The aim of the Integrated Genomics Core is to provide a comprehensive, cost effective and highly integrated pipeline to analyze and inter-relate the genomic data from all of the projects and accelerate the program. All components of this Program Project rely of genomic analyzes. Project-1 will perform whole exome sequencing (WES) of patient-parent trios to identify putative TED-causing mutations. Project-2 and project-3 will identify the transcriptional targets of HH, BMP, Gli2/3 and Sox2 in animal models and hPSC-derived TE organoids and determine how these pathways interact in a gene regulatory network (GRN). By integrating genomic data from each of these projects with information from diverse functional genomic databases, we will annotate candidate patient variants from project-1, prioritizing those to test in projects-2 and -3. Finally we will model the TEDcausing mutations to determine how they disrupt the GRN governing TE development. Together this will provide a systems level understanding of genotype-phenotype basis of TEDs. Thus, each of the projects, and the effective information flow between them, requires the rigorous computational, statistical and informatics analyses provided by the Integrated Genomics Core. We have assembled a team of genomics and computational specialists from Columbia and CCHMC to create a core with a synergistic suite of expertise not readily available at either institution. This provides cost effective, state-of-the-art, support for the entire program and facilitates synergy between the projects thus enhancing productivity and accelerating the overall goals. The core is jointly directed by Dr. Shen the Associate Director of the Columbia Genome Center, an expert computational genomics methods to study the genetics of human diseases, and Dr. Zorn at CCHMC, the co-Director of Xenbase, the Xenopus model organism database, who is an expert in gene regulatory networks.
The aims of the core are:
Aim 1 Analysis of WES and identification of candidate disease causing variants Aim 2 Analysis of RNA-seq and ChIP-seq data from animal models and human PSC-derived organoids.
Aim 3 Data integrations to 1) elucidate GRN controlling normal and defective TE development and 2) prioritize candidate TED-causing mutations.
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