Biology subjects

Corban, S.

Publications and source records attributed to Corban, S..

6 recordsLinked to original sources

bioRxiv2026

PanKbase Integrated Single-Cell Map: A Comprehensive Atlas of Human Pancreatic Islets

Single-cell RNA sequencing (scRNA-seq) of human pancreatic islet tissue is a powerful tool for investigating type 1 diabetes (T1D). However, individual datasets are limited in size and fragmented across donors, laboratories, and experimental conditions. To address this, we constructed a comprehensive, integrated scRNA-seq atlas of isolated human pancreatic islets by collating publicly available data generated from tissue provided by resources including the Human Pancreas Analysis Program, the Integrated Islet Distribution Program, and Prodo Labs. Systematic quality controls were implemented to select high-quality samples, reads, and cells. During integration, we accounted for important variables such as age, sex, body mass index, origin study, treatments, islet distribution resources, and sequencing chemistry. Our single-cell atlas comprises 191 high-quality samples from 140 donors (59 female, 81 male) across five phenotypic groups: no diabetes (controls, n=69), autoantibody positivity without diabetes (n=12), pre-diabetes (n=11), T1D (n=12), and type 2 diabetes (T2D) (n=36). In total, the atlas contains 448,935 cells, capturing 13 distinct populations, including alpha cells (43.3%) and beta cells (26.8%), as well as groups such as immune cells (0.6%). Publicly available at www.pankbase.org, this atlas provides a platform for hypothesis-driven investigation of diabetes pathophysiology and, given rigorous quality control, is well-suited for downstream machine-learning applications. Article HighlightsO_LICurrent scRNA-seq datasets of pancreatic islet tissue are limited in size and scattered across donors, laboratories, and experimental conditions, underscoring the need for a consolidated resource. C_LIO_LIWe harmonized datasets from multiple sources to build a comprehensive single-cell map of isolated human pancreatic islets. C_LIO_LIOur atlas captures 448,935 cells from 191 high-quality samples across 140 donors and multiple phenotypic groups, identifying 13 distinct cell populations. C_LIO_LIAvailable at www.pankbase.org, the atlas provides a scalable, rigorously curated platform to support hypothesis-driven diabetes research and can enable a broad range of downstream computational applications. C_LI

genomics↗

bioRxiv2026

Functional genomics reveals mediators of beta cell survival in ER stress and type 2 diabetes risk

Endoplasmic reticulum (ER) stress in pancreatic beta cells contributes to impaired function and type 2 diabetes (T2D). In this study we performed genome-wide perturbation screens and genomic profiling in beta cells to identify novel mediators of ER stress responses and diabetes risk. We defined gene regulatory networks in beta cells and identified specific beta cell networks enriched for T2D risk variants with altered expression in ER stress. We performed a loss-of-function CRISPR screen for survival under ER stress in EndoC-{beta}H1 cells, which identified 167 pro-survival and 47 pro-death genes involved in processes related to insulin secretion, mitochondrial transport and protein ubiquitination. Beta cell survival genes collectively had limited genomic change in stress yet showed significant, independent enrichment for T2D risk variants, including novel T2D candidate gene DTNB which we validated protects against beta cell death during stress. Overall, our results revealed mediators of ER stress responses in beta cells and identified new therapeutic targets to preserve beta cells in diabetes pathogenesis.

genomics↗

bioRxiv2025

Single cell and spatial characterization of the human pancreas reveals drivers of beta cell dysfunction in cystic fibrosis

Cystic fibrosis (CF) causes severely damaged pancreas morphology and results in high rates of cystic fibrosis-related diabetes (CFRD), but the cellular pathways and regulatory programs driving CFRD pathogenesis in the pancreas are not understood. In this study, we performed single cell multiomic and spatial profiling of 2.04M cells in the pancreas from 23 non-disease and CF donors and defined regulatory programs and tissue niches of specific cell types and sub-types in CF. A high-mucin sub-type of ductal cells had relatively preserved abundance, altered localization and up-regulated stress, secretion and pro-fibrotic activity in CF, and conventional ductal cells showed evidence for transition to the high-mucin state. Increased inflammatory and fibrotic pathway activity in CF was linked to closer proximity and crosstalk between immune and stellate cells in specific niches. Beta cells had extensive genomic changes in CF, including increased stress and insulin secretion-related processes, and these changes were broadly distinct from those in type 1 and type 2 diabetes. Islets in CF preferentially localized near large adipose tissue and collagen structures, and both areas were strongly linked to beta cell loss in CF due to signaling from adipocytes, macrophages, stellate, and high-mucin ductal cells. Overall, our results reveal cellular drivers of pancreatic dysfunction in CF and offer new in-roads to preserving beta cells in CFRD.

genomics↗

bioRxiv2025

Comprehensive molecular impact mapping of common and rare variants at GWAS loci

Deep learning sequence to function models can predict the molecular effects of genetic variants, but their predictions are limited to the cell types and assays they are trained on. Here we describe DNACipher, a deep learning model that predicts the effects of genetic variants across diverse biological contexts--including those not directly measured. DNACipher takes 196 kb of genome sequences as input and imputes variant effects across 38,582 cell type-assay combinations. DNACipher generates predictions for >7 times as many contexts as Enformer, which allows for better detection of variant effects at expression quantitative trait loci (eQTLs). We also introduce DNACipher Deep Variant Impact Mapping (DVIM), a method to identify variants with molecular effects at genome-wide association study (GWAS) loci. Application of DVIM to type 1 diabetes (T1D) reduced the mean fine-mapping credible set size from 24 to 1.4 variants per signal. DVIM variants had significantly higher fine-mapping posterior probabilities, and their predicted effects were supported by single-nucleus ATAC-seq and luciferase assays. DVIM also detected 6547 rare variants with molecular effects at 96% of GWAS T1D loci, and these were enriched for associations with immune traits. In summary, DNACipher DVIM prioritises common and rare variants at GWAS loci by predicting molecular effects across a broad range of contexts.

genetics↗

bioRxiv2021

Type 1 diabetes risk genes mediate pancreatic beta cell survival in response to proinflammatory cytokines

Beta cells intrinsically contribute to the pathogenesis of type 1 diabetes (T1D), but the genes and molecular processes that mediate beta cell survival in T1D remain largely unknown. We combined high throughput functional genomics and human genetics to identify T1D risk loci regulating genes affecting beta cell survival in response to the proinflammatory cytokines IL-1{beta}, IFN{gamma}, and TNF. We mapped 38,931 cytokine-responsive candidate cis-regulatory elements (cCREs) active in beta cells using ATAC-seq and single nuclear ATAC-seq (snATAC-seq), and linked cytokine-responsive beta cell cCREs to putative target genes using single cell co-accessibility and HiChIP. We performed a genome-wide pooled CRISPR loss-of-function screen in EndoC-{beta}H1 cells, which identified 867 genes affecting cytokine-induced beta cell loss. Genes that promoted beta cell survival and had up-regulated expression in cytokine exposure were specifically enriched at T1D loci, and these genes were preferentially involved in inhibiting inflammatory response, ubiquitin-mediated proteolysis, mitophagy and autophagy. We identified 2,229 variants in cytokine-responsive beta cell cCREs altering transcription factor (TF) binding using high-throughput SNP-SELEX, and variants altering binding of TF families regulating stress, inflammation and apoptosis were broadly enriched for T1D association. Finally, through integration with genetic fine mapping, we annotated T1D loci regulating beta cell survival in cytokine exposure. At the 16p13 locus, a T1D variant affected TF binding in a cytokine-induced beta cell cCRE that physically interacted with the SOCS1 promoter, and increased SOCS1 activity promoted beta cell survival in cytokine exposure. Together our findings reveal processes and genes acting in beta cells during cytokine exposure that intrinsically modulate risk of T1D.

genomics↗

bioRxiv2020

Mapping genetic effects on cell type-specific chromatin accessibility and annotating complex trait variants using single nucleus ATAC-seq

Gene regulation is highly cell type-specific and understanding the function of non-coding genetic variants associated with complex traits requires molecular phenotyping at cell type resolution. In this study we performed single nucleus ATAC-seq (snATAC-seq) and genotyping in peripheral blood mononuclear cells from 10 individuals. Clustering chromatin accessibility profiles of 66,843 total nuclei identified 14 immune cell types and sub-types. We mapped chromatin accessibility QTLs (caQTLs) in each immune cell type and sub-type which identified 6,248 total caQTLs, including those obscured from assays of bulk tissue such as with divergent effects on different cell types. For 3,379 caQTLs we further annotated putative target genes of variant activity using single cell co-accessibility, and caQTL variants were significantly correlated with the accessibility level of linked gene promoters. We fine-mapped loci associated with 16 complex immune traits and identified immune cell caQTLs at 517 candidate causal variants, including those with cell type-specific effects. At the 6q15 locus associated with type 1 diabetes, in line with previous reports, variant rs72928038 was a naive CD4+ T cell caQTL linked to BACH2 and we validated the allelic effects of this variant on regulatory activity in Jurkat T cells. These results highlight the utility of snATAC-seq for mapping genetic effects on accessible chromatin in specific cell types and provide a resource for annotating complex immune trait loci.

genomics↗