Quantification of gene expression patterns to reveal the origins of abnormal morphogenesis
Preprint posted on January 11, 2018 https://www.biorxiv.org/content/early/2018/01/11/246256
In this pre-print, the Sharpe lab develops a tool to quantitatively characterize gene expression patterns in whole embryos. They identify a limb defect in a mouse model of Apert syndrome carrying a missense mutation on the Fibroblast Growth Factor Receptor 2. In particular, quantifying downstream target Dusp6 allows them to spot the appearance of the limb defects, which have previously remained difficult to discern in mouse models of Apert syndrome.
Why I chose the paper:
One of my mantras is that new discoveries arise when biological phenomena are revisited in quantitative terms, even though they could have been previously studied on the basis of qualitative analysis; this preprint nicely provides a new look at gene expression.
The description of gene expression patterns over time during development is the pillar for our understanding of how genes work. In situ hybridisation is as a long existing technique that can be performed in any organism that contains RNA, and it has been used to unravel where and when genes are expressed. However, this technique has always been considered qualitative, difficult to analyse in whole embryos, and subjective at times. Neus Martinez-Abadias and colleagues develop a tool that allows them to accurately measure and determine subtle spatial changes in gene expression patterns in mouse mutants by combining image analysis, segmentation, and geometric morphometrics. There are very few examples where morphometric approaches have been applied to study morphological variability, and precisely relate it to gene expression. In the method, the authors first image and segment the shape of the tissue, and the expression pattern of Dusp6. Then, they describe its shape in 3D as a set of landmark coordinates. In this way, they objectively compare tissue morphology with a given gene expression pattern across embryos at various developmental stages to identify previously unrecognised limb defects at the molecular level.
How this work moves the field forward:
This preprint advances our understanding of how spatio-temporal changes in gene expression culminate in phenotypic variation, and builds the path towards quantitative developmental biology.
Questions to the authors:
Since the technique is very powerful, I wonder the amount of time the authors dedicated to process the data, and how easily could it be applied in other labs.
Which do the authors think are the limitations of the technique?
How subtle can the changes be to define a given phenotype?
Have they tried to do the analysis with more than one gene?
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