InterMOD: integrated data and tools for the unification of model organism research

FAWMine: An integrated database and analysis platform for fall armyworm genomics

Fall armyworm (Spodoptera frugiperda), a native insect species in the Americas, is rapidly becoming a major agricultural pest worldwide and is causing great damage to corn, rice, soybeans, and other crops. To control this pest, scientists have accumulated a great deal of high-throughput data of fall armyworm, and nine versions of its genomes and transcriptomes have been published. However, easily accessing and performing integrated analysis of these omics data sets is challenging. Here, we developed the Fall Armyworm Genome Database (FAWMine, http://159.226.67.243:8080/fawmine/) to maintain genome sequences, structural and functional annotations, transcriptomes, co-expression, protein interactions, homologs, pathways, and single-nucleotide variations. FAWMine provides a powerful framework that helps users to perform flexible and customized searching, present integrated data sets using diverse visualization methods, output results tables in a range of file formats, analyze candidate gene lists using multiple widgets, and query data available in other InterMine systems. Additionally, stand-alone JBrowse and BLAST services are also established, allowing the users to visualize RNA-Seq data and search genome and annotated gene sequences. Altogether, FAWMine is a useful tool for querying, visualizing, and analyzing compiled data sets rapidly and efficiently. FAWMine will be continually updated to function as a community resource for fall armyworm genomics and pest control research.

An Overview of In Vivo and In Vitro Models for Autosomal Dominant Polycystic Kidney Disease: A Journey from 3D-Cysts to Mini-Pigs

Autosomal dominant polycystic kidney disease (ADPKD) is the most common inheritable cause of end stage renal disease and, as of today, only a single moderately effective treatment is available for patients. Even though ADPKD research has made huge progress over the last decades, the precise disease mechanisms remain elusive. However, a wide variety of cellular and animal models have been developed to decipher the pathophysiological mechanisms and related pathways underlying the disease. As none of these models perfectly recapitulates the complexity of the human disease, the aim of this review is to give an overview of the main tools currently available to ADPKD researchers, as well as their main advantages and limitations.

WormBase 2017: molting into a new stage

WormBase (http://www.wormbase.org) is an important knowledge resource for biomedical researchers worldwide. To accommodate the ever increasing amount and complexity of research data, WormBase continues to advance its practices on data acquisition, curation and retrieval to most effectively deliver comprehensive knowledge about Caenorhabditis elegans, and genomic information about other nematodes and parasitic flatworms. Recent notable enhancements include user-directed submission of data, such as micropublication; genomic data curation and presentation, including additional genomes and JBrowse, respectively; new query tools, such as SimpleMine, Gene Enrichment Analysis; new data displays, such as the Person Lineage browser and the Summary of Ontology-based Annotations. Anticipating more rapid data growth ahead, WormBase continues the process of migrating to a cutting-edge database technology to achieve better stability, scalability, reproducibility and a faster response time. To better serve the broader research community, WormBase, with five other Model Organism Databases and The Gene Ontology project, have begun to collaborate formally as the Alliance of Genome Resources.

Expression of the Shrimp wap gene in Drosophila elicits defense responses and protease inhibitory activity

The wap gene encodes a single whey acidic protein (WAP) domain-containing peptide from Chinese white shrimp (Fenneropenaeus chinensis), which shows broad-spectrum antimicrobial activities and proteinase inhibitory activities in vitro. To explore the medical applications of the WAP peptide, a wap gene transgenic Drosophila melanogaster was constructed. In wap-expressing flies, high expression levels of wap gene (>100 times) were achieved, in contrast to those of control flies, by qRT-PCR analysis. The wap gene expression was associated with increased resistance to microbial infection and decreased bacterial numbers in the flies. In addition, the WAP protein extract from wap-expressing flies, compared with control protein extract from control flies, showed improved antimicrobial activities against broad Gram-positive and Gram-negative bacteria, including the clinical drug resistant bacterium of methicillin-resistant S. aureus (MRSA), improved protease inhibitor activities against crude proteinases and commercial proteinases, including elastase, subtilis proteinase A, and proteinase K in vitro, and improved growth rate and microbial resistance, as well as wound-healing in loach and mouse models. These results suggest that wap-expressing flies could be used as a food additive in aquaculture to prevent infections and a potential antibacterial for fighting drug-resistant bacteria.

AgBioData consortium recommendations for sustainable genomics and genetics databases for agriculture

The future of agricultural research depends on data. The sheer volume of agricultural biological data being produced today makes excellent data management essential. Governmental agencies, publishers and science funders require data management plans for publicly funded research. Furthermore, the value of data increases exponentially when they are properly stored, described, integrated and shared, so that they can be easily utilized in future analyses. AgBioData (https://www.agbiodata.org) is a consortium of people working at agricultural biological databases, data archives and knowledgbases who strive to identify common issues in database development, curation and management, with the goal of creating database products that are more Findable, Accessible, Interoperable and Reusable. We strive to promote authentic, detailed, accurate and explicit communication between all parties involved in scientific data. As a step toward this goal, we present the current state of biocuration, ontologies, metadata and persistence, database platforms, programmatic (machine) access to data, communication and sustainability with regard to data curation. Each section describes challenges and opportunities for these topics, along with recommendations and best practices.

Using ZFIN: Data Types, Organization, and Retrieval

The Zebrafish Model Organism Database (ZFIN; zfin.org) was established in 1994 as the primary genetic and genomic resource for the zebrafish research community. Some of the earliest records in ZFIN were for people and laboratories. Since that time, services and data types provided by ZFIN have grown considerably. Today, ZFIN provides the official nomenclature for zebrafish genes, mutants, and transgenics and curates many data types including gene expression, phenotypes, Gene Ontology, models of human disease, orthology, knockdown reagents, transgenic constructs, and antibodies. Ontologies are used throughout ZFIN to structure these expertly curated data. An integrated genome browser provides genomic context for genes, transgenics, mutants, and knockdown reagents. ZFIN also supports a community wiki where the research community can post new antibody records and research protocols. Data in ZFIN are accessible via web pages, download files, and the ZebrafishMine (zebrafishmine.org), an installation of the InterMine data warehousing software. Searching for data at ZFIN utilizes both parameterized search forms and a single box search for searching or browsing data quickly. This chapter aims to describe the primary ZFIN data and services, and provide insight into how to use and interpret ZFIN searches, data, and web pages.

BLAT2DOLite: An Online System for Identifying Significant Relationships between Genetic Sequences and Diseases

The significantly related diseases of sequences could play an important role in understanding the functions of these sequences. In this paper, we introduced BLAT2DOLite, an online system for annotating human genes and diseases and identifying the significant relationships between sequences and diseases. Currently, BLAT2DOLite integrates Entrez Gene database and Disease Ontology Lite (DOLite), which contain loci of gene and relationships between genes and diseases. It utilizes hypergeometric test to calculate P-values between genes and diseases of DOLite. The system can be accessed from: http://123.59.132.21:8080/BLAT2DOLite. The corresponding web service is described in: http://123.59.132.21:8080/BLAT2DOLite/BLAT2DOLiteIDMappingPort?wsdl.

Hymenoptera Genome Database: integrating genome annotations in HymenopteraMine

We report an update of the Hymenoptera Genome Database (HGD) (http://HymenopteraGenome.org), a model organism database for insect species of the order Hymenoptera (ants, bees and wasps). HGD maintains genomic data for 9 bee species, 10 ant species and 1 wasp, including the versions of genome and annotation data sets published by the genome sequencing consortiums and those provided by NCBI. A new data-mining warehouse, HymenopteraMine, based on the InterMine data warehousing system, integrates the genome data with data from external sources and facilitates cross-species analyses based on orthology. New genome browsers and annotation tools based on JBrowse/WebApollo provide easy genome navigation, and viewing of high throughput sequence data sets and can be used for collaborative genome annotation. All of the genomes and annotation data sets are combined into a single BLAST server that allows users to select and combine sequence data sets to search.

Bovine Genome Database: new tools for gleaning function from the Bos taurus genome

We report an update of the Bovine Genome Database (BGD) (http://BovineGenome.org). The goal of BGD is to support bovine genomics research by providing genome annotation and data mining tools. We have developed new genome and annotation browsers using JBrowse and WebApollo for two Bos taurus genome assemblies, the reference genome assembly (UMD3.1.1) and the alternate genome assembly (Btau_4.6.1). Annotation tools have been customized to highlight priority genes for annotation, and to aid annotators in selecting gene evidence tracks from 91 tissue specific RNAseq datasets. We have also developed BovineMine, based on the InterMine data warehousing system, to integrate the bovine genome, annotation, QTL, SNP and expression data with external sources of orthology, gene ontology, gene interaction and pathway information. BovineMine provides powerful query building tools, as well as customized query templates, and allows users to analyze and download genome-wide datasets. With BovineMine, bovine researchers can use orthology to leverage the curated gene pathways of model organisms, such as human, mouse and rat. BovineMine will be especially useful for gene ontology and pathway analyses in conjunction with GWAS and QTL studies.

Cross-organism analysis using InterMine

InterMine is a data integration warehouse and analysis software system developed for large and complex biological data sets. Designed for integrative analysis, it can be accessed through a user-friendly web interface. For bioinformaticians, extensive web services as well as programming interfaces for most common scripting languages support access to all features. The web interface includes a useful identifier look-up system, and both simple and sophisticated search options. Interactive results tables enable exploration, and data can be filtered, summarized, and browsed. A set of graphical analysis tools provide a rich environment for data exploration including statistical enrichment of sets of genes or other entities. InterMine databases have been developed for the major model organisms, budding yeast, nematode worm, fruit fly, zebrafish, mouse, and rat together with a newly developed human database. Here, we describe how this has facilitated interoperation and development of cross-organism analysis tools and reports. InterMine as a data exploration and analysis tool is also described. All the InterMine-based systems described in this article are resources freely available to the scientific community.

Mouse Genome Database: From sequence to phenotypes and disease models

The Mouse Genome Database (MGD, www.informatics.jax.org) is the international scientific database for genetic, genomic, and biological data on the laboratory mouse to support the research requirements of the biomedical community. To accomplish this goal, MGD provides broad data coverage, serves as the authoritative standard for mouse nomenclature for genes, mutants, and strains, and curates and integrates many types of data from literature and electronic sources. Among the key data sets MGD supports are: the complete catalog of mouse genes and genome features, comparative homology data for mouse and vertebrate genes, the authoritative set of Gene Ontology (GO) annotations for mouse gene functions, a comprehensive catalog of mouse mutations and their phenotypes, and a curated compendium of mouse models of human diseases. Here, we describe the data acquisition process, specifics about MGD's key data areas, methods to access and query MGD data, and outreach and user help facilities. genesis 53:458–473, 2015. © 2015 The Authors. Genesis Published by Wiley Periodicals, Inc.

Allele, phenotype and disease data at Mouse Genome Informatics: improving access and analysis

A core part of the Mouse Genome Informatics (MGI) resource is the collection of mouse mutations and the annotation phenotypes and diseases displayed by mice carrying these mutations. These data are integrated with the rest of data in MGI and exported to numerous other resources. The use of mouse phenotype data to drive translational research into human disease has expanded rapidly with the improvements in sequencing technology. MGI has implemented many improvements in allele and phenotype data annotation, search, and display to facilitate access to these data through multiple avenues. For example, the description of alleles has been modified to include more detailed categories of allele attributes. This allows improved discrimination between mutation types. Further, connections have been created between mutations involving multiple genes and each of the genes overlapping the mutation. This allows users to readily find all mutations affecting a gene and see all genes affected by a mutation. In a similar manner, the genes expressed by transgenic or knock-in alleles are now connected to these alleles. The advanced search forms and public reports have been updated to take advantage of these improvements. These search forms and reports are used by an expanding number of researchers to identify novel human disease genes and mouse models of human disease.

ZFIN, The zebrafish model organism database: Updates and new directions

The Zebrafish Model Organism Database (ZFIN; http://zfin.org) is the central resource for genetic and genomic data from zebrafish (Danio rerio) research. ZFIN staff curate detailed information about genes, mutants, genotypes, reporter lines, sequences, constructs, antibodies, knockdown reagents, expression patterns, phenotypes, gene product function, and orthology from publications. Researchers can submit mutant, transgenic, expression, and phenotype data directly to ZFIN and use the ZFIN Community Wiki to share antibody and protocol information. Data can be accessed through topic-specific searches, a new site-wide search, and the data-mining resource ZebrafishMine (http://zebrafishmine.org). Data download and web service options are also available. ZFIN collaborates with major bioinformatics organizations to verify and integrate genomic sequence data, provide nomenclature support, establish reciprocal links, and participate in the development of standardized structured vocabularies (ontologies) used for data annotation and searching. ZFIN-curated gene, function, expression, and phenotype data are available for comparative exploration at several multi-species resources. The use of zebrafish as a model for human disease is increasing. ZFIN is supporting this growing area with three major projects: adding easy access to computed orthology data from gene pages, curating details of the gene expression pattern changes in mutant fish, and curating zebrafish models of human diseases.

toxoMine: an integrated omics data warehouse for Toxoplasma gondii systems biology research

Toxoplasma gondii (T. gondii) is an obligate intracellular parasite that must monitor for changes in the host environment and respond accordingly; however, it is still not fully known which genetic or epigenetic factors are involved in regulating virulence traits of T. gondii. There are on-going efforts to elucidate the mechanisms regulating the stage transition process via the application of high-throughput epigenomics, genomics and proteomics techniques. Given the range of experimental conditions and the typical yield from such high-throughput techniques, a new challenge arises: how to effectively collect, organize and disseminate the generated data for subsequent data analysis. Here, we describe toxoMine, which provides a powerful interface to support sophisticated integrative exploration of high-throughput experimental data and metadata, providing researchers with a more tractable means toward understanding how genetic and/or epigenetic factors play a coordinated role in determining pathogenicity of T. gondii. As a data warehouse, toxoMine allows integration of high-throughput data sets with public T. gondii data. toxoMine is also able to execute complex queries involving multiple data sets with straightforward user interaction. Furthermore, toxoMine allows users to define their own parameters during the search process that gives users near-limitless search and query capabilities. The interoperability feature also allows users to query and examine data available in other InterMine systems, which would effectively augment the search scope beyond what is available to toxoMine. toxoMine complements the major community database ToxoDB by providing a data warehouse that enables more extensive integrative studies for T. gondii. Given all these factors, we believe it will become an indispensable resource to the greater infectious disease research community.

Database URL:http://toxomine.org

MouseMine: a new data warehouse for MGI

MouseMine (www.mousemine.org) is a new data warehouse for accessing mouse data from Mouse Genome Informatics (MGI). Based on the InterMine software framework, MouseMine supports powerful query, reporting, and analysis capabilities, the ability to save and combine results from different queries, easy integration into larger workflows, and a comprehensive Web Services layer. Through MouseMine, users can access a significant portion of MGI data in new and useful ways. Importantly, MouseMine is also a member of a growing community of online data resources based on InterMine, including those established by other model organism databases. Adopting common interfaces and collaborating on data representation standards are critical to fostering cross-species data analysis. This paper presents a general introduction to MouseMine, presents examples of its use, and discusses the potential for further integration into the MGI interface.

Neurogenomics: An opportunity to integrate neuroscience, genomics and bioinformatics research in Africa

Modern genomic approaches have made enormous contributions to improving our understanding of the function, development and evolution of the nervous system, and the diversity within and between species. However, most of these research advances have been recorded in countries with advanced scientific resources and funding support systems. On the contrary, little is known about, for example, the possible interplay between different genes, non-coding elements and environmental factors in modulating neurological diseases among populations in low-income countries, including many African countries. The unique ancestry of African populations suggests that improved inclusion of these populations in neuroscience-related genomic studies would significantly help to identify novel factors that might shape the future of neuroscience research and neurological healthcare. This perspective is strongly supported by the recent identification that diseased individuals and their kindred from specific sub-Saharan African populations lack common neurological disease-associated genetic mutations. This indicates that there may be population-specific causes of neurological diseases, necessitating further investigations into the contribution of additional, presently-unknown genomic factors. Here, we discuss how the development of neurogenomics research in Africa would help to elucidate disease-related genomic variants, and also provide a good basis to develop more effective therapies. Furthermore, neurogenomics would harness African scientists' expertise in neuroscience, genomics and bioinformatics to extend our understanding of the neural basis of behaviour, development and evolution.

The Mouse Genome Database (MGD): facilitating mouse as a model for human biology and disease

The Mouse Genome Database (MGD, http://www.informatics.jax.org) serves the international biomedical research community as the central resource for integrated genomic, genetic and biological data on the laboratory mouse. To facilitate use of mouse as a model in translational studies, MGD maintains a core of high-quality curated data and integrates experimentally and computationally generated data sets. MGD maintains a unified catalog of genes and genome features, including functional RNAs, QTL and phenotypic loci. MGD curates and provides functional and phenotype annotations for mouse genes using the Gene Ontology and Mammalian Phenotype Ontology. MGD integrates phenotype data and associates mouse genotypes to human diseases, providing critical mouse–human relationships and access to repositories holding mouse models. MGD is the authoritative source of nomenclature for genes, genome features, alleles and strains following guidelines of the International Committee on Standardized Genetic Nomenclature for Mice. A new addition to MGD, the Human–Mouse: Disease Connection, allows users to explore gene–phenotype–disease relationships between human and mouse. MGD has also updated search paradigms for phenotypic allele attributes, incorporated incidental mutation data, added a module for display and exploration of genes and microRNA interactions and adopted the JBrowse genome browser. MGD resources are freely available to the scientific community.

InterMine: extensive web services for modern biology

InterMine (www.intermine.org) is a biological data warehousing system providing extensive automatically generated and configurable RESTful web services that underpin the web interface and can be re-used in many other applications: to find and filter data; export it in a flexible and structured way; to upload, use, manipulate and analyze lists; to provide services for flexible retrieval of sequence segments, and for other statistical and analysis tools. Here we describe these features and discuss how they can be used separately or in combinations to support integrative and comparative analysis.

BioJS DAGViewer: A reusable JavaScript component for displaying directed graphs

Summary: The DAGViewer BioJS component is a reusable JavaScript component made available as part of the BioJS project and intended to be used to display graphs of structured data, with a particular emphasis on Directed Acyclic Graphs (DAGs). It enables users to embed representations of graphs of data, such as ontologies or phylogenetic trees, in hyper-text documents (HTML). This component is generic, since it is capable (given the appropriate configuration) of displaying any kind of data that is organised as a graph. The features of this component which are useful for examining and filtering large and complex graphs are described.

Availability:http://github.com/alexkalderimis/dag-viewer-biojs; http://github.com/biojs/biojs; http://dx.doi.org/10.5281/zenodo.8303.

metabolicMine: an integrated genomics, genetics and proteomics data warehouse for common metabolic disease research

Common metabolic and endocrine diseases such as diabetes affect millions of people worldwide and have a major health impact, frequently leading to complications and mortality. In a search for better prevention and treatment, there is ongoing research into the underlying molecular and genetic bases of these complex human diseases, as well as into the links with risk factors such as obesity. Although an increasing number of relevant genomic and proteomic data sets have become available, the quantity and diversity of the data make their efficient exploitation challenging. Here, we present metabolicMine, a data warehouse with a specific focus on the genomics, genetics and proteomics of common metabolic diseases. Developed in collaboration with leading UK metabolic disease groups, metabolicMine integrates data sets from a range of experiments and model organisms alongside tools for exploring them. The current version brings together information covering genes, proteins, orthologues, interactions, gene expression, pathways, ontologies, diseases, genome-wide association studies and single nucleotide polymorphisms. Although the emphasis is on human data, key data sets from mouse and rat are included. These are complemented by interoperation with the RatMine rat genomics database, with a corresponding mouse version under development by the Mouse Genome Informatics (MGI) group. The web interface contains a number of features including keyword search, a library of Search Forms, the QueryBuilder and list analysis tools. This provides researchers with many different ways to analyse, view and flexibly export data. Programming interfaces and automatic code generation in several languages are supported, and many of the features of the web interface are available through web services. The combination of diverse data sets integrated with analysis tools and a powerful query system makes metabolicMine a valuable research resource. The web interface makes it accessible to first-time users, whereas the Application Programming Interface (API) and web services provide convenient data access and tools for bioinformaticians. metabolicMine is freely available online at http://www.metabolicmine.org Database URL: http://www.metabolicmine.org.