No abstract

The zucchini (Cucurbita pepo) is an important food crop, the transcriptomics of which are a fundamental tool to accelerate the development of new varieties by breeders. However, the suitability of reference genes for data normalization in zucchini has not yet been studied. The aim of this study was to assess the suitability of 13 genes for their potential use as reference genes in quantitative real-time PCR. Assays were performed on 34 cDNA samples representing plants under different stresses and at different developmental stages. The application of geNorm and NormFinder software revealed that the use of a combination of UFP, EF-1A, RPL36aA, PP2A, and CAC genes for the different experimental sets was the best strategy for reliable normalization. In contrast, 18S rRNA and TUA were less stable and unsuitable for use as internal controls. These results provide the possibility to allow more accurate use of qPCR in this horticultural crop.

Reverse transcription-quantitative real-time polymerase chain reaction (RT-qPCR) is probably the most common molecular technique used in transcriptome analyses today. The simplicity of the technology and associated protocols that generate results without the need to understand the underlying principles has made RT-qPCR the method of choice for RNA quantification. Rather than the 'gold standard technology' often used to describe it, the performance of RT-qPCR suffers from considerable pitfalls during general workflow. The inconsistency of conventional methods for the evaluation of RNA quality and its influence on qPCR performance as well as stability of reference genes is summarized and discussed here.

The advent of affordable Next Generation Sequencing technologies has had major impact on studies of many crop species, where access to genomic technologies and genome-scale data sets has been extremely limited until now. The recent development of genomic resources in blueberry will enable the application of high throughput gene expression approaches that should relatively quickly increase our understanding of blueberry physiology. These studies, however, require a highly accurate and robust workflow and make necessary the identification of reference genes with high expression stability for correct target gene normalization. To create a set of superior reference genes for blueberry expression analyses, we mined a publicly available transcriptome data set from blueberry for orthologs to a set of Arabidopsis genes that showed the most stable expression in a developmental series. In total, the expression stability of 13 putative reference genes was evaluated by qPCR and a set of new references with high stability values across a developmental series in fruits and floral buds of blueberry were identified. We also demonstrated the need to use at least two, preferably three, reference genes to avoid inconsistencies in results, even when superior reference genes are used. The new references identified here provide a valuable resource for accurate normalization of gene expression in Vaccinium spp. and may be useful for other members of the Ericaceae family as well.