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A combined strategy of “in silico” transcriptome analysis and web search engine optimization allows an agile identification of reference genes suitable for normalization in gene expression studies

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Abstract

Traditionally housekeeping genes have been employed as endogenous reference (internal control) genes for normalization in gene expression studies. Since the utilization of single housekeepers cannot assure an unbiased result, new normalization methods involving multiple housekeeping genes and normalizing using their mean expression have been recently proposed. Moreover, since a gold standard gene suitable for every experimental condition does not exist, it is also necessary to validate the expression stability of every putative control gene on the specific requirements of the planned experiment. As a consequence, finding a good set of reference genes is for sure a non-trivial problem requiring quite a lot of lab-based experimental testing. In this work we identified novel candidate barley reference genes suitable for normalization in gene expression studies. An advanced web search approach aimed to collect, from publicly available web resources, the most interesting information regarding the expression profiling of candidate housekeepers on a specific experimental basis has been set up and applied, as an example, on stress conditions. A complementary lab-based analysis has been carried out to verify the expression profile of the selected genes in different tissues and during heat shock response. This combined dry/wet approach can be applied to any species and physiological condition of interest and can be considered very helpful to identify putative reference genes to be shortlisted every time a new experimental design has to be set up.

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Acknowledgements

This work was supported by “AGRONANOTECH” (MiPAAF) project and by “VIGNA” project.

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Authors and Affiliations

  1. CRA, Experimental Institute for Cereal Research, Via S. Protaso 302, 29017, Fiorenzuola d’Arda, PC, Italy

    Primetta Faccioli, Gian Paolo Ciceri, Antonio Michele Stanca, Caterina Morcia & Valeria Terzi

  2. Department of Genetics, Biology and Biochemistry, Molecular Biotechnology Center, University of Turin, Via Nizza 52, 10100, Torino, Italy

    Paolo Provero

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  1. Primetta Faccioli
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  2. Gian Paolo Ciceri
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  3. Paolo Provero
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  4. Antonio Michele Stanca
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  5. Caterina Morcia
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  6. Valeria Terzi
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Correspondence to Primetta Faccioli.

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Faccioli, P., Ciceri, G.P., Provero, P. et al. A combined strategy of “in silico” transcriptome analysis and web search engine optimization allows an agile identification of reference genes suitable for normalization in gene expression studies. Plant Mol Biol 63, 679–688 (2007). https://doi.org/10.1007/s11103-006-9116-9

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