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Mus musculus

ABSTRACT: Reconstruction of the dynamic regulatory network that controls Th17 cell differentiation by systematic perturbation in primary cells (RNA-Seq)

OTHER RELATED OMICS DATASETS IN: MODEL2101150001

PROVIDER: PRJNA188243 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR654102_1.fastq.gz	Fastqsanger.gz
	SRR654102_2.fastq.gz	Fastqsanger.gz
	SRR654103_1.fastq.gz	Fastqsanger.gz
	SRR654103_2.fastq.gz	Fastqsanger.gz
	SRR654104_1.fastq.gz	Fastqsanger.gz

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Mus musculus

Project description:Reconstruction of the dynamic regulatory network that controls Th17 cell differentiation by systematic perturbation in primary cells (Th17 differentiation timecourse)

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Project description:Reconstruction of the dynamic regulatory network that controls Th17 cell differentiation by systematic perturbation in primary cells (ChIP-Seq)

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Reconstruction of the dynamic regulatory network that controls Th17 cell differentiation by systematic perturbation in primary cells (Th17 differentiation timecourse)

Project description:Despite their enormous importance, the molecular circuits that control the differentiation of Th17 cells remain largely unknown. Recent studies have reconstructed regulatory networks in mammalian cells, but have focused on short-term responses and relied on perturbation approaches that cannot be applied to primary T cells. Here, we develop a systematic strategy – combining transcriptional profiling at high temporal resolution, novel computational algorithms, and innovative nanowire-based tools for performing gene perturbations in primary T cells – to derive and experimentally validate a temporal model of the dynamic regulatory network that controls Th17 differentiation. The network is arranged into two self-reinforcing and mutually antagonistic modules that either suppress or promote Th17 differentiation. The two modules contain 12 novel regulators with no previous implication in Th17 differentiation, which may be essential to maintain the appropriate balance of Th17 and other CD4+ T cell subsets. Overall, our study identifies and validates 39 regulatory factors that are embedded within a comprehensive temporal network and identifies novel drug targets and organizational principles for the differentiation of Th17 cells. Time course microarray data for Th17 differentiation, including Th0 control

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Reconstruction of the dynamic regulatory network that controls Th17 cell differentiation by systematic perturbation in primary cells (ChIP-Seq)

Project description:Despite their enormous importance, the molecular circuits that control the differentiation of Th17 cells remain largely unknown. Recent studies have reconstructed regulatory networks in mammalian cells, but have focused on short-term responses and relied on perturbation approaches that cannot be applied to primary T cells. Here, we develop a systematic strategy – combining transcriptional profiling at high temporal resolution, novel computational algorithms, and innovative nanowire-based tools for performing gene perturbations in primary T cells – to derive and experimentally validate a temporal model of the dynamic regulatory network that controls Th17 differentiation. The network is arranged into two self-reinforcing and mutually antagonistic modules that either suppress or promote Th17 differentiation. The two modules contain 12 novel regulators with no previous implication in Th17 differentiation, which may be essential to maintain the appropriate balance of Th17 and other CD4+ T cell subsets. Overall, our study identifies and validates 39 regulatory factors that are embedded within a comprehensive temporal network and identifies novel drug targets and organizational principles for the differentiation of Th17 cells. DNA binding of TSC22D3 in Th17 cells compared to WCE

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Reconstruction of the dynamic regulatory network that controls Th17 cell differentiation by systematic perturbation in primary cells (RNA-Seq)

Project description:Despite their enormous importance, the molecular circuits that control the differentiation of Th17 cells remain largely unknown. Recent studies have reconstructed regulatory networks in mammalian cells, but have focused on short-term responses and relied on perturbation approaches that cannot be applied to primary T cells. Here, we develop a systematic strategy – combining transcriptional profiling at high temporal resolution, novel computational algorithms, and innovative nanowire-based tools for performing gene perturbations in primary T cells – to derive and experimentally validate a temporal model of the dynamic regulatory network that controls Th17 differentiation. The network is arranged into two self-reinforcing and mutually antagonistic modules that either suppress or promote Th17 differentiation. The two modules contain 12 novel regulators with no previous implication in Th17 differentiation, which may be essential to maintain the appropriate balance of Th17 and other CD4+ T cell subsets. Overall, our study identifies and validates 39 regulatory factors that are embedded within a comprehensive temporal network and identifies novel drug targets and organizational principles for the differentiation of Th17 cells. RNA-seq of knockdown of 12 genes in Th17 cell differentiation

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Reconstruction of the dynamic regulatory network that controls Th17 cell differentiation by systematic perturbation in primary cells (Affymetrix timecourse IL23 KO)

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