Publication Date

2020

Document Type

Dissertation/Thesis

First Advisor

Calvo, Ana M.

Second Advisor

Yin, Yanbin

Degree Name

M.S. (Master of Science)

Legacy Department

Department of Biological Sciences

Abstract

Ascomycota fungi are mostly saprophytic in nature, living off dead or decaying matter. However, a small subset of these fungi possess the ability to infect live hosts and cause disease while obtaining nutrients. Phytopathogenic Ascomycota are responsible for substantial economic losses each year, destroying valuable crops. Previous genomic studies have been conducted to annotate sequenced genes and proteins of these fungi with predicted functions, and those annotations are publicly accessible through online databases. Through these means, several genes have been identified to play a role in pathogenicity in some agriculturally relevant fungi. Through a bioinformatic analysis approach the present study provides further insights between the functional annotations of known phytopathogenic and non-phytopathogenic Ascomycota fungi, specifically by categorizing orthologous groups from phytopathogenic and non-phytopathogenic Ascomycota genomes and identifying trends using their respective protein functional annotations. This approach determined positive enrichment existing between categories revealing a prediction of what genetic characteristics make an Ascomycete phytopathogenic.

Extent

43 pages

Language

eng

Publisher

Northern Illinois University

Rights Statement

In Copyright

Rights Statement 2

NIU theses are protected by copyright. They may be viewed from Huskie Commons for any purpose, but reproduction or distribution in any format is prohibited without the written permission of the authors.

Media Type

Text

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