Optimal Number Of Reference Genes Research Articles

Robust RT-qPCR Data Normalization: Validation and Selection of Internal Reference Genes during Post-Experimental Data Analysis

Reverse transcription and real-time PCR (RT-qPCR) has been widely used for rapid quantification of relative gene expression. To offset technical confounding variations, stably-expressed internal reference genes are measured simultaneously along with target genes for data normalization. Statistic methods have been developed for reference validation; however normalization of RT-qPCR data still remains arbitrary due to pre-experimental determination of particular reference genes. To establish a method for determination of the most stable normalizing factor (NF) across samples for robust data normalization, we measured the expression of 20 candidate reference genes and 7 target genes in 15 Drosophila head cDNA samples using RT-qPCR. The 20 reference genes exhibit sample-specific variation in their expression stability. Unexpectedly the NF variation across samples does not exhibit a continuous decrease with pairwise inclusion of more reference genes, suggesting that either too few or too many reference genes may detriment the robustness of data normalization. The optimal number of reference genes predicted by the minimal and most stable NF variation differs greatly from 1 to more than 10 based on particular sample sets. We also found that GstD1, InR and Hsp70 expression exhibits an age-dependent increase in fly heads; however their relative expression levels are significantly affected by NF using different numbers of reference genes. Due to highly dependent on actual data, RT-qPCR reference genes thus have to be validated and selected at post-experimental data analysis stage rather than by pre-experimental determination.

Identification of suitable reference genes for normalization of qPCR data in comparative transcriptomics analyses in the Triticeae

Comparative transcriptomics are useful to determine the role of orthologous genes among Triticeae species. Thus they constitute an interesting tool to improve the use of wild relatives for crop breeding. Reverse transcription quantitative real-time PCR (qPCR) is the most accurate measure of gene expression but efficient normalization is required. The choice and optimal number of reference genes must be experimentally determined and the primers optimized for cross-species amplification. Our goal was to test the utility of wheat-reference genes for qPCR normalization when species carrying the following genomes (A, B, D, R, H ( v ) and H ( ch )) are compared either simultaneously or in smaller subsets of samples. Wheat/barley/rye consensus primers outperformed wheat-specific ones which indicate that consensus primers should be considered for data normalization in comparative transcriptomics. All genes tested were stable but their ranking in terms of stability differed among subsets of samples. CDC (cell division control protein, AAA-superfamily of ATPases, Ta54227) and RLI (68kDa protein HP68 similar to Arabidopsis thaliana RNase L inhibitor protein, Ta2776) were always among the three most stable genes. The optimal number of reference genes varied between 2 and 3 depending on the subset of samples and the method used (geNorm vs. coefficient of determination between sequential normalization factors). In any case a maximum number of three reference genes would provide adequate normalization independent of the subset of samples considered. This work constitutes a substantial advance towards comparative transcriptomics using qPCR since it provides useful primers/reference genes.