Tissue expression map of a large number of expressed sequence tags and its application to in silico screening of stress response genes in common wheat
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In order to assess global changes in gene expression patterns in stress-induced tissues, we conducted large-scale analysis of expressed sequence tags (ESTs) in common wheat. Twenty-one cDNA libraries derived from stress-induced tissues, such as callus, as well as liquid cultures and abiotic stress conditions (temperature treatment, desiccation, photoperiod, moisture and ABA) were constructed. Several thousand colonies were randomly selected from each of these 21 cDNA libraries and sequenced from both the 5′ and 3′ ends. By computing abundantly expressed ESTs, correlated expression patterns of genes across the tissues were monitored. Furthermore, the relationships between gene expression profiles among the stress-induced tissues were inferred from the gene expression patterns. Multi-dimensional analysis of EST data is analogous to microarray experiments. As an example, genes specifically induced and/or suppressed by cold acclimation and heat-shock treatments were selected in silico. Four hundred and ninety genes showing fivefold induction or 218 genes for suppression in comparison to the control expression level were selected. These selected genes were annotated with the BLAST search. Furthermore, gene ontology was conducted for these genes with the InterPro search. Because genes regulated in response to temperature treatment were successfully selected, this method can be applied to other stress-treated tissues. Then, the method was applied to screen genes in response to abiotic stresses such as drought and ABA treatments. In silico selection of screened genes from virtual display should provide a powerful tool for functional plant genomics.
KeywordsGlobal gene expression Stress response gene Virtual display Common wheat
The authors would like to express their cordial thanks to members of the Wheat Consortium in Japan for supplying of original wheat RNAs; Dr. K. Murai, Fukui Prefectural University, Drs. E. Himi and K. Noda, Okayama University, Dr. S. Nasuda, Kyoto University, Drs. H. Miura and K. Kato, Obihiro University, Dr. T. Koba, Chiba University, and Drs. S. Takumi and C. Nakamura, Kobe University. This work was supported by Grants-in-Aid for Scientific Research on Priority Areas (C) “Genome Science” and basic research (A) (Nos. 13202055 and 13356001) from the Ministry of Education, Culture, Sports, Science and Technology of Japan. The sequence data from this study have been submitted to DDBJ under accession nos. CJ493525–CJ736986 for the EST sequences.
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