RESUMEN
CellWalker2 is a graph diffusion-based method for single-cell genomics data integration. It extends the CellWalker model by incorporating hierarchical relationships between cell types, providing estimates of statistical significance, and adding data structures for analyzing multi-omics data so that gene expression and open chromatin can be jointly modeled. Our open-source software enables users to annotate cells using existing ontologies and to probabilistically match cell types between two or more contexts, including across species. CellWalker2 can also map genomic regions to cell ontologies, enabling precise annotation of elements derived from bulk data, such as enhancers, genetic variants, and sequence motifs. Through simulation studies, we show that CellWalker2 performs better than existing methods in cell type annotation and mapping. We then use data from the brain and immune system to demonstrate CellWalker2's ability to discover cell type-specific regulatory programs and both conserved and divergent cell type relationships in complex tissues.
RESUMEN
Nucleotide changes in gene regulatory elements are important determinants of neuronal development and diseases. Using massively parallel reporter assays in primary human cells from mid-gestation cortex and cerebral organoids, we interrogated the cis-regulatory activity of 102,767 open chromatin regions, including thousands of sequences with cell type-specific accessibility and variants associated with brain gene regulation. In primary cells, we identified 46,802 active enhancer sequences and 164 variants that alter enhancer activity. Activity was comparable in organoids and primary cells, suggesting that organoids provide an adequate model for the developing cortex. Using deep learning we decoded the sequence basis and upstream regulators of enhancer activity. This work establishes a comprehensive catalog of functional gene regulatory elements and variants in human neuronal development.
Asunto(s)
Corteza Cerebral , Neurogénesis , Organoides , Humanos , Corteza Cerebral/embriología , Corteza Cerebral/metabolismo , Cromatina/metabolismo , Cromatina/genética , Aprendizaje Profundo , Elementos de Facilitación Genéticos , Regulación del Desarrollo de la Expresión Génica , Neurogénesis/genética , Neuronas/metabolismo , Organoides/metabolismo , Secuencias Reguladoras de Ácidos Nucleicos , Regiones Promotoras Genéticas , Elementos Reguladores de la TranscripciónRESUMEN
Neuropsychiatric genome-wide association studies (GWASs), including those for autism spectrum disorder and schizophrenia, show strong enrichment for regulatory elements in the developing brain. However, prioritizing risk genes and mechanisms is challenging without a unified regulatory atlas. Across 672 diverse developing human brains, we identified 15,752 genes harboring gene, isoform, and/or splicing quantitative trait loci, mapping 3739 to cellular contexts. Gene expression heritability drops during development, likely reflecting both increasing cellular heterogeneity and the intrinsic properties of neuronal maturation. Isoform-level regulation, particularly in the second trimester, mediated the largest proportion of GWAS heritability. Through colocalization, we prioritized mechanisms for about 60% of GWAS loci across five disorders, exceeding adult brain findings. Finally, we contextualized results within gene and isoform coexpression networks, revealing the comprehensive landscape of transcriptome regulation in development and disease.
Asunto(s)
Empalme Alternativo , Encéfalo , Regulación del Desarrollo de la Expresión Génica , Trastornos Mentales , Humanos , Atlas como Asunto , Trastorno del Espectro Autista/genética , Encéfalo/metabolismo , Encéfalo/crecimiento & desarrollo , Encéfalo/embriología , Redes Reguladoras de Genes , Estudio de Asociación del Genoma Completo , Isoformas de Proteínas/genética , Isoformas de Proteínas/metabolismo , Sitios de Carácter Cuantitativo , Esquizofrenia/genética , Transcriptoma , Trastornos Mentales/genéticaRESUMEN
Human accelerated regions (HARs) are conserved genomic loci that evolved at an accelerated rate in the human lineage and may underlie human-specific traits. We generated HARs and chimpanzee accelerated regions with an automated pipeline and an alignment of 241 mammalian genomes. Combining deep learning with chromatin capture experiments in human and chimpanzee neural progenitor cells, we discovered a significant enrichment of HARs in topologically associating domains containing human-specific genomic variants that change three-dimensional (3D) genome organization. Differential gene expression between humans and chimpanzees at these loci suggests rewiring of regulatory interactions between HARs and neurodevelopmental genes. Thus, comparative genomics together with models of 3D genome folding revealed enhancer hijacking as an explanation for the rapid evolution of HARs.
Asunto(s)
Sitios Genéticos , Neurogénesis , Animales , Humanos , Cromatina/genética , Genoma Humano , Genómica , Pan troglodytes/genética , Neurogénesis/genética , Aprendizaje ProfundoRESUMEN
Genomic regulatory elements active in the developing human brain are notably enriched in genetic risk for neuropsychiatric disorders, including autism spectrum disorder (ASD), schizophrenia, and bipolar disorder. However, prioritizing the specific risk genes and candidate molecular mechanisms underlying these genetic enrichments has been hindered by the lack of a single unified large-scale gene regulatory atlas of human brain development. Here, we uniformly process and systematically characterize gene, isoform, and splicing quantitative trait loci (xQTLs) in 672 fetal brain samples from unique subjects across multiple ancestral populations. We identify 15,752 genes harboring a significant xQTL and map 3,739 eQTLs to a specific cellular context. We observe a striking drop in gene expression and splicing heritability as the human brain develops. Isoform-level regulation, particularly in the second trimester, mediates the greatest proportion of heritability across multiple psychiatric GWAS, compared with eQTLs. Via colocalization and TWAS, we prioritize biological mechanisms for ~60% of GWAS loci across five neuropsychiatric disorders, nearly two-fold that observed in the adult brain. Finally, we build a comprehensive set of developmentally regulated gene and isoform co-expression networks capturing unique genetic enrichments across disorders. Together, this work provides a comprehensive view of genetic regulation across human brain development as well as the stage-and cell type-informed mechanistic underpinnings of neuropsychiatric disorders.
RESUMEN
Nucleotide changes in gene regulatory elements are important determinants of neuronal development and disease. Using massively parallel reporter assays in primary human cells from mid-gestation cortex and cerebral organoids, we interrogated the cis-regulatory activity of 102,767 sequences, including differentially accessible cell-type specific regions in the developing cortex and single-nucleotide variants associated with psychiatric disorders. In primary cells, we identified 46,802 active enhancer sequences and 164 disorder-associated variants that significantly alter enhancer activity. Activity was comparable in organoids and primary cells, suggesting that organoids provide an adequate model for the developing cortex. Using deep learning, we decoded the sequence basis and upstream regulators of enhancer activity. This work establishes a comprehensive catalog of functional gene regulatory elements and variants in human neuronal development.
RESUMEN
Chronic inflammation and tissue fibrosis are common stress responses that worsen organ function, yet the molecular mechanisms governing their crosstalk are poorly understood. In diseased organs, stress-induced changes in gene expression fuel maladaptive cell state transitions and pathological interaction between diverse cellular compartments. Although chronic fibroblast activation worsens dysfunction of lung, liver, kidney, and heart, and exacerbates many cancers, the stress-sensing mechanisms initiating the transcriptional activation of fibroblasts are not well understood. Here, we show that conditional deletion of the transcription co-activator Brd4 in Cx3cr1-positive myeloid cells ameliorates heart failure and is associated with a dramatic reduction in fibroblast activation. Analysis of single-cell chromatin accessibility and BRD4 occupancy in vivo in Cx3cr1-positive cells identified a large enhancer proximal to Interleukin-1 beta (Il1b), and a series of CRISPR deletions revealed the precise stress-dependent regulatory element that controlled expression of Il1b in disease. Secreted IL1B functioned non-cell autonomously to activate a p65/RELA-dependent enhancer near the transcription factor MEOX1, resulting in a profibrotic response in human cardiac fibroblasts. In vivo, antibody-mediated IL1B neutralization prevented stress-induced expression of MEOX1, inhibited fibroblast activation, and improved cardiac function in heart failure. The elucidation of BRD4-dependent crosstalk between a specific immune cell subset and fibroblasts through IL1B provides new therapeutic strategies for heart disease and other disorders of chronic inflammation and maladaptive tissue remodeling.
RESUMEN
Motivation: Unsupervised clustering of single-cell transcriptomics is a powerful method for identifying cell populations. Static visualization techniques for single-cell clustering only display results for a single resolution parameter. Analysts will often evaluate more than one resolution parameter but then only report one. Results: We developed Cell Layers, an interactive Sankey tool for the quantitative investigation of gene expression, co-expression, biological processes and cluster integrity across clustering resolutions. Cell Layers enhances the interpretability of single-cell clustering by linking molecular data and cluster evaluation metrics, providing novel insight into cell populations. Availability and implementation: https://github.com/apblair/CellLayers.
RESUMEN
SUMMARY: CellWalkR is an R package that integrates single-cell open chromatin data with cell type labels and bulk epigenetic data to identify cell type-specific regulatory regions. A Graphics Processing Unit (GPU) implementation and downsampling strategies enable thousands of cells to be processed in seconds. CellWalkR's user-friendly interface provides interactive analysis and visualization of cell labels and regulatory region mappings. AVAILABILITY AND IMPLEMENTATION: CellWalkR is freely available as an R package under a GNU GPL-2.0 License and can be accessed from https://github.com/PFPrzytycki/CellWalkR with an accompanying vignette. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Asunto(s)
Secuencias Reguladoras de Ácidos Nucleicos , Programas Informáticos , Interpretación Estadística de DatosRESUMEN
During mammalian development, differences in chromatin state coincide with cellular differentiation and reflect changes in the gene regulatory landscape1. In the developing brain, cell fate specification and topographic identity are important for defining cell identity2 and confer selective vulnerabilities to neurodevelopmental disorders3. Here, to identify cell-type-specific chromatin accessibility patterns in the developing human brain, we used a single-cell assay for transposase accessibility by sequencing (scATAC-seq) in primary tissue samples from the human forebrain. We applied unbiased analyses to identify genomic loci that undergo extensive cell-type- and brain-region-specific changes in accessibility during neurogenesis, and an integrative analysis to predict cell-type-specific candidate regulatory elements. We found that cerebral organoids recapitulate most putative cell-type-specific enhancer accessibility patterns but lack many cell-type-specific open chromatin regions that are found in vivo. Systematic comparison of chromatin accessibility across brain regions revealed unexpected diversity among neural progenitor cells in the cerebral cortex and implicated retinoic acid signalling in the specification of neuronal lineage identity in the prefrontal cortex. Together, our results reveal the important contribution of chromatin state to the emerging patterns of cell type diversity and cell fate specification and provide a blueprint for evaluating the fidelity and robustness of cerebral organoids as a model for cortical development.
Asunto(s)
Encéfalo/citología , Epigenómica , Neurogénesis , Análisis de la Célula Individual , Atlas como Asunto , Encéfalo/crecimiento & desarrollo , Encéfalo/metabolismo , Cromatina/química , Cromatina/genética , Cromatina/metabolismo , Susceptibilidad a Enfermedades , Elementos de Facilitación Genéticos , Humanos , Neuronas/citología , Neuronas/metabolismo , Organoides/citología , Tretinoina/metabolismoRESUMEN
In diseased organs, stress-activated signalling cascades alter chromatin, thereby triggering maladaptive cell state transitions. Fibroblast activation is a common stress response in tissues that worsens lung, liver, kidney and heart disease, yet its mechanistic basis remains unclear1,2. Pharmacological inhibition of bromodomain and extra-terminal domain (BET) proteins alleviates cardiac dysfunction3-7, providing a tool to interrogate and modulate cardiac cell states as a potential therapeutic approach. Here we use single-cell epigenomic analyses of hearts dynamically exposed to BET inhibitors to reveal a reversible transcriptional switch that underlies the activation of fibroblasts. Resident cardiac fibroblasts demonstrated robust toggling between the quiescent and activated state in a manner directly correlating with BET inhibitor exposure and cardiac function. Single-cell chromatin accessibility revealed previously undescribed DNA elements, the accessibility of which dynamically correlated with cardiac performance. Among the most dynamic elements was an enhancer that regulated the transcription factor MEOX1, which was specifically expressed in activated fibroblasts, occupied putative regulatory elements of a broad fibrotic gene program and was required for TGFß-induced fibroblast activation. Selective CRISPR inhibition of the single most dynamic cis-element within the enhancer blocked TGFß-induced Meox1 activation. We identify MEOX1 as a central regulator of fibroblast activation associated with cardiac dysfunction and demonstrate its upregulation after activation of human lung, liver and kidney fibroblasts. The plasticity and specificity of BET-dependent regulation of MEOX1 in tissue fibroblasts provide previously unknown trans- and cis-targets for treating fibrotic disease.
Asunto(s)
Elementos de Facilitación Genéticos , Fibroblastos/citología , Cardiopatías/genética , Proteínas de Homeodominio/metabolismo , Factores de Transcripción/metabolismo , Animales , Cromatina/metabolismo , Epigenómica , Regulación de la Expresión Génica , Humanos , Ratones , Proteínas/antagonistas & inhibidores , Análisis de la Célula Individual , Transcriptoma , Factor de Crecimiento Transformador beta/metabolismoRESUMEN
Single-cell and bulk genomics assays have complementary strengths and weaknesses, and alone neither strategy can fully capture regulatory elements across the diversity of cells in complex tissues. We present CellWalker, a method that integrates single-cell open chromatin (scATAC-seq) data with gene expression (RNA-seq) and other data types using a network model that simultaneously improves cell labeling in noisy scATAC-seq and annotates cell type-specific regulatory elements in bulk data. We demonstrate CellWalker's robustness to sparse annotations and noise using simulations and combined RNA-seq and ATAC-seq in individual cells. We then apply CellWalker to the developing brain. We identify cells transitioning between transcriptional states, resolve regulatory elements to cell types, and observe that autism and other neurological traits can be mapped to specific cell types through their regulatory elements.
Asunto(s)
Biología Computacional/métodos , Regulación de la Expresión Génica , Secuencias Reguladoras de Ácidos Nucleicos , Análisis de la Célula Individual , Programas Informáticos , Secuenciación de Inmunoprecipitación de Cromatina/métodos , Sitios Genéticos , Anotación de Secuencia Molecular , Especificidad de Órganos/genética , Reproducibilidad de los Resultados , Análisis de la Célula Individual/métodosRESUMEN
To discover regulatory elements driving the specificity of gene expression in different cell types and regions of the developing human brain, we generated an atlas of open chromatin from nine dissected regions of the mid-gestation human telencephalon, as well as microdissected upper and deep layers of the prefrontal cortex. We identified a subset of open chromatin regions (OCRs), termed predicted regulatory elements (pREs), that are likely to function as developmental brain enhancers. pREs showed temporal, regional, and laminar differences in chromatin accessibility and were correlated with gene expression differences across regions and gestational ages. We identified two functional de novo variants in a pRE for autism risk gene SLC6A1, and using CRISPRa, demonstrated that this pRE regulates SCL6A1. Additionally, mouse transgenic experiments validated enhancer activity for pREs proximal to FEZF2 and BCL11A. Thus, this atlas serves as a resource for decoding neurodevelopmental gene regulation in health and disease.
Asunto(s)
Cromatina/genética , Cromatina/metabolismo , Elementos de Facilitación Genéticos , Regulación del Desarrollo de la Expresión Génica/genética , Corteza Prefrontal/embriología , Telencéfalo/embriología , Animales , Trastorno Autístico/genética , Línea Celular , Secuenciación de Inmunoprecipitación de Cromatina , Eucromatina/genética , Proteínas Transportadoras de GABA en la Membrana Plasmática/genética , Ontología de Genes , Predisposición Genética a la Enfermedad , Edad Gestacional , Humanos , Ratones , Ratones Transgénicos , Motivos de Nucleótidos , Mutación Puntual , Corteza Prefrontal/metabolismo , Proteínas Represoras/genética , Proteínas Represoras/metabolismo , Análisis Espacio-Temporal , Telencéfalo/metabolismo , Factores de Transcripción/genética , Factores de Transcripción/metabolismoRESUMEN
Identifying cancer-relevant mutations in noncoding regions is challenging due to the large numbers of such mutations, their low levels of recurrence, and difficulties in interpreting their functional impact. To uncover genes that are dysregulated due to somatic mutations in cis, we build upon the concept of differential allele-specific expression (ASE) and introduce methods to identify genes within an individual's cancer whose ASE differs from what is found in matched normal tissue. When applied to breast cancer tumor samples, our methods detect the known allele-specific effects of copy number variation and nonsense-mediated decay. Further, genes that are found to recurrently exhibit differential ASE across samples are cancer relevant. Genes with cis mutations are enriched for differential ASE, and we find 147 potentially functional noncoding mutations cis to genes that exhibit significant differential ASE. We conclude that differential ASE is a promising means for discovering gene dysregulation due to cis noncoding mutations.
Asunto(s)
Neoplasias de la Mama/genética , Perfilación de la Expresión Génica/métodos , Secuenciación Completa del Genoma/métodos , Alelos , Femenino , Humanos , MutaciónRESUMEN
Due to an error introduced during copyediting of this article [1], reference [8] incorrectly reads.
RESUMEN
A major aim of cancer genomics is to pinpoint which somatically mutated genes are involved in tumor initiation and progression. We introduce a new framework for uncovering cancer genes, differential mutation analysis, which compares the mutational profiles of genes across cancer genomes with their natural germline variation across healthy individuals. We present DiffMut, a fast and simple approach for differential mutational analysis, and demonstrate that it is more effective in discovering cancer genes than considerably more sophisticated approaches. We conclude that germline variation across healthy human genomes provides a powerful means for characterizing somatic mutation frequency and identifying cancer driver genes. DiffMut is available at https://github.com/Singh-Lab/Differential-Mutation-Analysis .
Asunto(s)
Análisis Mutacional de ADN/métodos , Genes Relacionados con las Neoplasias , Mutación de Línea Germinal , Mutación , Neoplasias/genética , Exoma , Femenino , Predisposición Genética a la Enfermedad , Genómica/métodos , Humanos , Masculino , Polimorfismo Genético , Programas InformáticosRESUMEN
SUMMARY: SimBoolNet is an open source Cytoscape plugin that simulates the dynamics of signaling transduction using Boolean networks. Given a user-specified level of stimulation to signal receptors, SimBoolNet simulates the response of downstream molecules and visualizes with animation and records the dynamic changes of the network. It can be used to generate hypotheses and facilitate experimental studies about causal relations and crosstalk among cellular signaling pathways. AVAILABILITY: SimBoolNet package (with manual) is freely available at http://www.ncbi.nlm.nih.gov/CBBresearch/Przytycka/SimBoolNet
Asunto(s)
Algoritmos , Simulación por Computador , Modelos Biológicos , Modelos Estadísticos , Proteoma/metabolismo , Transducción de Señal/fisiología , Programas InformáticosRESUMEN
BACKGROUND: Cellular response to external stimuli requires propagation of corresponding signals through molecular signaling pathways. However, signaling pathways are not isolated information highways, but rather interact in a number of ways forming sophisticated signaling networks. Since defects in signaling pathways are associated with many serious diseases, understanding of the crosstalk between them is fundamental for designing molecularly targeted therapy. Unfortunately, we still lack technology that would allow high throughput detailed measurement of activity of individual signaling molecules and their interactions. This necessitates developing methods to prioritize selection of the molecules such that measuring their activity would be most informative for understanding the crosstalk. Furthermore, absence of the reaction coefficients necessary for detailed modeling of signal propagation raises the question whether simple parameter-free models could provide useful information about such pathways. RESULTS: We study the combined signaling network of three major pro-survival signaling pathways: Epidermal Growth Factor Receptor (EGFR), Insulin-like Growth Factor-1 Receptor (IGF-1R), and Insulin Receptor (IR). Our study involves static analysis and dynamic modeling of this network, as well as an experimental verification of the model by measuring the response of selected signaling molecules to differential stimulation of EGF, IGF and insulin receptors. We introduced two novel measures of the importance of a node in the context of such crosstalk. Based on these measures several molecules, namely Erk1/2, Akt1, Jnk, p70S6K, were selected for monitoring in the network simulation and for experimental studies. Our simulation method relies on the Boolean network model combined with stochastic propagation of the signal. Most (although not all) trends suggested by the simulations have been confirmed by experiments. CONCLUSION: The simple model implemented in this paper provides a valuable first step in modeling signaling networks. However, to obtain a fully predictive model, a more detailed knowledge regarding parameters of individual interactions might be necessary.