Validating internal controls for quantitative plant gene expression
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. However the usefulness of these is often limited by their sensitivity and accuracy, particularly for low-abundance transcripts.In contrast, quantitative reverse transcription – polymerase chain reaction (q RT-PCR or real-time RT-PCR) allows even weakly expressed genes to be accurately quantified .Employing reference genes to normalize the data generated with quantitative PCR (q PCR) can increase the accuracy and reliability of this method.Previous results have shown that no single housekeeping gene can be universally applied to all experiments.The first aim of this study was the identification of a suitable RNA extraction method that could retrieve a high quality and yield of RNA.After this, two distinct algorithms were used to assess the gene expression of fifteen different candidate genes in eighteen different samples, which were divided into two major datasets, the developmental and the leaf gradient.
In comparison to classical reverse transcription-polymerase chain reaction (RT-PCR), the main advantages of q PCR are higher sensitivity, specificity and broad quantification range of up to seven orders of magnitude , accurate data normalization is an absolute requirement for correct measurement of gene expression.Many of these affected expression of their genetic neighbors most strongly, a pattern also seen in analysis of maize.A preliminary study in humans showed that approximately 30% of more than 2500 differentially expressed genes had a detectable genetic component to their expression level.In mice subgrouped on the basis of fat pad mass, they identified five e QTLs associated with differences in obesity, indicating the potential of this technique for identifying gene expression patterns associated with disease states or predispositions."Unlike classical quantitative traits, which often represent gross clinical measurements that may be far removed from the biological processes giving rise to them, the genetic linkages associated with transcript abundance affords a closer look at biochemical processes," conclude the authors.In an accompanying News and Views article, Ariel Darvasi of the Hebrew University, Jerusalem, Israel, notes that this technique can be applied to any organism for which both genome expression profiling and genome-wide genetic analysis can be performed efficiently.
To date, the validation of reference genes in plants has received very little attention and suitable reference genes have not been defined for a great number of crop species including .