Bioinformatics Tools for Modeling Transcription Factor Target Genes and Epigenetic Changes

Author(s):  
Ramana V. Davuluri
Genomics ◽  
2017 ◽  
Vol 109 (2) ◽  
pp. 75-82 ◽  
Author(s):  
Mirana Ramialison ◽  
Ashley J. Waardenberg ◽  
Nicole Schonrock ◽  
Tram Doan ◽  
Danielle de Jong ◽  
...  

2014 ◽  
Vol 31 (6) ◽  
pp. 761-773 ◽  
Author(s):  
Emily Clough ◽  
Erin Jimenez ◽  
Yoo-Ah Kim ◽  
Cale Whitworth ◽  
Megan C. Neville ◽  
...  

FEBS Journal ◽  
2008 ◽  
Vol 275 (12) ◽  
pp. 3178-3192 ◽  
Author(s):  
Ralf Mrowka ◽  
Nils Blüthgen ◽  
Michael Fähling

Cancers ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 2823
Author(s):  
Ian M. Overton ◽  
Andrew H. Sims ◽  
Jeremy A. Owen ◽  
Bret S. E. Heale ◽  
Matthew J. Ford ◽  
...  

Cell identity is governed by gene expression, regulated by transcription factor (TF) binding at cis-regulatory modules. Decoding the relationship between TF binding patterns and gene regulation is nontrivial, remaining a fundamental limitation in understanding cell decision-making. We developed the NetNC software to predict functionally active regulation of TF targets; demonstrated on nine datasets for the TFs Snail, Twist, and modENCODE Highly Occupied Target (HOT) regions. Snail and Twist are canonical drivers of epithelial to mesenchymal transition (EMT), a cell programme important in development, tumour progression and fibrosis. Predicted “neutral” (non-functional) TF binding always accounted for the majority (50% to 95%) of candidate target genes from statistically significant peaks and HOT regions had higher functional binding than most of the Snail and Twist datasets examined. Our results illuminated conserved gene networks that control epithelial plasticity in development and disease. We identified new gene functions and network modules including crosstalk with notch signalling and regulation of chromatin organisation, evidencing networks that reshape Waddington’s epigenetic landscape during epithelial remodelling. Expression of orthologous functional TF targets discriminated breast cancer molecular subtypes and predicted novel tumour biology, with implications for precision medicine. Predicted invasion roles were validated using a tractable cell model, supporting our approach.


2010 ◽  
Vol 38 (Web Server) ◽  
pp. W233-W238 ◽  
Author(s):  
S. M. Kielbasa ◽  
N. Bluthgen ◽  
M. Fahling ◽  
R. Mrowka

2009 ◽  
Vol 23 (S1) ◽  
Author(s):  
Ralf Mrowka ◽  
Nils Blüthgen ◽  
Szymon Kielbasa ◽  
Pontus Börje Persson ◽  
Michael Fähling

2020 ◽  
Author(s):  
Zhiming Dai

AbstractKnockout analysis is a common tool to reveal transcription factor (TF) functions. However, such a reverse genetic analysis based on observed phenotype changes in mutant cell may lead to a misunderstanding of TF wild-type functions. Here, a model was proposed, in which the knockout-observed TF-target regulatory relationships might only occur in mutant cell, and they do not reflect TF normal functions in wild-type cell. Actually, the knockout of one TF might release another TF which is the protein-protein interaction partner of the deleted TF. The free TF could bind its new target genes and cause their significant expression changes. These seemingly TF knockout affected genes are thus not directly regulated by the deleted TF, but are gain-of-regulated genes of the latter TF in mutant cell. Based on this model, multiple sources of genome-wide data were used to identify 20 such TF pairs, and one pair was validated using other independent data. TF wild-type regulatory genes are not associated with their gain-of-regulated genes. My findings revealed TF-target relationships complicated by TF knockout analysis.


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