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Transcriptome analysis in non-model species: a new method for the analysis of heterologous hybridization on microarrays

BACKGROUND: Recent developments in high-throughput methods of analyzing transcriptomic profiles are promising for many areas of biology, including ecophysiology. However, although commercial microarrays are available for most common laboratory models, transcriptome analysis in non-traditional model...

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Autores principales: Degletagne, Cyril, Keime, Céline, Rey, Benjamin, de Dinechin, Marc, Forcheron, Fabien, Chuchana, Paul, Jouventin, Pierre, Gautier, Christian, Duchamp, Claude
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2901317/
https://www.ncbi.nlm.nih.gov/pubmed/20509979
http://dx.doi.org/10.1186/1471-2164-11-344
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author Degletagne, Cyril
Keime, Céline
Rey, Benjamin
de Dinechin, Marc
Forcheron, Fabien
Chuchana, Paul
Jouventin, Pierre
Gautier, Christian
Duchamp, Claude
author_facet Degletagne, Cyril
Keime, Céline
Rey, Benjamin
de Dinechin, Marc
Forcheron, Fabien
Chuchana, Paul
Jouventin, Pierre
Gautier, Christian
Duchamp, Claude
author_sort Degletagne, Cyril
collection PubMed
description BACKGROUND: Recent developments in high-throughput methods of analyzing transcriptomic profiles are promising for many areas of biology, including ecophysiology. However, although commercial microarrays are available for most common laboratory models, transcriptome analysis in non-traditional model species still remains a challenge. Indeed, the signal resulting from heterologous hybridization is low and difficult to interpret because of the weak complementarity between probe and target sequences, especially when no microarray dedicated to a genetically close species is available. RESULTS: We show here that transcriptome analysis in a species genetically distant from laboratory models is made possible by using MAXRS, a new method of analyzing heterologous hybridization on microarrays. This method takes advantage of the design of several commercial microarrays, with different probes targeting the same transcript. To illustrate and test this method, we analyzed the transcriptome of king penguin pectoralis muscle hybridized to Affymetrix chicken microarrays, two organisms separated by an evolutionary distance of approximately 100 million years. The differential gene expression observed between different physiological situations computed by MAXRS was confirmed by real-time PCR on 10 genes out of 11 tested. CONCLUSIONS: MAXRS appears to be an appropriate method for gene expression analysis under heterologous hybridization conditions.
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spelling pubmed-29013172010-07-10 Transcriptome analysis in non-model species: a new method for the analysis of heterologous hybridization on microarrays Degletagne, Cyril Keime, Céline Rey, Benjamin de Dinechin, Marc Forcheron, Fabien Chuchana, Paul Jouventin, Pierre Gautier, Christian Duchamp, Claude BMC Genomics Methodology Article BACKGROUND: Recent developments in high-throughput methods of analyzing transcriptomic profiles are promising for many areas of biology, including ecophysiology. However, although commercial microarrays are available for most common laboratory models, transcriptome analysis in non-traditional model species still remains a challenge. Indeed, the signal resulting from heterologous hybridization is low and difficult to interpret because of the weak complementarity between probe and target sequences, especially when no microarray dedicated to a genetically close species is available. RESULTS: We show here that transcriptome analysis in a species genetically distant from laboratory models is made possible by using MAXRS, a new method of analyzing heterologous hybridization on microarrays. This method takes advantage of the design of several commercial microarrays, with different probes targeting the same transcript. To illustrate and test this method, we analyzed the transcriptome of king penguin pectoralis muscle hybridized to Affymetrix chicken microarrays, two organisms separated by an evolutionary distance of approximately 100 million years. The differential gene expression observed between different physiological situations computed by MAXRS was confirmed by real-time PCR on 10 genes out of 11 tested. CONCLUSIONS: MAXRS appears to be an appropriate method for gene expression analysis under heterologous hybridization conditions. BioMed Central 2010-05-31 /pmc/articles/PMC2901317/ /pubmed/20509979 http://dx.doi.org/10.1186/1471-2164-11-344 Text en Copyright ©2010 Degletagne 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 Methodology Article
Degletagne, Cyril
Keime, Céline
Rey, Benjamin
de Dinechin, Marc
Forcheron, Fabien
Chuchana, Paul
Jouventin, Pierre
Gautier, Christian
Duchamp, Claude
Transcriptome analysis in non-model species: a new method for the analysis of heterologous hybridization on microarrays
title Transcriptome analysis in non-model species: a new method for the analysis of heterologous hybridization on microarrays
title_full Transcriptome analysis in non-model species: a new method for the analysis of heterologous hybridization on microarrays
title_fullStr Transcriptome analysis in non-model species: a new method for the analysis of heterologous hybridization on microarrays
title_full_unstemmed Transcriptome analysis in non-model species: a new method for the analysis of heterologous hybridization on microarrays
title_short Transcriptome analysis in non-model species: a new method for the analysis of heterologous hybridization on microarrays
title_sort transcriptome analysis in non-model species: a new method for the analysis of heterologous hybridization on microarrays
topic Methodology Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2901317/
https://www.ncbi.nlm.nih.gov/pubmed/20509979
http://dx.doi.org/10.1186/1471-2164-11-344
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