RESUMEN
The diversity of cell types and regulatory states in the brain, and how these change during aging, remains largely unknown. We present a single-cell transcriptome atlas of the entire adult Drosophila melanogaster brain sampled across its lifespan. Cell clustering identified 87 initial cell clusters that are further subclustered and validated by targeted cell-sorting. Our data show high granularity and identify a wide range of cell types. Gene network analyses using SCENIC revealed regulatory heterogeneity linked to energy consumption. During aging, RNA content declines exponentially without affecting neuronal identity in old brains. This single-cell brain atlas covers nearly all cells in the normal brain and provides the tools to study cellular diversity alongside other Drosophila and mammalian single-cell datasets in our unique single-cell analysis platform: SCope (http://scope.aertslab.org). These results, together with SCope, allow comprehensive exploration of all transcriptional states of an entire aging brain.
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Envejecimiento , Encéfalo/metabolismo , Proteínas de Drosophila/genética , Drosophila melanogaster/genética , Redes Reguladoras de Genes , Análisis de la Célula Individual/métodos , Transcriptoma , Animales , Drosophila melanogaster/fisiología , Femenino , Perfilación de la Expresión Génica , MasculinoRESUMEN
Many patients with advanced cancers achieve dramatic responses to a panoply of therapeutics yet retain minimal residual disease (MRD), which ultimately results in relapse. To gain insights into the biology of MRD, we applied single-cell RNA sequencing to malignant cells isolated from BRAF mutant patient-derived xenograft melanoma cohorts exposed to concurrent RAF/MEK-inhibition. We identified distinct drug-tolerant transcriptional states, varying combinations of which co-occurred within MRDs from PDXs and biopsies of patients on treatment. One of these exhibited a neural crest stem cell (NCSC) transcriptional program largely driven by the nuclear receptor RXRG. An RXR antagonist mitigated accumulation of NCSCs in MRD and delayed the development of resistance. These data identify NCSCs as key drivers of resistance and illustrate the therapeutic potential of MRD-directed therapy. They also highlight how gene regulatory network architecture reprogramming may be therapeutically exploited to limit cellular heterogeneity, a key driver of disease progression and therapy resistance.
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Regulación Neoplásica de la Expresión Génica/efectos de los fármacos , Melanoma/tratamiento farmacológico , Neoplasia Residual/tratamiento farmacológico , Células Madre Neoplásicas/efectos de los fármacos , Células-Madre Neurales/efectos de los fármacos , Inhibidores de Proteínas Quinasas/farmacología , Receptor gamma X Retinoide/antagonistas & inhibidores , Animales , Biomarcadores de Tumor , Resistencia a Antineoplásicos/efectos de los fármacos , Femenino , Humanos , MAP Quinasa Quinasa 1/antagonistas & inhibidores , MAP Quinasa Quinasa 1/genética , Masculino , Melanoma/metabolismo , Melanoma/patología , Ratones SCID , Mutación , Neoplasia Residual/metabolismo , Neoplasia Residual/patología , Células Madre Neoplásicas/metabolismo , Células Madre Neoplásicas/patología , Células-Madre Neurales/metabolismo , Células-Madre Neurales/patología , Proteínas Proto-Oncogénicas B-raf/antagonistas & inhibidores , Proteínas Proto-Oncogénicas B-raf/genética , Células Tumorales Cultivadas , Ensayos Antitumor por Modelo de XenoinjertoRESUMEN
Transcriptional enhancers act as docking stations for combinations of transcription factors and thereby regulate spatiotemporal activation of their target genes1. It has been a long-standing goal in the field to decode the regulatory logic of an enhancer and to understand the details of how spatiotemporal gene expression is encoded in an enhancer sequence. Here we show that deep learning models2-6, can be used to efficiently design synthetic, cell-type-specific enhancers, starting from random sequences, and that this optimization process allows detailed tracing of enhancer features at single-nucleotide resolution. We evaluate the function of fully synthetic enhancers to specifically target Kenyon cells or glial cells in the fruit fly brain using transgenic animals. We further exploit enhancer design to create 'dual-code' enhancers that target two cell types and minimal enhancers smaller than 50 base pairs that are fully functional. By examining the state space searches towards local optima, we characterize enhancer codes through the strength, combination and arrangement of transcription factor activator and transcription factor repressor motifs. Finally, we apply the same strategies to successfully design human enhancers, which adhere to enhancer rules similar to those of Drosophila enhancers. Enhancer design guided by deep learning leads to better understanding of how enhancers work and shows that their code can be exploited to manipulate cell states.
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Células , Aprendizaje Profundo , Drosophila melanogaster , Elementos de Facilitación Genéticos , Biología Sintética , Animales , Humanos , Animales Modificados Genéticamente/genética , Elementos de Facilitación Genéticos/genética , Regulación de la Expresión Génica , Factores de Transcripción/metabolismo , Células/clasificación , Células/metabolismo , Neuroglía/metabolismo , Encéfalo/citología , Drosophila melanogaster/citología , Drosophila melanogaster/genética , Proteínas Represoras/metabolismoRESUMEN
The Drosophila brain is a frequently used model in neuroscience. Single-cell transcriptome analysis1-6, three-dimensional morphological classification7 and electron microscopy mapping of the connectome8,9 have revealed an immense diversity of neuronal and glial cell types that underlie an array of functional and behavioural traits in the fly. The identities of these cell types are controlled by gene regulatory networks (GRNs), involving combinations of transcription factors that bind to genomic enhancers to regulate their target genes. Here, to characterize GRNs at the cell-type level in the fly brain, we profiled the chromatin accessibility of 240,919 single cells spanning 9 developmental timepoints and integrated these data with single-cell transcriptomes. We identify more than 95,000 regulatory regions that are used in different neuronal cell types, of which 70,000 are linked to developmental trajectories involving neurogenesis, reprogramming and maturation. For 40 cell types, uniquely accessible regions were associated with their expressed transcription factors and downstream target genes through a combination of motif discovery, network inference and deep learning, creating enhancer GRNs. The enhancer architectures revealed by DeepFlyBrain lead to a better understanding of neuronal regulatory diversity and can be used to design genetic driver lines for cell types at specific timepoints, facilitating their characterization and manipulation.
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Drosophila , Regulación de la Expresión Génica , Animales , Encéfalo/metabolismo , Drosophila/genética , Regulación del Desarrollo de la Expresión Génica , Redes Reguladoras de Genes/genética , Factores de Transcripción/metabolismoRESUMEN
Joint profiling of chromatin accessibility and gene expression in individual cells provides an opportunity to decipher enhancer-driven gene regulatory networks (GRNs). Here we present a method for the inference of enhancer-driven GRNs, called SCENIC+. SCENIC+ predicts genomic enhancers along with candidate upstream transcription factors (TFs) and links these enhancers to candidate target genes. To improve both recall and precision of TF identification, we curated and clustered a motif collection with more than 30,000 motifs. We benchmarked SCENIC+ on diverse datasets from different species, including human peripheral blood mononuclear cells, ENCODE cell lines, melanoma cell states and Drosophila retinal development. Next, we exploit SCENIC+ predictions to study conserved TFs, enhancers and GRNs between human and mouse cell types in the cerebral cortex. Finally, we use SCENIC+ to study the dynamics of gene regulation along differentiation trajectories and the effect of TF perturbations on cell state. SCENIC+ is available at scenicplus.readthedocs.io .
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Redes Reguladoras de Genes , Multiómica , Animales , Humanos , Ratones , Leucocitos Mononucleares , Regulación de la Expresión Génica , Cromatina/genética , Drosophila/genética , Elementos de Facilitación GenéticosRESUMEN
Here we describe the LifeTime Initiative, which aims to track, understand and target human cells during the onset and progression of complex diseases, and to analyse their response to therapy at single-cell resolution. This mission will be implemented through the development, integration and application of single-cell multi-omics and imaging, artificial intelligence and patient-derived experimental disease models during the progression from health to disease. The analysis of large molecular and clinical datasets will identify molecular mechanisms, create predictive computational models of disease progression, and reveal new drug targets and therapies. The timely detection and interception of disease embedded in an ethical and patient-centred vision will be achieved through interactions across academia, hospitals, patient associations, health data management systems and industry. The application of this strategy to key medical challenges in cancer, neurological and neuropsychiatric disorders, and infectious, chronic inflammatory and cardiovascular diseases at the single-cell level will usher in cell-based interceptive medicine in Europe over the next decade.
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Tratamiento Basado en Trasplante de Células y Tejidos , Atención a la Salud/métodos , Atención a la Salud/tendencias , Medicina/métodos , Medicina/tendencias , Patología , Análisis de la Célula Individual , Inteligencia Artificial , Atención a la Salud/ética , Atención a la Salud/normas , Diagnóstico Precoz , Educación Médica , Europa (Continente) , Femenino , Salud , Humanos , Legislación Médica , Masculino , Medicina/normasRESUMEN
Genomic sequence variation within enhancers and promoters can have a significant impact on the cellular state and phenotype. However, sifting through the millions of candidate variants in a personal genome or a cancer genome, to identify those that impact cis-regulatory function, remains a major challenge. Interpretation of noncoding genome variation benefits from explainable artificial intelligence to predict and interpret the impact of a mutation on gene regulation. Here we generate phased whole genomes with matched chromatin accessibility, histone modifications, and gene expression for 10 melanoma cell lines. We find that training a specialized deep learning model, called DeepMEL2, on melanoma chromatin accessibility data can capture the various regulatory programs of the melanocytic and mesenchymal-like melanoma cell states. This model outperforms motif-based variant scoring, as well as more generic deep learning models. We detect hundreds to thousands of allele-specific chromatin accessibility variants (ASCAVs) in each melanoma genome, of which 15%-20% can be explained by gains or losses of transcription factor binding sites. A considerable fraction of ASCAVs are caused by changes in AP-1 binding, as confirmed by matched ChIP-seq data to identify allele-specific binding of JUN and FOSL1. Finally, by augmenting the DeepMEL2 model with ChIP-seq data for GABPA, the TERT promoter mutation, as well as additional ETS motif gains, can be identified with high confidence. In conclusion, we present a new integrative genomics approach and a deep learning model to identify and interpret functional enhancer mutations with allelic imbalance of chromatin accessibility and gene expression.
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Cromatina , Aprendizaje Profundo , Alelos , Inteligencia Artificial , Cromatina/genética , Regiones Promotoras GenéticasRESUMEN
Deciphering the genomic regulatory code of enhancers is a key challenge in biology because this code underlies cellular identity. A better understanding of how enhancers work will improve the interpretation of noncoding genome variation and empower the generation of cell type-specific drivers for gene therapy. Here, we explore the combination of deep learning and cross-species chromatin accessibility profiling to build explainable enhancer models. We apply this strategy to decipher the enhancer code in melanoma, a relevant case study owing to the presence of distinct melanoma cell states. We trained and validated a deep learning model, called DeepMEL, using chromatin accessibility data of 26 melanoma samples across six different species. We show the accuracy of DeepMEL predictions on the CAGI5 challenge, where it significantly outperforms existing models on the melanoma enhancer of IRF4 Next, we exploit DeepMEL to analyze enhancer architectures and identify accurate transcription factor binding sites for the core regulatory complexes in the two different melanoma states, with distinct roles for each transcription factor, in terms of nucleosome displacement or enhancer activation. Finally, DeepMEL identifies orthologous enhancers across distantly related species, where sequence alignment fails, and the model highlights specific nucleotide substitutions that underlie enhancer turnover. DeepMEL can be used from the Kipoi database to predict and optimize candidate enhancers and to prioritize enhancer mutations. In addition, our computational strategy can be applied to other cancer or normal cell types.
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Biología Computacional/métodos , Melanoma/genética , Pez Cebra/genética , Animales , Aprendizaje Profundo , Perros , Elementos de Facilitación Genéticos , Regulación Neoplásica de la Expresión Génica , Caballos , Humanos , Ratones , PorcinosRESUMEN
Acute leukemias (ALs) of ambiguous lineage are a heterogeneous group of high-risk leukemias characterized by coexpression of myeloid and lymphoid markers. In this study, we identified a distinct subgroup of immature acute leukemias characterized by a broadly variable phenotype, covering acute myeloid leukemia (AML, M0 or M1), T/myeloid mixed-phenotype acute leukemia (T/M MPAL), and early T-cell precursor acute lymphoblastic leukemia (ETP-ALL). Rearrangements at 14q32/BCL11B are the cytogenetic hallmark of this entity. In our screening of 915 hematological malignancies, there were 202 AML and 333 T-cell acute lymphoblastic leukemias (T-ALL: 58, ETP; 178, non-ETP; 8, T/M MPAL; 89, not otherwise specified). We identified 20 cases of immature leukemias (4% of AML and 3.6% of T-ALL), harboring 4 types of 14q32/BCL11B translocations: t(2,14)(q22.3;q32) (n = 7), t(6;14)(q25.3;q32) (n = 9), t(7;14)(q21.2;q32) (n = 2), and t(8;14)(q24.2;q32) (n = 2). The t(2;14) produced a ZEB2-BCL11B fusion transcript, whereas the other 3 rearrangements displaced transcriptionally active enhancer sequences close to BCL11B without producing fusion genes. All translocations resulted in the activation of BCL11B, a regulator of T-cell differentiation associated with transcriptional corepressor complexes in mammalian cells. The expression of BCL11B behaved as a disease biomarker that was present at diagnosis, but not in remission. Deregulation of BCL11B co-occurred with variants at FLT3 and at epigenetic modulators, most frequently the DNMT3A, TET2, and/or WT1 genes. Transcriptome analysis identified a specific expression signature, with significant downregulation of BCL11B targets, and clearly separating BCL11B AL from AML, T-ALL, and ETP-ALL. Remarkably, an ex vivo drug-sensitivity profile identified a panel of compounds with effective antileukemic activity.
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Biomarcadores de Tumor , Cromosomas Humanos Par 14/genética , Regulación Leucémica de la Expresión Génica , Leucemia Mieloide Aguda , Leucemia-Linfoma Linfoblástico de Células T Precursoras , Proteínas Represoras , Translocación Genética , Proteínas Supresoras de Tumor , Adolescente , Adulto , Anciano , Biomarcadores de Tumor/biosíntesis , Biomarcadores de Tumor/genética , Niño , Preescolar , Femenino , Perfilación de la Expresión Génica , Humanos , Leucemia Mieloide Aguda/genética , Leucemia Mieloide Aguda/metabolismo , Leucemia Mieloide Aguda/patología , Masculino , Persona de Mediana Edad , Leucemia-Linfoma Linfoblástico de Células T Precursoras/genética , Leucemia-Linfoma Linfoblástico de Células T Precursoras/metabolismo , Leucemia-Linfoma Linfoblástico de Células T Precursoras/patología , Proteínas Represoras/biosíntesis , Proteínas Represoras/genética , Proteínas Supresoras de Tumor/biosíntesis , Proteínas Supresoras de Tumor/genéticaRESUMEN
We present cisTopic, a probabilistic framework used to simultaneously discover coaccessible enhancers and stable cell states from sparse single-cell epigenomics data ( http://github.com/aertslab/cistopic ). Using a compendium of single-cell ATAC-seq datasets from differentiating hematopoietic cells, brain and transcription factor perturbations, we demonstrate that topic modeling can be exploited for robust identification of cell types, enhancers and relevant transcription factors. cisTopic provides insight into the mechanisms underlying regulatory heterogeneity in cell populations.
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Epigenómica/métodos , Perfilación de la Expresión Génica/métodos , Modelos Teóricos , Análisis de la Célula Individual/métodos , Animales , Células Sanguíneas/metabolismo , Encéfalo/metabolismo , Células Cultivadas , Análisis por Conglomerados , Redes Reguladoras de Genes/genética , Humanos , Ratones , Secuencias Reguladoras de Ácidos Nucleicos/genética , Análisis de Secuencia de ARN , Flujo de TrabajoRESUMEN
Focal amplifications of chromosome 3p13-3p14 occur in about 10% of melanomas and are associated with a poor prognosis. The melanoma-specific oncogene MITF resides at the epicentre of this amplicon. However, whether other loci present in this amplicon also contribute to melanomagenesis is unknown. Here we show that the recently annotated long non-coding RNA (lncRNA) gene SAMMSON is consistently co-gained with MITF. In addition, SAMMSON is a target of the lineage-specific transcription factor SOX10 and its expression is detectable in more than 90% of human melanomas. Whereas exogenous SAMMSON increases the clonogenic potential in trans, SAMMSON knockdown drastically decreases the viability of melanoma cells irrespective of their transcriptional cell state and BRAF, NRAS or TP53 mutational status. Moreover, SAMMSON targeting sensitizes melanoma to MAPK-targeting therapeutics both in vitro and in patient-derived xenograft models. Mechanistically, SAMMSON interacts with p32, a master regulator of mitochondrial homeostasis and metabolism, to increase its mitochondrial targeting and pro-oncogenic function. Our results indicate that silencing of the lineage addiction oncogene SAMMSON disrupts vital mitochondrial functions in a cancer-cell-specific manner; this silencing is therefore expected to deliver highly effective and tissue-restricted anti-melanoma therapeutic responses.
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Melanoma/genética , Melanoma/patología , Oncogenes/genética , ARN Largo no Codificante/genética , Animales , Carcinogénesis/genética , Carcinogénesis/patología , Proteínas Portadoras , Linaje de la Célula , Proliferación Celular , Supervivencia Celular , Cromosomas Humanos Par 3/genética , Células Clonales/metabolismo , Células Clonales/patología , Femenino , Amplificación de Genes/genética , Técnicas de Silenciamiento del Gen , Humanos , Melanoma/terapia , Ratones , Factor de Transcripción Asociado a Microftalmía/genética , Mitocondrias/genética , Mitocondrias/metabolismo , Mitocondrias/patología , Proteínas Mitocondriales/metabolismo , Proteínas Quinasas Activadas por Mitógenos/antagonistas & inhibidores , Proteínas Quinasas Activadas por Mitógenos/metabolismo , Terapia Molecular Dirigida , ARN Largo no Codificante/uso terapéutico , Factores de Transcripción SOXE/metabolismo , Ensayos Antitumor por Modelo de XenoinjertoRESUMEN
In multipolar vertebrate neurons, action potentials (APs) initiate close to the soma, at the axonal initial segment. Invertebrate neurons are typically unipolar with dendrites integrating directly into the axon. Where APs are initiated in the axons of invertebrate neurons is unclear. Voltage-gated sodium (NaV) channels are a functional hallmark of the axonal initial segment in vertebrates. We used an intronic Minos-Mediated Integration Cassette to determine the endogenous gene expression and subcellular localization of the sole NaV channel in both male and female Drosophila, para Despite being the only NaV channel in the fly, we show that only 23 ± 1% of neurons in the embryonic and larval CNS express para, while in the adult CNS para is broadly expressed. We generated a single-cell transcriptomic atlas of the whole third instar larval brain to identify para expressing neurons and show that it positively correlates with markers of differentiated, actively firing neurons. Therefore, only 23 ± 1% of larval neurons may be capable of firing NaV-dependent APs. We then show that Para is enriched in an axonal segment, distal to the site of dendritic integration into the axon, which we named the distal axonal segment (DAS). The DAS is present in multiple neuron classes in both the third instar larval and adult CNS. Whole cell patch clamp electrophysiological recordings of adult CNS fly neurons are consistent with the interpretation that Nav-dependent APs originate in the DAS. Identification of the distal NaV localization in fly neurons will enable more accurate interpretation of electrophysiological recordings in invertebrates.SIGNIFICANCE STATEMENT The site of action potential (AP) initiation in invertebrates is unknown. We tagged the sole voltage-gated sodium (NaV) channel in the fly, para, and identified that Para is enriched at a distal axonal segment. The distal axonal segment is located distal to where dendrites impinge on axons and is the likely site of AP initiation. Understanding where APs are initiated improves our ability to model neuronal activity and our interpretation of electrophysiological data. Additionally, para is only expressed in 23 ± 1% of third instar larval neurons but is broadly expressed in adults. Single-cell RNA sequencing of the third instar larval brain shows that para expression correlates with the expression of active, differentiated neuronal markers. Therefore, only 23 ± 1% of third instar larval neurons may be able to actively fire NaV-dependent APs.
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Segmento Inicial del Axón/metabolismo , Proteínas de Drosophila/biosíntesis , Drosophila/metabolismo , Neuronas/metabolismo , Canales de Sodio/biosíntesis , Canales de Sodio Activados por Voltaje/biosíntesis , Potenciales de Acción/fisiología , Animales , Axones/fisiología , Dendritas/metabolismo , Proteínas de Drosophila/genética , Fenómenos Electrofisiológicos , Electrorretinografía , Expresión Génica/genética , Larva , Unión Neuromuscular/metabolismo , Unión Neuromuscular/fisiología , Técnicas de Placa-Clamp , Canales de Sodio/genética , Transcriptoma , Canales de Sodio Activados por Voltaje/genéticaRESUMEN
Upon gastrulation, the mammalian conceptus transforms rapidly from a simple bilayer into a multilayered embryo enveloped by its extra-embryonic membranes. Impaired development of the amnion, the innermost membrane, causes major malformations. To clarify the origin of the mouse amnion, we used single-cell labelling and clonal analysis. We identified four clone types with distinct clonal growth patterns in amniotic ectoderm. Two main types have progenitors in extreme proximal-anterior epiblast. Early descendants initiate and expand amniotic ectoderm posteriorly, while descendants of cells remaining anteriorly later expand amniotic ectoderm from its anterior side. Amniogenesis is abnormal in embryos deficient in the bone morphogenetic protein (BMP) signalling effector SMAD5, with delayed closure of the proamniotic canal, and aberrant amnion and folding morphogenesis. Transcriptomics of individual Smad5 mutant amnions isolated before visible malformations and tetraploid chimera analysis revealed two amnion defect sets. We attribute them to impairment of progenitors of the two main cell populations in amniotic ectoderm and to compromised cuboidal-to-squamous transition of anterior amniotic ectoderm. In both cases, SMAD5 is crucial for expanding amniotic ectoderm rapidly into a stretchable squamous sheet to accommodate exocoelom expansion, axial growth and folding morphogenesis.
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Amnios/embriología , Ectodermo/embriología , Morfogénesis/fisiología , Transducción de Señal/fisiología , Proteína Smad5/metabolismo , Células Madre/metabolismo , Amnios/citología , Animales , Ectodermo/citología , Ratones , Proteína Smad5/genética , Células Madre/citologíaRESUMEN
Single-cell technologies allow measuring chromatin accessibility and gene expression in each cell, but jointly utilizing both layers to map bona fide gene regulatory networks and enhancers remains challenging. Here, we generate independent single-cell RNA-seq and single-cell ATAC-seq atlases of the Drosophila eye-antennal disc and spatially integrate the data into a virtual latent space that mimics the organization of the 2D tissue using ScoMAP (Single-Cell Omics Mapping into spatial Axes using Pseudotime ordering). To validate spatially predicted enhancers, we use a large collection of enhancer-reporter lines and identify ~ 85% of enhancers in which chromatin accessibility and enhancer activity are coupled. Next, we infer enhancer-to-gene relationships in the virtual space, finding that genes are mostly regulated by multiple, often redundant, enhancers. Exploiting cell type-specific enhancers, we deconvolute cell type-specific effects of bulk-derived chromatin accessibility QTLs. Finally, we discover that Prospero drives neuronal differentiation through the binding of a GGG motif. In summary, we provide a comprehensive spatial characterization of gene regulation in a 2D tissue.
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Cromatina/metabolismo , Drosophila/genética , Elementos de Facilitación Genéticos , Perfilación de la Expresión Génica/métodos , Regulación de la Expresión Génica/genética , Análisis de la Célula Individual/métodos , Animales , Animales Modificados Genéticamente , Antenas de Artrópodos/metabolismo , Diferenciación Celular/genética , Cromatina/genética , Secuenciación de Inmunoprecipitación de Cromatina , Bases de Datos Genéticas , Drosophila/metabolismo , Proteínas de Drosophila/genética , Proteínas de Drosophila/metabolismo , Epigenómica , Ojo/crecimiento & desarrollo , Ojo/metabolismo , Ontología de Genes , Redes Reguladoras de Genes , Genómica , Inmunohistoquímica , Larva/genética , Larva/crecimiento & desarrollo , Larva/metabolismo , Proteínas del Tejido Nervioso/genética , Proteínas del Tejido Nervioso/metabolismo , Proteínas Nucleares/genética , Proteínas Nucleares/metabolismo , Células Fotorreceptoras/metabolismo , Regiones Promotoras Genéticas , Sitios de Carácter Cuantitativo , Análisis Espacio-Temporal , Factores de Transcripción/genética , Factores de Transcripción/metabolismo , Transcriptoma/genéticaRESUMEN
We present SCENIC, a computational method for simultaneous gene regulatory network reconstruction and cell-state identification from single-cell RNA-seq data (http://scenic.aertslab.org). On a compendium of single-cell data from tumors and brain, we demonstrate that cis-regulatory analysis can be exploited to guide the identification of transcription factors and cell states. SCENIC provides critical biological insights into the mechanisms driving cellular heterogeneity.
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Redes Reguladoras de Genes , Análisis de la Célula Individual , Algoritmos , Animales , Encéfalo/metabolismo , Análisis por Conglomerados , Perfilación de la Expresión Génica , Humanos , RatonesRESUMEN
SUMMARY: Inferring a Gene Regulatory Network (GRN) from gene expression data is a computationally expensive task, exacerbated by increasing data sizes due to advances in high-throughput gene profiling technology, such as single-cell RNA-seq. To equip researchers with a toolset to infer GRNs from large expression datasets, we propose GRNBoost2 and the Arboreto framework. GRNBoost2 is an efficient algorithm for regulatory network inference using gradient boosting, based on the GENIE3 architecture. Arboreto is a computational framework that scales up GRN inference algorithms complying with this architecture. Arboreto includes both GRNBoost2 and an improved implementation of GENIE3, as a user-friendly open source Python package. AVAILABILITY AND IMPLEMENTATION: Arboreto is available under the 3-Clause BSD license at http://arboreto.readthedocs.io. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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Algoritmos , Redes Reguladoras de Genes , Biología Computacional , Expresión Génica , Programas InformáticosRESUMEN
Transcription factors regulate their target genes by binding to regulatory regions in the genome. Although the binding preferences of TP53 are known, it remains unclear what distinguishes functional enhancers from nonfunctional binding. In addition, the genome is scattered with recognition sequences that remain unoccupied. Using two complementary techniques of multiplex enhancer-reporter assays, we discovered that functional enhancers could be discriminated from nonfunctional binding events by the occurrence of a single TP53 canonical motif. By combining machine learning with a meta-analysis of TP53 ChIP-seq data sets, we identified a core set of more than 1000 responsive enhancers in the human genome. This TP53 cistrome is invariably used between cell types and experimental conditions, whereas differences among experiments can be attributed to indirect nonfunctional binding events. Our data suggest that TP53 enhancers represent a class of unsophisticated cell-autonomous enhancers containing a single TP53 binding site, distinct from complex developmental enhancers that integrate signals from multiple transcription factors.
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Elementos de Facilitación Genéticos , Activación Transcripcional , Proteína p53 Supresora de Tumor/fisiología , Sitios de Unión , Bioensayo , Genes Reporteros , Humanos , Células MCF-7 , Unión ProteicaRESUMEN
Proper organ patterning depends on a tight coordination between cell proliferation and differentiation. The patterning of Drosophila retina occurs both very fast and with high precision. This process is driven by the dynamic changes in signaling activity of the conserved Hedgehog (Hh) pathway, which coordinates cell fate determination, cell cycle and tissue morphogenesis. Here we show that during Drosophila retinogenesis, the retinal determination gene dachshund (dac) is not only a target of the Hh signaling pathway, but is also a modulator of its activity. Using developmental genetics techniques, we demonstrate that dac enhances Hh signaling by promoting the accumulation of the Gli transcription factor Cubitus interruptus (Ci) parallel to or downstream of fused. In the absence of dac, all Hh-mediated events associated to the morphogenetic furrow are delayed. One of the consequences is that, posterior to the furrow, dac- cells cannot activate a Roadkill-Cullin3 negative feedback loop that attenuates Hh signaling and which is necessary for retinal cells to continue normal differentiation. Therefore, dac is part of an essential positive feedback loop in the Hh pathway, guaranteeing the speed and the accuracy of Drosophila retinogenesis.