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Background Ongoing innovation in phylogenetics and evolutionary biology has been accompanied by a proliferation of software tools, data formats, analytical techniques and web servers. This brings with it the challenge of integrating phylogenetic and other related biological data found in a wide variety of formats, and underlines the need for reusable software that can read, manipulate and transform this information into the various forms required to build computational pipelines. Results We built a Python software library for working with phylogenetic data that is tightly integrated with Biopython, a broad-ranging toolkit for computational biology. Our library, Bio.Phylo, is highly interoperable with existing libraries, tools and standards, and is capable of parsing common file formats for phylogenetic trees, performing basic transformations and manipulations, attaching rich annotations, and visualizing trees. We unified the modules for working with the standard file formats Newick, NEXUS and phyloXML behind a consistent and simple API, providing a common set of functionality independent of the data source. Conclusions Bio.Phylo meets a growing need in bioinformatics for working with heterogeneous types of phylogenetic data. By supporting interoperability with multiple file formats and leveraging existing Biopython features, this library simplifies the construction of phylogenetic workflows. We also provide examples of the benefits of building a community around a shared open-source project. Bio.Phylo is included with Biopython, available through the Biopython website, http://biopython.org .

Background The potato genome sequence derived from the Solanum tuberosum Group Phureja clone DM1-3 516 R44 provides unparalleled insight into the genome composition and organisation of this important crop. A key class of genes that comprises the vast majority of plant resistance ( R ) genes contains a nucleotide-binding and leucine-rich repeat domain, and is collectively known as NB-LRRs. Results As part of an effort to accelerate the process of functional R gene isolation, we performed an amino acid motif based search of the annotated potato genome and identified 438 NB-LRR type genes among the ~39,000 potato gene models. Of the predicted genes, 77 contain an N-terminal toll/interleukin 1 receptor (TIR)-like domain, and 107 of the remaining 361 non-TIR genes contain an N-terminal coiled-coil (CC) domain. Physical map positions were established for 370 predicted NB-LRR genes across all 12 potato chromosomes. The majority of NB-LRRs are physically organised within 63 identified clusters, of which 50 are homogeneous in that they contain NB-LRRs derived from a recent common ancestor. Conclusions By establishing the phylogenetic and positional relationship of potato NB-LRRs, our analysis offers significant insight into the evolution of potato R genes. Furthermore, the data provide a blueprint for future efforts to identify and more rapidly clone functional NB-LRR genes from Solanum species.

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.

The Galaxy Project offers the popular web browser-based platform Galaxy for running bioinformatics tools and constructing simple workflows. Here, we present a broad collection of additional Galaxy tools for large scale analysis of gene and protein sequences. The motivating research theme is the identification of specific genes of interest in a range of non-model organisms, and our central example is the identification and prediction of \"effector\" proteins produced by plant pathogens in order to manipulate their host plant. This functional annotation of a pathogen's predicted capacity for virulence is a key step in translating sequence data into potential applications in plant pathology. This collection includes novel tools, and widely-used third-party tools such as NCBI BLAST+ wrapped for use within Galaxy. Individual bioinformatics software tools are typically available separately as standalone packages, or in online browser-based form. The Galaxy framework enables the user to combine these and other tools to automate organism scale analyses as workflows, without demanding familiarity with command line tools and scripting. Workflows created using Galaxy can be saved and are reusable, so may be distributed within and between research groups, facilitating the construction of a set of standardised, reusable bioinformatic protocols. The Galaxy tools and workflows described in this manuscript are open source and freely available from the Galaxy Tool Shed (http://usegalaxy.org/toolshed or http://toolshed.g2.bx.psu.edu).

A coupled cell network describes interacting (coupled) individual systems (cells). As in networks from real applications, coupled cell networks can represent inhomogeneous networks where different types of cells interact with each other in different ways, which can be represented graphically by different symbols, or abstractly by equivalence relations. Various synchronous behaviors, from full synchrony to partial synchrony, can be observed for a given network. Patterns of synchrony, which do not depend on specific dynamics of the network, but only on the network structure, are associated with a special type of partition of cells, termed balanced equivalence relations. Algorithms in Aldis [J. W. Aldis, Internat. J. Bifur. Chaos Appl. Sci. Engrg., 18 (2008), pp. 407--427] and Belykh and Hasler [I. Belykh and M. Hasler, Chaos, 21 (2011), 016106] find the unique pattern of synchrony with the fewest clusters. In this paper, we compute the set of all possible patterns of synchrony and show their hierarchy structure as a complete lattice. We represent the network structure of a given coupled cell network by a symbolic adjacency matrix encoding the different coupling types. We show that balanced equivalence relations can be determined by a matrix computation on the adjacency matrix which forms a block structure for each balanced equivalence relation. This leads to a computer algorithm to search for all possible balanced equivalence relations. Our computer program outputs the balanced equivalence relations, quotient matrices, and a complete lattice for user specified coupled cell networks. Finding the balanced equivalence relations of any network of up to 15 nodes is tractable, but for larger networks this depends on the pattern of synchrony with the fewest clusters. [PUBLICATION ABSTRACT]

Background The potato cyst nematode Globodera pallida has biotrophic interactions with its host. The nematode induces a feeding structure – the syncytium – which it keeps alive for the duration of the life cycle and on which it depends for all nutrients required to develop to the adult stage. Interactions of G. pallida with the host are mediated by effectors, which are produced in two sets of gland cells. These effectors suppress host defences, facilitate migration and induce the formation of the syncytium. Results The recent completion of the G. pallida genome sequence has allowed us to identify the effector complement from this species. We identify 128 orthologues of effectors from other nematodes as well as 117 novel effector candidates. We have used in situ hybridisation to confirm gland cell expression of a subset of these effectors, demonstrating the validity of our effector identification approach. We have examined the expression profiles of all effector candidates using RNAseq; this analysis shows that the majority of effectors fall into one of three clusters of sequences showing conserved expression characteristics (invasive stage nematode only, parasitic stage only or invasive stage and adult male only). We demonstrate that further diversity in the effector pool is generated by alternative splicing. In addition, we show that effectors target a diverse range of structures in plant cells, including the peroxisome. This is the first identification of effectors from any plant pathogen that target this structure. Conclusion This is the first genome scale search for effectors, combined to a life-cycle expression analysis, for any plant-parasitic nematode. We show that, like other phylogenetically unrelated plant pathogens, plant parasitic nematodes deploy hundreds of effectors in order to parasitise plants, with different effectors required for different phases of the infection process.

Pine wilt disease (PWD) results from the interaction of three elements: the pathogenic nematode, Bursaphelenchus xylophilus; the insect-vector, Monochamus sp.; and the host tree, mostly Pinus species. Bacteria isolated from B. xylophilus may be a fourth element in this complex disease. However, the precise role of bacteria in this interaction is unclear as both plant-beneficial and as plant-pathogenic bacteria may be associated with PWD. Using whole genome sequencing and phenotypic characterization, we were able to investigate in more detail the genetic repertoire of Serratia marcescens PWN146, a bacterium associated with B. xylophilus. We show clear evidence that S. marcescens PWN146 is able to withstand and colonize the plant environment, without having any deleterious effects towards a susceptible host (Pinus thunbergii), B. xylophilus nor to the nematode model C. elegans. This bacterium is able to tolerate growth in presence of xenobiotic/organic compounds, and use phenylacetic acid as carbon source. Furthermore, we present a detailed list of S. marcescens PWN146 potentials to interfere with plant metabolism via hormonal pathways and/or nutritional acquisition, and to be competitive against other bacteria and/or fungi in terms of resource acquisition or production of antimicrobial compounds. Further investigation is required to understand the role of bacteria in PWD. We have now reinforced the theory that B. xylophilus-associated bacteria may have a plant origin.

Background Computational biology comprises a wide range of technologies and approaches. Multiple technologies can be combined to create more powerful workflows if the individuals contributing the data or providing tools for its interpretation can find mutual understanding and consensus. Much conversation and joint investigation are required in order to identify and implement the best approaches. Traditionally, scientific conferences feature talks presenting novel technologies or insights, followed up by informal discussions during coffee breaks. In multi-institution collaborations, in order to reach agreement on implementation details or to transfer deeper insights in a technology and practical skills, a representative of one group typically visits the other. However, this does not scale well when the number of technologies or research groups is large. Conferences have responded to this issue by introducing Birds-of-a-Feather (BoF) sessions, which offer an opportunity for individuals with common interests to intensify their interaction. However, parallel BoF sessions often make it hard for participants to join multiple BoFs and find common ground between the different technologies, and BoFs are generally too short to allow time for participants to program together. Results This report summarises our experience with computational biology Codefests, Hackathons and Sprints, which are interactive developer meetings. They are structured to reduce the limitations of traditional scientific meetings described above by strengthening the interaction among peers and letting the participants determine the schedule and topics. These meetings are commonly run as loosely scheduled \"unconferences\" (self-organized identification of participants and topics for meetings) over at least two days, with early introductory talks to welcome and organize contributors, followed by intensive collaborative coding sessions. We summarise some prominent achievements of those meetings and describe differences in how these are organised, how their audience is addressed, and their outreach to their respective communities. Conclusions Hackathons, Codefests and Sprints share a stimulating atmosphere that encourages participants to jointly brainstorm and tackle problems of shared interest in a self-driven proactive environment, as well as providing an opportunity for new participants to get involved in collaborative projects.

Two-component systems (TCSs) are diverse and abundant signal transduction pathways found predominantly in prokaryotes. This review focuses on insights into TCS evolution made possible by the sequencing of whole prokaryotic genomes. Typical TCSs comprise an autophosphorylating protein (a histidine kinase), which transfers a phosphoryl group onto an effector protein (a response regulator), thus modulating its activity. Histidine kinases and response regulators are usually found encoded as pairs of adjacent genes within a genome, with multiple examples in most prokaryotes. Recent studies have shed light on major themes of TCS evolution, including gene duplication, gene gain/loss, gene fusion/fission, domain gain/loss, domain shuffling and the emergence of complexity. Coupled with an understanding of the structural and biophysical properties of many TCS proteins, it has become increasingly possible to draw inferences regarding the functional consequences of such evolutionary changes. In turn, this increase in understanding has the potential to enhance both our ability to rationally engineer TCSs, and also allow us to more powerfully correlate TCS evolution with behavioural phenotypes and ecological niche occupancy.

Two-component systems (TCSs) are common signal transduction systems, typically comprising paired histidine protein kinase (HK) and response regulator (RR) proteins. In many examples, it appears RR and HK genes have fused, producing a \"hybrid kinase \" We have characterized a set of prokaryotic genes encoding RRs, HKs, and hybrid kinases, enabling characterization of gene fusion and fission. Primary factors correlating with fusion rates are the presence of transmembrane helices in HKs and the presence of DNA-binding domains in RRs, features that require correct (and separate) spatial location. In the absence of such features, there is a relative abundance of fused genes. The order of paired HK and RR genes and the nucleotide distance between encoded domains also correlate with apparent gene fusion rates. We propose that localization requirements and relative positioning of encoded domains within TCS genes affect the function (and therefore retention) of hybrid kinases resulting from gene fusion. [PUBLICATION ABSTRACT]