CEL-Seq: single-cell RNA-Seq by multiplexed linear amplification.

By T. Hashimshony, F. Wagner, Noa Sher, Itai Yanai. Cell Reports, 2012

1,172 citations recorded by the source corpus.

High-throughput sequencing has allowed for unprecedented detail in gene expression analyses, yet its efficient application to single cells is challenged by the small starting amounts of RNA. We have developed CEL-Seq, a method for overcoming this limitation by barcoding and pooling samples before linearly amplifying mRNA with the use of one round of in vitro transcription. We show that CEL-Seq gives more reproducible, linear, and sensitive results than a PCR-based amplification method. We demonstrate the power of this method by studying early C. elegans embryonic development at single-cell resolution. Differential distribution of transcripts between sister cells is seen as early as the two-cell stage embryo, and zygotic expression in the somatic cell lineages is enriched for transcription factors. The robust transcriptome quantifications enabled by CEL-Seq will be useful for transcriptomic analyses of complex tissues containing populations of diverse cell types.

Subfields: Aging, Genetics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/8597f6328cc1eaadd1e453f5a2155d6a6809f258

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Citations in the corpus

Computational and analytical challenges in single-cell transcriptomics (2015, methodology): “The cDNA is then amplified, using PCR 26,28,29,32 or in vitro transcription 31 , to obtain enough material for hybridization to a gene expression microarray 15 or, more recently, to be profiled using NGS 26 ; in the latter case, the technique is referred to as single-cell RNA-seq (scRNA-seq).…”
RNA Sequencing and Analysis (2015, positive): “Various single-cell RNA ampli ﬁ cation methods have been developed to accommodate less input RNA (Tang et al. 2009, 2010; Hashimshony et al. 2012; Islam et al. 2012; Picelli et al. 2013; Sasagawa et al. 2013; Shalek et al. 2013).”
Defining cell types and states with single-cell genomics (2015, background): “et al. (2011); Hashimshony et al. (2012); Jaitin et al. (2014); Fan et al. (2015); Klein et al. (2015); Macosko et al. (2015); Nakamura et al. (2015) DNA-seq Genotype Navin et al. (2011) DNA-seq +RNA-seq Genotype and gene expression Dey et al. (2015); Macaulay et al. (2015) In situ RNA-seq Gene…”
A Single-Cell Transcriptome Atlas of the Human Pancreas (2016, positive): “Initial single-cell transcriptomic studies were performed on cultured cells (Deng et al., 2014; Hashimshony et al., 2012; Islam et al., 2011; Klein et al., 2015; Shalek et al., 2013; Tang et al., 2010).”
Single-cell RNA-seq reveals changes in cell cycle and differentiation programs upon aging of hematopoietic stem cells (2015, background): “New advances in single-cell genomics (Wills et al. 2013), especially single-cell RNA-seq (Hashimshony et al. 2012; Ramskold et al. 2012), have opened the way to characterize distinct 8These authors contributed equally to this work.”
Design and computational analysis of single-cell RNA-sequencing experiments (2016, methodology): “If UMI-tagged data are available, counts can be obtained using approaches such as those detailed by Islam et al. [10] or Hashimshony et al. [31].”
Droplet barcoding for single cell transcriptomics applied to embryonic stem cells (2015, positive): “5 molecules/droplet on average; below that limit, we tended to over-count transcripts, a bias seen previously (Grün et al., 2014; Hashimshony et al., 2012).”