Catecholamine treatment induces reversible heart injury and cardiomyocyte gene expression.

BACKGROUND: Catecholamines are commonly used as therapeutic drugs in intensive care medicine to maintain sufficient organ perfusion during shock. However, excessive or sustained adrenergic activation drives detrimental cardiac remodeling and may lead to heart failure. Whether catecholamine treatment in absence of heart failure causes persistent cardiac injury, is uncertain. In this experimental study, we assessed the course of cardiac remodeling and recovery during and after prolonged catecholamine treatment and investigated the molecular mechanisms involved. RESULTS: C57BL/6N wild-type mice were assigned to 14 days catecholamine treatment with isoprenaline and phenylephrine (IsoPE), treatment with IsoPE and subsequent recovery, or healthy control groups. IsoPE improved left ventricular contractility but caused substantial cardiac fibrosis and hypertrophy. However, after discontinuation of catecholamine treatment, these alterations were largely reversible. To uncover the molecular mechanisms involved, we performed RNA sequencing from isolated cardiomyocyte nuclei. IsoPE treatment resulted in a transient upregulation of genes related to extracellular matrix formation and transforming growth factor signaling. While components of adrenergic receptor signaling were downregulated during catecholamine treatment, we observed an upregulation of endothelin-1 and its receptors in cardiomyocytes, indicating crosstalk between both signaling pathways. To follow this finding, we treated mice with endothelin-1. Compared to IsoPE, treatment with endothelin-1 induced minor but longer lasting changes in cardiomyocyte gene expression. DNA methylation-guided analysis of enhancer regions identified immediate early transcription factors such as AP-1 family members Jun and Fos as key drivers of pathological gene expression following catecholamine treatment. CONCLUSIONS: The results from this study show that prolonged catecholamine exposure induces adverse cardiac remodeling and gene expression before the onset of left ventricular dysfunction which has implications for clinical practice. The observed changes depend on the type of stimulus and are largely reversible after discontinuation of catecholamine treatment. Crosstalk with endothelin signaling and the downstream transcription factors identified in this study provide new opportunities for more targeted therapeutic approaches that may help to separate desired from undesired effects of catecholamine treatment.

Dynamic enhancer landscapes in human craniofacial development.

The genetic basis of human facial variation and craniofacial birth defects remains poorly understood. Distant-acting transcriptional enhancers control the fine-tuned spatiotemporal expression of genes during critical stages of craniofacial development. However, a lack of accurate maps of the genomic locations and cell type-resolved activities of craniofacial enhancers prevents their systematic exploration in human genetics studies. Here, we combine histone modification, chromatin accessibility, and gene expression profiling of human craniofacial development with single-cell analyses of the developing mouse face to define the regulatory landscape of facial development at tissue- and single cell-resolution. We provide temporal activity profiles for 14,000 human developmental craniofacial enhancers. We find that 56% of human craniofacial enhancers share chromatin accessibility in the mouse and we provide cell population- and embryonic stage-resolved predictions of their in vivo activity. Taken together, our data provide an expansive resource for genetic and developmental studies of human craniofacial development.

Defining the relationship of salivary gland malignancies to novel cell subpopulations in human salivary glands using single nucleus RNA-sequencing.

Salivary glands have essential roles in maintaining oral health, mastication, taste and speech, by secreting saliva. Salivary glands are composed of several types of cells, and each cell type is predicted to be involved in the carcinogenesis of different types of cancers including adenoid cystic carcinoma (ACC), acinic cell carcinoma (AciCC), salivary duct carcinoma (SDC), myoepithelial carcinoma (MECA) and other histology. In our study, we performed single nucleus RNA-seq on three human salivary gland samples to clarify the gene expression profile of each complex cellular component of the salivary glands and related these expression patterns to expression found in salivary gland cancers (SGC) to infer cell of origin. By single nucleus RNA-seq, salivary gland cells were stratified into four clusters: acinar cells, ductal cells 1, ductal cells 2 and myoepithelial cells/stromal cells. The localization of each cell group was verified by IHC of each cluster marker gene, and one group of ductal cells was found to represent intercalated ductal cells labeled with HES1. Furthermore, in comparison with SGC RNA-seq data, acinar cell markers were upregulated in AciCC, but downregulated in ACC and ductal cell markers were upregulated in SDC but downregulated in MECA, suggesting that markers of origin are highly expressed in some SGC. Cell type expressions in specific SGC histology are similar to those found in normal salivary gland populations, indicating a potential etiologic relationship.

Age-related structural and functional changes of the intracardiac nervous system.

BACKGROUND: Although aging is known to be associated with an increased incidence of both atrial and ventricular arrhythmias, there is limited knowledge about how Schwann cells (SC) and the intracardiac nervous system (iCNS) remodel with age. Here we investigate the differences in cardiac SC, parasympathetic nerve fibers, and muscarinic acetylcholine receptor M2 (M2R) expression in young and old mice. Additionally, we examine age-related changes in cardiac responses to sympathomimetic and parasympathomimetic drugs. METHODS AND RESULTS: Lower SC density, lower SC proliferation and fewer parasympathetic nerve fibers were observed in cardiac and, as a control sciatic nerves from old (20-24 months) compared to young mice (2-3 months). In old mice, chondroitin sulfate proteoglycan 4 (CSPG4) was increased in sciatic but not cardiac nerves. Expression of M2R was lower in ventricular myocardium and ventricular conduction system from old mice compared to young mice, while no significant difference was seen in M2R expression in sino-atrial or atrio-ventricular node pacemaker tissue. Heart rate was slower and PQ intervals were longer in Langendorff-perfused hearts from old mice. Ventricular tachycardia and fibrillation were more frequently observed in response to carbachol administration in hearts from old mice versus those from young mice. CONCLUSIONS: On the background of reduced presence of SC and parasympathetic nerve fibers, and of lower M2R expression in ventricular cardiomyocytes and conduction system of aged hearts, the propensity of ventricular arrhythmogenesis upon parasympathomimetic drug application is increased. Whether this is caused by an increase in heterogeneity of iCNS structure and function remains to be elucidated.

Single-cell analysis of chromatin accessibility in the adult mouse brain.

Recent advances in single-cell technologies have led to the discovery of thousands of brain cell types; however, our understanding of the gene regulatory programs in these cell types is far from complete1-4. Here we report a comprehensive atlas of candidate cis-regulatory DNA elements (cCREs) in the adult mouse brain, generated by analysing chromatin accessibility in 2.3 million individual brain cells from 117 anatomical dissections. The atlas includes approximately 1 million cCREs and their chromatin accessibility across 1,482 distinct brain cell populations, adding over 446,000 cCREs to the most recent such annotation in the mouse genome. The mouse brain cCREs are moderately conserved in the human brain. The mouse-specific cCREs-specifically, those identified from a subset of cortical excitatory neurons-are strongly enriched for transposable elements, suggesting a potential role for transposable elements in the emergence of new regulatory programs and neuronal diversity. Finally, we infer the gene regulatory networks in over 260 subclasses of mouse brain cells and develop deep-learning models to predict the activities of gene regulatory elements in different brain cell types from the DNA sequence alone. Our results provide a resource for the analysis of cell-type-specific gene regulation programs in both mouse and human brains.

A comparative atlas of single-cell chromatin accessibility in the human brain.

Recent advances in single-cell transcriptomics have illuminated the diverse neuronal and glial cell types within the human brain. However, the regulatory programs governing cell identity and function remain unclear. Using a single-nucleus assay for transposase-accessible chromatin using sequencing (snATAC-seq), we explored open chromatin landscapes across 1.1 million cells in 42 brain regions from three adults. Integrating this data unveiled 107 distinct cell types and their specific utilization of 544,735 candidate cis-regulatory DNA elements (cCREs) in the human genome. Nearly a third of the cCREs demonstrated conservation and chromatin accessibility in the mouse brain cells. We reveal strong links between specific brain cell types and neuropsychiatric disorders including schizophrenia, bipolar disorder, Alzheimer's disease (AD), and major depression, and have developed deep learning models to predict the regulatory roles of noncoding risk variants in these disorders.

Human microglia maturation is underpinned by specific gene regulatory networks.

Microglia phenotypes are highly regulated by the brain environment, but the transcriptional networks that specify the maturation of human microglia are poorly understood. Here, we characterized stage-specific transcriptomes and epigenetic landscapes of fetal and postnatal human microglia and acquired corresponding data in induced pluripotent stem cell (iPSC)-derived microglia, in cerebral organoids, and following engraftment into humanized mice. Parallel development of computational approaches that considered transcription factor (TF) co-occurrence and enhancer activity allowed prediction of shared and state-specific gene regulatory networks associated with fetal and postnatal microglia. Additionally, many features of the human fetal-to-postnatal transition were recapitulated in a time-dependent manner following the engraftment of iPSC cells into humanized mice. These data and accompanying computational approaches will facilitate further efforts to elucidate mechanisms by which human microglia acquire stage- and disease-specific phenotypes.

Cell Type- and Tissue-specific Enhancers in Craniofacial Development.

The genetic basis of craniofacial birth defects and general variation in human facial shape remains poorly understood. Distant-acting transcriptional enhancers are a major category of non-coding genome function and have been shown to control the fine-tuned spatiotemporal expression of genes during critical stages of craniofacial development1-3. However, a lack of accurate maps of the genomic location and cell type-specific in vivo activities of all craniofacial enhancers prevents their systematic exploration in human genetics studies. Here, we combined histone modification and chromatin accessibility profiling from different stages of human craniofacial development with single-cell analyses of the developing mouse face to create a comprehensive catalogue of the regulatory landscape of facial development at tissue- and single cell-resolution. In total, we identified approximately 14,000 enhancers across seven developmental stages from weeks 4 through 8 of human embryonic face development. We used transgenic mouse reporter assays to determine the in vivo activity patterns of human face enhancers predicted from these data. Across 16 in vivo validated human enhancers, we observed a rich diversity of craniofacial subregions in which these enhancers are active in vivo. To annotate the cell type specificities of human-mouse conserved enhancers, we performed single-cell RNA-seq and single-nucleus ATAC-seq of mouse craniofacial tissues from embryonic days e11.5 to e15.5. By integrating these data across species, we find that the majority (56%) of human craniofacial enhancers are functionally conserved in mice, providing cell type- and embryonic stage-resolved predictions of their in vivo activity profiles. Using retrospective analysis of known craniofacial enhancers in combination with single cell-resolved transgenic reporter assays, we demonstrate the utility of these data for predicting the in vivo cell type specificity of enhancers. Taken together, our data provide an expansive resource for genetic and developmental studies of human craniofacial development.

Robust enhancer-gene regulation identified by single-cell transcriptomes and epigenomes.

Single-cell sequencing could help to solve the fundamental challenge of linking millions of cell-type-specific enhancers with their target genes. However, this task is confounded by patterns of gene co-expression in much the same way that genetic correlation due to linkage disequilibrium confounds fine-mapping in genome-wide association studies (GWAS). We developed a non-parametric permutation-based procedure to establish stringent statistical criteria to control the risk of false-positive associations in enhancer-gene association studies (EGAS). We applied our procedure to large-scale transcriptome and epigenome data from multiple tissues and species, including the mouse and human brain, to predict enhancer-gene associations genome wide. We tested the functional validity of our predictions by comparing them with chromatin conformation data and causal enhancer perturbation experiments. Our study shows how controlling for gene co-expression enables robust enhancer-gene linkage using single-cell sequencing data.

Single Cell Multiomics Identifies Cells and Genetic Networks Underlying Alveolar Capillary Dysplasia.

Rationale: Alveolar capillary dysplasia with misalignment of pulmonary veins (ACDMPV) is a lethal developmental disorder of lung morphogenesis caused by insufficiency of FOXF1 (forkhead box F1) transcription factor function. The cellular and transcriptional mechanisms by which FOXF1 deficiency disrupts human lung formation are unknown. Objectives: To identify cell types, gene networks, and cell-cell interactions underlying the pathogenesis of ACDMPV. Methods: We used single-nucleus RNA and assay for transposase-accessible chromatin sequencing, immunofluorescence confocal microscopy, and RNA in situ hybridization to identify cell types and molecular networks influenced by FOXF1 in ACDMPV lungs. Measurements and Main Results: Pathogenic single-nucleotide variants and copy-number variant deletions involving the FOXF1 gene locus in all subjects with ACDMPV (n = 6) were accompanied by marked changes in lung structure, including deficient alveolar development and a paucity of pulmonary microvasculature. Single-nucleus RNA and assay for transposase-accessible chromatin sequencing identified alterations in cell number and gene expression in endothelial cells (ECs), pericytes, fibroblasts, and epithelial cells in ACDMPV lungs. Distinct cell-autonomous roles for FOXF1 in capillary ECs and pericytes were identified. Pathogenic variants involving the FOXF1 gene locus disrupt gene expression in EC progenitors, inhibiting the differentiation or survival of capillary 2 ECs and cell-cell interactions necessary for both pulmonary vasculogenesis and alveolar type 1 cell differentiation. Loss of the pulmonary microvasculature was associated with increased VEGFA (vascular endothelial growth factor A) signaling and marked expansion of systemic bronchial ECs expressing COL15A1 (collagen type XV α 1 chain). Conclusions: Distinct FOXF1 gene regulatory networks were identified in subsets of pulmonary endothelial and fibroblast progenitors, providing both cellular and molecular targets for the development of therapies for ACDMPV and other diffuse lung diseases of infancy.

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

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 13 individuals. Clustering chromatin accessibility profiles of 96,002 total nuclei identified 17 immune cell types and sub-types. We mapped chromatin accessibility QTLs (caQTLs) in each immune cell type and sub-type using individuals of European ancestry which identified 6,901 caQTLs at FDR < .10 and 4,220 caQTLs at FDR < .05, including those obscured from assays of bulk tissue such as with divergent effects on different cell types. For 3,941 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 622 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 naïve 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.

Interpreting non-coding disease-associated human variants using single-cell epigenomics.

Genome-wide association studies (GWAS) have linked hundreds of thousands of sequence variants in the human genome to common traits and diseases. However, translating this knowledge into a mechanistic understanding of disease-relevant biology remains challenging, largely because such variants are predominantly in non-protein-coding sequences that still lack functional annotation at cell-type resolution. Recent advances in single-cell epigenomics assays have enabled the generation of cell type-, subtype- and state-resolved maps of the epigenome in heterogeneous human tissues. These maps have facilitated cell type-specific annotation of candidate cis-regulatory elements and their gene targets in the human genome, enhancing our ability to interpret the genetic basis of common traits and diseases.

Integrated analysis of single-cell chromatin state and transcriptome identified common vulnerability despite glioblastoma heterogeneity.

In 2021, the World Health Organization reclassified glioblastoma, the most common form of adult brain cancer, into isocitrate dehydrogenase (IDH)-wild-type glioblastomas and grade IV IDH mutant (G4 IDHm) astrocytomas. For both tumor types, intratumoral heterogeneity is a key contributor to therapeutic failure. To better define this heterogeneity, genome-wide chromatin accessibility and transcription profiles of clinical samples of glioblastomas and G4 IDHm astrocytomas were analyzed at single-cell resolution. These profiles afforded resolution of intratumoral genetic heterogeneity, including delineation of cell-to-cell variations in distinct cell states, focal gene amplifications, as well as extrachromosomal circular DNAs. Despite differences in IDH mutation status and significant intratumoral heterogeneity, the profiled tumor cells shared a common chromatin structure defined by open regions enriched for nuclear factor 1 transcription factors (NFIA and NFIB). Silencing of NFIA or NFIB suppressed in vitro and in vivo growths of patient-derived glioblastomas and G4 IDHm astrocytoma models. These findings suggest that despite distinct genotypes and cell states, glioblastoma/G4 astrocytoma cells share dependency on core transcriptional programs, yielding an attractive platform for addressing therapeutic challenges associated with intratumoral heterogeneity.

Integrating genetics with single-cell multiomic measurements across disease states identifies mechanisms of beta cell dysfunction in type 2 diabetes.

Dysfunctional pancreatic islet beta cells are a hallmark of type 2 diabetes (T2D), but a comprehensive understanding of the underlying mechanisms, including gene dysregulation, is lacking. Here we integrate information from measurements of chromatin accessibility, gene expression and function in single beta cells with genetic association data to nominate disease-causal gene regulatory changes in T2D. Using machine learning on chromatin accessibility data from 34 nondiabetic, pre-T2D and T2D donors, we identify two transcriptionally and functionally distinct beta cell subtypes that undergo an abundance shift during T2D progression. Subtype-defining accessible chromatin is enriched for T2D risk variants, suggesting a causal contribution of subtype identity to T2D. Both beta cell subtypes exhibit activation of a stress-response transcriptional program and functional impairment in T2D, which is probably induced by the T2D-associated metabolic environment. Our findings demonstrate the power of multimodal single-cell measurements combined with machine learning for characterizing mechanisms of complex diseases.

Understanding cell fate acquisition in stem-cell-derived pancreatic islets using single-cell multiome-inferred regulomes.

Pancreatic islet cells derived from human pluripotent stem cells hold great promise for modeling and treating diabetes. Differences between stem-cell-derived and primary islets remain, but molecular insights to inform improvements are limited. Here, we acquire single-cell transcriptomes and accessible chromatin profiles during in vitro islet differentiation and pancreas from childhood and adult donors for comparison. We delineate major cell types, define their regulomes, and describe spatiotemporal gene regulatory relationships between transcription factors. CDX2 emerged as a regulator of enterochromaffin-like cells, which we show resemble a transient, previously unrecognized, serotonin-producing pre-ß cell population in fetal pancreas, arguing against a proposed non-pancreatic origin. Furthermore, we observe insufficient activation of signal-dependent transcriptional programs during in vitro ß cell maturation and identify sex hormones as drivers of ß cell proliferation in childhood. Altogether, our analysis provides a comprehensive understanding of cell fate acquisition in stem-cell-derived islets and a framework for manipulating cell identities and maturity.

Integration of single-cell multiomic measurements across disease states with genetics identifies mechanisms of beta cell dysfunction in type 2 diabetes.

Altered function and gene regulation of pancreatic islet beta cells is a hallmark of type 2 diabetes (T2D), but a comprehensive understanding of mechanisms driving T2D is still missing. Here we integrate information from measurements of chromatin activity, gene expression and function in single beta cells with genetic association data to identify disease-causal gene regulatory changes in T2D. Using machine learning on chromatin accessibility data from 34 non-diabetic, pre-T2D and T2D donors, we robustly identify two transcriptionally and functionally distinct beta cell subtypes that undergo an abundance shift in T2D. Subtype-defining active chromatin is enriched for T2D risk variants, suggesting a causal contribution of subtype identity to T2D. Both subtypes exhibit activation of a stress-response transcriptional program and functional impairment in T2D, which is likely induced by the T2D-associated metabolic environment. Our findings demonstrate the power of multimodal single-cell measurements combined with machine learning for identifying mechanisms of complex diseases.

Characterizing cis-regulatory elements using single-cell epigenomics.

Cell type-specific gene expression patterns and dynamics during development or in disease are controlled by cis-regulatory elements (CREs), such as promoters and enhancers. Distinct classes of CREs can be characterized by their epigenomic features, including DNA methylation, chromatin accessibility, combinations of histone modifications and conformation of local chromatin. Tremendous progress has been made in cataloguing CREs in the human genome using bulk transcriptomic and epigenomic methods. However, single-cell epigenomic and multi-omic technologies have the potential to provide deeper insight into cell type-specific gene regulatory programmes as well as into how they change during development, in response to environmental cues and through disease pathogenesis. Here, we highlight recent advances in single-cell epigenomic methods and analytical tools and discuss their readiness for human tissue profiling.

Single-cell epigenome analysis reveals age-associated decay of heterochromatin domains in excitatory neurons in the mouse brain.

Loss of heterochromatin has been implicated as a cause of pre-mature aging and age-associated decline in organ functions in mammals; however, the specific cell types and gene loci affected by this type of epigenetic change have remained unclear. To address this knowledge gap, we probed chromatin accessibility at single-cell resolution in the brains, hearts, skeletal muscles, and bone marrows from young, middle-aged, and old mice, and assessed age-associated changes at 353,126 candidate cis-regulatory elements (cCREs) across 32 major cell types. Unexpectedly, we detected increased chromatin accessibility within specific heterochromatin domains in old mouse excitatory neurons. The gain of chromatin accessibility at these genomic loci was accompanied by the cell-type-specific loss of heterochromatin and activation of LINE1 elements. Immunostaining further confirmed the loss of the heterochromatin mark H3K9me3 in the excitatory neurons but not in inhibitory neurons or glial cells. Our results reveal the cell-type-specific changes in chromatin landscapes in old mice and shed light on the scope of heterochromatin loss in mammalian aging.

Single nucleus multi-omics identifies human cortical cell regulatory genome diversity.

Single-cell technologies measure unique cellular signatures but are typically limited to a single modality. Computational approaches allow the fusion of diverse single-cell data types, but their efficacy is difficult to validate in the absence of authentic multi-omic measurements. To comprehensively assess the molecular phenotypes of single cells, we devised single-nucleus methylcytosine, chromatin accessibility, and transcriptome sequencing (snmCAT-seq) and applied it to postmortem human frontal cortex tissue. We developed a cross-validation approach using multi-modal information to validate fine-grained cell types and assessed the effectiveness of computational data fusion methods. Correlation analysis in individual cells revealed distinct relations between methylation and gene expression. Our integrative approach enabled joint analyses of the methylome, transcriptome, chromatin accessibility, and conformation for 63 human cortical cell types. We reconstructed regulatory lineages for cortical cell populations and found specific enrichment of genetic risk for neuropsychiatric traits, enabling the prediction of cell types that are associated with diseases.

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

We combined functional genomics and human genetics to investigate processes that affect type 1 diabetes (T1D) risk by mediating beta cell survival in response to proinflammatory cytokines. We mapped 38,931 cytokine-responsive candidate cis-regulatory elements (cCREs) in beta cells using ATAC-seq and snATAC-seq and linked them to target genes using co-accessibility and HiChIP. Using a genome-wide CRISPR screen in EndoC-ßH1 cells, we identified 867 genes affecting cytokine-induced survival, and genes promoting survival and up-regulated in cytokines were enriched at T1D risk loci. Using SNP-SELEX, we identified 2,229 variants in cytokine-responsive cCREs altering transcription factor (TF) binding, and variants altering binding of TFs regulating stress, inflammation, and apoptosis were enriched for T1D risk. At the 16p13 locus, a fine-mapped T1D variant altering TF binding in a cytokine-induced cCRE interacted with SOCS1, which promoted survival in cytokine exposure. Our findings reveal processes and genes acting in beta cells during inflammation that modulate T1D risk.