Abstract
We have evaluated suitable reference genes for real time (RT)-quantitative PCR (qPCR) analysis in Japanese pear (Pyrus pyrifolia). We tested most frequently used genes in the literature such as β-Tubulin, Histone H3, Actin, Elongation factor-1α, Glyceraldehyde-3-phosphate dehydrogenase, together with newly added genes Annexin, SAND and TIP41. A total of 17 primer combinations for these eight genes were evaluated using cDNAs synthesized from 16 tissue samples from four groups, namely: flower bud, flower organ, fruit flesh and fruit skin. Gene expression stabilities were analyzed using geNorm and NormFinder software packages or by ΔCt method. geNorm analysis indicated three best performing genes as being sufficient for reliable normalization of RT-qPCR data. Suitable reference genes were different among sample groups, suggesting the importance of validation of gene expression stability of reference genes in the samples of interest. Ranking of stability was basically similar between geNorm and NormFinder, suggesting usefulness of these programs based on different algorithms. ΔCt method suggested somewhat different results in some groups such as flower organ or fruit skin; though the overall results were in good correlation with geNorm or NormFinder. Gene expression of two cold-inducible genes PpCBF2 and PpCBF4 were quantified using the three most and the three least stable reference genes suggested by geNorm. Although normalized quantities were different between them, the relative quantities within a group of samples were similar even when the least stable reference genes were used. Our data suggested that using the geometric mean value of three reference genes for normalization is quite a reliable approach to evaluating gene expression by RT-qPCR. We propose that the initial evaluation of gene expression stability by ΔCt method, and subsequent evaluation by geNorm or NormFinder for limited number of superior gene candidates will be a practical way of finding out reliable reference genes.
Highlights
Gene expression analysis is an increasingly important strategy towards advancing our understanding of the complex signaling and metabolic pathways underlying developmental and cellular processes in biological organisms including plants
The limitation of real time-quantitative PCR (RTqPCR) in its ability to assess only a limited number of genes have been overcome with the development of the microfluidic technology that allows for high-throughput measurement of gene expression using dynamic arrays [8]
New generation sequencing data is currently expanding in many plant species and real time (RT)-quantitative PCR (qPCR) provides a reliable method for validating such huge amount of RNA-seq data
Summary
Gene expression analysis is an increasingly important strategy towards advancing our understanding of the complex signaling and metabolic pathways underlying developmental and cellular processes in biological organisms including plants. Ribonuclease protection assay, reverse transcriptionpolymerase chain reaction (RT-PCR), semi-quantitative RTPCR, DNA microarrays and real time-quantitative PCR (RTqPCR) have all been applied in the analysis of gene expression [1] Among these methods, the recently developed techniques of microarray and RT-qPCR have relatively gained much prominence and wider applicability for the quantification of gene expression, owing to their inherent advantages of speed, highthroughput and automation potential. The limitation of RTqPCR in its ability to assess only a limited number of genes have been overcome with the development of the microfluidic technology that allows for high-throughput measurement of gene expression using dynamic arrays [8] This microfluidic technology, which allows 9,216 simultaneous real-time PCR transcript quantification per single run has been extended to studies in plants such as Eucalyptus [9]. New generation sequencing data is currently expanding in many plant species and RT-qPCR provides a reliable method for validating such huge amount of RNA-seq data
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