Robust RT-qPCR data normalization: validation and selection of internal reference genes during post-experimental data analysis.

Robust RT-qPCR data normalization: validation and selection of internal reference genes during post-experimental data analysis.
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DOI:
10.1371/journal.pone.0017762
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发表时间:
2011-03-15
期刊:
影响因子:
3.7
通讯作者:
Salvaterra PM
Salvaterra PM
中科院分区:
综合性期刊3区
文献类型:
--
作者:
Ling D;Salvaterra PM

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逆转录实时聚合酶链式反应(RT-qPCR)已被广泛应用于相关基因表达的快速定量。为了抵消技术上的混杂变异,将稳定表达的内部参照基因与目标基因同时测量,以进行数据标准化。已经开发了用于参考验证的统计方法;然而,由于实验前对特定参考基因的确定,RT-qPCR数据的归一化仍然是随意的。为了建立一种跨样本确定最稳定的归一化因子(NF)的方法,以便进行稳健的数据归一化,我们利用RT-qPCR技术检测了15个果蝇头部cDNA样本中20个候选参考基因和7个靶基因的表达。这20个参考基因的表达稳定性因样本而异。出乎意料的是,随着更多参考基因的成对包含,样本间的核因子变异并没有表现出持续的减少,这表明参考基因太少或太多都可能损害数据归一化的稳健性。由最小和最稳定的核因子变异预测的最佳参考基因数量在特定样本集上从1个到10个以上差别很大。我们还发现,GstD1、INR和Hsp70在苍蝇头部的表达随年龄的增加而增加,但它们的相对表达水平受到使用不同数量参考基因的NF的显著影响。由于对实际数据的高度依赖,RT-qPCR参考基因的验证和选择必须在实验后数据分析阶段进行,而不是通过实验前的确定。
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.
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