Abstract
The annual devastation of soybean agriculture by the Phytophthora
sojae pathogen has caused worldwide concern in the past decades. This
loss accumulates billions dollars in cost each year. A previous
Independent Study by Matthew Reeder in 2014 investigated the targeted
conserved biological network of this pathogen. PsAvh172 an RxLR
proteins was expected to greatly inhibits host cells growth and function.
To characterize the response of the target host in the release of PsAvh172
protein, an RNA-Seq analysis was performed, but no denite conclusion
could be drawn from this analysis. In this study, we use linkage-based
hierarchical clustering to further characterize the data from Reeder's
research to analyze Phytophthora sojae infection process. This not only
provides insight into CCD but also adds to the literature of models of
interacting species, in which mutualisms have been less of a focus.
Advisor
Regan, Erzsebet
Second Advisor
Long, Colby
Department
Mathematics; Biochemistry and Molecular Biology
Recommended Citation
Huynh, Vi, "Computational Analysis of PsAvh172 Data to Investigate the Targets of Phytophthora sojae in Soybean Host A Hierarchical Clustering Evaluation of Yeast RNA-Seq Data" (2020). Senior Independent Study Theses. Paper 8774.
https://openworks.wooster.edu/independentstudy/8774
Publication Date
2020
Degree Granted
Bachelor of Arts
Document Type
Senior Independent Study Thesis
© Copyright 2020 Vi Huynh