Dr. Juli Atherton, Using SELEX Data to Model the Affinity of DNA Sequences to the Transcription Factor Bicoid

In genomic research, determining locations on the genome to which a transcription factor binds with medium to high affinity might help identify possible transcription factor binding sites. Hence, interest lies in developing models that predict the affinity of a transcription factor based on nucleotide sequence. Often, data from in-vitro experiments are used when building such models.

One such in-vitro experiment is a systematic evolution of ligands by exponential enrichment (SELEX) experiment. In a SELEX experiment one begins with a large random pool of DNA sequences in equilibrium with a transcription factor. Sequences that had bonded to the transcription factor are separated from the solution, amplified by polymerase chain reaction (PCR) and entered into the next round of SELEX. This process continues for as many rounds as the experimenter desires. Thus far SELEX has been very good at suggesting consensus sequences but making further inference from them has been difficult.

In this talk, I will begin with a simple biochemical explanation of SELEX. I will then discuss our analysis of the SELEX data for the transcription factor Bicoid focusing on our statistical methodology and addressing issues in the design of SELEX. Where possible, I will show how our analysis of the SELEX data compares to our analysis of other experiments.