Microarray and Genome-wide Sequencing Approaches to Characterizing DNA Binding Molecules

Citation

Puckett, James William (2009) Microarray and Genome-wide Sequencing Approaches to Characterizing DNA Binding Molecules. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/E3NT-SC46. https://resolver.caltech.edu/CaltechETD:etd-05282009-145527

Abstract

Hairpin and linear beta-alanine linked pyrrole-imidazole (Py-Im) polyamides are programmable oligomers that bind the DNA minor groove sequence-specifically with affinities comparable to those of DNA-binding proteins found in nature. These small molecules have been observed to localize within the nucleus of living cells and modulate endogenous gene expression. Herein, we demonstrate the utility of a linear beta-alanine linked pyrrole-imidazole polyamide to upregulate frataxin mRNA and protein expression in a cell line derived from a Friedreich’s Ataxia patient. We examine the binding affinities and specificities of additional linear beta-alanine linked polyamides. We examine binding specificities of a Cy3-fluorescently labeled version of the frataxin­ expression modulating-polyamide and a Cy3-labeled polyamide known to downregulate expression of the Vascular Endothelial Growth Factor using DNA microarrays composed of hairpins harboring all 524,800 unique 10 bp DNA sequences. We experimentally verify the correlation of Cy3 fluorescence intensity with quantitative DNase I footprint derived binding affinities. We find that Cy3 dye placement on the polyamide tail versus labeling of an internal pyrrole does not significantly alter DNA specificity. Finally, we examine the genome-wide binding preferences of Androgen Receptor (AR) in LNCaP cells using ChIP-Seq (chromatin immunoprecipitation followed by high-throughput DNA sequencing). We observe the canonical ARE motif to be present in a majority of the immunoprecipitated binding regions. We observe a secondary sequence motif that may be the dimerization of AR with a forkhead protein, an interaction known in the literature but without a defined sequence motif. We also define AR occupancy with respect to location in and about known genes. We correlate gene expression profiles from mRNA microarray data with the ChIP-Seq data.

Thesis Files