GSE64410
Translatome analyses of opposing tissue-specific brassinosteroid signals orchestrating root meristem differentiation
The mechanisms ensuring balanced growth remain a critical question in developmental biology. In plants, this balance relies on spatiotemporal integration of hormonal signaling pathways, but the understanding of the precise contribution of each hormone is just beginning to take form. Brassinosteroid (BR) hormone, is shown here to have opposing effects on root meristem size, depending on its site of action. BR is demonstrated to both delay and promote onset of stem cell daughter differentiation, when acting in the outer tissue of the root meristem, the epidermis, and the inner-most tissue, the stele, respectively. To understand the molecular basis of this phenomenon, a comprehensive spatiotemporal translatome mapping of Arabidopsis roots was performed. Analyses of wild type and mutants featuring different distributions of BR, revealed autonomous, tissue-specific gene responses to BR, implying its contrasting tissue-dependent impact on growth. BR-induced genes were primarily detected in epidermal cells of the basal meristem zone and were enriched by auxin-related genes. In contrast, repressed BR genes prevailed in the stele of the apical meristem zone. Furthermore, auxin was found to mediate the growth-promoting impact of BR signaling originating in the epidermis, while BR signaling in the stele buffered this effect. We propose that context-specific BR activity and responses are oppositely interpreted at the organ level, ensuring coherent growth. Overall design: 24 samples of polyribosome-associated mRNA (following 0, 3, and 8 hours of BR treatment, in two biological repetitions), were collected. RNA samples were sequenced on an Illumina HiSeq 2500, to obtain 50 bp single-end reads. These reads were aligned to the TAIR10 assembly of the Arabidopsis thaliana genome, using Tophat2 v2.0.9. Transcript coordinates from the TAIR10 reference set were used to guide the alignment process. After alignment, the numbers of reads per transcript were estimated using HTSeq v0.5.3p3, and DESeq2 v1.2.8 was used to normalize read counts and call differentially expressed genes.