# Discovery of diabetes-relevant β cell enhancers through 4D enhancer mapping, integrative analysis, and large-scale CRISPRi perturbation screens > **NIH NIH U01** · SLOAN-KETTERING INST CAN RESEARCH · 2020 · $717,356 ## Abstract ABSTRACT Enhancers are essential regulatory elements that together with transcription factors (TFs) instruct cell- type specific transcriptional programs during development, tissue homeostasis and regeneration. Initiatives such as the ENCODE project, revealed tens of thousands putative enhancers based on linear proximity, using criteria like chromatin accessibility, TF binding, and histone modifications such as H3K27ac. However, a main challenge of uncovering functional enhancers and assigning them to target genes lies in the complexity of the 3D chromatin organization, which can influence enhancer specificity and activity. Using an advanced chromosome conformation capture assay, we recently captured the dynamic rewiring of 3D enhancer networks during mouse somatic cell reprogramming and discovered multi-connected enhancers that we named “3D enhancer hubs”. Here we extend the 3D mapping approach to human primary islets, and compare islets from healthy and type 2 diabetes (T2D) donors to assemble a 4D atlas to capture the rewiring of 3D enhancer network in disease progression. At the same time, we plan to compare the enhancer network in adult islets to earlier stages of development by using human pluripotent stem cells (hPSCs) to generate early β cells and their developmental precursors. Utilizing these 4D genomic data, we will computationally nominate core β-cell specific enhancers relevant to β cell development, function, and T2D, and then interrogate these putative enhancers through large-scale CRISPRi mediated perturbation screens using hPSC-β cells. Enhancers identified from the screening effort will be further validated in an established human β cell line and primary human islet β cells. This proposal addresses a critical gap in the 4DN initiative, that is how to translate 3D genomics data into functional data with respect to gene expression in the context of human health. Successful completion of our aims will establish a paradigm for the discovery and interrogation of functional enhancers that instruct transcriptional programs specific to a cell type of interest, reveal unique insights into their mechanisms of action, and identify enhancers with relevance to human development and disease. For instance, uncovering functional enhancers could assist the identification of noncoding causal variants identified in genome-wide association studies. ## Key facts - **NIH application ID:** 10117708 - **Project number:** 1U01DK128852-01 - **Recipient organization:** SLOAN-KETTERING INST CAN RESEARCH - **Principal Investigator:** Effie Apostolou - **Activity code:** U01 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2020 - **Award amount:** $717,356 - **Award type:** 1 - **Project period:** 2020-09-15 → 2025-06-30 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10117708 ## Citation > US National Institutes of Health, RePORTER application 10117708, Discovery of diabetes-relevant β cell enhancers through 4D enhancer mapping, integrative analysis, and large-scale CRISPRi perturbation screens (1U01DK128852-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10117708. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*