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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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Autores principales: Nakamura, Tomonori, Yabuta, Yukihiro, Okamoto, Ikuhiro, Aramaki, Shinya, Yokobayashi, Shihori, Kurimoto, Kazuki, Sekiguchi, Kiyotoshi, Nakagawa, Masato, Yamamoto, Takuya, Saitou, Mitinori
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4482058/
https://www.ncbi.nlm.nih.gov/pubmed/25722368
http://dx.doi.org/10.1093/nar/gkv134
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author Nakamura, Tomonori
Yabuta, Yukihiro
Okamoto, Ikuhiro
Aramaki, Shinya
Yokobayashi, Shihori
Kurimoto, Kazuki
Sekiguchi, Kiyotoshi
Nakagawa, Masato
Yamamoto, Takuya
Saitou, Mitinori
author_facet Nakamura, Tomonori
Yabuta, Yukihiro
Okamoto, Ikuhiro
Aramaki, Shinya
Yokobayashi, Shihori
Kurimoto, Kazuki
Sekiguchi, Kiyotoshi
Nakagawa, Masato
Yamamoto, Takuya
Saitou, Mitinori
author_sort Nakamura, Tomonori
collection PubMed
description 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.
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spelling pubmed-44820582015-06-30 SC3-seq: a method for highly parallel and quantitative measurement of single-cell gene expression Nakamura, Tomonori Yabuta, Yukihiro Okamoto, Ikuhiro Aramaki, Shinya Yokobayashi, Shihori Kurimoto, Kazuki Sekiguchi, Kiyotoshi Nakagawa, Masato Yamamoto, Takuya Saitou, Mitinori Nucleic Acids Res Methods Online 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. Oxford University Press 2015-05-19 2015-02-26 /pmc/articles/PMC4482058/ /pubmed/25722368 http://dx.doi.org/10.1093/nar/gkv134 Text en © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Methods Online
Nakamura, Tomonori
Yabuta, Yukihiro
Okamoto, Ikuhiro
Aramaki, Shinya
Yokobayashi, Shihori
Kurimoto, Kazuki
Sekiguchi, Kiyotoshi
Nakagawa, Masato
Yamamoto, Takuya
Saitou, Mitinori
SC3-seq: a method for highly parallel and quantitative measurement of single-cell gene expression
title SC3-seq: a method for highly parallel and quantitative measurement of single-cell gene expression
title_full SC3-seq: a method for highly parallel and quantitative measurement of single-cell gene expression
title_fullStr SC3-seq: a method for highly parallel and quantitative measurement of single-cell gene expression
title_full_unstemmed SC3-seq: a method for highly parallel and quantitative measurement of single-cell gene expression
title_short SC3-seq: a method for highly parallel and quantitative measurement of single-cell gene expression
title_sort sc3-seq: a method for highly parallel and quantitative measurement of single-cell gene expression
topic Methods Online
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4482058/
https://www.ncbi.nlm.nih.gov/pubmed/25722368
http://dx.doi.org/10.1093/nar/gkv134
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