Genome sequencing and transcript analysis of Hemileia vastatrix reveal expression dynamics of candidate effectors dependent on host compatibility.

Coffee leaf rust caused by the fungus Hemileia vastatrix is one of the most important leaf diseases of coffee plantations worldwide. Current knowledge of the H. vastatrix genome is limited and only a small fraction of the total fungal secretome has been identified. In order to obtain a more comprehensive understanding of its secretome, we aimed to sequence and assemble the entire H. vastatrix genome using two next-generation sequencing platforms and a hybrid assembly strategy. This resulted in a 547 Mb genome of H. vastatrix race XXXIII (Hv33), with 13,364 predicted genes that encode 13,034 putative proteins with transcriptomic support. Based on this proteome, 615 proteins contain putative secretion peptides, and lack transmembrane domains. From this putative secretome, 111 proteins were identified as candidate effectors (EHv33) unique to H. vastatrix, and a subset consisting of 17 EHv33 genes was selected for a temporal gene expression analysis during infection. Five genes were significantly induced early during an incompatible interaction, indicating their potential role as pre-haustorial effectors possibly recognized by the resistant coffee genotype. Another nine genes were significantly induced after haustorium formation in the compatible interaction. Overall, we suggest that this fungus is able to selectively mount its survival strategy with effectors that depend on the host genotype involved in the infection process

Genome-wide transcriptional profiling of appressorium development by the rice blast fungus Magnaporthe oryzae.

addresses: College of Life and Environmental Sciences, University of Exeter, Exeter, United Kingdom.notes: PMCID: PMC3276559The rice blast fungus Magnaporthe oryzae is one of the most significant pathogens affecting global food security. To cause rice blast disease the fungus elaborates a specialised infection structure called an appressorium. Here, we report genome wide transcriptional profile analysis of appressorium development using next generation sequencing (NGS). We performed both RNA-Seq and High-Throughput SuperSAGE analysis to compare the utility of these procedures for identifying differential gene expression in M. oryzae. We then analysed global patterns of gene expression during appressorium development. We show evidence for large-scale gene expression changes, highlighting the role of autophagy, lipid metabolism and melanin biosynthesis in appressorium differentiation. We reveal the role of the Pmk1 MAP kinase as a key global regulator of appressorium-associated gene expression. We also provide evidence for differential expression of transporter-encoding gene families and specific high level expression of genes involved in quinate uptake and utilization, consistent with pathogen-mediated perturbation of host metabolism during plant infection. When considered together, these data provide a comprehensive high-resolution analysis of gene expression changes associated with cellular differentiation that will provide a key resource for understanding the biology of rice blast disease

Transcriptome profiling of the rice blast fungus during invasive plant infection and in vitro stresses

<p>Abstract</p> <p>Background</p> <p>Rice blast is the most threatening disease to cultivated rice. <it>Magnaporthe oryzae</it>, its causal agent, is likely to encounter environmental challenges during invasive growth in its host plants that require shifts in gene expression to establish a compatible interaction. Here, we tested the hypothesis that gene expression patterns during <it>in planta </it>invasive growth are similar to <it>in vitro </it>stress conditions, such as nutrient limitation, temperature up shift and oxidative stress, and determined which condition most closely mimicked that of <it>in planta </it>invasive growth. Gene expression data were collected from these <it>in vitro </it>experiments and compared to fungal gene expression during the invasive growth phase at 72 hours post-inoculation in compatible interactions on two grass hosts, rice and barley.</p> <p>Results</p> <p>We identified 4,973 genes that were differentially expressed in at least one of the <it>in planta </it>and <it>in vitro </it>stress conditions when compared to fungal mycelia grown in complete medium, which was used as reference. From those genes, 1,909 showed similar expression patterns between at least one of the <it>in vitro </it>stresses and rice and/or barley. Hierarchical clustering of these 1,909 genes showed three major clusters in which <it>in planta </it>conditions closely grouped with the nutrient starvation conditions. Out of these 1,909 genes, 55 genes and 129 genes were induced and repressed in all treatments, respectively. Functional categorization of the 55 induced genes revealed that most were either related to carbon metabolism, membrane proteins, or were involved in oxidoreduction reactions. The 129 repressed genes showed putative roles in vesicle trafficking, signal transduction, nitrogen metabolism, or molecular transport.</p> <p>Conclusions</p> <p>These findings suggest that <it>M. oryzae </it>is likely primarily coping with nutrient-limited environments at the invasive growth stage 72 hours post-inoculation, and not with oxidative or temperature stresses.</p

Genome of Herbaspirillum seropedicae Strain SmR1, a Specialized Diazotrophic Endophyte of Tropical Grasses

The molecular mechanisms of plant recognition, colonization, and nutrient exchange between diazotrophic endophytes and plants are scarcely known. Herbaspirillum seropedicae is an endophytic bacterium capable of colonizing intercellular spaces of grasses such as rice and sugar cane. The genome of H. seropedicae strain SmR1 was sequenced and annotated by The Paraná State Genome Programme—GENOPAR. The genome is composed of a circular chromosome of 5,513,887 bp and contains a total of 4,804 genes. The genome sequence revealed that H. seropedicae is a highly versatile microorganism with capacity to metabolize a wide range of carbon and nitrogen sources and with possession of four distinct terminal oxidases. The genome contains a multitude of protein secretion systems, including type I, type II, type III, type V, and type VI secretion systems, and type IV pili, suggesting a high potential to interact with host plants. H. seropedicae is able to synthesize indole acetic acid as reflected by the four IAA biosynthetic pathways present. A gene coding for ACC deaminase, which may be involved in modulating the associated plant ethylene-signaling pathway, is also present. Genes for hemagglutinins/hemolysins/adhesins were found and may play a role in plant cell surface adhesion. These features may endow H. seropedicae with the ability to establish an endophytic life-style in a large number of plant species

eulerAPE: Drawing Area-proportional 3-Venn Diagrams Using Ellipses

Venn diagrams with three curves are used extensively in various medical and scientific disciplines to visualize relationships between data sets and facilitate data analysis. The area of the regions formed by the overlapping curves is often directly proportional to the cardinality of the depicted set relation or any other related quantitative data. Drawing these diagrams manually is difficult and current automatic drawing methods do not always produce appropriate diagrams. Most methods depict the data sets as circles, as they perceptually pop out as complete distinct objects due to their smoothness and regularity. However, circles cannot draw accurate diagrams for most 3-set data and so the generated diagrams often have misleading region areas. Other methods use polygons to draw accurate diagrams. However, polygons are non-smooth and non-symmetric, so the curves are not easily distinguishable and the diagrams are difficult to comprehend. Ellipses are more flexible than circles and are similarly smooth, but none of the current automatic drawing methods use ellipses. We present eulerAPE as the first method and software that uses ellipses for automatically drawing accurate area-proportional Venn diagrams for 3-set data. We describe the drawing method adopted by eulerAPE and we discuss our evaluation of the effectiveness of eulerAPE and ellipses for drawing random 3-set data. We compare eulerAPE and various other methods that are currently available and we discuss differences between their generated diagrams in terms of accuracy and ease of understanding for real world data