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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 \u201c3D enhancer hubs\u201d. 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 \u03b2 cells and their developmental precursors. Utilizing these 4D genomic data, we will computationally nominate core \u03b2-cell specific enhancers relevant to \u03b2 cell development, function, and T2D, and then interrogate these putative enhancers through large-scale CRISPRi mediated perturbation screens using hPSC-\u03b2 cells. Enhancers identified from the screening effort will be further validated in an established human \u03b2 cell line and primary human islet \u03b2 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. 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Our gene regulatory network modeling identified that nonlinear  enhancer gene regulation during cell state transitions can be leveraged to  improve the sensitivity of enhancer discovery. Using human embryonic stem cell  definitive endoderm differentiation as a dynamic transition system, we conducted  a mid-transition CRISPRi-based enhancer screen. We discovered a comprehensive set  of enhancers for each of the core endoderm-specifying transcription factors. Many  enhancers had strong effects mid-transition but weak effects post-transition,  consistent with the nonlinear temporal responses to enhancer perturbation  predicted by the modeling. Integrating three-dimensional genomic information, we  were able to develop a CTCF-loop-constrained Interaction Activity model that can  better predict functional enhancers compared to models that rely on Hi-C-based  enhancer-promoter contact frequency. 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