A systems approach delivers a functional microRNA catalog and expanded targets for seizure suppression in temporal lobe epilepsy.

Temporal lobe epilepsy is the most common drug-resistant form of epilepsy in adults. The reorganization of neural networks and the gene expression landscape underlying pathophysiologic network behavior in brain structures such as the hippocampus has been suggested to be controlled, in part, by microRNAs. To systematically assess their significance, we sequenced Argonaute-loaded microRNAs to define functionally engaged microRNAs in the hippocampus of three different animal models in two species and at six time points between the initial precipitating insult through to the establishment of chronic epilepsy. We then selected commonly up-regulated microRNAs for a functional in vivo therapeutic screen using oligonucleotide inhibitors. Argonaute sequencing generated 1.44 billion small RNA reads of which up to 82% were microRNAs, with over 400 unique microRNAs detected per model. Approximately half of the detected microRNAs were dysregulated in each epilepsy model. We prioritized commonly up-regulated microRNAs that were fully conserved in humans and designed custom antisense oligonucleotides for these candidate targets. Antiseizure phenotypes were observed upon knockdown of miR-10a-5p, miR-21a-5p, and miR-142a-5p and electrophysiological analyses indicated broad safety of this approach. Combined inhibition of these three microRNAs reduced spontaneous seizures in epileptic mice. Proteomic data, RNA sequencing, and pathway analysis on predicted and validated targets of these microRNAs implicated derepressed TGF-ß signaling as a shared seizure-modifying mechanism. Correspondingly, inhibition of TGF-ß signaling occluded the antiseizure effects of the antagomirs. Together, these results identify shared, dysregulated, and functionally active microRNAs during the pathogenesis of epilepsy which represent therapeutic antiseizure targets.

Genetics in an isolated population like Finland: a different basis for genomic medicine?

A unique genetic background in an isolated population like that of Finland offers special opportunities for genetic research as well as for applying the genetic developments to the health care. On the other hand, the different genetic background may require local attempts to develop diagnostics and treatment as the selection of diseases and mutations differs from that in the other populations. In this review, we describe the experiences of research and health care in this genetic isolate starting from the identification of specific monogenic diseases enriched in the Finnish population all the way to implementing the knowledge of the unique genetic background to genomic medicine at population level.

Identifiers for the 21st century: How to design, provision, and reuse persistent identifiers to maximize utility and impact of life science data.

In many disciplines, data are highly decentralized across thousands of online databases (repositories, registries, and knowledgebases). Wringing value from such databases depends on the discipline of data science and on the humble bricks and mortar that make integration possible; identifiers are a core component of this integration infrastructure. Drawing on our experience and on work by other groups, we outline 10 lessons we have learned about the identifier qualities and best practices that facilitate large-scale data integration. Specifically, we propose actions that identifier practitioners (database providers) should take in the design, provision and reuse of identifiers. We also outline the important considerations for those referencing identifiers in various circumstances, including by authors and data generators. While the importance and relevance of each lesson will vary by context, there is a need for increased awareness about how to avoid and manage common identifier problems, especially those related to persistence and web-accessibility/resolvability. We focus strongly on web-based identifiers in the life sciences; however, the principles are broadly relevant to other disciplines.

Expanded national database collection and data coverage in the FINDbase worldwide database for clinically relevant genomic variation allele frequencies.

FINDbase (http://www.findbase.org) is a comprehensive data repository that records the prevalence of clinically relevant genomic variants in various populations worldwide, such as pathogenic variants leading mostly to monogenic disorders and pharmacogenomics biomarkers. The database also records the incidence of rare genetic diseases in various populations, all in well-distinct data modules. Here, we report extensive data content updates in all data modules, with direct implications to clinical pharmacogenomics. Also, we report significant new developments in FINDbase, namely (i) the release of a new version of the ETHNOS software that catalyzes development curation of national/ethnic genetic databases, (ii) the migration of all FINDbase data content into 90 distinct national/ethnic mutation databases, all built around Microsoft's PivotViewer (http://www.getpivot.com) software (iii) new data visualization tools and (iv) the interrelation of FINDbase with DruGeVar database with direct implications in clinical pharmacogenomics. The abovementioned updates further enhance the impact of FINDbase, as a key resource for Genomic Medicine applications.

The Finnish disease heritage database (FinDis) update-a database for the genes mutated in the Finnish disease heritage brought to the next-generation sequencing era.

The Finnish Disease Heritage Database (FinDis) (http://findis.org) was originally published in 2004 as a centralized information resource for rare monogenic diseases enriched in the Finnish population. The FinDis database originally contained 405 causative variants for 30 diseases. At the time, the FinDis database was a comprehensive collection of data, but since 1994, a large amount of new information has emerged, making the necessity to update the database evident. We collected information and updated the database to contain genes and causative variants for 35 diseases, including six more genes and more than 1,400 additional disease-causing variants. Information for causative variants for each gene is collected under the LOVD 3.0 platform, enabling easy updating. The FinDis portal provides a centralized resource and user interface to link information on each disease and gene with variant data in the LOVD 3.0 platform. The software written to achieve this has been open-sourced and made available on GitHub (http://github.com/findis-db), allowing biomedical institutions in other countries to present their national data in a similar way, and to both contribute to, and benefit from, standardized variation data. The updated FinDis portal provides a unique resource to assist patient diagnosis, research, and the development of new cures.

VarioML framework for comprehensive variation data representation and exchange.

BACKGROUND: Sharing of data about variation and the associated phenotypes is a critical need, yet variant information can be arbitrarily complex, making a single standard vocabulary elusive and re-formatting difficult. Complex standards have proven too time-consuming to implement. RESULTS: The GEN2PHEN project addressed these difficulties by developing a comprehensive data model for capturing biomedical observations, Observ-OM, and building the VarioML format around it. VarioML pairs a simplified open specification for describing variants, with a toolkit for adapting the specification into one's own research workflow. Straightforward variant data can be captured, federated, and exchanged with no overhead; more complex data can be described, without loss of compatibility. The open specification enables push-button submission to gene variant databases (LSDBs) e.g., the Leiden Open Variation Database, using the Cafe Variome data publishing service, while VarioML bidirectionally transforms data between XML and web-application code formats, opening up new possibilities for open source web applications building on shared data. A Java implementation toolkit makes VarioML easily integrated into biomedical applications. VarioML is designed primarily for LSDB data submission and transfer scenarios, but can also be used as a standard variation data format for JSON and XML document databases and user interface components. CONCLUSIONS: VarioML is a set of tools and practices improving the availability, quality, and comprehensibility of human variation information. It enables researchers, diagnostic laboratories, and clinics to share that information with ease, clarity, and without ambiguity.

A genome-wide association study of monozygotic twin-pairs suggests a locus related to variability of serum high-density lipoprotein cholesterol.

Genome-wide association analysis on monozygotic twin-pairs offers a route to discovery of gene environment interactions through testing for variability loci associated with sensitivity to individual environment/lifestyle. We present a genome-wide scan of loci associated with intra-pair differences in serum lipid and apolipoprotein levels. We report data for 1,720 monozygotic female twin-pairs from GenomEUtwin project with 2.5 million SNPs, imputed or genotyped, and measured serum lipid fractions for both twins. We found one locus associated with intra-pair differences in high-density lipoprotein cholesterol, rs2483058 in an intron of SRGAP2, where twins carrying the C allele are more sensitive to environmental factors(P=3.98 x 10-8). We followed up the association in further genotyped monozygotic twins (N= 1,261),which showed a moderate association for the variant (P= 0.200, same direction of an effect). In addition,we report a new association on the level of apolipoprotein A-ll (P= 4.03 x 1 o-8).

Observ-OM and Observ-TAB: Universal syntax solutions for the integration, search, and exchange of phenotype and genotype information.

Genetic and epidemiological research increasingly employs large collections of phenotypic and molecular observation data from high quality human and model organism samples. Standardization efforts have produced a few simple formats for exchange of these various data, but a lightweight and convenient data representation scheme for all data modalities does not exist, hindering successful data integration, such as assignment of mouse models to orphan diseases and phenotypic clustering for pathways. We report a unified system to integrate and compare observation data across experimental projects, disease databases, and clinical biobanks. The core object model (Observ-OM) comprises only four basic concepts to represent any kind of observation: Targets, Features, Protocols (and their Applications), and Values. An easy-to-use file format (Observ-TAB) employs Excel to represent individual and aggregate data in straightforward spreadsheets. The systems have been tested successfully on human biobank, genome-wide association studies, quantitative trait loci, model organism, and patient registry data using the MOLGENIS platform to quickly setup custom data portals. Our system will dramatically lower the barrier for future data sharing and facilitate integrated search across panels and species. All models, formats, documentation, and software are available for free and open source (LGPLv3) at http://www.observ-om.org.

NordicDB: a Nordic pool and portal for genome-wide control data.

A cost-efficient way to increase power in a genetic association study is to pool controls from different sources. The genotyping effort can then be directed to large case series. The Nordic Control database, NordicDB, has been set up as a unique resource in the Nordic area and the data are available for authorized users through the web portal (http://www.nordicdb.org). The current version of NordicDB pools together high-density genome-wide SNP information from ∼5000 controls originating from Finnish, Swedish and Danish studies and shows country-specific allele frequencies for SNP markers. The genetic homogeneity of the samples was investigated using multidimensional scaling (MDS) analysis and pairwise allele frequency differences between the studies. The plot of the first two MDS components showed excellent resemblance to the geographical placement of the samples, with a clear NW-SE gradient. We advise researchers to assess the impact of population structure when incorporating NordicDB controls in association studies. This harmonized Nordic database presents a unique genome-wide resource for future genetic association studies in the Nordic countries.

The MOLGENIS toolkit: rapid prototyping of biosoftware at the push of a button.

BACKGROUND: There is a huge demand on bioinformaticians to provide their biologists with user friendly and scalable software infrastructures to capture, exchange, and exploit the unprecedented amounts of new *omics data. We here present MOLGENIS, a generic, open source, software toolkit to quickly produce the bespoke MOLecular GENetics Information Systems needed. METHODS: The MOLGENIS toolkit provides bioinformaticians with a simple language to model biological data structures and user interfaces. At the push of a button, MOLGENIS' generator suite automatically translates these models into a feature-rich, ready-to-use web application including database, user interfaces, exchange formats, and scriptable interfaces. Each generator is a template of SQL, JAVA, R, or HTML code that would require much effort to write by hand. This 'model-driven' method ensures reuse of best practices and improves quality because the modeling language and generators are shared between all MOLGENIS applications, so that errors are found quickly and improvements are shared easily by a re-generation. A plug-in mechanism ensures that both the generator suite and generated product can be customized just as much as hand-written software. RESULTS: In recent years we have successfully evaluated the MOLGENIS toolkit for the rapid prototyping of many types of biomedical applications, including next-generation sequencing, GWAS, QTL, proteomics and biobanking. Writing 500 lines of model XML typically replaces 15,000 lines of hand-written programming code, which allows for quick adaptation if the information system is not yet to the biologist's satisfaction. Each application generated with MOLGENIS comes with an optimized database back-end, user interfaces for biologists to manage and exploit their data, programming interfaces for bioinformaticians to script analysis tools in R, Java, SOAP, REST/JSON and RDF, a tab-delimited file format to ease upload and exchange of data, and detailed technical documentation. Existing databases can be quickly enhanced with MOLGENIS generated interfaces using the 'ExtractModel' procedure. CONCLUSIONS: The MOLGENIS toolkit provides bioinformaticians with a simple model to quickly generate flexible web platforms for all possible genomic, molecular and phenotypic experiments with a richness of interfaces not provided by other tools. All the software and manuals are available free as LGPLv3 open source at http://www.molgenis.org.