• Overview
• Protein Binding Microarrays
• Cis Regulatory codes
• In vivo Cis Regulatory Elements

Research Overview

The ability of a cell to respond to environmental stresses, differentiate properly, and progress normally through the cell cycle requires a specific and coordinated gene expression program involving regulated transcription of thousands of genes. The initiation of transcription is in large part controlled by the sequence-specific DNA binding of transcriptional activators and repressors. Despite their importance, the sequence specificities of most transcription factors (TFs) remain unknown, underscoring the need for a rapid and universal method to discover TF binding sites.

Recently, we developed a new DNA microarray-based in vitro technology, termed protein binding microarrays (PBMs), that allows rapid, high-throughput characterization of the DNA binding site sequence specificities of TFs in a single day (Mukherjee et al., Nature Genetics (2004) 36(12):1331-9). Using PBMs, we identified the DNA binding site sequence specificities of a number of yeast transcription factors. Similar PBM experiments will be useful in identifying cis regulatory elements and gene regulatory networks in various other genomes, including mouse and human. The resulting binding site datasets will allow for improved computational methods for predicting not only genomic TF binding sites but also their combinatorial co-regulation of their target genes in various eukaryotic genomes.

To this effect, we have developed computational approaches for analyzing cis regulatory modules (including transcriptional enhancers). We have developed algorithms that include a rigorous statistical consideration of TF binding site clustering, their combinatorial co-occurrences, and cross-species conservation in order to identify candidate cis regulatory modules (CRMs). We have seen that our predicted CRMs are bound by the corresponding TFs in mammalian cells, and that predicted transcriptional enhancers drive temporal- and cell-specific gene expression in the developing Drosophila embryo. A newer algorithm of ours can refine a prior hypothesis of TFs' combinatorial co-regulation of the expression of their target genes. These and newer strategies under development in our lab can be applied widely for analyzing metazoan transcriptional regulatory networks.

This page was last updated September 9, 2005