Publication
Meta Gene Regulatory Networks in Maize Highlight Functionally Relevant Regulatory Interactions
Publisher:
Oxford University Press (OUP)
Date:
17-03-2020
DOI:
10.1105/TPC.20.00080
Abstract: The regulation of gene expression is central to many biological processes. Gene regulatory networks (GRNs) link transcription factors (TFs) to their target genes and represent maps of potential transcriptional regulation. Here, we analyzed a large number of publically available maize (Zea mays) transcriptome data sets including & RNA sequencing s les to generate 45 coexpression-based GRNs that represent potential regulatory relationships between TFs and other genes in different populations of s les (cross-tissue, cross-genotype, and tissue-and-genotype s les). While these networks are all enriched for biologically relevant interactions, different networks capture distinct TF-target associations and biological processes. By examining the power of our coexpression-based GRNs to accurately predict covarying TF-target relationships in natural variation data sets, we found that presence/absence changes rather than quantitative changes in TF gene expression are more likely associated with changes in target gene expression. Integrating information from our TF-target predictions and previous expression quantitative trait loci (eQTL) mapping results provided support for 68 TFs underlying 74 previously identified trans-eQTL hotspots spanning a variety of metabolic pathways. This study highlights the utility of developing multiple GRNs within a species to detect putative regulators of important plant pathways and provides potential targets for breeding or biotechnological applications.