Peter Cock

Abstract Summary: The Biopython project is a mature open source international collaboration of volunteer developers, providing Python libraries for a wide range of bioinformatics problems. Biopython includes modules for reading and writing different sequence file formats and multiple sequence alignments, dealing with 3D macro molecular structures, interacting with common tools such as BLAST, ClustalW and EMBOSS, accessing key online databases, as well as providing numerical methods for statistical learning. Availability: Biopython is freely available, with documentation and source code at www.biopython.org under the Biopython license. Contact: All queries should be directed to the Biopython mailing lists, see www.biopython.org/wiki/_Mailing_listspeter.cock@scri.ac.uk.

FASTQ has emerged as a common file format for sharing sequencing read data combining both the sequence and an associated per base quality score, despite lacking any formal definition to date, and existing in at least three incompatible variants. This article defines the FASTQ format, covering the original Sanger standard, the Solexa/Illumina variants and conversion between them, based on publicly available information such as the MAQ documentation and conventions recently agreed by the Open Bioinformatics Foundation projects Biopython, BioPerl, BioRuby, BioJava and EMBOSS. Being an open access publication, it is hoped that this description, with the example files provided as Supplementary Data, will serve in future as a reference for this important file format.

The advent of second-generation sequencing (2GS) has provided a range of significant new challenges for the visualization of sequence assemblies. These include the large volume of data being generated, short-read lengths and different data types and data formats associated with the diversity of new sequencing technologies. This article illustrates how Tablet-a high-performance graphical viewer for visualization of 2GS assemblies and read mappings-plays an important role in the analysis of these data. We present Tablet, and through a selection of use cases, demonstrate its value in quality assurance and scientific discovery, through features such as whole-reference coverage overviews, variant highlighting, paired-end read mark-up, GFF3-based feature tracks and protein translations. We discuss the computing and visualization techniques utilized to provide a rich and responsive graphical environment that enables users to view a range of file formats with ease. Tablet installers can be freely downloaded from http://bioinf.hutton.ac.uk/tablet in 32 or 64-bit versions for Windows, OS X, Linux or Solaris. For further details on the Tablet, contact tablet@hutton.ac.uk.

Bursaphelenchus xylophilus is the nematode responsible for a devastating epidemic of pine wilt disease in Asia and Europe, and represents a recent, independent origin of plant parasitism in nematodes, ecologically and taxonomically distinct from other nematodes for which genomic data is available. As well as being an important pathogen, the B. xylophilus genome thus provides a unique opportunity to study the evolution and mechanism of plant parasitism. Here, we present a high-quality draft genome sequence from an inbred line of B. xylophilus, and use this to investigate the biological basis of its complex ecology which combines fungal feeding, plant parasitic and insect-associated stages. We focus particularly on putative parasitism genes as well as those linked to other key biological processes and demonstrate that B. xylophilus is well endowed with RNA interference effectors, peptidergic neurotransmitters (including the first description of ins genes in a parasite) stress response and developmental genes and has a contracted set of chemosensory receptors. B. xylophilus has the largest number of digestive proteases known for any nematode and displays expanded families of lysosome pathway genes, ABC transporters and cytochrome P450 pathway genes. This expansion in digestive and detoxification proteins may reflect the unusual diversity in foods it exploits and environments it encounters during its life cycle. In addition, B. xylophilus possesses a unique complement of plant cell wall modifying proteins acquired by horizontal gene transfer, underscoring the impact of this process on the evolution of plant parasitism by nematodes. Together with the lack of proteins homologous to effectors from other plant parasitic nematodes, this confirms the distinctive molecular basis of plant parasitism in the Bursaphelenchus lineage. The genome sequence of B. xylophilus adds to the diversity of genomic data for nematodes, and will be an important resource in understanding the biology of this unusual parasite.

RenSeq is a NB-LRR (nucleotide binding-site leucine-rich repeat) gene-targeted, Resistance gene enrichment and sequencing method that enables discovery and annotation of pathogen resistance gene family members in plant genome sequences. We successfully applied RenSeq to the sequenced potato Solanum tuberosum clone DM, and increased the number of identified NB-LRRs from 438 to 755. The majority of these identified R gene loci reside in poorly or previously unannotated regions of the genome. Sequence and positional details on the 12 chromosomes have been established for 704 NB-LRRs and can be accessed through a genome browser that we provide. We compared these NB-LRR genes and the corresponding oligonucleotide baits with the highest sequence similarity and demonstrated that ~80% sequence identity is sufficient for enrichment. Analysis of the sequenced tomato S. lycopersicum 'Heinz 1706' extended the NB-LRR complement to 394 loci. We further describe a methodology that applies RenSeq to rapidly identify molecular markers that co-segregate with a pathogen resistance trait of interest. In two independent segregating populations involving the wild Solanum species S. berthaultii (Rpi-ber2) and S. ruiz-ceballosii (Rpi-rzc1), we were able to apply RenSeq successfully to identify markers that co-segregate with resistance towards the late blight pathogen Phytophthora infestans. These SNP identification workflows were designed as easy-to-adapt Galaxy pipelines.