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Open Access Technical Note

Spatial gene expression quantification: a tool for analysis of in situ hybridizations in sea anemone Nematostella vectensis

Daniel Botman and Jaap A Kaandorp*

Author Affiliations

Section Computational Science, University of Amsterdam, Science Park 904, 1098 XH, Amsterdam, The Netherlands

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BMC Research Notes 2012, 5:555  doi:10.1186/1756-0500-5-555

Published: 5 October 2012

Abstract

Background

Spatial gene expression quantification is required for modeling gene regulation in developing organisms. The fruit fly Drosophila melanogaster is the model system most widely applied for spatial gene expression analysis due to its unique embryonic properties: the shape does not change significantly during its early cleavage cycles and most genes are differentially expressed along a straight axis. This system of development is quite exceptional in the animal kingdom.

In the sea anemone Nematostella vectensis the embryo changes its shape during early development; there are cell divisions and cell movement, like in most other metazoans. Nematostella is an attractive case study for spatial gene expression since its transparent body wall makes it accessible to various imaging techniques.

Findings

Our new quantification method produces standardized gene expression profiles from raw or annotated Nematostella in situ hybridizations by measuring the expression intensity along its cell layer. The procedure is based on digital morphologies derived from high-resolution fluorescence pictures. Additionally, complete descriptions of nonsymmetric expression patterns have been constructed by transforming the gene expression images into a three-dimensional representation.

Conclusions

We created a standard format for gene expression data, which enables quantitative analysis of in situ hybridizations from embryos with various shapes in different developmental stages. The obtained expression profiles are suitable as input for optimization of gene regulatory network models, and for correlation analysis of genes from dissimilar Nematostella morphologies. This approach is potentially applicable to many other metazoan model organisms and may also be suitable for processing data from three-dimensional imaging techniques.

Keywords:
Nematostella vectensis; Gene expression quantification; Gene network modelling; Embryonic development; Embryo morphology