PT - JOURNAL ARTICLE AU - Tobias Lange AU - Tobias Groß AU - Ábris Jeney AU - Julia Scherzinger AU - Elly Sinkala AU - Christoph Niemöller AU - Stefan Zimmermann AU - Peter Koltay AU - Felix von Stetten AU - Roland Zengerle AU - Csaba Jeney TI - Validation of scRNA-seq by scRT-ddPCR using the example of <em>ErbB2</em> in MCF7 cells AID - 10.1101/2022.05.31.494164 DP - 2022 Jan 01 TA - bioRxiv PG - 2022.05.31.494164 4099 - http://biorxiv.org/content/early/2022/11/16/2022.05.31.494164.short 4100 - http://biorxiv.org/content/early/2022/11/16/2022.05.31.494164.full AB - Single-cell RNA sequencing (scRNA-seq) can unmask transcriptional heterogeneity facilitating the detection of rare subpopulations at unprecedented resolution. In response to challenges related to coverage and quantity of transcriptome analysis, the lack of unbiased and absolutely quantitative validation methods hampers further improvements. Digital PCR (dPCR) represents such a method as we could show that the inherent partitioning enhances molecular detections by increasing effective mRNA concentrations. We developed a scRT-ddPCR method and validated it using two breast cancer cell lines, MCF7 and BT-474, and bulk methods. ErbB2, a low-abundant transcript in MCF7 cells, suffers from dropouts in scRNA-seq and thus calculated fold changes are biased. Using our scRT-ddPCR, we could improve the detection of ErbB2 and based on the absolute counts obtained we could validate the scRNA-seq fold change. We think this workflow is a valuable addition to the single-cell transcriptomic research toolbox and could even become a new standard in fold change validation because of its reliability, ease of use and increased sensitivity.Competing Interest StatementJ.S., E.S. and C.N. are employees of CYTENA GmbH, which produces the F.SIGHT single cell dispenser used in this study. T.L., T.G., P.K, and C.J. are employees of Actome GmbH, which develops the LBT lysis buffer used in this study and P.K., R.Z. and C.J. are shareholders of Actome GmbH. The remaining authors declare no competing interest.CIconfidence interval,clcrude lysate,CVcoefficient of variance,DEdifferential expression,DEGdifferentially expressed gene,dPCRdigital PCR,FACSfluorescence-activated cell sorting,log2FClog2 of fold change between two conditions,RT-qPCRreverse transcription quantitative PCR,scsingle-cell,scRNA-seqsingle-cell RNA sequencing,scRT-ddPCRsingle-cell reverse transcription droplet digital PCR,TPMTranscripts per kilobase million,UMAPuniform manifold approximation and projection,