Biology subjects

Benaglio, P.

Publications and source records attributed to Benaglio, P..

14 recordsLinked to original sources

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↗

bioRxiv2024

Single cell multiome profiling of pancreatic islets reveals physiological changes in cell type-specific regulation associated with diabetes risk

Physiological variability in pancreatic cell type gene regulation and the impact on diabetes risk is poorly understood. In this study we mapped gene regulation in pancreatic cell types using single cell multiomic (joint RNA-seq and ATAC-seq) profiling in 28 non-diabetic donors in combination with single cell data from 35 non-diabetic donors in the Human Pancreas Analysis Program. We identified widespread associations with age, sex, BMI, and HbA1c, where gene regulatory responses were highly cell type- and phenotype-specific. In beta cells, donor age associated with hypoxia, apoptosis, unfolded protein response, and external signal-dependent transcriptional regulators, while HbA1c associated with inflammatory responses and gender with chromatin organization. We identified 10.8K loci where genetic variants were QTLs for cis regulatory element (cRE) accessibility, including 20% with lineage- or cell type-specific effects which disrupted distinct transcription factor motifs. Type 2 diabetes and glycemic trait associated variants were enriched in both phenotype- and QTL-associated beta cell cREs, whereas type 1 diabetes showed limited enrichment. Variants at 226 diabetes and glycemic trait loci were QTLs in beta and other cell types, including 40 that were statistically colocalized, and annotating target genes of colocalized QTLs revealed genes with putatively novel roles in disease. Our findings reveal diverse responses of pancreatic cell types to phenotype and genotype in physiology, and identify pathways, networks, and genes through which physiology impacts diabetes risk.

genomics↗

bioRxiv2024

Variant-to-function dissection of rare non-coding GWAS loci with high impact on blood traits

Understanding the function of genetic variants associated with human traits and diseases remains a significant challenge. Here we combined analyses based on natural genetic variation and genetic engineering to dissect the function of 94 non-coding variants associated with haematological traits. We describe 22 genetic variants impacting haematological variation through gene expression. Further, through in-depth functional analysis, we illustrate how a rare, non-coding variant near the CUX1 transcription factor impacts megakaryopoiesis through modulation of the CUX1 transcriptional cascade. Collectively, our findings enhance the functional interpretation of genetic association studies and advance understanding of how non-coding variants contribute to blood and immune system variation.

genetics↗

bioRxiv2023

An integrated map of cell type-specific gene expression in pancreatic islets

Pancreatic islets are comprised of multiple endocrine cell types that produce hormones required for glucose homeostasis, and islet dysfunction is a major factor in the development of type 1 and type 2 diabetes (T1D, T2D). Numerous studies have generated gene expression profiles in individual islet cell types using single cell assays. However, there is no canonical reference of gene expression in islet cell types in both health and disease that is also easily accessible for researchers to access, query, and use in bioinformatics pipelines. Here we present an integrated reference map of islet cell type-specific gene expression from 192,203 cells derived from single cell RNA-seq assays of 65 non-diabetic, T1D autoantibody positive (Aab+), T1D, and T2D donors from the Human Pancreas Analysis Program. We identified 10 endocrine and non-endocrine cell types as well as sub-populations of several cell types, and defined sets of marker genes for each cell type and sub-population. We tested for differential expression within each cell type in T1D Aab+, T1D, and T2D states, and identified 1,701 genes with significant changes in expression in any cell type. Most changes were observed in beta cells in T1D, and, by comparison, there were almost no genes with changes in T1D Aab+. To facilitate user interaction with this reference, we provide the data using several single cell visualization and reference mapping tools as well as open-access analytical pipelines used to create this reference. The results will serve as a valuable resource to investigators studying islet biology and diabetes.

genomics↗

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↗

bioRxiv2021

Large-scale genetic association and single cell accessible chromatin mapping defines cell type-specific mechanisms of type 1 diabetes risk

Translating genome-wide association studies (GWAS) of complex disease into mechanistic insight requires a comprehensive understanding of risk variant effects on disease-relevant cell types. To uncover cell type-specific mechanisms of type 1 diabetes (T1D) risk, we combined genetic association mapping and single cell epigenomics. We performed the largest to-date GWAS of T1D in 489,679 samples imputed into 59.2M variants, which identified 74 novel association signals including several large-effect rare variants. Fine-mapping of 141 total signals substantially improved resolution of causal variant credible sets, which primarily mapped to non-coding sequence. To annotate cell type-specific regulatory mechanisms of T1D risk variants, we mapped 448,142 candidate cis-regulatory elements (cCREs) in pancreas and peripheral blood mononuclear cell types using snATAC-seq of 131,554 nuclei. T1D risk variants were enriched in cCREs active in CD4+ T cells as well as several additional cell types including pancreatic exocrine acinar and ductal cells. High-probability T1D risk variants at multiple signals mapped to exocrine-specific cCREs including novel loci near CEL, GP2 and CFTR. At the CFTR locus, the likely causal variant rs7795896 mapped in a ductal-specific distal cCRE which regulated CFTR and the risk allele reduced transcription factor binding, enhancer activity and CFTR expression in ductal cells. These findings support a role for the exocrine pancreas in T1D pathogenesis and highlight the power of combining large-scale GWAS and single cell epigenomics to provide insight into the cellular origins of complex disease.

genetics↗

bioRxiv2020

FOXO1 mitigates the SMAD3/FOXL2C134W Transcriptomic Effect in a Model of Human Adult Granulosa Cell Tumor

BackgroundAdult granulosa cell tumor (aGCT) is a rare type of stromal cell malignant cancer of the ovary characterized by elevated estrogen levels. aGCTs ubiquitously harbor a somatic mutation in FOXL2 gene, Cys134Trp (c.402C<G); however, the general molecular effect of this mutation and its putative pathogenic role in aGCT tumorigenesis is not completely understood. We previously studied the role of FOXL2C134W, its partner SMAD3 and its antagonist FOXO1 in cellular models of aGCT. MethodsIn this work, seeking more comprehensive profiling of FOXL2C134W transcriptomic effects, we performed an RNA-seq analysis comparing the effect of FOXL2WT/SMAD3 and FOXL2C143W/SMAD3 overexpression in an established human GC line (HGrC1), which is not luteinized, and bears normal alleles of FOXL2. ResultsOur data shows that FOXL2C143W/SMAD3 overexpression alters the expression of 717 genes. These genes include known and novel FOXL2 targets (TGFB2, SMARCA4, HSPG2, MKI67, NFKBIA) and are enriched for neoplastic pathways (Proteoglycans in Cancer, Chromatin remodeling, Apoptosis, Tissue Morphogenesis, Tyrosine Kinase Receptors). We additionally expressed the FOXL2 antagonistic Forkhead protein, FOXO1. Surprisingly, overexpression of FOXO1 mitigated 40% of the altered genome-wide effects specifically related to FOXL2C134W, suggesting it can be a new target for aGCT treatment. Conclusionsour transcriptomic data provide novel insights into potential genes (FOXO1 regulated) that could be used as biomarkers of efficacy in aGCT patients.

cancer biology↗

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↗

bioRxiv2020

Glucocorticoid signaling in pancreatic islets modulates gene regulatory programs and genetic risk of type 2 diabetes

Glucocorticoids are key regulators of glucose homeostasis and pancreatic islet function, but the gene regulatory programs driving responses to glucocorticoid signaling in islets and the contribution of these programs to diabetes risk are unknown. In this study we used ATAC-seq and RNA-seq to map chromatin accessibility and gene expression from eight primary human islet samples cultured in vitro with the glucocorticoid dexamethasone. We identified 2,838 accessible chromatin sites and 1,114 genes with significant changes in activity in response to glucocorticoids. Chromatin sites up-regulated in glucocorticoid signaling were prominently enriched for glucocorticoid receptor binding sites and up-regulated genes were enriched for ion transport and lipid metabolism, whereas down-regulated chromatin sites and genes were enriched for inflammatory, stress response and proliferative processes. Genetic variants associated with glucose levels and T2D risk were enriched in glucocorticoid-responsive chromatin sites, including fine-mapped risk variants at 54 known signals. Among fine-mapped variants in glucocorticoid-responsive chromatin, a likely casual variant at the 2p21 locus had glucocorticoid-dependent allelic effects on beta cell enhancer activity and affected SIX2 and SIX3 expression. Our results provide a comprehensive map of islet regulatory programs in response to glucocorticoids through which we uncover a role for islet glucocorticoid signaling in mediating risk of type 2 diabetes.

genomics↗

bioRxiv2019

Human iPSC gene signatures and X chromosome dosage impact response to WNT inhibition and cardiac differentiation fate

Non-genetic variability in human induced pluripotent stem cell (iPSC) lines impacts their differentiation outcome, limiting their utility for genetic studies and clinical applications. Despite the importance of understanding how non-genetic molecular variability influences iPSC differentiation outcome, large-scale studies capable of addressing this question have not yet been conducted. Here, we performed 258 directed differentiations of 191 iPSC lines using established protocols to generate iPSC-derived cardiovascular progenitor cells (iPSC-CVPCs). We observed cellular heterogeneity across the iPSC-CVPC samples due to varying fractions of two cell types: cardiomyocytes (CMs) and epicardium-derived cells (EPDCs). Analyzing the transcriptomes of CM-fated and EPDC-fated iPSCs discovered that 91 signature genes and X chromosome dosage differences influence WNT inhibition response during differentiation and are associated with cardiac fate. Analysis of an independent set of 39 iPSCs differentiated to the cardiac lineage confirmed shared sex and transcriptional differences that impact cardiac fate outcome. The scale and systematic approach of our study enabled novel insights into how iPSC transcriptional and X chromosome gene dosage differences influence WNT signaling during differentiation and hence cardiac cell fate.

genomics↗

bioRxiv2019

Chromatin co-accessibility is highly structured, spans entire chromosomes, and mediates long range regulatory genetic effects

Chromatin accessibility identifies active regions of the genome, often at transcription factor (TF) binding sites, enhancers, and promoters, and contains regulatory genetic variation. Functionally related accessible sites have been reported to be co-accessible; however, the prevalence and range of co-accessibility is unknown. We perform ATAC-seq in induced pluripotent stem cells from 134 individuals and integrate it with RNA-seq, WGS, and ChIP-seq, providing the first long-range chromosome-length analysis of co-accessibility. We show that co-accessibility is highly connected, with sites having a median of 24 co-accessible partners up to 250Mb away. We also show that co-accessibility can de novo identify known and novel co-expressed genes, and co-regulatory TFs and chromatin states. We perform a cis and trans-caQTL, a trans-eQTL, and examine allelic effects of co-accessibility, identifying tens of thousands of trans-caQTLs, and showing that trans genetic effects can be propagated through co-accessibility to gene expression for cell-type and disease relevant genes.

genomics↗

bioRxiv2018

Allele-specific NKX2-5 binding underlies multiple genetic associations with human EKG traits

Genetic variation affecting the binding of transcription factors (TFs) has been proposed as a major mechanism underlying susceptibility to common disease. NKX2-5, a key cardiac development TF, has been associated with electrocardiographic (EKG) traits through GWAS, but the extent to which differential binding of NKX2-5 contributes to these traits has not yet been studied. Here, we analyzed transcriptomic and epigenomic data generated from iPSC-derived cardiomyocyte lines (iPSC-CMs) from seven whole-genome sequenced individuals in a three-generational family. We identified ~2,000 single nucleotide variants (SNVs) associated with allele-specific effects (ASE) on NKX2-5 binding. These ASE-SNVs were enriched for altered TF motifs (both cognate and other cardiac TFs), and were positively correlated with changes in H3K27ac in iPSC-CMs, suggesting they impact cardiac enhancer activity. We found that NKX2-ASE-SNVs were significantly enriched for being heart-specific eQTLs and EKG GWAS variants, suggesting that altered NKX2-5 binding at multiple sites across the genome influences EKG traits. We used a fine-mapping approach to integrate iPSC-CM molecular phenotype data with a GWAS for heart rate, and determined that NKX2-5 ASE variants are likely causal for numerous known, as well as previously unidentified, heart rate loci. Analyzing Hi-C and gene expression data from iPSC-CMs at these heart rate loci, we identified several genes likely to be causally involved in heart rate variability. Our study demonstrates that differential binding of NKX2-5 is a common mechanism underlying genetic association with EKG traits, and shows that characterizing variants associated with differential binding of development TFs in iPSC-derived cell lines can identify novel loci and mechanisms influencing complex traits.

genetics↗

bioRxiv2018

Integration of phased Hi-C and molecular phenotype data to study genetic and epigenetic effects on chromatin looping

While genetic variation at chromatin loops is relevant for human disease, the relationships between loop strength, genetics, gene expression, and epigenetics are unclear. Here, we quantitatively interrogate this relationship using Hi-C and molecular phenotype data across cell types and haplotypes. We find that chromatin loops consistently form across multiple cell types and quantitatively vary in strength, instead of exclusively forming within only one cell type. We show that large haplotype loop imbalance is primarily associated with imprinting and copy number variation, rather than genetically driven traits such as allele-specific expression. Finally, across cell types and haplotypes, we show that subtle changes in chromatin loop strength are associated with large differences in other molecular phenotypes, with a 2-fold change in looping corresponding to a 100-fold change in gene expression. Our study suggests that regulatory genetic variation could mediate its effects on gene expression through subtle modification of chromatin loop strength.

genomics↗

bioRxiv2018

Using deep whole genome sequence, transcriptome and epigenome data to characterize the mutational burden of induced pluripotent stem cells

To understand the mutational burden of human induced pluripotent stem cells (iPSCs), we whole genome sequenced 18 fibroblast-derived iPSC lines and identified different classes of somatic mutations based on structure, origin and frequency. Copy number alterations affected 295 kb in each sample and strongly impacted gene expression. UV-damage mutations were present in ~45% of the iPSCs and accounted for most of the observed heterogeneity in mutation rates across lines. Subclonal mutations (not present in all iPSCs within a line) composed 10% of point mutations, and compared with clonal variants, showed an enrichment in active promoters and increased association with altered gene expression. Our study shows that, by combining WGS, transcriptome and epigenome data, we can understand the mutational burden of each iPSC line on an individual basis and suggests that this information could be used to prioritize iPSC lines for models of specific human diseases and/or transplantation therapy.

genomics↗