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.
Abstract. The arbuscular mycorrhizal (AM) association between terrestrial plants and soil fungi of the phylum Glomeromycota is the most widespread beneficial plant-microbe interaction on earth. In the course of the symbiosis, fungal hyphae colonise plant roots and supply limiting nutrients, in particular phosphorus, in exchange for carbon compounds. Owing to the obligate biotrophy of mycorrhizal fungi and the lack of genetic systems to study them, targeted molecular studies on AM symbioses proved to be difficult. With the emergence of plant genomics and the selection of suitable models, an application of untargeted expression profiling experiments became possible. In the model legume Medicago truncatula, high-throughput expressed sequence tag (EST)-sequencing in conjunction with in silico and experimental transcriptome profiling provided transcriptional snapshots that together defined the global genetic program activated during AM. Owing to an asynchronous development of the symbiosis, several hundred genes found to be activated during the symbiosis cannot be easily correlated with symbiotic structures, but the expression of selected genes has been extended to the cellular level to correlate gene expression with specific stages of AM development. These approaches identified marker genes for the AM symbiosis and provided the first insights into the molecular basis of gene expression regulation during AM.
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