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A novel method for the normalization of microRNA RT-PCR data

机译：微小RNA RT-PCR数据标准化的新方法

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Background MicroRNAs (miRNAs) are short non-coding RNA molecules that regulate mRNA transcript levels and translation. Deregulation of microRNAs is indicated in a number of diseases and microRNAs are seen as a promising target for biomarker identification and drug development. miRNA expression is commonly measured by microarray or real-time polymerase chain reaction (RT-PCR). The findings of RT-PCR data are highly dependent on the normalization techniques used during preprocessing of the Cycle Threshold readings from RT-PCR. Some of the commonly used endogenous controls themselves have been discovered to be differentially expressed in various conditions such as cancer, making them inappropriate internal controls. Methods We demonstrate that RT-PCR data contains a systematic bias resulting in large variations in the Cycle Threshold (CT) values of the low-abundant miRNA samples. We propose a new data normalization method that considers all available microRNAs as endogenous controls. A weighted normalization approach is utilized to allow contribution from all microRNAs, weighted by their empirical stability. Results The systematic bias in RT-PCR data is illustrated on a microRNA dataset obtained from primary cutaneous melanocytic neoplasms. We show that through a single control parameter, this method is able to emulate other commonly used normalization methods and thus provides a more general approach. We explore the consistency of RT-PCR expression data with microarray expression by utilizing a dataset where both RT-PCR and microarray profiling data is available for the same miRNA samples. Conclusions A weighted normalization method allows the contribution of all of the miRNAs, whether they are highly abundant or have low expression levels. Our findings further suggest that the normalization of a particular miRNA should rely on only miRNAs that have comparable expression levels.
机译：背景MicroRNA（miRNA）是调节mRNA转录水平和翻译的短非编码RNA分子。在许多疾病中都表明microRNA的失控，并且microRNA被视为生物标记物鉴定和药物开发的有希望的目标。 miRNA表达通常通过微阵列或实时聚合酶链反应（RT-PCR）进行测量。 RT-PCR数据的发现高度依赖于预处理来自RT-PCR的循环阈值读数期间使用的归一化技术。已发现某些常用的内源性对照本身在各种条件下（例如癌症）差异表达，使其成为不合适的内部对照。方法我们证明RT-PCR数据包含系统性偏差，导致低丰度miRNA样品的循环阈值（CT）值发生较大变化。我们提出了一种新的数据标准化方法，该方法将所有可用的microRNA视为内源性对照。加权归一化方法用于允许所有microRNA贡献，并以其经验稳定性加权。结果在从原发性皮肤黑素细胞瘤获得的microRNA数据集上说明了RT-PCR数据的系统偏差。我们表明，通过单个控制参数，该方法能够模仿其他常用的归一化方法，从而提供了一种更通用的方法。我们通过利用一个数据集来探索RT-PCR表达数据与微阵列表达的一致性，其中RT-PCR和微阵列分析数据均可用于相同的miRNA样品。结论加权归一化方法允许所有miRNA的贡献，无论它们是高度丰富还是表达水平较低。我们的发现进一步表明，特定miRNA的标准化应仅依赖具有可比表达水平的miRNA。

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