A central problem in biology is defining the information that controls gene expression in particular cellular contexts. This information is contained within enhancer and repressor elements that bind to specific transcription factors. Standard molecular approaches for identifying these elements are laborious, while bioinformatic analyses cannot reveal elements that function in particular contexts. The proposed studies will develop and validate a high throughput procedure for context specific identification of transcription factor binding sites. The procedure combines Chromatin Immunoprecipitation (CHIP) with rapid serial analysis of enriched sequences and is called Serial Analysis of Genomic Sites (SAGS). For development of SAGS we will use the Neural Restrictive Silencer Factor (NRSF) as an exemplar because it has an unusually long (2 lbp) recognition motif(NRSE) that can be easily predicted by bioinformatics. Predicted elements will be compared to actual cellular binding sites that are identified using SAGS. 100-300bp genomic fragments that are bound by NRSF in P 19 cells will be enriched by CHIP, and a novel restriction enzyme will be used to cleave unique 26bp tags from each end of the fragments. These tags will be concatenated, and sequenced en masse. Sequences of individual tags will then be extracted and mapped to the mouse genome to identify binding sites and associated genes. We will also identify direct regulatory targets of NRSF using microarray analysis in NRSF null embryos and after RNAi-mediated inhibition of NRSF expression in P19 cells. Together these studies will provide global analysis of transcription factor binding sites and correlation of this binding with gene expression. SAGS and microarray analysis promises to be a powerful combination for identifying regulatory sequences that are differentially active during development, after treatment with drugs or in a variety of pathological conditions. Such information may be particularly useful in the design of specifically targeted promoter sequences for gene therapy vectors.
