Composite Medicago truncatula plants harbouring Agrobacterium rhizogenes-transformed roots reveal normal mycorrhization by Glomus intraradices

Composite plants consisting of a wild-type shoot and a transgenic root are frequently used for functional genomics in legume research. Although transformation of roots using Agrobacterium rhizogenes leads to morphologically normal roots, the question arises as to whether such roots interact with arbuscular mycorrhizal (AM) fungi in the same way as wild-type roots. To address this question, roots transformed with a vector containing the fluorescence marker DsRed were used to analyse AM in terms of mycorrhization rate, morphology of fungal and plant subcellular structures, as well as transcript and secondary metabolite accumulations. Mycorrhization rate, appearance, and developmental stages of arbuscules were identical in both types of roots. Using Mt16kOLI1Plus microarrays, transcript profiling of mycorrhizal roots showed that 222 and 73 genes exhibited at least a 2-fold induction and less than half of the expression, respectively, most of them described as AM regulated in the same direction in wild-type roots. To verify this, typical AM marker genes were analysed by quantitative reverse transcription-PCR and revealed equal transcript accumulation in transgenic and wild-type roots. Regarding secondary metabolites, several isoflavonoids and apocarotenoids, all known to accumulate in mycorrhizal wild-type roots, have been found to be up-regulated in mycorrhizal in comparison with non-mycorrhizal transgenic roots. This set of data revealed a substantial similarity in mycorrhization of transgenic and wild-type roots of Medicago truncatula, validating the use of composite plants for studying AM-related effects.

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.