Research Project
10296063
PROJECT SUMMARY This project aims to assemble a foundational resource of functional DNA elements, transcription factor (TF) binding sites and gene regulatory interactions for the Impact of Genomic Variation on Function (IGVF) consortium. The resource will facilitate interpretation of noncoding genetic variation associated with human traits and diseases, advance understanding of disease mechanisms and hasten progress towards genomic medicine. A large majority of genetic variants associated with human diseases are non-coding, which has hindered their interpretation and utility for understanding disease. Non-coding disease variants are enriched within promoters, enhancers and TF binding sites. Hence, a compelling hypothesis is that they modulate the activity of functional elements, TF interactions and gene targets in specific cellular contexts. To interpret the function of a variant, investigators must determine the element and/or TF that they impact, which gene is affected, and the cell state in which the effect is manifested. This process is greatly facilitated by genome-wide maps of functional elements, TFs and regulatory interactions. However, existing resources under-represent disease-relevant functional elements that are specific to early developmental stages, rare cell states, physiological responses, genotypes or disease states. To overcome these limitations, the proposed project will deploy an innovative suite of single-cell assays to profile RNA transcripts, chromatin accessibility, TF footprints and histone modifications at unprecedented scale. These assays will be applied to an expansive collection of phenotypically- and genotypically-diverse BioSamples selected for their relevance to cardiovascular, metabolic, autoimmune, neuropsychiatric and neurodegenerative diseases. We will acquire >16 million single-cell profiles for thousands of BioSamples that span cadaveric tissues, surgical specimens, peripheral blood mononuclear cell (PBMC) cohorts, brain organoids and other innovative experimental models. Integration of this vast dataset will enable us to (1) annotate millions of regulatory elements and TF motifs; (2) predict gene targets from co-variation of element accessibility and gene expression across single cells; and (3) identify quantitative trait loci for gene expression (eQTLs) and chromatin accessibility (caQTLs) from the diverse genotypes represented in our cohorts. The project will bring together a diverse team of experts in human genetics, disease biology, genomics and production research. The team will coordinate closely with IGVF colleagues and the DACC in the design, assembly and integration of this resource. All data will be made freely available and maximally accessible to the scientific community, with the goal to catalyze human genetics, disease biology and genomic medicine.
