There is a growing need to engineer an increased yield in food crops coupled with greater resistance to environmental stresses, such as drought, to meet the requirement of a growing population. As plant responses to drought (and other abiotic stress) are complex, many studies have attempted to understand the drought response in a holistic manner, for example, by analysing transcriptomics data obtained from plants subjected to drought. Preliminary work of obtaining time-series microarray data from a slow-drying experiment of Arabidopsis was used to construct Gene Regulatory Networks using Variational Bayesian State Space Modelling. This led to the identification of a number of transcription factors RAP2.12, FD, BHLH038, ANL2, and two unknown genes, UKTF and POZ, as possibly being important regulatory genes in the drought response. Loss- and gain-of-function mutants of these genes, as well as those of AGL22 identified by Bechtold et al. (2016), were phenotyped under drought conditions. Only the flowering time AGL22 showed a drought phenotype. Network connections in the gene network of AGL22 were tested by qPCR. Drought responsive transcription factors, such as DREB1A and WRKY20 were found to be induced by AGL22.
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