Carnegie Mellon University and the University of Pittsburgh are awarded a grant to develop and implement algorithms and software tools for the analysis of gene expression experiments that study the same biological system in multiple species. Biological systems, including the cell division process which plays a major role in development and cancer, immune response and circadian rhythm (which governs our behavior over the course of a day) are similarly activated across many different species. Indeed, much of the progress in understanding these systems was achieved by studying their behavior in model organisms. When using expression experiments, which measure the level of genes at different time points and in different conditions, to study these systems, researchers often identify hundreds, or even thousands, of genes as being expressed in each of the species. This makes it hard to analyze the resulting sets and to accurately identify genes that control key aspects of the system. In addition, our ability to correctly detect interactions among these genes is greatly reduced since many potential interactions can be used to explain the observed expression values. This joint computational-experimental project will allow us to identify a core set of genes; genes which are conserved in both sequence and expression across multiple species.
These genes represent key components of the biological system, are essential to its proper maintenance and function and would be used for further studies and for initial modeling. Predictions made by our method for these systems will be validated by new biological experiments which will in turn be used to further refine the computational model leading to a computational-experimental loop. As part of the proposal we will also develop an open source software package for cross species expression analysis. We will also develop and offer a new class on the analysis and use of cross species genomics data.
