Title Microfluidic single-cell whole-transcriptome sequencing
Authors Streets, Aaron M.
Zhang, Xiannian
Cao, Chen
Pang, Yuhong
Wu, Xinglong
Xiong, Liang
Yang, Lu
Fu, Yusi
Zhao, Liang
Tang, Fuchou
Huang, Yanyi
Affiliation Peking Univ, Biodynam Opt Imaging Ctr BIOPIC, Beijing 100871, Peoples R China.
Peking Univ, Coll Engn, Beijing 100871, Peoples R China.
Peking Univ, Sch Life Sci, Beijing 100871, Peoples R China.
Univ Sci & Technol Beijing, Res Ctr Bioengn & Sensing Technol, Beijing 100083, Peoples R China.
Keywords genomics
lab on chip
embryonic stem cell
EMBRYONIC STEM-CELLS
MESSENGER-RNA-SEQ
GENE-EXPRESSION
HETEROGENEITY
AMPLIFICATION
STOCHASTICITY
SMART-SEQ2
LANDSCAPE
LEVEL
QPCR
Issue Date 2014
Publisher proceedings of the national academy of sciences of the united states of america
Citation PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA.2014,111,(19),7048-7053.
Abstract Single-cell whole-transcriptome analysis is a powerful tool for quantifying gene expression heterogeneity in populations of cells. Many techniques have, thus, been recently developed to perform transcriptome sequencing (RNA-Seq) on individual cells. To probe subtle biological variation between samples with limiting amounts of RNA, more precise and sensitive methods are still required. We adapted a previously developed strategy for single-cell RNA-Seq that has shown promise for superior sensitivity and implemented the chemistry in a microfluidic platform for single-cell whole-transcriptome analysis. In this approach, single cells are captured and lysed in a microfluidic device, where mRNAs with poly(A) tails are reverse-transcribed into cDNA. Double-stranded cDNA is then collected and sequenced using a next generation sequencing platform. We prepared 94 libraries consisting of single mouse embryonic cells and technical replicates of extracted RNA and thoroughly characterized the performance of this technology. Microfluidic implementation increased mRNA detection sensitivity as well as improved measurement precision compared with tube-based protocols. With 0.2 M reads per cell, we were able to reconstruct a majority of the bulk transcriptome with 10 single cells. We also quantified variation between and within different types of mouse embryonic cells and found that enhanced measurement precision, detection sensitivity, and experimental throughput aided the distinction between biological variability and technical noise. With this work, we validated the advantages of an early approach to single-cell RNA-Seq and showed that the benefits of combining microfluidic technology with high-throughput sequencing will be valuable for large-scale efforts in single-cell transcriptome analysis.
URI http://hdl.handle.net/20.500.11897/315637
ISSN 0027-8424
DOI 10.1073/pnas.1402030111
Indexed SCI(E)
PubMed
Appears in Collections: 生物医学前沿创新中心
工学院
生命科学学院

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