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Abstract Background Organisms use highly accurate molecular processes to transcribe their genes and a variety of mRNA quality control and ribosome proofreading mechanisms to maintain intact the fidelity of genetic information flow. Despite this, low level gene translational errors induced by mutations and environmental factors cause neurodegeneration and premature death in mice and mitochondrial disorders in humans. Paradoxically, such errors can generate advantageous phenotypic diversity in fungi and bacteria through poorly understood molecular processes. Results In order to clarify the biological relevance of gene translational errors we have engineered codon misreading in yeast and used profiling of total and polysome-associated mRNAs, molecular and biochemical tools to characterize the recombinant cells. We demonstrate here that gene translational errors, which have negligible impact on yeast growth rate down-regulate protein synthesis, activate the unfolded protein response and environmental stress response pathways, and down-regulate chaperones linked to ribosomes. Conclusions We provide the first global view of transcriptional and post-transcriptional responses to global gene translational errors and we postulate that they cause gradual cell degeneration through synergistic effects of overloading protein quality control systems and deregulation of protein synthesis, but generate adaptive phenotypes in unicellular organisms through activation of stress cross-protection. We conclude that these genome wide gene translational infidelities can be degenerative or adaptive depending on cellular context and physiological condition.

Abstract Background Ontologies have become an essential asset in the bioinformatics toolbox and a number of ontology access resources are now available, for example, the EBI Ontology Lookup Service (OLS) and the NCBO BioPortal. However, these resources differ substantially in mode, ease of access, and ontology content. This makes it relatively difficult to access each ontology source separately, map their contents to research data, and much of this effort is being replicated across different research groups. Results OntoCAT provides a seamless programming interface to query heterogeneous ontology resources including OLS and BioPortal, as well as user-specified local OWL and OBO files. Each resource is wrapped behind easy to learn Java, Bioconductor/R and REST web service commands enabling reuse and integration of ontology software efforts despite variation in technologies. It is also available as a stand-alone MOLGENIS database and a Google App Engine application. Conclusions OntoCAT provides a robust, configurable solution for accessing ontology terms specified locally and from remote services, is available as a stand-alone tool and has been tested thoroughly in the ArrayExpress, MOLGENIS, EFO and Gen2Phen phenotype use cases. Availability http://www.ontocat.org

ArrayExpress is a public resource for microarray data that has two major goals: to serve as an archive providing access to microarray data supporting publications and to build a knowledge base of gene expression profiles. ArrayExpress consists of two tightly integrated databases: ArrayExpress repository, which is an archive, and ArrayExpress data warehouse, which contains reannotated data and is optimized for queries. As of December 2005, ArrayExpress contains gene expression and other microarray data from almost 35,000 hybridizations, comprising over 1200 studies, covering 70 different species. Most data are related to peer-reviewed publications. Password-protected access to prepublication data is provided for reviewers and authors. Data in the repository can be queried by various parameters such as species, authors, or words used in the experiment description. The data warehouse provides a wide range of queries, including ones based on gene and sample properties, and provides capabilities to retrieve data combined from different studies. The ArrayExpress resource also includes Expression Profiler (EP)-a microarray data mining, analysis, and visualization tool-and MIAMExpress-an online data submission tool. This chapter describes all major ArrayExpress components from the user perspective: how to submit to, retrieve from, and analyze data in ArrayExpress.