SC3-seq: a method for highly parallel and quantitative measurement of single-cell gene expression

Single-cell mRNA sequencing (RNA-seq) methods have undergone rapid development in recent years, and transcriptome analysis of relevant cell populations at single-cell resolution has become a key research area of biomedical sciences. We here present single-cell mRNA 3-prime end sequencing (SC3-seq),...

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Veröffentlicht in:Nucleic acids research 2015-05, Vol.43 (9), p.e60-e60
Hauptverfasser: Nakamura, Tomonori, Yabuta, Yukihiro, Okamoto, Ikuhiro, Aramaki, Shinya, Yokobayashi, Shihori, Kurimoto, Kazuki, Sekiguchi, Kiyotoshi, Nakagawa, Masato, Yamamoto, Takuya, Saitou, Mitinori
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Sprache:eng
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Zusammenfassung:Single-cell mRNA sequencing (RNA-seq) methods have undergone rapid development in recent years, and transcriptome analysis of relevant cell populations at single-cell resolution has become a key research area of biomedical sciences. We here present single-cell mRNA 3-prime end sequencing (SC3-seq), a practical methodology based on PCR amplification followed by 3-prime-end enrichment for highly quantitative, parallel and cost-effective measurement of gene expression in single cells. The SC3-seq allows excellent quantitative measurement of mRNAs ranging from the 10,000-cell to 1-cell level, and accordingly, allows an accurate estimate of the transcript levels by a regression of the read counts of spike-in RNAs with defined copy numbers. The SC3-seq has clear advantages over other typical single-cell RNA-seq methodologies for the quantitative measurement of transcript levels and at a sequence depth required for the saturation of transcript detection. The SC3-seq distinguishes four distinct cell types in the peri-implantation mouse blastocysts. Furthermore, the SC3-seq reveals the heterogeneity in human-induced pluripotent stem cells (hiPSCs) cultured under on-feeder as well as feeder-free conditions, demonstrating a more homogeneous property of the feeder-free hiPSCs. We propose that SC3-seq might be used as a powerful strategy for single-cell transcriptome analysis in a broad range of investigations in biomedical sciences.
ISSN:0305-1048
1362-4962
DOI:10.1093/nar/gkv134