EMAP/EMAPA ontology of mouse developmental anatomy: 2013 update

Transcriptional network governing extraembryonic endoderm cell fate choice

The mechanism by which transcription factor (TF) network instructs cell-type-specific transcriptional programs to drive primitive endoderm (PrE) progenitors to commit to parietal endoderm (PE) versus visceral endoderm (VE) cell fates remains poorly understood. To address the question, we analyzed the single-cell transcriptional signatures defining PrE, PE, and VE cell states during the onset of the PE-VE lineage bifurcation. By coupling with the epigenomic comparison of active enhancers unique to PE and VE cells, we identified GATA6, SOX17, and FOXA2 as central regulators for the lineage divergence. Transcriptomic analysis of cXEN cells, an in vitro model for PE cells, after the acute depletion of GATA6 or SOX17 demonstrated that these factors induce Mycn, imparting the self-renewal properties of PE cells. Concurrently, they suppress the VE gene program, including key genes like Hnf4a and Ttr, among others. We proceeded with RNA-seq analysis on cXEN cells with FOXA2 knockout, in conjunction with GATA6 or SOX17 depletion. We found FOXA2 acts as a potent suppressor of Mycn while simultaneously activating the VE gene program. The antagonistic gene regulatory activities of GATA6/SOX17 and FOXA2 in promoting alternative cell fates, and their physical co-bindings at the enhancers provide molecular insights to the plasticity of the PrE lineage. Finally, we show that the external cue, BMP signaling, promotes the VE cell fate by activation of VE TFs and repression of PE TFs including GATA6 and SOX17. These data reveal a putative core gene regulatory module that underpins PE and VE cell fate choice.

Bridging mouse and human anatomies; a knowledge-based approach to comparative anatomy for disease model phenotyping

The laboratory mouse is the foremost mammalian model used for studying human diseases and is closely anatomically related to humans. Whilst knowledge about human anatomy has been collected throughout the history of mankind, the first comprehensive study of the mouse anatomy was published less than 60 years ago. This has been followed by the more recent publication of several books and resources on mouse anatomy. Nevertheless, to date, our understanding and knowledge of mouse anatomy is far from being at the same level as that of humans. In addition, the alignment between current mouse and human anatomy nomenclatures is far from being as developed as those existing between other species, such as domestic animals and humans. To close this gap, more in depth mouse anatomical research is needed and it will be necessary to extent and refine the current vocabulary of mouse anatomical terms.

Extending and using anatomical vocabularies in the stimulating peripheral activity to relieve conditions project

The stimulating peripheral activity to relieve conditions (SPARC) program is a US National Institutes of Health-funded effort to improve our understanding of the neural circuitry of the autonomic nervous system (ANS) in support of bioelectronic medicine. As part of this effort, the SPARC project is generating multi-species, multimodal data, models, simulations, and anatomical maps supported by a comprehensive knowledge base of autonomic circuitry. To facilitate the organization of and integration across multi-faceted SPARC data and models, SPARC is implementing the findable, accessible, interoperable, and reusable (FAIR) data principles to ensure that all SPARC products are findable, accessible, interoperable, and reusable. We are therefore annotating and describing all products with a common FAIR vocabulary. The SPARC Vocabulary is built from a set of community ontologies covering major domains relevant to SPARC, including anatomy, physiology, experimental techniques, and molecules. The SPARC Vocabulary is incorporated into tools researchers use to segment and annotate their data, facilitating the application of these ontologies for annotation of research data. However, since investigators perform deep annotations on experimental data, not all terms and relationships are available in community ontologies. We therefore implemented a term management and vocabulary extension pipeline where SPARC researchers may extend the SPARC Vocabulary using InterLex, an online vocabulary management system. To ensure the quality of contributed terms, we have set up a curated term request and review pipeline specifically for anatomical terms involving expert review. Accepted terms are added to the SPARC Vocabulary and, when appropriate, contributed back to community ontologies to enhance ANS coverage. Here, we provide an overview of the SPARC Vocabulary, the infrastructure and process for implementing the term management and review pipeline. In an analysis of >300 anatomical contributed terms, the majority represented composite terms that necessitated combining terms within and across existing ontologies. Although these terms are not good candidates for community ontologies, they can be linked to structures contained within these ontologies. We conclude that the term request pipeline serves as a useful adjunct to community ontologies for annotating experimental data and increases the FAIRness of SPARC data.

Planarian Anatomy Ontology: a resource to connect data within and across experimental platforms

As the planarian research community expands, the need for an interoperable data organization framework for tool building has become increasingly apparent. Such software would streamline data annotation and enhance cross-platform and cross-species searchability. We created the Planarian Anatomy Ontology (PLANA), an extendable relational framework of defined Schmidtea mediterranea (Smed) anatomical terms used in the field. At publication, PLANA contains over 850 terms describing Smed anatomy from subcellular to system levels across all life cycle stages, in intact animals and regenerating body fragments. Terms from other anatomy ontologies were imported into PLANA to promote interoperability and comparative anatomy studies. To demonstrate the utility of PLANA as a tool for data curation, we created resources for planarian embryogenesis, including a staging series and molecular fate-mapping atlas, and the Planarian Anatomy Gene Expression database, which allows retrieval of a variety of published transcript/gene expression data associated with PLANA terms. As an open-source tool built using FAIR (findable, accessible, interoperable, reproducible) principles, our strategy for continued curation and versioning of PLANA also provides a platform for community-led growth and evolution of this resource.

Summary: Description of the construction of an anatomy ontology tool for planaria with examples of its potential use to curate and mine data across multiple experimental platforms.

LAMA: automated image analysis for the developmental phenotyping of mouse embryos

Advanced 3D imaging modalities, such as micro-computed tomography (micro-CT), have been incorporated into the high-throughput embryo pipeline of the International Mouse Phenotyping Consortium (IMPC). This project generates large volumes of raw data that cannot be immediately exploited without significant resources of personnel and expertise. Thus, rapid automated annotation is crucial to ensure that 3D imaging data can be integrated with other multi-dimensional phenotyping data. We present an automated computational mouse embryo phenotyping pipeline that harnesses the large amount of wild-type control data available in the IMPC embryo pipeline in order to address issues of low mutant sample number as well as incomplete penetrance and variable expressivity. We also investigate the effect of developmental substage on automated phenotyping results. Designed primarily for developmental biologists, our software performs image pre-processing, registration, statistical analysis and segmentation of embryo images. We also present a novel anatomical E14.5 embryo atlas average and, using it with LAMA, show that we can uncover known and novel dysmorphology from two IMPC knockout lines.

GXD's RNA-Seq and Microarray Experiment Search: using curated metadata to reliably find mouse expression studies of interest

The Gene Expression Database (GXD), an extensive community resource of curated expression information for the mouse, has developed an RNA-Seq and Microarray Experiment Search (http://www.informatics.jax.org/gxd/htexp_index). This tool allows users to quickly and reliably find specific experiments in ArrayExpress and the Gene Expression Omnibus (GEO) that study endogenous gene expression in wild-type and mutant mice. Standardized metadata annotations, curated by GXD, allow users to specify the anatomical structure, developmental stage, mutated gene, strain and sex of samples of interest, as well as the study type and key parameters of the experiment. These searches, powered by controlled vocabularies and ontologies, can be combined with free text searching of experiment titles and descriptions. Search result summaries include link-outs to ArrayExpress and GEO, providing easy access to the expression data itself. Links to the PubMed entries for accompanying publications are also included. More information about this tool and GXD can be found at the GXD home page (http://www.informatics.jax.org/expression.shtml).

Database URL:http://www.informatics.jax.org/expression.shtml

Modelling kidney disease using ontology: insights from the Kidney Precision Medicine Project

An important need exists to better understand and stratify kidney disease according to its underlying pathophysiology in order to develop more precise and effective therapeutic agents. National collaborative efforts such as the Kidney Precision Medicine Project are working towards this goal through the collection and integration of large, disparate clinical, biological and imaging data from patients with kidney disease. Ontologies are powerful tools that facilitate these efforts by enabling researchers to organize and make sense of different data elements and the relationships between them. Ontologies are critical to support the types of big data analysis necessary for kidney precision medicine, where heterogeneous clinical, imaging and biopsy data from diverse sources must be combined to define a patient's phenotype. The development of two new ontologies - the Kidney Tissue Atlas Ontology and the Ontology of Precision Medicine and Investigation - will support the creation of the Kidney Tissue Atlas, which aims to provide a comprehensive molecular, cellular and anatomical map of the kidney. These ontologies will improve the annotation of kidney-relevant data, and eventually lead to new definitions of kidney disease in support of precision medicine.

The mouse Gene Expression Database (GXD): 2019 update

The mouse Gene Expression Database (GXD) is an extensive, well-curated community resource freely available at www.informatics.jax.org/expression.shtml. Covering all developmental stages, GXD includes data from RNA in situ hybridization, immunohistochemistry, RT-PCR, northern blot and western blot experiments in wild-type and mutant mice. GXD's gene expression information is integrated with the other data in Mouse Genome Informatics and interconnected with other databases, placing these data in the larger biological and biomedical context. Since the last report, the ability of GXD to provide insights into the molecular mechanisms of development and disease has been greatly enhanced by the addition of new data and by the implementation of new web features. These include: improvements to the Differential Gene Expression Data Search, facilitating searches for genes that have been shown to be exclusively expressed in a specified structure and/or developmental stage; an enhanced anatomy browser that now provides access to expression data and phenotype data for a given anatomical structure; direct access to the wild-type gene expression data for the tissues affected in a specific mutant; and a comparison matrix that juxtaposes tissues where a gene is normally expressed against tissues, where mutations in that gene cause abnormalities.

An atlas of evidence-based phenotypic associations across the mouse phenome

To date, reliable relationships between mammalian phenotypes, based on diagnostic test measurements, have not been reported on a large scale. The purpose of this study was to present a large mouse phenotype-phenotype relationships dataset as a reference resource, alongside detailed evaluation of the resource. We used bias-minimized comprehensive mouse phenotype data and applied association rule mining to a dataset consisting of only binary (normal and abnormal phenotypes) data to determine relationships among phenotypes. We present 3,686 evidence-based significant associations, comprising 345 phenotypes covering 60 biological systems (functions), and evaluate their characteristics in detail. To evaluate the relationships, we defined a set of phenotype-phenotype association pairs (PPAPs) as a module of phenotypic expression for each of the 345 phenotypes. By analyzing each PPAP, we identified phenotype sub-networks consisting of the largest numbers of phenotypes and distinct biological systems. Furthermore, using hierarchical clustering based on phenotype similarities among the 345 PPAPs, we identified seven community types within a putative phenome-wide association network. Moreover, to promote leverage of these data, we developed and published web-application tools. These mouse phenome-wide phenotype-phenotype association data reveal general principles of relationships among mammalian phenotypes and provide a reference resource for biomedical analyses.

Comprehensive anatomic ontologies for lung development: A comparison of alveolar formation and maturation within mouse and human lung

BACKGROUND

Although the mouse is widely used to model human lung development, function, and disease, our understanding of the molecular mechanisms involved in alveolarization of the peripheral lung is incomplete. Recently, the Molecular Atlas of Lung Development Program (LungMAP) was funded by the National Heart, Lung, and Blood Institute to develop an integrated open access database (known as BREATH) to characterize the molecular and cellular anatomy of the developing lung. To support this effort, we designed detailed anatomic and cellular ontologies describing alveolar formation and maturation in both mouse and human lung.

DESCRIPTION

While the general anatomic organization of the lung is similar for these two species, there are significant variations in the lung's architectural organization, distribution of connective tissue, and cellular composition along the respiratory tract. Anatomic ontologies for both species were constructed as partonomic hierarchies and organized along the lung's proximal-distal axis into respiratory, vascular, neural, and immunologic components. Terms for developmental and adult lung structures, tissues, and cells were included, providing comprehensive ontologies for application at varying levels of resolution. Using established scientific resources, multiple rounds of comparison were performed to identify common, analogous, and unique terms that describe the lungs of these two species. Existing biological and biomedical ontologies were examined and cross-referenced to facilitate integration at a later time, while additional terms were drawn from the scientific literature as needed. This comparative approach eliminated redundancy and inconsistent terminology, enabling us to differentiate true anatomic variations between mouse and human lungs. As a result, approximately 300 terms for fetal and postnatal lung structures, tissues, and cells were identified for each species.

CONCLUSION

These ontologies standardize and expand current terminology for fetal and adult lungs, providing a qualitative framework for data annotation, retrieval, and integration across a wide variety of datasets in the BREATH database. To our knowledge, these are the first ontologies designed to include terminology specific for developmental structures in the lung, as well as to compare common anatomic features and variations between mouse and human lungs. These ontologies provide a unique resource for the LungMAP, as well as for the broader scientific community.

Mammalian SWI/SNF collaborates with a polycomb-associated protein to regulate male germline transcription in the mouse

A deficiency in BRG1, the catalytic subunit of the SWI/SNF chromatin remodeling complex, results in a meiotic arrest during spermatogenesis. Here, we explore the causative mechanisms. BRG1 is preferentially enriched at active promoters of genes essential for spermatogonial pluripotency and meiosis. In contrast, BRG1 is also associated with the repression of somatic genes. Chromatin accessibility at these target promoters is dependent upon BRG1. These results favor a model in which BRG1 coordinates spermatogenic transcription to ensure meiotic progression. In spermatocytes, BRG1 interacts with SCML2, a testis-specific PRC1 factor that is associated with the repression of somatic genes. We present evidence to suggest that BRG1 and SCML2 concordantly regulate genes during meiosis. Furthermore, BRG1 is required for the proper localization of SCML2 and its associated deubiquitylase, USP7, to the sex chromosomes during pachynema. SCML2-associated mono-ubiquitylation of histone H2A lysine 119 (H2AK119ub1) and acetylation of histone lysine 27 (H3K27ac) are elevated in Brg1cKO testes. Coincidentally, the PRC1 ubiquitin ligase RNF2 is activated while a histone H2A/H2B deubiquitylase USP3 is repressed. Thus, BRG1 impacts the male epigenome by influencing the localization and expression of epigenetic modifiers. This mechanism highlights a novel paradigm of cooperativity between SWI/SNF and PRC1.

Common and distinct transcriptional signatures of mammalian embryonic lethality

The Deciphering the Mechanisms of Developmental Disorders programme has analysed the morphological and molecular phenotypes of embryonic and perinatal lethal mouse mutant lines in order to investigate the causes of embryonic lethality. Here we show that individual whole-embryo RNA-seq of 73 mouse mutant lines (>1000 transcriptomes) identifies transcriptional events underlying embryonic lethality and associates previously uncharacterised genes with specific pathways and tissues. For example, our data suggest that Hmgxb3 is involved in DNA-damage repair and cell-cycle regulation. Further, we separate embryonic delay signatures from mutant line-specific transcriptional changes by developing a baseline mRNA expression catalogue of wild-type mice during early embryogenesis (4-36 somites). Analysis of transcription outside coding sequence identifies deregulation of repetitive elements in Morc2a mutants and a gene involved in gene-specific splicing. Collectively, this work provides a large scale resource to further our understanding of early embryonic developmental disorders.

eHistology image and annotation data from the Kaufman Atlas of Mouse Development

“The Atlas of Mouse Development” by Kaufman is a classic paper atlas that is the de facto standard for the definition of mouse embryo anatomy in the context of standard histological images. We have redigitized the original haematoxylin and eosin–stained tissue sections used for the book at high resolution and transferred the hand-drawn annotations to digital form. We have augmented the annotations with standard ontological assignments (EMAPA anatomy) and made the data freely available via an online viewer (eHistology) and from the University of Edinburgh DataShare archive. The dataset captures and preserves the definitive anatomical knowledge of the original atlas, provides a core image set for deeper community annotation and teaching, and delivers a unique high-quality set of high-resolution histological images through mammalian development for manual and automated analysis.

High-throughput mouse phenomics for characterizing mammalian gene function

We are entering a new era of mouse phenomics, driven by large-scale and economical generation of mouse mutants coupled with increasingly sophisticated and comprehensive phenotyping. These studies are generating large, multidimensional gene-phenotype data sets, which are shedding new light on the mammalian genome landscape and revealing many hitherto unknown features of mammalian gene function. Moreover, these phenome resources provide a wealth of disease models and can be integrated with human genomics data as a powerful approach for the interpretation of human genetic variation and its relationship to disease. In the future, the development of novel phenotyping platforms allied to improved computational approaches, including machine learning, for the analysis of phenotype data will continue to enhance our ability to develop a comprehensive and powerful model of mammalian gene-phenotype space.

Selective Constraints on Coding Sequences of Nervous System Genes Are a Major Determinant of Duplicate Gene Retention in Vertebrates

The evolutionary history of vertebrates is marked by three ancient whole-genome duplications: two successive rounds in the ancestor of vertebrates, and a third one specific to teleost fishes. Biased loss of most duplicates enriched the genome for specific genes, such as slow evolving genes, but this selective retention process is not well understood. To understand what drives the long-term preservation of duplicate genes, we characterized duplicated genes in terms of their expression patterns. We used a new method of expression enrichment analysis, TopAnat, applied to in situ hybridization data from thousands of genes from zebrafish and mouse. We showed that the presence of expression in the nervous system is a good predictor of a higher rate of retention of duplicate genes after whole-genome duplication. Further analyses suggest that purifying selection against the toxic effects of misfolded or misinteracting proteins, which is particularly strong in nonrenewing neural tissues, likely constrains the evolution of coding sequences of nervous system genes, leading indirectly to the preservation of duplicate genes after whole-genome duplication. Whole-genome duplications thus greatly contributed to the expansion of the toolkit of genes available for the evolution of profound novelties of the nervous system at the base of the vertebrate radiation.

Mouse Genome Informatics (MGI) Resource: Genetic, Genomic, and Biological Knowledgebase for the Laboratory Mouse

The Mouse Genome Informatics (MGI) Resource supports basic, translational, and computational research by providing high-quality, integrated data on the genetics, genomics, and biology of the laboratory mouse. MGI serves a strategic role for the scientific community in facilitating biomedical, experimental, and computational studies investigating the genetics and processes of diseases and enabling the development and testing of new disease models and therapeutic interventions. This review describes the nexus of the body of growing genetic and biological data and the advances in computer technology in the late 1980s, including the World Wide Web, that together launched the beginnings of MGI. MGI develops and maintains a gold-standard resource that reflects the current state of knowledge, provides semantic and contextual data integration that fosters hypothesis testing, continually develops new and improved tools for searching and analysis, and partners with the scientific community to assure research data needs are met. Here we describe one slice of MGI relating to the development of community-wide large-scale mutagenesis and phenotyping projects and introduce ways to access and use these MGI data. References and links to additional MGI aspects are provided.

The mouse Gene Expression Database (GXD): 2017 update

The Gene Expression Database (GXD; www.informatics.jax.org/expression.shtml) is an extensive and well-curated community resource of mouse developmental expression information. Through curation of the scientific literature and by collaborations with large-scale expression projects, GXD collects and integrates data from RNA in situ hybridization, immunohistochemistry, RT-PCR, northern blot and western blot experiments. Expression data from both wild-type and mutant mice are included. The expression data are combined with genetic and phenotypic data in Mouse Genome Informatics (MGI) and made readily accessible to many types of database searches. At present, GXD includes over 1.5 million expression results and more than 300 000 images, all annotated with detailed and standardized metadata. Since our last report in 2014, we have added a large amount of data, we have enhanced data and database infrastructure, and we have implemented many new search and display features. Interface enhancements include: a new Mouse Developmental Anatomy Browser; interactive tissue-by-developmental stage and tissue-by-gene matrix views; capabilities to filter and sort expression data summaries; a batch search utility; gene-based expression overviews; and links to expression data from other species.

PhenoImageShare: an image annotation and query infrastructure

Background

High throughput imaging is now available to many groups and it is possible to generate a large quantity of high quality images quickly. Managing this data, consistently annotating it, or making it available to the community are all challenges that come with these methods.

Results

PhenoImageShare provides an ontology-enabled lightweight image data query, annotation service and a single point of access backed by a Solr server for programmatic access to an integrated image collection enabling improved community access. PhenoImageShare also provides an easy to use online image annotation tool with functionality to draw regions of interest on images and to annotate them with terms from an autosuggest-enabled ontology-lookup widget. The provenance of each image, and annotation, is kept and links to original resources are provided. The semantic and intuitive search interface is species and imaging technology neutral. PhenoImageShare now provides access to annotation for over 100,000 images for 2 species.

Conclusion

The PhenoImageShare platform provides underlying infrastructure for both programmatic access and user-facing tools for biologists enabling the query and annotation of federated images. PhenoImageShare is accessible online at http://www.phenoimageshare.org.

Representation of anatomy in online atlases and databases: a survey and collection of patterns for interface design

BACKGROUND

A large number of online atlases and databases have been developed to mange the rapidly growing amount of data describing embryogenesis. As these community resources continue to evolve, it is important to understand how representations of anatomy can facilitate the sharing and integration of data. In addition, attention to the design of the interfaces is critical to make online resources useful and usable.

RESULTS

I first present a survey of online atlases and gene expression resources for model organisms, with a focus on methods of semantic and spatial representation of anatomy. A total of 14 anatomical atlases and 21 gene expression resources are included. This survey demonstrates how choices in semantic representation, in the form of ontologies, can enhance interface search functions and provide links between relevant information. This survey also reviews methods for spatially representing anatomy in online resources. I then provide a collection of patterns for interface design based on the atlases and databases surveyed. These patterns include methods for displaying graphics, integrating semantic and spatial representations, organizing information, and querying databases to find genes expressed in anatomical structures.

CONCLUSIONS

This collection of patterns for interface design will assist biologists and software developers in planning the interfaces of new atlases and databases or enhancing existing ones. They also show the benefits of standardizing semantic and spatial representations of anatomy by demonstrating how interfaces can use standardization to provide enhanced functionality.

The old and new face of craniofacial research: How animal models inform human craniofacial genetic and clinical data

The craniofacial skeletal structures that comprise the human head develop from multiple tissues that converge to form the bones and cartilage of the face. Because of their complex development and morphogenesis, many human birth defects arise due to disruptions in these cellular populations. Thus, determining how these structures normally develop is vital if we are to gain a deeper understanding of craniofacial birth defects and devise treatment and prevention options. In this review, we will focus on how animal model systems have been used historically and in an ongoing context to enhance our understanding of human craniofacial development. We do this by first highlighting "animal to man" approaches; that is, how animal models are being utilized to understand fundamental mechanisms of craniofacial development. We discuss emerging technologies, including high throughput sequencing and genome editing, and new animal repository resources, and how their application can revolutionize the future of animal models in craniofacial research. Secondly, we highlight "man to animal" approaches, including the current use of animal models to test the function of candidate human disease variants. Specifically, we outline a common workflow deployed after discovery of a potentially disease causing variant based on a select set of recent examples in which human mutations are investigated in vivo using animal models. Collectively, these topics will provide a pipeline for the use of animal models in understanding human craniofacial development and disease for clinical geneticist and basic researchers alike.

Developing the eHistology Atlas

The eMouseAtlas project has undertaken to generate a new resource providing access to high-resolution colour images of the slides used in the renowned textbook 'The Atlas of Mouse Development' by Matthew H. Kaufman. The original histology slides were digitized, and the associated anatomy annotations captured for display in the new resource. These annotations were assigned to objects in the standard reference anatomy ontology, allowing the eHistology resource to be linked to other data resources including the Edinburgh Mouse Atlas Gene-Expression database (EMAGE) an the Mouse Genome Informatics (MGI) gene-expression database (GXD). The provision of the eHistology Atlas resource was assisted greatly by the expertise of the eMouseAtlas project in delivering large image datasets within a web environment, using IIP3D technology. This technology also permits future extensions to the resource through the addition of further layers of data and annotations to the resource. Database URL: www.emouseatlas.org/emap/eHistology/index.php.

eMouseAtlas informatics: embryo atlas and gene expression database

A significant proportion of developmental biology data is presented in the form of images at morphologically diverse stages of development. The curation of these datasets presents different challenges to that of sequence/text-based data. Towards this end, the eMouseAtlas project created a digital atlas of mouse embryo development as a means of understanding developmental anatomy and exploring the relationship between genes and development in a spatial context. Using the morphological staging system pioneered by Karl Theiler, the project has generated 3D models of post-implantation mouse development and used them as a spatial framework for the delineation of anatomical components and for archiving in situ gene expression data in the EMAGE database. This has allowed us to develop a unique online resource for mouse developmental biology. We describe here the underlying structure of the resource, as well as some of the tools that have been developed to allow users to mine the curated image data. These tools include our IIP3D/X3DOM viewer that allows 3D visualisation of anatomy and/or gene expression in the context of a web browser, and the eHistology resource that extends this functionality to allow visualisation of high-resolution cellular level images of histology sections. Furthermore, we review some of the informatics aspects of eMouseAtlas to provide a deeper insight into the use of the atlas and gene expression database.

My Corporis Fabrica Embryo: An ontology-based 3D spatio-temporal modeling of human embryo development

BACKGROUND

Embryology is a complex morphologic discipline involving a set of entangled mechanisms, sometime difficult to understand and to visualize. Recent computer based techniques ranging from geometrical to physically based modeling are used to assist the visualization and the simulation of virtual humans for numerous domains such as surgical simulation and learning. On the other side, the ontology-based approach applied to knowledge representation is more and more successfully adopted in the life-science domains to formalize biological entities and phenomena, thanks to a declarative approach for expressing and reasoning over symbolic information. 3D models and ontologies are two complementary ways to describe biological entities that remain largely separated. Indeed, while many ontologies providing a unified formalization of anatomy and embryology exist, they remain only descriptive and make the access to anatomical content of complex 3D embryology models and simulations difficult.

RESULTS

In this work, we present a novel ontology describing the development of the human embryology deforming 3D models. Beyond describing how organs and structures are composed, our ontology integrates a procedural description of their 3D representations, temporal deformation and relations with respect to their developments. We also created inferences rules to express complex connections between entities. It results in a unified description of both the knowledge of the organs deformation and their 3D representations enabling to visualize dynamically the embryo deformation during the Carnegie stages. Through a simplified ontology, containing representative entities which are linked to spatial position and temporal process information, we illustrate the added-value of such a declarative approach for interactive simulation and visualization of 3D embryos.

CONCLUSIONS

Combining ontologies and 3D models enables a declarative description of different embryological models that capture the complexity of human developmental anatomy. Visualizing embryos with 3D geometric models and their animated deformations perhaps paves the way towards some kind of hypothesis-driven application. These can also be used to assist the learning process of this complex knowledge.

AVAILABILITY

http://www.mycorporisfabrica.org/.

Orthology for comparative genomics in the mouse genome database

The mouse genome database (MGD) is the model organism database component of the mouse genome informatics system at The Jackson Laboratory. MGD is the international data resource for the laboratory mouse and facilitates the use of mice in the study of human health and disease. Since its beginnings, MGD has included comparative genomics data with a particular focus on human-mouse orthology, an essential component of the use of mouse as a model organism. Over the past 25 years, novel algorithms and addition of orthologs from other model organisms have enriched comparative genomics in MGD data, extending the use of orthology data to support the laboratory mouse as a model of human biology. Here, we describe current comparative data in MGD and review the history and refinement of orthology representation in this resource.

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.

Mouse anatomy ontologies: enhancements and tools for exploring and integrating biomedical data

Mouse anatomy ontologies provide standard nomenclature for describing normal and mutant mouse anatomy, and are essential for the description and integration of data directly related to anatomy such as gene expression patterns. Building on our previous work on anatomical ontologies for the embryonic and adult mouse, we have recently developed a new and substantially revised anatomical ontology covering all life stages of the mouse. Anatomical terms are organized in complex hierarchies enabling multiple relationships between terms. Tissue classification as well as partonomic, developmental, and other types of relationships can be represented. Hierarchies for specific developmental stages can also be derived. The ontology forms the core of the eMouse Atlas Project (EMAP) and is used extensively for annotating and integrating gene expression patterns and other data by the Gene Expression Database (GXD), the eMouse Atlas of Gene Expression (EMAGE) and other database resources. Here we illustrate the evolution of the developmental and adult mouse anatomical ontologies toward one combined system. We report on recent ontology enhancements, describe the current status, and discuss future plans for mouse anatomy ontology development and application in integrating data resources.

The mouse gene expression database: New features and how to use them effectively

The Gene Expression Database (GXD) is an extensive and freely available community resource of mouse developmental expression data. GXD curates and integrates expression data from the literature, via electronic data submissions, and by collaborations with large-scale projects. As an integral component of the Mouse Genome Informatics Resource, GXD combines expression data with genetic, functional, phenotypic, and disease-related data, and provides tools for the research community to search for and analyze expression data in this larger context. Recent enhancements include: an interactive browser to navigate the mouse developmental anatomy and find expression data for specific anatomical structures; the capability to search for expression data of genes located in specific genomic regions, supporting the identification of disease candidate genes; a summary displaying all the expression images that meet specified search criteria; interactive matrix views that provide overviews of spatio-temporal expression patterns (Tissue × Stage Matrix) and enable the comparison of expression patterns between genes (Tissue × Gene Matrix); data zoom and filter utilities to iteratively refine summary displays and data sets; and gene-based links to expression data from other model organisms, such as chicken, Xenopus, and zebrafish, fostering comparative expression analysis for species that are highly relevant for developmental research.

An illustrated anatomical ontology of the developing mouse lower urogenital tract

Malformation of the urogenital tract represents a considerable paediatric burden, with many defects affecting the lower urinary tract (LUT), genital tubercle and associated structures. Understanding the molecular basis of such defects frequently draws on murine models. However, human anatomical terms do not always superimpose on the mouse, and the lack of accurate and standardised nomenclature is hampering the utility of such animal models. We previously developed an anatomical ontology for the murine urogenital system. Here, we present a comprehensive update of this ontology pertaining to mouse LUT, genital tubercle and associated reproductive structures (E10.5 to adult). Ontology changes were based on recently published insights into the cellular and gross anatomy of these structures, and on new analyses of epithelial cell types present in the pelvic urethra and regions of the bladder. Ontology changes include new structures, tissue layers and cell types within the LUT, external genitalia and lower reproductive structures. Representative illustrations, detailed text descriptions and molecular markers that selectively label muscle, nerves/ganglia and epithelia of the lower urogenital system are also presented. The revised ontology will be an important tool for researchers studying urogenital development/malformation in mouse models and will improve our capacity to appropriately interpret these with respect to the human situation.

GXD: a community resource of mouse Gene Expression Data

The Gene Expression Database (GXD) is an extensive, easily searchable, and freely available database of mouse gene expression information (www.informatics.jax.org/expression.shtml). GXD was developed to foster progress toward understanding the molecular basis of human development and disease. GXD contains information about when and where genes are expressed in different tissues in the mouse, especially during the embryonic period. GXD collects different types of expression data from wild-type and mutant mice, including RNA in situ hybridization, immunohistochemistry, RT-PCR, and northern and western blot results. The GXD curators read the scientific literature and enter the expression data from those papers into the database. GXD also acquires expression data directly from researchers, including groups doing large-scale expression studies. GXD currently contains nearly 1.5 million expression results for over 13,900 genes. In addition, it has over 265,000 images of expression data, allowing users to retrieve the primary data and interpret it themselves. By being an integral part of the larger Mouse Genome Informatics (MGI) resource, GXD’s expression data are combined with other genetic, functional, phenotypic, and disease-oriented data. This allows GXD to provide tools for researchers to evaluate expression data in the larger context, search by a wide variety of biologically and biomedically relevant parameters, and discover new data connections to help in the design of new experiments. Thus, GXD can provide researchers with critical insights into the functions of genes and the molecular mechanisms of development, differentiation, and disease.

Unraveling the association between mRNA expressions and mutant phenotypes in a genome-wide assessment of mice

High-throughput gene expression profiling has revealed substantial leaky and extraneous transcription of eukaryotic genes, challenging the perceptions that transcription is strictly regulated and that changes in transcription have phenotypic consequences. To assess the functional implications of mRNA transcription directly, we analyzed mRNA expression data derived from microarrays, RNA-sequencing, and in situ hybridization, together with phenotype data of mouse mutants as a proxy of gene function at the tissue level. The results indicated that despite the presence of widespread ectopic transcription, mRNA expression and mutant phenotypes of mammalian genes or tissues remain associated. The expression-phenotype association at the gene level was particularly strong for tissue-specific genes, and the association could be underestimated due to data insufficiency and incomprehensive phenotyping of mouse mutants; the strength of expression-phenotype association at the tissue level depended on tissue functions. Mutations on genes expressed at higher levels or expressed at earlier embryonic stages more often result in abnormal phenotypes in the tissues where they are expressed. The mRNA expression profiles that have stronger associations with their phenotype profiles tend to be more evolutionarily conserved, indicating that the evolution of transcriptome and the evolution of phenome are coupled. Therefore, mutations resulting in phenotypic aberrations in expressed tissues are more likely to occur in highly transcribed genes, tissue-specific genes, genes expressed during early embryonic stages, or genes with evolutionarily conserved mRNA expression profiles.

Single-cell-level spatial gene expression in the embryonic neural differentiation niche

With the rapidly increasing availability of high-throughput in situ hybridization images, how to effectively analyze these images at high resolution for global patterns and testable hypotheses has become an urgent challenge. Here we developed a semi-automated image analysis pipeline to analyze in situ hybridization images of E14.5 mouse embryos at single-cell resolution for more than 1600 telencephalon-expressed genes from the Eurexpress database. Using this pipeline, we derived the spatial gene expression profiles at single-cell resolution across the cortical layers to gain insight into the key processes occurring during cerebral cortex development. These profiles displayed high spatial modularity in gene expression, precisely recapitulated known differentiation zones, and uncovered additional unknown transition zones or cellular states. In particular, they revealed a distinctive spatial transition phase dedicated to chromatin remodeling events during neural differentiation, which can be validated by genomic clustering patterns, epigenetic modifications switches, and network modules. Our analysis further revealed a role of mitotic checkpoints during spatial gene expression state transition. As a novel approach to analyzing at the single-cell level the spatial modularity, dynamic trajectory, and transient states of gene expression during embryonic neural differentiation and to inferring regulatory events, our approach will be useful and applicable in many different systems for understanding the dynamic differentiation processes in vivo and at high resolution.

Mouse IDGenes: a reference database for genetic interactions in the developing mouse brain

The study of developmental processes in the mouse and other vertebrates includes the understanding of patterning along the anterior–posterior, dorsal–ventral and medial– lateral axis. Specifically, neural development is also of great clinical relevance because several human neuropsychiatric disorders such as schizophrenia, autism disorders or drug addiction and also brain malformations are thought to have neurodevelopmental origins, i.e. pathogenesis initiates during childhood and adolescence. Impacts during early neurodevelopment might also predispose to late-onset neurodegenerative disorders, such as Parkinson’s disease. The neural tube develops from its precursor tissue, the neural plate, in a patterning process that is determined by compartmentalization into morphogenetic units, the action of local signaling centers and a well-defined and locally restricted expression of genes and their interactions. While public databases provide gene expression data with spatio-temporal resolution, they usually neglect the genetic interactions that govern neural development. Here, we introduce Mouse IDGenes, a reference database for genetic interactions in the developing mouse brain. The database is highly curated and offers detailed information about gene expressions and the genetic interactions at the developing mid-/hindbrain boundary. To showcase the predictive power of interaction data, we infer new Wnt/β-catenin target genes by machine learning and validate one of them experimentally. The database is updated regularly. Moreover, it can easily be extended by the research community. Mouse IDGenes will contribute as an important resource to the research on mouse brain development, not exclusively by offering data retrieval, but also by allowing data input.

Database URL:http://mouseidgenes.helmholtz-muenchen.de.

The gene expression database for mouse development (GXD): putting developmental expression information at your fingertips

Because molecular mechanisms of development are extraordinarily complex, the understanding of these processes requires the integration of pertinent research data. Using the Gene Expression Database for Mouse Development (GXD) as an example, we illustrate the progress made toward this goal, and discuss relevant issues that apply to developmental databases and developmental research in general. Since its first release in 1998, GXD has served the scientific community by integrating multiple types of expression data from publications and electronic submissions and by making these data freely and widely available. Focusing on endogenous gene expression in wild-type and mutant mice and covering data from RNA in situ hybridization, in situ reporter (knock-in), immunohistochemistry, reverse transcriptase-polymerase chain reaction, Northern blot, and Western blot experiments, the database has grown tremendously over the years in terms of data content and search utilities. Currently, GXD includes over 1.4 million annotated expression results and over 260,000 images. All these data and images are readily accessible to many types of database searches. Here we describe the data and search tools of GXD; explain how to use the database most effectively; discuss how we acquire, curate, and integrate developmental expression information; and describe how the research community can help in this process.

The zebrafish anatomy and stage ontologies: representing the anatomy and development of Danio rerio

Background

The Zebrafish Anatomy Ontology (ZFA) is an OBO Foundry ontology that is used in conjunction with the Zebrafish Stage Ontology (ZFS) to describe the gross and cellular anatomy and development of the zebrafish, Danio rerio, from single cell zygote to adult. The zebrafish model organism database (ZFIN) uses the ZFA and ZFS to annotate phenotype and gene expression data from the primary literature and from contributed data sets.

Results

The ZFA models anatomy and development with a subclass hierarchy, a partonomy, and a developmental hierarchy and with relationships to the ZFS that define the stages during which each anatomical entity exists. The ZFA and ZFS are developed utilizing OBO Foundry principles to ensure orthogonality, accessibility, and interoperability. The ZFA has 2860 classes representing a diversity of anatomical structures from different anatomical systems and from different stages of development.

Conclusions

The ZFA describes zebrafish anatomy and development semantically for the purposes of annotating gene expression and anatomical phenotypes. The ontology and the data have been used by other resources to perform cross-species queries of gene expression and phenotype data, providing insights into genetic relationships, morphological evolution, and models of human disease.

EMAGE mouse embryo spatial gene expression database: 2014 update

EMAGE (http://www.emouseatlas.org/emage/) is a freely available database of in situ gene expression patterns that allows users to perform online queries of mouse developmental gene expression. EMAGE is unique in providing both text-based descriptions of gene expression plus spatial maps of gene expression patterns. This mapping allows spatial queries to be accomplished alongside more traditional text-based queries. Here, we describe our recent progress in spatial mapping and data integration. EMAGE has developed a method of spatially mapping 3D embryo images captured using optical projection tomography, and through the use of an IIP3D viewer allows users to view arbitrary sections of raw and mapped 3D image data in the context of a web browser. EMAGE now includes enhancer data, and we have spatially mapped images from a comprehensive screen of transgenic reporter mice that detail the expression of mouse non-coding genomic DNA fragments with enhancer activity. We have integrated the eMouseAtlas anatomical atlas and the EMAGE database so that a user of the atlas can query the EMAGE database easily. In addition, we have extended the atlas framework to enable EMAGE to spatially cross-index EMBRYS whole mount in situ hybridization data. We additionally report on recent developments to the EMAGE web interface, including new query and analysis capabilities.

In silico approaches and the role of ontologies in aging research

The 2013 Rostock Symposium on Systems Biology and Bioinformatics in Aging Research was again dedicated to dissecting the aging process using in silico means. A particular focus was on ontologies, because these are a key technology to systematically integrate heterogeneous information about the aging process. Related topics were databases and data integration. Other talks tackled modeling issues and applications, the latter including talks focused on marker development and cellular stress as well as on diseases, in particular on diseases of kidney and skin.