Project Summary Genetic variants explain and offer insights into the development of various complex diseases. Genome-wide association studies (GWAS) enabled the discovery of tens of thousands of loci associated with human traits, but work remains to decipher underlying biological mechanisms affected by variants in these loci. The long-term goal of the Project Leader’s research is to identify disease-causal genetic variants and to understand their mechanistic contribution to pathogenesis. In line with this goal, this project will leverage multi-omics data, particularly single-cell multi-omics data, to understand the functional impact of genetic variants and use this information to identify disease-causal variants. The Center of Quantitative Biology will advance the Project Leader's independent career by providing critical resources and expertise. This includes mentoring by senior faculty to provide guidance on grant applications, lab management, and identifying key resources. Research projects in the Project Leader's lab rely heavily on collaboration with the Single-Cell Genomics Core and the Genomic Data Science Core to conduct sequencing and data analysis. The proposed Research Project will explore a new framework to study the functional effect of genetic variants using a small cohort of organoids and use this information to identify causal variants for colon-related diseases. Aim 1 will focus on setting up a genomic data collection and analysis framework to identify cell-type- and treatment condition-specific genetic effect variants with potential regulatory roles. We plan to collect single-cell multi-omics data from a cohort of colon organoids, which contain multiple cell types present in colon tissue. We also plan to collect epigenetic information of the organoids with and without stimulating treatment. We plan to identify variants with functional effects using such data and expand the list of functional variants by developing new computational methods. In Aim 2, we will identify causal variants and genes for colon-related diseases by leveraging functional genomics. We plan to evaluate the relevance of different cell types for colon diseases by estimating the heritability enrichment in functional genetic variants identified in different cell types and treatment conditions. Next, they plan to use functional annotations generated from Aim1 to identify causal genetic variants in GWAS for inflammatory bowel disease and colorectal cancer. To validate regulatory effects of variants, the team plans to use Perturb-seq, which targets candidate variants by CRISPRi in conjunction with single-cell RNA sequencing to get cell-level readout of effect. This study framework will be a fundamental step used by the research team to achieve long- term goals of understanding the role of common genetic variants in leading to human diseases. In the future, we plan to collaborate with labs in different disease domains to generate and analyze data using this framework...