Recent advances in global gene expression measurement and the development of large- scale public repositories for storage of such data have made a wealth of information available to researchers. While one gene expression study may lack sufficient replicates to make statistically significant pronouncements, the combination of studies through meta-analysis can yield results with a much greater likelihood of accuracy. In order to combine multiple sets of data, one must first address the issue of cross-comparison between global gene expression platforms, as well as resolve the issue of repeated measures (multiple probes representing the same gene) within each platform. In this work, I present computational methods for probe reannotation and scoring and for redundant probe consolidation that together allow for greatly improved access to data for meta-analysis. I also present an example of the application of these methods, in the analysis of the gene expression regulated by estrogen across multiple cell types.
Estrogen, a steroid hormone, interacts with its receptors to regulate gene transcription in both direct and indirect manners. Estrogen has the effect of increasing proliferation in some tissues, while inhibiting proliferation or increasing apoptosis in others. How estrogen achieves these highly divergent results remains unclear. Through meta-analysis of gene expression experiments across multiple cell types, I show that patterns of estrogen regulation in many tissues involve the same key genes and pathways, including cell cycle, p53 signaling, and TGFβ signaling pathways. However, regulation in different cell types can result from regulation of different genes, or the same genes regulated in different directions. Many patterns of gene regulation support known physiological consequences of estrogen on these tissues. In particular, genes promoting proliferation are upregulated in uterus and certain breast and ovarian cancer cell lines. One gene, thrombospondin-1, is up-regulated in eleven out of nineteen cell types and may be a key player in regulating proliferation in re- sponse to estrogen. Results in other cell types are unexpected. Most notably, neither genes promoting nor inhibiting proliferation are differentially regulated upon estrogen treatment in vascular smooth muscle cells, despite estrogen inhibiting proliferation of these cells.
| Identifer | oai:union.ndltd.org:bu.edu/oai:open.bu.edu:2144/14151 |
| Date | 22 January 2016 |
| Creators | Schneider, Stephanie G. |
| Source Sets | Boston University |
| Language | en_US |
| Detected Language | English |
| Type | Thesis/Dissertation |
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