Genomic and proteomic analysis in soybean, and building of related databases

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Towson University Graduate Theses and Dissertations

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2014-09-23

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dissertations
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Towson University. Department of Computer and Information Sciences

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Abstract

Soybean (Glycine max) is the second most valuable and inexpensive source of proteins for humans and animals in the United States. In this dissertation we analyzed proteomic and genomic data related to soybean. On the proteomics side, we used 2d gel data to identify proteins present in soybean seeds, which is of importance since the seeds are used often in agriculature as feed for animals, or incorporated into food products for human consumption. We also used 2D gel data to identify soybean proteins in the soybean cyst nematode (SCN), which is a major pest of soybean in the United States and causes million dollars losses annually. For both these analysis, we developed publicly available databases that are accessible through the web for researchers to access the data freely. From the genomics side, we used RNA-Seq data to analyze soybean treated with different plant hormones. The goal here was to see how genes in soybean react when treated with one of these hormones: Salicylic acid (SA), Jasmonic acid (JA), auxin (IAA), and ethylene (Eth). Many of these hormones are used in the agirculature industry, so knowing their effect at the molecular level is of importance to human health. We also used pathway visualization tools to map the gene expression measurements we got from the RNA-Seq experiemnts onto biological pathways, to better understand their effects.