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Background Orius laevigatus , a minute pirate bug, is a highly effective beneficial predator of crop pests including aphids, spider mites and thrips in integrated pest management (IPM) programmes. No genomic information is currently available for O. laevigatus , as is the case for the majority of beneficial predators which feed on crop pests. In contrast, genomic information for crop pests is far more readily available. The lack of publicly available genomes for beneficial predators to date has limited our ability to perform comparative analyses of genes encoding potential insecticide resistance mechanisms between crop pests and their predators. These mechanisms include several gene/protein families including cytochrome P450s (P450s), ATP binding cassette transporters (ABCs), glutathione S-transferases (GSTs), UDP-glucosyltransferases (UGTs) and carboxyl/cholinesterases (CCEs). Methods and findings In this study, a high-quality scaffold level de novo genome assembly for O. laevigatus has been generated using a hybrid approach with PacBio long-read and Illumina short-read data. The final assembly achieved a scaffold N50 of 125,649 bp and a total genome size of 150.98 Mb. The genome assembly achieved a level of completeness of 93.6% using a set of 1658 core insect genes present as full-length genes. Genome annotation identified 15,102 protein-coding genes - 87% of which were assigned a putative function. Comparative analyses revealed gene expansions of sigma class GSTs and CYP3 P450s. Conversely the UGT gene family showed limited expansion. Differences were seen in the distributions of resistance-associated gene families at the subfamily level between O. laevigatus and some of its targeted crop pests. A target site mutation in ryanodine receptors (I4790M, PxRyR) which has strong links to diamide resistance in crop pests and had previously only been identified in lepidopteran species was found to also be present in hemipteran species, including O. laevigatus . Conclusion and significance This assembly is the first published genome for the Anthocoridae family and will serve as a useful resource for further research into target-site selectivity issues and potential resistance mechanisms in beneficial predators. Furthermore, the expansion of gene families often linked to insecticide resistance may be an indicator of the capacity of this predator to detoxify selective insecticides. These findings could be exploited by targeted pesticide screens and functional studies to increase effectiveness of IPM strategies, which aim to increase crop yields by sustainably, environmentally-friendly and effectively control pests without impacting beneficial predator populations.

Despite intensive research, the aetiology of multiple sclerosis (MS) remains unknown. Cerebrospinal fluid proteomics has the potential to reveal mechanisms of MS pathogenesis, but analyses must account for disease heterogeneity. We previously reported explorative multivariate analysis by hierarchical clustering of proteomics data of MS patients and controls, which resulted in two groups of individuals. Grouping reflected increased levels of intrathecal inflammatory response proteins and decreased levels of proteins involved in neural development in one group relative to the other group. MS patients and controls were present in both groups. Here we reanalysed these data and we also reanalysed data from an independent cohort of patients diagnosed with clinically isolated syndrome (CIS), who have symptoms of MS without evidence of dissemination in space and/or time. Some, but not all, CIS patients had intrathecal inflammation. The analyses reported here identified a common protein signature of MS/CIS that was not linked to elevated intrathecal inflammation. The signature included low levels of complement proteins, semaphorin-7A, reelin, neural cell adhesion molecules, inter-alpha-trypsin inhibitor heavy chain H2, transforming growth factor beta 1, follistatin-related protein 1, malate dehydrogenase 1 cytoplasmic, plasma retinol-binding protein, biotinidase, and transferrin, all known to play roles in neural development. Low levels of these proteins suggest that MS/CIS patients suffer from abnormally low oxidative capacity that results in disrupted neural development from an early stage of the disease.

Background Sphaerophoria rueppellii , a European species of hoverfly, is a highly effective beneficial predator of hemipteran crop pests including aphids, thrips and coleopteran/lepidopteran larvae in integrated pest management (IPM) programmes. It is also a key pollinator of a wide variety of important agricultural crops. No genomic information is currently available for S. rueppellii . Without genomic information for such beneficial predator species, we are unable to perform comparative analyses of insecticide target-sites and genes encoding metabolic enzymes potentially responsible for insecticide resistance, between crop pests and their predators. These metabolic mechanisms include several gene families - cytochrome P450 monooxygenases (P450s), ATP binding cassette transporters (ABCs), glutathione- S -transferases (GSTs), UDP-glycosyltransferases (UGTs) and carboxyl/choline esterases (CCEs). Methods and findings In this study, a high-quality near-chromosome level de novo genome assembly (as well as a mitochondrial genome assembly) for S. rueppellii has been generated using a hybrid approach with PacBio long-read and Illumina short-read data, followed by super scaffolding using Hi-C data. The final assembly achieved a scaffold N50 of 87Mb, a total genome size of 537.6Mb and a level of completeness of 96% using a set of 1,658 core insect genes present as full-length genes. The assembly was annotated with 14,249 protein-coding genes. Comparative analysis revealed gene expansions of CYP6Zx P450s, epsilon-class GSTs, dietary CCEs and multiple UGT families (UGT37/302/308/430/431). Conversely, ABCs, delta-class GSTs and non-CYP6Zx P450s showed limited expansion. Differences were seen in the distributions of resistance-associated gene families across subfamilies between S. rueppellii and some hemipteran crop pests. Additionally, S. rueppellii had larger numbers of detoxification genes than other pollinator species. Conclusion and significance This assembly is the first published genome for a predatory member of the Syrphidae family and will serve as a useful resource for further research into selectivity and potential tolerance of insecticides by beneficial predators. Furthermore, the expansion of some gene families often linked to insecticide resistance and selectivity may be an indicator of the capacity of this predator to detoxify IPM selective insecticides. These findings could be exploited by targeted insecticide screens and functional studies to increase effectiveness of IPM strategies, which aim to increase crop yields by sustainably and effectively controlling pests without impacting beneficial predator populations.

Background Systems biology experiments generate large volumes of data of multiple modalities and this information presents a challenge for integration due to a mix of complexity together with rich semantics. Here, we describe how graph databases provide a powerful framework for storage, querying and envisioning of biological data. Results We show how graph databases are well suited for the representation of biological information, which is typically highly connected, semi-structured and unpredictable. We outline an application case that uses the Neo4j graph database for building and querying a prototype network to provide biological context to asthma related genes. Conclusions Our study suggests that graph databases provide a flexible solution for the integration of multiple types of biological data and facilitate exploratory data mining to support hypothesis generation.

KnetMaps is a BioJS component for the interactive visualization of biological knowledge networks. It is well suited for applications that need to visualise complementary, connected and content-rich data in a single view in order to help users to traverse pathways linking entities of interest, for example to go from genotype to phenotype. KnetMaps loads data in JSON format, visualizes the structure and content of knowledge networks using lightweight JavaScript libraries, and supports interactive touch gestures. KnetMaps uses effective visualization techniques to prevent information overload and to allow researchers to progressively build their knowledge.

Background Combining multiple evidence-types from different information sources has the potential to reveal new relationships in biological systems. The integrated information can be represented as a relationship network, and clustering the network can suggest possible functional modules. The value of such modules for gaining insight into the underlying biological processes depends on their functional coherence. The challenges that we wish to address are to define and quantify the functional coherence of modules in relationship networks, so that they can be used to infer function of as yet unannotated proteins, to discover previously unknown roles of proteins in diseases as well as for better understanding of the regulation and interrelationship between different elements of complex biological systems. Results We have defined the functional coherence of modules with respect to the Gene Ontology (GO) by considering two complementary aspects: (i) the fragmentation of the GO functional categories into the different modules and (ii) the most representative functions of the modules. We have proposed a set of metrics to evaluate these two aspects and demonstrated their utility in Arabidopsis thaliana . We selected 2355 proteins for which experimentally established protein-protein interaction (PPI) data were available. From these we have constructed five relationship networks, four based on single types of data: PPI, co-expression, co-occurrence of protein names in scientific literature abstracts and sequence similarity and a fifth one combining these four evidence types. The ability of these networks to suggest biologically meaningful grouping of proteins was explored by applying Markov clustering and then by measuring the functional coherence of the clusters. Conclusions Relationship networks integrating multiple evidence-types are biologically informative and allow more proteins to be assigned to a putative functional module. Using additional evidence types concentrates the functional annotations in a smaller number of modules without unduly compromising their consistency. These results indicate that integration of more data sources improves the ability to uncover functional association between proteins, both by allowing more proteins to be linked and producing a network where modular structure more closely reflects the hierarchy in the gene ontology.

The electronic Rothamsted Archive, e-RA (www.era.rothamsted.ac.uk) provides a permanent managed database to both securely store and disseminate data from Rothamsted Research's long-term field experiments (since 1843) and meteorological stations (since 1853). Both historical and contemporary data are made available via this online database which provides the scientific community with access to a unique continuous record of agricultural experiments and weather measured since the mid-19th century. Qualitative information, such as treatment and management practices, plans and soil information, accompanies the data and are made available on the e-RA website. e-RA was released externally to the wider scientific community in 2013 and this paper describes its development, content, curation and the access process for data users. Case studies illustrate the diverse applications of the data, including its original intended purposes and recent unforeseen applications. Usage monitoring demonstrates the data are of increasing interest. Future developments, including adopting FAIR data principles, are proposed as the resource is increasingly recognised as a unique archive of data relevant to sustainable agriculture, agroecology and the environment.

Background In response to the rapid growth of available genome sequences, efforts have been made to develop automatic inference methods to functionally characterize them. Pipelines that infer functional annotation are now routinely used to produce new annotations at a genome scale and for a broad variety of species. These pipelines differ widely in their inference algorithms, confidence thresholds and data sources for reasoning. This heterogeneity makes a comparison of the relative merits of each approach extremely complex. The evaluation of the quality of the resultant annotations is also challenging given there is often no existing gold-standard against which to evaluate precision and recall. Results In this paper, we present a pragmatic approach to the study of functional annotations. An ensemble of 12 metrics, describing various aspects of functional annotations, is defined and implemented in a unified framework, which facilitates their systematic analysis and inter-comparison. The use of this framework is demonstrated on three illustrative examples: analysing the outputs of state-of-the-art inference pipelines, comparing electronic versus manual annotation methods, and monitoring the evolution of publicly available functional annotations. The framework is part of the AIGO library ( http://code.google.com/p/aigo ) for the Analysis and the Inter-comparison of the products of Gene Ontology (GO) annotation pipelines. The AIGO library also provides functionalities to easily load, analyse, manipulate and compare functional annotations and also to plot and export the results of the analysis in various formats. Conclusions This work is a step toward developing a unified framework for the systematic study of GO functional annotations. This framework has been designed so that new metrics on GO functional annotations can be added in a very straightforward way.

Background Sphaerophoria rueppellii, a European species of hoverfly, is a highly effective beneficial predator of hemipteran crop pests including aphids, thrips and coleopteran/lepidopteran larvae in integrated pest management (IPM) programmes. It is also a key pollinator of a wide variety of important agricultural crops. No genomic information is currently available for S. rueppellii. Without genomic information for such beneficial predator species, we are unable to perform comparative analyses of insecticide target-sites and genes encoding metabolic enzymes potentially responsible for insecticide resistance, between crop pests and their predators. These metabolic mechanisms include several gene families - cytochrome P450 monooxygenases (P450s), ATP binding cassette transporters (ABCs), glutathione-S-transferases (GSTs), UDP-glycosyltransferases (UGTs) and carboxyl/choline esterases (CCEs). Methods and findings In this study, a high-quality near-chromosome level de novo genome assembly (as well as a mitochondrial genome assembly) for S. rueppellii has been generated using a hybrid approach with PacBio long-read and Illumina short-read data, followed by super scaffolding using Hi-C data. The final assembly achieved a scaffold N50 of 87Mb, a total genome size of 537.6Mb and a level of completeness of 96% using a set of 1,658 core insect genes present as full-length genes. The assembly was annotated with 14,249 protein-coding genes. Comparative analysis revealed gene expansions of CYP6Zx P450s, epsilon-class GSTs, dietary CCEs and multiple UGT families (UGT37/302/308/430/431). Conversely, ABCs, delta-class GSTs and non-CYP6Zx P450s showed limited expansion. Differences were seen in the distributions of resistance-associated gene families across subfamilies between S. rueppellii and some hemipteran crop pests. Additionally, S. rueppellii had larger numbers of detoxification genes than other pollinator species. Conclusion and significance This assembly is the first published genome for a predatory member of the Syrphidae family and will serve as a useful resource for further research into selectivity and potential tolerance of insecticides by beneficial predators. Furthermore, the expansion of some gene families often linked to insecticide resistance and selectivity may be an indicator of the capacity of this predator to detoxify IPM selective insecticides. These findings could be exploited by targeted insecticide screens and functional studies to increase effectiveness of IPM strategies, which aim to increase crop yields by sustainably and effectively controlling pests without impacting beneficial predator populations.

Background: Orius laevigatus, a minute pirate bug, is a highly effective beneficial predator of crop pests including aphids, spider mites and thrips in integrated pest management (IPM) programmes. No genomic information is currently available for O. laevigatus, as is the case for the majority of beneficial predators which feed on crop pests. In contrast, genomic information for crop pests is far more readily available. The lack of publicly available genomes for beneficial predators to date has limited our ability to perform comparative analyses of genes encoding potential insecticide resistance mechanisms between crop pests and their predators. These mechanisms include several gene/protein families including cytochrome P450s (P450s), ATP binding cassette transporters (ABCs), glutathione S-transferases (GSTs), UDP-glucosyltransferases (UGTs) and carboxyl/cholinesterases (CCEs). Methods and findings: In this study, a high-quality scaffold level de novo genome assembly for O. laevigatus has been generated using a hybrid approach with PacBio long-read and Illumina short-read data. The final assembly achieved a scaffold N50 of 125,649 bp and a total genome size of 150.98 Mb. The genome assembly achieved a level of completeness of 93.6% using a set of 1658 core insect genes present as full-length genes. Genome annotation identified 15,102 protein-coding genes - 87% of which were assigned a putative function. Comparative analyses revealed gene expansions of sigma class GSTs and CYP3 P450s. Conversely the UGT gene family showed limited expansion. Differences were seen in the distributions of resistance-associated gene families at the subfamily level between O. laevigatus and some of its targeted crop pests. A target site mutation in ryanodine receptors (I4790M, PxRyR) which has strong links to diamide resistance in crop pests and had previously only been identified in lepidopteran species was found to also be present in hemipteran species, including O. laevigatus. Conclusion and significance: This assembly is the first published genome for the Anthocoridae family and will serve as a useful resource for further research into target-site selectivity issues and potential resistance mechanisms in beneficial predators. Furthermore, the expansion of gene families often linked to insecticide resistance may be an indicator of the capacity of this predator to detoxify selective insecticides. These findings could be exploited by targeted pesticide screens and functional studies to increase effectiveness of IPM strategies, which aim to increase crop yields by sustainably, environmentally-friendly and effectively control pests without impacting beneficial predator populations.