Biology subjects

Orchard, P.

Publications and source records attributed to Orchard, P..

At least 19 recordsLinked to original sources

bioRxiv2026

Single-nucleus multi-omics reveals reversible molecular signatures in skeletal muscle of patients with heart failure with preserved ejection fraction

Heart failure with preserved ejection fraction (HFpEF) is a complex systemic syndrome characterized by severe exercise intolerance. In addition to cardiac dysfunction, abnormalities in peripheral skeletal muscle are key contributors to reduced exercise capacity in HFpEF. Multiple studies show that exercise training and caloric restriction improve exercise capacity and quality of life in HFpEF patients. To map the HFpEF-associated molecular signatures in skeletal muscle and the effect of lifestyle intervention, we generated single-nucleus (sn) multiome (joint snRNA-seq and snATAC-seq) profiles of 140 biopsies. Our study included 95 individuals: 25 healthy controls and 70 HFpEF patients, of whom 45 had paired biopsies collected before and after a supervised diet and exercise intervention. From 132,568 nuclei, we resolved 15 skeletal muscle cell types and identified HFpEF-specific remodeling, including type 1 fiber and pericyte depletion and type 2x fiber enrichment, reflecting the cellular basis of exercise intolerance. Transcriptional changes in HFpEF muscle indicated dysregulation of metabolic pathways, stress-responsive programs, cytoskeletal integrity, and calcium signaling. Transcription factor (TF) motifs enriched in differentially accessible chromatin corresponded to concordantly differentially expressed TF-genes, revealing coordinated regulatory programs underlying these changes. Importantly, HFpEF-related changes in both chromatin accessibility and transcription were partially reversible following diet and exercise. Integrative multiomic velocity analyses revealed increased coordinated repression in both chromatin accessibility and transcription of calcium handling genes in HFpEF. HFpEF-linked chromatin was enriched for HF and cardiometabolic GWAS signals, and cross-modal analyses further nominated candidate causal variants and effector genes linking genetic risk to peripheral muscle dysfunction in HFpEF. Together, these findings highlight the molecular mechanisms underlying skeletal muscle remodeling in HFpEF and identify pathways responsive to lifestyle interventions.

genomics↗

bioRxiv2026

Erosion of regenerative regulation: age-associated shifts in the skeletal muscle fiber epigenome and transcriptome

Skeletal muscle aging is characterized by the deterioration of muscle function, which can lead to negative quality-of-life outcomes including frailty and sarcopenia. While understanding the mechanisms of this process is increasingly important as the global population ages, previous molecular studies of skeletal muscle aging have been limited by statistical power and cell type resolution. In this study, we analyzed single-nucleus gene expression and chromatin accessibility data from 287 human skeletal muscle samples from individuals aged 20-79 years to explore sex- and cell type- specific aging effects. Across 467,126 nuclei from 13 cell types, we identify 384 age-associated genes and 4,061 age-associated chromatin regions. These age-associated molecular features are enriched for functional pathways, including metabolic processes, cell-to-cell communication, and senescence Kyoto Encyclopedia of Genes and Genomes KEGG terms. Age-associated closing chromatin was more common across fiber types and sexes than opening chromatin, and was enriched in active enhancer regions while depleted for active transcription start sites. We observe enrichment for specific transcription factor motifs in closing chromatin, including those of glucocorticoid and androgen receptors, both of which play a key role in the maintenance of healthy skeletal muscle. Together, these findings identify an age-associated regulatory shift, largely invisible in matched transcriptomic data, characterized by closing chromatin which reduces accessibility to hormone receptor binding sites and enhancer regions in the muscle fiber epigenome.

bioinformatics↗

bioRxiv2026

Integrated Analysis of Skeletal Muscle Transcriptional Networks Characterizes Dysregulation in Pathways and Trait-Associated Regulatory Regions in Type 2 Diabetes

Skeletal muscle, a primary site of insulin-mediated glucose uptake, plays a central role in the pathogenesis of type 2 diabetes. It is therefore critical to understand the disease-associated alterations in skeletal muscle and identify the underlying drivers of this dysregulation. Here, we characterize type 2 diabetes associated transcriptional dysregulation using 301 skeletal muscle biopsies from living donors with and without diabetes. Using weighted gene co-expression network analysis, we identify 56 distinct gene modules, which we further characterize using single-nucleus RNA-seq-derived cell type signatures and pathway enrichment analysis. We identify numerous cell type-associated dysregulated pathways in skeletal muscle tissue from individuals with diabetes, including muscle fiber-associated mitochondrial function and mRNA splicing and processing; endothelial vascularization and phospholipase D signaling; and macrophage- and T-cell-associated inflammation. Through analysis of module hub genes and transcription factor regulatory network analysis, we further identify candidate driver genes of this dysregulation including ATP5L, ATF2, SIRT1, and THRAP3 in muscle fibers; JAM2 and CLEC14A in endothelial cells; and F13A1 and IRF8 in immune cells. Finally, we integrate our co-expression networks with single-nucleus ATAC-seq data to identify proximal and distal genomic regulatory elements and identify context-specific enrichment for type 2 diabetes and related trait GWAS signals in muscle fiber and endothelial modules. Together, our results reveal dysregulation in pathways in muscle tissue from individuals with diabetes, identify candidate drivers, and connect the genomic drivers of this dysregulation across type 2 diabetes and related metabolic traits.

bioinformatics↗

bioRxiv2026

Unveiling the Hidden Rules: Enhancing NMD Prediction for Protein-Truncating Variants

Nonsense-mediated decay (NMD) is a conserved RNA quality-control pathway that degrades transcripts containing premature termination codons. Because roughly a third of pathogenic variants in ClinVar can lead to truncated protein synthesis, predicting whether such transcripts undergo NMD is central to interpreting variant effects, yet the canonical 50-55 nucleotide rule explains only about half of observed outcome variability. Using paired whole-genome and RNA-sequencing from 10,306 individual samples in the Trans-Omics for Precision Medicine (TOPMed) program, we quantified NMD efficiency for 5,749 germline truncating variants via allele-specific expression and trained a gradient-boosting classifier, TrunCat, that distinguished NMD-sensitive from NMD-escape transcripts with [~]78% ROC-AUC (Receiver Operating Characteristic - Area Under the Curve). A reduced model using the ten features with the highest mean SHAP (SHapley Additive exPlanations) value as a measure of each features average contribution to predictions nearly matched this performance. Applied across large variant databases and a rare-disease cohort, the model produced NMD outcome predictions, with variants of uncertain significance showing higher predicted escape than pathogenic ones. This framework confirms the canonical rule, identifies non-canonical determinants, and offers a scalable resource for interpreting protein-truncating variants.

genomics↗

bioRxiv2026

Genetic demultiplexing and transcript start site identification from nanopore sequencing of 10x Genomics multiome libraries

Short-read Illumina sequencing of 10x Genomics single-nucleus multiome libraries captures only the 3 end of RNA transcripts, losing transcription start site (TSS) information. Here we demonstrate nanopore sequencing of 10x multiome libraries, which enables the profiling of full length transcripts. We show concordance with common short-read sequencing based workflows including successful genetic demultiplexing of nanopore data despite its higher error rate. We compare TSS identified using nanopore sequencing of multiome cDNA to those identified using a short-read 5 assay, and provide an optimized approach for the preprocessing of nanopore reads prior to TSS identification. We find that nanopore sequencing of multiome cDNA captures a median of 63% of the TSS detected by the 5 assay.

bioinformatics↗

bioRxiv2026

3D chromatin compartment of round spermatids encodes the spatiotemporal program of histone-to-protamine exchange in spermiogenesis

Sperm formation requires a radical chromatin reorganization, where nucleosomes are replaced by transition proteins (TNPs) and subsequently by protamines (PRM1 and PRM2). Although essential for fertility, the regulatory logic governing this exchange is unknown, but its presumed to be stochastic and unregulated. Using endogenously tagged PRM mouse models and stage-resolved, genome-wide profiling, we revise the order of histone-to-protamine exchange and show that the chromatin remodeling process is highly programmed. Imaging and biochemical experiments reveal a direct histone-to-PRM1 exchange, while TNPs appear after PRM1 but precede PRM2 incorporation. This temporal uncoupling of PRM1 and PRM2 incorporation coincides with dynamic, region-specific chromatin remodeling that is not governed by histone acetylation but is instructed by the three-dimensional nuclear architecture of round spermatids. Therefore, by integrating ATAC-seq, CUT&Tag, and Hi-C, we define a compartment-encoded "blueprint" that prescribes the assembly of the mature sperm epigenome and establishes a complex molecular hierarchy for the histone-to-protamine exchange.

genomics↗

bioRxiv2026

Donor-matched iPSC model reveals context-dependent T2D genetic signals in fibro-adipogenic progenitors

Fibro-adipogenic progenitors (FAPs) in skeletal muscle have been implicated in type 2 diabetes (T2D), yet their heterogeneity and context-dependent regulation remain poorly understood. Here, we establish induced pluripotent stem cell (iPSC)-derived FAPs as a model of primary FAPs by leveraging a unique resource: iPSC lines and skeletal muscle biopsies obtained from 34 individuals, a subset of 30 profiled using single-nucleus multiomics. Donor-matched comparisons reveal iPSC-FAPs recapitulate the transcriptome, epigenome, and subtype composition of primary FAPs. Using single-nucleus multiomics, we show that high-insulin exposure drives iPSC-FAPs toward an adipogenic fate - and this adipogenic subtype is enriched for T2D GWAS signals, an enrichment undetectable at baseline. We map the T2D-associated rs3814707 non-coding signal to LTBP3, a gene that influences FAP adipogenic differentiation. These findings reveal how disease-relevant regulatory mechanisms can be masked in unstimulated cells and establish iPSC-FAPs as a powerful platform for dissecting the state-dependent biology of complex metabolic disease.

genetics↗

bioRxiv2025

Opposite directions of association of higher physical activity and higher insulin resistance with human skeletal muscle cell type abundance and fiber type-level gene expression

To investigate the interplay between physical activity and cardiometabolic traits in human skeletal muscle, we characterized gene expression and chromatin accessibility across skeletal muscle cell types in 263 Finnish individuals from the FUSION Tissue Biopsy Study. We analyzed skeletal muscle single-nucleus RNA-seq data (168,309 nuclei, 23,849 genes), ATAC-seq data (242,069 nuclei, 927,588 peaks), and bulk RNA-seq data (22,309 genes). Lower insulin resistance (HOMA-IR) and higher total physical activity were both associated with higher proportions of Type 1 nuclei and lower proportions of Type 2x nuclei. We identified cell-type-level and tissue-level gene expression-trait and gene set-trait associations for cardiometabolic and physical activity traits, and a smaller proportion of cell-type-level chromatin accessibility-trait associations. Traits typically associated with better health--lower trait values of cardiometabolic traits (BMI, HOMA-IR, normal glucose tolerance vs. type 2 diabetes, 2-hour plasma glucose) and higher physical activity levels (total and vigorous)--were associated with higher expression of energy metabolism genes and lower expression of signaling pathway genes across muscle fiber types, total pseudobulk, and to some extent in bulk tissue. For HOMA-IR and physical activity, these directions of association remained when adjusting for both traits in the same model, indicating apparently independent associations in the same pathways.

genomics↗

bioRxiv2025

Integrative multi-omics uncovers skeletal muscle enhancer programming of cardiorespiratory fitness

Cardiorespiratory fitness (CRF) is a heritable trait associated with improved metabolic health and longevity. To identify regulatory mechanisms underlying CRF, we integrated 546 transcriptomic and epigenomic profiles from skeletal muscle of 128 genetically heterogeneous rats selectively bred for high and low running capacity, a model that mirrors CRF-associated traits in humans. Selection drove genetic convergence in coordinated skeletal muscle enhancer networks linked to lipid metabolism and angiogenesis genes. We validated thousands of these genetic effects through integration of 426 genotype, gene expression, and chromatin accessibility profiles in an independent HCRxLCR F2 population (n=147). These 972 multi-omics profiles show that CRF-associated genetic variation reshapes the chromatin landscape to support energy metabolism and oxygen delivery, offering a molecular framework for identifying targets to reduce cardiometabolic disease risk. Glossary of TermsO_LIModality/modalities: essentially a dataset. A modality can refer to one or multiple of ATAC-Seq, H3K27ac & additional histone modifications, chromatin states such as Strong Enhancer, and/or RNA-Seq C_LIO_LIPeaks: only refers to ATAC-Seq and CUT&Tag data C_LIO_LIFeatures: can collectively refer to genomic regions of one or more modality classes (genes, peaks, and/or chromatin state regions) C_LIO_LIVariant(s): SNP(s) C_LI O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/679855v2_ufig1.gif" ALT="Figure 1"> View larger version (56K): org.highwire.dtl.DTLVardef@1ee52eorg.highwire.dtl.DTLVardef@5848b7org.highwire.dtl.DTLVardef@debaforg.highwire.dtl.DTLVardef@1ec43ba_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

bioRxiv2024

Evidence for compensatory evolution within pleiotropic regulatory elements

Pleiotropy, measured as expression breadth across tissues, is one of the best predictors for protein sequence and expression conservation. In this study, we investigated its effect on the evolution of cis-regulatory elements (CREs). To this end, we carefully reanalyzed the Epigenomics Roadmap data for nine fetal tissues, assigning a measure of pleiotropic degree to nearly half a million CREs. To assess the functional conservation of CREs, we generated ATAC-seq and RNA-seq data from humans and macaques. We found that more pleiotropic CREs exhibit greater conservation in accessibility, and the mRNA expression levels of the associated genes are more conserved. This trend of higher conservation for higher degrees of pleiotropy persists when analyzing the transcription factor binding repertoire. In contrast, simple DNA sequence conservation of orthologous sites between species tends to be even lower for pleiotropic CREs than for species-specific CREs. Combining various lines of evidence, we suggest that the lack of sequence conservation for functionally conserved pleiotropic elements is due to compensatory evolution within these large pleiotropic CREs. Furthermore, for less pleiotropic CREs, we find an indication of compensation across CREs. This suggests that pleiotropy is also a good predictor for the functional conservation of CREs, but this is not reflected in the sequence conservation for pleiotropic CREs.

evolutionary biology↗

bioRxiv2023

Population-scale skeletal muscle single-nucleus multi-omic profiling reveals extensive context specific genetic regulation

Skeletal muscle, the largest human organ by weight, is relevant in several polygenic metabolic traits and diseases including type 2 diabetes (T2D). Identifying genetic mechanisms underlying these traits requires pinpointing cell types, regulatory elements, target genes, and causal variants. Here, we use genetic multiplexing to generate population-scale single nucleus (sn) chromatin accessibility (snATAC-seq) and transcriptome (snRNA-seq) maps across 287 frozen human skeletal muscle biopsies representing nearly half a million nuclei. We identify 13 cell types and integrate genetic variation to discover >7,000 expression quantitative trait loci (eQTL) and >100,000 chromatin accessibility QTLs (caQTL) across cell types. Learning patterns of e/caQTL sharing across cell types increased precision of effect estimates. We identify high-resolution cell-states and context-specific e/caQTL with significant genotype by context interaction. We identify nearly 2,000 eGenes colocalized with caQTL and construct causal directional maps for chromatin accessibility and gene expression. Almost 3,500 genome-wide association study (GWAS) signals across 38 relevant traits colocalize with sn-e/caQTL, most in a cell-specific manner. These signals typically colocalize with caQTL and not eQTL, highlighting the importance of population-scale chromatin profiling for GWAS functional studies. Finally, our GWAS-caQTL colocalization data reveal distinct cell-specific regulatory paradigms. Our results illuminate the genetic regulatory architecture of human skeletal muscle at high resolution epigenomic, transcriptomic, and cell-state scales and serve as a template for population-scale multi-omic mapping in complex tissues and traits.

genomics↗

bioRxiv2023

A novel mouse model of cerebral adrenoleukodystrophy highlights NLRP3 activity in lesion pathogenesis

ObjectiveWe sought to create and characterize a mouse model of the inflammatory, cerebral demyelinating phenotype of X-linked adrenoleukodystrophy (ALD) that would facilitate the study of disease pathogenesis and therapy development. We also sought to cross-validate potential therapeutic targets such as fibrin, oxidative stress, and the NLRP3 inflammasome, in post-mortem human and murine brain tissues. BackgroundALD is caused by mutations in the gene ABCD1 encoding a peroxisomal transporter. More than half of males with an ABCD1 mutation develop the cerebral phenotype (cALD). Incomplete penetrance and absence of a genotype-phenotype correlation imply a role for environmental triggers. Mechanistic studies have been limited by the absence of a cALD phenotype in the Abcd1-null mouse. MethodsWe generated a cALD phenotype in 8-week-old, male Abcd1-null mice by deploying a two-hit method that combines cuprizone (CPZ) and experimental autoimmune encephalomyelitis (EAE) models. We employed in vivo MRI and post-mortem immunohistochemistry to evaluate myelin loss, astrogliosis, blood-brain barrier (BBB) disruption, immune cell infiltration, fibrin deposition, oxidative stress, and Nlrp3 inflammasome activation in mice. We used bead-based immunoassay and immunohistochemistry to evaluate IL-18 in CSF and post-mortem human cALD brain tissue. ResultsMRI studies revealed T2 hyperintensities and post-gadolinium enhancement in the medial corpus callosum of cALD mice, similar to human cALD lesions. Both human and mouse cALD lesions shared common histologic features of myelin phagocytosis, myelin loss, abundant microglial activation, T and B-cell infiltration, and astrogliosis. Compared to wild-type controls, Abcd1-null mice had more severe cerebral inflammation, demyelination, fibrin deposition, oxidative stress, and IL-18 activation. IL-18 immunoreactivity co-localized with macrophages/microglia in the perivascular region of both human and mouse brain tissue. InterpretationThis novel mouse model of cALD suggests loss of Abcd1 function predisposes to more severe cerebral inflammation, oxidative stress, fibrin deposition, and Nlrp3 pathway activation, which parallels the findings seen in humans with cALD. We expect this model to enable long-sought investigations into cALD mechanisms and accelerate development of candidate therapies for lesion prevention, cessation, and remyelination. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=133 SRC="FIGDIR/small/564025v1_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@1fbfebforg.highwire.dtl.DTLVardef@111e1e8org.highwire.dtl.DTLVardef@10647eborg.highwire.dtl.DTLVardef@15b9af4_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2022

Single-cell gene expression and chromatin accessibility profiling of human pancreatic islets at basal and stimulatory conditions nominates mechanisms of type 1 diabetes genetic risk

Type 1 diabetes (T1D) is a complex autoimmune disease characterized by the loss of pancreatic islet beta cells. The mechanisms of T1D genetic risk remain poorly understood. Here, we present a multi-omic integrative study of single-cell/nucleus molecular profiles of gene expression and chromatin accessibility in the same biological samples from healthy and beta cell autoantibody+ (AAB+) human pancreatic islets to characterize mechanisms of islet-mediated T1D genetic risk. We additionally performed single-cell/nucleus multi-omic profiling of healthy islets under two stimulatory conditions used as in vitro models of T1D (cytokine cocktail and CVB4 infection) to evaluate how environmental exposures recapitulate multi-omic signatures of T1D. In total, we analyzed 121,272 cells/nuclei across 34 libraries, identifying 10 distinct cell types. We identified cell-type-specific and disease-associated cis-regulatory elements and nominated likely target genes. We provide evidence that T1D genetic risk is mediated through multiple pancreatic cell populations, including islet endocrine cells (beta, alpha, gamma, and delta), exocrine acinar and ductal cells, and immune cells. Finally, we identified three independent T1D risk variants acting through pancreatic islet endocrine cells at the TOX, RASGRP1, and DLK1/MEG3 loci. Together, this work improves our understanding of how non-coding genetic variants encode T1D risk through a complex interplay of different cell types in the pancreas.

genomics↗

bioRxiv2022

Fixing reference errors efficiently improves sequencing results

The GRCh38 reference is the current standard in human genomics research and clinical applications, but includes errors across 33 protein-coding genes, including 12 with medical relevance. Current studies rely on the correctness of this reference genome and require an accurate and cost-effective way to improve variant calling and expression analysis across these erroneous loci. We identified likely artifacts in GTEx, gnomAD, 1000 Genomes Project, and other important genomic resources leading to wrong interpretations for these genes. Here, we present FixItFelix together with a modified GRCh38 version that improves the subsequent analysis across these genes within minutes for an existing BAM/CRAM file. We showcase these improvements over multi-ethnic control samples across short and long-read DNA-, and RNA-sequencing. Furthermore, applying our approach across thousands of genomes demonstrates improvements for population variant calling as well as eQTL studies. Still, some genes e.g., DUSP22 indicate mixed results due to their complexity.

genomics↗

bioRxiv2021

RFX6-mediated dysregulation defines human β cell dysfunction in early type 2 diabetes

A hallmark of type 2 diabetes (T2D), a major cause of world-wide morbidity and mortality, is dysfunction of insulin-producing pancreatic islet {beta} cells1-3. T2D genome-wide association studies (GWAS) have identified hundreds of signals, mostly in the non-coding genome and overlapping {beta} cell regulatory elements, but translating these into biological mechanisms has been challenging4-6. To identify early disease-driving events, we performed single cell spatial proteomics, sorted cell transcriptomics, and assessed islet physiology on pancreatic tissue from short-duration T2D and control donors. Here, through integrative analyses of these diverse modalities, we show that multiple gene regulatory modules are associated with early-stage T2D {beta} cell-intrinsic defects. One notable example is the transcription factor RFX6, which we show is a highly connected {beta} cell hub gene that is reduced in T2D and governs a gene regulatory network associated with insulin secretion defects and T2D GWAS variants. We validated the critical role of RFX6 in {beta} cells through direct perturbation in primary human islets followed by physiological and single nucleus multiome profiling, which showed reduced dynamic insulin secretion and large-scale changes in the {beta} cell transcriptome and chromatin accessibility landscape. Understanding the molecular mechanisms of complex, systemic diseases necessitates integration of signals from multiple molecules, cells, organs, and individuals and thus we anticipate this approach will be a useful template to identify and validate key regulatory networks and master hub genes for other diseases or traits with GWAS data.

cell biology↗

bioRxiv2020

Comprehensive enhancer-target gene assignments improve gene set level interpretation of genome-wide regulatory data

Revealing the gene targets of distal regulatory elements is challenging yet critical for interpreting regulome data. Experiment-derived enhancer-gene links are restricted to a small set of enhancers and/or cell types, while the accuracy of genome-wide approaches remains elusive due to the lack of a systematic evaluation. We combined multiple spatial and in silico approaches for defining enhancer locations and linking them to their target genes aggregated across >500 cell types, generating 1,860 human genome-wide distal Enhancer to Target gene Definitions (EnTDefs). To evaluate performance, we used gene set enrichment testing on 87 independent ENCODE ChIP-seq datasets of 34 transcription factors (TFs) and assessed concordance of results with known TF Gene Ontology (GO) annotations., assuming that greater concordance with TF-GO annotation signifies better enrichment results and thus more accurate enhancer-to-gene assignments. Notably, the top ranked 741 (40%) EnTDefs significantly outperformed the common, naive approach of linking distal regions to the nearest genes (FDR < 0.05), and the top 10 ranked EnTDefs performed well when applied to ChIP-seq data of other cell types. These general EnTDefs also showed comparable performance to EnTDefs generated using cell-type-specific data. Our findings illustrate the power of our approach to provide genome-wide interpretation regardless of cell type.

bioinformatics↗

bioRxiv2020

Human and rat skeletal muscle single-nuclei multi-omic integrative analyses nominate causal cell types, regulatory elements, and SNPs for complex traits

BackgroundSkeletal muscle accounts for the largest proportion of human body mass, on average, and is a key tissue in complex diseases, mobility, and quality of life. It is composed of several different cell and muscle fiber types. ResultsHere, we optimize single-nucleus ATAC-seq (snATAC-seq) to map skeletal muscle cell-specific chromatin accessibility landscapes in frozen human and rat samples, and single-nucleus RNA-seq (snRNA-seq) to map cell-specific transcriptomes in human. We capture type I and type II muscle fiber signatures, which are generally missed by existing single-cell RNA-seq methods. We perform cross-modality and cross-species integrative analyses on 30,531 nuclei, representing 11 libraries, profiled in this study, and identify seven distinct cell types ranging in abundance from 63% (type II fibers) to 0.9% (muscle satellite cells) of all nuclei. We introduce a regression-based approach to infer cell types by comparing transcription start site-distal ATAC-seq peaks to reference enhancer maps and show consistency with RNA-based marker gene cell type assignments. We find heterogeneity in enrichment of genetic variants linked to complex phenotypes from the UK Biobank and diabetes genome wide association studies in cell-specific ATAC-seq peaks, with the most striking enrichment patterns in muscle mesenchymal stem cells ([~]3% of nuclei). Finally, we overlay these chromatin accessibility maps on GWAS data to nominate causal cell types, SNPs, and transcription factor motifs for creatinine levels and type 2 diabetes signals. ConclusionsThese chromatin accessibility profiles for human and rat skeletal muscle cell types are a useful resource for investigating specific cell types and nominating causal GWAS SNPs and cell types.

genomics↗

bioRxiv2019

Integrating enhancer RNA signatures with diverse omics data identifies characteristics of transcription initiation in pancreatic islets

Identifying the tissue-specific molecular signatures of active regulatory elements is critical to understand gene regulatory mechanisms. Here, we identify transcription start sites (TSS) using cap analysis of gene expression (CAGE) across 57 human pancreatic islet samples. We identify 9,954 reproducible CAGE tag clusters (TCs), ~20% of which are islet-specific and occur mostly distal to known gene TSSs. We integrated islet CAGE data with histone modification and chromatin accessibility profiles to identify epigenomic signatures of transcription initiation. Using a massively parallel reporter assay, we validate transcriptional enhancer activity (5% FDR) for 2,279 of 3,378 (~68%) tested islet CAGE elements. TCs within accessible enhancers show higher enrichment to overlap type 2 diabetes genome-wide association study (GWAS) signals than existing islet annotations, which emphasizes the utility of mapping CAGE profiles in disease-relevant tissue. This work provides a high-resolution map of transcriptional initiation in human pancreatic islets with utility for dissecting functional enhancers at GWAS loci.

genomics↗