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Published in Yuan, J., Zhu, M., Iqbal, M. J., Yang, J. Y., & Lightfoot, D. A. (2007). A computational approach to understand Arabidopsis thaliana and soybean resistance to Fusarium solani (Fsg). Proceedings of the 7th IEEE International Conference on Bioinformatics and Bioengineering, 2007. BIBE 2007, 585 - 592. doi: 10.1109/BIBE.2007.4375620 ©2007 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.

Abstract

In this study, we reported the analysis of Arabidopsis thaliana microarray gene expression profile of root tissues after the plant was challenged with fungal pathogen Fusarium solani f. sp. glycines (Fsg). Our microarray analysis showed that the infection caused 130 transcript abundances (TAs) to increase by more than 2 fold and 32 out of 130 TAs were increased by more than 3 fold in the root tissues. However, only nineteen ESTs were observed with a decrease in TAs by more than 2 fold and 13 of them went down more than 3 fold due to the pathogen infection. In addition, the number of the up-regulated genes was nearly seven times more than that of downregulated genes. The coordinate regulation of adjacent genes was detected and the distance distribution of the nearest neighbor genes was less likely to be randomly scattered in genome. The results of this study enabled us to decipher the resistance mechanism to Fsg through an integrated computational approach.

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