Motivation: Although many next-generation sequencing (NGS) read preprocessing tools already existed, we could not find any tool or combination of tools that met our requirements in terms of flexibility, correct handling of paired-end data and high performance. We have developed Trimmomatic as a more flexible and efficient preprocessing tool, which could correctly handle paired-end data.Results: The value of NGS read preprocessing is demonstrated for both reference-based and reference-free tasks. Trimmomatic is shown to produce output that is at least competitive with, and in many cases superior to, that produced by other tools, in all scenarios tested.Availability and implementation: Trimmomatic is licensed under GPL V3. It is cross-platform (Java 1.5+ required) and available at http://www.usadellab.org/cms/index.php?page=trimmomaticContact: usadel@bio1.rwth-aachen.deSupplementary information: Supplementary data are available at Bioinformatics online.

Mitochondria and plastids (chloroplasts) are cell organelles of endosymbiotic origin that possess their own genetic information. Most organellar DNAs map as circular double-stranded genomes. Across the eukaryotic kingdom, organellar genomes display great size variation, ranging from ∼15 to 20 kb (the size of the mitochondrial genome in most animals) to >10 Mb (the size of the mitochondrial genome in some lineages of flowering plants). We have developed OrganellarGenomeDraw (OGDRAW), a suite of software tools that enable users to create high-quality visual representations of both circular and linear annotated genome sequences provided as GenBank files or accession numbers. Although all types of DNA sequences are accepted as input, the software has been specifically optimized to properly depict features of organellar genomes. A recent extension facilitates the plotting of quantitative gene expression data, such as transcript or protein abundance data, directly onto the genome map. OGDRAW has already become widely used and is available as a free web tool (http://ogdraw.mpimp-golm.mpg.de/). The core processing components can be downloaded as a Perl module, thus also allowing for convenient integration into custom processing pipelines.

Mitochondria and plastids are DNA-containing cell organelles whose genomes occur at high copy numbers per cell. Organellar genomes vary greatly in size ranging from approximately 15 kb for some animal mitochondrial genomes to more than 2 Mb for some plant mitochondrial genomes. The vast majority of organellar genomes map as circular molecules that are difficult to illustrate by available commercial or free software tools. Thus, published genome maps are extremely heterogeneous in design, often tediously drawn semi-manually and lack any consensus in display. Here, we present a new web-based tool, OrganellarGenomeDRAW (OGDRAW), which produces high-resolution custom graphical maps of DNA sequences as stored in standard GenBank format entries. GenBank data can be provided as either file uploads or accession numbers. The program is specially optimized for the display of chloroplast and mitochondrial genomes but can also be used to depict other circular DNA sequences. The design of the program core as a Perl module with an object-oriented interface allows easy integration into custom scripts.

Recent rapid advances in next generation RNA sequencing (RNA-Seq)-based provide researchers with unprecedentedly large data sets and open new perspectives in transcriptomics. Furthermore, RNA-Seq-based transcript profiling can be applied to non-model and newly discovered organisms because it does not require a predefined measuring platform (like e.g. microarrays). However, these novel technologies pose new challenges: the raw data need to be rigorously quality checked and filtered prior to analysis, and proper statistical methods have to be applied to extract biologically relevant information. Given the sheer volume of data, this is no trivial task and requires a combination of considerable technical resources along with bioinformatics expertise. To aid the individual researcher, we have developed RobiNA as an integrated solution that consolidates all steps of RNA-Seq-based differential gene-expression analysis in one user-friendly cross-platform application featuring a rich graphical user interface. RobiNA accepts raw FastQ files, SAM/BAM alignment files and counts tables as input. It supports quality checking, flexible filtering and statistical analysis of differential gene expression based on state-of-the art biostatistical methods developed in the R/Bioconductor projects. In-line help and a step-by-step manual guide users through the analysis. Installer packages for Mac OS X, Windows and Linux are available under the LGPL licence from http://mapman.gabipd.org/web/guest/robin.

SummaryThe specificity of intracellular signaling and developmental patterning in biological systems relies on selective interactions between different proteins in specific cellular compartments. The identification of such proteinprotein interactions is essential for unraveling complex signaling and regulatory networks. Recently, bimolecular fluorescence complementation (BiFC) has emerged as a powerful technique for the efficient detection of protein interactions in their native subcellular localization. Here we report significant technical advances in the methodology of plant BiFC. We describe a series of versatile BiFC vector sets that are fully compatible with previously generated vectors. The new vectors enable the generation of both C-terminal and N-terminal fusion proteins and carry optimized fluorescent protein genes that considerably improve the sensitivity of BiFC. Using these vectors, we describe a multicolor BiFC (mcBiFC) approach for the simultaneous visualization of multiple protein interactions in the same cell. Application to a protein interaction network acting in calciummediated signal transduction revealed the concurrent interaction of the protein kinase CIPK24 with the calcium sensors CBL1 and CBL10 at the plasma membrane and tonoplast, respectively. We have also visualized by mcBiFC the simultaneous formation of CBL1/CIPK1 and CBL9/CIPK1 protein complexes at the plasma membrane. Thus, mcBiFC provides a useful new tool for exploring complex regulatory networks in plants.

MapMan is a software tool that supports the visualization of profiling data sets in the context of existing knowledge. Scavenger modules generate hierarchical and essentially non-redundant gene ontologies ('mapping files'). An ImageAnnotator module visualizes the data on a gene-bygene basis on schematic diagrams ('maps') of biological processes. The PageMan module uses the same ontologies to statistically evaluate responses at the pathway or processes level. The generic structure of MapMan also allows it to be used for transcripts, proteins, enzymes and metabolites. MapMan was developed for use with Arabidopsis, but has already been extended for use with several other species. These tools are available as downloadable and web-based versions. After providing an introduction to the scope and use of MapMan, we present a case study where MapMan is used to analyse the transcriptional response of the crop plant maize to diurnal changes and an extension of the night. We then explain how MapMan can be customized to visually and systematically compare responses in maize and Arabidopsis. These analyses illustrate how MapMan can be used to analyse and compare global transcriptional responses between phylogenetically distant species, and show that analyses at the level of functional categories are especially useful in cross-species comparisons.

Next-generation technologies generate an overwhelming amount of gene sequence data. Efficient annotation tools are required to make these data amenable to functional genomics analyses. The Mercator pipeline automatically assigns functional terms to protein or nucleotide sequences. It uses the MapMan 'BIN' ontology, which is tailored for functional annotation of plant 'omics' data. The classification procedure performs parallel sequence searches against reference databases, compiles the results and computes the most likely MapMan BINs for each query. In the current version, the pipeline relies on manually curated reference classifications originating from the three reference organisms (Arabidopsis, Chlamydomonas, rice), various other plant species that have a reviewed SwissProt annotation, and more than 2000 protein domain and family profiles at InterPro, CDD and KOG. Functional annotations predicted by Mercator achieve accuracies above 90% when benchmarked against manual annotation. In addition to mapping files for direct use in the visualization software MapMan, Mercator provides graphical overview charts, detailed annotation information in a convenient web browser interface and a MapMan-to-GO translation table to export results as GO terms. Mercator is available free of charge via http://mapman.gabipd.org/web/guest/app/ Mercator.

SummaryPlastids (chloroplasts) possess an enormous capacity to synthesize and accumulate foreign proteins. Here we have maximized chloroplast protein production by over-expressing a proteinaceous antibiotic against pathogenic group A and group B streptococci from the plastid genome. The antibiotic, a phage lytic protein, accumulated to enormously high levels (>70% of the plant's total soluble protein), and proved to be extremely stable in chloroplasts. This massive over-expression exhausted the protein synthesis capacity of the chloroplast such that the production of endogenous plastid-encoded proteins was severely compromised. Our data suggest that this is due to translational rather than transcriptional limitation of gene expression. We also show that the chloroplast-produced protein antibiotic efficiently kills the target bacteria. These unrivaled expression levels, together with the chloroplast's insensitivity to enzymes that degrade bacterial cell walls and the elimination of the need to remove bacterial endotoxins by costly purification procedures, indicate that this is an effective plant-based production platform for next-generation antibiotics, which are urgently required to keep pace with rapidly emerging bacterial resistance.