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Time-series transcriptomics reveals that AGAMOUS-LIKE22 affects primary metabolism and developmental processes in drought-stressed arabidopsis

Bechtold, U and Penfold, CA and Jenkins, DJ and Legaie, R and Moore, JD and Lawson, T and Matthews, JSA and Vialet-Chabrand, SRM and Baxter, L and Subramaniam, S and Hickman, R and Florance, H and Sambles, C and Salmon, DL and Feil, R and Bowden, L and Hill, C and Baker, NR and Lunn, JE and Finkenstädt, B and Mead, A and Buchanan-Wollaston, V and Beynon, J and Rand, DA and Wild, DL and Denby, KJ and Ott, S and Smirnoff, N and Mullineaux, PM (2016) 'Time-series transcriptomics reveals that AGAMOUS-LIKE22 affects primary metabolism and developmental processes in drought-stressed arabidopsis.' Plant Cell, 28 (2). pp. 345-366. ISSN 1040-4651

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In Arabidopsis thaliana, changes in metabolism and gene expression drive increased drought tolerance and initiate diverse drought avoidance and escape responses. To address regulatory processes that link these responses, we set out to identify genes that govern early responses to drought. To do this, a high-resolution time series transcriptomics data set was produced, coupled with detailed physiological and metabolic analyses of plants subjected to a slow transition from well-watered to drought conditions. A total of 1815 drought-responsive differentially expressed genes were identified. The early changes in gene expression coincided with a drop in carbon assimilation, and only in the late stages with an increase in foliar abscisic acid content. To identify gene regulatory networks (GRNs) mediating the transition between the early and late stages of drought, we used Bayesian network modeling of differentially expressed transcription factor (TF) genes. This approach identified AGAMOUS-LIKE22 (AGL22), as key hub gene in a TF GRN. It has previously been shown that AGL22 is involved in the transition from vegetative state to flowering but here we show that AGL22 expression influences steady state photosynthetic rates and lifetime water use. This suggests that AGL22 uniquely regulates a transcriptional network during drought stress, linking changes in primary metabolism and the initiation of stress responses.

Item Type: Article
Uncontrolled Keywords: Arabidopsis; Abscisic Acid; Plant Growth Regulators; Arabidopsis Proteins; Transcription Factors; Cluster Analysis; Bayes Theorem; Photosynthesis; Gene Expression Regulation, Plant; Phenotype; Mutation; Gene Regulatory Networks; Stress, Physiological; Droughts
Subjects: Q Science > Q Science (General)
Q Science > QK Botany
Q Science > QP Physiology
Divisions: Faculty of Science and Health
Faculty of Science and Health > Life Sciences, School of
Faculty of Science and Health > Computer Science and Electronic Engineering, School of
SWORD Depositor: Elements
Depositing User: Elements
Date Deposited: 24 Feb 2016 16:52
Last Modified: 23 Sep 2022 18:26

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