Cell Fate Determination by Transcription Factors

2016 ◽  
pp. 445-454 ◽  
Author(s):  
John B. Gurdon
Keyword(s):  
Transcription Factors ◽  
Cell Fate ◽  
Cell Fate Determination ◽  
Fate Determination

scholarly journals FGF-induced Pea3 transcription factors program the genetic landscape for cell fate determination

PLoS Genetics ◽  
2018 ◽  
Vol 14 (9) ◽  
pp. e1007660 ◽  
Author(s):  
Ankur Garg ◽  
Abdul Hannan ◽  
Qian Wang ◽  
Tamica Collins ◽  
Siying Teng ◽  
...  
Keyword(s):  
Transcription Factors ◽  
Cell Fate ◽  
Cell Fate Determination ◽  
Fate Determination ◽  
Genetic Landscape

scholarly journals ANANSE: An enhancer network-based computational approach for predicting key transcription factors in cell fate determination

2020 ◽  
Author(s):  
Quan Xu ◽  
Georgios Georgiou ◽  
Gert Jan C. Veenstra ◽  
Huiqing Zhou ◽  
Simon J. van Heeringen
Keyword(s):  
Transcription Factors ◽  
Cell Fate ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Cell Types ◽  
Cell Fate Determination ◽  
Cell Type ◽  
Fate Determination ◽  
Cell Type Specific ◽  
Gene Regulatory

AbstractProper cell fate determination is largely orchestrated by complex gene regulatory networks centered around transcription factors. However, experimental elucidation of key transcription factors that drive cellular identity is currently often intractable. Here, we present ANANSE (ANalysis Algorithm for Networks Specified by Enhancers), a network-based method that exploits enhancer-encoded regulatory information to identify the key transcription factors in cell fate determination. As cell type-specific transcription factors predominantly bind to enhancers, we use regulatory networks based on enhancer properties to prioritize transcription factors. First, we predict genome-wide binding profiles of transcription factors in various cell types using enhancer activity and transcription factor binding motifs. Subsequently, applying these inferred binding profiles, we construct cell type-specific gene regulatory networks, and then predict key transcription factors controlling cell fate conversions using differential gene networks between cell types. This method outperforms existing approaches in correctly predicting major transcription factors previously identified to be sufficient for trans-differentiation. Finally, we apply ANANSE to define an atlas of key transcription factors in 18 normal human tissues. In conclusion, we present a ready-to-implement computational tool for efficient prediction of transcription factors in cell fate determination and to study transcription factor-mediated regulatory mechanisms. ANANSE is freely available at https://github.com/vanheeringen-lab/ANANSE.

Molecular Mechanisms Underlying the Regulation of Alternate Macrophage and Neutrophil Gene Programs by the Egr Transcription Factors

Blood ◽  
2008 ◽  
Vol 112 (11) ◽  
pp. 4773-4773
Author(s):  
Jason X Cheng ◽  
Peter Laslo ◽  
Chauncey Spooner ◽  
Eric Bertolino ◽  
Harinder Singh
Keyword(s):  
Transcription Factors ◽  
Cell Fate ◽  
Molecular Mechanisms ◽  
Target Genes ◽  
Gene Activity ◽  
Gene Promoters ◽  
Cell Fate Determination ◽  
Fate Determination ◽  
Gene Regulatory ◽  
Progenitor Cell Line

Abstract Cell fate determination in the hematopoietic system involves the onset and resolution of mixed lineage patterns of gene expression. Molecular mechanisms underlying the concerted activation and repression of alternate lineage genes remain to be elucidated. We have proposed a gene regulatory network for macrophage development in which the transcription factors PU.1 and the Egr’s function in a feed forward loop to activate macrophage genes. In the network, the Egr’s counteract the neutrophil regulator Gfi-1 and also repress alternate lineage genes. Using mutant alleles of Egr-1 and Egr-2 we validate the model and demonstrate that the Egr’s are required for initiating but not maintaining the repression of neutrophil genes during macrophage differentiation. Employing a PU.1−/− progenitor cell line we show that PU.1 transiently binds to and activates both macrophage and neutrophil gene promoters thereby leading to the onset of mixed lineage gene activity. While inducing macrophage cell fate determination, PU.1 remains persistently bound to macrophage gene promoters aided by the Egr’s. Surprisingly, the Egr’s displace PU.1 from neutrophil gene promoters by interacting with a co-repressor Nab-2 thereby repressing the alternate lineage program. We propose that the Egr’s have evolved to molecularly discriminate distinct sets of target genes and delineate divergent patterns of gene activity.

Sign in / Sign up

Export Citation Format

Share Document