard University, Washington, DC 20059, USA
| | - William Beggs
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Farhad Hormozdiari
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
- Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA 02142, USA
| | | | - Gaonyadiwe George Mokone
- Department of Biomedical Sciences, University of Botswana School of Medicine, Gaborone, Botswana
| | - Thomas Nyambo
- Department of Biochemistry, Muhimbili University of Health and Allied Sciences, Dar es Salaam, Tanzania
| | | | - Gurja Belay
- Department of Biology, Addis Ababa University, Addis Ababa, Ethiopia
| | - Jake Haut
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Harriet Rothschild
- Stem Cell Program, Division of Hematology and Oncology, Pediatric Hematology Program, Boston Children's Hospital and Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA
| | - Leonard Zon
- Stem Cell Program, Division of Hematology and Oncology, Pediatric Hematology Program, Boston Children's Hospital and Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA
- Howard Hughes Medical Institute, Harvard Medical School, Boston, MA 02115, USA
| | - Yi Zhou
- Stem Cell Program, Division of Hematology and Oncology, Pediatric Hematology Program, Boston Children's Hospital and Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA
- Harvard Stem Cell Institute, Harvard University, Cambridge, MA 02138, USA
| | - Michael A Kovacs
- Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Mai Xu
- Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Tongwu Zhang
- Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Kevin Bishop
- Translational and Functional Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Jason Sinclair
- Translational and Functional Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Cecilia Rivas
- Genetic Disease Research Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Eugene Elliot
- Genetic Disease Research Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Jiyeon Choi
- Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Shengchao A Li
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD 20892, USA
- Frederick National Laboratory for Cancer Research, Leidos Biomedical Research Inc., Frederick, MD 21701, USA
| | - Belynda Hicks
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD 20892, USA
- Frederick National Laboratory for Cancer Research, Leidos Biomedical Research Inc., Frederick, MD 21701, USA
| | - Shawn Burgess
- Translational and Functional Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Christian Abnet
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD 20892, USA
| | - Dawn E Watkins-Chow
- Genetic Disease Research Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Elena Oceana
- Department of Molecular Pharmacology, Physiology and Biotechnology, Brown University, Providence, RI 02912, USA
| | - Yun S Song
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley, CA 94704, USA
- Department of Statistics, University of California, Berkeley, Berkeley, CA 94704, USA
- Chan Zuckerberg Biohub, San Francisco, CA 94158, USA
- Department of Biology, School of Arts and Sciences, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Mathematics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Eleazar Eskin
- Department of Computer Science and Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Kevin M Brown
- Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Michael S Marks
- Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia Research Institute, Philadelphia, PA 19104, USA
- Department of Pathology and Laboratory Medicine and Department of Physiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Stacie K Loftus
- Genetic Disease Research Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - William J Pavan
- Genetic Disease Research Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Meredith Yeager
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD 20892, USA
- Frederick National Laboratory for Cancer Research, Leidos Biomedical Research Inc., Frederick, MD 21701, USA
| | - Stephen Chanock
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD 20892, USA
| | - Sarah A Tishkoff
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
- Department of Biology, School of Arts and Sciences, University of Pennsylvania, Philadelphia, PA 19104, USA
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15
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High-altitude adaptation in humans: from genomics to integrative physiology. J Mol Med (Berl) 2017; 95:1269-1282. [PMID: 28951950 DOI: 10.1007/s00109-017-1584-7] [Citation(s) in RCA: 60] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2017] [Revised: 08/07/2017] [Accepted: 08/20/2017] [Indexed: 12/19/2022]
Abstract
About 1.2 to 33% of high-altitude populations suffer from Monge's disease or chronic mountain sickness (CMS). Number of factors such as age, sex, and population of origin (older, male, Andean) contribute to the percentage reported from a variety of samples. It is estimated that there are around 83 million people who live at altitudes > 2500 m worldwide and are at risk for CMS. In this review, we focus on a human "experiment in nature" in various high-altitude locations in the world-namely, Andean, Tibetan, and Ethiopian populations that have lived under chronic hypoxia conditions for thousands of years. We discuss the adaptive as well as mal-adaptive changes at the genomic and physiological levels. Although different genes seem to be involved in adaptation in the three populations, we can observe convergence at genetic and signaling, as well as physiological levels. What is important is that we and others have shown that lessons learned from the genes mined at high altitude can be helpful in better understanding and treating diseases that occur at sea level. We discuss two such examples: EDNRB and SENP1 and their role in cardiac tolerance and in the polycythemic response, respectively.
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16
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Diversity and inclusion in genomic research: why the uneven progress? J Community Genet 2017; 8:255-266. [PMID: 28770442 PMCID: PMC5614884 DOI: 10.1007/s12687-017-0316-6] [Citation(s) in RCA: 168] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2017] [Accepted: 06/29/2017] [Indexed: 12/15/2022] Open
Abstract
Conducting genomic research in diverse populations has led to numerous advances in our understanding of human history, biology, and health disparities, in addition to discoveries of vital clinical significance. Conducting genomic research in diverse populations is also important in ensuring that the genomic revolution does not exacerbate health disparities by facilitating discoveries that will disproportionately benefit well-represented populations. Despite the general agreement on the need for genomic research in diverse populations in terms of equity and scientific progress, genomic research remains largely focused on populations of European descent. In this article, we describe the rationale for conducting genomic research in diverse populations by reviewing examples of advances facilitated by their inclusion. We also explore some of the factors that perpetuate the disproportionate attention on well-represented populations. Finally, we discuss ongoing efforts to ameliorate this continuing bias. Collaborative and intensive efforts at all levels of research, from the funding of studies to the publication of their findings, will be necessary to ensure that genomic research does not conserve historical inequalities or curtail the contribution that genomics could make to the health of all humanity.
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17
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Tekola-Ayele F, Peprah E. Examining How Our Shared Evolutionary History Shapes Future Disease Outcomes. Glob Heart 2017; 12:169-171. [PMID: 28302556 DOI: 10.1016/j.gheart.2017.01.008] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2017] [Accepted: 01/13/2017] [Indexed: 01/13/2023] Open
Abstract
Cardiometabolic diseases are major contributors to mortality and morbidity, and their burden displays global and regional disparities. Gene-environment interactions contribute to the pathogenesis of cardiometabolic diseases. Population differences in genetic structure, ancient environmental pressures that shape the human genome, and early life environmental adversities (e.g., in utero conditions) all contribute to observed disparities in global cardiometabolic diseases. The genetic and sociocultural diversity of global populations presents opportunities for discovering genomic loci that influence cardiometabolic diseases as illustrated by a few genetic, epigenetic, and population-genetic discoveries leading to notable understanding of disease mechanisms. However, African, Latin American and Hispanic, and indigenous peoples represent <4% of all genome-wide association study samples analyzed to date. Using examples of recent studies in African populations, we discuss the crucial importance of conducting genomic studies in ancestrally diverse populations to understand disease mechanisms and to prepare fertile ground for future delivery of precise health care to all individuals.
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Affiliation(s)
- Fasil Tekola-Ayele
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA.
| | - Emmanuel Peprah
- Center for Translation Research and Implementation Science, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
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18
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Rotimi CN, Tekola-Ayele F, Baker JL, Shriner D. The African diaspora: history, adaptation and health. Curr Opin Genet Dev 2016; 41:77-84. [PMID: 27644073 DOI: 10.1016/j.gde.2016.08.005] [Citation(s) in RCA: 35] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2016] [Revised: 06/30/2016] [Accepted: 08/02/2016] [Indexed: 01/13/2023]
Abstract
The trans-Atlantic slave trade brought millions of Africans to the New World. Advances in genomics are providing novel insights into the history and health of Africans and the diasporan populations. Recent examples reviewed here include the unraveling of substantial hunter-gatherer and 'Eurasian' admixtures across sub-Saharan Africa, expanding our understanding of ancestral African genetics; the global ubiquity of mixed ancestry; the revealing of African ancestry in Latin Americans that likely derived from the slave trade; and understanding of the ancestral backgrounds of APOL1 and LPL found to influence kidney disease and lipid levels, respectively, providing specific insights into disease etiology and health disparities.
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Affiliation(s)
- Charles N Rotimi
- Center for Research on Genomics and Global Health National Human Genome Research Institute, Building 12A, Room 4047 12 South Drive, Bethesda, MD 20892, USA.
| | - Fasil Tekola-Ayele
- Center for Research on Genomics and Global Health National Human Genome Research Institute, Building 12A, Room 4047 12 South Drive, Bethesda, MD 20892, USA
| | - Jennifer L Baker
- Center for Research on Genomics and Global Health National Human Genome Research Institute, Building 12A, Room 4047 12 South Drive, Bethesda, MD 20892, USA
| | - Daniel Shriner
- Center for Research on Genomics and Global Health National Human Genome Research Institute, Building 12A, Room 4047 12 South Drive, Bethesda, MD 20892, USA
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19
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He Y, Wang M, Huang X, Li R, Xu H, Xu S, Jin L. A probabilistic method for testing and estimating selection differences between populations. Genome Res 2015; 25:1903-9. [PMID: 26463656 PMCID: PMC4665011 DOI: 10.1101/gr.192336.115] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2015] [Accepted: 10/13/2015] [Indexed: 01/18/2023]
Abstract
Human populations around the world encounter various environmental challenges and, consequently, develop genetic adaptations to different selection forces. Identifying the differences in natural selection between populations is critical for understanding the roles of specific genetic variants in evolutionary adaptation. Although numerous methods have been developed to detect genetic loci under recent directional selection, a probabilistic solution for testing and quantifying selection differences between populations is lacking. Here we report the development of a probabilistic method for testing and estimating selection differences between populations. By use of a probabilistic model of genetic drift and selection, we showed that logarithm odds ratios of allele frequencies provide estimates of the differences in selection coefficients between populations. The estimates approximate a normal distribution, and variance can be estimated using genome-wide variants. This allows us to quantify differences in selection coefficients and to determine the confidence intervals of the estimate. Our work also revealed the link between genetic association testing and hypothesis testing of selection differences. It therefore supplies a solution for hypothesis testing of selection differences. This method was applied to a genome-wide data analysis of Han and Tibetan populations. The results confirmed that both the EPAS1 and EGLN1 genes are under statistically different selection in Han and Tibetan populations. We further estimated differences in the selection coefficients for genetic variants involved in melanin formation and determined their confidence intervals between continental population groups. Application of the method to empirical data demonstrated the outstanding capability of this novel approach for testing and quantifying differences in natural selection.
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Affiliation(s)
- Yungang He
- Chinese Academy of Sciences Key Laboratory of Computational Biology, Chinese Academy of Sciences-Max Planck Society Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Minxian Wang
- Chinese Academy of Sciences Key Laboratory of Computational Biology, Chinese Academy of Sciences-Max Planck Society Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Xin Huang
- Chinese Academy of Sciences Key Laboratory of Computational Biology, Chinese Academy of Sciences-Max Planck Society Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Ran Li
- Chinese Academy of Sciences Key Laboratory of Computational Biology, Chinese Academy of Sciences-Max Planck Society Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Hongyang Xu
- Chinese Academy of Sciences Key Laboratory of Computational Biology, Chinese Academy of Sciences-Max Planck Society Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Shuhua Xu
- Chinese Academy of Sciences Key Laboratory of Computational Biology, Chinese Academy of Sciences-Max Planck Society Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Li Jin
- Chinese Academy of Sciences Key Laboratory of Computational Biology, Chinese Academy of Sciences-Max Planck Society Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China; State Key Laboratory of Genetic Engineering and Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai 200433, China
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20
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Ronen R, Tesler G, Akbari A, Zakov S, Rosenberg NA, Bafna V. Predicting Carriers of Ongoing Selective Sweeps without Knowledge of the Favored Allele. PLoS Genet 2015; 11:e1005527. [PMID: 26402243 PMCID: PMC4581834 DOI: 10.1371/journal.pgen.1005527] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2015] [Accepted: 08/24/2015] [Indexed: 11/19/2022] Open
Abstract
Methods for detecting the genomic signatures of natural selection have been heavily studied, and they have been successful in identifying many selective sweeps. For most of these sweeps, the favored allele remains unknown, making it difficult to distinguish carriers of the sweep from non-carriers. In an ongoing selective sweep, carriers of the favored allele are likely to contain a future most recent common ancestor. Therefore, identifying them may prove useful in predicting the evolutionary trajectory—for example, in contexts involving drug-resistant pathogen strains or cancer subclones. The main contribution of this paper is the development and analysis of a new statistic, the Haplotype Allele Frequency (HAF) score. The HAF score, assigned to individual haplotypes in a sample, naturally captures many of the properties shared by haplotypes carrying a favored allele. We provide a theoretical framework for computing expected HAF scores under different evolutionary scenarios, and we validate the theoretical predictions with simulations. As an application of HAF score computations, we develop an algorithm (PreCIOSS: Predicting Carriers of Ongoing Selective Sweeps) to identify carriers of the favored allele in selective sweeps, and we demonstrate its power on simulations of both hard and soft sweeps, as well as on data from well-known sweeps in human populations. Methods for detecting the genomic signatures of natural selection have been heavily studied, and they have been successful in identifying genomic regions under positive selection. However, methods that detect positive selective sweeps do not typically identify the favored allele, or even the haplotypes carrying the favored allele. The main contribution of this paper is the development and analysis of a new statistic (the HAF score), assigned to individual haplotypes. Using both theoretical analyses and simulations, we describe how the HAF scores differ for carriers and non-carriers of the favored allele, and how they change dynamically during a selective sweep. We also develop an algorithm, PreCIOSS, for separating carriers and non-carriers. Our tool has broad applicability as carriers of the favored allele are likely to contain a future most recent common ancestor. Therefore, identifying them may prove useful in predicting the evolutionary trajectory—for example, in contexts involving drug-resistant pathogen strains or cancer subclones.
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Affiliation(s)
- Roy Ronen
- Bioinformatics Graduate Program, University of California, San Diego, La Jolla, California, United States of America
| | - Glenn Tesler
- Department of Mathematics, University of California, San Diego, La Jolla, California, United States of America
| | - Ali Akbari
- Department of Electrical & Computer Engineering, University of California, San Diego, La Jolla, California, United States of America
| | - Shay Zakov
- Department of Computer Science & Engineering, University of California, San Diego, La Jolla, California, United States of America
| | - Noah A. Rosenberg
- Department of Biology, Stanford University, Stanford, California, United States of America
| | - Vineet Bafna
- Department of Computer Science & Engineering, University of California, San Diego, La Jolla, California, United States of America
- * E-mail:
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