Gene regulatory networks contain multiple components including microRNAs (miRNAs) that coordinate regulation of genes to produce higher level cell functions. miRNAs are small non-coding RNA molecules that modulate gene expression post-transcriptionally by binding to short target motifs on mRNA transcripts to down-regulate target genes. Because miRNA regulation of genes is dependent on short target motifs, miRNAs have been thought to have both gene and cumulative, system-level impact on gene regulation. In recent years, ', 'aberrant miRNA expression and miRNA dysregulation has been associated with multiple diseases including cancer, likely due to the mechanistic impact of genetic variation or mutations.', 'The present work generalizes a framework to study miRNA regulation of genes from the systems-level to the gene-level in the context of genetic variation. I employ integrative, multi-omic statistical analyses to (i) identify miRNAs that differentially regulate functional gene networks that confer specific cell functions (pathways) between tumor and healthy tissue, and (ii) find tumor-associated genetic variants that modulate miRNA:mRNA co-expression patterns on identified dysregulated pathways. Finally, I use molecular dynamics simulations to study the biophysical impact of genetic variants on miRNA:mRNA binding interactions in atomic-level detail. The simulations provide support to the discoveries in the multi-omic, statistical analyses and yield a framework for finding genetic variants that contribute to miRNA dysregulation of genes in cancer.

Last modified

• 10/21/2019

Creator

• Gary Wilk

DOI

• https://doi.org/10.21985/n2-rcbs-5p98

Subject

• Chemical and Biological Engineering

Keyword

• Gene Regulation
• Systems Biology
• Single Nucleotide Polymorphisms
• Pathways
• Cancer
• microRNAs

Date created

• 2018-01-01

Resource type

• Dissertation

Rights statement

• In Copyright