Application of an RNA amplification method for reliable single-cell transcriptome analysis

Diverse cell types have unique transcriptional signatures that are best interrogated at single-cell resolution. Here we describe a novel RNA amplification approach that allows for high fidelity gene profiling of individual cells. This technique significantly diminishes the problem of 3′ bias, enabli...

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Published inBioTechniques Vol. 59; no. 3; pp. 137 - 148
Main Authors Suslov, Oleg, Silver, Daniel J, Siebzehnrubl, Florian A, Orjalo, Arturo, Ptitsyn, Andrey, Steindler, Dennis A
Format Journal Article
LanguageEnglish
Published England Future Science Ltd 01.09.2015
Taylor & Francis Group
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ISSN0736-6205
1940-9818
1940-9818
DOI10.2144/000114331

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Summary:Diverse cell types have unique transcriptional signatures that are best interrogated at single-cell resolution. Here we describe a novel RNA amplification approach that allows for high fidelity gene profiling of individual cells. This technique significantly diminishes the problem of 3′ bias, enabling detection of all regions of transcripts, including the recognition of mRNA with short or completely absent poly(A) tails, identification of noncoding RNAs, and discovery of the full array of splice isoforms from any given gene product. We assess this technique using statistical and bioinformatics analyses of microarray data to establish the limitations of the method. To demonstrate applicability, we profiled individual cells isolated from the mouse subventricular zone (SVZ)'a well-characterized, discrete yet highly heterogeneous neural structure involved in persistent neurogenesis. Importantly, this method revealed multiple splice variants of key germinal zone gene products within individual cells, as well as an unexpected coexpression of several mRNAs considered markers of distinct and separate SVZ cell types. These findings were independently confirmed using RNA-fluorescence in situ hybridization (RNA-FISH), contributing to the utility of this new technology that offers genomic and transcriptomic analysis of small numbers of dynamic and clinically relevant cells.
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ISSN:0736-6205
1940-9818
1940-9818
DOI:10.2144/000114331