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Automated detection and quantification of single RNAs at cellular resolution in zebrafish embryos.

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Stapel,  L Carine
Max Planck Institute of Molecular Cell Biology and Genetics, Max Planck Society;

Lombardot,  Benoit
Max Planck Society;

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Broaddus,  Coleman
Max Planck Institute of Molecular Cell Biology and Genetics, Max Planck Society;

Kainmueller,  Dagmar
Max Planck Society;

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Jug,  Florian
Max Planck Institute of Molecular Cell Biology and Genetics, Max Planck Society;

/persons/resource/persons219475

Myers,  Eugene W
Max Planck Institute of Molecular Cell Biology and Genetics, Max Planck Society;

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Vastenhouw,  Nadine
Max Planck Institute of Molecular Cell Biology and Genetics, Max Planck Society;

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Citation

Stapel, L. C., Lombardot, B., Broaddus, C., Kainmueller, D., Jug, F., Myers, E. W., et al. (2016). Automated detection and quantification of single RNAs at cellular resolution in zebrafish embryos. Development (Cambridge, England), 143(3), 540-546.


Cite as: https://hdl.handle.net/21.11116/0000-0001-0289-2
Abstract
Analysis of differential gene expression is crucial for the study of cell fate and behavior during embryonic development. However, automated methods for the sensitive detection and quantification of RNAs at cellular resolution in embryos are lacking. With the advent of single-molecule fluorescence in situ hybridization (smFISH), gene expression can be analyzed at single-molecule resolution. However, the limited availability of protocols for smFISH in embryos and the lack of efficient image analysis pipelines have hampered quantification at the (sub)cellular level in complex samples such as tissues and embryos. Here, we present a protocol for smFISH on zebrafish embryo sections in combination with an image analysis pipeline for automated transcript detection and cell segmentation. We use this strategy to quantify gene expression differences between different cell types and identify differences in subcellular transcript localization between genes. The combination of our smFISH protocol and custom-made, freely available, analysis pipeline will enable researchers to fully exploit the benefits of quantitative transcript analysis at cellular and subcellular resolution in tissues and embryos.