Fusarium genome

A successful collaboration both on the fungal and wheat side between BOKU researchers and bioinformatics experts from the TU Munich (previously F3705) has been established in previous funding periods. The project is led and coordinated by Prof. Hans-Werner MEWES, the task leaders for wheat and Fusarium are Dr. Klaus F. X. MAYER und Dr. Ulrich GÜLDENER, respectively. Resequencing of F. graminearum, a new assembly and manual annotation efforts supported by RNA-Seq data will result in an update of the primary F. graminearum PH-1 GenBank submission, resolving annotation version conflicts and therefore improving genome analysis for the whole Fusarium community. The updated version will also be distributed to available third party resources (FungiDB, JGI, etc). The inventory on secondary metabolite gene clusters will be extended to all available Fusarium genomes. The genome sequence of F. torulosum will be annotated and the genome sequences of NX-producing F. graminearum and Austrian isolates will be investigated. Gene expression and ChIP-Seq data generated by partners (F3702, F3703) will be analysed and further integrated in genome browsers and the RNA-Seq ExpressionBrowser. The recent draft genome annotation of hexaploid bread wheat (version 2.2) comprises around 100,000 high confidence genes and an even significantly larger number when considering pseudogenes, gene fragments, and orphan genes (lacking homology support). In previous work we have characterized the effects of the Fhb1 and Qfhs.ifa-5A QTLs on highthroughput transcriptome data in collaboration with F3711 and the scoring of treatment differences in metabolomics time course data (with F3706/15). Integrative analysis and application of network-based methods for clustering data and extracting genes and metabolites of interest will be continued. During project phase II F3711 has established the F. graminearum response transcriptomes of an association mapping panel, which will be analyzed in close collaboration. We aim to use these data to construct a gene co-expression network and combine it with the initially generated cis and trans regulated eQTL data to infer functional connections of map positions and genes relevant for F. graminearum resistance. Partner F3702 will be supported in the analysis of the very large family of glutathione-Stransferases to identify candidate genes for DON detoxification. Dissecting the ChIP-Seq data as generated by F3703 we will characterize how biotic stress, i.e. treatment with F. graminearum, affects the landscape of chromatin modifications in bread wheat.