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Due to an advanced understanding of cancer biology and the rapid development of genomic technologies, cancer has shifted from 200 diseases based on pathology (i.e., what a tumor looks like under the microscope) to thousands of diseases based on molecular tumor profiles (i.e., what a tumor looks like when its altered genome is interrogated). Most cancers arise from alterations to the genome, including changes in the number or structure of chromosomes and variations in a single building block of the genetic code.
Type-2 diabetes is a systemic condition with rising global prevalence, disproportionately affecting Indigenous communities worldwide. Recent advances in epigenomics methods, particularly in DNA methylation detection, have enabled the discovery of associations between epigenetic changes and Type-2 diabetes. In this review, we summarise DNA methylation profiling methods, and discuss how these technologies can facilitate the discovery of epigenomic biomarkers for Type-2 diabetes.
Whole genome sequencing offers significant potential to improve the diagnosis and treatment of rare diseases by enabling the identification of thousands of rare, potentially pathogenic variants. Existing variant prioritisation tools can be complemented by approaches that incorporate phenotype specificity and provide contextual biological information, such as tissue or cell-type specificity.
Timo Lassmann BSc (Hons) MSc PhD Feilman Fellow; Head, Precision Health Research and Head, Translational Intelligence timo.lassmann@thekids.org.au
Genomic sequencing in congenital heart disease (CHD) patients often discovers novel genetic variants, which are classified as variants of uncertain significance (VUS). Functional analysis of each VUS is required in specialised laboratories, to determine whether the VUS is disease causative or not, leading to lengthy diagnostic delays.
Genomic information is increasingly used to inform medical treatments and manage future disease risks. However, any personal and societal gains must be carefully balanced against the risk to individuals contributing their genomic data. Expanding our understanding of actionable genomic insights requires researchers to access large global datasets to capture the complexity of genomic contribution to diseases.
The specific role of chromatin modifying factors in the timely execution of transcriptional changes in gene expression to regulate organ size remains largely unknown. Here, we report that in Drosophila melanogaster depletion of the histone demethylase dLsd1 results in the reduction of wing size. dLsd1 depletion affects cell proliferation and causes an increase in DNA damage and cell death.
Current differentiation protocols have not been successful in reproducibly generating fully functional human beta cells in vitro, partly due to incomplete understanding of human pancreas development. Here, we present detailed transcriptomic analysis of the various cell types of the developing human pancreas, including their spatial gene patterns. We integrated single-cell RNA sequencing with spatial transcriptomics at multiple developmental time points and revealed distinct temporal-spatial gene cascades.
To define clinical common data elements (CDEs) and a mandatory minimum data set (MDS) for genomic studies of cerebral palsy (CP). Method: Candidate data elements were collated following a review of the literature and existing CDEs.
The goal of this study was to understand individuals with cerebral palsy (CP) and their family's attitudes and preferences to genomic research, including international data sharing and biobanking.