Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1165215 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| Other | ||||
| SRR30795800.fastq.gz | Fastqsanger.gz | |||
| SRR30795801.fastq.gz | Fastqsanger.gz | |||
| SRR30795802.fastq.gz | Fastqsanger.gz | |||
| SRR30795803.fastq.gz | Fastqsanger.gz |
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Project description:The goal of this study was discover the transcription binding synthax for the key differentiation TFs in mouse embryonic stem cells. Genes are regulated through enhancer sequences, in which transcription factor binding motifs and their specific arrangements (syntax) form a cis-regulatory code. To understand the relationship between motif syntax and transcription factor binding, we train a deep learning model that uses DNA sequence to predict base-resolution binding profiles of four pluripotency transcription factors Oct4, Sox2, Nanog, and Klf4. We interpret the model to accurately map hundreds of thousands of motifs in the genome, learn novel motif representations and identify rules by which motifs and syntax influence transcription factor binding. We find that instances of strict motif spacing are largely due to retrotransposons, but that soft motif syntax influences motif interactions at protein and nucleosome range. Most strikingly, Nanog binding is driven by motifs with a strong preference for ~10.5 bp spacings corresponding to helical periodicity. Interpreting deep learning models applied to high-resolution binding data is a powerful and versatile approach to uncover the motifs and syntax of cis-regulatory sequences.
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Project description:Enhancer elements in the genome direct cell type-specific gene expression programs. In response to injury, cells undergo dynamic changes in gene expression that drive adaptation and initiate tissue repair. Here, we investigate how injury-induced gene expression programs are encoded within enhancer elements in the mammalian CNS. Leveraging single-nucleus transcriptomics and chromatin accessibility profiling, we identify thousands of injury-induced, cell type-specific enhancers in the mouse spinal cord. These enhancers are more abundant in glial cells and retain cell type specificity, even when regulating shared wound response genes. By modeling glial injury-responsive enhancers using deep learning, we reveal that their architecture encodes cell type specificity by integrating generic stimulus response elements with cell identity programs. Finally, through in vivo enhancer screening, we demonstrate that injury-responsive enhancers can selectively target reactive astrocytes bordering lesion sites across the CNS using therapeutically relevant gene delivery vectors. Our decoding of the principles of injury-responsive enhancers enables the design of sequences that can be programmed to therapeutically target disease related cell states.
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Project description:Enhancer elements in the genome direct cell type-specific gene expression programs. In response to injury, cells undergo dynamic changes in gene expression that drive adaptation and initiate tissue repair. Here, we investigate how injury-induced gene expression programs are encoded within enhancer elements in the mammalian CNS. Leveraging single-nucleus transcriptomics and chromatin accessibility profiling, we identify thousands of injury-induced, cell type-specific enhancers in the mouse spinal cord. These enhancers are more abundant in glial cells and retain cell type specificity, even when regulating shared wound response genes. By modeling glial injury-responsive enhancers using deep learning, we reveal that their architecture encodes cell type specificity by integrating generic stimulus response elements with cell identity programs. Finally, through in vivo enhancer screening, we demonstrate that injury-responsive enhancers can selectively target reactive astrocytes bordering lesion sites across the CNS using therapeutically relevant gene delivery vectors. Our decoding of the principles of injury-responsive enhancers enables the design of sequences that can be programmed to therapeutically target disease related cell states.
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Project description:Enhancer elements in the genome direct cell type-specific gene expression programs. In response to injury, cells undergo dynamic changes in gene expression that drive adaptation and initiate tissue repair. Here, we investigate how injury-induced gene expression programs are encoded within enhancer elements in the mammalian CNS. Leveraging single-nucleus transcriptomics and chromatin accessibility profiling, we identify thousands of injury-induced, cell type-specific enhancers in the mouse spinal cord. These enhancers are more abundant in glial cells and retain cell type specificity, even when regulating shared wound response genes. By modeling glial injury-responsive enhancers using deep learning, we reveal that their architecture encodes cell type specificity by integrating generic stimulus response elements with cell identity programs. Finally, through in vivo enhancer screening, we demonstrate that injury-responsive enhancers can selectively target reactive astrocytes bordering lesion sites across the CNS using therapeutically relevant gene delivery vectors. Our decoding of the principles of injury-responsive enhancers enables the design of sequences that can be programmed to therapeutically target disease related cell states.
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Project description:A human tissue map of 5-hydroxymethylcytosines exhibits tissue specificity through gene and enhancer modulation
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Project description:Accumulating evidence indicates that both putative promoters and enhancers can exert dual promoter and enhancer functions. However, how these activities are related within individual elements and what determines this dual functionality remain poorly understood. We developed a massively parallel dual reporter assay that enables simultaneous assessment of the intrinsic promoter and enhancer potential exerted by the same sequence. Parallel quantification for thousands of elements reveals that canonical human promoters and enhancers can act as both promoters and enhancers under the same contexts, and that promoter activity may be necessary but not sufficient for enhancer function. Perturbations to element transcription factor binding motifs lead to disruptions in both activities, implicating a shared syntax for the two regulatory functions. Combinations of elements with different minimal promoters reveal reciprocal activity modulation, which, together with a strong correlation between promoter and enhancer functions, imply a bidirectional feedback loop to sustain environments of high transcriptional activity. Finally, we validate this reciprocity and correlation in situ using CRISPR activation at the human β-globin locus. Our approach reveals that the functional convergence between promoters and enhancers arises from a shared regulatory logic and sequence syntax, advancing a unified model for regulatory element biology.
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Project description:Gene syntax---the order and arrangement of genes and their regulatory elements---shapes the dynamic coordination of both natural and synthetic gene circuits. Transcription at one locus profoundly impacts the transcription of nearby adjacent genes, but the molecular basis of this effect remains poorly understood. Here, using integrated reporter circuits in human cells, we show that the reciprocal effects of transcription and DNA supercoiling, which we term supercoiling-mediated feedback, regulates expression of adjacent genes in a syntax-specific manner. Using a suite of chromatin state assays, we measure syntax- and induction-dependent formation of chromatin structures in human induced pluripotent stem cells. Applying syntax as a design parameter and without altering sequence or copy number, we built compact gene circuits, tuning the expression mean, noise, and stoichiometry across diverse delivery methods and cell types. Integrating supercoiling-mediated feedback into models of gene regulation will expand our understanding of native systems and enhance the design of synthetic gene circuits.
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Project description:Gene syntax---the order and arrangement of genes and their regulatory elements---shapes the dynamic coordination of both natural and synthetic gene circuits. Transcription at one locus profoundly impacts the transcription of nearby adjacent genes, but the molecular basis of this effect remains poorly understood. Here, using integrated reporter circuits in human cells, we show that the reciprocal effects of transcription and DNA supercoiling, which we term supercoiling-mediated feedback, regulates expression of adjacent genes in a syntax-specific manner. Using a suite of chromatin state assays, we measure syntax- and induction-dependent formation of chromatin structures in human induced pluripotent stem cells. Applying syntax as a design parameter and without altering sequence or copy number, we built compact gene circuits, tuning the expression mean, noise, and stoichiometry across diverse delivery methods and cell types. Integrating supercoiling-mediated feedback into models of gene regulation will expand our understanding of native systems and enhance the design of synthetic gene circuits.
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Project description:The information about when and where each gene is to be expressed is mainly encoded in the DNA sequence of enhancers, sequence elements that comprise binding sites (motifs) for different transcription factors (TFs). Most of the research on enhancer sequences has been focused on TF motif presence, while the enhancer syntax, i.e. the flexibility of important motif positions and how the sequence context modulates the activity of TF motifs, remain poorly understood. Here, we explore the rules of enhancer syntax by a two-pronged approach in Drosophila melanogaster S2 cells: we (1) replace important motifs by an exhaustive set of all possible 65,536 eight-nucleotide-long random sequences and (2) paste eight important TF motif types into 763 motif positions within 496 enhancers. These complementary strategies reveal that enhancers display constrained sequence flexibility and the context-specific modulation of motif function. Important motifs can be functionally replaced by hundreds of sequences constituting several distinct motif types, but only a fraction of all possible sequences and motif types restore enhancer activity. Moreover, TF motifs contribute with different intrinsic strengths that are strongly modulated by the enhancer sequence context (the flanking sequence, presence and diversity of other motif types, and distance between motifs), such that not all motif types can work in all positions. Constrained sequence flexibility and the context-specific modulation of motif function are also hallmarks of human enhancers and TF motifs, as we demonstrate experimentally. Overall, these two general principles of enhancer sequences are important to understand and predict enhancer function during development, evolution and in disease.
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Project description:The information about when and where each gene is to be expressed is mainly encoded in the DNA sequence of enhancers, sequence elements that comprise binding sites (motifs) for different transcription factors (TFs). Most of the research on enhancer sequences has been focused on TF motif presence, while the enhancer syntax, i.e. the flexibility of important motif positions and how the sequence context modulates the activity of TF motifs, remain poorly understood. Here, we explore the rules of enhancer syntax by a two-pronged approach in Drosophila melanogaster S2 cells: we (1) replace important motifs by an exhaustive set of all possible 65,536 eight-nucleotide-long random sequences and (2) paste eight important TF motif types into 763 motif positions within 496 enhancers. These complementary strategies reveal that enhancers display constrained sequence flexibility and the context-specific modulation of motif function. Important motifs can be functionally replaced by hundreds of sequences constituting several distinct motif types, but only a fraction of all possible sequences and motif types restore enhancer activity. Moreover, TF motifs contribute with different intrinsic strengths that are strongly modulated by the enhancer sequence context (the flanking sequence, presence and diversity of other motif types, and distance between motifs), such that not all motif types can work in all positions. Constrained sequence flexibility and the context-specific modulation of motif function are also hallmarks of human enhancers and TF motifs, as we demonstrate experimentally. Overall, these two general principles of enhancer sequences are important to understand and predict enhancer function during development, evolution and in disease.
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