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Landscape and significance of human super enhancer-driven core transcription regulatory circuitry

A core transcription regulatory circuitry (CRC) is an interconnected self-regulatory circuitry that is formed by a group of core transcription factors (TFs). These core TFs collectively regulate gene expression by binding not only to their own super enhancers (SEs) but also to the SEs of one another...

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Detalles Bibliográficos
Autores principales: Feng, Chenchen, Song, Chao, Jiang, Yong, Zhao, Jun, Zhang, Jian, Wang, Yuezhu, Yin, Mingxue, Zhu, Jiang, Ai, Bo, Wang, Qiuyu, Qian, Fengcui, Zhang, Yuexin, Shang, Desi, Liu, Jiaqi, Li, Chunquan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Society of Gene & Cell Therapy 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10149290/
https://www.ncbi.nlm.nih.gov/pubmed/37131406
http://dx.doi.org/10.1016/j.omtn.2023.03.014
Descripción
Sumario:A core transcription regulatory circuitry (CRC) is an interconnected self-regulatory circuitry that is formed by a group of core transcription factors (TFs). These core TFs collectively regulate gene expression by binding not only to their own super enhancers (SEs) but also to the SEs of one another. For most human tissue/cell types, a global view of CRCs and core TFs has not been generated. Here, we identified numerous CRCs using two identification methods and detailed the landscape of the CRCs driven by SEs in large cell/tissue samples. The comprehensive biological analyses, including sequence conservation, CRC activity and genome binding affinity were conducted for common TFs, moderate TFs, and specific TFs, which exhibit different biological features. The local module located from the common CRC network highlighted the essential functions and prognostic performance. The tissue-specific CRC network was highly related to cell identity. Core TFs in tissue-specific CRC networks exhibited disease markers, and had regulatory potential for cancer immunotherapy. Moreover, a user-friendly resource named CRCdb (http://www.licpathway.net/crcdb/index.html) was developed, which contained the detailed information of CRCs and core TFs used in this study, as well as other interesting results, such as the most representative CRC, frequency of TFs, and indegree/outdegree of TFs.