Project Leaders:   
Steven Jones, Marco Marra

Involved Institutions:   
BC Cancer Agency, Genome Sciences Centre

Technology Applications:   
Bioinformatics software, Predictive tools, Diagnostic methods

Research Funding Program:   
Competition II

The various cell types in our bodies are dependent on the correct amount of gene expression in the proper place at the right time. This project proposes to find the DNA elements that control gene expression with computational biology and gene expression profiling. The scientists at the Genome Science Centre will compare genome DNA sequences across species and expression data across different platforms to identify regulatory elements. This project will determine and record the expression of all mouse and many human genes, the most comprehensive effort in mammals to date. This will lead to an understanding of the complex networks of gene regulation that play a role in the normal development of mice and humans. The ability to predict key regulatory events and gene expression controls will facilitate the development of innovative diagnostic tools and gene-based therapies for many disease states.

The project will also use gene expression data to identify co-expressed genes. The researchers hypothesize that genes with similar expression patterns have similar control and will therefore share some regulatory elements. They are analyzing data from three sources: SAGE, cDNA microarray and Affymetrix-based profiling platforms. This effort represents one of the most comprehensive expression surveys of the developing tissues for mammals. Ultimately, the sets of genes consistently determined to be co-expressed in all three platforms will represent powerful datasets for detection of shared regulatory elements.

In the first two years, this project has completed a pipeline to align the upstream regions of user-defined sets of genes with the results displayed in a web-based graphical interface. Another pipeline has been created to evaluate regulatory element discovery algorithms against known transcription factor binding sites. Finally, the project has published a 3D genome browser, which can perform these tasks in an interactive manner.

In summary, this project applies bioinformatics tools to better understand gene regulation and will therefore advance the understanding of both normal cellular development and the etiology of disease.