The appropriate development of conidia and appressoria is critical in the disease cycle of many fungal pathogens, including Magnaporthe oryzae. A total of eight genes (MoHOX1 to MoHOX8) encoding putative homeobox transcription factors (TFs) were identified from the M. oryzae genome. Knockout mutants for each MoHOX gene were obtained via homology-dependent gene replacement. Two mutants, ΔMohox3 and ΔMohox5, exhibited no difference to wild-type in growth, conidiation, conidium size, conidial germination, appressorium formation, and pathogenicity. However, the ΔMohox1 showed a dramatic reduction in hyphal growth and increase in melanin pigmentation, compared to those in wild-type. ΔMohox4 and ΔMohox6 showed significantly reduced conidium size and hyphal growth, respectively. ΔMohox8 formed normal appressoria, but failed in pathogenicity, probably due to defects in the development of penetration peg and invasive growth. It is most notable that asexual reproduction was completely abolished in ΔMohox2, in which no conidia formed. ΔMohox2 was still pathogenic through hypha-driven appressoria in a manner similar to that of the wild-type. However, ΔMohox7 was unable to form appressoria either on conidial germ tubes, or at hyphal tips, being non-pathogenic. These factors indicate that M. oryzae is able to cause foliar disease via hyphal appressorium-mediated penetration, and MoHOX7 is mutually required to drive appressorium formation from hyphae and germ tubes. Transcriptional analyses suggest that the functioning of M. oryzae homeobox TFs is mediated through the regulation of gene expression and is affected by cAMP and Ca2+ signaling and/or MAPK pathways. The divergent roles of this gene set may help reveal how the genome and regulatory pathways evolved within the rice blast pathogen and close relatives.

Rapid translation of genome sequences into meaningful biological information hinges on the integration of multiple experimental and informatics methods into a cohesive platform. Despite the explosion in the number of genome sequences available, such a platform does not exist for filamentous fungi. Here we present the development and application of a functional genomics and informatics platform for a model plant pathogenic fungus, Magnaporthe oryzae. In total, we produced 21,070 mutants through large-scale insertional mutagenesis using Agrobacterium tumefaciens-mediated transformation. We used a high-throughput phenotype screening pipeline to detect disruption of seven phenotypes encompassing the fungal life cycle and identified the mutated gene and the nature of mutation for each mutant. Comparative analysis of phenotypes and genotypes of the mutants uncovered 202 new pathogenicity loci. Our findings demonstrate the effectiveness of our platform and provide new insights on the molecular basis of fungal pathogenesis. Our approach promises comprehensive functional genomics in filamentous fungi and beyond.

All data described in this study can be browsed through the FTFD web site at http://ftfd.snu.ac.kr/.

Since the completion of the Saccharomyces cerevisiae genome sequencing project in 1996, the genomes of over 80 fungal species have been sequenced or are currently being sequenced. Resulting data provide opportunities for studying and comparing fungal biology and evolution at the genome level. To support such studies, the Comparative Fungal Genomics Platform (CFGP; http://cfgp.snu.ac.kr), a web-based multifunctional informatics workbench, was developed. The CFGP comprises three layers, including the basal layer, middleware and the user interface. The data warehouse in the basal layer contains standardized genome sequences of 65 fungal species. The middleware processes queries via six analysis tools, including BLAST, ClustalW, InterProScan, SignalP 3.0, PSORT II and a newly developed tool named BLASTMatrix. The BLASTMatrix permits the identification and visualization of genes homologous to a query across multiple species. The Data-driven User Interface (DUI) of the CFGP was built on a new concept of pre-collecting data and post-executing analysis instead of the ‘fill-in-the-form-and-press-SUBMIT’ user interfaces utilized by most bioinformatics sites. A tool termed Favorite, which supports the management of encapsulated sequence data and provides a personalized data repository to users, is another novel feature in the DUI.