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Published on: December 22, 2017
Genomic DNA-based absolute quantification of gene expression in Vitis
Gregory A Gambetta1, Andrew J McElrone, Mark A Matthews
1Department of Viticulture and Enology, University of California at Davis, Davis, CA 95616, USA. gagambetta@ucdavis.edu
Absolute gene expression quantification in Vitis offers greater accuracy than relative methods. This approach, using genomic DNA standard curves, reduces variation and increases statistical power by avoiding faulty assumptions about reference gene stability and reaction efficiency.
Area of Science:
- Molecular Biology
- Plant Science
- Genomics
Background:
- Gene expression studies commonly use relative quantification against a reference gene (RG).
- This method relies on assumptions of RG stability and equal reaction efficiencies, which are often inaccurate.
- Experimental determination of RG variability and reaction efficiencies is rarely performed.
Purpose of the Study:
- To develop a rapid and robust method for absolute gene expression quantification in Vitis.
- To assess the variability of a reference gene (VvUbi) using absolute quantification.
- To compare absolute quantification with traditional relative quantification methods.
Main Methods:
- Absolute quantification of gene expression using polymerase chain reaction (PCR) in Vitis.
- Construction of standard curves with varying concentrations of genomic DNA for absolute quantification.
- Validation of a reference gene (VvUbi) and quantification of a gene of interest (GOI) across different tissues and studies.
Main Results:
- Reference gene (VvUbi) expression varied significantly between studies and among samples.
- Absolute quantification consistently reduced coefficients of variation for genes of interest by over 50%.
- Differences in statistical significance were observed, with absolute quantification sometimes altering fundamental results.
Conclusions:
- Genomic DNA-based absolute quantification is a fast and efficient method for Vitis gene expression analysis.
- This methodology enhances accuracy and statistical power by eliminating errors from RG stability and efficiency assumptions.
- Absolute quantification provides a more reliable assessment of gene expression compared to relative methods.
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