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Quartz-Seq2: a high-throughput single-cell RNA-sequencing method that effectively uses limited sequence reads

View ORCID ProfileYohei Sasagawa, Hiroki Danno, Hitomi Takada, View ORCID ProfileMasashi Ebisawa, Tetsutaro Hayashi, View ORCID ProfileAkira Kurisaki, View ORCID ProfileItoshi Nikaido
doi: https://doi.org/10.1101/159384
Yohei Sasagawa
1Bioinformatics Research Unit, Advanced Center for Computing and Communication, RIKEN, Hirosawa 2-1, Wako, Saitama, Japan
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  • ORCID record for Yohei Sasagawa
Hiroki Danno
1Bioinformatics Research Unit, Advanced Center for Computing and Communication, RIKEN, Hirosawa 2-1, Wako, Saitama, Japan
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Hitomi Takada
2Laboratory of Stem Cell Technology, Graduate School of Biological Sciences, Nara Institute of Science and Technology, Takayama-cho 8916-5, Ikoma, Nara, Japan
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Masashi Ebisawa
1Bioinformatics Research Unit, Advanced Center for Computing and Communication, RIKEN, Hirosawa 2-1, Wako, Saitama, Japan
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Tetsutaro Hayashi
1Bioinformatics Research Unit, Advanced Center for Computing and Communication, RIKEN, Hirosawa 2-1, Wako, Saitama, Japan
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Akira Kurisaki
2Laboratory of Stem Cell Technology, Graduate School of Biological Sciences, Nara Institute of Science and Technology, Takayama-cho 8916-5, Ikoma, Nara, Japan
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Itoshi Nikaido
1Bioinformatics Research Unit, Advanced Center for Computing and Communication, RIKEN, Hirosawa 2-1, Wako, Saitama, Japan
3Single-cell Omics Research Unit, RIKEN Center for Developmental Biology. 2-2-3 Minatojima-minamimachi, Chuou-ku, Kobe, Japan
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Abstract

High-throughput single-cell RNA-seq methods assign limited unique molecular identifier (UMI) counts as gene expression values to single cells from shallow sequence reads and detect limited gene counts. We thus developed a high-throughput single-cell RNA-seq method, Quartz-Seq2, to overcome these issues. Our improvements in several of the reaction steps of Quartz-Seq2 allow us to effectively convert initial reads to UMI counts (at a rate of 30%–50%). To demonstrate the power of Quartz-Seq2, we analyzed transcriptomes from a cell population of in vitro embryonic stem cells and an in vivo stromal vascular fraction with a limited number of sequence reads.

Footnotes

  • Yohei Sasagawa: youhei.sasagawa{at}riken.jp

  • Hiroki Danno: hiroki.danno{at}riken.jp, redgrapefruit{at}mac.com

  • Hitomi Takada: htakada{at}bs.naist.jp

  • Masashi Ebisawa: masashi.ebisawa{at}riken.jp

  • Tetsutaro Hayashi: tetsutaro.hayashi{at}riken.jp

  • Akira Kurisaki: akikuri{at}bs.naist.jp

  • Itoshi Nikaido: itoshi.nikaido{at}riken.jp

  • List of abbreviations

    UMI
    unique molecular identifier
    PCR
    polymerase chain reaction
    SCC
    Spearman’s rank correlation coefficient
    CV
    coefficient of variation
    ES cell
    embryonic stem cell
    PrE cell
    primitive endoderm cell
    SVF
    stromal vascular fraction
    RT
    reverse-transcription
    Dex
    dexamethasone
    PCA
    principal component analysis
    MSC
    mesenchymal stem cell
    TdT
    terminal deoxynucleotidyl transferase
    GO
    Gene Ontology
    FDR
    false discovery rate
    t-SNE
    t-distributed stochastic neighbor embedding
    nt
    nucleotide
    bp
    base pair
    SSC
    side scatter
  • Copyright 
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    Posted July 21, 2017.
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    Quartz-Seq2: a high-throughput single-cell RNA-sequencing method that effectively uses limited sequence reads
    Yohei Sasagawa, Hiroki Danno, Hitomi Takada, Masashi Ebisawa, Tetsutaro Hayashi, Akira Kurisaki, Itoshi Nikaido
    bioRxiv 159384; doi: https://doi.org/10.1101/159384
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    Quartz-Seq2: a high-throughput single-cell RNA-sequencing method that effectively uses limited sequence reads
    Yohei Sasagawa, Hiroki Danno, Hitomi Takada, Masashi Ebisawa, Tetsutaro Hayashi, Akira Kurisaki, Itoshi Nikaido
    bioRxiv 159384; doi: https://doi.org/10.1101/159384

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