Magnaporthe grisea is the most destructive pathogen of rice worldwide and the principal model organism for elucidating the molecular basis of fungal disease of plants. Here, we report the draft sequence of the M. grisea genome. Analysis of the gene set provides an insight into the adaptations required by a fungus to cause disease. The genome encodes a large and diverse set of secreted proteins, including those defined by unusual carbohydrate-binding domains. This fungus also possesses an expanded family of G-protein-coupled receptors, several new virulence-associated genes and large suites of enzymes involved in secondary metabolism. Consistent with a role in fungal pathogenesis, the expression of several of these genes is upregulated during the early stages of infection-related development. The M. grisea genome has been subject to invasion and proliferation of active transposable elements, reflecting the clonal nature of this fungus imposed by widespread rice cultivation.Outbreaks of rice blast disease are a serious and recurrent problem in all rice-growing regions of the world, and the disease is extremely difficult to control 1,2 . Rice blast, caused by the fungus Magnaporthe grisea, is therefore a significant economic and humanitarian problem. It is estimated that each year enough rice is destroyed by rice blast disease to feed 60 million people 3 . The life cycle of the rice blast fungus is shown in Fig. 1. Infections occur when fungal spores land and attach themselves to leaves using a special adhesive released from the tip of each spore 4 . The germinating spore develops an appressorium-a specialized infection cell-which generates enormous turgor pressure (up to 8 MPa) that ruptures the leaf cuticle, allowing invasion of the underlying leaf tissue 5,6 . Subsequent colonization of the leaf produces disease lesions from which the fungus sporulates and spreads to new plants. When rice blast infects young rice seedlings, whole plants often die, whereas spread of the disease to the stems, nodes or panicle of older plants results in nearly total loss of the rice grain 2 . Different host-limited forms of M. grisea also infect a broad range of grass species including wheat, barley and millet. Recent reports have shown that the fungus has the capacity to infect plant roots 7 .Here we present our preliminary analysis of the draft genome sequence of M. grisea, which has emerged as a model system for understanding plant-microbe interactions because of both its economic significance and genetic tractability 1,2 . Acquisition of the M. grisea genome sequenceThe genome of a rice pathogenic strain of M. grisea, 70-15, was sequenced through a whole-genome shotgun approach. In all, greater than sevenfold sequence coverage was produced, and a summary of the principal genome sequence data is provided in Table 1 and Supplementary Table S1. The draft genome sequence consists of 2,273 sequence contigs longer than 2 kilobases (kb), ordered and orientated within 159 scaffolds. The total length of all sequence contigs is 38.8 mega...

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Advancing technologies have facilitated the ever-widening application of genetic markers such as microsatellites into new systems and research questions in biology. In light of the data and experience accumulated from several years of using microsatellites, we present here a literature review that synthesizes the limitations of microsatellites in population genetic studies. With a focus on population structure, we review the widely used fixation (FST) statistics and Bayesian clustering algorithms and find that the former can be confusing and problematic for microsatellites and that the latter may be confounded by complex population models and lack power in certain cases. Clustering, multivariate analyses, and diversity-based statistics are increasingly being applied to infer population structure, but in some instances these methods lack formalization with microsatellites. Migration-specific methods perform well only under narrow constraints. We also examine the use of microsatellites for inferring effective population size, changes in population size, and deeper demographic history, and find that these methods are untested and/or highly context-dependent. Overall, each method possesses important weaknesses for use with microsatellites, and there are significant constraints on inferences commonly made using microsatellite markers in the areas of population structure, admixture, and effective population size. To ameliorate and better understand these constraints, researchers are encouraged to analyze simulated datasets both prior to and following data collection and analysis, the latter of which is formalized within the approximate Bayesian computation framework. We also examine trends in the literature and show that microsatellites continue to be widely used, especially in non-human subject areas. This review assists with study design and molecular marker selection, facilitates sound interpretation of microsatellite data while fostering respect for their practical limitations, and identifies lessons that could be applied toward emerging markers and high-throughput technologies in population genetics.

Aflatoxins produced by Aspergillus flavus are potent carcinogens that contaminate agricultural crops. Recent efforts to reduce aflatoxin concentrations in crops have focused on biological control using nonaflatoxigenic A. flavus strains AF36 (=NRRL 18543) and NRRL 21882 (the active component of afla-guard. However, the evolutionary potential of these strains to remain nonaflatoxigenic in nature is unknown. To elucidate the underlying population processes that influence aflatoxigenicity, we examined patterns of linkage disequilibrium (LD) spanning 21 regions in the aflatoxin gene cluster of A. flavus. We show that recombination events are unevenly distributed across the cluster in A. flavus. Six distinct LD blocks separate late pathway genes aflE, aflM, aflN, aflG, aflL, aflI and aflO, and there is no discernable evidence of recombination among early pathway genes aflA, aflB, aflC, aflD, aflR and aflS. The discordance in phylogenies inferred for the aflW/aflX intergenic region and two noncluster regions, tryptophan synthase and acetamidase, is indicative of trans-species evolution in the cluster. Additionally, polymorphisms in aflW/aflX divide A. flavus strains into two distinct clades, each harbouring only one of the two approved biocontrol strains. The clade with AF36 includes both aflatoxigenic and nonaflatoxigenic strains, whereas the clade with NRRL 21882 comprises only nonaflatoxigenic strains and includes all strains of A. flavus missing the entire gene cluster or with partial gene clusters. Our detection of LD blocks in partial clusters indicates that recombination may have played an important role in cluster disassembly, and multilocus coalescent analyses of cluster and noncluster regions indicate lineage-specific gene loss in A. flavus. These results have important implications in assessing the stability of biocontrol strains in nature.