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Functional annotation of micrornas in signal transduction pathways via high-throughput cell based screening / Anthony O. Olarerin-George.
LIBRA R001 2013 .O42
Available from offsite location
- Format:
- Book
- Manuscript
- Thesis/Dissertation
- Author/Creator:
- Olarerin-George, Anthony O.
- Language:
- English
- Subjects (All):
- Penn dissertations--Genomics and Computational Biology.
- Genomics and Computational Biology--Penn dissertations.
- Local Subjects:
- Penn dissertations--Genomics and Computational Biology.
- Genomics and Computational Biology--Penn dissertations.
- Physical Description:
- ix, 188 pages : color illustrations ; 29 cm
- Production:
- 2013.
- Summary:
- MicroRNAs (miRNAs) are a class of regulatory genes whose role in cell biology is increasingly appreciated [1]. In metazoans, miRNAs mediate post-transcriptional regulation by base-pairing with partially complementary sequences in their target transcripts. This interaction with mRNA frequently inhibits its translation but can also result in its deadenylation and consequent degradation [2]. Although estimates vary, miRNAs are thought to target as much as 60% of human genes, highlighting their potential as master regulators of gene expression [3, 4]. However, despite the identification of hundreds of human miRNAs and computational predictions of thousands of their target genes, many lack experimentally validated functions.
- Functional genomics methodologies such as cell-based screening (CBS) offer a high-throughput approach to close the gap between the identification of miRNAs and understanding their function. To this end, this thesis examines the role of miRNAs in the regulation of signal transduction pathways using CBS. I identified and characterized novel regulators of NF-kappaB and CREB signaling. Notably, I found miR-517a and miR-517c were potent activators of NF-kappademonstrated that miR-132 could act as a feedback repressor or activator of CREB signaling depending on the pathway stimulus and the promoter makeup of CREB target genes. Lastly, I developed a novel computational pipeline to deduce functional coding components of a pathway by integrating CBS data and miRNA target predictions. Together these studies extend our knowledge of the general function of miRNAs and serve as a resource for their functional output in signal transduction pathways.
- Notes:
- Adviser: John B. Hogenesch.
- Thesis (Ph.D. in Genomics and Computational Biology) -- University of Pennsylvania, 2013.
- Includes bibliographical references.
- OCLC:
- 862507812
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