A temporal hierarchy underpins the transcription factor–DNA interactome of the maize UPR

Citation

Kwan Ko et al. “A temporal hierarchy underpins the transcription factor-DNA interactome of the maize UPR” The Plant journal (2020) 105, 1 [DOI: 10.1111/tpj.15044]

Description

Adverse environmental conditions reduce crop productivity and often increase the load of unfolded or misfolded proteins in the endoplasmic reticulum (ER). This potentially lethal condition, known as ER stress, is buffered by the unfolded protein response (UPR), a set of signaling pathways designed to either recover ER functionality or ignite programmed cell death. Despite the biological significance of the UPR to the life of the organism, the regulatory transcriptional landscape underpinning ER stress management is largely unmapped, especially in crops. To fill this significant knowledge gap, we performed a large-scale systems-level analysis of the protein-DNA interaction (PDI) network in maize (Zea mays). Using 23 promoter fragments of six UPR marker genes in a high-throughput enhanced yeast one-hybrid assay, we identified a highly interconnected network of 262 transcription factors (TFs) associated with significant biological traits and 831 PDIs underlying the UPR. We established a temporal hierarchy of TF binding to gene promoters within the same family as well as across different families of TFs. Cistrome analysis revealed the dynamic activities of a variety of cis-regulatory elements (CREs) in ER stress-responsive gene promoters. By integrating the cistrome results into a TF network analysis, we mapped a subnetwork of TFs associated with a CRE that may contribute to UPR management. Finally, we validated the role of a predicted network hub gene using the Arabidopsis system. The PDIs, TF networks, and CREs identified in our work are foundational resources for understanding transcription-regulatory mechanisms in the stress responses and crop improvement.

Data Access

Data is available for download as tables in the Supplementary Information

Feedstocks
Genomics
Proteomics