A Comparative Genomic Approach to Identifying the Plasticity Transcriptome
The aim of this project is to use computational methods to analyze the set of genes expressed in response to neural activity. When a neuron receives a stimulus from seizure or learning and memory, the amount of certain proteins that the cell produces increases through a mechanism called gene expression. This change is governed by the binding of transcription factors to DNA at specific sequences near the gene. Using a probabilistic model and a comparison between human and mouse, we identified a set of genes with CREB, zif268, and AP-1 transcription factor binding sequences. The presence of those sequences are known in many cases increase gene expression and protein amount. This set genes provides information about the role of the transcription factors as well as a resource for biologists looking to build specific networks of protein activation. We found that the transcription factors CREB and zif268 are likely to bind near genes involved in regulatory networks and the change of neuron structure. These results are compared to studies of gene expression following seizure. This work is a crucial first step in using computational methods to study learning and memory at the level of the neuron.