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Genetic factors underlying leukocyte telomere length (LTL) may provide insights into telomere homeostasis, with direct links to disease susceptibility. Genetic evaluation of 23,096 Singaporean Chinese samples identifies 10 genome-wide loci ( P  < 5 × 10 −8 ). Several of these contain candidate genes ( TINF2 , PARP1 , TERF1 , ATM and POT1 ) with potential roles in telomere biology and DNA repair mechanisms. Meta-analyses with additional 37,505 European individuals reveals six more genome-wide loci, including associations at MPHOSPH6 , NKX2-3 and TYMS . We demonstrate that longer LTL associates with protection against respiratory disease mortality [HR = 0.854(0.804–0.906), P  = 1.88 × 10 −7 ] in the Singaporean Chinese samples. We further show that the LTL reducing SNP rs7253490 associates with respiratory infections ( P  = 7.44 × 10 −4 ) although this effect may not be strongly mediated through LTL. Our data expands on the genetic basis of LTL and may indicate on a potential role of LTL in immune competence. Shortening of leukocyte telomere length (LTL) is associated with age and increased risk for various chronic diseases. Here, the authors report genome-wide association studies for LTL in Singaporean Chinese populations and find that longer LTL associates with less severe outcomes of respiratory disease phenotypes.

The role of low frequency variants associated with telomere length homeostasis in chronic diseases and mortalities is relatively understudied in the East-Asian population. Here we evaluated low frequency variants, including 1,915,154 Asian specific variants, for leukocyte telomere length (LTL) associations among 25,533 Singapore Chinese samples. Three East Asian specific variants in/near POT1, TERF1 and STN1 genes are associated with LTL (Meta-analysis P 2.49×10−14–6.94×10−10). Rs79314063, a missense variant (p.Asp410His) at POT1, shows effect 5.3 fold higher and independent of a previous common index SNP. TERF1 (rs79617270) and STN1 (rs139620151) are linked to LTL-associated common index SNPs at these loci. Rs79617270 is associated with cancer mortality [HR95%CI = 1.544 (1.173, 2.032), PAdj = 0.018] and 4.76% of the association between the rs79617270 and colon cancer is mediated through LTL. Overall, genetically determined LTL is particularly associated with lung adenocarcinoma [HR95%CI = 1.123 (1.051, 1.201), Padj = 0.007]. Ethnicity-specific low frequency variants may affect LTL homeostasis and associate with certain cancers.Xuling Chang et al. study whether low frequency variants are associated with leukocyte telomere length and whether these variants predispose to incident cancers and mortalities among East Asians. They find that three East Asian specific variants at POT1, TERF1 and STN1 loci are associated with leukocyte telomere length and report a mechanistic pathway linking TERF1, leukocyte telomere length and incident colon cancer.

Genomic researchers are increasingly utilizing commercial cloud platforms (CCPs) to manage their data and analytics needs. Commercial clouds allow researchers to grow their storage and analytics capacity on demand, keeping pace with expanding project data footprints and enabling researchers to avoid large capital expenditures while paying only for IT capacity consumed by their project. Cloud computing also allows researchers to overcome common network and storage bottlenecks encountered when combining or re-analysing large datasets. However, cloud computing presents a new set of challenges. Without adequate security controls, the risk of unauthorised access may be higher for data stored on the cloud. In addition, regulators are increasingly mandating data access patterns and specific security protocols on the storage and use of genomic data to safeguard rights of the study participants. While CCPs provide tools for security and regulatory compliance, utilising these tools to build the necessary controls required for cloud solutions is not trivial as such skill sets are not commonly found in a genomics lab. The Research Assets Provisioning and Tracking Online Repository (RAPTOR) by the Genome Institute of Singapore is a cloud native genomics data repository and analytics platform focusing on security and regulatory compliance. Using a 'five-safes' framework (Safe Purpose, Safe People, Safe Settings, Safe Data and Safe Output), RAPTOR provides security and governance controls to data contributors and users leveraging cloud computing for sharing and analysis of large genomic datasets without the risk of security breaches or running afoul of regulations. RAPTOR can also enable data federation with other genomic data repositories using GA4GH community-defined standards, allowing researchers to boost the statistical power of their work and overcome geographic and ancestry limitations of data setsCompeting Interest StatementThe authors have declared no competing interest.Footnotes* Typo for an author's name: Ching-Yu Chen -> Ching-Yu Cheng

Precision medicine (PM) research in recent years has witnessed a remarkable surge in large-scale population genomics programs. In 2017, Singapore initiated the National Precision Medicine (NPM) program, a three-phase national strategy driving PM research, innovation, and enterprise capitalizing on Singapore’s unique multi-ancestral Asian population. Coordinated by Precision Health Research, Singapore (PRECISE), NPM Phase I assembled an Asian reference genome of 10,000 individuals completed using highly manual and laborious laboratory sample workflows. NPM Phase II, targeting a 100,000 population cohort (PRECISE-SG100K), required the transformation of the genome sequencing workflow to a production-scale operation leveraging high-throughput automation and robotics. Here we share detailed technical blueprints for implementing and maintaining Singapore’s PRECISE-SG100K Genomic Engine, learning from and overcoming Phase I’s pain-points and bottlenecks. The Genomic Engine allowed the successful scale up of genomic sequencing and throughput, enabling the anticipated completion of sequencing of 100,000 whole genomes in three years.