Reference gene validation for quantitative RT-PCR during biotic and abiotic stresses in Vitis vinifera

Grapevine is one of the most cultivated fruit crop worldwide with Vitis vinifera being the species with the highest economical importance. Being highly susceptible to fungal pathogens and increasingly affected by environmental factors, it has become an important agricultural research area, where gene expression analysis plays a fundamental role. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) is currently amongst the most powerful techniques to perform gene expression studies. Nevertheless, accurate gene expression quantification strongly relies on appropriate reference gene selection for sample normalization. Concerning V. vinifera, limited information still exists as for which genes are the most suitable to be used as reference under particular experimental conditions. In this work, seven candidate genes were investigated for their stability in grapevine samples referring to four distinct stresses (Erysiphe necator, wounding and UV-C irradiation in leaves and Phaeomoniella chlamydospora colonization in wood). The expression stability was evaluated using geNorm, NormFinder and BestKeeper. In all cases, full agreement was not observed for the three methods. To provide comprehensive rankings integrating the three different programs, for each treatment, a consensus ranking was created using a non-weighted unsupervised rank aggregation method. According to the last, the three most suitable reference genes to be used in grapevine leaves, regardless of the stress, are UBC, VAG and PEP. For the P. chlamydospora treatment, EF1, CYP and UBC were the best scoring genes. Acquaintance of the most suitable reference genes to be used in grapevine samples can contribute for accurate gene expression quantification in forthcoming studiesinfo:eu-repo/semantics/publishedVersio

Selection of Suitable Reference Genes for RT-qPCR Analyses in Cyanobacteria

Cyanobacteria are a group of photosynthetic prokaryotes that have a diverse morphology, minimal nutritional requirements and metabolic plasticity that has made them attractive organisms to use in biotechnological applications. The use of these organisms as cell factories requires the knowledge of their physiology and metabolism at a systems level. For the quantification of gene transcripts real-time quantitative polymerase chain reaction (RT-qPCR) is the standard technique. However, to obtain reliable RT-qPCR results the use and validation of reference genes is mandatory. Towards this goal we have selected and analyzed twelve candidate reference genes from three morphologically distinct cyanobacteria grown under routinely used laboratory conditions. The six genes exhibiting less variation in each organism were evaluated in terms of their expression stability using geNorm, NormFinder and BestKeeper. In addition, the minimum number of reference genes required for normalization was determined. Based on the three algorithms, we provide a list of genes for cyanobacterial RT-qPCR data normalization. To our knowledge, this is the first work on the validation of reference genes for cyanobacteria constituting a valuable starting point for future works

Reference genes for gene expression studies in wheat flag leaves grown under different farming conditions

<p>Abstract</p> <p>Background</p> <p>Internal control genes with highly uniform expression throughout the experimental conditions are required for accurate gene expression analysis as no universal reference genes exists. In this study, the expression stability of 24 candidate genes from <it>Triticum aestivum </it>cv. Cubus flag leaves grown under organic and conventional farming systems was evaluated in two locations in order to select suitable genes that can be used for normalization of real-time quantitative reverse-transcription PCR (RT-qPCR) reactions. The genes were selected among the most common used reference genes as well as genes encoding proteins involved in several metabolic pathways.</p> <p>Findings</p> <p>Individual genes displayed different expression rates across all samples assayed. Applying geNorm, a set of three potential reference genes were suitable for normalization of RT-qPCR reactions in winter wheat flag leaves cv. Cubus: <it>TaFNRII </it>(ferredoxin-NADP(H) oxidoreductase; AJ457980.1), <it>ACT2 </it>(actin 2; TC234027), and <it>rrn26 </it>(a putative homologue to RNA 26S gene; AL827977.1). In addition of these three genes that were also top-ranked by NormFinder, two extra genes: <it>CYP18-2 </it>(Cyclophilin A, AY456122.1) and <it>TaWIN1 </it>(14-3-3 like protein, AB042193) were most consistently stably expressed.</p> <p>Furthermore, we showed that <it>TaFNRII, ACT2</it>, and <it>CYP18-2 </it>are suitable for gene expression normalization in other two winter wheat varieties (Tommi and Centenaire) grown under three treatments (organic, conventional and no nitrogen) and a different environment than the one tested with cv. Cubus.</p> <p>Conclusions</p> <p>This study provides a new set of reference genes which should improve the accuracy of gene expression analyses when using wheat flag leaves as those related to the improvement of nitrogen use efficiency for cereal production.</p

Synergism between particle-based multiplexing and microfluidics technologies may bring diagnostics closer to the patient

In the field of medical diagnostics there is a growing need for inexpensive, accurate, and quick high-throughput assays. On the one hand, recent progress in microfluidics technologies is expected to strongly support the development of miniaturized analytical devices, which will speed up (bio)analytical assays. On the other hand, a higher throughput can be obtained by the simultaneous screening of one sample for multiple targets (multiplexing) by means of encoded particle-based assays. Multiplexing at the macro level is now common in research labs and is expected to become part of clinical diagnostics. This review aims to debate on the “added value” we can expect from (bio)analysis with particles in microfluidic devices. Technologies to (a) decode, (b) analyze, and (c) manipulate the particles are described. Special emphasis is placed on the challenges of integrating currently existing detection platforms for encoded microparticles into microdevices and on promising microtechnologies that could be used to down-scale the detection units in order to obtain compact miniaturized particle-based multiplexing platforms