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United States Department of Agriculture

Agricultural Research Service

Research Project: APPLICATION OF PLANT-VIRAL BASED VECTORS TO THE DEVELOPMENT OF NOVEL DISEASE CONTROL STRATEGIES Title: Comparative analysis of microarray data in Arabidopsis transcriptome during compatible interactions with plant viruses

Authors
item Postnikova, Olga -
item Nemchinov, Lev

Submitted to: Virology Journal
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: April 23, 2012
Publication Date: May 29, 2012
Citation: Postnikova, O.A., Nemchinov, L.G. 2012. Comparative analysis of microarray data in Arabidopsis transcriptome during compatible interactions with plant viruses. Virology Journal. 9(101):1-7.

Interpretive Summary: Understanding the mechanisms that plants engage to protect themselves against a variety of pathogens plays a key role in the development of control strategies aimed to reduce crop losses caused by plant diseases. There are several well-studied model plants on which most of this research is being conducted, such as the small flowering plant Arabidopsis thaliana L. whose genome was the first plant genome to be sequenced. In this work, using publicly available data on Arabidopsis genome, we described genes involved in stress response against viruses infecting the Arabidopsis plant. This knowledge may be applicable to increase resistance to pathogens in agriculturally important crops. It is expected that results of this study will be of interest to the wide spectrum of plant researchers in academia and government organizations as well as to representatives of industry.

Technical Abstract: To analyze transcriptome response to virus infection, we have assembled currently available microarray data on changes in gene expression levels in compatible Arabidopsis-virus interactions. We used the mean r (Pearson’s correlation coefficient) for neighboring pairs to estimate pairwise local similarity in expression in the Arabidopsis genome. We provided a functional classification of the genes with altered expression levels. We also demonstrated that responsive genes may be grouped or clustered based on their co-expression pattern and chromosomal location. Each virus-host interaction was found to be unique in terms of the genes with altered expression levels. The number of shared genes affected by all viruses is very limited. At the same time, common genes can participate in virus-, fungi- and bacteria-host interaction. According to our data, non-homologous genes that are located in close proximity to each other on the chromosomes and whose expression profiles are modified as a result of the viral infection occupy 12% of the genome and among them 5% form co-expressed and co-regulated clusters.

Last Modified: 4/19/2014