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Normalization of qRT-PCR data: the necessity of adopting a systematic, experimental conditions-specific, validation of references
Author(s) -
Samuel Guénin,
Mélanie Mauriat,
Jérôme Pelloux,
Olivier Van Wuytswinkel,
Catherine Bellini,
Laurent Gutierrez
Publication year - 2009
Publication title -
journal of experimental botany
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.616
H-Index - 242
eISSN - 1460-2431
pISSN - 0022-0957
DOI - 10.1093/jxb/ern305
Subject(s) - housekeeping gene , normalization (sociology) , reference genes , computational biology , computer science , database normalization , biology , gene , real time polymerase chain reaction , transcriptome , data mining , systematic error , bioinformatics , genetics , statistics , gene expression , mathematics , artificial intelligence , pattern recognition (psychology) , sociology , anthropology
Quantitative RT-PCR (reverse transcription polymerase chain reaction, also known as qRT-PCR or real-time RT-PCR) has been used in large proportions of transcriptome analyses published to date. The accuracy of the results obtained by this method strongly depends on accurate transcript normalization using stably expressed genes, known as references. Statistical algorithms have been developed recently to help validate reference genes but, surprisingly, this robust approach is under-utilized in plants. Instead, putative 'housekeeping' genes tend to be used as references without any proper validation. The concept of normalization in transcript quantification is introduced here and the factors affecting its reliability in qRT-PCR are discussed in an attempt to convince molecular biologists, and non-specialists, that systematic validation of reference genes is essential for producing accurate, reliable data in qRT-PCR analyses, and thus should be an integral component of them.

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