Functional genomics of the soybean-cyst nematode interaction.

摘要

The soybean cyst nematode (SCN; Heterodera glycines Ichinohe) is the major pest of soybean and is responsible for an estimated loss of over one billion dollars per annum in the United States. The genome of soybean is not completely sequenced and few functional genomic studies have been conducted on the soybean cyst nematode interaction. We apply bioinformatics and data mining tools to analyze DNA microarray data and soybean ESTs to find genes and pathways involved in the resistance of soybean to SCN. We found a number of candidate resistant genes, and found the salicylic acid induced pathway to interact with the jasmonic acid and other pathways to infer resistance in soybean against SCN. The world's first public soybean microarray database was constructed to store microarray data and soybean ESTs. Analysis tools were integrated into this database for faster analysis of DNA microarray experiments. O&barbelow;nl&barbelow;ine a&barbelow;nalytical p&barbelow;rocessing (OLAP) was used to mine the microarray experiments and was found to be an efficient and fast method to mine gene expression data.