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Abstract Background MicroRNAs (miRNAs), short ~21-nucleotide RNA molecules, play an important role in post-transcriptional regulation of gene expression. The number of known miRNA hairpins registered in the miRBase database is rapidly increasing, but recent reports suggest that many miRNAs with restricted temporal or tissue-specific expression remain undiscovered. Various strategies for in silico miRNA identification have been proposed to facilitate miRNA discovery. Notably support vector machine (SVM) methods have recently gained popularity. However, a drawback of these methods is that they do not provide insight into the biological properties of miRNA sequences. Results We here propose a new strategy for miRNA hairpin prediction in which the likelihood that a genomic hairpin is a true miRNA hairpin is evaluated based on statistical distributions of observed biological variation of properties (descriptors) of known miRNA hairpins. These distributions are transformed into a single and continuous outcome classifier called the L score. Using a dataset of known miRNA hairpins from the miRBase database and an exhaustive set of genomic hairpins identified in the genome of Caenorhabditis elegans, a subset of 18 most informative descriptors was selected after detailed analysis of correlation among and discriminative power of individual descriptors. We show that the majority of previously identified miRNA hairpins have high L scores, that the method outperforms miRNA prediction by threshold filtering and that it is more transparent than SVM classifiers. Conclusion The L score is applicable as a prediction classifier with high sensitivity for novel miRNA hairpins. The L-score approach can be used to rank and select interesting miRNA hairpin candidates for downstream experimental analysis when coupled to a genome-wide set of in silico-identified hairpins or to facilitate the analysis of large sets of putative miRNA hairpin loci obtained in deep-sequencing efforts of small RNAs. Moreover, the in-depth analyses of miRNA hairpins descriptors preceding and determining the L score outcome could be used as an extension to miRBase entries to help increase the reliability and biological relevance of the miRNA registry.

Abstract Background Modern omics research involves the application of high-throughput technologies that generate vast volumes of data. These data need to be pre-processed, analyzed and integrated with existing knowledge through the use of diverse sets of software tools, models and databases. The analyses are often interdependent and chained together to form complex workflows or pipelines. Given the volume of the data used and the multitude of computational resources available, specialized pipeline software is required to make high-throughput analysis of large-scale omics datasets feasible. Results We have developed a generic pipeline system called Cyrille2. The system is modular in design and consists of three functionally distinct parts: 1) a web based, graphical user interface (GUI) that enables a pipeline operator to manage the system; 2) the Scheduler, which forms the functional core of the system and which tracks what data enters the system and determines what jobs must be scheduled for execution, and; 3) the Executor, which searches for scheduled jobs and executes these on a compute cluster. Conclusion The Cyrille2 system is an extensible, modular system, implementing the stated requirements. Cyrille2 enables easy creation and execution of high throughput, flexible bioinformatics pipelines.

The plant-pathogenic fungus Mycosphaerella graminicola (asexual stage: Septoria tritici) causes septoria tritici blotch, a disease that greatly reduces the yield and quality of wheat. This disease is economically important in most wheat-growing areas worldwide and threatens global food production. Control of the disease has been hampered by a limited understanding of the genetic and biochemical bases of pathogenicity, including mechanisms of infection and of resistance in the host. Unlike most other plant pathogens, M. graminicola has a long latent period during which it evades host defenses. Although this type of stealth pathogenicity occurs commonly in Mycosphaerella and other Dothideomycetes, the largest class of plant-pathogenic fungi, its genetic basis is not known. To address this problem, the genome of M. graminicola was sequenced completely. The finished genome contains 21 chromosomes, eight of which could be lost with no visible effect on the fungus and thus are dispensable. This eight-chromosome dispensome is dynamic in field and progeny isolates, is different from the core genome in gene and repeat content, and appears to have originated by ancient horizontal transfer from an unknown donor. Synteny plots of the M. graminicola chromosomes versus those of the only other sequenced Dothideomycete, Stagonospora nodorum, revealed conservation of gene content but not order or orientation, suggesting a high rate of intra-chromosomal rearrangement in one or both species. This observed "mesosynteny" is very different from synteny seen between other organisms. A surprising feature of the M. graminicola genome compared to other sequenced plant pathogens was that it contained very few genes for enzymes that break down plant cell walls, which was more similar to endophytes than to pathogens. The stealth pathogenesis of M. graminicola probably involves degradation of proteins rather than carbohydrates to evade host defenses during the biotrophic stage of infection and may have evolved from endophytic ancestors.

The Gene Ontology (GO) is a widely used controlled vocabulary for the description of gene function. In this study we quantify the usage of multiple and hierarchically independent GO terms in the curated genome annotations of seven well-studied species. In most genomes, significant proportions (6–60%) of genes have been annotated with multiple and hierarchically independent terms. This may be necessary to attain adequate specificity of description. One noticeable exception is Arabidopsis thaliana, in which genes are much less frequently annotated with multiple terms (6–14%). In contrast, an analysis of the occurrence of InterPro hits in the proteomes of the seven species, followed by a mapping of the hits to GO terms, did not reveal an aberrant pattern for the A. thaliana genome. This study shows the widespread usage of multiple hierarchically independent GO terms in the functional annotation of genes. By consequence, probabilistic methods that aim to predict gene function automatically through integration of diverse genomic datasets, and that employ the GO, must be able to predict such multiple terms. We attribute the low frequency with which multiple GO terms are used in Arabidopsis to deviating practices in the genome annotation and curation process between communities of annotators. This may bias genome-scale comparisons of gene function between different species. GO term assignment should therefore be performed according to strictly similar rules and standards. [ABSTRACT FROM AUTHOR]

With the rapid expansion of the application of genomics and sequencing in plant breeding, there is a constant drive for better reference genomes. In potato ( Solanum tuberosum ), the third largest food crop in the world, the related species S. phureja , designated "DM", has been used as the most popular reference genome for the last 10 years. Here, we introduce the de novo sequenced genome of Solyntus as the next standard reference in potato genome studies. A true Solanum tuberosum made up of 116 contigs that is also highly homozygous, diploid, vigorous and self-compatible, Solyntus provides a more direct and contiguous reference then ever before available. It was constructed by sequencing with state-of-the-art long and short read technology and assembled with Canu. The 116 contigs were assembled into scaffolds to form each pseudochromosome, with three contigs to 17 contigs per chromosome. This assembly contains 93.7% of the single-copy gene orthologs from the Solanaceae set and has an N50 of 63.7 Mbp. The genome and related files can be found at https://www.plantbreeding.wur.nl/Solyntus/ With the release of this research line and its draft genome we anticipate many exciting developments in (diploid) potato research., (Copyright © 2020 van Lieshout et al.)

Pseudogenes are genes with significant homology to functional genes, but contain disruptive mutations (DMs) leading to the production of non- or partially functional proteins. Little is known about pseudogenization in pathogenic fungi with different lifestyles. Here, we report the identification of DMs causing pseudogenes in the genomes of the fungal plant pathogens Botrytis cinerea, Cladosporium fulvum, Dothistroma septosporum, Mycosphaerella fijiensis, Verticillium dahliae and Zymoseptoria tritici. In these fungi, we identified 1740 gene models containing 2795 DMs obtained by an alignment-based gene prediction method. The contribution of sequencing errors to DMs was minimized by analyses of resequenced genomes to obtain a refined dataset of 924 gene models containing 1666 true DMs. The frequency of pseudogenes varied from 1% to 5% in the gene catalogues of these fungi, being the highest in the asexually reproducing fungus C. fulvum (4.9%), followed by D. septosporum (2.4%) and V. dahliae (2.1%). The majority of pseudogenes do not represent recent gene duplications, but members of multi-gene families and unitary genes. In general, there was no bias for pseudogenization of specific genes in the six fungi. Single exceptions were those encoding secreted proteins, including proteases, which appeared more frequently pseudogenized in C. fulvum than in D. septosporum. Most pseudogenes present in these two phylogenetically closely related fungi are not shared, suggesting that they are related to adaptation to a different host (tomato versus pine) and lifestyle (biotroph versus hemibiotroph)., (© 2013 BSPP AND JOHN WILEY & SONS LTD.)