View the Expression Landscape
Using OmniViz to analyze XpressWay data, it is possible to get an overview of the gene-expression patterns of all ~2,000 genes (Figure 1), and then to quickly identify those gene-expression profiles that possess features of interest. For example, if you are interested in developing a drug for a CNS disorder, you may be interested in the targets (see orange arrows on the left hand side of Figure 1) that have high expression (red) in nervous tissue and low expression (blue) in peripheral tissues.
Assess Individual Targets
Individual gene-expression profiles across the panel of 72 tissues can provide valuable information about potential drug action in those tissues. Within OmniViz, users can retrieve the expression profile for a drug target with a text query for the target name. The example target expression profile shown (Figure 2, ATP1A3) highlights high copy numbers in CNS and heart samples. Depending on the approach being used, this expression pattern may represent opportunities for the development of drugs for CNS or cardiac disorders, or may suggest potential side-effect liabilities in these areas. Knowledge of these data will help users to make rational decisions on the future of a drug developed against this target.
In addition to searching for genes by their name or by their functional role, OmniViz provides the capability to make complex numeric queries of the data. For example, users can identify targets with a particular expression profile, or profiles that are most similar to a chosen target.
As an example, it is possible to search for genes with high expression in hippocampus as potential targets for Alzheimer’s disease (AD). It is known that the hippocampus atrophies in AD, and that it plays a role in processes that are affected in AD (e.g., memory). Within OmniViz, the user can to set up a search for genes that have greater than 10,000 mRNA copies in the hippocampus, but less than 100 mRNA copies in most of the other tissues. This particular query retrieves mGluR5-splice variant 2 (mGluR5-2). As an additional step, it is possible to retrieve other gene profiles with the closest similarity to mGluR5-2, by correlation or Euclidean matching (Figure 3).
Furthermore, it is possible to assess the relevance of the retrieved targets by viewing diseases and processes associated with them. As can be seen from the Table, mGluR5-2 and its closest neighbors play a role in several processes (e.g. synaptic transmission, synaptic plasticity) that may be relevant to AD. Therefore, these may be interesting targets to progress for this disorder.