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Parallel deep transcriptome and proteome analysis of zebrafish larvae

BACKGROUND: Sensitivity and throughput of transcriptomic and proteomic technologies have advanced tremendously in recent years. With the use of deep sequencing of RNA samples (RNA-seq) and mass spectrometry technology for protein identification and quantitation, it is now feasible to compare gene an...

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Autores principales: Palmblad, Magnus, Henkel, Christiaan V, Dirks, Ron P, Meijer, Annemarie H, Deelder, André M, Spaink, Herman P
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4016144/
https://www.ncbi.nlm.nih.gov/pubmed/24156766
http://dx.doi.org/10.1186/1756-0500-6-428
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author Palmblad, Magnus
Henkel, Christiaan V
Dirks, Ron P
Meijer, Annemarie H
Deelder, André M
Spaink, Herman P
author_facet Palmblad, Magnus
Henkel, Christiaan V
Dirks, Ron P
Meijer, Annemarie H
Deelder, André M
Spaink, Herman P
author_sort Palmblad, Magnus
collection PubMed
description BACKGROUND: Sensitivity and throughput of transcriptomic and proteomic technologies have advanced tremendously in recent years. With the use of deep sequencing of RNA samples (RNA-seq) and mass spectrometry technology for protein identification and quantitation, it is now feasible to compare gene and protein expression on a massive scale and for any organism for which genomic data is available. Although these technologies are currently applied to many research questions in various model systems ranging from cell cultures to the entire organism level, there are few comparative studies of these technologies in the same system, let alone on the same samples. Here we present a comparison between gene and protein expression in embryos of zebrafish, which is an upcoming model in disease studies. RESULTS: We compared Agilent custom made expression microarrays with Illumina deep sequencing for RNA analysis, showing as expected a high degree of correlation of expression of a common set of 18,230 genes. Gene expression was also found to correlate with the abundance of 963 distinct proteins, with several categories of genes as exceptions. These exceptions include ribosomal proteins, histones and vitellogenins, for which biological and technical explanations are discussed. CONCLUSIONS: By comparing state of the art transcriptomic and proteomic technologies on samples derived from the same group of organisms we have for the first time benchmarked the differences in these technologies with regard to sensitivity and bias towards detection of particular gene categories in zebrafish. Our datasets submitted to public repositories are a good starting point for researchers interested in disease progression in zebrafish at a stage of development highly suited for high throughput screening technologies.
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spelling pubmed-40161442014-05-10 Parallel deep transcriptome and proteome analysis of zebrafish larvae Palmblad, Magnus Henkel, Christiaan V Dirks, Ron P Meijer, Annemarie H Deelder, André M Spaink, Herman P BMC Res Notes Research Article BACKGROUND: Sensitivity and throughput of transcriptomic and proteomic technologies have advanced tremendously in recent years. With the use of deep sequencing of RNA samples (RNA-seq) and mass spectrometry technology for protein identification and quantitation, it is now feasible to compare gene and protein expression on a massive scale and for any organism for which genomic data is available. Although these technologies are currently applied to many research questions in various model systems ranging from cell cultures to the entire organism level, there are few comparative studies of these technologies in the same system, let alone on the same samples. Here we present a comparison between gene and protein expression in embryos of zebrafish, which is an upcoming model in disease studies. RESULTS: We compared Agilent custom made expression microarrays with Illumina deep sequencing for RNA analysis, showing as expected a high degree of correlation of expression of a common set of 18,230 genes. Gene expression was also found to correlate with the abundance of 963 distinct proteins, with several categories of genes as exceptions. These exceptions include ribosomal proteins, histones and vitellogenins, for which biological and technical explanations are discussed. CONCLUSIONS: By comparing state of the art transcriptomic and proteomic technologies on samples derived from the same group of organisms we have for the first time benchmarked the differences in these technologies with regard to sensitivity and bias towards detection of particular gene categories in zebrafish. Our datasets submitted to public repositories are a good starting point for researchers interested in disease progression in zebrafish at a stage of development highly suited for high throughput screening technologies. BioMed Central 2013-10-24 /pmc/articles/PMC4016144/ /pubmed/24156766 http://dx.doi.org/10.1186/1756-0500-6-428 Text en Copyright © 2013 Palmblad et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Palmblad, Magnus
Henkel, Christiaan V
Dirks, Ron P
Meijer, Annemarie H
Deelder, André M
Spaink, Herman P
Parallel deep transcriptome and proteome analysis of zebrafish larvae
title Parallel deep transcriptome and proteome analysis of zebrafish larvae
title_full Parallel deep transcriptome and proteome analysis of zebrafish larvae
title_fullStr Parallel deep transcriptome and proteome analysis of zebrafish larvae
title_full_unstemmed Parallel deep transcriptome and proteome analysis of zebrafish larvae
title_short Parallel deep transcriptome and proteome analysis of zebrafish larvae
title_sort parallel deep transcriptome and proteome analysis of zebrafish larvae
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4016144/
https://www.ncbi.nlm.nih.gov/pubmed/24156766
http://dx.doi.org/10.1186/1756-0500-6-428
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