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Application of an RNA amplification method for reliable single-cell transcriptome analysis
Author(s) -
Oleg Suslov,
Daniel J. Silver,
Florian A. Siebzehnrübl,
Arturo V. Orjalo,
Andrey Ptitsyn,
Dennis A. Steindler
Publication year - 2015
Publication title -
biotechniques
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.617
H-Index - 131
eISSN - 1940-9818
pISSN - 0736-6205
DOI - 10.2144/000114331
Subject(s) - biology , computational biology , rna , transcriptome , alternative splicing , subventricular zone , gene expression profiling , genetics , dna microarray , gene , cell type , gene expression , gene isoform , cell , neural stem cell , stem cell
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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