Genome-wide association studies (GWAS) have identified >100 independent SNPs that modulate the risk of type 2 diabetes (T2D) and related traits. However, the pathogenic mechanisms of most of these SNPs remain elusive. Here, we examined genomic, epigenomic, and transcriptomic profiles in human pancreatic islets to understand the links between genetic variation, chromatin landscape, and gene expression in the context of T2D. We first integrated genome and transcriptome variation across 112 islet samples to produce dense cis-expression quantitative trait loci (cis-eQTL) maps. Additional integration with chromatin-state maps for islets and other diverse tissue types revealed that cis-eQTLs for islet-specific genes are specifically and significantly enriched in islet stretch enhancers. High-resolution chromatin accessibility profiling using assay for transposase-accessible chromatin sequencing (ATACseq) in two islet samples enabled us to identify specific transcription factor (TF) footprints embedded in active regulatory elements, which are highly enriched for islet cis-eQTL. Aggregate allelic bias signatures in TF footprints enabled us de novo to reconstruct TF binding affinities genetically, which support the high-quality nature of the TF footprint predictions. Interestingly, we found that T2D GWAS loci were strikingly and specifically enriched in islet Regulatory Factor X (RFX) footprints. Remarkably, within and across independent loci, T2D risk alleles that overlap with RFX footprints uniformly disrupt the RFX motifs at high-information content positions. Together, these results suggest that common regulatory variations have shaped islet TF footprints and the transcriptome and that a confluent RFX regulatory grammar plays a significant role in the genetic component of T2D predisposition.chromatin | diabetes | eQTL | epigenome | footprint T ype 2 diabetes (T2D) is a complex disease characterized by pancreatic islet dysfunction and insulin resistance in peripheral tissues; >90% of T2D SNPs identified through genome-wide association studies (GWASs) reside in nonprotein coding regions and are likely to perturb gene expression rather than alter protein function (1). In support of this finding, we and others recently showed that T2D GWAS SNPs are significantly enriched in enhancer elements that are specific to pancreatic islets (2-4). The critical next steps to translate these islet enhancer T2D genetic associations into mechanistic biological knowledge are (i) identifying the putative functional SNP(s) from all of those that are in tight linkage disequilibrium (LD), (ii) localizing their target gene(s), and (iii) understanding the direction of effect (increased or decreased target gene expression) conferred by the risk allele. Two recent studies analyzed genome variation and gene expression variation across human islet samples to identify cis-expression quantitative trait loci (cis-eQTLs) that linked T2D GWAS SNPs to target genes (5, 6). However, the transcription factor (TF) molecular mediators of the islet cis-eQTLs...

Glycemic traits are used to diagnose and monitor type 2 diabetes, and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here, we aggregated genome-wide association studies in up to 281,416 individuals without diabetes (30% non-European ancestry) with fasting glucose, 2h-glucose post-challenge, glycated hemoglobin, and fasting insulin data. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P <5x10 -8 ), 80% with no significant evidence of between-ancestry heterogeneity. Analyses restricted to European ancestry individuals with equivalent sample size would have led to 24 fewer new loci. Compared to single-ancestry, equivalent sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase understanding of diabetes pathophysiology by use of trans-ancestry studies for improved power and resolution.

Most signals detected by genome-wide association studies map to non-coding sequence and their tissue-specific effects influence transcriptional regulation. However, key tissues and cell-types required for functional inference are absent from large-scale resources. Here we explore the relationship between genetic variants influencing predisposition to type 2 diabetes (T2D) and related glycemic traits, and human pancreatic islet transcription using data from 420 donors. We find: (a) 7741 cis-eQTLs in islets with a replication rate across 44 GTEx tissues between 40% and 73%; (b) marked overlap between islet cis-eQTL signals and active regulatory sequences in islets, with reduced eQTL effect size observed in the stretch enhancers most strongly implicated in GWAS signal location; (c) enrichment of islet cis-eQTL signals with T2D risk variants identified in genome-wide association studies; and (d) colocalization between 47 islet cis-eQTLs and variants influencing T2D or glycemic traits, including DGKB and TCF7L2. Our findings illustrate the advantages of performing functional and regulatory studies in disease relevant tissues.

SUMMARY EndoC-βH1 is emerging as a critical human β cell model to study the genetic and environmental etiologies of β cell (dys)function and diabetes. Comprehensive knowledge of its molecular landscape is lacking, yet required, for effective use of this model. Here, we report chromosomal (spectral karyotyping), genetic (genotyping), epigenomic (ChIP-seq and ATAC-seq), chromatin interaction (Hi-C and Pol2 ChIA-PET), and transcriptomic (RNA-seq and miRNA-seq) maps of EndoC-βH1. Analyses of these maps define known (e.g., PDX1 and ISL1 ) and putative (e.g., PCSK1 and mir-375 ) β cell-specific transcriptional cis -regulatory networks and identify allelic effects on cis -regulatory element use. Importantly, comparison with maps generated in primary human islets and/or β cells indicates preservation of chromatin looping but also highlights chromosomal aberrations and fetal genomic signatures in EndoC-βH1. Together, these maps, and a web application we created for their exploration, provide important tools for the design of experiments to probe and manipulate the genetic programs governing β cell identity and (dys)function in diabetes.

A leading strategy in tissue engineering is the design of biomimetic scaffolds that stimulate the body’s repair mechanisms through the recruitment of endogenous stem cells to sites of injury. Approaches that employ the use of chemoattractant gradients to guide tissue regeneration without external cell sources are favored over traditional cell-based therapies that have limited potential for clinical translation. Following this concept, bioactive scaffolds can be engineered to provide a temporally and spatially controlled release of biological cues, with the possibility to mimic the complex signaling patterns of endogenous tissue regeneration. Another effective way to regulate stem cell activity is to leverage the inherent chemotactic properties of extracellular matrix (ECM)-based materials to build versatile cell-instructive platforms. This review introduces the concept of endogenous stem cell recruitment, and provides a comprehensive overview of the strategies available to achieve effective cardiovascular and bone tissue regeneration.