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

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 thos

SUBMITTER: Tu X 

PROVIDER: S-EPMC7547689 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature