DMDD consortium members Richard Baldock and Chris Armit have been awarded a grant by the BBSRC to develop ePhenotype, a new visualisation tool for mouse embryo data. The tool will allow users to map phenotype deformation fields onto a reference embryo, with the hope that new insights can be gained from existing embryonic-lethal data. This exciting new project will take place at the Institute for Genetics and Molecular Medicine (IGMM) in Edinburgh, and it is expected that the tool will be available by mid-2017.
AUTOMATED PHENOTYPING AND HEAT MAPS
Automated phenotyping of mouse embryos is now a well-established technique with Micro CT data (Wong et al, 2014) and recently a proof of principle using higher-resolution HREM data from the DMDD programme was also published (Henkelman et al, 2016). The technique works by combining wild-type embryos to create an average ‘atlas’ embryo. Morphological abnormalities in the mutant can then be determined via a statistical comparison between the mutant and the atlas.
The output of these screens is typically a heat map, showing the volumetric changes between the mutant and the reference embryo.
But is there more that we can learn from this heatmap data?
The team at IGMM believe that there is much more information to be mined from phenotype heat maps. By developing ePhenotype, they plan to unlock some of these hidden secrets.
Based on the eMouseAtlas tool, ePhenotype will allow web-based visualisation of the deformation field used to match a mutant embryo to an atlas model. A web interface will allow researchers to visualise the data in the context of a 3D model, and to select 3D regions of interest to investigate further.
ePhenotype will show, in a more visual way than ever before, how mutants differ from their wild-type counterparts.
For those working on molecular phenotypes, the tool will also have the capability to map gene expression data onto a reference embryo, unlocking further insights from sequencing data.
LINKING GENOTYPE AND PHENOTYPE
Until now it has been difficult to correlate gene expression patterns with phenotype data, meaning that molecular and anatomical phenotypes have been considered quite separately.
Users of ePhenotype will be able make these links by visualising compound phenotypes from multiple embryo datasets. This will include the facility to map both gene expression patterns and phenotype data onto one atlas embryo.
ePhenotype will open up new possibilities to explore the relationship between genotype and phenotype. It is hoped that the tool will lead to new understanding of how genotype-phenotype relationships impact on embryogenesis and developmental disorders.
M. D. Wong1, Y. Maezawa2, J. P. Lerch1, R. M. Henkelman1 (2014)
Automated pipeline for anatomical phenotyping of mouse embryos using micro-CT
Development, DOI: 10.1242/dev.107722
R. Mark Henkelman1, Miriam Friedel1, Jason P. Lerch1, Robert Wilson2, Tim Mohun2 (2016)
Comparing homologous microscopic sections from multiple embryos using HREM
Developmental Biology [Epub ahead of print], DOI: 10.1016/j.ydbio.2016.05.011
Y. Wang1, N. Guo, J. Nathans
The role of Frizzled3 and Frizzled6 in neural tube closure and in the planar polarity of inner-ear sensory hair cells
J. Neuroscience, DOI:10.1523/JNEUROSCI.4698-05-2005
1 John Hopkins University School of Medicine, Baltimore, USA