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Nat Commun. 2017 Sep 21;8(1):653. doi: 10.1038/s41467-017-00413-x.

Establishing multiple omics baselines for three Southeast Asian populations in the Singapore Integrative Omics Study.

Author information

1
Saw Swee Hock School of Public Health, National University of Singapore, 12 Science Drive, Singapore, 117549, Singapore.
2
Life Sciences Institute, National University of Singapore, 28 Medical Drive, Singapore, 117456, Singapore.
3
Baker IDI Heart and Diabetes Institute, 75 Commercial Road, Melbourne, VIC, 3004, Australia.
4
MiRXES, Agency for Science, Technology and Research Singapore, 10 Biopolis Road, Chromos, Singapore, 138670, Singapore.
5
Translational Laboratory in Genetic Medicine, Agency for Science, Technology and Research Singapore, 8A Biomedical Grove, Immunos, Singapore, 138648, Singapore.
6
Department of Medical Microbiology, University of Manitoba, 730 William Avenue, Winnipeg, MB, Canada, R3E 0Z2.
7
National Microbiology Laboratory, 1015 Arlington St, Winnipeg, MB, Canada, R3E.
8
Department of Biochemistry and Molecular Biology, The University of Melbourne, Bio21, 30 Flemington Road, Melbourne, VIC, 3010, Australia.
9
Genome Institute of Singapore, Agency for Science, Technology and Research Singapore, 60 Biopolis St, Singapore, 138672, Singapore.
10
Singapore Eye Research Institute, 20 College Road, Singapore, 169856, Singapore.
11
Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, 8 Medical Drive, Singapore, 117597, Singapore.
12
Molecular Engineering of Biological and Chemical System/Chemical Pharmaceutical Engineering, Singapore-Massachusetts Institute of Technology Alliance, 4 Engineering Drive 3, Singapore, 117576, Singapore.
13
Bioprocessing Technology Institute, A*STAR (Agency for Science, Technology and Research, Singapore), 20 Biopolis Way, Singapore, 138668, Singapore.
14
Cancer Science Institute of Singapore, National University of Singapore, 14 Medical Drive, Singapore, 117599, Singapore.
15
NUS Graduate School for Integrative Science and Engineering, National University of Singapore, 28 Medical Drive, Singapore, 117456, Singapore.
16
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.
17
Department of Biological Sciences, National University of Singapore, 16 Science Drive 4, Singapore, 117543, Singapore.
18
Saw Swee Hock School of Public Health, National University of Singapore, 12 Science Drive, Singapore, 117549, Singapore. statyy@nus.edu.sg.
19
Life Sciences Institute, National University of Singapore, 28 Medical Drive, Singapore, 117456, Singapore. statyy@nus.edu.sg.
20
Genome Institute of Singapore, Agency for Science, Technology and Research Singapore, 60 Biopolis St, Singapore, 138672, Singapore. statyy@nus.edu.sg.
21
NUS Graduate School for Integrative Science and Engineering, National University of Singapore, 28 Medical Drive, Singapore, 117456, Singapore. statyy@nus.edu.sg.
22
Department of Statistics and Applied Probability, National University of Singapore, 6 Science Drive 2, Singapore, 117546, Singapore. statyy@nus.edu.sg.

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.

PMID:
28935855
PMCID:
PMC5608948
DOI:
10.1038/s41467-017-00413-x
[Indexed for MEDLINE]
Free PMC Article

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