Laser microdissection of Arabidopsis cells at the powdery mildew infection site reveals site-specific processes and regulators.

To elucidate host processes and components required for the sustained growth and reproduction of the obligate biotrophic fungus Golovinomyces orontii on Arabidopsis thaliana, laser microdissection was used to isolate cells at the site of infection at 5 days postinfection for downstream global Arabidopsis expression profiling. Site-specific profiling increased sensitivity dramatically, allowing us to identify specific host processes, process components, and their putative regulators hidden in previous whole-leaf global expression analyses. For example, 67 transcription factors exhibited altered expression at the powdery mildew (PM) infection site, with subsets of these playing known or inferred roles in photosynthesis, cold/dehydration responses, defense, auxin signaling, and the cell cycle. Using integrated informatics analyses, we constructed putative regulatory networks for a subset of these processes and provided strong support for host cell cycle modulation at the PM infection site. Further experimentation revealed induced host endoreduplication occurred exclusively at the infection site and led us to identify MYB3R4 as a transcriptional regulator of this process. Induced endoreduplication was abrogated in myb3r4 mutants, and G. orontii growth and reproduction were reduced. This suggests that, by increasing gene copy number, localized endoreduplication serves as a mechanism to meet the enhanced metabolic demands imposed by the fungus, which acquires all its nutrients from the plant host.

EMMA 2--a MAGE-compliant system for the collaborative analysis and integration of microarray data.

BACKGROUND: Understanding transcriptional regulation by genome-wide microarray studies can contribute to unravel complex relationships between genes. Attempts to standardize the annotation of microarray data include the Minimum Information About a Microarray Experiment (MIAME) recommendations, the MAGE-ML format for data interchange, and the use of controlled vocabularies or ontologies. The existing software systems for microarray data analysis implement the mentioned standards only partially and are often hard to use and extend. Integration of genomic annotation data and other sources of external knowledge using open standards is therefore a key requirement for future integrated analysis systems. RESULTS: The EMMA 2 software has been designed to resolve shortcomings with respect to full MAGE-ML and ontology support and makes use of modern data integration techniques. We present a software system that features comprehensive data analysis functions for spotted arrays, and for the most common synthesized oligo arrays such as Agilent, Affymetrix and NimbleGen. The system is based on the full MAGE object model. Analysis functionality is based on R and Bioconductor packages and can make use of a compute cluster for distributed services. CONCLUSION: Our model-driven approach for automatically implementing a full MAGE object model provides high flexibility and compatibility. Data integration via SOAP-based web-services is advantageous in a distributed client-server environment as the collaborative analysis of microarray data is gaining more and more relevance in international research consortia. The adequacy of the EMMA 2 software design and implementation has been proven by its application in many distributed functional genomics projects. Its scalability makes the current architecture suited for extensions towards future transcriptomics methods based on high-throughput sequencing approaches which have much higher computational requirements than microarrays.