A database for mouse development

Genome Sequencing and Transcriptome Profiling in Twins Discordant for Mayer-Rokitansky-Küster-Hauser Syndrome

To identify potential genetic causes for Mayer-Rokitansky-Küster-Hauser syndrome (MRKH), we analyzed blood and rudimentary uterine tissue of 5 MRKH discordant monozygotic twin pairs. Assuming that a variant solely identified in the affected twin or affected tissue could cause the phenotype, we identified a mosaic variant in ACTR3B with high allele frequency in the affected tissue, low allele frequency in the blood of the affected twin, and almost absent in blood of the unaffected twin. Focusing on MRKH candidate genes, we detected a pathogenic variant in GREB1L in one twin pair and their unaffected mother showing a reduced phenotypic penetrance. Furthermore, two variants of unknown clinical significance in PAX8 and WNT9B were identified. In addition, we conducted transcriptome analysis of affected tissue and observed perturbations largely similar to those in sporadic cases. These shared transcriptional changes were enriched for terms associated with estrogen and its receptors pointing at a role of estrogen in MRKH pathology. Our genome sequencing approach of blood and uterine tissue of discordant twins is the most extensive study performed on twins discordant for MRKH so far. As no clear pathogenic differences were detected, research to evaluate other regulatory layers are required to better understand the complex etiology of MRKH.

Museum of spatial transcriptomics

The function of many biological systems, such as embryos, liver lobules, intestinal villi, and tumors, depends on the spatial organization of their cells. In the past decade, high-throughput technologies have been developed to quantify gene expression in space, and computational methods have been developed that leverage spatial gene expression data to identify genes with spatial patterns and to delineate neighborhoods within tissues. To comprehensively document spatial gene expression technologies and data-analysis methods, we present a curated review of literature on spatial transcriptomics dating back to 1987, along with a thorough analysis of trends in the field, such as usage of experimental techniques, species, tissues studied, and computational approaches used. Our Review places current methods in a historical context, and we derive insights about the field that can guide current research strategies. A companion supplement offers a more detailed look at the technologies and methods analyzed: https://pachterlab.github.io/LP_2021/ .

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.

Leveraging Online Resources to Prioritize Candidate Genes for Functional Analyses: Using the Fetal Testis as a Test Case

With each new microarray or RNA-seq experiment, massive quantities of transcriptomic information are generated with the purpose to produce a list of candidate genes for functional analyses. Yet an effective strategy remains elusive to prioritize the genes on these candidate lists. In this review, we outline a prioritizing strategy by taking a step back from the bench and leveraging the rich range of public databases. This in silico approach provides an economical, less biased, and more effective solution. We discuss the publicly available online resources that can be used to answer a range of questions about a gene. Is the gene of interest expressed in the system of interest (using expression databases)? Where else is this gene expressed (using added-value transcriptomic resources)? What pathways and processes is the gene involved in (using enriched gene pathway analysis and mouse knockout databases)? Is this gene correlated with human diseases (using human disease variant databases)? Using mouse fetal testis as an example, our strategies identified 298 genes annotated as expressed in the fetal testis. We cross-referenced these genes to existing microarray data and narrowed the list down to cell-type-specific candidates (35 for Sertoli cells, 11 for Leydig cells, and 25 for germ cells). Our strategies can be customized so that they allow researchers to effectively and confidently prioritize genes for functional analysis.

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.

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/.

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.

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 mouse Gene Expression Database (GXD): 2014 update

The Gene Expression Database (GXD; http://www.informatics.jax.org/expression.shtml) is an extensive and well-curated community resource of mouse developmental expression information. GXD collects different types of expression data from studies of wild-type and mutant mice, covering all developmental stages and including data from RNA in situ hybridization, immunohistochemistry, RT-PCR, northern blot and western blot experiments. The data are acquired from the scientific literature and from researchers, including groups doing large-scale expression studies. Integration with the other data in Mouse Genome Informatics (MGI) and interconnections with other databases places GXD's gene expression information in the larger biological and biomedical context. Since the last report, the utility of GXD has been greatly enhanced by the addition of new data and by the implementation of more powerful and versatile search and display features. Web interface enhancements include the capability to search for expression data for genes associated with specific phenotypes and/or human diseases; new, more interactive data summaries; easy downloading of data; direct searches of expression images via associated metadata; and new displays that combine image data and their associated annotations. At present, GXD includes >1.4 million expression results and 250,000 images that are accessible to our search tools.

BioGPS and GXD: mouse gene expression data-the benefits and challenges of data integration

Mouse gene expression data are complex and voluminous. To maximize the utility of these data, they must be made readily accessible through databases, and those resources need to place the expression data in the larger biological context. Here we describe two community resources that approach these problems in different but complementary ways: BioGPS and the Mouse Gene Expression Database (GXD). BioGPS connects its large and homogeneous microarray gene expression reference data sets via plugins with a heterogeneous collection of external gene centric resources, thus casting a wide but loose net. GXD acquires different types of expression data from many sources and integrates these data tightly with other types of data in the Mouse Genome Informatics (MGI) resource, with a strong emphasis on consistency checks and manual curation. We describe and contrast the "loose" and "tight" data integration strategies employed by BioGPS and GXD, respectively, and discuss the challenges and benefits of data integration. BioGPS is freely available at http://biogps.org . GXD is freely available through the MGI web site ( www.informatics.jax.org ) or directly at www.informatics.jax.org/expression.shtml .

Biomedical atlases: systematics, informatics and analysis

Biomedical imaging is ubiquitous in the Life Sciences. Technology advances, and the resulting multitude of imaging modalities, have led to a sharp rise in the quantity and quality of such images. In addition, computational models are increasingly used to study biological processes involving spatio-temporal changes from the cell to the organism level, e.g., the development of an embryo or the growth of a tumour, and models and images are extensively described in natural language, for example, in research publications and patient records. Together this leads to a major spatio-temporal data and model integration challenge. Biomedical atlases have emerged as a key technology in solving this integration problem. Such atlases typically include an image-based (2D and/or 3D) component as well as a conceptual representation (ontologies) of the organisms involved. In this chapter, we review the notion of atlases in the biomedical domain, how they can be created, how they provide an index to spatio-temporal experimental data, issues of atlas data integration and their use for the analysis of large volumes of biomedical data.

A high-resolution anatomical atlas of the transcriptome in the mouse embryo

Ascertaining when and where genes are expressed is of crucial importance to understanding or predicting the physiological role of genes and proteins and how they interact to form the complex networks that underlie organ development and function. It is, therefore, crucial to determine on a genome-wide level, the spatio-temporal gene expression profiles at cellular resolution. This information is provided by colorimetric RNA in situ hybridization that can elucidate expression of genes in their native context and does so at cellular resolution. We generated what is to our knowledge the first genome-wide transcriptome atlas by RNA in situ hybridization of an entire mammalian organism, the developing mouse at embryonic day 14.5. This digital transcriptome atlas, the Eurexpress atlas (http://www.eurexpress.org), consists of a searchable database of annotated images that can be interactively viewed. We generated anatomy-based expression profiles for over 18,000 coding genes and over 400 microRNAs. We identified 1,002 tissue-specific genes that are a source of novel tissue-specific markers for 37 different anatomical structures. The quality and the resolution of the data revealed novel molecular domains for several developing structures, such as the telencephalon, a novel organization for the hypothalamus, and insight on the Wnt network involved in renal epithelial differentiation during kidney development. The digital transcriptome atlas is a powerful resource to determine co-expression of genes, to identify cell populations and lineages, and to identify functional associations between genes relevant to development and disease.

The mouse Gene Expression Database (GXD): 2011 update

The Gene Expression Database (GXD) is a community resource of mouse developmental expression information. GXD integrates different types of expression data at the transcript and protein level and captures expression information from many different mouse strains and mutants. GXD places these data in the larger biological context through integration with other Mouse Genome Informatics (MGI) resources and interconnections with many other databases. Web-based query forms support simple or complex searches that take advantage of all these integrated data. The data in GXD are obtained from the literature, from individual laboratories, and from large-scale data providers. All data are annotated and reviewed by GXD curators. Since the last report, the GXD data content has increased significantly, the interface and data displays have been improved, new querying capabilities were implemented, and links to other expression resources were added. GXD is available through the MGI web site (www.informatics.jax.org), or directly at www.informatics.jax.org/expression.shtml.

Visualization of image data from cells to organisms

Advances in imaging techniques and high-throughput technologies are providing scientists with unprecedented possibilities to visualize internal structures of cells, organs and organisms and to collect systematic image data characterizing genes and proteins on a large scale. To make the best use of these increasingly complex and large image data resources, the scientific community must be provided with methods to query, analyze and crosslink these resources to give an intuitive visual representation of the data. This review gives an overview of existing methods and tools for this purpose and highlights some of their limitations and challenges.

More than a decade of developmental gene expression atlases: where are we now?

To unravel regulatory networks of genes functioning during embryonic development, information on in situ gene expression is required. Enormous amounts of such data are available in literature, where each paper reports on a limited number of genes and developmental stages. The best way to make these data accessible is via spatio-temporal gene expression atlases. Eleven atlases, describing developing vertebrates and covering at least 100 genes, were reviewed. This review focuses on: (i) the used anatomical framework, (ii) the handling of input data and (iii) the retrieval of information. Our aim is to provide insights into both the possibilities of the atlases, as well as to describe what more than a decade of developmental gene expression atlases can teach us about the requirements of the design of the ‘ideal atlas’. This review shows that most ingredients needed to develop the ideal atlas are already applied to some extent in at least one of the discussed atlases. A review of these atlases shows that the ideal atlas should be based on a spatial framework, i.e. a series of 3D reference models, which is anatomically annotated using an ontology with sufficient resolution, both for relations as well as for anatomical terms.

aGEM: an integrative system for analyzing spatial-temporal gene-expression information

Motivation: The work presented here describes the ‘anatomical Gene-Expression Mapping (aGEM)’ Platform, a development conceived to integrate phenotypic information with the spatial and temporal distributions of genes expressed in the mouse. The aGEM Platform has been built by extending the Distributed Annotation System (DAS) protocol, which was originally designed to share genome annotations over the WWW. DAS is a client-server system in which a single client integrates information from multiple distributed servers.

Results: The aGEM Platform provides information to answer three main questions. (i) Which genes are expressed in a given mouse anatomical component? (ii) In which mouse anatomical structures are a given gene or set of genes expressed? And (iii) is there any correlation among these findings? Currently, this Platform includes several well-known mouse resources (EMAGE, GXD and GENSAT), hosting gene-expression data mostly obtained from in situ techniques together with a broad set of image-derived annotations.

Availability: The Platform is optimized for Firefox 3.0 and it is accessed through a friendly and intuitive display: http://agem.cnb.csic.es

Contact:natalia@cnb.csic.es

Supplementary information:Supplementary data are available at http://bioweb.cnb.csic.es/VisualOmics/aGEM/home.html and http://bioweb.cnb.csic.es/VisualOmics/index_VO.html and Bioinformatics online.

A new dynamic 3D virtual methodology for teaching the mechanics of atrial septation as seen in the human heart

Learning embryology remains difficult, since it requires understanding of many complex phenomena. The temporal evolution of developmental events has classically been illustrated using cartoons, which create difficulty in linking spatial and temporal aspects, such correlation being the keystone of descriptive embryology. We synthesized the bibliographic data from recent studies of atrial septal development. On the basis of this synthesis, consensus on the stages of atrial septation as seen in the human heart has been reached by a group of experts in cardiac embryology and pediatric cardiology. This has permitted the preparation of three-dimensional (3D) computer graphic objects for the anatomical components involved in the different stages of normal human atrial septation. We have provided a virtual guide to the process of normal atrial septation, the animation providing an appreciation of the temporal and morphologic events necessary to separate the systemic and pulmonary venous returns. We have shown that our animations of normal human atrial septation increase significantly the teaching of the complex developmental processes involved, and provide a new dynamic for the process of learning.

Multimodal, multidimensional models of mouse brain

Naturally occurring mutants and genetically manipulated strains of mice are widely used to model a variety of human diseases. Atlases are an invaluable aid in understanding the impact of such manipulations by providing a standard for comparison and to facilitate the integration of anatomic, genetic, and physiologic observations from multiple subjects and experiments. We have developed digital atlases of the C57BL/6J mouse brain (adult and neonate) as comprehensive frameworks for storing and accessing the myriad types of information about the mouse brain. Along with raw and annotated images, these contain database management systems and a set of tools for comparing information from different techniques and different animals. Each atlas establishes a canonical representation of the mouse brain and provides the tools for the manipulation and analysis of new data. We describe both these atlases and discuss how they may be put to use in organizing and analyzing data from mouse models of epilepsy.

Integrative database management for mouse development: Systems and concepts

Cells in the developing embryo must integrate complex signals from the genome and environment to make decisions about their behavior or fate. The ability to understand the fundamental biology of the decision-making process, and how these decisions may go awry during abnormal development, requires a systems biology paradigm. Presently, the ability to build models with predictive capability in birth defects research is constrained by an incomplete understanding of the fundamental parameters underlying embryonic susceptibility, sensitivity, and vulnerability. Key developmental milestones must be parameterized in terms of system structure and dynamics, the relevant control methods, and the overall design logic of metabolic and regulatory networks. High-content data from genome-based studies provide some comprehensive coverage of these operational processes but a key research challenge is data integration. Analysis can be facilitated by data management resources and software to reveal the structure and function of bionetwork motifs potentially associated with an altered developmental phenotype. Borrowing from applied mathematics and artificial intelligence, we conceptualize a system that can help address the new challenges posed by the transformation of birth defects research into a data-driven science.

The mouse Gene Expression Database (GXD): 2007 update

The Gene Expression Database (GXD) provides the scientific community with an extensive and easily searchable database of gene expression information about the mouse. Its primary emphasis is on developmental studies. By integrating different types of expression data, GXD aims to provide comprehensive information about expression patterns of transcripts and proteins in wild-type and mutant mice. Integration with the other Mouse Genome Informatics (MGI) databases places the gene expression information in the context of genetic, sequence, functional and phenotypic information, enabling valuable insights into the molecular biology that underlies developmental and disease processes. In recent years the utility of GXD has been greatly enhanced by a large increase in data content, obtained from the literature and provided by researchers doing large-scale in situ and cDNA screens. In addition, we have continued to refine our query and display features to make it easier for users to interrogate the data. GXD is available through the MGI web site at or directly at .

Integrating partonomic hierarchies in anatomy ontologies

BACKGROUND

Anatomy ontologies play an increasingly important role in developing integrated bioinformatics applications. One of the primary relationships between anatomical tissues represented in such ontologies is part-of. As there are a number of ways to divide up the anatomical structure of an organism, each may be represented by more than one valid partonomic (part-of) hierarchy. This raises the issue of how to represent and integrate multiple such hierarchies.

RESULTS

In this paper we describe a solution that is based on our work on an anatomy ontology for mouse embryo development, which is part of the Edinburgh Mouse Atlas Project (EMAP). The paper describes the basic conceptual aspects of our approach and discusses strengths and limitations of the proposed solution. A prototype was implemented in Prolog for evaluation purposes.

CONCLUSION

With the proposed name set approach, rather than having to standardise hierarchies, it is sufficient to agree on a suitable set of basic tissue terms and their meaning in order to facilitate the integration of multiple partonomic hierarchies.

A scalable mediator approach to process large biomedical 3-D images

The Edinburgh Mouse Atlas is a spatial-temporal framework to store and analyze biological data including three-dimensional (3-D) images that relate to mouse embryo development. The purpose of the system is the analysis and querying of complex spatial patterns, in particular the patterns of gene activity during embryo development. The framework holds large 3-D gray level images and is implemented in part as an object-oriented database. In this paper, we propose a dynamic layered architecture, based on the mediator approach, for the design of a transparent and scalable distributed system which can process objects that can exceed 1 GB in size. The system's data are distributed and/or declustered across a number of image servers and are processed by specialized mediators.

A multimodal, multidimensional atlas of the C57BL/6J mouse brain

Strains of mice, through breeding or the disruption of normal genetic pathways, are widely used to model human diseases. Atlases are an invaluable aid in understanding the impact of such manipulations by providing a standard for comparison. We have developed a digital atlas of the adult C57BL/6J mouse brain as a comprehensive framework for storing and accessing the myriad types of information about the mouse brain. Our implementation was constructed using several different imaging techniques: magnetic resonance microscopy, blockface imaging, classical histology and immunohistochemistry. Along with raw and annotated images, it contains database management systems and a set of tools for comparing information from different techniques. The framework allows facile correlation of results from different animals, investigators or laboratories by establishing a canonical representation of the mouse brain and providing the tools for the insertion of independent data into the same space as the atlas. This tool will aid in managing the increasingly complex and voluminous amounts of information about the mammalian brain. It provides a framework that encompasses genetic information in the context of anatomical imaging and holds tremendous promise for producing new insights into the relationship between genotype and phenotype. We describe a suite of tools that enables the independent entry of other types of data, facile retrieval of information and straightforward display of images. Thus, the atlas becomes a framework for managing complex genetic and epigenetic information about the mouse brain. The atlas and associated tools may be accessed at http://www.loni.ucla.edu/MAP.

The informatics of a C57BL/6J mouse brain atlas

The Mouse Atlas Project (MAP) aims to produce a framework for organizing and analyzing the large volumes of neuroscientific data produced by the proliferation of genetically modified animals. Atlases provide an invaluable aid in understanding the impact of genetic manipulations by providing a standard for comparison. We use a digital atlas as the hub of an informatics network, correlating imaging data, such as structural imaging and histology, with text-based data, such as nomenclature, connections, and references. We generated brain volumes using magnetic resonance microscopy (MRM), classical histology, and immunohistochemistry, and registered them into a common and defined coordinate system. Specially designed viewers were developed in order to visualize multiple datasets simultaneously and to coordinate between textual and image data. Researchers can navigate through the brain interchangeably, in either a text-based or image-based representation that automatically updates information as they move. The atlas also allows the independent entry of other types of data, the facile retrieval of information, and the straight-forward display of images. In conjunction with centralized servers, image and text data can be kept current and can decrease the burden on individual researchers' computers. A comprehensive framework that encompasses many forms of information in the context of anatomic imaging holds tremendous promise for producing new insights. The atlas and associated tools can be found at http://www.loni.ucla.edu/MAP.

The mouse Gene Expression Database (GXD): updates and enhancements

The Gene Expression Database (GXD) is a community resource for gene expression information in the laboratory mouse. By collecting and integrating different types of expression data, GXD provides information about expression profiles in different mouse strains and mutants. Participation in the Gene Ontology (GO) project classifies genes and gene products with regard to molecular functions, biological processes, and cellular components. Integration with other Mouse Genome Informatics (MGI) databases places the gene expression information in the context of mouse genetic, genomic and phenotypic information. The integration of these types of information enables valuable insights into the molecular biology that underlies development and disease. The utility of GXD has been improved by the daily addition of new data and through the implementation of new query and display features. These improvements make it easier for users to interrogate and visualize expression data in the context of their specific needs. GXD is accessible through the MGI website at http://www.informatics.jax.org/ or directly at http://www. informatics.jax.org/menus/expression_menu.shtml.

High resolution scanning and three-dimensional reconstruction of cellular events in large objects during brain development

Detailed knowledge of the spatial and temporal interactions of distinct cellular events and of the genes involved in their regulation is a precondition for the understanding of morphogenetic and pathogenetic processes. Here, how patterns of cellular events in large objects can be visualized with the help of the image acquisition system 'Huge Image' is demonstrated. Huge images are composed of a multitude of small images scanned with the highest light microscopical resolution. The system is equipped with a programmable autofocus device and permits precise and rapid cytological diagnosis. A vector-based three-dimensional (3-D) reconstruction method which, in future projects, will be combined with 'Huge Image', is applied to visualize dynamic interactions between macrophages and the occurrence of apoptotic neuroepithelial cells in the early developing forebrain of Tupaia belangeri (Scandentia). Proportionally correct meshwire surfaces of small and large objects are generated independently of each other. The combined reconstruction of cellular events and large embryonic surfaces can be carried out from only subsets of histological serial sections, and, compared with volume-based systems, with a much lower need for memory. The practicability of our approach is compared with recent other methods used to demonstrate apoptotic patterns.

Bioinformatics beyond sequence: mapping gene function in the embryo

The spatio-temporal expression pattern of a gene during development is a valuable piece of information. But there is no way to compare precisely the patterns of expression of different genes, or the way the patterns are changed in a mutant. One way to solve this problem is to construct digital reference images of development (a bioinformatics framework), to which expression patterns can be mapped and stored, then compared. Such frameworks are under active development in several model systems. They will form the basis of powerful and integrated gene expression databases, which facilitate comparisons between genes, tissues and species.

In situ hybridization: use of 35S-labeled probes on paraffin tissue sections

The following protocol is for radioactive in situ hybridization detection of RNA using paraffin-embedded tissue sections on glass microscope slides. Steps taken to inhibit RNase activity such as diethyl pyrocarbonate (DEPC) treatment of solutions and baked glassware are unnecessary. The tissue is fixed using 4% paraformaldehyde, hybridized with (35)S-labeled RNA probes, and exposed to nuclear-track emulsion. The entire procedure takes 2-3 days prior to autoradiography. The time required for autoradiography is variable with an average time of 10 days. Parameters that affect the length of the autoradiography include: (1) number of copies of mRNA in the tissue, (2) incorporation of label into the probe, and (3) amount of background signal. Additional steps involved in the autoradiography process, including development of the emulsion, cleaning of the microscope slides, counterstaining of the tissue, and mounting coverslips on the microscope slides, are discussed. In addition, a general guide to the interpretation of the in situ results is provided.

The Mouse Gene Expression Database (GXD)

The Gene Expression Database (GXD) is a community resource of gene expression information for the laboratory mouse. By combining the different types of expression data, GXD aims to provide increasingly complete information about the expression profiles of genes in different mouse strains and mutants, thus enabling valuable insights into the molecular networks that underlie normal development and disease. GXD is integrated with the Mouse Genome Database (MGD). Extensive interconnections with sequence databases and with databases from other species, and the development and use of shared controlled vocabularies extend GXD's utility for the analysis of gene expression information. GXD is accessible through the Mouse Genome Informatics web site at http://www.informatics.jax.org/ or directly at http://www.informatics.jax.org/menus/expression_menu. shtml.

Data mining in brain imaging

Data mining in brain imaging is proving to be an effective methodology for disease prognosis and prevention. This, together with the rapid accumulation of massive heterogeneous data sets, motivates the need for efficient methods that filter, clarify, assess, correlate and cluster brain-related information. Here, we present data mining methods that have been or could be employed in the analysis of brain images. These methods address two types of brain imaging data: structural and functional. We introduce statistical methods that aid the discovery of interesting associations and patterns between brain images and other clinical data. We consider several applications of these methods, such as the analysis of task-activation, lesion-deficit, and structure morphological variability; the development of probabilistic atlases; and tumour analysis. We include examples of applications to real brain data. Several data mining issues, such as that of method validation or verification, are also discussed.

Computer-based three-dimensional visualization of developmental gene expression

A broad understanding of the relationship between gene activation, pattern formation and morphogenesis will require adequate tools for three-dimensional and, perhaps four-dimensional, representation and analysis of molecular developmental processes. We present a novel, computer-based method for the 3D visualization of embryonic gene expression and morphological structures from serial sections. The information from these automatically aligned 3D reconstructions exceeds that from single-section and whole-mount visualizations of in situ hybridizations. In addition, these 3D models of gene-expression patterns can become a central component of a future developmental database designed for the collection and presentation of digitized, morphological and gene-expression data. This work is accompanied by a web site (http://www.univie.ac.at/GeneEMAC).

Histometrical and three-dimensional analyses of liver hematopoiesis in the mouse embryo

The development and cytoarchitectures of liver hematopoiesis in the mouse from 10 to 19 days of gestation were examined by light and electron microscopy. In fetal liver hematopoiesis, four stages were identified: Stage I, the onset of hematopoiesis at 10 days; Stage II, expansion of the volume of the hematopoietic compartment at 11 and 12 days; Stage III, the peak in the volume of the hematopoietic compartment at 13 and 14 days; and Stage IV, the involution of hematopoiesis after 15 days. During Stages I-II, hematopoietic stem cells appeared to move from the sinusoidal lumina into primitive hepatic cell cords through the sinusoidal endothelium to give rise to colonies among hepatoblasts. At Stage III, the hematopoietic colonies formed ellipsoidal foci as a structural unit of hematopoiesis. These foci were 35-70 x 20-40 microm in size, and erythroblastic islands could be observed in the center of each. Each island contained central macrophages surrounded by a ring of erythroblasts. The macrophages underwent mitosis, showing close contact with the erythroblasts, after which the hematopoietic foci appeared as cords. At Stage IV, these cord-shaped hematopoietic foci became disrupted, and round solitary foci including macrophages appeared within the hepatic cell cords on meandering sinusoids. In fetal liver hematopoiesis, macrophages could be one of the major cell components comprising the hematopoietic microenvironment, especially at Stages II and III.

GXD: a Gene Expression Database for the laboratory mouse: current status and recent enhancements. The Gene Expresison Database group

The Gene Expression Database (GXD) is a community resource of gene expression information for the laboratory mouse. The database is designed as an open-ended system that can integrate different types of expression data. New expression data are made available on a daily basis. Thus, GXD provides increasingly complete information about what transcripts and proteins are produced by what genes; where, when and in what amounts these gene products are expressed; and how their expression varies in different mouse strains and mutants. GXD is integrated with the Mouse Genome Database (MGD). Continuously refined interconnections with sequence databases and with databases from other species place the gene expression information in the larger biological and analytical context. GXD is accessible through the Mouse Genome Informatics Web site at http://www.informatics.jax.org/ or directly at http://www.informatics.jax.org/menus/expression_menu.shtm l

A three-dimensional model of the mouse at embryonic day 9

This paper describes a digital, three-dimensional model of the mouse embryo at E9. The model was made by reconstruction from images of serial histological sections digitally warped to remove distortions and has a resolution of approximately 9 microns. The model can be digitally resectioned in any plane to provide images which resemble conventional histological sections. The main tissues have been identified and delineated by digital painting so that the anatomical components can be visualized and manipulated in 3-D surface- and volume-rendered views. This provides a three-dimensional definition of anatomy that will provide a useful tool for interpreting and understanding spatial data in mouse embryos. The anatomy of the model is discussed where it provides landmarks for interpretation and navigation or where it is unexpected in light of existing descriptions of the E9 mouse embryo. The complete anatomy is not presented in this paper but will be available on CD-ROM. A detailed description of the technical aspects of the construction of the model is included in an appendix. The model is the first of a series that will form the basis for an atlas/database of mouse development. This reconstruction and its associated anatomy are available in a variety of data formats with some supporting software from http:@genex.hgu.mrc.ac.uk/.

Gene expression informatics--it's all in your mine

Technologies for whole-genome RNA expression studies are becoming increasingly reliable and accessible. However, universal standards to make the data more suitable for comparative analysis and for inter-operability with other information resources have yet to emerge. Improved access to large electronic data sets, reliable and consistent annotation and effective tools for 'data mining' are critical. Analysis methods that exploit large data warehouses of gene expression experiments will be necessary to realize the full potential of this technology.

Electronic access to mouse tumor data: the Mouse Tumor Biology Database (MTB) project

The Mouse Tumor Biology (MTB) Database supports the use of the mouse as a model system of hereditary and induced cancers by providing electronic access to: (i) tumor names and classifications, (ii) tumor incidence and latency data in different strains of mice, (iii) tumor pathology reports and images, (iv) information on genetic factors associated with tumors and tumor development, and (v) references (published and unpublished data). This resource has been designed to aid researchers in such areas as choosing experimental models, reviewing patterns of mutations in specific cancers, and identifying genes that are commonly mutated across a spectrum of cancers. MTB also provides hypertext links to related on-line resources and databases. MTB is accessible via the World Wide Web at http://tumor.informatics.jax.org. User support is available for MTB by Email at mgi-help@informatics.jax.org

GXD: a gene expression database for the laboratory mouse. The Gene Expression Database Group

The Gene Expression Database (GXD) is a community resource that stores and integrates expression information for the laboratory mouse, with a particular emphasis on mouse development, and makes these data freely available in formats appropriate for comprehensive analysis. GXD is implemented as a relational database and integrated with the Mouse Genome Database (MGD) to enable global analysis of genotype, expression and phenotype information. Interconnections with sequence databases and with databases from other species further extend GXD's utility for the analysis of gene expression data. GXD is available through the Mouse Genome Informatics Web Site at http://www.informatics.jax.org/

Computer-aided interactive three-dimensional reconstruction of the embryonic human heart

Despite the fact that development of the human embryo heart is of considerable clinical importance, there is still disagreement over the process and the timing of events. It is likely that some of the conflicting accounts may have arisen from difficulties in describing and visualising 3-dimensional structures from 2-dimensional sections. To help overcome this problem and to improve our understanding of the development of the heart, we have devised techniques for the production of interactive 3D models reconstructed from serial histological sections of human embryos. Our method uses commercial software designed for the creation of 3D models and virtual reality environments. The ability to construct interactive visual images which both illustrate and communicate complex 3D information contributes to our understanding of the complex developmental changes occurring in embryogenesis.

Computer-generated three-dimensional reconstructions of serially sectioned mouse embryos

We have been involved with a group of computer scientists and anatomists in the development of computer-based methodologies that not only combine the advantages of scanning electron microscopy and conventional histology, but provide the additional dimension of tissue recognition. The latter is achieved by the appropriate labelling of tissues and structures by delineation or 'painting'. Individually segmented anatomically defined tissues can be highlighted in a particular colour and viewed either in isolation or in combination with other appropriately labelled tissues and organs. Tissues can be shown in any orientation either as a transparent overlay on computer-generated histological sections or as 3-D images without the histological background. An additional feature of the system is that computer graphics technology combined with 3-D glasses now also allows the viewer to see the object under analysis in stereo. This facility has been found to be particularly helpful in drawing attention to topological relationships that had not previously been readily noted. As the mouse is now the mammalian model of choice in many areas of developmental research, it is of critical importance that a basic level of skill is available in the research community in the interpretation of serially sectioned material, for example, for the rapidly expanding field in which gene expression studies play a significant role. It is equally important that there is an understanding of the dynamic changes that occur in relation to the differentiation of the various organ systems seen in these early stages of development. What we emphasise here is the additional information that it is possible to gain from the use of this tool which, in our view, could not readily have been gained from the analysis of scanning electron micrographs or by studying conventional serial histological sections of similar stages of mouse embryonic development. The methodology has been developed as part of a large project to prepare a database of mouse developmental anatomy covering all stages from fertilisation to birth in order to allow the accurate spatial mapping of gene expression and cell lineage data onto the digital Atlas of normal mouse development. In this paper we show how this digital anatomical Atlas also represents a valuable teaching aid and research tool in anatomy.

A chromosomal deletion map of human malformations

Malformations are common causes of pediatric morbidity and mortality, and genetic factors are a significant component of their etiology. Autosomal deletions, in almost all cases, cause a nonspecific embryopathy that presents after birth as growth failure, mental retardation, and multiple malformations. We have constructed a chromosome map of autosomal deletions associated with 47 different congenital malformations, using detailed clinical and cytogenetic information on 1,753 patients with nonmosaic single contiguous autosomal deletions. The 1,753 deletions involved 258 (89%) of 289 possible autosomal bands (by the use of ISCN 400-band nomenclature), giving a total of 4,190 deleted autosomal bands for analysis. We compared the band distributions of deletions associated with common major malformations with the distribution of all 1,753 deletions. We noted 283 positive associations between deleted bands and specific malformations, of which 199 were significant (P<.05, P>.001) and 84 were highly significant (P<.001). These "malformation-associated bands" (MABs) were distributed among 137 malformation-associated chromosome regions (MACRs). An average of 6 MABs in 2.9 MACRs were detected per malformation studied; 18 (6%) of 283 MABs contain a locus known to be associated with the particular malformation. A further 18 (6%) of 283 are in seven recognized specific malformation-associated aneuploid regions. Therefore, 36 (26%) of 137 of the MACRs contain an MAB coinciding with a previously recognized locus or malformation-associated aneuploid region. This map should facilitate identification of genes important in human development.

An internet-accessible database of mouse developmental anatomy based on a systematic nomenclature

This paper reports an internet-accessible database of mouse developmental anatomy (DMDA) that currently holds a hierarchy of the names and synonyms of the tissues in the first 22 Theiler stages of development (E1-E13.5), together with other appropriate information. The purposes of the database are to provide, first, a nomenclature for analyzing normal and mutant mouse anatomy, and second a language for inputting, storing and querying gene-expression and other spatially organized data. DMDA currently contains some 6900 named and staged tissues (e.g. 360 and 1161 tissues in Theiler stage (TS) 14 (E9) and TS22 (E13.5) embryos). DMDA will be extended to include further lineage and other data when it becomes available. The database can be interactively accessed over the internet using either a Java or a non-Java WWW browser at http://genex.hgu.mrc.ac.uk/.

Cartilaginous development of the human craniovertebral junction as visualised by a new three-dimensional computer reconstruction technique

Serial transverse histological sections of the human craniovertebral junction (CVJ) of 4 normal human embryos (aged 45 to 58 d) and of a fetus (77 d) were used to create 3-dimensional computer models of the CVJ. The main components modelled included the chondrified basioccipital, atlas and axis, notochord, the vertebrobasilar complex and the spinal cord. Chondrification of the component parts of CVJ had already begun at 45 d (Stage 18). The odontoid process appeared to develop from a short eminence of the axis forming a third occipital condyle with the caudal end of the basioccipital. The cartilaginous anterior arch of C1 appeared at 50-53 d (Stages 20-21). Neural arches of C1 and C2 showed gradual closure, but there was still a wide posterior spina bifida in the oldest reconstructed specimen (77 d fetus). The position of the notochord was constant throughout. The normal course of the vertebral arteries was already established and the chondrified vertebral foramina showed progressive closure. The findings confirm that the odontoid process is not derived solely from the centrum of C1 and that there is a 'natural basilar invagination' of C2 during normal embryonic development. On the basis of the observed shape and developmental pattern of structures of the cartilaginous human CVJ, we suggest that certain pathologies are likely to originate during the chondrification phase of development.