scholarly journals Predicting Evolution of the Transcription Regulatory Network in a Bacteriophage

2018 ◽  
Vol 10 (10) ◽  
pp. 2614-2628
Author(s):  
Daniel J Garry ◽  
Adam J Meyer ◽  
Jared W Ellefson ◽  
James J Bull ◽  
Andrew D Ellington
Keyword(s):  
Regulatory Network ◽  
Transcription Regulatory Network

HNF1, a homeoprotein member of the hepatic transcription regulatory network

BioEssays ◽  
1992 ◽  
Vol 14 (9) ◽  
pp. 579-587 ◽  
Author(s):  
Fran�lois Tronche ◽  
Moshe Yaniv
Keyword(s):  
Regulatory Network ◽  
Transcription Regulatory Network

Matrix and Steiner-triple-system smart pooling assays for high-performance transcription regulatory network mapping

2007 ◽  
Vol 4 (8) ◽  
pp. 659-664 ◽  
Author(s):  
Vanessa Vermeirssen ◽  
Bart Deplancke ◽  
M Inmaculada Barrasa ◽  
John S Reece-Hoyes ◽  
H Efsun Arda ◽  
...  
Keyword(s):  
Regulatory Network ◽  
Triple System ◽  
High Performance ◽  
Steiner Triple System ◽  
Transcription Regulatory Network ◽  
Network Mapping

scholarly journals Reconstructing the maize leaf regulatory network using ChIP-seq data of 104 transcription factors

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Xiaoyu Tu ◽  
María Katherine Mejía-Guerra ◽  
Jose A. Valdes Franco ◽  
David Tzeng ◽  
Po-Yu Chu ◽  
...  
Keyword(s):  
Transcription Factors ◽  
Regulatory Network ◽  
Large Scale ◽  
Eukaryotic Cell ◽  
Core Network ◽  
Binding Studies ◽  
Evolutionary Trajectory ◽  
Maize Leaf ◽  
Scale Free ◽  
Transcription Regulatory Network

Abstract The transcription regulatory network inside a eukaryotic cell is defined by the combinatorial actions of transcription factors (TFs). However, TF binding studies in plants are too few in number to produce a general picture of this complex network. In this study, we use large-scale ChIP-seq to reconstruct it in the maize leaf, and train machine-learning models to predict TF binding and co-localization. The resulting network covers 77% of the expressed genes, and shows a scale-free topology and functional modularity like a real-world network. TF binding sequence preferences are conserved within family, while co-binding could be key for their binding specificity. Cross-species comparison shows that core network nodes at the top of the transmission of information being more conserved than those at the bottom. This study reveals the complex and redundant nature of the plant transcription regulatory network, and sheds light on its architecture, organizing principle and evolutionary trajectory.

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