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Housekeeping gene selection for quantitative real-time PCR assays in the seagrass Zostera marina subjected to heat stress

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http://pubman.mpdl.mpg.de/cone/persons/resource/persons56873

Ransbotyn,  Vanessa
Department Ecophysiology, Max Planck Institute for Limnology, Max Planck Institute for Evolutionary Biology, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons56884

Reusch,  Thorsten B. H.
Department Ecophysiology, Max Planck Institute for Limnology, Max Planck Institute for Evolutionary Biology, Max Planck Society;
Department Evolutionary Ecology, Max Planck Institute for Evolutionary Biology, Max Planck Society;

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Citation

Ransbotyn, V., & Reusch, T. B. H. (2006). Housekeeping gene selection for quantitative real-time PCR assays in the seagrass Zostera marina subjected to heat stress. Limnology and Oceanography: Methods, 4, 367-373.


Cite as: http://hdl.handle.net/11858/00-001M-0000-000F-D922-C
Abstract
In light of increasing sea surface temperatures, quantifying the expression of stress-inducible genes in coastal organisms is an important topic of marine molecular ecology and evolution. As a prerequisite for quantitative realtime PCR (QPCR) assays, we tested the suitability of 12 candidate housekeeping genes (HKGs) for normalization of messenger RNA abundance and quality in the ecologically important seagrass species Zostera marina. In comparing several algorithms used to identify appropriate HKGs, two approaches using reciprocal cross-validation among a larger group of HKG candidates implemented in geNorm or NormFinder yielded largely consistent results. Using these approaches, 3 HKG candidates were selected that are stable alone or in combination in the target tissue (leaf) with respect to the imposed temperature stress treatments (TATA box binding protein, translation elongation factor, eukaryotic initiation factor 4A). Example calculations revealed spurious gene expression changes of a factor of 2 in hypothetical target genes when using less stable HKGs as reference for standardization. These results highlight the need for devoting considerable effort to selecting appropriate HKGs for normalization of QPCR data before performing experiments with the target genes.