Nucleic Acids Research · 2011 · 46 citations · 17 references
Life SciencesCell BiologyMolecular BiologyGene ExpressionGene Expression AnalysisTranscriptomicsSingle-cell AnalysisSingle-cell Rna Sequencing AnalysisSingle-cell TranscriptomicsSingle-molecule MeasurementsBiological Matrix AnalysisNormalization Of Single-cell DataSingle-cell Analysis PlatformsSingle-cell Cytokine ProfilingSingle-cell Gene Expression ProfilingSingle-cell Rna SequencingSingle-cell Transcriptomic VariabilitySingle-cell Variability
In quantitative single-cell studies, the critical part is the low amount of nucleic acids present and the resulting experimental variations. In addition biological data obtained from heterogeneous tissue are not reflecting the expression behaviour of every single-cell. These variations can be derived from natural biological variance or can be introduced externally. Both have negative effects on the quantification result. The aim of this study is to make quantitative single-cell studies more transparent and reliable in order to fulfil the MIQE guidelines at the single-cell level. The technical variability introduced by RT, pre-amplification, evaporation, biological material and qPCR itself was evaluated by using RNA or DNA standards. Secondly, the biological expression variances of GAPDH, TNFα, IL-1β, TLR4 were measured by mRNA profiling experiment in single lymphocytes. The used quantification setup was sensitive enough to detect single standard copies and transcripts out of one solitary cell. Most variability was introduced by RT, followed by evaporation, and pre-amplification. The qPCR analysis and the biological matrix introduced only minor variability. Both conducted studies impressively demonstrate the heterogeneity of expression patterns in individual cells and showed clearly today's limitation in quantitative single-cell expression analysis.
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mRNA-Seq whole-transcriptome analysis of a single cell
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