Dataset Information

Arabidopsis defense against Botrytis cinerea: chronology and regulation deciphered by high-resolution temporal transcriptomic analysis (tga3-2 knockout data)

ABSTRACT: Transcriptional reprogramming forms a major part of a plant's response to pathogen infection. Many individual components and pathways operating during plant defense have been identified but our knowledge of how these different components interact is still rudimentary. We have generated a high-resolution time series of gene expression profiles from a single Arabidopsis leaf during infection by the necrotrophic fungal pathogen, Botrytis cinerea. Approximately one-third of the Arabidopsis genome is differentially expressed during the first 48 hours after infection, with the majority of gene expression changes occurring before significant lesion development. We have used computational tools to obtain a detailed chronology of the defense response against B. cinerea, highlighting the times at which signaling and metabolic processes change, and identify transcription factor families operating at different times after infection. Motif enrichment and network inference predicted regulatory interactions and testing of one such prediction identified a novel role for TGA3 in defense against necrotrophic pathogens. These data provide an unprecedented level of detail about transcriptional change during a defense response and are suited to systems biology analyses to generate predictive models of the gene regulatory networks underlying the Arabidopsis response to B. cinerea.

ORGANISM(S): Arabidopsis thaliana

PROVIDER: GSE39597 | GEO | 2012/10/03

SECONDARY ACCESSION(S): PRJNA176553

REPOSITORIES: GEO

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Project description:Transcriptional reprogramming forms a major part of a plant's response to pathogen infection. Many individual components and pathways operating during plant defense have been identified but our knowledge of how these different components interact is still rudimentary. We have generated a high-resolution time series of gene expression profiles from a single Arabidopsis leaf during infection by the necrotrophic fungal pathogen, Botrytis cinerea. Approximately one-third of the Arabidopsis genome is differentially expressed during the first 48 hours after infection, with the majority of gene expression changes occurring before significant lesion development. We have used computational tools to obtain a detailed chronology of the defense response against B. cinerea, highlighting the times at which signaling and metabolic processes change, and identify transcription factor families operating at different times after infection. Motif enrichment and network inference predicted regulatory interactions and testing of one such prediction identified a novel role for TGA3 in defense against necrotrophic pathogens. These data provide an unprecedented level of detail about transcriptional change during a defense response and are suited to systems biology analyses to generate predictive models of the gene regulatory networks underlying the Arabidopsis response to B. cinerea. Samples were compared at three time points: 16, 24 and 32 hours post infection. Time points were chosen based on the expression profile of TGA3 in the high-resolution time series also presented in this paper. Samples were collected for three different conditions: tga3-2 mock inoculated, tga3-2 infected and Col-0 infected. Four individual leaves (biological replicates) from separate plants were collected for each treatment-time point totalling 36 samples. The four biological replicates for each treatment-time point were pooled. At each time point, the expression of the 4 pooled replicates was compared between tga3-2 mock inoculated vs. tga3-2 infected and tga3-2 infected vs. Col-0 infected using four technical replicates for each comparison which included balanced dye swaps.

Project description:Transcriptomic analysis in response to Botrytis cinerea infections under conrasting nitrate regime Nitrogen (N) is one of the main limiting nutrients for plant growth and crop yield. It is well documented that changes in nitrate availability, the main N source found in agricultural soils, influences a myriad of developmental programs and processes including the plant defense response. Indeed, many agronomical reports indicate that the plant N nutritional status influences their ability to respond effectively when challenged by different pathogens. However, the molecular mechanisms involved in N-modulation of plant susceptibility to pathogens are poorly characterized. In this work, we show that Solanum lycopersicum defense response to the necrotrophic fungus Botrytis cinerea is affected by plant N availability, with higher susceptibility in nitrate-limiting conditions. Global gene expression responses of tomato against B. cinerea under contrasting nitrate conditions reveals that plant primary metabolism is affected by the fungal infection regardless of N regimes. This result suggests that differential susceptibility to pathogen attack under contrasting N conditions is not only explained by a metabolic alteration. We used a systems biology approach to identify the transcriptional regulatory network implicated in plant response to the fungus infection under contrasting nitrate conditions. Interestingly, hub genes in this network are known key transcription factors involved in ethylene and jasmonic acid signaling. This result positions these hormones as key integrators of nitrate and defense against B. cinerea in tomato plants. Our results provide insights into potential crosstalk mechanisms between necrotrophic defense response and N status in plants. To better understand the molecular changes underlying the impact of nitrate availability on plant susceptibility to B. cinerea, we performed plant transcriptome profiling assays on mock-treated (3 biological replicates) and infected plants ( 3 biological replicates) grown under three N conditions, using GeneChip Tomato Genome Arrays (Affymetrix).

Dataset Information

Arabidopsis defense against Botrytis cinerea: chronology and regulation deciphered by high-resolution temporal transcriptomic analysis (tga3-2 knockout data)

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