Access count of this item: 49

Files in This Item:
File Description SizeFormat 
nar_gkv134.pdf5.04 MBAdobe PDFView/Open
Title: SC3-seq: A method for highly parallel and quantitative measurement of single-cell gene expression
Authors: Nakamura, Tomonori  kyouindb  KAKEN_id
Yabuta, Yukihiro
Okamoto, Ikuhiro
Aramaki, Shinya
Yokobayashi, Shihori
Kurimoto, Kazuki  kyouindb  KAKEN_id
Sekiguchi, Kiyotoshi
Nakagawa, Masato
Yamamoto, Takuya  kyouindb  KAKEN_id
Saitou, Mitinori
Author's alias: 中村, 友紀
岡本, 郁弘
荒牧, 伸弥
横林, しほり
栗本, 一基
中川, 誠人
斎藤, 通紀
Issue Date: 19-May-2015
Publisher: Oxford University Press
Journal title: Nucleic Acids Research
Volume: 43
Issue: 9
Thesis number: e60
Abstract: 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.
Rights: © 2015 The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
DOI(Published Version): 10.1093/nar/gkv134
Appears in Collections:Journal Articles

Show full item record

Export to RefWorks

Export Format: 

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.