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Title: Transcriptional analysis of the interaction between Botrytis cinerea and a host Arabidopsis thaliana using high-throughput data
Author: Cooke, Emma J.
ISNI:       0000 0004 2735 7368
Awarding Body: University of Warwick
Current Institution: University of Warwick
Date of Award: 2013
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Botrytis cinerea is an economically important necrotrophic pathogen which causes disease in hundreds of species of plants during pre- and post-harvest conditions. This thesis investigates the transcriptional responses of B. cinerea and the host Arabidopsis thaliana during the infection through the analysis of microarray and RNA-seq data sets. This work develops techniques for clustering time series expression profiles and identifying direct gene targets using microarray data; and techniques for identifying differentially expressed and differentially spliced genes using RNA-seq data. A clustering algorithm which uses Gaussian process regression to capture the time series structure of microarray data was developed and analysed. Features which are not considered by standard clustering algorithms were added, specifically the ability to include replicate data by using replicate information to inform a prior distribution for noise, and the ability to consider outlier values by using a mixture model likelihood. This algorithm is shown to produce more coherent and biologically meaningful clusters than standard algorithms when applied to publicly available time series data. This algorithm was also used to cluster A. thaliana transcription factors with similar expression profiles during B. cinerea infection. The transcription factors CAMTA3 and MYB108 are known to play a role in the A. thaliana defence response to B. cinerea. Mutant A. thaliana plants were generated which constitutively express the CAMTA3 gene, and these are shown to be more susceptible to B. cinerea infection than wild-type plants. Microarray data sets from mutant CAMTA3 and MYB108 A. thaliana plants were generated and used together with a time series data set of A. thaliana infected with B. cinerea to identify the most likely direct targets for these two transcription factors. Possible regulatory motifs to which these transcription factors bind were also identified. RNA-seq data sets of A. thaliana infected and mock-infected with B. cinerea at three key infection stages were generated. 2,081 novel splice junctions were identi fied for A. thaliana from the data. Differentially expressed genes for A. thaliana and B. cinerea were identified between the key infection stages using existing methods, however these methods are limited to pairwise testing. An improved method using generalised linear models was developed to enable the incorporation of both time and infection stage factors, which identified 12,940 A. thaliana genes differentially expressed due to B. cinerea infection. Different isoforms of A. thaliana genes were identified at a transcript level, at an event level and at a splice junction level. Generalised linear models were then used with the multinomial distribution, which considered both time and infection stage factors, to identify 928 A. thaliana genes which are likely to be differentially spliced due to B. cinerea infection.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: QK Botany ; SB Plant culture