Statistical Analysis of Patterned Gene Expression
The long-term goal of my research is to understand the molecular mechanism for the regulation of gene expression. Previous studies in the Tapscott lab demonstrate that MyoD, a muscle specific transcription factor, directly regulates discrete subprograms of gene expression through promoter-specific regulation of MtoD binding and activity. To better understand the patterned gene expression regulated by MyoD in myogenesis, we have proposed to apply statistical analysis to expression array data to identify the elements that pattern the program of muscle differentiation. The Specific Aims of this proposal are:
1) Use expression array analysis to identify subprograms of skeletal gene expression in mouse fibroblasts.
2) Extend the array analysis to cells with co-factor mutations and identify the subsets of gene expression that are altered by each mutation
3) Identify the conserved regulatory regions in the distinct subprograms of MyoD regulated genes.
The significance of this proposal is that we will develop a methodology to identify the elements that pattern the subprograms of gene expression in muscle differentiation. This will provide a fundamental framework for our future understanding of the molecular mechanism during myogenesis in muscle development and muscular disease. Through this training program, I hope to systematically learn how to apply emerging bioinformatic tools to answer important biological questions, which will be of great value for my future career development.