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A single cell-based computational platform to identify chemical compounds targeting desired sets of transcription factors for cellular conversion [Bulk RNA-seq]

ABSTRACT: A single cell-based computational platform to identify chemical compounds targeting desired sets of transcription factors for cellular conversion [Bulk RNA-seq]

PROVIDER: PRJNA683798 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR13224359_1.fastq.gz	Fastqsanger.gz
	SRR13224359_2.fastq.gz	Fastqsanger.gz
	SRR13224360_1.fastq.gz	Fastqsanger.gz
	SRR13224360_2.fastq.gz	Fastqsanger.gz
	SRR13224361_1.fastq.gz	Fastqsanger.gz

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A single cell-based computational platform to identify chemical compounds targeting desired sets of transcription factors for cellular conversion [Single-cell RNA-seq]

Project description:Conversion of cellular identity can be achieved safely, without genetic manipulation, by inducing signalling perturbations with chemical compounds to target cell fate-governing transcription factors (TFs). However, chemical-induced cellular conversion currently requires large-scale screening of small compounds, which is time- and labour-intensive. There are no existing computational approaches that facilitate chemical conversion of cell fate. Here, we develop a computational framework (SiPer) to systematically predict chemical compounds specifically targeting desired sets of TFs to direct cellular conversion. This framework integrates a large compendium of chemical perturbation datasets with a network model. We show that SiPer is generally applicable to diverse cellular conversion examples, recapitulating the known chemical compounds and their corresponding protein targets. Furthermore, using chemical compounds predicted by SiPer, we develop a highly efficient protocol for the generation of functional human induced hepatocytes (hiHeps). These results demonstrate that SiPer provides a valuable resource to efficiently identify chemical compounds for cellular conversion.

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Project description:Cellular conversion can be induced by perturbing a handful of key transcription factors (TFs). Replacement of direct manipulation of key TFs with chemical compounds offers a less laborious and safer strategy to drive cellular conversion for regenerative medicine. Nevertheless, identifying optimal chemical compounds currently requires large-scale screening of chemical libraries, which is resource-intensive. Existing computational methods aim at predicting cell conversion TFs, however there are no methods for identifying chemical compounds targeting these TFs. Here, we develop a single cell-based platform (SiPer) to systematically prioritize chemical compounds targeting desired TFs to guide cellular conversions. SiPer integrates a large compendium of chemical perturbations on non-cancer cells with a network model, and predicted known and novel chemical compounds in diverse cell conversion examples. Importantly, we applied SiPer to develop a highly efficient protocol for human hepatic maturation. Overall, SiPer provides a valuable resource to efficiently identify chemical compounds for cell conversion.

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A single cell-based computational platform to identify chemical compounds targeting desired sets of transcription factors for cellular conversion

Project description:This SuperSeries is composed of the SubSeries listed below.

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