Identification of valid reference genes for the normalization of RT qPCR gene expression data in human brain tissue

Background

Transfection of cells with gene-specific, single-stranded oligonucleotides can induce the targeted exchange of one or two nucleotides in the targeted gene. To characterize the features of the DNA-repair mechanisms involved, we examined the maximal distance for the simultaneous exchange of two nucleotides by a single-stranded oligonucleotide. The chosen experimental system was the correction of a hprt-point mutation in a hamster cell line, the generation of an additional nucleotide exchange at a variable distance from the first exchange position and the investigation of the rate of simultaneous nucleotide exchanges.

Results

The smaller the distance between the two exchange positions, the higher was the probability of a simultaneous exchange. The detected simultaneous nucleotide exchanges were found to cluster in a region of about fourteen nucleotides upstream and downstream from the first exchange position.

Conclusion

We suggest that the mechanism involved in the repair of the targeted DNA strand utilizes only a short sequence of the single-stranded oligonucleotide, which may be physically incorporated into the DNA or be used as a matrix for a repair process.     

RNA-Seq is not required to determine stable reference genes for qPCR normalization

Assessment of differential gene expression by qPCR is heavily influenced by the choice of reference genes. Although numerous statistical approaches have been proposed to determine the best reference genes, they can give rise to conflicting results depending on experimental conditions. Hence, recent studies propose the use of RNA-Seq to identify stable genes followed by the application of different statistical approaches to determine the best set of reference genes for qPCR data normalization. In this study, however, we demonstrate that the statistical approach to determine the best reference genes from commonly used conventional candidates is more important than the preselection of ‘stable’ candidates from RNA-Seq data. Using a qPCR data normalization workflow that we have previously established; we show that qPCR data normalization using conventional reference genes render the same results as stable reference genes selected from RNA-Seq data. We validated these observations in two distinct cross-sectional experimental conditions involving human iPSC derived microglial cells and mouse sciatic nerves. These results taken together show that given a robust statistical approach for reference gene selection, stable genes selected from RNA-Seq data do not offer any significant advantage over commonly used reference genes for normalizing qPCR assays.     

Identification of suitable reference genes for quantitative real‐time PCR normalization in blotched snakehead Channa maculata

A systematic study was conducted to identify reliable reference genes for normalization of gene expression analysis in the blotched snakehead Channa maculata under normal physiological conditions. Firstly, the partial complementary (c)DNA of nine candidate reference genes (actb, tmem104, ube2l3, ef1α, churc1, tmem256, rpl13a, sep15 and g6pd) were cloned from C. maculata. The expression levels of these genes were then assessed in embryos of different developmental stages and various tissue types of adult fish using quantitative real‐time (qrt‐)PCR. RefFinder algorithm was used to evaluate the expression stability of these genes based on their cycle‐threshold (C_t) values in the qrt‐PCR analysis. Results showed that there was no single best reference gene for all stages of embryos and adult tissues tested. Furthermore, it was found that, among the nine candidate genes tested, actb and tmem104 were the most stable reference genes across adult tissue types, while sep15 and tmem256 were the most stable ones across developmental stages of embryos. These stable reference genes are recommended for normalization of gene expression analysis in C. maculata.     

Identification and validation of reference genes for quantitative RT-PCR normalization in wheat

Background  

Usually the reference genes used in gene expression analysis have been chosen for their known or suspected housekeeping roles, however the variation observed in most of them hinders their effective use. The assessed lack of validated reference genes emphasizes the importance of a systematic study for their identification. For selecting candidate reference genes we have developed a simple in silico method based on the data publicly available in the wheat databases Unigene and TIGR.     

Evaluation of potential reference genes for qRT-PCR data normalization in HeLa cells

Reference genes selection is one of the most important stages in qPCR data normalization when a problem of quantitative determination of gene expression is addressed. Stability of gene expression level in all experimental conditions is a basic criterion for the reference gene selection. Over the past decade a lot of publications concerning validation methods of suitable reference genes appeared. In this paper, the main approaches (ΔCt, geNorm, qBase and Haller’s equivalence test) were applied for the reference genes identification in HeLa cell line which is one of the most popular cellular models. Expression stability of seven candidate genes (HPRT1, ACTB, GAPDH, RPS18, HSPC3, UBC and SDHA) was determined at standard conditions, under heat shock and during relaxation. The genes RPS18 and HSPC3 were chosen as reference after the combination of all the validation methods.     

Selection of optimal reference genes for normalization in quantitative RT-PCR

Background  

Normalization in real-time qRT-PCR is necessary to compensate for experimental variation. A popular normalization strategy employs reference gene(s), which may introduce additional variability into normalized expression levels due to innate variation (between tissues, individuals, etc). To minimize this innate variability, multiple reference genes are used. Current methods of selecting reference genes make an assumption of independence in their innate variation. This assumption is not always justified, which may lead to selecting a suboptimal set of reference genes.     

Identification and evaluation of suitable reference genes for gene expression analysis in rubber tree leaf

Molecular Biology Reports - Gene expression profiles are increasingly applied to investigate molecular mechanism for which, normalization with suitable reference genes is critical. Previously we...