Genetic interactions, a phenomenon whereby combinations of mutations lead to unexpected effects, reflect how cellular processes are wired and play an important role in complex genetic diseases. Understanding the molecular basis of genetic interactions is crucial for deciphering pathway organization as well as understanding the relationship between genetic variation and disease. Several hypothetical molecular mechanisms have been linked to different genetic interaction types. However, differences in genetic interaction patterns and their underlying mechanisms have not yet been compared systematically between different functional gene classes. Here, differences in the occurrence and types of genetic interactions are compared for two classes, gene-specific transcription factors (GSTFs) and signaling genes (kinases and phosphatases). Genome-wide gene expression data for 63 single and double deletion mutants in baker's yeast reveals that the two most common genetic interaction patterns are buffering and inversion. Buffering is typically associated with redundancy and is well understood. In inversion, genes show opposite behavior in the double mutant compared to the corresponding single mutants. The underlying mechanism is poorly understood. Although both classes show buffering and inversion patterns, the prevalence of inversion is much stronger in GSTFs. To decipher potential mechanisms, a Petri Net modeling approach was employed, where genes are represented as nodes and relationships between genes as edges. This allowed over 9 million possible three and four node models to be exhaustively enumerated. The models show that a quantitative difference in interaction strength is a strict requirement for obtaining inversion. In addition, this difference is frequently accompanied with a second gene that shows buffering. Taken together, these results provide a mechanistic explanation for inversion. Furthermore, the ability of transcription factors to differentially regulate expression of their targets provides a likely explanation why inversion is more prevalent for GSTFs compared to kinases and phosphatases.

MOTIVATION: The scientific community urgently needs to standardize the exchange of biological data. This is helped by the use of a common protocol and the definition of shared data structures. We have based our standardization work on CORBA, a technology that has become a standard in the past years and allows interoperability between distributed objects. RESULTS: We have defined an IDL specification for genome maps and present it to the scientific community. We have implemented CORBA servers based on this IDL to distribute RHdb and HuGeMap maps. The IDL will co-evolve with the needs of the mapping community. AVAILABILITY: The standard IDL for genome maps is available at http:// corba.ebi.ac.uk/RHdb/EUCORBA/MapIDL.htm l. The IORs to browse maps from Infobiogen and EBI are at http://www.infobiogen.fr/services/Hugemap/IOR and http://corba.ebi.ac.uk/RHdb/EUCORBA/IOR CONTACT: [email protected], [email protected]