Aedes aegypti is an important vector of human pathogens including the viruses yellow fever, dengue and chikungunya. The small interfering RNA (siRNA) pathway is a critical immune response for controlling viral replication in Aedes aegypti. The goal of this research is to identify components of the Aedes aegypti genome that influence this pathway.
A transgenic mosquito strain that reports the status of the siRNA pathway via enhanced green fluorescent protein (EGFP) intensity was employed to differentiate silencing abilities among individuals. Extreme EGFP expression phenotypes, representing efficient and poor silencing abilities, were enriched over five generations.
Transcriptome sequencing and analyses were performed from pools of individuals from each enriched phenotype, revealing potential RNAi contributors. 1,120 transcripts were significantly different (FDR<0.0001) among the extreme phenotypes.
Four genes were chosen, amplified, sequenced for SNP analysis. These analyses were performed on samples obtained by crossing enriched, extreme phenotype F0 individuals, intercrossing their progeny, then selecting individuals representing the extreme phenotypes from the F2 population. Though further verification is needed, findings from these analyses imply the regions of Aedes aegypti, Liverpool strain (AAEL) gene identifiers AAEL005026, AAEL013438 and AAEL011704 amplified do not contribute to the two extreme, opposite RNAi silencing in the sensor strain used here. SNP analyses of AAEL000817 indicate this gene either influences extreme RNAi phenotypes or is closely linked to a gene(s) that contributes to RNAi in Aedes aegypti.
The 1,120 genes identified can be validated or eliminated as potential targets in the quest to mitigate the impact of Aedes aegypti. / Master of Science in Life Sciences
Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/75141 |
Date | 02 September 2015 |
Creators | Saadat, Angela P. |
Contributors | Entomology, Adelman, Zachary N., Myles, Kevin M., Hoeschele, Ina |
Publisher | Virginia Tech |
Source Sets | Virginia Tech Theses and Dissertation |
Detected Language | English |
Type | Thesis |
Format | ETD, application/pdf, application/pdf |
Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
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