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Taiji-reprogram: a framework to uncover cell-type specific regulators and predict cellular reprogramming cocktails
Author(s) -
Jun Wang,
Cong Liu,
Yue Chen,
Wei Wang
Publication year - 2021
Publication title -
nar genomics and bioinformatics
Language(s) - English
Resource type - Journals
ISSN - 2631-9268
DOI - 10.1093/nargab/lqab100
Subject(s) - reprogramming , cell type , computational biology , biology , transcription factor , epigenomics , cell , gene regulatory network , systems biology , genetics , gene , gene expression , dna methylation
Cellular reprogramming is a promising technology to develop disease models and cell-based therapies. Identification of the key regulators defining the cell type specificity is pivotal to devising reprogramming cocktails for successful cell conversion but remains a great challenge. Here, we present a systems biology approach called Taiji-reprogram to efficiently uncover transcription factor (TF) combinations for conversion between 154 diverse cell types or tissues. This method integrates the transcriptomic and epigenomic data to construct cell-type specific genetic networks and assess the global importance of TFs in the network. Comparative analysis across cell types revealed TFs that are specifically important in a particular cell type and often tightly associated with cell-type specific functions. A systematic search of TFs with differential importance in the source and target cell types uncovered TF combinations for desired cell conversion. We have shown that Taiji-reprogram outperformed the existing methods to better recover the TFs in the experimentally validated reprogramming cocktails. This work not only provides a comprehensive catalog of TFs defining cell specialization but also suggests TF combinations for direct cell conversion.

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