Introduction and Objective: The dysfunction of beta cells in pancreatic islets is a driving force of Type 2 diabetes (T2D) pathogenesis. Genome-wide association studies (GWAS) have revealed that numerous T2D-associated SNPs (genetic variants) located in non-coding regions, suggesting a crucial role for distal cis-elements in regulating gene expression. However, a major challenge remains in defining the specific tissues and cell types through which these diabetes-associated variants exert their effects. Methods: In this study, we performed epigenomic profiling of the enhancer mark H3K4me1 in human islet cells isolated from healthy and T2D subjects using Paired-Tag, a multiomic approach which profiles the chromatin modification and RNA from same single cells. Results: We defined cell type-specific histone modification landscapes in human pancreatic islets, revealing distinct active enhancer states and transcription factor motifs across islet cell types. We integrated genome-wide association study (GWAS) data with Paired-Tag epigenomic profiles to identify type 2 diabetes-associated SNPs residing in enhancers and assess their functional relevance. To further identify the putative function variants, we applied machine learning to predict and interpret functional noncoding variants associated with type 2 diabetes, revealing islet cell type-specific effects on chromatin accessibility. We identified a small cohort of T2D-associated H3K4me1+ enhancer SNPs which potentially determine transcription factor binding and regulate gene expression. Taken together, this work evaluates the putative mechanism of T2D-associated SNPs in modulating activity of pancreatic enhancers at single cell level. Conclusion: Our results highlighted the functional importance of T2D variants in regulating enhancer activity measured by H3K4me1, which may yield novel insights into the pathogenesis of T2D. Disclosure L. Wang: None. Z. Wei: None.
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