Evaluation of reference genes for RT-qPCR studies in the leaves of rice seedlings under salt stress

Abstract

ABSTRACT.To obtain accurate and reliable results for the expression of genes of interest using quantitative real-time polymerase chain reaction (RT-qPCR) techniques, it is necessary to normalize the data by comparing them to constitutive genes that exhibit uniform expression levels under experimental conditions. In this study, the stability of expression was evaluated for the following ten candidate reference genes in rice leaves (Oryza sativa L.) from the BRS Bojuru and BRS Ligeirinho genotypes that were subjected to salt stress (150 mM): actin 11 (ACT11), beta-tubulin (β-TUB), eukaryote elongation factor 1-α (Eef-1), eukaryotic initiation factor 4-α (eIF-4-α), E2 ubiquitinconjugating enzyme (UBC-E2), ubiquitin 5 (UBQ5), ubiquitin 10 (UBQ10), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), TIP41-like, and cyclophilin. The stability of expression for the aforementioned genes was then compared to that of three LTP genes using UBQ10, Eef-1, and eIF-4-α as references. After analyzing the Reference genes for RT-qPCR in rice under salt stress expression levels using analysis of variance tests, the results indicated that UBQ10 was the most stable in all treatments (M = 0.404 and SV = 0.327). Furthermore, the eIF-4-α, TIP41-like, and cyclophilin genes exhibited the highest total coefficient of variation (CV = 269, 169.2, 179.2, respectively), which signifies that they exhibited the least stable expression. The expression levels of each candidate gene (LTP7, LTP10, and LTP13) were in contrast to the reference genes. Therefore, we concluded that UBQ10 is the best reference gene for RT-qPCR reactions under the experimental conditions. The expression analysis of LTP7, LTP10, and LTP13 confirmed the importance of validating reference genes to achieve accurate RT-qPCR results.

Reference gene selection for gene expression studies in lily using quantitative real-time PCR

“…In contrast, TIP, EF, Clathrin and BHLH were good candidates for normalization in Lilium x formolongi across all samples. While for rice under salt stress, the results were different that TIP, EF, Clathrin and BHLH were not suitable as candidate reference genes (Moraes et al, 2015).…”

“…The NormFinder algorithm is based on an analysis of variance model. This algorithm evaluates the total variation in the expression of the candidate genes using the sum of variance (Moraes et al, 2015). As for BestKeeper, raw data in the form of raw Cq values generated by the RT-PCR platform are input to the BestKeeper software are on excel, separately for HKGs and TGs.…”

SUMOylation of rice DELLA SLR1 modulates transcriptional responses and improves yield under salt stress

“…The RT-qPCR reactions were carried out with the primers listed in Supplemental Table S4. PCR running conditions were: one cycle at 95ºC for 5 min and 45 cycles of amplification at 95ºC for 10 s, 56–60ºC for 10 s and 72ºC /10 s. The CT values were calculated using three technical replicates, and gene expression was assessed relative to described internal reference transcript controls, rice UBIQUITIN CONJUGASE2 (OsUBC2) and UBIQUITIN10 (OsUBQ10) (Moraes et al, 2015; Pabuayon et al, 2016). For the RNA-seq procedure, the small RNAs in the extracted total RNA samples were cleaned by using the RNeasy spin column from RNeasy Mini Kit (Qiagen) following RNA Cleanup protocol.…”

Morphophysiological analysis and expression of proline genes in rice (Oryza sativa L. cv. BRS AG) subjected to in vitro salt stress

“…The amplification conditions were as follow: 95 °C for 10 min, 40 cycles at 95 °C for 15 s, 60 °C for 1 min with the insertion of melting curve at 65 to 95 °C, incrementing 5 °C at each fluorescence measure. The OsUBQ10 gene was used as internal control (Moraes et al 2015). The relative quantification of differential expression was made using the CT (comparative threshold cycle method) method, as described by (Livak and Schmittgen, 2001).…”