Powdery mildews are phytopathogens whose growth and reproduction are entirely dependent on living plant cells. The molecular basis of this life-style, obligate biotrophy, remains unknown. We present the genome analysis of barley powdery mildew, Blumeria graminis f.sp. hordei (Blumeria), as well as a comparison with the analysis of two powdery mildews pathogenic on dicotyledonous plants. These genomes display massive retrotransposon proliferation, genome-size expansion, and gene losses. The missing genes encode enzymes of primary and secondary metabolism, carbohydrate-active enzymes, and transporters, probably reflecting their redundancy in an exclusively biotrophic life-style. Among the 248 candidate effectors of pathogenesis identified in the Blumeria genome, very few (less than 10) define a core set conserved in all three mildews, suggesting that most effectors represent species-specific adaptations.
Biological pathways have become the standard way to represent the coordinated reactions and actions of a series of molecules in a cell. A series of interconnected pathways is referred to as a biological network, which denotes a more holistic view on the entanglement of cellular reactions. Biological pathways and networks are not only an appropriate approach to visualize molecular reactions. They have also become one leading method in -omics data analysis and visualization. Here, we review a set of pathway and network visualization and analysis methods and take a look at potential future developments in the field.
40Background 41 Mitochondria produce cellular energy in the form of ATP and are involved in various 42 metabolic and signaling processes. However, the cellular requirements for 43 mitochondria are different depending on cell type, cell state or organism. Information 44 on the expression dynamics of genes with mitochondrial functions (mito-genes) is 45 embedded in publicly available transcriptomic or proteomic studies and the variety of 46 available datasets enables us to study the expression dynamics of mito-genes in many 47 different cell types, conditions and organisms. Yet, we lack an easy way of extracting 48 these data for gene groups such as mito-genes. 49 50 Results 51 Here, we introduce the web-based visual data mining platform mitoXplorer, which 52 systematically integrates expression and mutation data of mito-genes. The central part 53 of mitoXplorer is a manually curated mitochondrial interactome containing ~1200 54 genes, which we have annotated in 35 different mitochondrial processes. This 55 mitochondrial interactome can be integrated with publicly available transcriptomic, 56 proteomic or mutation data in a user-centric manner. A set of analysis and visualization 57 tools allows the mining and exploration of mitochondrial expression dynamics and 58 mutations across various datasets from different organisms and to quantify the 59 adaptation of mitochondrial dynamics to different conditions. We apply mitoXplorer to 60 quantify expression changes of mito-genes of a set of aneuploid cell lines that carry 61 an extra copy of chromosome 21. mitoXplorer uncovers remarkable differences in the 62 regulation of the mitochondrial transcriptome and proteome due to the dysregulation 63 of the mitochondrial ribosome in retinal pigment epithelial trisomy 21 cells which 64 results in severe defects in oxidative phosphorylation. 65 3 66Conclusions 67 We demonstrate the power of the visual data mining platform mitoXplorer to explore 68 expression data in a focused and detailed way to uncover underlying potential 69 mechanisms for further experimental studies. We validate the hypothesis-creating 70 power of mitoXplorer by testing predicted phenotypes in trisomy 21 model systems. 71 MitoXplorer is freely available at http://mitoxplorer.ibdm.univ-mrs.fr. MitoXplorer does 72 not require installation nor programming knowledge and is web-based. Therefore, 73 mitoXplorer is accessible to a wide audience of experimental experts studying 74 mitochondrial dynamics. 75 76 77 4
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