Biology subjects

Friedlander, Y.

Publications and source records attributed to Friedlander, Y..

3 recordsLinked to original sources

bioRxiv2024

Time is encoded by methylation changes at clustered CpG sites

Age-dependent changes in DNA methylation allow chronological and biological age inference, but the underlying mechanisms remain unclear. Using ultra-deep sequencing of >300 blood samples from healthy individuals, we show that age-dependent DNA methylation changes are regional and occur at multiple adjacent CpG sites, either stochastically or in a coordinated block-like manner. Deep learning analysis of single-molecule patterns in two genomic loci achieved accurate age prediction with a median error of 1.46-1.7 years on held-out human blood samples, dramatically improving current epigenetic clocks. Factors such as gender, BMI, smoking and other measures of biological aging do not affect chronological age inference. Longitudinal 10-year samples revealed that early deviations from epigenetic age are maintained throughout life and subsequent changes faithfully record time. Lastly, the model inferred chronological age from as few as 50 DNA molecules, suggesting that age is encoded by individual cells. Overall, DNA methylation changes in clustered CpG sites illuminate the principles of time measurement by cells and tissues, and facilitate medical and forensic applications. O_FIG O_LINKSMALLFIG WIDTH=174 HEIGHT=200 SRC="FIGDIR/small/626674v1_ufig1.gif" ALT="Figure 1"> View larger version (46K): org.highwire.dtl.DTLVardef@c4dd52org.highwire.dtl.DTLVardef@9e6e62org.highwire.dtl.DTLVardef@160f8c3org.highwire.dtl.DTLVardef@16be7a3_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

bioRxiv2022

RAPTOR: A Five-Safes approach to a secure, cloud native and serverless genomics data repository

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 sets

genomics↗

bioRxiv2017

A study of Kibbutzim in Israel reveals risk factors for cardiometabolictraits and subtle population structure

Genetic studies in isolated populations have provided increased power for identifying loci associated with complex diseases and traits. We present here the Kibbutzim Family Study (KFS), initiated for investigating environmental and genetic determinants of cardiometabolic traits in extended Israeli families living in communes characterized by long-term social stability and homogeneous environment. Extensive information on cardiometabolic traits, as well as genome-wide genetic data, was collected on 901 individuals, making this study, to the best of our knowledge, the largest of its kind in Israel. We have thoroughly characterized the KFS genetic structure, observing that most participants were of Ashkenazi Jewish (AJ) origin, and confirming a recent severe bottleneck in their recent history (point estimates: effective size {approx}450 individuals, 23 generations ago). Focusing on genetic variants enriched in KFS compared with non-Finnish Europeans, we demonstrated that AJ-specific variants are largely involved in cancer-related pathways. Using linear mixed models, we conducted an association study of these enriched variants with 16 cardiometabolic traits. We found 24 variants to be significantly associated with cardiometabolic traits. The strongest association, which we also replicated, was between a variant upstream of the MSRA gene, {approx}200-fold enriched in KFS, and weight (P=3.6{middle dot}10-8). In summary, the KFS is a valuable resource for the study of the population genetics of Israel as well as the genetics of cardiometabolic traits in a homogeneous environment.

genetics↗