What is EMAGE?

EMAGE is a database of in situ gene expression data in the mouse embryo and an accompanying suite of tools to search and analyse the data.

mRNA in situ hybridisation, protein immunohistochemistry, in situ transgenic reporter data, and in situ enhancer data is included. These are sourced from the community and our curators take this data and describe it in a standardised way that allows data query and exchange. The description includes a text-based component but the unique aspect of EMAGE is its spatial annotation focus.

A brief description of the main concepts are given below. For a more in-depth explanation, please refer to this pdf document.


  • The conceptual framework which houses the descriptions of the expression patterns in EMAGE is the EMAP Mouse Embryo Anatomy Atlas.

    This consists of a set of 3D virtual embryos at different stages of development, as well as an accompanying ontology of anatomical terms found at each stage:
EMAP Atlas Schematic

Schematic representation of the EMAP Mouse Embryo Anatomy Atlas.

The panel on the left shows the set of virtual 3D embryos at different stages of development. The panel on the right shows an example of the hierarchically organised anatomy ontology at one stage of development (one 'anatomy tree' exists for each stage of development).
The 3D models and the anatomy ontology are linked by 3D regions (shown in the different colours) that have been defined within the virtual embryos that correspond to specific anatomy terms in the ontology. In this example the ontology and domains are shown for the TS07 (~5dpc) embryo. Larger image.


  • Sites of gene/enhancer expression in EMAGE are described by denoting appropriate regions in the EMAP virtual embryos where expression is detected (and not detected) and also describing this information with an accompanying text-based description, which is achieved by referring to appropriate terms in the anatomy ontology:
EMAGE Data Annotation Schematic Explanation

EMAGE Data Annotation Methods

The upper panel shows two examples of WM data annotation. Both show right-hand side views of WM stained embryos at TS15 (~9.5dpc). These have both spatially annotated to the corresponding right-hand side view of the TS15 model. The different colours represent different levels of expression (e.g. red = strong, yellow = moderate, and cyan = no detectable expression).

The lower panel shows two examples of section data annotation. Both depict views of sections (either 1 or 3 sections) taken from TS12(~8.0dpc) embryos. These have been spatially annotated onto an appropriately matching section plane chosen from the TS12 virtual embryo. Views of the spatial annotations are shown here directly on the virtual section planes and in the 3D context of the virtual embryo model.

The accompanying text annotations to terms in the EMAP anatomy ontology (right-hand column), are based on the original descriptions given by the author. Larger image.


  • Spatial mapping is used to warp raw image data onto a stage-matched model. This allows the EMAGE Editorial Team to spatially map gene expression patterns.

3d mapping


3d mapping

3d mapping


EMAGE 3D Spatial Warp

The upper panel shows points of equivalence or landmark points that are manually added to 3D rawimage data and a stage-matched 3D model. These landmark points are used to spatially warp the raw image data onto the 3D model. This warping procedure utilises a Constrained Distance Transform (CDT) and allows the EMAGE Editorial Team to spatially map gene expression patterns

The middle panel highlights the steps that are used to generate a space-filling tetrahedral mesh that is utilised by the CDT. A domain is derived from the embryo model, but not the surrounding space, and this is used to generate a 3D mesh that accurately describes the 3D model. Internal spaces in the embryo, such as the neural lumen of the developing brain, are also omitted from the mesh. The mesh serves to constrain the spatial warp, allowing for an organic deformation of raw image data.

The lower panel shows raw OPT data and this gene expression pattern spatially mapped onto a grayscale model.



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