Arabidopsis Ensemble Reverse-Engineered Gene Regulatory Network Discloses Interconnected Transcription Factors in Oxidative Stress

Abstract

The abiotic stress response in plants is complex and tightly controlled by gene regulation. We present an abiotic stress gene regulatory network of 200,014 interactions for 11,938 target genes by integrating four complementary reverse-engineering solutions through average rank aggregation on an Arabidopsis thaliana microarray expression compendium. This ensemble performed the most robustly in benchmarking and greatly expands upon the availability of interactions currently reported. Besides recovering 1182 known regulatory interactions, cis-regulatory motifs and coherent functionalities of target genes corresponded with the predicted transcription factors. We provide a valuable resource of 572 abiotic stress modules of coregulated genes with functional and regulatory information, from which we deduced functional relationships for 1966 uncharacterized genes and many regulators. Using gain-and loss-of-function mutants of seven transcription factors grown under control and salt stress conditions, we experimentally validated 141 out of 271 predictions (52% precision) for 102 selected genes and mapped 148 additional transcription factor-gene regulatory interactions (49% recall). We identified an intricate core oxidative stress regulatory network where NAC13, NAC053, ERF6, WRKY6, and NAC032 transcription factors interconnect and function in detoxification. Our work shows that ensemble reverse-engineering can generate robust biological hypotheses of gene regulation in a multicellular eukaryote that can be tested by medium-throughput experimental validation.

Computational approaches to identify regulators of plant stress response using high-throughput gene expression data

“…Examples of these approaches are briefly described here. Vermeirssen et al [130] combined the Learning Module Networks algorithm [131] developed for yeast, Context Likelihood of Relatedness algorithm [132] tested on Escherichia coli, and Double Two-way t-tests algorithm tested on E. coli to identify oxidative stress regulatory transcription factors in A. thaliana (Type 3 output). The Algorithm for the Reconstruction of Gene Regulatory Networks (ARACNE) [58] was developed to infer transcriptional regulations in human B cells, but then used for other applications including the inference of transcriptional interactions underlying root development and physiological processes in A. thaliana [133] (Type 3 output).…”

Gene expression analysis of rocket salad under pre-harvest and postharvest stresses: A transcriptomic resource for Diplotaxis tenuifolia

“…The identification of overlapping sets of TFs activated will provide further scope for understanding the postharvest TF network that is emerging for senescence and abiotic stresses [50]. …”

The ETHYLENE RESPONSE FACTORs ERF6 and ERF11 Antagonistically Regulate Mannitol-Induced Growth Inhibition in Arabidopsis

“…The literature also contains many examples of studies, mainly biotic stress related, in which ERF6 and ERF11 were found among the differentially expressed genes, although the experiments were not conducted on growing leaves but rather on mature leaf tissue or complete seedlings (McGrath et al, 2005;AbuQamar et al, 2006;Dombrecht et al, 2007;Eulgem and Somssich, 2007;Libault et al, 2007;Ma and Bohnert, 2007;Hu et al, 2008;Moffat et al, 2012;Son et al, 2012;Meng et al, 2013;Vermeirssen et al, 2014). In brief, ethylene and the described ERFs are generally induced in response to necrotrophic pathogens such as Botrytis cinerea and control the expression of the plant defensive proteins PDF1.1 and PDF1.2.…”

“…These contain an N-terminally located conserved stretch of acidic amino acids (called the 2nd Conserved Motif of group IX [CMIX-2]), which might function as a transcriptional activator domain. The transcriptional activators ERF5 and ERF6 additionally harbor a conserved C-terminal motif (CMIX-5) identified as a putative phosphorylation site by mitogen-activated protein kinases (MPKs), which distinguishes group IXa from group IXb (Fujimoto et al, 2000;Nakano et al, 2006).ERF6 is an activating transcription factor with documented roles in the response to various abiotic and biotic stress conditions, such as oxidative stress (Sewelam et al, 2013;Wang et al, 2013;Vermeirssen et al, 2014), high light (Vogel et al, 2014), cold (Lee et al, 2005;Xin et al, 2007), and biotic stress induced by biotrophic and necrotrophic pathogens (AbuQamar et al, 2006;Dombrecht et al, 2007;Hu et al, 2008;Moffat et al, 2012;Son et al, 2012;Meng et al, 2013). We have previously unraveled the molecular and biological function of ERF6 and its close homolog ERF5 in the mannitol-induced stress response, specifically in actively growing young Arabidopsis leaves (Dubois et al, 2013).…”