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.
Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:700262 |
Date | January 2016 |
Creators | Subramaniam, Sunitha |
Publisher | University of Essex |
Source Sets | Ethos UK |
Detected Language | English |
Type | Electronic Thesis or Dissertation |
Source | http://repository.essex.ac.uk/17941/ |
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