Search

Hepatocellular carcinoma (HCC) has one of the poorest survival rates among cancers. Using multi-regional sampling of nine resected HCC with different aetiologies, here we construct phylogenetic relationships of these sectors, showing diverse levels of genetic sharing, spanning early to late diversification. Unlike the variegated pattern found in colorectal cancers, a large proportion of HCC display a clear isolation-by-distance pattern where spatially closer sectors are genetically more similar. Two resected intra-hepatic metastases showed genetic divergence occurring before and after primary tumour diversification, respectively. Metastatic tumours had much higher variability than their primary tumours, suggesting that intra-hepatic metastasis is accompanied by rapid diversification at the distant location. The presence of co-existing mutations offers the possibility of drug repositioning for HCC treatment. Taken together, these insights into intra-tumour heterogeneity allow for a comprehensive understanding of the evolutionary trajectories of HCC and suggest novel avenues for personalized therapy., Hepatocellular carcinoma has one of the poorest survival rates amongst cancers. Here, the authors highlight the intra-tumour heterogeneity of this disease, finding that spatially closer tumour sectors are genetically more similar and that intra-hepatic metastasis is accompanied by rapid genetic diversification.

Asian populations are currently underrepresented in human genetics research. Here we present whole-genome sequencing data of 4,810 Singaporeans from three diverse ethnic groups: 2,780 Chinese, 903 Malays, and 1,127 Indians. Despite a medium depth of 13.7×, we achieved essentially perfect (>99.8%) sensitivity and accuracy for detecting common variants and good sensitivity (>89%) for detecting extremely rare variants with 0.01) that were absent in the existing public databases, highlighting the importance of local population reference for genetic diagnosis. We describe fine-scale genetic structure of Singapore populations and their relationship to worldwide populations from the 1000 Genomes Project. In addition to revealing noticeable amounts of admixture among three Singapore populations and a Malay-related novel ancestry component that has not been captured by the 1000 Genomes Project, our analysis also identified some fine-scale features of genetic structure consistent with two waves of prehistoric migration from south China to Southeast Asia. Finally, we demonstrate that our data can substantially improve genotype imputation not only for Singapore populations, but also for populations across Asia and Oceania. These results highlight the genetic diversity in Singapore and the potential impacts of our data as a resource to empower human genetics discovery in a broad geographic region.

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).