Weed-induced changes in the maize root transcriptome reveal transcription factors and physiological processes impacted early in crop–weed interactions

Abstract

Abstract A new paradigm suggests weeds primarily reduce crop yield by altering crop developmental and physiological processes long before the weeds reduce resources through competition. Multiple studies have implicated stress response pathways are activated when crops such as maize are grown in close proximity with weeds during the first 4–8 weeks of growth—the point at which weeds have their greatest impact on subsequent crop yields. To date, these studies have mostly focused on the response of above-ground plant parts and have not examined the early signal transduction processes associated with maize root response to weeds. To investigate the impact of signals from a below-ground competitor on the maize root transcriptome when most vulnerable to weed pressure, a system was designed to expose maize to only below-ground signals. Gene set enrichment analyses identified over-represented ontologies associated with oxidative stress signalling throughout the time of weed exposure, with additional ontologies associated with nitrogen use and transport and abscisic acid (ABA) signalling, and defence responses being enriched at later time points. Enrichment of promoter motifs indicated over-representation of sequences known to bind FAR-RED IMPAIRED RESPONSE 1 (FAR1), several AP2/ERF transcription factors and others. Likewise, co-expression networks were identified using Weighted-Gene Correlation Network Analysis (WGCNA) and Spatiotemporal Clustering and Inference of Omics Networks (SC-ION) algorithms. WGCNA highlighted the potential roles of several transcription factors including a MYB 3r-4, TB1, WRKY65, CONSTANS-like5, ABF3, HOMEOBOX 12, among others. These studies also highlighted the role of several specific proteins involved in ABA signalling as being important for the initiation of the early response of maize to weeds. SC-ION highlighted potential roles for NAC28, LOB37, NAC58 and GATA2 transcription factors, among many others.