Duncan Davidson

A High-Resolution Anatomical Atlas of the Transcriptome in the Mouse Embryo

The manuscript describes the “digital transcriptome atlas” of the developing mouse embryo, 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.

3 dimensional modelling of early human brain development using optical projection tomography.

BackgroundAs development proceeds the human embryo attains an ever more complex three dimensional (3D) structure. Analyzing the gene expression patterns that underlie these changes and interpreting their significance depends on identifying the anatomical structures to which they map and following these patterns in developing 3D structures over time. The difficulty of this task greatly increases as more gene expression patterns are added, particularly in organs with complex 3D structures such as the brain. Optical Projection Tomography (OPT) is a new technology which has been developed for rapidly generating digital 3D models of intact specimens. We have assessed the resolution of unstained neuronal structures within a Carnegie Stage (CS)17 OPT model and tested its use as a framework onto which anatomical structures can be defined and gene expression data mapped.ResultsResolution of the OPT models was assessed by comparison of digital sections with physical sections stained, either with haematoxylin and eosin (H&E) or by immunocytochemistry for GAP43 or PAX6, to identify specific anatomical features. Despite the 3D models being of unstained tissue, peripheral nervous system structures from the trigeminal ganglion (~300 μm by ~150 μm) to the rootlets of cranial nerve XII (~20 μm in diameter) were clearly identifiable, as were structures in the developing neural tube such as the zona limitans intrathalamica (core is ~30 μm thick). Fourteen anatomical domains have been identified and visualised within the CS17 model. Two 3D gene expression domains, known to be defined by Pax6 expression in the mouse, were clearly visible when PAX6 data from 2D sections were mapped to the CS17 model. The feasibility of applying the OPT technology to all stages from CS12 to CS23, which encompasses the major period of organogenesis for the human developing central nervous system, was successfully demonstrated.ConclusionIn the CS17 model considerable detail is visible within the developing nervous system at a minimum resolution of ~20 μm and 3D anatomical and gene expression domains can be defined and visualised successfully. The OPT models and accompanying technologies for manipulating them provide a powerful approach to visualising and analysing gene expression and morphology during early human brain development.

Sustaining the Data and Bioresource Commons

Globalization of biomedical research requires sustained investment for databases and biorepositories. Development of powerful, high-throughput technologies, together with globalization of scientific research, presents the biomedical research community with unprecedented challenges for the management, archiving, and distribution of data and bioresources (1). We need a social contract between funding agencies and the scientific community to accommodate “bottom-up” integration and “top-down” financing of databases and biorepositories on an international scale.

Ontologies for the description of mouse phenotypes

Ontologies are becoming increasingly important for the efficient storage, retrieval and mining of biological data. The description of phenotypes using ontologies is a particularly complex problem. We outline a schema that can be used to describe phenotypes by combining orthologous axiomatic ontologies. We also describe tools for storing, browsing and searching such complex ontologies. Central to this approach is that assays (protocols for measuring phenotypic characters) describe what has been measured as well as how this was done, allowing assays to link individual organisms to ontologies describing phenotypes. We have evaluated this approach by automatically annotating data on 600 000 mutant mice phenotypes using the SHIRPA protocol. We believe this approach will enable the flexible, extensible and detailed description of phenotypes from any organism.

3D mouse embryo model: EMA38, Stage TS16, Age E10.0 (est)

The eMouseAtlas team have generated a series of 3D images to capture mouse embryo development and to use as a spatial framework for gene-expression and other spatially organised data. The resource is published and available on the Web at http://www.emouseatlas.org/emap/ema/.

3D mouse embryo model: EMA80, Stage TS23, Age E15.0 (est)

The eMouseAtlas team have generated a series of 3D images to capture mouse embryo development and to use as a spatial framework for gene-expression and other spatially organised data. The resource is published and available on the Web at http://www.emouseatlas.org/emap/ema/.

Ontologies for the description of mouse phenotypes: Conference Papers

This conference brought the microbial genomics community together to share their most up-to-the-minute achievements, so much so that several talks cannot be covered here, as the work discussed has not yet been published. This meeting report has details of a cross-section of the talks from the sessions on ‘Genome analysis and comparative genomics’, ‘Computational genomics’ and ‘Functional genomics’, ranging from studies on complex environmental samples, to specific pathogenic bacteria, to yeasts. Copyright