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Related Experiment Video

Updated: May 6, 2026

Sample Preparation and Analysis of RNASeq-based Gene Expression Data from Zebrafish
11:42

Sample Preparation and Analysis of RNASeq-based Gene Expression Data from Zebrafish

Published on: October 27, 2017

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Parallel deep transcriptome and proteome analysis of zebrafish larvae.

Magnus Palmblad1, Christiaan V Henkel, Ron P Dirks

  • 1Center for Proteomics and Metabolomics, Leiden University Medical Center, Zone L04-Q, P,O, Box 9600, 2300 RC, Leiden, The Netherlands. n.m.palmblad@lumc.nl.

BMC Research Notes
|October 26, 2013
PubMed
Summary
This summary is machine-generated.

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This study compares gene and protein expression in zebrafish embryos using advanced transcriptomic and proteomic technologies. Results show high correlation but highlight exceptions like ribosomal proteins, offering insights for disease research.

Area of Science:

  • Comparative genomics and proteomics
  • Biomedical research using model organisms

Background:

  • Advancements in RNA sequencing (RNA-seq) and mass spectrometry enable large-scale gene and protein expression analysis.
  • Few studies compare these technologies using the same biological samples.
  • Zebrafish embryos are an emerging model for disease studies.

Purpose of the Study:

  • To compare gene and protein expression in zebrafish embryos.
  • To benchmark state-of-the-art transcriptomic and proteomic technologies.
  • To identify differences in sensitivity and bias between these technologies.

Main Methods:

  • Comparison of Agilent microarrays and Illumina deep sequencing for RNA analysis.
  • Correlation analysis between gene expression and protein abundance.

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Related Experiment Videos

Last Updated: May 6, 2026

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Sample Preparation and Analysis of RNASeq-based Gene Expression Data from Zebrafish

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  • Analysis of specific gene categories with differing expression patterns.

    • Main Results:

    • High correlation observed between RNA expression and protein abundance for 18,230 genes.
    • Gene expression correlated with 963 distinct proteins, with notable exceptions.
    • Exceptions include ribosomal proteins, histones, and vitellogenins, with discussed biological and technical reasons.

    Conclusions:

    • First benchmarking of transcriptomic and proteomic technology differences in zebrafish.
    • Identified sensitivities and biases in detecting specific gene categories.
    • Provided datasets for researchers studying zebrafish disease progression using high-throughput screening.