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An optimised pipeline for parallel image-based quantification of gene expression and genotyping after in situ hybridisation

Advances in genome engineering have resulted in the generation of numerous zebrafish mutant lines. A commonly used method to assess gene expression in the mutants is in situ hybridisation (ISH). Because the embryos can be distinguished by genotype after ISH, comparing gene expression between wild-ty...

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Autores principales: Dobrzycki, Tomasz, Krecsmarik, Monika, Bonkhofer, Florian, Patient, Roger, Monteiro, Rui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Company of Biologists Ltd 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5936060/
https://www.ncbi.nlm.nih.gov/pubmed/29535102
http://dx.doi.org/10.1242/bio.031096
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author Dobrzycki, Tomasz
Krecsmarik, Monika
Bonkhofer, Florian
Patient, Roger
Monteiro, Rui
author_facet Dobrzycki, Tomasz
Krecsmarik, Monika
Bonkhofer, Florian
Patient, Roger
Monteiro, Rui
author_sort Dobrzycki, Tomasz
collection PubMed
description Advances in genome engineering have resulted in the generation of numerous zebrafish mutant lines. A commonly used method to assess gene expression in the mutants is in situ hybridisation (ISH). Because the embryos can be distinguished by genotype after ISH, comparing gene expression between wild-type and mutant siblings can be done blinded and in parallel. Such experimental design reduces the technical variation between samples and minimises the risk of bias. This approach, however, requires an efficient method of genomic DNA extraction from post-ISH fixed zebrafish samples to ascribe phenotype to genotype. Here we describe a method to obtain PCR-quality DNA from 95-100% of zebrafish embryos, suitable for genotyping after ISH. In addition, we provide an image analysis protocol for quantifying gene expression of ISH-probed embryos, adaptable for the analysis of different expression patterns. Finally, we show that intensity-based image analysis enables accurate representation of the variability of gene expression detected by ISH and that it can complement quantitative methods like qRT-PCR. By combining genotyping after ISH and computer-based image analysis, we have established a high-confidence, unbiased methodology to assign gene expression levels to specific genotypes, and applied it to the analysis of molecular phenotypes of newly generated lmo4a mutants.
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spelling pubmed-59360602018-05-22 An optimised pipeline for parallel image-based quantification of gene expression and genotyping after in situ hybridisation Dobrzycki, Tomasz Krecsmarik, Monika Bonkhofer, Florian Patient, Roger Monteiro, Rui Biol Open Methods & Techniques Advances in genome engineering have resulted in the generation of numerous zebrafish mutant lines. A commonly used method to assess gene expression in the mutants is in situ hybridisation (ISH). Because the embryos can be distinguished by genotype after ISH, comparing gene expression between wild-type and mutant siblings can be done blinded and in parallel. Such experimental design reduces the technical variation between samples and minimises the risk of bias. This approach, however, requires an efficient method of genomic DNA extraction from post-ISH fixed zebrafish samples to ascribe phenotype to genotype. Here we describe a method to obtain PCR-quality DNA from 95-100% of zebrafish embryos, suitable for genotyping after ISH. In addition, we provide an image analysis protocol for quantifying gene expression of ISH-probed embryos, adaptable for the analysis of different expression patterns. Finally, we show that intensity-based image analysis enables accurate representation of the variability of gene expression detected by ISH and that it can complement quantitative methods like qRT-PCR. By combining genotyping after ISH and computer-based image analysis, we have established a high-confidence, unbiased methodology to assign gene expression levels to specific genotypes, and applied it to the analysis of molecular phenotypes of newly generated lmo4a mutants. The Company of Biologists Ltd 2018-03-13 /pmc/articles/PMC5936060/ /pubmed/29535102 http://dx.doi.org/10.1242/bio.031096 Text en © 2018. Published by The Company of Biologists Ltd http://creativecommons.org/licenses/by/3.0This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution and reproduction in any medium provided that the original work is properly attributed.
spellingShingle Methods & Techniques
Dobrzycki, Tomasz
Krecsmarik, Monika
Bonkhofer, Florian
Patient, Roger
Monteiro, Rui
An optimised pipeline for parallel image-based quantification of gene expression and genotyping after in situ hybridisation
title An optimised pipeline for parallel image-based quantification of gene expression and genotyping after in situ hybridisation
title_full An optimised pipeline for parallel image-based quantification of gene expression and genotyping after in situ hybridisation
title_fullStr An optimised pipeline for parallel image-based quantification of gene expression and genotyping after in situ hybridisation
title_full_unstemmed An optimised pipeline for parallel image-based quantification of gene expression and genotyping after in situ hybridisation
title_short An optimised pipeline for parallel image-based quantification of gene expression and genotyping after in situ hybridisation
title_sort optimised pipeline for parallel image-based quantification of gene expression and genotyping after in situ hybridisation
topic Methods & Techniques
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5936060/
https://www.ncbi.nlm.nih.gov/pubmed/29535102
http://dx.doi.org/10.1242/bio.031096
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