Genetics and Genomics Commons^™

Uncovering Novel Small Regulatory Rna In Protostome, Sweta Khanal

Dissertations

Small RNAs play pivotal roles in post-transcriptional gene regulation across diverse phylum of protostomes. In this study, we investigate the functional significance of atypical miRNAs, mirtron miR-1017 in Drosophila. Through ectopic expression in neuronal cells, we demonstrate that miR-1017 extends lifespan by targeting its host transcript, acetylcholine receptor Dα2, and influencing its splicing. This novel trans-regulatory function suggests a mechanism for mirtron evolution, highlighting the interplay between splicing and post-transcriptional regulation. Additionally, we profile small RNA populations in the polychaete developmental model Capitella teleta, shedding light on the small RNA landscape in annelid worms. Our analysis reveals a rich …

Characterizing Endogenous Dicer Products To Unravel Novel Rnai Biogenesis Pathways, Jacob Oche Peter

Dissertations

ABSTRACT

RNA interference (RNAi) is a pervasive gene regulatory mechanism in eukaryotes based on the action of multiple classes of small RNA (sRNA). Exploiting RNAi pathways in non-model systems have great potential for creating potent RNAi technologies. Here, we accessed RNAi-mediated control of gene expression in the two-spotted spider mite, Tetranychus urticae (T. urticae) using engineered dsRNA designed to modulate the host RNAi pathway and increase RNAi efficacy. Analysis of Dicer (Dcr) generated fragments revealed how exogenous RNAs access the host RNAi pathway in this animal, opening avenues for designing RNAi technology for their control. Further, some organisms …

A Context-Forward In Vivo Functional Genomics Platform For Target Discovery And Establishing Vulnerability Context In Pancreatic Cancer, Johnathon Rose, Johnathon Lynn Rose

Dissertations & Theses (Open Access)

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy with a very poor patient prognosis (5-year survival of ≤ 7%). While transcriptional profiling has aided in the classification of this disease into at least two broader subtypes, this alone has so far been insufficient to inform on more nuanced patterns of oncogenic dependency. We hypothesized that a more comprehensive and granular characterization of PDAC disease diversity is required to establish relevant context for targeted therapy. To this end, we sought to establish an integrated platform to: i) more comprehensively characterize differential oncogenic signaling across our tumor models, and ii) establish …

Identification And Characterization Of Epigenetic Regulators In The Yellow Fever Mosquito, Aedes Aegypti, Shankar C. R. R. Chereddy

Theses and Dissertations--Entomology

Due to the increased interactions between the sylvatic and urban cycles of Aedes aegypti life cycle, there has been an increase in the incidence of vector-borne diseases. The risk involved through the transmission of viruses like Dengue, Zika, Yellow-fever and Chikungunya calls for an effective control method for the deadly vector. The possibility of pesticide resistance and the costs involved in producing new pesticides have pushed Sterile Insect Technique (SIT) into prominence. However, current methods used to sterize insects for SIT are not highly efficient. This study tackles current issues in mosquito control by identifying and characterizing epigenetic regulators that …

Application Of Genomic Technologies To Study Infertility, Nicholas Rui Yuan Ho

Arts & Sciences Electronic Theses and Dissertations

An estimated one in eight couples in the United States are diagnosed with infertility. There is a significant genetic contribution to infertility, with estimates of heritability ranging from 0.2 to 0.5. We know surprisingly little about the genetic causes, with only slightly more than a hundred genes known to cause human infertility. I have been translating recent advances in genomics to study infertility in a more efficient manner, in order to improve our knowledge of the genetic causes. By using high throughput genomics and proteomics datasets from other groups, I was able to feed that into a machine learning algorithm …