MOTIVATION: The vast amount of already available and currently generated read mapping data requires comprehensive visualization, and should benefit from bioinformatics tools offering a wide spectrum of analysis functionality from just one source. Appropriate handling of multiple mapped reads during mapping analyses remains an issue that demands improvement. RESULTS: The capabilities of the read mapping analysis and visualization tool ReadXplorer were vastly enhanced. Here, we present an even finer granulated read mapping classification, improving the level of detail for analyses and visualizations. The spectrum of automatic analysis functions has been broadened to include genome rearrangement detection as well as correlation analysis between two mapping data sets. Existing functions were refined and enhanced, namely the computation of differentially expressed genes, the read count and normalization analysis and the transcription start site detection. Additionally, ReadXplorer 2 features a highly improved support for large eukaryotic data sets and a command line version, enabling its integration into workflows. Finally, the new version is now able to display any kind of tabular results from other bioinformatics tools. AVAILABILITY AND IMPLEMENTATION: http://www.readxplorer.org CONTACT: [email protected] information: Supplementary data are available at Bioinformatics online.

BACKGROUND: Third generation sequencing methods, like SMRT (Single Molecule, Real-Time) sequencing developed by Pacific Biosciences, offer much longer read length in comparison to Next Generation Sequencing (NGS) methods. Hence, they are well suited for de novo- or re-sequencing projects. Sequences generated for these purposes will not only contain reads originating from the nuclear genome, but also a significant amount of reads originating from the organelles of the target organism. These reads are usually discarded but they can also be used for an assembly of organellar replicons. The long read length supports resolution of repetitive regions and repeats within the organelles genome which might be problematic when just using short read data. Additionally, SMRT sequencing is less influenced by GC rich areas and by long stretches of the same base. RESULTS: We describe a workflow for a de novo assembly of the sugar beet (Beta vulgaris ssp. vulgaris) chloroplast genome sequence only based on data originating from a SMRT sequencing dataset targeted on its nuclear genome. We show that the data obtained from such an experiment are sufficient to create a high quality assembly with a higher reliability than assemblies derived from e.g. Illumina reads only. The chloroplast genome is especially challenging for de novo assembling as it contains two large inverted repeat (IR) regions. We also describe some limitations that still apply even though long reads are used for the assembly. CONCLUSIONS: SMRT sequencing reads extracted from a dataset created for nuclear genome (re)sequencing can be used to obtain a high quality de novo assembly of the chloroplast of the sequenced organism. Even with a relatively small overall coverage for the nuclear genome it is possible to collect more than enough reads to generate a high quality assembly that outperforms short read based assemblies. However, even with long reads it is not always possible to clarify the order of elements of a chloroplast genome sequence reliantly which we could demonstrate with Fosmid End Sequences (FES) generated with Sanger technology. Nevertheless, this limitation also applies to short read sequencing data but is reached in this case at a much earlier stage during finishing.

Abstract Summary: GABI-Kat SimpleSearch is a database of flanking sequence tags (FSTs) of T-DNA mutagenized Arabidopsis thaliana lines that were generated by the GABI-Kat project. Sequences flanking the T-DNA insertion sites were aligned to the A.thaliana genome sequence, annotated with information about the FST, the insertion site and the line from which the FST was derived. A web interface permits text-based as well as sequence-based searches for relevant insertions. GABI-Kat SimpleSearch aims to help biologists to quickly find T-DNA insertion mutants for their research. Availability: http://www.mpiz-koeln.mpg.de/GABI-Kat/ Contact: [email protected] * To whom correspondence should be addressed. † Present address: Max Planck Unit for Structural Molecular Biology, Notkestrasse 85, D-22607 Hamburg, Germany. ‡ Present address: Bielefeld University, Faculty of Biology, PO Box, D-33501 Bielefeld, Germany.