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Lorenzini PA, Gusareva ES, Ghosh AG, Ramli NAB, Preiser PR, Kim HL. Population-specific positive selection on low CR1 expression in malaria-endemic regions. PLoS One 2023; 18:e0280282. [PMID: 36626386 PMCID: PMC9831336 DOI: 10.1371/journal.pone.0280282] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Accepted: 12/25/2022] [Indexed: 01/11/2023] Open
Abstract
Complement Receptor Type 1 (CR1) is a malaria-associated gene that encodes a transmembrane receptor of erythrocytes and is crucial for malaria parasite invasion. The expression of CR1 contributes to the rosetting of erythrocytes in the brain bloodstream, causing cerebral malaria, the most severe form of the disease. Here, we study the history of adaptation against malaria by analyzing selection signals in the CR1 gene. We used whole-genome sequencing datasets of 907 healthy individuals from malaria-endemic and non-endemic populations. We detected robust positive selection in populations from the hyperendemic regions of East India and Papua New Guinea. Importantly, we identified a new adaptive variant, rs12034598, which is associated with a slower rate of erythrocyte sedimentation and is linked with a variant associated with low levels of CR1 expression. The combination of the variants likely drives natural selection. In addition, we identified a variant rs3886100 under positive selection in West Africans, which is also related to a low level of CR1 expression in the brain. Our study shows the fine-resolution history of positive selection in the CR1 gene and suggests a population-specific history of CR1 adaptation to malaria. Notably, our novel approach using population genomic analyses allows the identification of protective variants that reduce the risk of malaria infection without the need for patient samples or malaria individual medical records. Our findings contribute to understanding of human adaptation against cerebral malaria.
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Affiliation(s)
- Paolo Alberto Lorenzini
- Asian School of the Environment, Nanyang Technological University, Singapore, Singapore
- The GenomeAsia 100K Consortium, Singapore, Singapore
| | - Elena S. Gusareva
- Asian School of the Environment, Nanyang Technological University, Singapore, Singapore
- The GenomeAsia 100K Consortium, Singapore, Singapore
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore, Singapore
| | - Amit Gourav Ghosh
- Asian School of the Environment, Nanyang Technological University, Singapore, Singapore
- The GenomeAsia 100K Consortium, Singapore, Singapore
| | - Nurul Adilah Binte Ramli
- Asian School of the Environment, Nanyang Technological University, Singapore, Singapore
- The GenomeAsia 100K Consortium, Singapore, Singapore
| | - Peter Rainer Preiser
- School of Biological Sciences, Nanyang Technological University, Singapore, Singapore
| | - Hie Lim Kim
- Asian School of the Environment, Nanyang Technological University, Singapore, Singapore
- The GenomeAsia 100K Consortium, Singapore, Singapore
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore, Singapore
- * E-mail:
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Hoh BP, Deng L, Xu S. The Peopling and Migration History of the Natives in Peninsular Malaysia and Borneo: A Glimpse on the Studies Over the Past 100 years. Front Genet 2022; 13:767018. [PMID: 35154269 PMCID: PMC8829068 DOI: 10.3389/fgene.2022.767018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2021] [Accepted: 01/07/2022] [Indexed: 12/05/2022] Open
Abstract
Southeast Asia (SEA) has one of the longest records of modern human habitation out-of-Africa. Located at the crossroad of the mainland and islands of SEA, Peninsular Malaysia is an important piece of puzzle to the map of peopling and migration history in Asia, a question that is of interest to many anthropologists, archeologists, and population geneticists. This review aims to revisit our understanding to the population genetics of the natives from Peninsular Malaysia and Borneo over the past century based on the chronology of the technology advancement: 1) Anthropological and Physical Characterization; 2) Blood Group Markers; 3) Protein Markers; 4) Mitochondrial and Autosomal DNA Markers; and 5) Whole Genome Analysis. Subsequently some missing gaps of the study are identified. In the later part of this review, challenges of studying the population genetics of natives will be elaborated. Finally, we conclude our review by reiterating the importance of unveiling migration history and genetic diversity of the indigenous populations as a steppingstone towards comprehending disease evolution and etiology.
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Affiliation(s)
- Boon-Peng Hoh
- Faculty of Medicine and Health Sciences, UCSI University, UCSI Hospital, Port Dickson, Malaysia
- *Correspondence: Boon-Peng Hoh,
| | - Lian Deng
- State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai, China
| | - Shuhua Xu
- State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai, China
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
- Department of Liver Surgery and Transplantation Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China
- Ministry of Education Key Laboratory of Contemporary Anthropology, School of Life Sciences, Human Phenome Institute, Fudan University, Shanghai, China
- School of Life Science and Technology, ShanghaiTech University, Shanghai, China
- Jiangsu Key Laboratory of Phylogenomics and Comparative Genomics, School of Life Sciences, Jiangsu Normal University, Xuzhou, China
- Henan Institute of Medical and Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, China
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, China
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Deng L, Pan Y, Wang Y, Chen H, Yuan K, Chen S, Lu D, Lu Y, Mokhtar SS, Rahman TA, Hoh BP, Xu S. Genetic connections and convergent evolution of tropical indigenous peoples in Asia. Mol Biol Evol 2021; 39:6481554. [PMID: 34940850 PMCID: PMC8826522 DOI: 10.1093/molbev/msab361] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Tropical indigenous peoples in Asia (TIA) attract much attention for their unique appearance, whereas their genetic history and adaptive evolution remain mysteries. We conducted a comprehensive study to characterize the genetic distinction and connection of broad geographical TIAs. Despite the diverse genetic makeup and large interarea genetic differentiation between the TIA groups, we identified a basal Asian ancestry (bASN) specifically shared by these populations. The bASN ancestry was relatively enriched in ancient Asian human genomes dated as early as ∼50,000 years before the present and diminished in more recent history. Notably, the bASN ancestry is unlikely to be derived from archaic hominins. Instead, we suggest it may be better modeled as a survived lineage of the initial peopling of Asia. Shared adaptations inherited from the ancient Asian ancestry were detected among the TIA groups (e.g., LIMS1 for hair morphology, and COL24A1 for bone formation), and they are enriched in neurological functions either at an identical locus (e.g., NKAIN3), or different loci in an identical gene (e.g., TENM4). The bASN ancestry could also have formed the substrate of the genetic architecture of the dark pigmentation observed in the TIA peoples. We hypothesize that phenotypic convergence of the dark pigmentation in TIAs could have resulted from parallel (e.g., DDB1/DAK) or genetic convergence driven by admixture (e.g., MTHFD1 and RAD18), new mutations (e.g., STK11), or notably purifying selection (e.g., MC1R). Our results provide new insights into the initial peopling of Asia and an advanced understanding of the phenotypic convergence of the TIA peoples.
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Affiliation(s)
- Lian Deng
- State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai 200438, China
| | - Yuwen Pan
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health,University of Chinese Academy of Sciences,Chinese Academy of Sciences, Shanghai 200031, China
| | - Yinan Wang
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health,University of Chinese Academy of Sciences,Chinese Academy of Sciences, Shanghai 200031, China
- Department of Liver Surgery and Transplantation Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Hao Chen
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health,University of Chinese Academy of Sciences,Chinese Academy of Sciences, Shanghai 200031, China
| | - Kai Yuan
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health,University of Chinese Academy of Sciences,Chinese Academy of Sciences, Shanghai 200031, China
| | - Sihan Chen
- Ministry of Education Key Laboratory of Contemporary Anthropology, School of Life Sciences, Human Phenome Institute, Fudan University, Shanghai 200438, China
| | - Dongsheng Lu
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health,University of Chinese Academy of Sciences,Chinese Academy of Sciences, Shanghai 200031, China
| | - Yan Lu
- State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai 200438, China
| | - Siti Shuhada Mokhtar
- Institute of Medical Molecular Biotechnology, Faculty of Medicine, Universiti Teknologi MARA, Sungai Buloh Campus, 47000 Sungai Buloh, Selangor, Malaysia
| | - Thuhairah Abdul Rahman
- Clinical Pathology Diagnostic Centre Research Laboratory, Faculty of Medicine, Universiti Teknologi MARA, Sungai Buloh Campus, 47000 Sungai Buloh, Selangor, Malaysia
| | - Boon-Peng Hoh
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health,University of Chinese Academy of Sciences,Chinese Academy of Sciences, Shanghai 200031, China
- Faculty of Medicine and Health Sciences, UCSI University, Jalan Menara Gading, UCSI Heights 56000 Cheras, Kuala Lumpur, Malaysia
| | - Shuhua Xu
- State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai 200438, China
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health,University of Chinese Academy of Sciences,Chinese Academy of Sciences, Shanghai 200031, China
- Department of Liver Surgery and Transplantation Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai 200032, China
- Ministry of Education Key Laboratory of Contemporary Anthropology, School of Life Sciences, Human Phenome Institute, Fudan University, Shanghai 200438, China
- School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China
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4
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Munajat MB, Rahim MAFA, Wahid W, Seri Rakna MIM, Divis PCS, Chuangchaiya S, Lubis IND, Osman E, Mohd Kasri MR, Idris ZM. Perceptions and prevention practices on malaria among the indigenous Orang Asli community in Kelantan, Peninsular Malaysia. Malar J 2021; 20:202. [PMID: 33906645 PMCID: PMC8077949 DOI: 10.1186/s12936-021-03741-y] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2020] [Accepted: 04/19/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Malaysia is on track towards malaria elimination. However, several cases of malaria still occur in the country. Contributing factors and communal aspects have noteworthy effects on any malaria elimination activities. Thus, assessing the community's knowledge, attitudes and practices (KAP) towards malaria is essential. This study was performed to evaluate KAP regarding malaria among the indigenous people (i.e. Orang Asli) in Peninsular Malaysia. METHODS A household-based cross-sectional study was conducted in five remote villages (clusters) of Orang Asli located in the State of Kelantan, a central region of the country. Community members aged six years and above were interviewed. Demographic, socio-economic and KAP data on malaria were collected using a structured questionnaire and analysed using descriptive statistics. RESULTS Overall, 536 individuals from 208 households were interviewed. Household indoor residual spraying (IRS) coverage and bed net ownership were 100% and 89.2%, respectively. A majority of respondents used mosquito bed nets every night (95.1%), but only 50.2% were aware that bed nets were used to prevent malaria. Nevertheless, almost all of the respondents (97.9%) were aware that malaria is transmitted by mosquitoes. Regarding practice for managing malaria, the most common practice adopted by the respondents was seeking treatment at the health facilities (70.9%), followed by self-purchase of medication from a local shop (12.7%), seeking treatment from a traditional healer (10.5%) and self-healing (5.9%). Concerning potential zoonotic malaria, about half of the respondents (47.2%) reported seeing monkeys from their houses and 20.1% reported entering nearby forests within the last 6 months. CONCLUSION This study found that most populations living in the villages have an acceptable level of knowledge and awareness about malaria. However, positive attitudes and practices concerning managing malaria require marked improvement.
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Affiliation(s)
- Mohd Bakhtiar Munajat
- Department of Parasitology and Medical Entomology, Faculty of Medicine, Universiti Kebangsaan Malaysia, 56000, Cheras, Kuala Lumpur, Malaysia
| | - Mohd Amirul Fitri A Rahim
- Department of Parasitology and Medical Entomology, Faculty of Medicine, Universiti Kebangsaan Malaysia, 56000, Cheras, Kuala Lumpur, Malaysia
| | - Wathiqah Wahid
- Department of Parasitology and Medical Entomology, Faculty of Medicine, Universiti Kebangsaan Malaysia, 56000, Cheras, Kuala Lumpur, Malaysia
| | | | - Paul C S Divis
- Malaria Research Centre, Faculty of Medicine and Health Sciences, Universiti Malaysia Sarawak, 94300, Kota Samarahan, Sarawak, Malaysia
| | - Sriwipa Chuangchaiya
- Department of Community Health, Faculty of Public Health, Kasetsart University, Chalermphrakiat Sakon Nakhon Province Campus, Sakon Nakhon, 47000, Thailand
| | - Inke Nadia D Lubis
- Department of Paediatric, Faculty of Medicine, Universitas Sumatera Utara, Medan, 20154, Indonesia
| | - Emelia Osman
- Department of Parasitology and Medical Entomology, Faculty of Medicine, Universiti Kebangsaan Malaysia, 56000, Cheras, Kuala Lumpur, Malaysia
| | | | - Zulkarnain Md Idris
- Department of Parasitology and Medical Entomology, Faculty of Medicine, Universiti Kebangsaan Malaysia, 56000, Cheras, Kuala Lumpur, Malaysia.
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5
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Hoh BP, Rahman TA. The indigenous populations as the model by nature to understand human genomic-phenomics interactions. QUANTITATIVE BIOLOGY 2021. [DOI: 10.15302/j-qb-021-0251] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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6
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Mario-Vásquez JE, Naranjo-González CA, Montiel J, Zuluaga LM, Vásquez AM, Tobón-Castaño A, Bedoya G, Segura C. Association of variants in IL1B, TLR9, TREM1, IL10RA, and CD3G and Native American ancestry on malaria susceptibility in Colombian populations. INFECTION GENETICS AND EVOLUTION 2020; 87:104675. [PMID: 33316430 DOI: 10.1016/j.meegid.2020.104675] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/18/2020] [Revised: 11/19/2020] [Accepted: 12/09/2020] [Indexed: 12/24/2022]
Abstract
Host genetics is an influencing factor in the manifestation of infectious diseases. In this study, the association of mild malaria with 28 variants in 16 genes previously reported in other populations and/or close to ancestry-informative markers (AIMs) selected was evaluated in an admixed 736 Colombian population sample. Additionally, the effect of genetic ancestry on phenotype expression was explored. For this purpose, the ancestral genetic composition of Turbo and El Bagre was determined. A higher Native American ancestry trend was found in the population with lower malaria susceptibility [odds ratio (OR) = 0.416, 95% confidence interval (95% CI) = 0.234-0.740, P = 0.003]. Three AIMs presented significant associations with the disease phenotype (MID1752, MID921, and MID1586). The first two were associated with greater malaria susceptibility (D/D, OR = 2.23, 95% CI = 1.06-4.69, P = 0.032 and I/D-I/I, OR = 2.14, 95% CI = 1.18-3.87, P = 0.011, respectively), and the latter has a protective effect on the appearance of malaria (I/I, OR = 0.18, 95% CI = 0.08-0.40, P < 0.0001). After adjustment by age, sex, municipality, and genetic ancestry, genotype association analysis showed evidence of association with malaria susceptibility for variants in or near IL1B, TLR9, TREM1, IL10RA, and CD3G genes: rs1143629-IL1B (G/A-A/A, OR = 0.41, 95% CI = 0.21-0.78, P = 0.0051), rs352139-TLR9 (T/T, OR = 0.28, 95% CI = 0.11-0.72, P = 0.0053), rs352140-TLR9 (C/C, OR = 0.41, 95% CI = 0.20-0.87, P = 0.019), rs2234237-TREM1 (T/A-A/A, OR = 0.43, 95% CI = 0.23-0.79, P = 0.0056), rs4252246-IL10RA (C/A-A/A, OR = 2.11, 95% CI = 1.18-3.75, P = 0.01), and rs1561966-CD3G (A/A, OR = 0.20, 95% CI = 0.06-0.69, P = 0.0058). The results showed the participation of genes involved in immunological processes and suggested an effect of ancestral genetic composition over the traits analyzed. Compared to the paisa population (Antioquia), Turbo and El Bagre showed a strong decrease in European ancestry and an increase in African and Native American ancestries. Also, a novel association of two single nucleotide polymorphisms with malaria susceptibility was identified in this study.
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Affiliation(s)
- Jorge Eliécer Mario-Vásquez
- Grupo Genética Molecular (GENMOL), Universidad de Antioquia, Carrera 53 No. 61-30, Lab 430. Medellín, Colombia
| | | | - Jehidys Montiel
- Grupo Malaria-Facultad de Medicina, Universidad de Antioquia, Carrera 53 No. 61-30, Lab 610, Medellín, Colombia
| | - Lina M Zuluaga
- Grupo Malaria-Facultad de Medicina, Universidad de Antioquia, Carrera 53 No. 61-30, Lab 610, Medellín, Colombia
| | - Ana M Vásquez
- Grupo Malaria-Facultad de Medicina, Universidad de Antioquia, Carrera 53 No. 61-30, Lab 610, Medellín, Colombia
| | - Alberto Tobón-Castaño
- Grupo Malaria-Facultad de Medicina, Universidad de Antioquia, Carrera 53 No. 61-30, Lab 610, Medellín, Colombia
| | - Gabriel Bedoya
- Grupo Genética Molecular (GENMOL), Universidad de Antioquia, Carrera 53 No. 61-30, Lab 430. Medellín, Colombia
| | - Cesar Segura
- Grupo Malaria-Facultad de Medicina, Universidad de Antioquia, Carrera 53 No. 61-30, Lab 610, Medellín, Colombia.
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Hoh BP, Zhang X, Deng L, Yuan K, Yew CW, Saw WY, Hoque MZ, Aghakhanian F, Phipps ME, Teo YY, Subbiah VK, Xu S. Shared Signature of Recent Positive Selection on the TSBP1-BTNL2-HLA-DRA Genes in Five Native Populations from North Borneo. Genome Biol Evol 2020; 12:2245-2257. [PMID: 33022050 PMCID: PMC7738747 DOI: 10.1093/gbe/evaa207] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/28/2020] [Indexed: 11/17/2022] Open
Abstract
North Borneo (NB) is home to more than 40 native populations. These natives are believed to have undergone local adaptation in response to environmental challenges such as the mosquito-abundant tropical rainforest. We attempted to trace the footprints of natural selection from the genomic data of NB native populations using a panel of ∼2.2 million genome-wide single nucleotide polymorphisms. As a result, an ∼13-kb haplotype in the Major Histocompatibility Complex Class II region encompassing candidate genes TSBP1–BTNL2–HLA-DRA was identified to be undergoing natural selection. This putative signature of positive selection is shared among the five NB populations and is estimated to have arisen ∼5.5 thousand years (∼220 generations) ago, which coincides with the period of Austronesian expansion. Owing to the long history of endemic malaria in NB, the putative signature of positive selection is postulated to be driven by Plasmodium parasite infection. The findings of this study imply that despite high levels of genetic differentiation, the NB populations might have experienced similar local genetic adaptation resulting from stresses of the shared environment.
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Affiliation(s)
- Boon-Peng Hoh
- Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.,Faculty of Medicine and Health Sciences, UCSI University, Jalan Menara Gading, Taman Connaught, Malaysia Cheras, Kuala Lumpur
| | - Xiaoxi Zhang
- Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.,School of Life Science and Technology, ShanghaiTech University, Shanghai, China
| | - Lian Deng
- Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Kai Yuan
- Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Chee-Wei Yew
- Biotechnology Research Institute, Universiti Malaysia Sabah, Jalan UMS, Kota Kinabalu, Sabah, Malaysia
| | - Woei-Yuh Saw
- Department of Statistics and Applied Probability, Faculty of Science, National University of Singapore, Singapore
| | - Mohammad Zahirul Hoque
- Faculty of Medicine and Health Sciences, Universiti Malaysia Sabah, Jalan UMS, Kota Kinabalu, Sabah, Malaysia
| | - Farhang Aghakhanian
- Jeffrey Cheah School of Medicine and Health Sciences, Monash University Malaysia, Selangor, Malaysia
| | - Maude E Phipps
- Jeffrey Cheah School of Medicine and Health Sciences, Monash University Malaysia, Selangor, Malaysia
| | - Yik-Ying Teo
- Department of Statistics and Applied Probability, Faculty of Science, National University of Singapore, Singapore.,Saw Swee Hock School of Public Health, National University of Singapore, Singapore.,NUS Graduate School for Integrative Science and Engineering, National University of Singapore, Singapore.,Life Sciences Institute, National University of Singapore, Singapore.,Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore
| | - Vijay Kumar Subbiah
- Biotechnology Research Institute, Universiti Malaysia Sabah, Jalan UMS, Kota Kinabalu, Sabah, Malaysia
| | - Shuhua Xu
- Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.,School of Life Science and Technology, ShanghaiTech University, Shanghai, China.,Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, China.,Henan Institute of Medical and Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, China.,Collaborative Innovation Centre of Genetics and Development, Shanghai, China
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8
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Werren EA, Garcia O, Bigham AW. Identifying adaptive alleles in the human genome: from selection mapping to functional validation. Hum Genet 2020; 140:241-276. [PMID: 32728809 DOI: 10.1007/s00439-020-02206-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2020] [Accepted: 07/07/2020] [Indexed: 12/19/2022]
Abstract
The suite of phenotypic diversity across geographically distributed human populations is the outcome of genetic drift, gene flow, and natural selection throughout human evolution. Human genetic variation underlying local biological adaptations to selective pressures is incompletely characterized. With the emergence of population genetics modeling of large-scale genomic data derived from diverse populations, scientists are able to map signatures of natural selection in the genome in a process known as selection mapping. Inferred selection signals further can be used to identify candidate functional alleles that underlie putative adaptive phenotypes. Phenotypic association, fine mapping, and functional experiments facilitate the identification of candidate adaptive alleles. Functional investigation of candidate adaptive variation using novel techniques in molecular biology is slowly beginning to unravel how selection signals translate to changes in biology that underlie the phenotypic spectrum of our species. In addition to informing evolutionary hypotheses of adaptation, the discovery and functional annotation of adaptive alleles also may be of clinical significance. While selection mapping efforts in non-European populations are growing, there remains a stark under-representation of diverse human populations in current public genomic databases, of both clinical and non-clinical cohorts. This lack of inclusion limits the study of human biological variation. Identifying and functionally validating candidate adaptive alleles in more global populations is necessary for understanding basic human biology and human disease.
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Affiliation(s)
- Elizabeth A Werren
- Department of Human Genetics, The University of Michigan, Ann Arbor, MI, USA
- Department of Anthropology, The University of Michigan, Ann Arbor, MI, USA
| | - Obed Garcia
- Department of Anthropology, The University of Michigan, Ann Arbor, MI, USA
| | - Abigail W Bigham
- Department of Anthropology, University of California Los Angeles, 341 Haines Hall, Los Angeles, CA, 90095, USA.
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9
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Deng L, Lou H, Zhang X, Thiruvahindrapuram B, Lu D, Marshall CR, Liu C, Xie B, Xu W, Wong LP, Yew CW, Farhang A, Ong RTH, Hoque MZ, Thuhairah AR, Jong B, Phipps ME, Scherer SW, Teo YY, Kumar SV, Hoh BP, Xu S. Analysis of five deep-sequenced trio-genomes of the Peninsular Malaysia Orang Asli and North Borneo populations. BMC Genomics 2019; 20:842. [PMID: 31718558 PMCID: PMC6852992 DOI: 10.1186/s12864-019-6226-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2019] [Accepted: 10/25/2019] [Indexed: 12/18/2022] Open
Abstract
Background Recent advances in genomic technologies have facilitated genome-wide investigation of human genetic variations. However, most efforts have focused on the major populations, yet trio genomes of indigenous populations from Southeast Asia have been under-investigated. Results We analyzed the whole-genome deep sequencing data (~ 30×) of five native trios from Peninsular Malaysia and North Borneo, and characterized the genomic variants, including single nucleotide variants (SNVs), small insertions and deletions (indels) and copy number variants (CNVs). We discovered approximately 6.9 million SNVs, 1.2 million indels, and 9000 CNVs in the 15 samples, of which 2.7% SNVs, 2.3% indels and 22% CNVs were novel, implying the insufficient coverage of population diversity in existing databases. We identified a higher proportion of novel variants in the Orang Asli (OA) samples, i.e., the indigenous people from Peninsular Malaysia, than that of the North Bornean (NB) samples, likely due to more complex demographic history and long-time isolation of the OA groups. We used the pedigree information to identify de novo variants and estimated the autosomal mutation rates to be 0.81 × 10− 8 – 1.33 × 10− 8, 1.0 × 10− 9 – 2.9 × 10− 9, and ~ 0.001 per site per generation for SNVs, indels, and CNVs, respectively. The trio-genomes also allowed for haplotype phasing with high accuracy, which serves as references to the future genomic studies of OA and NB populations. In addition, high-frequency inherited CNVs specific to OA or NB were identified. One example is a 50-kb duplication in DEFA1B detected only in the Negrito trios, implying plausible effects on host defense against the exposure of diverse microbial in tropical rainforest environment of these hunter-gatherers. The CNVs shared between OA and NB groups were much fewer than those specific to each group. Nevertheless, we identified a 142-kb duplication in AMY1A in all the 15 samples, and this gene is associated with the high-starch diet. Moreover, novel insertions shared with archaic hominids were identified in our samples. Conclusion Our study presents a full catalogue of the genome variants of the native Malaysian populations, which is a complement of the genome diversity in Southeast Asians. It implies specific population history of the native inhabitants, and demonstrated the necessity of more genome sequencing efforts on the multi-ethnic native groups of Malaysia and Southeast Asia.
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Affiliation(s)
- Lian Deng
- Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Haiyi Lou
- Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Xiaoxi Zhang
- Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.,School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China
| | | | - Dongsheng Lu
- Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Christian R Marshall
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, Ontario, Canada.,Genome Diagnostics, Department of Paediatric Laboratory Medicine, The Hospital for Sick Children, Toronto, Ontario, Canada.,Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada
| | - Chang Liu
- Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Bo Xie
- Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Wanxing Xu
- Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.,School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China
| | - Lai-Ping Wong
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, 117597, Singapore
| | - Chee-Wei Yew
- Biotechnology Research Institute, Universiti Malaysia Sabah, Jalan UMS, 88400, Kota Kinabalu, Sabah, Malaysia
| | - Aghakhanian Farhang
- Jefrey Cheah School of Medicine and Health Sciences, Monash University Malaysia, Jalan Lagoon Selatan, Sunway, 46150, Subang Jaya, Selangor, Malaysia.,Tropical Medicine and Biology Platform, Monash University Malaysia, Jalan Lagoon Selatan, 46150 Sunway, Subang Jaya, Selangor, Malaysia
| | - Rick Twee-Hee Ong
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, 117597, Singapore
| | - Mohammad Zahirul Hoque
- Faculty of Medicine and Health Sciences, Universiti Malaysia Sabah, Jalan UMS, 88400, Kota Kinabalu, Sabah, Malaysia
| | - Abdul Rahman Thuhairah
- Clinical Pathology Diagnostic Centre Research Laboratory, Faculty of Medicine, Universiti Teknologi MARA, Sungai Buloh Campus, 47000 Sg Buloh, Subang Jaya, Selangor, Malaysia
| | - Bhak Jong
- Personal Genomics Institute, Genome Research Foundation, Suwon, Republic of Korea.,Geromics, Ulsan, 44919, Republic of Korea.,Biomedical Engineering Department, The Genomics Institute, UNIST, Ulsan, Republic of Korea
| | - Maude E Phipps
- Tropical Medicine and Biology Platform, Monash University Malaysia, Jalan Lagoon Selatan, 46150 Sunway, Subang Jaya, Selangor, Malaysia
| | - Stephen W Scherer
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, Ontario, Canada.,Genome Diagnostics, Department of Paediatric Laboratory Medicine, The Hospital for Sick Children, Toronto, Ontario, Canada.,Program in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, Ontario, Canada.,Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
| | - Yik-Ying Teo
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, 117597, Singapore.,NUS Graduate School for Integrative Science and Engineering, National University of Singapore, Singapore, 117456, Singapore.,Life Sciences Institute, National University of Singapore, Singapore, Singapore.,Department of Statistics and Applied Probability, National University of Singapore, Singapore, Singapore.,Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, 138672, Singapore
| | - Subbiah Vijay Kumar
- Biotechnology Research Institute, Universiti Malaysia Sabah, Jalan UMS, 88400, Kota Kinabalu, Sabah, Malaysia.
| | - Boon-Peng Hoh
- Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China. .,Faculty of Medicine and Health Sciences, UCSI University, Jalan Menara Gading, Taman Connaught, Cheras, 56000, Kuala Lumpur, Malaysia.
| | - Shuhua Xu
- Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 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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10
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Hoh BP, Abdul Rahman T, Yusoff K. Natural selection and local adaptation of blood pressure regulation and their perspectives on precision medicine in hypertension. Hereditas 2019; 156:1. [PMID: 30636949 PMCID: PMC6323824 DOI: 10.1186/s41065-019-0080-1] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2018] [Accepted: 01/01/2019] [Indexed: 01/09/2023] Open
Abstract
Prevalence of hypertension (HTN) varies substantially across different populations. HTN is not only common - affecting at least one third of the world's adult population - but is also the most important driver for cardiovascular diseases. Yet up to a third of hypertensive patients are resistant to therapy, contributed by secondary hypertension but more commonly the hitherto inability to precisely predict response to specific antihypertensive agents. Population and individual genomics information could be useful in guiding the selection and predicting the response to treatment - an approach known as precision medicine. However this cannot be achieved without the knowledge of genetic variations that influence blood pressure (BP). A number of evolutionary factors including population demographics and forces of natural selection may be involved. This article explores some ideas on how natural selection influences BP regulation in ethnically and geographically diverse populations that could lead to them being susceptible to HTN. We explore how such evolutionary factors could impact the implementation of precision medicine in HTN. Finally, in order to ensure the success of precision medicine in HTN, we call for more initiatives to understand the genetic architecture within and between diverse populations with ancestry from different parts of the world, and to precisely classify the intermediate phenotypes of HTN.
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Affiliation(s)
- Boon-Peng Hoh
- 1Faculty of Medicine and Health Sciences, UCSI University, Cheras, 56000 Kuala Lumpur, Malaysia.,2Chinese Academy of Sciences Key Laboratory of Computational Biology, Max Planck Independent Research Group on Population Genomics, CAS-MPG Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, CAS, Shanghai, 200031 China
| | - Thuhairah Abdul Rahman
- 3Clinical Pathology Diagnostic Centre Research Laboratory, Faculty of Medicine, Universiti Teknologi MARA, Sungai Buloh Campus, 47000 Sungai Buloh, Selangor Malaysia
| | - Khalid Yusoff
- 1Faculty of Medicine and Health Sciences, UCSI University, Cheras, 56000 Kuala Lumpur, Malaysia
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11
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Mokhsin A, Mokhtar SS, Mohd Ismail A, M Nor F, Shaari SA, Nawawi H, Yusoff K, Abdul Rahman T, Hoh BP. Observational study of the status of coronary risk biomarkers among Negritos with metabolic syndrome in the east coast of Malaysia. BMJ Open 2018; 8:e021580. [PMID: 30518581 PMCID: PMC6286619 DOI: 10.1136/bmjopen-2018-021580] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/22/2023] Open
Abstract
OBJECTIVES To determine the prevalence of metabolic syndrome (MS), ascertain the status of coronary risk biomarkers and establish the independent predictors of these biomarkers among the Negritos. SETTINGS Health screening programme conducted in three inland settlements in the east coast of Malaysia and Peninsular Malaysia. SUBJECTS 150 Negritos who were still living in three inland settlements in the east coast of Malaysia and 1227 Malays in Peninsular Malaysia. These subjects were then categorised into MS and non-MS groups based on the International Diabetes Federation (IDF) consensus worldwide definition of MS and were recruited between 2010 and 2015. The subjects were randomly selected and on a voluntary basis. PRIMARY AND SECONDARY OUTCOME MEASURES This study was a cross-sectional study. Serum samples were collected for analysis of inflammatory (hsCRP), endothelial activation (sICAM-1) and prothrombogenesis [lp(a)] biomarkers. RESULTS MS was significantly higher among the Malays compared with Negritos (27.7%vs12.0%). Among the Malays, MS subjects had higher hsCRP (p=0.01) and sICAM-1 (p<0.05) than their non-MS counterpart. There were no significant differences in all the biomarkers between MS and the non-MS Negritos. However, when compared between ethnicity, all biomarkers were higher in Negritos compared with Malays (p<0.001). Binary logistic regression analysis affirmed that Negritos were an independent predictor for Lp(a) concentration (p<0.001). CONCLUSIONS This study suggests that there may possibly be a genetic influence other than lifestyle, which could explain the lack of difference in biomarkers concentration between MS and non-MS Negritos and for Negritos predicting Lp(a).
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Affiliation(s)
- Atiqah Mokhsin
- Faculty of Medicine, Universiti Teknologi MARA, Sungai Buloh, Selangor, Malaysia
| | - Siti Shuhada Mokhtar
- Faculty of Medicine, Universiti Teknologi MARA, Sungai Buloh, Selangor, Malaysia
| | - Aletza Mohd Ismail
- Faculty of Medicine, Universiti Teknologi MARA, Sungai Buloh, Selangor, Malaysia
| | - Fadzilah M Nor
- Faculty of Medicine, Universiti Teknologi MARA, Sungai Buloh, Selangor, Malaysia
| | - Syahrul Azlin Shaari
- Faculty of Medicine, Universiti Teknologi MARA, Sungai Buloh, Selangor, Malaysia
| | - Hapizah Nawawi
- Institute of Pathology, Laboratory and Forensic Medicine (I-PPerForM), Universiti Teknologi MARA, Sungai Buloh, Selangor, Malaysia
| | - Khalid Yusoff
- Faculty of Medicine and Health Sciences, UCSI University, Cheras, Kuala Lumpur, Malaysia
| | | | - Boon Peng Hoh
- Faculty of Medicine and Health Sciences, UCSI University, Cheras, Kuala Lumpur, Malaysia
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12
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Jinam TA, Phipps ME, Aghakhanian F, Majumder PP, Datar F, Stoneking M, Sawai H, Nishida N, Tokunaga K, Kawamura S, Omoto K, Saitou N. Discerning the Origins of the Negritos, First Sundaland People: Deep Divergence and Archaic Admixture. Genome Biol Evol 2018; 9:2013-2022. [PMID: 28854687 PMCID: PMC5597900 DOI: 10.1093/gbe/evx118] [Citation(s) in RCA: 45] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/09/2017] [Indexed: 12/26/2022] Open
Abstract
Human presence in Southeast Asia dates back to at least 40,000 years ago, when the current islands formed a continental shelf called Sundaland. In the Philippine Islands, Peninsular Malaysia, and Andaman Islands, there exist indigenous groups collectively called Negritos whose ancestry can be traced to the "First Sundaland People." To understand the relationship between these Negrito groups and their demographic histories, we generated genome-wide single nucleotide polymorphism data in the Philippine Negritos and compared them with existing data from other populations. Phylogenetic tree analyses show that Negritos are basal to other East and Southeast Asians, and that they diverged from West Eurasians at least 38,000 years ago. We also found relatively high traces of Denisovan admixture in the Philippine Negritos, but not in the Malaysian and Andamanese groups, suggesting independent introgression and/or parallel losses involving Denisovan introgressed regions. Shared genetic loci between all three Negrito groups could be related to skin pigmentation, height, facial morphology and malarial resistance. These results show the unique status of Negrito groups as descended from the First Sundaland People.
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Affiliation(s)
- Timothy A Jinam
- Division of Population Genetics, National Institute of Genetics, Mishima, Japan
| | - Maude E Phipps
- Jeffrey Cheah School of Medicine and Health Sciences, Monash University Malaysia, Sunway City, Selangor, Malaysia
| | - Farhang Aghakhanian
- Jeffrey Cheah School of Medicine and Health Sciences, Monash University Malaysia, Sunway City, Selangor, Malaysia
| | - Partha P Majumder
- National Institute of Biomedical Genomics, Kalyani, West Bengal, India
| | - Francisco Datar
- Department of Anthropology, University of the Philippines, Diliman, Quezon City, The Philippines
| | - Mark Stoneking
- Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
| | - Hiromi Sawai
- Department of Human Genetics, Graduate School of Medicine, The University of Tokyo, Japan
| | - Nao Nishida
- Department of Human Genetics, Graduate School of Medicine, The University of Tokyo, Japan.,Department of Hepatic Disease, Research Center for Hepatitis and Immunology, National Center for Global Health and Medicine, Chiba, Japan
| | - Katsushi Tokunaga
- Department of Human Genetics, Graduate School of Medicine, The University of Tokyo, Japan
| | - Shoji Kawamura
- Department of Integrated Biosciences, Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa, Japan
| | - Keiichi Omoto
- Department of Anthropology, Faculty of Science, The University of Tokyo, Japan
| | - Naruya Saitou
- Division of Population Genetics, National Institute of Genetics, Mishima, Japan
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13
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Fu R, Mokhtar SS, Phipps ME, Hoh BP, Xu S. A genome-wide characterization of copy number variations in native populations of Peninsular Malaysia. Eur J Hum Genet 2018; 26:886-897. [PMID: 29476164 DOI: 10.1038/s41431-018-0120-8] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2017] [Revised: 11/20/2017] [Accepted: 02/01/2018] [Indexed: 11/09/2022] Open
Abstract
Copy number variations (CNVs) are genomic structural variations that result from the deletion or duplication of large genomic segments. The characterization of CNVs is largely underrepresented, particularly those of indigenous populations, such as the Orang Asli in Peninsular Malaysia. In the present study, we first characterized the genome-wide CNVs of four major native populations from Peninsular Malaysia, including the Malays and three Orang Asli populations; namely, Proto-Malay, Senoi, and Negrito (collectively called PM). We subsequently assessed the distribution of CNVs across the four populations. The resulting global CNV map revealed 3102 CNVs, with an average of more than 100 CNVs per individual. We identified genes harboring CNVs that are highly differentiated between PM and global populations, indicating that these genes are predominantly enriched in immune responses and defense functions, including APOBEC3A_B, beta-defensin genes, and CCL3L1, followed by other biological functions, such as drug and toxin metabolism and responses to radiation, suggesting some attributions between CNV variations and adaptations of the PM groups to the local environmental conditions of tropical rainforests.
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Affiliation(s)
- Ruiqing Fu
- Chinese Academy of Sciences (CAS), Key Laboratory of Computational Biology, Max Planck Independent Research Group on Population Genomics, CAS-MPG Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Shanghai, 200031, China.,University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Siti Shuhada Mokhtar
- Institute of Medical Molecular Biotechnology, Faculty of Medicine, Universiti Teknologi MARA, Sungai Buloh Campus, Selangor, Malaysia
| | - Maude Elvira Phipps
- School of Medicine, Monash University Sunway Campus, Petaling Jaya, Malaysia
| | - Boon-Peng Hoh
- Chinese Academy of Sciences (CAS), Key Laboratory of Computational Biology, Max Planck Independent Research Group on Population Genomics, CAS-MPG Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Shanghai, 200031, China.,Faculty of Medicine and Health Sciences, UCSI University, Jalan Menara Gading, Taman Connaught, Cheras, Kuala Lumpur, Malaysia
| | - Shuhua Xu
- Chinese Academy of Sciences (CAS), Key Laboratory of Computational Biology, Max Planck Independent Research Group on Population Genomics, CAS-MPG Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Shanghai, 200031, China. .,University of Chinese Academy of Sciences, Beijing, 100049, 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.
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14
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Yew CW, Lu D, Deng L, Wong LP, Ong RTH, Lu Y, Wang X, Yunus Y, Aghakhanian F, Mokhtar SS, Hoque MZ, Voo CLY, Abdul Rahman T, Bhak J, Phipps ME, Xu S, Teo YY, Kumar SV, Hoh BP. Genomic structure of the native inhabitants of Peninsular Malaysia and North Borneo suggests complex human population history in Southeast Asia. Hum Genet 2018; 137:161-173. [DOI: 10.1007/s00439-018-1869-0] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2017] [Accepted: 01/22/2018] [Indexed: 11/28/2022]
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15
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Saw WY, Tantoso E, Begum H, Zhou L, Zou R, He C, Chan SL, Tan LWL, Wong LP, Xu W, Moong DKN, Lim Y, Li B, Pillai NE, Peterson TA, Bielawny T, Meikle PJ, Mundra PA, Lim WY, Luo M, Chia KS, Ong RTH, Brunham LR, Khor CC, Too HP, Soong R, Wenk MR, Little P, Teo YY. Establishing multiple omics baselines for three Southeast Asian populations in the Singapore Integrative Omics Study. Nat Commun 2017; 8:653. [PMID: 28935855 PMCID: PMC5608948 DOI: 10.1038/s41467-017-00413-x] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2017] [Accepted: 06/28/2017] [Indexed: 11/09/2022] Open
Abstract
The Singapore Integrative Omics Study provides valuable insights on establishing population reference measurement in 364 Chinese, Malay, and Indian individuals. These measurements include > 2.5 millions genetic variants, 21,649 transcripts expression, 282 lipid species quantification, and 284 clinical, lifestyle, and dietary variables. This concept paper introduces the depth of the data resource, and investigates the extent of ethnic variation at these omics and non-omics biomarkers. It is evident that there are specific biomarkers in each of these platforms to differentiate between the ethnicities, and intra-population analyses suggest that Chinese and Indians are the most biologically homogeneous and heterogeneous, respectively, of the three groups. Consistent patterns of correlations between lipid species also suggest the possibility of lipid tagging to simplify future lipidomics assays. The Singapore Integrative Omics Study is expected to allow the characterization of intra-omic and inter-omic correlations within and across all three ethnic groups through a systems biology approach.The Singapore Genome Variation projects characterized the genetics of Singapore's Chinese, Malay, and Indian populations. The Singapore Integrative Omics Study introduced here goes further in providing multi-omic measurements in individuals from these populations, including genetic, transcriptome, lipidome, and lifestyle data, and will facilitate the study of common diseases in Asian communities.
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Affiliation(s)
- Woei-Yuh Saw
- Saw Swee Hock School of Public Health, National University of Singapore, 12 Science Drive, Singapore, 117549, Singapore.,Life Sciences Institute, National University of Singapore, 28 Medical Drive, Singapore, 117456, Singapore
| | - Erwin Tantoso
- Saw Swee Hock School of Public Health, National University of Singapore, 12 Science Drive, Singapore, 117549, Singapore
| | - Husna Begum
- Life Sciences Institute, National University of Singapore, 28 Medical Drive, Singapore, 117456, Singapore.,Baker IDI Heart and Diabetes Institute, 75 Commercial Road, Melbourne, VIC, 3004, Australia
| | - Lihan Zhou
- MiRXES, Agency for Science, Technology and Research Singapore, 10 Biopolis Road, Chromos, Singapore, 138670, Singapore
| | - Ruiyang Zou
- MiRXES, Agency for Science, Technology and Research Singapore, 10 Biopolis Road, Chromos, Singapore, 138670, Singapore
| | - Cheng He
- MiRXES, Agency for Science, Technology and Research Singapore, 10 Biopolis Road, Chromos, Singapore, 138670, Singapore
| | - Sze Ling Chan
- Translational Laboratory in Genetic Medicine, Agency for Science, Technology and Research Singapore, 8A Biomedical Grove, Immunos, Singapore, 138648, Singapore
| | - Linda Wei-Lin Tan
- Saw Swee Hock School of Public Health, National University of Singapore, 12 Science Drive, Singapore, 117549, Singapore
| | - Lai-Ping Wong
- Saw Swee Hock School of Public Health, National University of Singapore, 12 Science Drive, Singapore, 117549, Singapore
| | - Wenting Xu
- Saw Swee Hock School of Public Health, National University of Singapore, 12 Science Drive, Singapore, 117549, Singapore
| | - Don Kyin Nwe Moong
- Saw Swee Hock School of Public Health, National University of Singapore, 12 Science Drive, Singapore, 117549, Singapore
| | - Yenly Lim
- Saw Swee Hock School of Public Health, National University of Singapore, 12 Science Drive, Singapore, 117549, Singapore
| | - Bowen Li
- Saw Swee Hock School of Public Health, National University of Singapore, 12 Science Drive, Singapore, 117549, Singapore
| | - Nisha Esakimuthu Pillai
- Life Sciences Institute, National University of Singapore, 28 Medical Drive, Singapore, 117456, Singapore
| | - Trevor A Peterson
- Department of Medical Microbiology, University of Manitoba, 730 William Avenue, Winnipeg, MB, Canada, R3E 0Z2.,National Microbiology Laboratory, 1015 Arlington St, Winnipeg, MB, Canada, R3E
| | - Tomasz Bielawny
- Department of Medical Microbiology, University of Manitoba, 730 William Avenue, Winnipeg, MB, Canada, R3E 0Z2.,National Microbiology Laboratory, 1015 Arlington St, Winnipeg, MB, Canada, R3E
| | - Peter J Meikle
- Baker IDI Heart and Diabetes Institute, 75 Commercial Road, Melbourne, VIC, 3004, Australia.,Department of Biochemistry and Molecular Biology, The University of Melbourne, Bio21, 30 Flemington Road, Melbourne, VIC, 3010, Australia
| | - Piyushkumar A Mundra
- Baker IDI Heart and Diabetes Institute, 75 Commercial Road, Melbourne, VIC, 3004, Australia
| | - Wei-Yen Lim
- Saw Swee Hock School of Public Health, National University of Singapore, 12 Science Drive, Singapore, 117549, Singapore
| | - Ma Luo
- Department of Medical Microbiology, University of Manitoba, 730 William Avenue, Winnipeg, MB, Canada, R3E 0Z2.,National Microbiology Laboratory, 1015 Arlington St, Winnipeg, MB, Canada, R3E
| | - Kee-Seng Chia
- Saw Swee Hock School of Public Health, National University of Singapore, 12 Science Drive, Singapore, 117549, Singapore
| | - Rick Twee-Hee Ong
- Saw Swee Hock School of Public Health, National University of Singapore, 12 Science Drive, Singapore, 117549, Singapore
| | - Liam R Brunham
- Translational Laboratory in Genetic Medicine, Agency for Science, Technology and Research Singapore, 8A Biomedical Grove, Immunos, Singapore, 138648, Singapore
| | - Chiea-Chuen Khor
- Genome Institute of Singapore, Agency for Science, Technology and Research Singapore, 60 Biopolis St, Singapore, 138672, Singapore.,Singapore Eye Research Institute, 20 College Road, Singapore, 169856, Singapore
| | - Heng Phon Too
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, 8 Medical Drive, Singapore, 117597, Singapore.,Molecular Engineering of Biological and Chemical System/Chemical Pharmaceutical Engineering, Singapore-Massachusetts Institute of Technology Alliance, 4 Engineering Drive 3, Singapore, 117576, Singapore.,Bioprocessing Technology Institute, A*STAR (Agency for Science, Technology and Research, Singapore), 20 Biopolis Way, Singapore, 138668, Singapore
| | - Richie Soong
- Cancer Science Institute of Singapore, National University of Singapore, 14 Medical Drive, Singapore, 117599, Singapore
| | - Markus R Wenk
- Life Sciences Institute, National University of Singapore, 28 Medical Drive, Singapore, 117456, Singapore.,Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, 8 Medical Drive, Singapore, 117597, Singapore.,NUS Graduate School for Integrative Science and Engineering, National University of Singapore, 28 Medical Drive, Singapore, 117456, Singapore.,State Key Laboratory of Molecular Developmental Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, No.1 West Beichen Road, Chaoyang District, Beijing, 100101, China.,Department of Biological Sciences, National University of Singapore, 16 Science Drive 4, Singapore, 117543, Singapore
| | - Peter Little
- Life Sciences Institute, National University of Singapore, 28 Medical Drive, Singapore, 117456, Singapore
| | - Yik-Ying Teo
- Saw Swee Hock School of Public Health, National University of Singapore, 12 Science Drive, Singapore, 117549, Singapore. .,Life Sciences Institute, National University of Singapore, 28 Medical Drive, Singapore, 117456, Singapore. .,Genome Institute of Singapore, Agency for Science, Technology and Research Singapore, 60 Biopolis St, Singapore, 138672, Singapore. .,NUS Graduate School for Integrative Science and Engineering, National University of Singapore, 28 Medical Drive, Singapore, 117456, Singapore. .,Department of Statistics and Applied Probability, National University of Singapore, 6 Science Drive 2, Singapore, 117546, Singapore.
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16
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Liu X, Lu D, Saw WY, Shaw PJ, Wangkumhang P, Ngamphiw C, Fucharoen S, Lert-Itthiporn W, Chin-Inmanu K, Chau TNB, Anders K, Kasturiratne A, de Silva HJ, Katsuya T, Kimura R, Nabika T, Ohkubo T, Tabara Y, Takeuchi F, Yamamoto K, Yokota M, Mamatyusupu D, Yang W, Chung YJ, Jin L, Hoh BP, Wickremasinghe AR, Ong RH, Khor CC, Dunstan SJ, Simmons C, Tongsima S, Suriyaphol P, Kato N, Xu S, Teo YY. Characterising private and shared signatures of positive selection in 37 Asian populations. Eur J Hum Genet 2017; 25:499-508. [PMID: 28098149 DOI: 10.1038/ejhg.2016.181] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2016] [Revised: 10/22/2016] [Accepted: 11/01/2016] [Indexed: 11/09/2022] Open
Abstract
The Asian Diversity Project (ADP) assembled 37 cosmopolitan and ethnic minority populations in Asia that have been densely genotyped across over half a million markers to study patterns of genetic diversity and positive natural selection. We performed population structure analyses of the ADP populations and divided these populations into four major groups based on their genographic information. By applying a highly sensitive algorithm haploPS to locate genomic signatures of positive selection, 140 distinct genomic regions exhibiting evidence of positive selection in at least one population were identified. We examined the extent of signal sharing for regions that were selected in multiple populations and observed that populations clustered in a similar fashion to that of how the ancestry clades were phylogenetically defined. In particular, populations predominantly located in South Asia underwent considerably different adaptation as compared with populations from the other geographical regions. Signatures of positive selection present in multiple geographical regions were predicted to be older and have emerged prior to the separation of the populations in the different regions. In contrast, selection signals present in a single population group tended to be of lower frequencies and thus can be attributed to recent evolutionary events.
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Affiliation(s)
- Xuanyao Liu
- NUS Graduate School for Integrative Science and Engineering, National University of Singapore, Singapore, Singapore.,Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | - Dongsheng Lu
- Max Planck Independent Research Group on Population Genomics, Chinese Academy of Sciences and Max Planck Society Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Woei-Yuh Saw
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore.,Life Sciences Institute, National University of Singapore, Singapore, Singapore
| | - Philip J Shaw
- National Center for Genetic Engineering and Biotechnology, National Science and Technology Development Agency, Pathum Thani, Thailand
| | - Pongsakorn Wangkumhang
- National Center for Genetic Engineering and Biotechnology, National Science and Technology Development Agency, Pathum Thani, Thailand
| | - Chumpol Ngamphiw
- National Center for Genetic Engineering and Biotechnology, National Science and Technology Development Agency, Pathum Thani, Thailand
| | - Suthat Fucharoen
- Institute of Molecular Biosciences, Mahidol University, Nakhon Pathom, Thailand
| | - Worachart Lert-Itthiporn
- Faculty of Science, Molecular Medicine Graduate Programme, Mahidol University, Bangkok, Thailand.,Division of Bioinformatics and Data Management for Research, Department of Research and Development, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
| | - Kwanrutai Chin-Inmanu
- Division of Bioinformatics and Data Management for Research, Department of Research and Development, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
| | - Tran Nguyen Bich Chau
- Oxford University Clinical Research Unit, Hospital for Tropical Diseases, Ho Chi Minh City, Vietnam
| | - Katie Anders
- Oxford University Clinical Research Unit, Hospital for Tropical Diseases, Ho Chi Minh City, Vietnam.,Nuffield Department of Clinical Medicine, Centre for Tropical Medicine, University of Oxford, Oxford, UK
| | | | - H Janaka de Silva
- Department of Medicine, Faculty of Medicine, University of Kelaniya, Ragama, Sri Lanka
| | - Tomohiro Katsuya
- Department of Clinical Gene Therapy, Osaka University Graduate School of Medicine, Suita, Japan
| | - Ryosuke Kimura
- Department of Human Biology and Anatomy, Graduate School of Medicine, University of the Ryukyus, Nishihara-cho, Japan
| | - Toru Nabika
- Department of Functional Pathology, Shimane University School of Medicine, Izumo, Japan
| | - Takayoshi Ohkubo
- Department of Hygiene and Public Health, Teikyo University School of Medicine, Tokyo, Japan
| | - Yasuharu Tabara
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Fumihiko Takeuchi
- Department of Gene Diagnostics and Therapeutics, National Center for Global Health and Medicine, Tokyo, Japan
| | - Ken Yamamoto
- Department of Medical Chemistry, Kurume University School of Medicine, Kurume, Japan
| | - Mitsuhiro Yokota
- Department of Genome Science, School of Dentistry, Aichi Gakuin University, Nagoya, Japan
| | - Dolikun Mamatyusupu
- College of the Life Sciences and Technology, Xinjiang University, Urumqi, China
| | - Wenjun Yang
- Key Laboratory of Reproduction and Heredity of Ningxia Region, Ningxia Medical University, YinchuanChina
| | - Yeun-Jun Chung
- Department of Microbiology, Integrated Research Center for Genome Polymorphism, The Catholic University Medical College, Seoul, Korea
| | - Li Jin
- State Key Laboratory of Genetic Engineering and Ministry of Education (MOE), Key Laboratory of Contemporary Anthropology, School of Life Sciences, Fudan University, Shanghai, China
| | - Boon-Peng Hoh
- Faculty of Medicine and Health Sciences, UCSI University, Kuala Lumpur, Malaysia
| | | | - RickTwee-Hee Ong
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | - Chiea-Chuen Khor
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore
| | - Sarah J Dunstan
- Oxford University Clinical Research Unit, Hospital for Tropical Diseases, Ho Chi Minh City, Vietnam.,Nuffield Department of Clinical Medicine, Centre for Tropical Medicine, University of Oxford, Oxford, UK.,The Peter Doherty Institute for Infection and Immunity, The University of Melbourne, Melbourne, Victoria, Australia
| | - Cameron Simmons
- Oxford University Clinical Research Unit, Hospital for Tropical Diseases, Ho Chi Minh City, Vietnam.,Nuffield Department of Clinical Medicine, Centre for Tropical Medicine, University of Oxford, Oxford, UK.,Department of Microbiology and Immunology, The University of Melbourne, Melbourne, Victoria, Australia
| | - Sissades Tongsima
- National Center for Genetic Engineering and Biotechnology, National Science and Technology Development Agency, Pathum Thani, Thailand
| | - Prapat Suriyaphol
- Division of Bioinformatics and Data Management for Research, Department of Research and Development, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand.,Institute of Personalized Genomics and Gene Therapy (IPGG), Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
| | - Norihiro Kato
- Department of Gene Diagnostics and Therapeutics, National Center for Global Health and Medicine, Tokyo, Japan
| | - Shuhua Xu
- Max Planck Independent Research Group on Population Genomics, Chinese Academy of Sciences and Max Planck Society Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China.,School of Life Sciences and Technology, ShanghaiTech University, Shanghai, China.,Collaborative Innovation Center of Genetics and Development, Shanghai, China
| | - Yik-Ying Teo
- NUS Graduate School for Integrative Science and Engineering, National University of Singapore, Singapore, Singapore.,Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore.,Life Sciences Institute, National University of Singapore, Singapore, Singapore.,Department of Gene Diagnostics and Therapeutics, National Center for Global Health and Medicine, Tokyo, Japan.,Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore.,Department of Statistics and Applied Probability, National University of Singapore, Singapore, Singapore
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17
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Norhalifah HK, Syaza FH, Chambers GK, Edinur HA. The genetic history of Peninsular Malaysia. Gene 2016; 586:129-35. [DOI: 10.1016/j.gene.2016.04.008] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2015] [Revised: 03/17/2016] [Accepted: 04/05/2016] [Indexed: 12/27/2022]
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18
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Mackinnon MJ, Ndila C, Uyoga S, Macharia A, Snow RW, Band G, Rautanen A, Rockett KA, Kwiatkowski DP, Williams TN. Environmental Correlation Analysis for Genes Associated with Protection against Malaria. Mol Biol Evol 2016; 33:1188-204. [PMID: 26744416 PMCID: PMC4839215 DOI: 10.1093/molbev/msw004] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Abstract
Genome-wide searches for loci involved in human resistance to malaria are currently being conducted on a large scale in Africa using case-control studies. Here, we explore the utility of an alternative approach-"environmental correlation analysis, ECA," which tests for clines in allele frequencies across a gradient of an environmental selection pressure-to identify genes that have historically protected against death from malaria. We collected genotype data from 12,425 newborns on 57 candidate malaria resistance loci and 9,756 single nucleotide polymorphisms (SNPs) selected at random from across the genome, and examined their allele frequencies for geographic correlations with long-term malaria prevalence data based on 84,042 individuals living under different historical selection pressures from malaria in coastal Kenya. None of the 57 candidate SNPs showed significant (P < 0.05) correlations in allele frequency with local malaria transmission intensity after adjusting for population structure and multiple testing. In contrast, two of the random SNPs that had highly significant correlations (P < 0.01) were in genes previously linked to malaria resistance, namely, CDH13, encoding cadherin 13, and HS3ST3B1, encoding heparan sulfate 3-O-sulfotransferase 3B1. Both proteins play a role in glycoprotein-mediated cell-cell adhesion which has been widely implicated in cerebral malaria, the most life-threatening form of this disease. Other top genes, including CTNND2 which encodes δ-catenin, a molecular partner to cadherin, were significantly enriched in cadherin-mediated pathways affecting inflammation of the brain vascular endothelium. These results demonstrate the utility of ECA in the discovery of novel genes and pathways affecting infectious disease.
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Affiliation(s)
| | - Carolyne Ndila
- Department of Epidemiology and Demography, KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya
| | - Sophie Uyoga
- Department of Epidemiology and Demography, KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya
| | - Alex Macharia
- Department of Epidemiology and Demography, KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya
| | - Robert W. Snow
- Department of Public Health Research, KEMRI-Wellcome Trust Research Programme, Nairobi, Kenya
- Centre for Tropical Medicine, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, United Kingdom
| | - Gavin Band
- Wellcome Trust Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Anna Rautanen
- Wellcome Trust Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Kirk A. Rockett
- Wellcome Trust Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
- The Wellcome Trust Sanger Institute, Cambridge, United Kingdom
| | - Dominic P. Kwiatkowski
- Wellcome Trust Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
- The Wellcome Trust Sanger Institute, Cambridge, United Kingdom
| | - Thomas N. Williams
- Department of Epidemiology and Demography, KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya
- Department of Medicine, Imperial College, London, United Kingdom
- INDEPTH Network, Kanda, Accra, Ghana
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19
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Rishishwar L, Conley AB, Wigington CH, Wang L, Valderrama-Aguirre A, Jordan IK. Ancestry, admixture and fitness in Colombian genomes. Sci Rep 2015. [PMID: 26197429 PMCID: PMC4508918 DOI: 10.1038/srep12376] [Citation(s) in RCA: 63] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
The human dimension of the Columbian Exchange entailed substantial genetic admixture between ancestral source populations from Africa, the Americas and Europe, which had evolved separately for many thousands of years. We sought to address the implications of the creation of admixed American genomes, containing novel allelic combinations, for human health and fitness via analysis of an admixed Colombian population from Medellin. Colombian genomes from Medellin show a wide range of three-way admixture contributions from ancestral source populations. The primary ancestry component for the population is European (average = 74.6%, range = 45.0%–96.7%), followed by Native American (average = 18.1%, range = 2.1%–33.3%) and African (average = 7.3%, range = 0.2%–38.6%). Locus-specific patterns of ancestry were evaluated to search for genomic regions that are enriched across the population for particular ancestry contributions. Adaptive and innate immune system related genes and pathways are particularly over-represented among ancestry-enriched segments, including genes (HLA-B and MAPK10) that are involved in defense against endemic pathogens such as malaria. Genes that encode functions related to skin pigmentation (SCL4A5) and cutaneous glands (EDAR) are also found in regions with anomalous ancestry patterns. These results suggest the possibility that ancestry-specific loci were differentially retained in the modern admixed Colombian population based on their utility in the New World environment.
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Affiliation(s)
- Lavanya Rishishwar
- 1] School of Biology, Georgia Institute of Technology, Atlanta, GA 30332, USA [2] PanAmerican Bioinformatics Institute, Cali, Valle del Cauca, Colombia [3] BIOS Centro de Bioinformática y Biología Computacional, Manizales, Caldas, Colombia
| | - Andrew B Conley
- School of Biology, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | | | - Lu Wang
- School of Biology, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Augusto Valderrama-Aguirre
- 1] PanAmerican Bioinformatics Institute, Cali, Valle del Cauca, Colombia [2] Biomedical Research Institute, Universidad Libre, Cali, Valle del Cauca, Colombia [3] Regenerar - Center of Excellence for Regenerative and Personalized Medicine, Cali, Valle del Cauca, Colombia
| | - I King Jordan
- 1] School of Biology, Georgia Institute of Technology, Atlanta, GA 30332, USA [2] PanAmerican Bioinformatics Institute, Cali, Valle del Cauca, Colombia [3] BIOS Centro de Bioinformática y Biología Computacional, Manizales, Caldas, Colombia
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