Tag Archives: CED

In plants, nitrogen is the most important nutritional factor limiting the

In plants, nitrogen is the most important nutritional factor limiting the yield of cultivated crops. of expression. In addition, our results suggest the inclusion of 3 or 4 4 references to obtain highly reliable results of target genes expression in all cucumber organs under nitrogen-related stress. Introduction Real-time 452105-23-6 manufacture quantitative reverse transcription polymerase chain reaction (RT-qPCR) is currently the method of choice for mRNA transcription studies, since it provides outputs with high sensitivity, specificity and capacity [1], [2]. However, for accurate gene expression quantification, it is essential to normalize real-time PCR data to a fixed reference. Reference genes are commonly referred to as genes of highly reliable expression, which is not affected by numerous experimental settings and is stable in different types of tissues and organs used in the assay [3]. The most widely used internal controls include the genes encoding: actin and tubulin (alpha/beta), cytoskeletal proteins; glyceraldehyde 3-phosphate dehydrogenase (GAPDH), involved in glycolysis; ubiquitins (UBQs), involved in the degradation of cellular proteins; 18S RNA, a part of the ribosomal functional core; RNA polymerase II (RPII or POLR2A), catalyzing the synthesis of the precursors of mRNA, most snRNA and microRNA; elongation factor 1-alpha (EF1), which facilitates translational elongation; tyrosine-3 monooxygenase/tryptophan-5 monooxygenase activation protein; zeta polypeptide ((or and cDNAs, Blastn [47] and FGENESH or FGENESH+ [48] softwares. The genomic business and putative function of all selected CED candidate genes are offered in table 1. The gene encoding cucumber nitrate transporter NRT1.1 was used as the target for the normalization of expression data. Primer pairs around the selected reference and target gene sequences (Table S1) were designed using the Lightcycler Probe Design software (Roche), with the conditions of 154C290 base pairs (bp) as the PCR amplicon length and 60C as the optimal Tm (melting heat). Table 1 Description of cucumber candidate reference genes based on the comparison with their Arabidopsis orthologs. Amplification of gene transcripts The expression study was performed using a 96 well plate on an Lightcycler 480 (Roche) with 2 SYBR Green Mix B (A&A Biotechnology). The reactions were performed according to the manufacturer’s instructions: the 452105-23-6 manufacture PCR program was initiated at 95C for 10 min to activate DNA polymerase, followed by 45 thermal cycles of 10 seconds at 94C, 10 seconds at 452105-23-6 manufacture 60C and 15 seconds at 72C. Melting curve analysis was performed immediately after the real-time PCR. The heat range utilized for the melting curve generation was from 65C to 95C. All assays were performed using three technical and biological replicates, a non-template 452105-23-6 manufacture control and a non-RT control. 452105-23-6 manufacture The standard curves were generated by amplifying at least seven dilution series of cDNA (Table S1). The correlation coefficient (R2) and PCR efficiency were calculated using the slopes of the standard curves (Physique S2). The linear R2 for all the primers ranged between 0.978C0.999, whereas PCR efficiencies of primers ranged from 95%C105% (Determine S2, Table S1). To confirm the PCR products size, the reactions were subjected to electrophoresis on 2.0% agarose gels stained with ethidium bromide following Real-time PCR assay. The determination of the crossing amplification point (Cp) as well as the relative quantification analysis (CT-method) were performed using the Lightcycler 480 software 1.5. The amplification of non-template controls generated Cp values above 45 or was not detectable. The non-normalized expression data were analyzed by geNorm v3.5 and NormFinder version 2 whereas the raw Cp values were imported into BestKeeper version 1. The evaluation of reference gene expression stability Considering the heterogeneity of treatments, the biological samples from 2-week-old plants and 4-week-old plants were analyzed separately. For each analysis of stability of gene expression, four subsets were established based on the organ used, including roots, stems, leaves and all organs of cucumber plants. At first, the reliability of all twelve cucumber candidate genes was evaluated using two different statistical algorithms, geNorm [14] and NormFinder [17]. Based on the their outputs, the two worst references were removed and the expression stability of the remaining ten genes was further validated using BestKeeper [18]. All three Visual Basic applets for Microsoft Excel base on different principles. The geNorm calculates an internal control gene-stability measure as the average pairwise variation of each gene with other candidate genes and select two ideal recommendations through the sequential exclusion of genes with the lowest stability of expression [14]..