PUBLICATION
Detection and Automated Analysis of Single Transcripts at Subcellular Resolution in Zebrafish Embryos
- Authors
- Stapel, L.C., Broaddus, C., Vastenhouw, N.L.
- ID
- ZDB-PUB-171114-3
- Date
- 2018
- Source
- Methods in molecular biology (Clifton, N.J.) 1649: 143-162 (Chapter)
- Registered Authors
- Stapel, Carine, Vastenhouw, Nadine
- Keywords
- Automated cell segmentation, Cryosections, Transcript detection, Zebrafish, smFISH
- MeSH Terms
-
- Animals
- Automation
- Cryoultramicrotomy
- Embryo, Nonmammalian/metabolism*
- Image Processing, Computer-Assisted
- In Situ Hybridization, Fluorescence/methods*
- Paraffin Embedding
- RNA, Messenger/genetics*
- RNA, Messenger/metabolism
- Subcellular Fractions/metabolism
- Zebrafish/embryology*
- PubMed
- 29130195 Full text @ Meth. Mol. Biol.
Citation
Stapel, L.C., Broaddus, C., Vastenhouw, N.L. (2018) Detection and Automated Analysis of Single Transcripts at Subcellular Resolution in Zebrafish Embryos. Methods in molecular biology (Clifton, N.J.). 1649:143-162.
Abstract
Single molecule fluorescence in situ hybridization (smFISH) is a method to visualize single mRNA molecules. When combined with cellular and nuclear segmentation, transcripts can be assigned to different cellular compartments resulting in quantitative information on transcript levels at subcellular resolution. The use of smFISH in zebrafish has been limited by the lack of protocols and an automated image analysis pipeline for samples of multicellular organisms. Here we present a protocol for smFISH on zebrafish cryosections. The protocol includes a method to obtain high-quality sections of zebrafish embryos, an smFISH protocol optimized for zebrafish cryosections, and a user-friendly, automated analysis pipeline for cell segmentation and transcript detection. The software is freely available and can be used to analyze sections of any multicellular organism.
Genes / Markers
Expression
Phenotype
Mutations / Transgenics
Human Disease / Model
Sequence Targeting Reagents
Fish
Orthology
Engineered Foreign Genes
Mapping