Taruttis, Franziska and Feist, Maren and Schwarzfischer, Phillip and Gronwald, Wolfram and Kube, Dieter and Spang, Rainer and Engelmann, Julia C. (2017) External calibration with Drosophila whole-cell spike-ins delivers absolute mRNA fold changes from human RNA-Seq and qPCR data. BIOTECHNIQUES, 62 (2). pp. 53-61. ISSN 0736-6205, 1940-9818
Full text not available from this repository. (Request a copy)Abstract
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 Drosophila melanogaster cells and scaled the expression levels of the human genes relative to those of the Drosophila genes. This approach restored the original gene expression ratios generated by the dilutions. We then used Drosophila 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. Drosophila 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.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | C-MYC; RNA sequencing (RNA-Seq); qPCR; gene expression; spike-in; external reference; calibration |
| Subjects: | 500 Science > 500 Natural sciences & mathematics 600 Technology > 610 Medical sciences Medicine |
| Divisions: | Medicine > Institut für Funktionelle Genomik > Lehrstuhl für Funktionelle Genomik (Prof. Oefner) Medicine > Institut für Funktionelle Genomik > Lehrstuhl für Statistische Bioinformatik (Prof. Spang) |
| Depositing User: | Dr. Gernot Deinzer |
| Date Deposited: | 14 Dec 2018 13:01 |
| Last Modified: | 27 Feb 2019 12:25 |
| URI: | https://pred.uni-regensburg.de/id/eprint/484 |
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