, Volume 227, Issue 6, pp 1343–1349 | Cite as

Normalisation of real-time RT-PCR gene expression measurements in Arabidopsis thaliana exposed to increased metal concentrations

  • Tony Remans
  • Karen Smeets
  • Kelly Opdenakker
  • Dennis Mathijsen
  • Jaco Vangronsveld
  • Ann Cuypers
Original Article


Accurate quantification by real-time RT-PCR relies on normalisation of the measured gene expression data. Normalisation with multiple reference genes is becoming the standard, but the best reference genes for gene expression studies within one organism may depend on the applied treatments or the organs and tissues studied. Ideally, reference genes should be evaluated in all experimental systems. A number of candidate reference genes for Arabidopsis have been proposed, which can be used as a starting point to evaluate their expression stability in individual experimental systems by available computer algorithms like geNorm and NormFinder. Using this approach, we identified the best three reference genes from a set of ten candidates, which included three traditional “housekeeping” genes, for normalisation of gene expression when roots and leaves of Arabidopsis thaliana are exposed to cadmium (Cd) and copper (Cu). The expression stabilities of AT5G15710 (F-box protein), AT2G28390 (SAND family protein) and AT5G08290 (mitosis protein YLS8) were the highest when considering the effect to the roots and shoots of Cd and Cu treatments. Even though the effect of Cd and excess Cu on the plants is very different, the same best reference genes were identified when considering Cd or Cu treatments separately. This suggests that these three genes may also be suitable when studying the gene expression after exposure of Arabidopsis thaliana to increased concentrations of other metals.


Cadmium Copper Metal stress Reference genes Housekeeping genes Real-time PCR qBase geNorm NormFinder 







Reactive oxygen species

Supplementary material

425_2008_706_MOESM1_ESM.pdf (29 kb)
Average expression stability (M) and pairwise variation (V) graphs obtained from the geNorm algorithm using input of all samples (biological replicates of each treatment/organ combination entered separately). (PDF 29 kb)
425_2008_706_MOESM2_ESM.pdf (29 kb)
Average expression stability (M) and pairwise variation (V) graphs obtained from the geNorm algorithm using averaged input per treatment/organ combination for different data sets. (PDF 29 kb)
425_2008_706_MOESM3_ESM.pdf (12 kb)
"NormFinder" output for the selected data sets, obtained by using expression values for individual samples as input (A), or by using an averaged input per treatment/organ combination (B). (PDF 12 kb)


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Copyright information

© Springer-Verlag 2008

Authors and Affiliations

  • Tony Remans
    • 1
  • Karen Smeets
    • 1
  • Kelly Opdenakker
    • 1
  • Dennis Mathijsen
    • 1
  • Jaco Vangronsveld
    • 1
  • Ann Cuypers
    • 1
  1. 1.Environmental Biology Hasselt UniversityDiepenbeekBelgium

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