SUMMARY Identifying functional sequence variants and effector genes for disease-associated functional variants, understanding how the variants influence effector genes and disease, and utilizing this information to advance precision medicine are among the most important yet formidable challenges in current genetic research of common diseases. Sequence variants identified by genome-wide association studies (GWAS) can have substantial effects on gene expression, and identification of GWAS effector genes and the mechanisms involved has important clinical and scientific implications. Chronic kidney disease occurs in more than 10% of the general population. GWAS in up to 1 million people have identified more than 200 genomic loci associated with renal function, chronic kidney disease, or urinary albumin-to-creatinine ratio. Haplotypes in linkage disequilibrium (LD) at these loci contain more than 7,000 unique single nucleotide polymorphisms (SNPs). Very few studies have gone beyond associations to ascertain the effect of kidney-associated SNPs on gene expression or investigate the mechanisms involved. Such studies would have to overcome substantial challenges including the tissue-specific nature of the effect of regulatory SNPs on gene expression. Many LD regions are thousands of base pairs long and may contain dozens of SNPs. These long LD regions are particularly difficult to study. We have developed a unique approach and innovative methods for definitively and mechanistically linking haplotype variants, including long haplotypes, to genes in specific disease-relevant cell types. In RIGERR (Resources for Investigating Genetic and Epigenetic Regulation of Renal Disease), we propose to use this suite of sophisticated technologies to generate a large collection of innovative tools and resources to transform genetic and epigenetic research of kidney disease broadly. Aim 1 of RIGERR is to generate more than 100 lines of human induced pluripotent stem cells genetically engineered to contain readily editable or precisely reconstituted haplotypes or high-penetrance variants associated with kidney function or disease. These edited cell lines will be provided to the research community for a wide range of molecular, functional, or drug testing studies for kidney disease. In Aim 2, we will produce novel datasets and establish a workflow for utilizing these unprecedented resources to conduct mechanistic and in vivo studies of kidney function and disease, using albuminuria as an example. We have obtained exciting preliminary data that strongly support the conceptual and technical feasibility of RIGERR.