bioRxivPlant Biology
Shade-induced WRKY transcription factors restrict root growth during the shade avoidance response
D. Rosado, A. Ackermann, O. Spassibojko, M. Rossi, U. V. Pedmale
Abstract
Shade-intolerant plants rapidly elongate their stems, branches, and leaf stalks to compete with their neighboring vegetation to maximize sunlight capture for photosynthesis. This rapid growth adaptation, known as the shade avoidance response (SAR), comes at a cost; reduced biomass, crop yield, and root growth. Significant progress has been made on the mechanistic understanding of hypocotyl elongation during SAR; however, the molecular account of how root growth is repressed is not well understood. Here, we explore the mechanisms by which low red:far-red induced SAR restrict the primary and lateral root (LR) growth. By analyzing whole-genome transcriptome, we identified a core set of shade-induced genes in the roots of Arabidopsis and tomato seedlings grown in the shade. Abiotic and biotic stressors also induce many of these shade-induced genes and are predominantly regulated by the WRKY transcription factors. Correspondingly, a majority of the WRKYs were also among the shade-induced genes. Functional analysis using transgenics of these shade-induced WRKYs revealed their role is essentially to restrict primary root and LR growth in the shade, and captivatingly, they did not affect hypocotyl elongation. Similarly, we also show that ethylene hormone signaling is necessary to limit root growth in the shade. Our study proposes that during SAR, shade-induced WRKY26, 45, and 75, and ethylene reprogram gene expression in the root to restrict its growth and development. The reduced growth of root organs helps the plant divert its critical resources to the elongating organs in the shoot to ensure competitiveness under limiting photosynthetic radiation. One sentence summaryShade represses root growth by inducing WRKY transcription factors.
- organism: Arabidopsis
- assay: bulk RNA-seq
- research focus: gene regulatory network inference
- approach: statistical model
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