Smart-seq2 for sensitive full-length transcriptome profiling in single cells
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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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).”
From Design principles of cell-state-specific enhancers in hematopoiesis (2025) · cites this paper as [69]
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.”
From Revealing the vectors of cellular identity with single-cell genomics (2016) · cites this paper as [9]
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.”
From Scrublet: computational identification of cell doublets in single-cell transcriptomic data (2019) · cites this paper as Picelli et al., 2013
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
Smart-seq2 showed a more even coverage than Smart-seq.
“Smart-seq2 showed a more even coverage than Smart-seq, confirming previous findings (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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