Cited by 2,358Single-cell and spatial transcriptomicsGenomics and Phylogenetic StudiesMolecular Biology Techniques and Applications

Smart-seq2 for sensitive full-length transcriptome profiling in single cells

Picelli, Simone, Björklund, Åsa K, Faridani, Omid R, Sagasser, Sven, Winberg, Gösta, Sandberg, Rickard·2013·Nature Methods

Abstract

Single-cell gene expression analyses hold promise for characterizing cellular heterogeneity, but current methods compromise on either the coverage, the sensitivity or the throughput. Here, we introduce Smart-seq2 with improved reverse transcription, template switching and preamplification to increase both yield and length of cDNA libraries generated from individual cells. Smart-seq2 transcriptome libraries have improved detection, coverage, bias and accuracy compared to Smart-seq libraries and are generated with off-the-shelf reagents at lower cost.

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Registry

Crossref · 10.1038/nmeth.2639

Cites

21 of 21 references verified0 citation errors · 0 not checkable

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  • The purity of the FACS-sorted populations was confirmed by smart-seq2.

    “The purity of the resulting FACS-sorted populations was confirmed by smart-seq269 (Figure S1I).”
  • Newer protocols such as Smart-seq and Smart-seq2 have enabled work from very small amounts of starting mRNA that can be obtained from just a single cell.

    “Newer protocols such as Smart-seq [173] and Smart-seq2 [174] have enabled us to work from very small amounts of starting mRNA that, with proper amplification, can be obtained from just a single cell.”

    From A survey of best practices for RNA-seq data analysis (2016) · cites this paper as [174]

  • Rapid technological advances have enabled genome-wide profiling of RNA, DNA, protein, epigenetic modifications, chromatin accessibility, and other molecular events in single cells.

    “rapid technological advances have enabled genome-wide profiling of RNA7–10, DNA11–17, protein18–21, epigenetic modifications22–26, chromatin accessibility27,28, and other molecular events29 in single cells.”
  • Pre-sorting cells into wells can avoid these problems but reduces throughput.

    “Pre-sorting cells into wells can overcome these problems (Jaitin et al., 2014; Picelli et al., 2013) but at a cost in throughput.”
  • The Smart-seq protocol has been optimized for sensitivity, more even full-length coverage, accuracy, and cost.

    “Furthermore, the Smart-seq protocol has been optimized for sensitivity, more even full-length coverage, accuracy, and cost (Picelli et al., 2013)”

    From Comparative Analysis of Single-Cell RNA Sequencing Methods (2017) · cites this paper as Picelli et al., 2013

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Authors
Picelli, S., Björklund, Å. K., Faridani, O. R., Sagasser, S., Winberg, G., & Sandberg, R.
Affiliations
  • Ludwig Cancer Research (SE)
  • Karolinska Institutet (SE)
Corresponding author
Sandberg, Rickard
Venue
Nature Methods
Published
2013-09-22
Volume
10
Issue
11
Pages
1096-1098
ISSN
  • 1548-7091 (ISSN-L)
  • 1548-7105
OpenAlex
W2019552331
Cited by
2,358
References
21
Citations by year
2026: 121 · 2025: 182 · 2024: 233 · 2023: 222 · 2022: 260 · 2021: 286 · 2020: 278 · 2019: 227 · 2018: 226 · 2017: 138 · 2016: 86 · 2015: 49 · 2014: 44 · 2013: 5
FWCI
27.64
Type
journal article
Language
en
Open access
closed
Locations
  • Nature Methods (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Molecular Biology Techniques and Applications
Keywords
SmartSeq2, single-cell transcriptomics, single-cell gene expression, reverse transcription, template switching, preamplification, detection sensitivity, cellular heterogeneity
MeSH terms
Animals, Humans, Polymerase Chain Reaction, DNA, Complementary, Gene Expression Profiling, HEK293 Cells, Single-Cell Analysis, Transcriptome

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