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SC3-seq: a method for highly parallel and quantitative measurement of single-cell gene expression
Author(s) -
Tomonori Nakamura,
Yukihiro Yabuta,
Ikuhiro Okamoto,
Shinya Aramaki,
Shihori Yokobayashi,
Kazuki Kurimoto,
Kiyotoshi Sekiguchi,
Masato Nakagawa,
Takuya Yamamoto,
Mitinori Saitou
Publication year - 2015
Publication title -
nucleic acids research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 9.008
H-Index - 537
eISSN - 1362-4954
pISSN - 0305-1048
DOI - 10.1093/nar/gkv134
Subject(s) - biology , transcriptome , rna seq , computational biology , single cell analysis , gene , induced pluripotent stem cell , cell , rna , gene expression , cell type , single cell sequencing , phenotype , genetics , microbiology and biotechnology , embryonic stem cell , exome sequencing
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 s ingle- c ell mRNA 3 -prime end seq uencing (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.

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