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Taiji-reprogram: a framework to uncover cell-type specific regulators and predict cellular reprogramming cocktails
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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8573821/ https://www.ncbi.nlm.nih.gov/pubmed/34761218 http://dx.doi.org/10.1093/nargab/lqab100 |
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author | Wang, Jun Liu, Cong Chen, Yue Wang, Wei |
author_facet | Wang, Jun Liu, Cong Chen, Yue Wang, Wei |
author_sort | Wang, Jun |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8573821 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-85738212021-11-09 Taiji-reprogram: a framework to uncover cell-type specific regulators and predict cellular reprogramming cocktails Wang, Jun Liu, Cong Chen, Yue Wang, Wei NAR Genom Bioinform Standard Article 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. Oxford University Press 2021-11-08 /pmc/articles/PMC8573821/ /pubmed/34761218 http://dx.doi.org/10.1093/nargab/lqab100 Text en © The Author(s) 2021. Published by Oxford University Press on behalf of NAR Genomics and Bioinformatics. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Standard Article Wang, Jun Liu, Cong Chen, Yue Wang, Wei Taiji-reprogram: a framework to uncover cell-type specific regulators and predict cellular reprogramming cocktails |
title | Taiji-reprogram: a framework to uncover cell-type specific regulators and predict cellular reprogramming cocktails |
title_full | Taiji-reprogram: a framework to uncover cell-type specific regulators and predict cellular reprogramming cocktails |
title_fullStr | Taiji-reprogram: a framework to uncover cell-type specific regulators and predict cellular reprogramming cocktails |
title_full_unstemmed | Taiji-reprogram: a framework to uncover cell-type specific regulators and predict cellular reprogramming cocktails |
title_short | Taiji-reprogram: a framework to uncover cell-type specific regulators and predict cellular reprogramming cocktails |
title_sort | taiji-reprogram: a framework to uncover cell-type specific regulators and predict cellular reprogramming cocktails |
topic | Standard Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8573821/ https://www.ncbi.nlm.nih.gov/pubmed/34761218 http://dx.doi.org/10.1093/nargab/lqab100 |
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