Digital Encoding of Cellular mRNAs Enabling Precise and Absolute Gene Expression Measurement by Single-Molecule Counting
datasetposted on 17.12.2015, 01:03 by Glenn K. Fu, Julie Wilhelmy, David Stern, H. Christina Fan
We present a new approach for the sensitive detection and accurate quantitation of messenger ribonucleic acid (mRNA) gene transcripts in single cells. First, the entire population of mRNAs is encoded with molecular barcodes during reverse transcription. After amplification of the gene targets of interest, molecular barcodes are counted by sequencing or scored on a simple hybridization detector to reveal the number of molecules in the starting sample. Since absolute quantities are measured, calibration to standards is unnecessary, and many of the relative quantitation challenges such as polymerase chain reaction (PCR) bias are avoided. We apply the method to gene expression analysis of minute sample quantities and demonstrate precise measurements with sensitivity down to sub single-cell levels. The method is an easy, single-tube, end point assay utilizing standard thermal cyclers and PCR reagents. Accurate and precise measurements are obtained without any need for cycle-to-cycle intensity-based real-time monitoring or physical partitioning into multiple reactions (e.g., digital PCR). Further, since all mRNA molecules are encoded with molecular barcodes, amplification can be used to generate more material for multiple measurements and technical replicates can be carried out on limited samples. The method is particularly useful for small sample quantities, such as single-cell experiments. Digital encoding of cellular content preserves true abundance levels and overcomes distortions introduced by amplification.
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hybridization detectoramplificationDigital EncodingmRNA moleculesabundance levelsDigital encodingmeasurementmethodbarcodegene expression analysisAbsolute Gene Expression Measurementminute sample quantitiesend point assaysample quantitiespolymerase chain reactionPCR reagentsgene targetsquantitation challengesCellular mRNAs Enablinggene transcriptsquantity