» Articles » PMID: 34761218

Taiji-reprogram: a Framework to Uncover Cell-type Specific Regulators and Predict Cellular Reprogramming Cocktails

Overview
Specialty Biology
Date 2021 Nov 11
PMID 34761218
Authors
Affiliations
Soon will be listed here.
Abstract

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.

References
1.
Zhou M, Yan J, Ma Z, Zhou Y, Abbood N, Liu J . Comparative and evolutionary analysis of the HES/HEY gene family reveal exon/intron loss and teleost specific duplication events. PLoS One. 2012; 7(7):e40649. PMC: 3396596. DOI: 10.1371/journal.pone.0040649. View

2.
Yu B, Zhang K, Milner J, Toma C, Chen R, Scott-Browne J . Erratum: Epigenetic landscapes reveal transcription factors that regulate CD8 T cell differentiation. Nat Immunol. 2017; 18(6):705. DOI: 10.1038/ni0617-705b. View

3.
Schacht T, Oswald M, Eils R, Eichmuller S, Konig R . Estimating the activity of transcription factors by the effect on their target genes. Bioinformatics. 2014; 30(17):i401-7. PMC: 4147899. DOI: 10.1093/bioinformatics/btu446. View

4.
Rackham O, Firas J, Fang H, Oates M, Holmes M, Knaupp A . A predictive computational framework for direct reprogramming between human cell types. Nat Genet. 2016; 48(3):331-5. DOI: 10.1038/ng.3487. View

5.
Betzenhauser M, Pitt G, Antzelevitch C . Calcium Channel Mutations in Cardiac Arrhythmia Syndromes. Curr Mol Pharmacol. 2015; 8(2):133-42. PMC: 4762596. DOI: 10.2174/1874467208666150518114857. View