Taruttis Franziska, Feist Maren, Schwarzfischer Phillip, Gronwald Wolfram, Kube Dieter, Spang Rainer, Engelmann Julia C
Statistical Bioinformatics, University of Regensburg, Regensburg, Germany.
Haematology and Oncology, University Medical Center Göttingen, Göttingen, Germany.
Biotechniques. 2017 Feb 1;62(2):53-61. doi: 10.2144/000114514.
Gene expression measurements are typically performed on a fixed-weight aliquot of RNA, which assumes that the total number of transcripts per cell stays nearly constant across all conditions. In cases where this assumption does not hold (e.g., when comparing cell types with different cell sizes) the expression data provide a distorted view of cellular events. Assuming constant numbers of total transcripts, increases in expression of some RNAs must be compensated for by decreases in expression of others. Therefore, we propose calibrating gene expression data to an external reference point, the number of cells in the sample, using whole-cell spike-ins. In a systematic dilution experiment, we mixed varying numbers of human cells with fixed numbers of cells and scaled the expression levels of the human genes relative to those of the genes. This approach restored the original gene expression ratios generated by the dilutions. We then used whole-cell spike-ins to uncover non-symmetric gene expression changes, in this case much larger numbers of induced than repressed genes, under perturbations of the human cell line P493-6. whole-cell spike-ins are an experimentally and computationally easy and low-priced method to derive mRNA fold changes of absolute abundances from RNA sequencing (RNA-Seq) and quantitative real-time PCR (qPCR) data.
基因表达测量通常是在固定重量的RNA等分试样上进行的,这假定每个细胞中转录本的总数在所有条件下几乎保持恒定。在这种假设不成立的情况下(例如,在比较不同细胞大小的细胞类型时),表达数据会提供细胞事件的扭曲视图。假设总转录本数量恒定,一些RNA表达的增加必须由其他RNA表达的减少来补偿。因此,我们建议使用全细胞掺入物将基因表达数据校准到一个外部参考点,即样品中的细胞数量。在一项系统稀释实验中,我们将不同数量的人类细胞与固定数量的[未提及的细胞类型]细胞混合,并将人类基因的表达水平相对于[未提及的细胞类型]基因的表达水平进行缩放。这种方法恢复了稀释产生的原始基因表达比率。然后,我们使用全细胞掺入物来揭示在人类细胞系P493 - 6受到扰动的情况下非对称的基因表达变化,在这种情况下,诱导基因的数量比抑制基因多得多。全细胞掺入物是一种在实验和计算上都简单且价格低廉的方法,可从RNA测序(RNA - Seq)和定量实时PCR(qPCR)数据中得出绝对丰度的mRNA倍数变化。