Data mining of genomic data generated from soybean treated with different phytohormones

Abstract

Plant hormones, or phytohormones, have been implicated in a range of defensive reactions in plants. They have been found to help plants ward off pathogenic infections ranging from fungi to nematode\pest infections. Soybean (Glycine max) is the second most valuable agricultural commodity and an inexpensive source of proteins for humans and animals in the United States. In this study we use next generation sequencing (Illumina, RNASeq) and Bioinformatics analysis methods to study the impact of four natural phytohormones on soybeans and it's resistance to a nematode called the soybean cyst nematode (SCN), which causes over 1 billion dollars in losses to US farmers per annum. To that end we have developed a relational database that stores genomic information from soybean in addition to the RNASeq data from each hormone treated soybean sample. Together the database provide a resource to mine the data to find key genes and pathways. The database can be accessed from: http://bioinformatics.towson.edu/soybean/D efault.aspx