"Per cell" normalization method for mRNA measurement by quantitative PCR and microarrays
"Per cell" normalization method for mRNA measurement by quantitative PCR and microarrays
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DOI：
10.1186/1471-2164-7-64
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发表时间：
2006-03-29
期刊：
影响因子：
4.4
通讯作者：
Nagao, T
中科院分区：
文献类型：
--
作者：
Kanno, J;Aisaki, K;Nagao, T
背景：定量 PCR (Q-PCR) 和 DNA 微阵列的转录组数据通常是从每个样品收集的固定量的 RNA 中获得的。因此，实验系列中样品间组织细胞结构和 RNA 产量的变化会影响对任何样品中每个细胞的每种 mRNA 种类的绝对水平的准确测定。由于 mRNA 是从基因组 DNA 中复制的，表达 mRNA 水平的最简单方法是每个模板 DNA 的拷贝数，或者更实际地，每个细胞的拷贝数。 结果：在这里，我们报告了一种用于标准化生物样品中 mRNA 值表达的方法（称为“Percellome”方法）。它提供“每个细胞”的 mRNA 拷贝数读数，适用于定量 PCR (Q-PCR) 和 DNA 微阵列研究。从一小份样品中测量每个样品匀浆的基因组 DNA 含量，以得出样品中的细胞数量。制备以剂量分级方式混合的五种外部刺突 RNA 的混合物（剂量分级刺突混合物；GSC），并按照其 DNA 含量的比例添加到每个匀浆中。通过这种方式，刺突 mRNA 代表了样品中每个细胞的绝对拷贝数。来自五个刺突 mRNA 的信号被用作每个样品的剂量反应标准曲线，使我们能够以与表达谱无关的方式将所有测量到的信号转换为每个细胞的拷贝数。使用Percellome方法对一系列样品进行Q-PCR和Affymetrix GeneChip芯片检测，结果一致性高达90%。结论：Percellome数据可以在样品之间、不同研究之间、不同平台之间直接进行比较，无需进一步标准化。因此，“percellome”标准化可以作为跨不同平台和不同实验室之间交换和比较数据的标准方法。
Background: Transcriptome data from quantitative PCR (Q-PCR) and DNA microarrays are typically obtained from a fixed amount of RNA collected per sample. Therefore, variations in tissue cellularity and RNA yield across samples in an experimental series compromise accurate determination of the absolute level of each mRNA species per cell in any sample. Since mRNAs are copied from genomic DNA, the simplest way to express mRNA level would be as copy number per template DNA, or more practically, as copy number per cell.Results: Here we report a method (designated the "Percellome" method) for normalizing the expression of mRNA values in biological samples. It provides a "per cell" readout in mRNA copy number and is applicable to both quantitative PCR (Q-PCR) and DNA microarray studies. The genomic DNA content of each sample homogenate was measured from a small aliquot to derive the number of cells in the sample. A cocktail of five external spike RNAs admixed in a dose-graded manner (dose-graded spike cocktail; GSC) was prepared and added to each homogenate in proportion to its DNA content. In this way, the spike mRNAs represented absolute copy numbers per cell in the sample. The signals from the five spike mRNAs were used as a dose-response standard curve for each sample, enabling us to convert all the signals measured to copy numbers per cell in an expression profile-independent manner. A series of samples was measured by Q-PCR and Affymetrix GeneChip microarrays using this Percellome method, and the results showed up to 90% concordance.Conclusion: Percellome data can be compared directly among samples and among different studies, and between different platforms, without further normalization. Therefore, "percellome" normalization can serve as a standard method for exchanging and comparing data across different platforms and among different laboratories.