bioRxivMolecular BiologyPreprint
Epigenetic Profiling of Human Insulinomas Reveals AP-1 Family as Critical Regulators of Beta Cell Maturation
Xuedi WangiD, Saul CarcamoiD, Luca LambertiniiD, Peng WangiD, Hongtao Liu, John David PaulseniD, Rachel BrodyiD, Gustavo Gabriel Fernandez-RanvieriD, Dan HassoniD, Andrew F. StewartiD, Esra KaraköseiD
Abstract
Insulinomas are rare and benign human pancreatic adenomas that overproduce insulin and display increased beta cell mass. We and others have shown that transcriptomic and genomic profiling on insulinomas provides a data mine for identifying targets that can be manipulated to induce human beta cell regeneration. Majority of causative genetic variants in insulinomas involve epigenetic regulatory genes. Yet, specifically how these variants lead to human beta cell expansion and increased function is largely unknown. Here, we performed bulk and single-nucleus epigenomic and transcriptomic profiling to define regulatory alterations in human insulinomas. Bulk ATAC-seq and H3K27Ac ChIP-seq revealed significant enrichment of AP-1 transcription factor binding motifs within beta cell-associated open chromatin/enhancer regions in normal islets, accompanied by robust expression of AP-1 family members; in contrast, insulinomas exhibited marked reductions in both AP-1 motif enrichment and AP-1 expression. Our snRNA-seq and snATAC-seq profiling across four independent insulinomas identified a consistent and previously unrecognized signature defined by suppression of AP-1 transcription factors and widespread loss of chromatin accessibility at AP-1 binding sites, particularly at enhancers governing beta cell identity. Collectively, these results establish AP-1-mediated regulatory programs as critical determinants of beta cell maturation and define their disruption as a signature among human insulinomas.
- organism: human
- assay: bulk RNA-seq
- assay: ATAC-seq
- assay: scRNA-seq
- assay: scATAC-seq
- research focus: differential expression
- research focus: gene regulatory network inference
- research focus: database / resource
- approach: statistical model
- approach: experimental assay
- Citations
- 0
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