UC San Diego

With the advent of whole genome sequences, biologists are confronted with the problem of understanding the non protein-coding portion of the genome. This remains a difficult task due to the many enigmatic features of cis- controlling sequences. In this thesis, I will present the genomic tools, methodologies, and observations I have made in the course of studying the peripheral nervous system of Drosophila melanogaster, a model system well suited for the study of transcriptional regulatory networks. In the first chapter, I will describe a software tool that I created to facilitate the use of genome sequences in wet- lab experiments. This tool, GenePalette, is particularly well suited for inspecting genomic regions that have been implicated by whole-genome analysis (searches for transcription factor binding sites, core promoter sequences, microRNA target sites, etc), and it was used extensively in the analyses presented in each subsequent chapter. In the second chapter, I describe a technique I developed for searching a genome for biologically relevant transcription factor binding site clusters. Using this methodology, we came to the surprising realization that many known Notch targets have statistically significant clusters of binding sites for Suppressor of Hairless [Su(H)], the transcription factor responsible for transducing the Notch signal. In chapter three, I validate a novel cluster of Su(H) binding sites, identified by my in silico study, residing within the numb gene. The investigation of this enhancer not only validates my bioinformatic approach, but also serves to illuminate several as of yet unappreciated aspects of bristle development. In chapter four, I take a different approach to finding new cis-regulatory sequences. By composing a hypothetical dual input code for neural precursors, we identify a cluster of binding sites that implements this code through a candidate gene approach. Finally, in chapter five, I present the discovery of an ancient transcription factor binding site, conserved for >700 million years. This finding establishes that although cis- regulatory change is a major engine for evolution, some transcriptional linkages can withstand the constant erosion of sequence turnover for extremely long periods