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A quantitative RT-PCR platform for high-throughput expression profiling of 2500 rice transcription factors

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons97097

Caldana,  C.
Small Molecules, Department Willmitzer, Max Planck Institute of Molecular Plant Physiology, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons97377

Scheible,  W.-R.
Molecular Genomics, Department Stitt, Max Planck Institute of Molecular Plant Physiology, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons97307

Mueller-Roeber,  B.
Plant Signalling, Cooperative Research Groups, Max Planck Institute of Molecular Plant Physiology, Max Planck Society;

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Caldana-2007-A quantitative RT-PC.pdf
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Zitation

Caldana, C., Scheible, W.-R., Mueller-Roeber, B., & Ruzicic, S. (2007). A quantitative RT-PCR platform for high-throughput expression profiling of 2500 rice transcription factors. Plant Methods, 3, 7. doi:10.1186/1746-4811-3-7.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-0014-2952-B
Zusammenfassung
BACKGROUND: Quantitative reverse transcription - polymerase chain reaction (qRT-PCR) has been demonstrated to be particularly suitable for the analysis of weakly expressed genes, such as those encoding transcription factors. Rice (Oryza sativa L.) is an important crop and the most advanced model for monocotyledonous species; its nuclear genome has been sequenced and molecular tools are being developed for functional analyses. However, high-throughput methods for rice research are still limited and a large-scale qRT-PCR platform for gene expression analyses has not been reported. RESULTS: We established a qRT-PCR platform enabling the multi-parallel determination of the expression levels of more than 2500 rice transcription factor genes. Additionally, using different rice cultivars, tissues and physiological conditions, we evaluated the expression stability of seven reference genes. We demonstrate this resource allows specific and reliable detection of the expression of transcription factor genes in rice. CONCLUSION: Multi-parallel qRT-PCR allows the versatile and sensitive transcriptome profiling of large numbers of rice transcription factor genes. The new platform complements existing microarray-based expression profiling techniques, by allowing the analysis of lowly expressed transcription factor genes to determine their involvement in developmental or physiological processes. We expect that this resource will be of broad utility to the scientific community in the further development of rice as an important model for plant science.