Project description:This clinical trial studies the effectiveness of a web-based cancer education tool called Helping Oncology Patients Explore Genomics (HOPE-Genomics) in improving patient knowledge of personal genomic testing results and cancer and genomics in general. HOPE-Genomics is a web-based education tool that teaches cancer/leukemia patients, and patients who may be at high-risk for developing cancer, about genomic testing and provide patients with information about their own genomic test results. The HOPE-Genomics tool may improve patient’s genomic knowledge and quality of patient-centered care. In addition, it may also improve education and care quality for future patients.
Project description:An overall goal of functional genomics has been to measure the impact of variants on molecular endophenotypes (e.g. gene expression levels or the degree of TF binding) and relate this to organismal traits and disease phenotypes. However, all the experiments to date have been described relative to a generic reference genome, significantly hobbling their interpretation. Here, we describe a strategy for finding significant relationships between disease variation and genomic annotation via personal functional genomics, by performing personal genome sequencing and paired functional genomics experiments, on the same individual.
Project description:Migration is essential for the reproduction and survival of many animals, yet little is understood about its underlying molecular mechanisms. We used the salmonid Oncorhynchus mykiss to gain mechanistic insight into smoltification, which is a morphological, physiological, and behavioral transition undertaken by some juveniles that culminates in a seaward migration. This species is experimentally tractable and, unlike common model species, displays intra- and inter-population variation in migration propensity. Migratory individuals can produce non-migratory progeny and vice versa, indicating a high degree of phenotypic plasticity. One potential way that phenotypic plasticity might be linked to variation in migration-related life history tactics is through epigenetic regulation of gene expression. To explore this, we quantitatively measured genome-scale DNA methylation in fin tissue using reduced representation bisulfite sequencing of F2 siblings produced from a cross between steelhead (migratory) and rainbow trout (non-migratory) lines. We identified 57 differentially methylated regions (DMRs) between smolt and resident O. mykiss juveniles. DMRs were of high magnitude, ranging from 20-62% differential methylation between life history types, and over half of the gene-associated DMRs were in transcriptional regulatory regions. Many of the DMRs encode proteins with activity relevant to migration-related transitions (e.g. circadian rhythm pathway, nervous system development, protein kinase activity). This study provides the first evidence of a relationship between epigenetic variation and life history divergence associated with a migration-related transition in any species. Comparing global DNA methyldation profiles (via RRBS) of resident and smolt O. mykiss siblings using caudal fin tissue.
Project description:Genomic sequencing of many thousands of tumors has revealed many genes associated with specific types of cancer. Similarly, large scale CRISPR functional genomics efforts have mapped genes required for proliferation or survival in hundreds of cancer cell lines. Despite this, for specific disease subtypes, such as metastatic prostate cancer, it is likely that there exist many undiscovered tumor specific genetic dependencies, such as prostate cancer specific drivers, that represent drug targets. To identify such genetic dependencies, we performed genome-scale CRISPRi screens in metastatic prostate cancer models. We then created a pipeline in which we integrated publicly available pan-cancer functional genomics data with our metastatic prostate cancer functional and clinical genomics data to identify genes that can drive aggressive prostate cancer phenotypes. Our integrative analysis of these data revealed two known prostate cancer specific driver genes, AR and HOXB13, as the top two hits and also nominated a number of unexpected genes. In this study we highlight the strength of an integrated clinical and functional genomics pipeline and focus on two hit genes, KIF4A and WDR62. We demonstrate that both KIF4A and WDR62 drive aggressive prostate cancer phenotypes in vitro and in vivo in multiple models, irrespective of AR-status, and are also associated with poor patient outcome.