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Underrepresentation of Asian genomes has hindered population and medical genetics research on Asians, leading to population disparities in precision medicine. By whole-genome sequencing of 4,810 Singapore Chinese, Malays, and Indians, we found 98.3 million SNPs and small insertions or deletions, over half of which are novel. Population structure analysis demonstrated great representation of Asian genetic diversity by three ethnicities in Singapore and revealed a Malay-related novel ancestry component. Furthermore, demographic inference suggested that Malays split from Chinese ∼24,800 years ago and experienced significant admixture with East Asians ∼1,700 years ago, coinciding with the Austronesian expansion. Additionally, we identified 20 candidate loci for natural selection, 14 of which harbored robust associations with complex traits and diseases. Finally, we show that our data can substantially improve genotype imputation in diverse Asian and Oceanian populations. These results highlight the value of our data as a resource to empower human genetics discovery across broad geographic regions. Agency for Science, Technology and Research (A*STAR) National Medical Research Council (NMRC) National Research Foundation (NRF) Accepted version We acknowledge H.M. Kang, S. Das, A. Tan, F. Zhang, J. Terhorst, P.-R. Loh, and G. Hellenthal for helpful discussions and support from all participants and clinical research coordinators of the contributing cohorts and studies: the TTSH Healthy Control Workgroup, the SEED cohort, the Asian Sudden Cardiac Death in Heart Failure Study, the Singapore Heart Failure Outcomes and Phenotypes (SHOP) cohort, the Asian neTwork for Translational Research and Cardiovascular Trials (ATTRaCT), the Parkinson’s Disease Study, the Peranakan Genome Study, the Platinum Asian Genomes Project, the Bariatric Surgery Study, the National Heart Centre Singapore Biobank and SingHEART cohorts, and the GUSTO and S-PRESTO study groups. This study was supported by Singapore’s A*STAR (core funding and IAF-PP H17/01/a0/007), BMRC (SPF2014/001, SPF2013/002, SPF2014/003, SPF2014/004, and SPF2014/005), NMRC (CIRG/1371/2013, CIRG/1417/2015, CIRG/1488/ 2018, CSA-SI/0012/2017, CG/017/2013, CG/M006/2017_NHCS, TCR/013- NNI/2014, STaR/0011/2012, STaR2013/001, STaR/014/2013, STaR/0026/ 2015, TCR/006-NUHS/2013, TCR/012-NUHS/2014, TCR/004-NUS/2008, TCR/012-NUHS/2014, and center grants 2010-13 and 2013-2017), NRF (NRFF2016-03), National University of Singapore, SingHealth and DukeNUS, and Alexandra Health small innovative grant SIGII/15203 and funding from Huazhong University of Science and Technology, the Tanoto Foundation, the Lee Foundation, the Boston Scientific Investigator Sponsored Research Program and Bayer, the NSF (DEB-1753489), and the Alfred P. Sloan Foundation. The computation was partially performed on resources of the National Supercomputing Centre, Singapore (https://www.nscc.sg).

Background Genetic determinants of drug response remain stable throughout life and offer great promise to patient-tailored drug therapy. The adoption of pharmacogenetic (PGx) testing in patient care requires accurate, cost effective and rapid genotyping with clear guidance on the use of the results. Hence, we evaluated a 32 SNPs panel for implementing PGx testing in clinical laboratories. Methods We designed a 32-SNP panel for PGx testing in clinical laboratories. The variants were selected using the clinical annotations of the Pharmacogenomics Knowledgebase (PharmGKB) and include polymorphisms of CYP2C9, CYP2C19, CYP2D6, CYP3A5 and VKORC1 genes. The CYP2D6 gene allele quantification was determined simultaneously with TaqMan copy number assays targeting intron 2 and exon 9 regions. The genotyping results showed high call rate accuracy according to concordance with genotypes identified by independent analyses on Sequenome massarray and droplet digital PCR. Furthermore, 506 genomic samples across three major ethnic groups of Singapore (Malay, Indian and Chinese) were analysed on our workflow. Results We found that 98% of our study subjects carry one or more CPIC actionable variants. The major alleles detected include CYP2C9*3, CYP2C19*2, CYP2D6*10, CYP2D6*36, CYP2D6*41, CYP3A5*3 and VKORC1*2. These translate into a high percentage of intermediate (IM) and poor metabolizer (PM) phenotypes for these genes in our population. Conclusion Genotyping may be useful to identify patients who are prone to drug toxicity with standard doses of drug therapy in our population. The simplicity and robustness of this PGx panel is highly suitable for use in a clinical laboratory.

Introduction While overexpression of syndecan-1 has been associated with aggressive breast cancer in the Caucasian population, the expression pattern of syndecan-1 in Asian women remains unclear. Triple-positive breast carcinoma, in particular, is a unique subtype that has not been extensively studied. We aimed to evaluate the role of syndecan-1 as a potential biomarker and prognostic factor for triple-positive breast carcinoma in Asian women. Methods Using immunohistochemistry, staining scores of 61 triple‑positive breast carcinoma specimens were correlated with patients' clinicopathological variables such as age, ethnicity, tumour size, histological grade, lymph node status, lymphovascular invasion, associated ductal carcinoma in situ grade, recurrence and overall survival. Results Syndecan-1 had intense staining scores in triple‑positive invasive ductal breast carcinomas when compared to normal breast tissue. On multivariate analysis, syndecan-1 epithelial total percentage and immunoreactivity score showed statistical correlation with survival (p = 0.02). Conclusion The intense staining scores of syndecan-1 and their correlation with overall survival in patients with triple-positive breast carcinoma suggest that syndecan-1 may have a role as a biological and prognostic marker in patients with this specific subtype of breast cancer.