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Ding Y, Er S, Tan A, Gounot JS, Saw WY, Tan LWL, Teo YY, Nagarajan N, Seedorf H. Comparison of tet(X4)-containing contigs assembled from metagenomic sequencing data with plasmid sequences of isolates from a cohort of healthy subjects. Microbiol Spectr 2024; 12:e0396923. [PMID: 38441466 DOI: 10.1128/spectrum.03969-23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Accepted: 02/12/2024] [Indexed: 04/06/2024] Open
Abstract
Recently discovered tet(X) gene variants have provided new insights into microbial antibiotic resistance mechanisms and their potential consequences for public health. This study focused on detection, analysis, and characterization of Tet(X4)-positive Enterobacterales from the gut microbiota of a healthy cohort of individuals in Singapore using cultivation-dependent and cultivation-independent approaches. Twelve Tet(X4)-positive Enterobacterales strains that were previously obtained from the cohort were fully genome-sequenced and comparatively analyzed. A metagenomic sequencing (MS) data set of the same samples was mined for contigs that harbored the tet(X4) resistance gene. The sequences of tet(X4)-containing contigs and plasmids sequences were compared. The presence of the resistance genes floR and estT (previously annotated as catD) was detected in the same cassette in 10 and 12 out of the 12 tet(X4)-carrying plasmids, respectively. MS detected tet(X4)-containing contigs in 2 out of the 109 subjects, while cultivation-dependent analysis previously reported a prevalence of 10.1%. The tet(X4)-containing sequences assembled from MS data are relatively short (~14 to 33 kb) but show high similarity to the respective plasmid sequences of the isolates. Our findings show that MS can complement efforts in the surveillance of antibiotic resistance genes for clinical samples, while it has a lower sensitivity than a cultivation-based method when the target organism has a low abundance. Further optimization is required if MS is to be utilized in antibiotic resistance surveillance.IMPORTANCEThe global rise in antibiotic resistance makes it necessary to develop and apply new approaches to detect and monitor the prevalence of antibiotic resistance genes in human populations. In this regard, of particular interest are resistances against last-resort antibiotics, such as tigecycline. In this study, we show that metagenomic sequencing can help to detect high abundance of the tigecycline resistance gene tet(X4) in fecal samples from a cohort of healthy human subjects. However, cultivation-based approaches currently remain the most reliable and cost-effective method for detection of antibiotic-resistant bacteria.
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Affiliation(s)
- Yichen Ding
- Temasek Life Sciences Laboratory, 1 Research Link, Singapore, Singapore
| | - Shuan Er
- Temasek Life Sciences Laboratory, 1 Research Link, Singapore, Singapore
| | - Abel Tan
- Temasek Life Sciences Laboratory, 1 Research Link, Singapore, Singapore
| | - Jean-Sebastien Gounot
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore
| | - Woei-Yuh Saw
- Baker Heart and Diabetes Institute, Melbourne, Victoria, Singapore
| | - Linda Wei Lin Tan
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | - Yik Ying Teo
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
- NUS Graduate School for Integrative Science and Engineering, National University of Singapore, Singapore, Singapore
- Department of Statistics and Applied Probability, National University of Singapore, Singapore, Singapore
- Life Sciences Institute, National University of Singapore, Singapore, Singapore
| | - Niranjan Nagarajan
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore
- NUS Graduate School for Integrative Science and Engineering, National University of Singapore, Singapore, Singapore
| | - Henning Seedorf
- Temasek Life Sciences Laboratory, 1 Research Link, Singapore, Singapore
- Department of Biological Sciences, National University of Singapore, Singapore, Singapore
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Low A, Lee JKY, Gounot JS, Ravikrishnan A, Ding Y, Saw WY, Tan LWL, Moong DKN, Teo YY, Nagarajan N, Seedorf H. Mutual Exclusion of Methanobrevibacter Species in the Human Gut Microbiota Facilitates Directed Cultivation of a Candidatus Methanobrevibacter Intestini Representative. Microbiol Spectr 2022; 10:e0084922. [PMID: 35699469 PMCID: PMC9431525 DOI: 10.1128/spectrum.00849-22] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Accepted: 05/25/2022] [Indexed: 11/20/2022] Open
Abstract
Methanogenic Archaea (methanogens) are a phylogenetically diverse group of microorganisms and are considered to be the most abundant archaeal representatives in the human gut. However, the gut methanogen diversity of human populations in many global regions remains poorly investigated. Here, we report the abundance and diversity of gut methanogenic Archaea in a multi-ethnic cohort of healthy Singaporeans by using a concerted approach of metagenomic sequencing, 16S rRNA gene amplicon sequencing, and quantitative PCR. Our results indicate a mutual exclusion of Methanobrevibacter species, i.e., the highly prevalent Methanobrevibacter smithii and the less prevalent Candidatus Methanobrevibacter intestini in more than 80% of the samples when using an amplicon sequencing-based approach. Leveraging on this finding, we were able to select a fecal sample to isolate a representative strain, TLL-48-HuF1, for Candidatus Methanobrevibacter intestini. The analyzed physiological parameters of M. smithii DSM 861T and strain TLL-48-HuF1 suggest high similarity of the two species. Comparative genome analysis and the mutual exclusion of the Methanobrevibacter species indicate potentially different niche adaptation strategies in the human host, which may support the designation of Candidatus M. intestini as a novel species. IMPORTANCE Methanogens are important hydrogen consumers in the gut and are associated with differing host health. Here, we determine the prevalence and abundance of archaeal species in the guts of a multi-ethnic cohort of healthy Singapore residents. While Methanobrevibacter smithii is the most prevalent and abundant methanogen in the human gut of local subjects, the recently proposed Candidatus Methanobrevibacter intestini is the abundant methanogen in a minority of individuals that harbor them. The observed potential mutual exclusion of M. smithii and Ca. M. intestini provides further support to the proposal that the two physiologically similar strains may belong to different Methanobrevibacter species.
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Affiliation(s)
- Adrian Low
- Temasek Life Sciences Laboratory, Singapore
| | | | | | | | | | - Woei-Yuh Saw
- Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
| | - Linda Wei Lin Tan
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore
| | - Don Kyin Nwe Moong
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore
| | - Yik Ying Teo
- Genome Institute of Singapore, A*STAR, 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
- Department of Statistics and Applied Probability, National University of Singapore, Singapore
- Life Sciences Institute, National University of Singapore, Singapore
| | - Niranjan Nagarajan
- Genome Institute of Singapore, A*STAR, Singapore
- NUS Graduate School for Integrative Science and Engineering, National University of Singapore, Singapore
| | - Henning Seedorf
- Temasek Life Sciences Laboratory, Singapore
- Department of Biological Sciences, National University of Singapore, Singapore
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Abstract
Bioinformatic research relies on large-scale computational infrastructures which have a nonzero carbon footprint but so far, no study has quantified the environmental costs of bioinformatic tools and commonly run analyses. In this work, we estimate the carbon footprint of bioinformatics (in kilograms of CO2 equivalent units, kgCO2e) using the freely available Green Algorithms calculator (www.green-algorithms.org, last accessed 2022). We assessed 1) bioinformatic approaches in genome-wide association studies (GWAS), RNA sequencing, genome assembly, metagenomics, phylogenetics, and molecular simulations, as well as 2) computation strategies, such as parallelization, CPU (central processing unit) versus GPU (graphics processing unit), cloud versus local computing infrastructure, and geography. In particular, we found that biobank-scale GWAS emitted substantial kgCO2e and simple software upgrades could make it greener, for example, upgrading from BOLT-LMM v1 to v2.3 reduced carbon footprint by 73%. Moreover, switching from the average data center to a more efficient one can reduce carbon footprint by approximately 34%. Memory over-allocation can also be a substantial contributor to an algorithm’s greenhouse gas emissions. The use of faster processors or greater parallelization reduces running time but can lead to greater carbon footprint. Finally, we provide guidance on how researchers can reduce power consumption and minimize kgCO2e. Overall, this work elucidates the carbon footprint of common analyses in bioinformatics and provides solutions which empower a move toward greener research.
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Affiliation(s)
- Jason Grealey
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia.,Department of Mathematics and Statistics, La Trobe University, Melbourne, Australia
| | - Loïc Lannelongue
- Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.,British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.,Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
| | - Woei-Yuh Saw
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
| | - Jonathan Marten
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Guillaume Méric
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia.,Department of Infectious Diseases, Central Clinical School, Monash University, Melbourne, Australia
| | - Sergio Ruiz-Carmona
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
| | - Michael Inouye
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia.,Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.,British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.,Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK.,British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge, UK.,The Alan Turing Institute, London, UK
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Ding Y, Saw WY, Tan LWL, Moong DKN, Nagarajan N, Teo YY, Seedorf H. Emergence of tigecycline- and eravacycline-resistant Tet(X4)-producing Enterobacteriaceae in the gut microbiota of healthy Singaporeans. J Antimicrob Chemother 2021; 75:3480-3484. [PMID: 32853333 DOI: 10.1093/jac/dkaa372] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2020] [Accepted: 08/03/2020] [Indexed: 01/01/2023] Open
Abstract
OBJECTIVES The recently discovered tigecycline-inactivating enzyme Tet(X4) can confer high-level tigecycline resistance on its hosts, which makes it a public health concern. This study focused on isolation and screening of Tet(X4)-positive Enterobacteriaceae from the gut microbiota of a cohort of healthy individuals in Singapore. METHODS MinION and Illumina sequencing was performed to obtain the complete genome sequences of Escherichia coli 2EC1-1 and 94EC. Subsequently, 109 human faecal samples were screened retrospectively for eravacycline-resistant Enterobacteriaceae strains, which were further tested for tet(X4) by PCR. The taxonomy of the isolated strains was determined by 16S rRNA gene PCR and Sanger sequencing. RESULTS Comparative genomic analysis of E. coli 2EC1-1 and 94EC revealed that both carry tet(X4), which is encoded by IncI1-type plasmids p2EC1-1 and p94EC-2, respectively. Retrospective screening of faecal samples collected from 109 healthy individuals showed that the faecal carriage rate of Tet(X4)-producing Enterobacteriaceae is 10.1% (95% CI = 5.1%-17.3%), suggesting that tet(X4) is widely distributed in the gut microbiota of healthy individuals in Singapore. CONCLUSIONS To the best of our knowledge, this is the first report on the prevalence of tet(X4) in the gut microbiota of a healthy human cohort, as well as the first description of this resistance mechanism outside of China. Our findings suggest that surveillance of tet(X4) in community settings is vital to monitor the spread of this resistance mechanism.
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Affiliation(s)
- Yichen Ding
- Temasek Life Sciences Laboratory, 1 Research Link, 117604, Singapore
| | - Woei-Yuh Saw
- Baker Heart and Diabetes Institute, 75 Commercial Rd, Melbourne, 3004, Victoria, Australia
| | - Linda Wei Lin Tan
- Saw Swee Hock School of Public Health, National University of Singapore, 12 Science Drive 2, 117549, Singapore
| | - Don Kyin Nwe Moong
- Saw Swee Hock School of Public Health, National University of Singapore, 12 Science Drive 2, 117549, Singapore
| | - Niranjan Nagarajan
- Genome Institute of Singapore, A*STAR, 138672, Singapore.,NUS Graduate School for Integrative Science and Engineering, National University of Singapore, 119077, Singapore
| | - Yik Ying Teo
- Saw Swee Hock School of Public Health, National University of Singapore, 12 Science Drive 2, 117549, Singapore.,Genome Institute of Singapore, A*STAR, 138672, Singapore.,NUS Graduate School for Integrative Science and Engineering, National University of Singapore, 119077, Singapore.,Department of Statistics and Applied Probability, National University of Singapore, 117546, Singapore.,Life Sciences Institute, National University of Singapore, 117456, Singapore
| | - Henning Seedorf
- Temasek Life Sciences Laboratory, 1 Research Link, 117604, Singapore.,Department of Biological Sciences, National University of Singapore, 117558, Singapore
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Kassam I, Tan S, Gan FF, Saw WY, Tan LWL, Moong DKN, Soong R, Teo YY, Loh M. Genome-wide identification of cis DNA methylation quantitative trait loci in three Southeast Asian Populations. Hum Mol Genet 2021; 30:603-618. [PMID: 33547791 DOI: 10.1093/hmg/ddab038] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2020] [Revised: 01/25/2021] [Accepted: 01/28/2021] [Indexed: 12/12/2022] Open
Abstract
DNA methylation (DNAm) is an epigenetic modification that acts to regulate gene transcription, is essential for cellular processes and plays an important role in complex traits and disease. Variation in DNAm levels is influenced by both genetic and environmental factors. Several studies have examined the extent to which common genetic variation influences DNAm (i.e. mQTLs), however, an improved understanding of mQTLs across diverse human populations is needed to increase their utility in integrative genomic studies in order to further our understanding of complex trait and disease biology. Here, we systematically examine cis-mQTLs in three Southeast Asian populations in the Singapore Integrative Omics (iOmics) Study, comprised of Chinese (n = 93), Indians (n = 83) and Malays (n = 78). A total of 24 851 cis-mQTL probes were associated with at least one SNP in meta- and ethnicity-specific analyses at a stringent significance level. These cis-mQTL probes show significant differences in local SNP heritability between the ethnicities, enrichment in functionally relevant regions using data from the Roadmap Epigenomics Mapping Consortium and are associated with nearby genes and complex traits due to pleiotropy. Importantly, DNAm prediction performance and the replication of cis-mQTLs both within iOmics and between two independent mQTL studies in European and Bangladeshi individuals is best when the genetic distance between the ethnicities is small, with differences in cis-mQTLs likely due to differences in allele frequency and linkage disequilibrium. This study highlights the importance of, and opportunities from, extending investigation of the genetic control of DNAm to Southeast Asian populations.
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Affiliation(s)
- Irfahan Kassam
- Life Sciences Institute, National University of Singapore, Singapore 117456.,Saw Swee Hock School of Public Health, National University of Singapore, Singapore 117549
| | - Sili Tan
- KK Research Centre, KK Women's and Children's Hospital, Singapore 229899
| | - Fei Fei Gan
- Department of NUH Tissue Repository, National University Health System, Singapore 119228
| | - Woei-Yuh Saw
- Baker Heart and Diabetes Institute, Melbourne Victoria, Australia 3004
| | - Linda Wei-Lin Tan
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore 117549
| | - Don Kyin Nwe Moong
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore 117549
| | - Richie Soong
- Cancer Science Institute of Singapore, National University of Singapore, Singapore 117599
| | - Yik-Ying Teo
- Life Sciences Institute, National University of Singapore, Singapore 117456.,Saw Swee Hock School of Public Health, National University of Singapore, Singapore 117549
| | - Marie Loh
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore 308232.,Department of Epidemiology and Biostatistics, Imperial College London, London, United Kingdom W2 1PG.,Translational Laboratory in Genetic Medicine, Agency for Science, Technology and Research (ASTAR), Singapore 138648
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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] [What about the content of this article? (0)] [Affiliation(s)] [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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7
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Sun J, Wei LH, Wang LX, Huang YZ, Yan S, Cheng HZ, Ong RTH, Saw WY, Fan ZQ, Deng XH, Lu Y, Zhang C, Xu SH, Jin L, Teo YY, Li H. Paternal gene pool of Malays in Southeast Asia and its applications for the early expansion of Austronesians. Am J Hum Biol 2020; 33:e23486. [PMID: 32851723 DOI: 10.1002/ajhb.23486] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2019] [Revised: 06/16/2020] [Accepted: 07/10/2020] [Indexed: 11/08/2022] Open
Abstract
OBJECTIVES The origin and differentiation of Austronesian populations and their languages have long fascinated linguists, archeologists, and geneticists. However, the founding process of Austronesians and when they separated from their close relatives, such as the Daic and Austro-Asiatic populations in the mainland of Asia, remain unclear. In this study, we explored the paternal origin of Malays in Southeast Asia and the early differentiation of Austronesians. MATERIALS AND METHODS We generated whole Y-chromosome sequences of 50 Malays and co-analyzed 200 sequences from other Austronesians and related populations. We generated a revised phylogenetic tree with time estimation. RESULTS We identified six founding paternal lineages among the studied Malays samples. These founding lineages showed a surprisingly coincident expansion age at 5000 to 6000 years ago. We also found numerous mostly close related samples of the founding lineages of Malays among populations from Mainland of Asia. CONCLUSION Our analyses provided a refined phylogenetic resolution for the dominant paternal lineages of Austronesians found by previous studies. We suggested that the co-expansion of numerous founding paternal lineages corresponds to the initial differentiation of the most recent common ancestor of modern Austronesians. The splitting time and divergence pattern in perspective of paternal Y-chromosome evidence are highly consistent with the previous theories of ethnologists, linguists, and archeologists.
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Affiliation(s)
- Jin Sun
- Department of Anthropology and Ethnology, Institute of Anthropology, Xiamen University, Xiamen, China
| | - Lan-Hai Wei
- Department of Anthropology and Ethnology, Institute of Anthropology, Xiamen University, Xiamen, China.,B&R International Joint Laboratory for Eurasian Anthropology, Fudan University, Shanghai, China
| | | | - Yun-Zhi Huang
- MOE Key Laboratory of Contemporary Anthropology, School of Life Sciences, Fudan University, Shanghai, China
| | - Shi Yan
- Human Phenome Institute, Fudan University, Shanghai, China
| | - Hui-Zhen Cheng
- Department of Anthropology and Ethnology, Institute of Anthropology, Xiamen University, Xiamen, China
| | - Rick Twee-Hee Ong
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | - 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
| | - Zhi-Quan Fan
- Department of Anthropology and Ethnology, Institute of Anthropology, Xiamen University, Xiamen, China
| | - Xiao-Hua Deng
- Department of Anthropology and Ethnology, Institute of Anthropology, Xiamen University, Xiamen, China.,Center for collation and studies of Fujian local literature, Fujian University of Technology, Fuzhou, China
| | - Yan Lu
- 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 (PICB), Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, CAS, Shanghai, China
| | - Chao Zhang
- 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 (PICB), Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, CAS, Shanghai, China.,School of Life Science and Technology, Shanghai Tech University, Shanghai, China
| | - Shu-Hua 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 (PICB), Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, CAS, Shanghai, China.,School of Life Science and Technology, Shanghai Tech University, Shanghai, China.,Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, China
| | - Li Jin
- MOE Key Laboratory of Contemporary Anthropology, School of Life Sciences, Fudan University, Shanghai, China.,Human Phenome Institute, Fudan University, Shanghai, China
| | - Yik-Ying Teo
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore.,Life Sciences Institute, National University of Singapore, Singapore, Singapore.,Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore.,NUS Graduate School for Integrative Science and Engineering, National University of Singapore, Singapore, Singapore.,Department of Statistics and Applied Probability, National University of Singapore, Singapore, Singapore
| | - Hui Li
- B&R International Joint Laboratory for Eurasian Anthropology, Fudan University, Shanghai, China.,MOE Key Laboratory of Contemporary Anthropology, School of Life Sciences, Fudan University, Shanghai, China.,Human Phenome Institute, Fudan University, Shanghai, China
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8
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Tedja MS, Wojciechowski R, Hysi PG, Eriksson N, Furlotte NA, Verhoeven VJ, Iglesias AI, Meester-Smoor MA, Tompson SW, Fan Q, Khawaja AP, Cheng CY, Höhn R, Yamashiro K, Wenocur A, Grazal C, Haller T, Metspalu A, Wedenoja J, Jonas JB, Wang YX, Xie J, Mitchell P, Foster PJ, Klein BE, Klein R, Paterson AD, Hosseini SM, Shah RL, Williams C, Teo YY, Tham YC, Gupta P, Zhao W, Shi Y, Saw WY, Tai ES, Sim XL, Huffman JE, Polašek O, Hayward C, Bencic G, Rudan I, Wilson JF, Joshi PK, Tsujikawa A, Matsuda F, Whisenhunt KN, Zeller T, van der Spek PJ, Haak R, Meijers-Heijboer H, van Leeuwen EM, Iyengar SK, Lass JH, Hofman A, Rivadeneira F, Uitterlinden AG, Vingerling JR, Lehtimäki T, Raitakari OT, Biino G, Concas MP, Schwantes-An TH, Igo RP, Cuellar-Partida G, Martin NG, Craig JE, Gharahkhani P, Williams KM, Nag A, Rahi JS, Cumberland PM, Delcourt C, Bellenguez C, Ried JS, Bergen AA, Meitinger T, Gieger C, Wong TY, Hewitt AW, Mackey DA, Simpson CL, Pfeiffer N, Pärssinen O, Baird PN, Vitart V, Amin N, van Duijn CM, Bailey-Wilson JE, Young TL, Saw SM, Stambolian D, MacGregor S, Guggenheim JA, Tung JY, Hammond CJ, Klaver CC. Genome-wide association meta-analysis highlights light-induced signaling as a driver for refractive error. Nat Genet 2018; 50:834-848. [PMID: 29808027 PMCID: PMC5980758 DOI: 10.1038/s41588-018-0127-7] [Citation(s) in RCA: 191] [Impact Index Per Article: 31.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2017] [Accepted: 03/26/2018] [Indexed: 12/18/2022]
Abstract
Refractive errors, including myopia, are the most frequent eye disorders worldwide and an increasingly common cause of blindness. This genome-wide association meta-analysis in 160,420 participants and replication in 95,505 participants increased the number of established independent signals from 37 to 161 and showed high genetic correlation between Europeans and Asians (>0.78). Expression experiments and comprehensive in silico analyses identified retinal cell physiology and light processing as prominent mechanisms, and also identified functional contributions to refractive-error development in all cell types of the neurosensory retina, retinal pigment epithelium, vascular endothelium and extracellular matrix. Newly identified genes implicate novel mechanisms such as rod-and-cone bipolar synaptic neurotransmission, anterior-segment morphology and angiogenesis. Thirty-one loci resided in or near regions transcribing small RNAs, thus suggesting a role for post-transcriptional regulation. Our results support the notion that refractive errors are caused by a light-dependent retina-to-sclera signaling cascade and delineate potential pathobiological molecular drivers.
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Affiliation(s)
- Milly S. Tedja
- Department of Ophthalmology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Robert Wojciechowski
- Department of Epidemiology and Medicine, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
- Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA
- Wilmer Eye Institute, Johns Hopkins Medical Institutions, Baltimore, Maryland, USA
| | - Pirro G. Hysi
- Section of Academic Ophthalmology, School of Life Course Sciences, King’s College London, London, UK
| | | | | | - Virginie J.M. Verhoeven
- Department of Ophthalmology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Clinical Genetics, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Adriana I. Iglesias
- Department of Ophthalmology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Clinical Genetics, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Magda A. Meester-Smoor
- Department of Ophthalmology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Stuart W. Tompson
- Department of Ophthalmology and Visual Sciences, University of Wisconsin–Madison, Madison, Wisconsin, USA
| | - Qiao Fan
- Centre for Quantitative Medicine, DUKE-National University of Singapore, Singapore
| | - Anthony P. Khawaja
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- NIHR Biomedical Research Centre, Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London, UK
| | - Ching-Yu Cheng
- Centre for Quantitative Medicine, DUKE-National University of Singapore, Singapore
- Ocular Epidemiology Research Group, Singapore Eye Research Institute, Singapore National Eye Centre, Singapore
| | - René Höhn
- Department of Ophthalmology, University Hospital Bern, Inselspital, University of Bern, Bern, Switzerland
- Department of Ophthalmology, University Medical Center Mainz, Mainz, Germany
| | - Kenji Yamashiro
- Department of Ophthalmology and Visual Sciences, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Adam Wenocur
- Department of Ophthalmology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Clare Grazal
- Department of Ophthalmology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Toomas Haller
- Estonian Genome Center, University of Tartu, Tartu, Estonia
| | | | - Juho Wedenoja
- Department of Ophthalmology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Jost B. Jonas
- Department of Ophthalmology, Medical Faculty Mannheim of the Ruprecht-Karls-University of Heidelberg, Mannheim, Germany
- Beijing Institute of Ophthalmology, Beijing Key Laboratory of Ophthalmology and Visual Sciences, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Ya Xing Wang
- Beijing Institute of Ophthalmology, Beijing Key Laboratory of Ophthalmology and Visual Sciences, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Jing Xie
- Centre for Eye Research Australia, Ophthalmology, Department of Surgery, University of Melbourne, Royal Victorian Eye and Ear Hospital, Melbourne, Australia
| | - Paul Mitchell
- Department of Ophthalmology, Centre for Vision Research, Westmead Institute for Medical Research, University of Sydney, Sydney, Australia
| | - Paul J. Foster
- NIHR Biomedical Research Centre, Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London, UK
| | - Barbara E.K. Klein
- Department of Ophthalmology and Visual Sciences, University of Wisconsin–Madison, Madison, Wisconsin, USA
| | - Ronald Klein
- Department of Ophthalmology and Visual Sciences, University of Wisconsin–Madison, Madison, Wisconsin, USA
| | - Andrew D. Paterson
- Program in Genetics and Genome Biology, Hospital for Sick Children and University of Toronto, Toronto, Ontario, Canada
| | - S. Mohsen Hosseini
- Program in Genetics and Genome Biology, Hospital for Sick Children and University of Toronto, Toronto, Ontario, Canada
| | - Rupal L. Shah
- School of Optometry & Vision Sciences, Cardiff University, Cardiff, UK
| | - Cathy Williams
- Department of Population Health Sciences, Bristol Medical School, Bristol, UK
| | - Yik Ying Teo
- Department of Statistics and Applied Probability, National University of Singapore, Singapore
- Saw Swee Hock School of Public Health, National University Health Systems, National University of Singapore, Singapore
| | - Yih Chung Tham
- Ocular Epidemiology Research Group, Singapore Eye Research Institute, Singapore National Eye Centre, Singapore
| | - Preeti Gupta
- Department of Health Service Research, Singapore Eye Research Institute, Singapore National Eye Centre, Singapore
| | - Wanting Zhao
- Centre for Quantitative Medicine, DUKE-National University of Singapore, Singapore
- Statistics Support Platform, Singapore Eye Research Institute, Singapore National Eye Centre, Singapore
| | - Yuan Shi
- Statistics Support Platform, Singapore Eye Research Institute, Singapore National Eye Centre, Singapore
| | - Woei-Yuh Saw
- Life Sciences Institute, National University of Singapore, Singapore
| | - E-Shyong Tai
- Saw Swee Hock School of Public Health, National University Health Systems, National University of Singapore, Singapore
| | - Xue Ling Sim
- Saw Swee Hock School of Public Health, National University Health Systems, National University of Singapore, Singapore
| | - Jennifer E. Huffman
- MRC Human Genetics Unit, MRC Institute of Genetics & Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Ozren Polašek
- Faculty of Medicine, University of Split, Split, Croatia
| | - Caroline Hayward
- MRC Human Genetics Unit, MRC Institute of Genetics & Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Goran Bencic
- Department of Ophthalmology, Sisters of Mercy University Hospital, Zagreb, Croatia
| | - Igor Rudan
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - James F. Wilson
- MRC Human Genetics Unit, MRC Institute of Genetics & Molecular Medicine, University of Edinburgh, Edinburgh, UK
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | | | | | | | - Peter K. Joshi
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - Akitaka Tsujikawa
- Department of Ophthalmology and Visual Sciences, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Fumihiko Matsuda
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Kristina N. Whisenhunt
- Department of Ophthalmology and Visual Sciences, University of Wisconsin–Madison, Madison, Wisconsin, USA
| | - Tanja Zeller
- Clinic for General and Interventional Cardiology, University Heart Center Hamburg, Hamburg, Germany
| | | | - Roxanna Haak
- Department of Bioinformatics, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Hanne Meijers-Heijboer
- Department of Clinical Genetics, Academic Medical Center, Amsterdam, The Netherlands
- Department of Clinical Genetics, VU University Medical Center, Amsterdam, The Netherlands
| | - Elisabeth M. van Leeuwen
- Department of Ophthalmology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Sudha K. Iyengar
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, Ohio, USA
- Department of Ophthalmology and Visual Sciences, Case Western Reserve University and University Hospitals Eye Institute, Cleveland, Ohio, USA
- Department of Genetics, Case Western Reserve University, Cleveland, Ohio, USA
| | - Jonathan H. Lass
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, Ohio, USA
- Department of Ophthalmology and Visual Sciences, Case Western Reserve University and University Hospitals Eye Institute, Cleveland, Ohio, USA
| | - Albert Hofman
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Epidemiology, Harvard T.HChan School of Public Health, Boston, Massachusetts, USA
- Netherlands Consortium for Healthy Ageing, Netherlands Genomics Initiative, the Hague, the Netherlands
| | - Fernando Rivadeneira
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
- Netherlands Consortium for Healthy Ageing, Netherlands Genomics Initiative, the Hague, the Netherlands
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - André G. Uitterlinden
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
- Netherlands Consortium for Healthy Ageing, Netherlands Genomics Initiative, the Hague, the Netherlands
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | | | - Terho Lehtimäki
- Department of Clinical Chemistry, Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Life Sciences, University of Tampere
- Department of Clinical Chemistry, Fimlab Laboratories, University of Tampere, Tampere, Finland
| | - Olli T. Raitakari
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
| | - Ginevra Biino
- Institute of Molecular Genetics, National Research Council of Italy, Sassari, Italy
| | - Maria Pina Concas
- Institute for Maternal and Child Health - IRCCS “Burlo Garofolo”, Trieste, Italy
| | - Tae-Hwi Schwantes-An
- Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA
- Department of Medical and Molecular Genetics, Indiana University, School of Medicine, Indianapolis, Indiana, USA
| | - Robert P. Igo
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, Ohio, USA
| | | | - Nicholas G. Martin
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Jamie E. Craig
- Department of Ophthalmology, Flinders University, Adelaide, Australia
| | - Puya Gharahkhani
- Statistical Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Katie M. Williams
- Section of Academic Ophthalmology, School of Life Course Sciences, King’s College London, London, UK
| | - Abhishek Nag
- Department of Twin Research and Genetic Epidemiology, King’s College London, London, UK
| | - Jugnoo S. Rahi
- NIHR Biomedical Research Centre, Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London, UK
- Great Ormond Street Institute of Child Health, University College London, London, UK
- Ulverscroft Vision Research Group, University College London, London, UK
| | | | - Cécile Delcourt
- Université de Bordeaux, Inserm, Bordeaux Population Health Research Center, team LEHA, UMR 1219, F-33000 Bordeaux, France
| | - Céline Bellenguez
- Institut Pasteur de Lille, Lille, France
- Inserm, U1167, RID-AGE - Risk factors and molecular determinants of aging-related diseases, Lille, France
- Université de Lille, U1167 - Excellence Laboratory LabEx DISTALZ, Lille, France
| | - Janina S. Ried
- Institute of Genetic Epidemiology, Helmholtz Zentrum München—German Research Center for Environmental Health, Neuherberg, Germany
| | - Arthur A. Bergen
- Department of Clinical Genetics, Academic Medical Center, Amsterdam, The Netherlands
- Department of Ophthalmology, Academic Medical Center, Amsterdam, The Netherlands
- The Netherlands Institute for Neurosciences (NIN-KNAW), Amsterdam, The Netherlands
| | - Thomas Meitinger
- Institute of Human Genetics, Helmholtz Zentrum München, Neuherberg, Germany
- Institute of Human Genetics, Klinikum rechts der Isar, Technische Universität München, Munich, Germany
| | - Christian Gieger
- Institute of Genetic Epidemiology, Helmholtz Zentrum München—German Research Center for Environmental Health, Neuherberg, Germany
| | - Tien Yin Wong
- Academic Medicine Research Institute, Singapore
- Retino Center, Singapore National Eye Centre, Singapore, Singapore
| | - Alex W. Hewitt
- Centre for Eye Research Australia, Ophthalmology, Department of Surgery, University of Melbourne, Royal Victorian Eye and Ear Hospital, Melbourne, Australia
- Department of Ophthalmology, Menzies Institute of Medical Research, University of Tasmania, Hobart, Australia
- Centre for Ophthalmology and Visual Science, Lions Eye Institute, University of Western Australia, Perth, Australia
| | - David A. Mackey
- Centre for Eye Research Australia, Ophthalmology, Department of Surgery, University of Melbourne, Royal Victorian Eye and Ear Hospital, Melbourne, Australia
- Department of Ophthalmology, Menzies Institute of Medical Research, University of Tasmania, Hobart, Australia
- Centre for Ophthalmology and Visual Science, Lions Eye Institute, University of Western Australia, Perth, Australia
| | - Claire L. Simpson
- Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Sciences Center, Memphis, Tenessee
| | - Norbert Pfeiffer
- Department of Ophthalmology, University Medical Center Mainz, Mainz, Germany
| | - Olavi Pärssinen
- Department of Ophthalmology, Central Hospital of Central Finland, Jyväskylä, Finland
- Gerontology Research Center, Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland
| | - Paul N. Baird
- Centre for Eye Research Australia, Ophthalmology, Department of Surgery, University of Melbourne, Royal Victorian Eye and Ear Hospital, Melbourne, Australia
| | - Veronique Vitart
- MRC Human Genetics Unit, MRC Institute of Genetics & Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Najaf Amin
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | | | - Joan E. Bailey-Wilson
- Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Terri L. Young
- Department of Ophthalmology and Visual Sciences, University of Wisconsin–Madison, Madison, Wisconsin, USA
| | - Seang-Mei Saw
- Saw Swee Hock School of Public Health, National University Health Systems, National University of Singapore, Singapore
- Myopia Research Group, Singapore Eye Research Institute, Singapore National Eye Centre, Singapore
| | - Dwight Stambolian
- Department of Ophthalmology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Stuart MacGregor
- Statistical Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | | | | | - Christopher J. Hammond
- Section of Academic Ophthalmology, School of Life Course Sciences, King’s College London, London, UK
| | - Caroline C.W. Klaver
- Department of Ophthalmology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Ophthalmology, Radboud University Medical Center, Nijmegen, The Netherlands
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9
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Lim HW, Saw WY, Feng L, Lee YK, Mahendran R, Cheah IKM, Rawtaer I, Kumar AP, Kua EH, Mahendran R, Tan EC. Dataset on gene expression in the elderly after Mindfulness Awareness Practice or Health Education Program. Data Brief 2018; 18:902-912. [PMID: 29900257 PMCID: PMC5996403 DOI: 10.1016/j.dib.2018.03.086] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2018] [Revised: 03/15/2018] [Accepted: 03/20/2018] [Indexed: 12/20/2022] Open
Abstract
It has been reported that relaxation techniques can improve physical health and cognitive function. A number of studies involving different types of relaxation practices showed changes in expression of genes. We investigated the gene expression pattern of a cohort of elderly subjects of Asian descent after weekly (for the first three months) and monthly (for the subsequent six months) intervention. Sixty consenting elderly subjects (aged 60-90 years) with mild cognitive impairment were assigned to either the Mindfulness Awareness Practice (MAP) or Health Education Program (HEP) group in a randomized controlled trial to assess the effectiveness of the programs in preventing further cognitive decline and evaluate the influence on neurological, cellular and biochemical factors. Blood samples were collected before the start of intervention and after nine months for gene expression profiling using Affymetrix Human Genome U133 Plus 2.0 arrays. The dataset is publicly available for further analyses.
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Affiliation(s)
- Hwee-Woon Lim
- KK Research Laboratory, KK Women's and Children's Hospital, Singapore
| | - Woei-Yuh Saw
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore.,Life Sciences Institute, National University of Singapore, Singapore
| | - Lei Feng
- Department of Psychological Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Yuan-Kun Lee
- Department of Microbiology and Immunology, Yong Loo Lin School of Medicine, National University Hospital, Singapore
| | - Ratha Mahendran
- Department of Surgery, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Irwin Kee-Mun Cheah
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Iris Rawtaer
- Department of Psychological Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Alan Prem Kumar
- Medical Science Cluster, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.,Cancer Science Institute of Singapore, National University of Singapore, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Ee-Heok Kua
- Department of Psychological Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Rathi Mahendran
- Department of Psychological Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.,Duke-NUS Medical School, Singapore
| | - Ene-Choo Tan
- KK Research Laboratory, KK Women's and Children's Hospital, Singapore.,SingHealth Duke-NUS Paediatrics Academic Clinical Program, Singapore
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10
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Takeuchi F, Katsuya T, Kimura R, Nabika T, Isomura M, Ohkubo T, Tabara Y, Yamamoto K, Yokota M, Liu X, Saw WY, Mamatyusupu D, Yang W, Xu S, Teo YY, Kato N. The fine-scale genetic structure and evolution of the Japanese population. PLoS One 2017; 12:e0185487. [PMID: 29091727 PMCID: PMC5665431 DOI: 10.1371/journal.pone.0185487] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2016] [Accepted: 09/13/2017] [Indexed: 11/21/2022] Open
Abstract
The contemporary Japanese populations largely consist of three genetically distinct groups—Hondo, Ryukyu and Ainu. By principal-component analysis, while the three groups can be clearly separated, the Hondo people, comprising 99% of the Japanese, form one almost indistinguishable cluster. To understand fine-scale genetic structure, we applied powerful haplotype-based statistical methods to genome-wide single nucleotide polymorphism data from 1600 Japanese individuals, sampled from eight distinct regions in Japan. We then combined the Japanese data with 26 other Asian populations data to analyze the shared ancestry and genetic differentiation. We found that the Japanese could be separated into nine genetic clusters in our dataset, showing a marked concordance with geography; and that major components of ancestry profile of Japanese were from the Korean and Han Chinese clusters. We also detected and dated admixture in the Japanese. While genetic differentiation between Ryukyu and Hondo was suggested to be caused in part by positive selection, genetic differentiation among the Hondo clusters appeared to result principally from genetic drift. Notably, in Asians, we found the possibility that positive selection accentuated genetic differentiation among distant populations but attenuated genetic differentiation among close populations. These findings are significant for studies of human evolution and medical genetics.
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Affiliation(s)
- Fumihiko Takeuchi
- Department of Gene Diagnostics and Therapeutics, National Center for Global Health and Medicine, Tokyo, Japan
- * E-mail: (FT); (NK)
| | - 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
| | - Minoru Isomura
- 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
| | - 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
| | - Xuanyao Liu
- 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, Singapore
| | - Woei-Yuh Saw
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore
- Life Sciences Institute, National University of Singapore, Singapore, Singapore
| | - 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, Yinchuan, Ningxia, China
| | - 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
- Department of Gene Diagnostics and Therapeutics, National Center for Global Health and Medicine, Tokyo, Japan
- 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, Singapore
- Life Sciences Institute, National University of Singapore, Singapore, Singapore
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore
- Department of Statistics and Applied Probability, National University of Singapore, Singapore, Singapore
| | - Norihiro Kato
- Department of Gene Diagnostics and Therapeutics, National Center for Global Health and Medicine, Tokyo, Japan
- * E-mail: (FT); (NK)
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11
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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] [What about the content of this article? (0)] [Affiliation(s)] [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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12
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Wei LH, Yan S, Teo YY, Huang YZ, Wang LX, Yu G, Saw WY, Ong RTH, Lu Y, Zhang C, Xu SH, Jin L, Li H. Phylogeography of Y-chromosome haplogroup O3a2b2-N6 reveals patrilineal traces of Austronesian populations on the eastern coastal regions of Asia. PLoS One 2017; 12:e0175080. [PMID: 28380021 PMCID: PMC5381892 DOI: 10.1371/journal.pone.0175080] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2016] [Accepted: 03/20/2017] [Indexed: 12/31/2022] Open
Abstract
Austronesian diffusion is considered one of the greatest dispersals in human history; it led to the peopling of an extremely vast region, ranging from Madagascar in the Indian Ocean to Easter Island in Remote Oceania. The Y-chromosome haplogroup O3a2b*-P164(xM134), a predominant paternal lineage of Austronesian populations, is found at high frequencies in Polynesian populations. However, the internal phylogeny of this haplogroup remains poorly investigated. In this study, we analyzed -seventeen Y-chromosome sequences of haplogroup O3a2b*-P164(xM134) and generated a revised phylogenetic tree of this lineage based on 310 non-private Y-chromosome polymorphisms. We discovered that all available O3a2b*-P164(xM134) samples belong to the newly defined haplogroup O3a2b2-N6 and samples from Austronesian populations belong to the sublineage O3a2b2a2-F706. Additionally, we genotyped a series of Y-chromosome polymorphisms in a large collection of samples from China. We confirmed that the sublineage O3a2b2a2b-B451 is unique to Austronesian populations. We found that O3a2b2-N6 samples are widely distributed on the eastern coastal regions of Asia, from Korea to Vietnam. Furthermore, we propose- that the O3a2b2a2b-B451 lineage represents a genetic connection between ancestors of Austronesian populations and ancient populations in North China, where foxtail millet was domesticated about 11,000 years ago. The large number of newly defined Y-chromosome polymorphisms and the revised phylogenetic tree of O3a2b2-N6 will be helpful to explore the origin of proto-Austronesians and the early diffusion process of Austronesian populations.
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Affiliation(s)
- Lan-Hai Wei
- MOE Key Laboratory of Contemporary Anthropology, School of Life Sciences, Fudan University, Shanghai, China
- Institut National des Langues et Civilisations Orientales, Paris, France
| | - Shi Yan
- MOE Key Laboratory of Contemporary Anthropology, School of Life Sciences, Fudan University, Shanghai, China
| | - Yik-Ying Teo
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | - Yun-Zhi Huang
- MOE Key Laboratory of Contemporary Anthropology, School of Life Sciences, Fudan University, Shanghai, China
| | - Ling-Xiang Wang
- MOE Key Laboratory of Contemporary Anthropology, School of Life Sciences, Fudan University, Shanghai, China
| | - Ge Yu
- MOE Key Laboratory of Contemporary Anthropology, School of Life Sciences, Fudan University, Shanghai, China
| | - Woei-Yuh Saw
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | - Rick Twee-Hee Ong
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | - Yan Lu
- Chinese Academy of Sciences and Max Planck Society (CAS-MPG) Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Chao Zhang
- Chinese Academy of Sciences and Max Planck Society (CAS-MPG) Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Shu-Hua Xu
- Chinese Academy of Sciences and Max Planck Society (CAS-MPG) Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China
- University of Chinese Academy of Sciences, Beijing, China
- School of Life Science and Technology, ShanghaiTech University, Shanghai, China
- Collaborative Innovation Center of Genetics and Development, Shanghai, China
| | - Li Jin
- MOE Key Laboratory of Contemporary Anthropology, School of Life Sciences, Fudan University, Shanghai, China
- Collaborative Innovation Center of Genetics and Development, Shanghai, China
| | - Hui Li
- MOE Key Laboratory of Contemporary Anthropology, School of Life Sciences, Fudan University, Shanghai, China
- * E-mail:
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13
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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] [What about the content of this article? (0)] [Affiliation(s)] [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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14
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Saw WY, Liu X, Khor CC, Takeuchi F, Katsuya T, Kimura R, Nabika T, Ohkubo T, Tabara Y, Yamamoto K, Yokota M, Teo YY, Kato N. Mapping the genetic diversity of HLA haplotypes in the Japanese populations. Sci Rep 2015; 5:17855. [PMID: 26648100 PMCID: PMC4673465 DOI: 10.1038/srep17855] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2015] [Accepted: 11/06/2015] [Indexed: 11/09/2022] Open
Abstract
Japan has often been viewed as an Asian country that possesses a genetically homogenous community. The basis for partitioning the country into prefectures has largely been geographical, although cultural and linguistic differences still exist between some of the districts/prefectures, especially between Okinawa and the mainland prefectures. The Major Histocompatibility Complex (MHC) region has consistently emerged as the most polymorphic region in the human genome, harbouring numerous biologically important variants; nevertheless the presence of population-specific long haplotypes hinders the imputation of SNPs and classical HLA alleles. Here, we examined the extent of genetic variation at the MHC between eight Japanese populations sampled from Okinawa, and six other prefectures located in or close to the mainland of Japan, specifically focusing at the haplotypes observed within each population, and what the impact of any variation has on imputation. Our results indicated that Okinawa was genetically farther to the mainland Japanese than were Gujarati Indians from Tamil Indians, while the mainland Japanese from six prefectures were more homogeneous than between northern and southern Han Chinese. The distribution of haplotypes across Japan was similar, although imputation was most accurate for Okinawa and several mainland prefectures when population-specific panels were used as reference.
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Affiliation(s)
- Woei-Yuh Saw
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore 117549.,Life Sciences Institute, National University of Singapore, Singapore 117456
| | - Xuanyao Liu
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore 117549.,NUS Graduate School for Integrative Science and Engineering, National University of Singapore, Singapore 117456
| | - Chiea-Chuen Khor
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore 138672
| | - Fumihiko Takeuchi
- Department of Gene Diagnostics and Therapeutics, National Center for Global Health and Medicine, Tokyo, Japan 162-8655
| | - Tomohiro Katsuya
- Department of Clinical Gene Therapy, Osaka University Graduate School of Medicine, Suita, Japan 565-0871
| | - Ryosuke Kimura
- Department of Human Biology and Anatomy, Graduate School of Medicine, University of the Ryukyus, Nishihara-cho, Japan 903-0215
| | - Toru Nabika
- Department of Functional Pathology, Shimane University School of Medicine, Izumo, Japan 693-8501
| | - Takayoshi Ohkubo
- Department of Hygiene and Public Health, Teikyo University School of Medicine, Tokyo, Japan 162-8655
| | - Yasuharu Tabara
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan 606-8501
| | - Ken Yamamoto
- Department of Medical Chemistry, Kurume University School of Medicine, Kurume, Japan 830-0011
| | - Mitsuhiro Yokota
- Department of Genome Science, School of Dentistry, Aichi Gakuin University, Nagoya, Japan 464-8651
| | | | - Yik-Ying Teo
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore 117549.,Life Sciences Institute, National University of Singapore, Singapore 117456.,NUS Graduate School for Integrative Science and Engineering, National University of Singapore, Singapore 117456.,Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore 138672.,Department of Gene Diagnostics and Therapeutics, National Center for Global Health and Medicine, Tokyo, Japan 162-8655.,Department of Statistics and Applied Probability, National University of Singapore, Singapore
| | - Norihiro Kato
- Department of Gene Diagnostics and Therapeutics, National Center for Global Health and Medicine, Tokyo, Japan 162-8655
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15
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Kim K, Bang SY, Lee HS, Okada Y, Han B, Saw WY, Teo YY, Bae SC. The HLA-DRβ1 amino acid positions 11–13–26 explain the majority of SLE–MHC associations. Nat Commun 2014; 5:5902. [DOI: 10.1038/ncomms6902] [Citation(s) in RCA: 69] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2014] [Accepted: 11/17/2014] [Indexed: 01/05/2023] Open
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16
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Tantoso E, Wong LP, Li B, Saw WY, Xu W, Little P, Ong RTH, Teo YY. Evaluating the coverage and potential of imputing the exome microarray with next-generation imputation using the 1000 Genomes Project. PLoS One 2014; 9:e106681. [PMID: 25203698 PMCID: PMC4159276 DOI: 10.1371/journal.pone.0106681] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2014] [Accepted: 07/29/2014] [Indexed: 11/18/2022] Open
Abstract
Next-generation genotyping microarrays have been designed with insights from large-scale sequencing of exomes and whole genomes. The exome genotyping arrays promise to query the functional regions of the human genome at a fraction of the sequencing cost, thus allowing large number of samples to be genotyped. However, two pertinent questions exist: firstly, how representative is the content of the exome chip for populations not involved in the design of the chip; secondly, can the content of the exome chip be imputed with the reference data from the 1000 Genomes Project (1KGP). By deep whole-genome sequencing two Asian populations that are not part of the 1KGP, comprising 96 Southeast Asian Malays and 36 South Asian Indians for which the same samples have also been genotyped on both the Illumina 2.5 M and exome microarrays, we discovered the exome chip is a poor representation of exonic content in our two populations. However, up to 94.1% of the variants on the exome chip that are polymorphic in our populations can be confidently imputed with existing non-exome-centric microarrays using the 1KGP panel. The coverage further increases if there exists population-specific reference data from whole-genome sequencing. There is thus limited gain in using the exome chip for populations not involved in the microarray design. Instead, for the same cost of genotyping 2,000 samples on the exome chip, performing whole-genome sequencing of at least 35 samples in that population to complement the 1KGP may yield a higher coverage of the exonic content from imputation instead.
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Affiliation(s)
- Erwin Tantoso
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | - Lai-Ping Wong
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | - Bowen Li
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | - Woei-Yuh Saw
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | - Wenting Xu
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | - Peter Little
- Life Sciences Institute, National University of Singapore, Singapore, Singapore
| | - Rick Twee-Hee Ong
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | - Yik-Ying Teo
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
- Life Sciences Institute, National University of Singapore, Singapore, Singapore
- Department of Statistics and Applied Probability, National University of Singapore, Singapore, Singapore
- NUS Graduate School for Integrative Science and Engineering, National University of Singapore, Singapore, Singapore
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore
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17
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Okada Y, Kim K, Han B, Pillai NE, Ong RTH, Saw WY, Luo M, Jiang L, Yin J, Bang SY, Lee HS, Brown MA, Bae SC, Xu H, Teo YY, de Bakker PIW, Raychaudhuri S. Risk for ACPA-positive rheumatoid arthritis is driven by shared HLA amino acid polymorphisms in Asian and European populations. Hum Mol Genet 2014; 23:6916-26. [PMID: 25070946 DOI: 10.1093/hmg/ddu387] [Citation(s) in RCA: 119] [Impact Index Per Article: 11.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023] Open
Abstract
Previous studies have emphasized ethnically heterogeneous human leukocyte antigen (HLA) classical allele associations to rheumatoid arthritis (RA) risk. We fine-mapped RA risk alleles within the major histocompatibility complex (MHC) in 2782 seropositive RA cases and 4315 controls of Asian descent. We applied imputation to determine genotypes for eight class I and II HLA genes to Asian populations for the first time using a newly constructed pan-Asian reference panel. First, we empirically measured high imputation accuracy in Asian samples. Then we observed the most significant association in HLA-DRβ1 at amino acid position 13, located outside the classical shared epitope (Pomnibus = 6.9 × 10(-135)). The individual residues at position 13 have relative effects that are consistent with published effects in European populations (His > Phe > Arg > Tyr ≅ Gly > Ser)--but the observed effects in Asians are generally smaller. Applying stepwise conditional analysis, we identified additional independent associations at positions 57 (conditional Pomnibus = 2.2 × 10(-33)) and 74 (conditional Pomnibus = 1.1 × 10(-8)). Outside of HLA-DRβ1, we observed independent effects for amino acid polymorphisms within HLA-B (Asp9, conditional P = 3.8 × 10(-6)) and HLA-DPβ1 (Phe9, conditional P = 3.0 × 10(-5)) concordant with European populations. Our trans-ethnic HLA fine-mapping study reveals that (i) a common set of amino acid residues confer shared effects in European and Asian populations and (ii) these same effects can explain ethnically heterogeneous classical allelic associations (e.g. HLA-DRB1*09:01) due to allele frequency differences between populations. Our study illustrates the value of high-resolution imputation for fine-mapping causal variants in the MHC.
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Affiliation(s)
- Yukinori Okada
- Department of Human Genetics and Disease Diversity, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, Tokyo, Japan Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan Division of Rheumatology, Immunology, and Allergy and Division of Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
| | - Kwangwoo Kim
- Division of Rheumatology, Immunology, and Allergy and Division of Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA Department of Rheumatology, Hanyang University Hospital for Rheumatic Diseases, Seoul, South Korea
| | - Buhm Han
- Division of Rheumatology, Immunology, and Allergy and Division of Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
| | | | | | | | - Ma Luo
- Department of Medical Microbiology, University of Manitoba, Winnepeg, Canada National Microbiology Laboratory, Winnipeg, Canada
| | - Lei Jiang
- Department of Rheumatology and Immunology, Shanghai Changzheng Hospital, The Second Military Medical University, Shanghai, China
| | - Jian Yin
- Department of Rheumatology and Immunology, Shanghai Changzheng Hospital, The Second Military Medical University, Shanghai, China
| | - So-Young Bang
- Department of Rheumatology, Hanyang University Hospital for Rheumatic Diseases, Seoul, South Korea
| | - Hye-Soon Lee
- Department of Rheumatology, Hanyang University Hospital for Rheumatic Diseases, Seoul, South Korea
| | - Matthew A Brown
- The University of Queensland Diamantina Institute, Translational Research Institute, Princess Alexandra Hospital, University of Queensland, Brisbane, QLD, Australia
| | - Sang-Cheol Bae
- Department of Rheumatology, Hanyang University Hospital for Rheumatic Diseases, Seoul, South Korea
| | - Huji Xu
- Department of Rheumatology and Immunology, Shanghai Changzheng Hospital, The Second Military Medical University, Shanghai, China
| | - Yik-Ying Teo
- Saw Swee Hock School of Public Health Life Sciences Institute Department of Statistics and Applied Probability and NUS Graduate School for Integrative Science and Engineering, National University of Singapore, Singapore, Singapore Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore
| | - Paul I W de Bakker
- Department of Medical Genetics, Center for Molecular Medicine and Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands and
| | - Soumya Raychaudhuri
- Division of Rheumatology, Immunology, and Allergy and Division of Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA NIHR Manchester Musculoskeletal Biomedical, Research Unit, Central Manchester NHS Foundation Trust, Manchester Academic Health Sciences Centre, Manchester, UK
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18
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Wong LP, Lai JKH, Saw WY, Ong RTH, Cheng AY, Pillai NE, Liu X, Xu W, Chen P, Foo JN, Tan LWL, Koo SH, Soong R, Wenk MR, Lim WY, Khor CC, Little P, Chia KS, Teo YY. Insights into the genetic structure and diversity of 38 South Asian Indians from deep whole-genome sequencing. PLoS Genet 2014; 10:e1004377. [PMID: 24832686 PMCID: PMC4022468 DOI: 10.1371/journal.pgen.1004377] [Citation(s) in RCA: 37] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2013] [Accepted: 03/28/2014] [Indexed: 12/18/2022] Open
Abstract
South Asia possesses a significant amount of genetic diversity due to considerable intergroup differences in culture and language. There have been numerous reports on the genetic structure of Asian Indians, although these have mostly relied on genotyping microarrays or targeted sequencing of the mitochondria and Y chromosomes. Asian Indians in Singapore are primarily descendants of immigrants from Dravidian-language–speaking states in south India, and 38 individuals from the general population underwent deep whole-genome sequencing with a target coverage of 30X as part of the Singapore Sequencing Indian Project (SSIP). The genetic structure and diversity of these samples were compared against samples from the Singapore Sequencing Malay Project and populations in Phase 1 of the 1,000 Genomes Project (1 KGP). SSIP samples exhibited greater intra-population genetic diversity and possessed higher heterozygous-to-homozygous genotype ratio than other Asian populations. When compared against a panel of well-defined Asian Indians, the genetic makeup of the SSIP samples was closely related to South Indians. However, even though the SSIP samples clustered distinctly from the Europeans in the global population structure analysis with autosomal SNPs, eight samples were assigned to mitochondrial haplogroups that were predominantly present in Europeans and possessed higher European admixture than the remaining samples. An analysis of the relative relatedness between SSIP with two archaic hominins (Denisovan, Neanderthal) identified higher ancient admixture in East Asian populations than in SSIP. The data resource for these samples is publicly available and is expected to serve as a valuable complement to the South Asian samples in Phase 3 of 1 KGP. Indians of South Asia has long been a population of interest to a wide audience, due to its unique diversity. We have deep-sequenced 38 individuals of Indian descent residing in Singapore (SSIP) in an effort to illustrate their diversity from a whole-genome standpoint. Indeed, among Asians in our population panel, SSIP was most diverse, followed by the Malays in Singapore (SSMP). Their diversity is further observed in the population's chromosome Y haplogroup and mitochondria haplogroup profiles; individuals with European-dominant haplogroups had greater proportion of European admixture. Among variants (single nucleotide polymorphism and small insertions/deletions) discovered in SSIP, 21.69% were novel with respect to previous sequencing projects. In addition, some 14 loss-of-function variants (LOFs) were associated to cancer, Type II diabetes, and cholesterol levels. Finally, D statistic test with ancient hominids concurred that there was gene flow to East Asians compared to South Asians.
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Affiliation(s)
- Lai-Ping Wong
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore
| | - Jason Kuan-Han Lai
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore
| | - Woei-Yuh Saw
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore
| | - Rick Twee-Hee Ong
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore
| | - Anthony Youzhi Cheng
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore
| | | | - Xuanyao Liu
- 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
| | - Wenting Xu
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore
| | - Peng Chen
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore
| | - Jia-Nee Foo
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore
| | - Linda Wei-Lin Tan
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore
| | - Seok-Hwee Koo
- Pharmacogenetics Laboratory, National University of Singapore, Singapore
| | - Richie Soong
- Cancer Science Institute of Singapore, National University of Singapore, Singapore
| | - Markus Rene Wenk
- Department of Biochemistry, National University of Singapore, Singapore
- Department of Biological Sciences, National University of Singapore, Singapore
| | - Wei-Yen Lim
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore
| | - Chiea-Chuen Khor
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore
| | - Peter Little
- Life Sciences Institute, National University of Singapore, Singapore
| | - Kee-Seng Chia
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore
| | - Yik-Ying Teo
- 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
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore
- Life Sciences Institute, National University of Singapore, Singapore
- Department of Statistics and Applied Probability, National University of Singapore, Singapore
- * E-mail:
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Liu X, Saw WY, Ali M, Ong RTH, Teo YY. Evaluating the possibility of detecting evidence of positive selection across Asia with sparse genotype data from the HUGO Pan-Asian SNP Consortium. BMC Genomics 2014; 15:332. [PMID: 24885517 PMCID: PMC4035063 DOI: 10.1186/1471-2164-15-332] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2013] [Accepted: 04/25/2014] [Indexed: 11/22/2022] Open
Abstract
Background The HUGO Pan-Asian SNP Consortium (PASNP) has generated a genetic resource of almost 55,000 autosomal single nucleotide polymorphisms (SNPs) across more than 1,800 individuals from 73 urban and indigenous populations in Asia. This has offered valuable insights into the correlation between the genetic ancestry of these populations with major linguistic systems and geography. Here, we attempt to understand whether adaptation to local climate, diet and environment partly explains the genetic variation present in these populations by investigating the genomic signatures of positive selection. Results To evaluate the impact to the selection analyses due to the considerably lower SNP density as compared to other population genetics resources such as the International HapMap Project (HapMap) or the Singapore Genome Variation Project, we evaluated the extent of haplotype phasing switch errors and the consistency of selection signals from three haplotype-based approaches (iHS, XP-EHH, haploPS) when the HapMap data is thinned to a similar density as PASNP. We subsequently applied haploPS to detect and characterize positive selection in the PASNP populations, identifying 59 genomics regions that were selected in at least one PASNP populations. A cluster analysis on the basis of these 59 signals showed that indigenous populations such as the Negrito from Malaysia and Philippines, the China Hmong, and the Taiwan Ami and Atayal shared more of these signals. We also reported evidence of a positive selection signal encompassing the beta globin gene in the Taiwan Ami and Atayal that was distinct from the signal in the HapMap Africans, suggesting the possibility of convergent evolution at this locus due to malarial selection. Conclusions We established that the lower SNP content of the PASNP data conferred weaker ability to detect signatures of positive selection, but the availability of the new approach haploPS retained modest power. Out of all the populations in PASNP, we identified only 59 signals, suggesting a strong need for high-density population-level genotyping data or sequencing data in order to achieve a comprehensive survey of positive selection in Asian populations. Electronic supplementary material The online version of this article (doi:10.1186/1471-2164-15-332) contains supplementary material, which is available to authorized users.
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Affiliation(s)
| | | | | | | | - Yik-Ying Teo
- Saw Swee Hock School of Public Health, National University of Singapore, MD3 16 Medical Drive, Singapore 117597, Singapore.
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Pillai NE, Okada Y, Saw WY, Ong RTH, Wang X, Tantoso E, Xu W, Peterson TA, Bielawny T, Ali M, Tay KY, Poh WT, Tan LWL, Koo SH, Lim WY, Soong R, Wenk M, Raychaudhuri S, Little P, Plummer FA, Lee EJD, Chia KS, Luo M, De Bakker PIW, Teo YY. Predicting HLA alleles from high-resolution SNP data in three Southeast Asian populations. Hum Mol Genet 2014; 23:4443-51. [DOI: 10.1093/hmg/ddu149] [Citation(s) in RCA: 72] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
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