The 6th Annual

NC State University

Undergraduate Summer Research Symposium

 

NSF Fungal Genomics REU


Abstracts are listed in alphabetical order by the last name of the corresponding author.

 


 

 

 

Student Author(s): 

Birdsall, Paige M.

Home Institution:

Meredith College

Program:

NSF Fungal Genomics REU

College:

CALS

Department(s):

Center for Integrated Fungal Research

Research Mentor(s)

Ralph Dean/Center for Integrated Fungal Research

Abdelaty Saleh/Center for Integrated Fungal Research

Title of Presentation:

Plant-Pathogen Warfare: Protein-Protein Interactions Between Rice and the Rice Blast Fungus

 

 

Rice blast is caused by the fungus Magnaporthe grisea which is a major limiting factor in rice production throughout the world. M. grisea is a leading model for the study of fungus-plant interactions. The goal of this project was to determine protein-protein interactions that control disease between the rice plant and the rice blast pathogen. The resistance gene from the rice plant, PITA and the corresponding avirulence gene, AVR-PITA from the rice blast were amplified using Polymerase Chain Reaction and placed in Gateway Cloning Vectors. They were then tested to see the interaction through Bimolecular Fluorescence Complementation when transformed into rice protoplasts. 

 

 


 

 

 

Student Author(s): 

Johnson, April T.

Home Institution:

Claflin University

Program:

NSF Fungal Genomics REU

College:

CALS

Department(s):

Center for Integrated Fungal Research

Research Mentor(s)

Ralph Dean/Center for Integrated Fungal Research

Doug Brown/Bioinformatics

Title of Presentation:

A Computational Analysis of microRNAs from the Genome Sequence of the Rice Blast Fungus Magnaporthe grisea

 

 

The rice blast fungus, Magnaporthe grisea is a destructive pathogen that kills a vast amount of rice crops each year. M. grisea is the limiting factor to rice production in many regions and is very difficult to control. MiRNAs are 17-21 nucleotide sequences that negatively regulate gene expression. Consequently, identifying and analyzing the M. grisea genome for miRNAs will provide greater insight into why the fungus is so damaging and what can be done to control this organism. From the Bioinformatics approach, a computational analysis of the miRNAs of M. grisea was performed. A computer program using PERL© and UNIX© was created to extract the predicted target sites from thirty-three miRNAs. In addition, these miRNAs were blasted against the NCBI database to identify possible matches in other fungi. The data extraction program read each file of miRNA data matches of M. grisea and displayed an output of the gene name, miRNA name, folding energy, and genome location. The extracted information was compiled into a database in order to provide researchers the opportunity to compare data collected from wet lab experiments. In conclusion, these comparisons and analyses will help to gain a better understanding of miRNAs and the role they play in fungal pathogenesis.

 


 

 

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