Cited by 854Single-cell and spatial transcriptomicsGenomics and Phylogenetic StudiesGene expression and cancer classification

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Single-cell RNA-seq: advances and future challenges

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Abstract

Phenotypically identical cells can dramatically vary with respect to behavior during their lifespan and this variation is reflected in their molecular composition such as the transcriptomic landscape. Single-cell transcriptomics using next-generation transcript sequencing (RNA-seq) is now emerging as a powerful tool to profile cell-to-cell variability on a genomic scale. Its application has already greatly impacted our conceptual understanding of diverse biological processes with broad implications for both basic and clinical research. Different single-cell RNA-seq protocols have been introduced and are reviewed here-each one with its own strengths and current limitations. We further provide an overview of the biological questions single-cell RNA-seq has been used to address, the major findings obtained from such studies, and current challenges and expected future developments in this booming field.

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Crossref · 10.1093/nar/gku555

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Figure 1. Methods to isolate single cells. (A) Principle of fluorescence-activated cell sorting. A stream of droplets, each containing a single cell, passes through an excitation laser beam and the fluorescence signal emerging from each cell is analyzed by a multispectral detector. If the emitted fluorescence signal gates in the preset window, the respective cell will be sorted into a multi-well plate. (B) Optofluidic-based cell handling. (i) A cell suspension is arrayed in a plate, each well containing a single cell. (ii) A laser, also called an optical tweezer, is used to manipulate each individual cell. Adapted from (62). Reprinted by permission from Macmillan Publishers Ltd on behalf of Scientific Reports, copyright 2013. (C) Two examples of emerging microfluidics-based cell sorting technologies. (i) A microfluidic system integrates all steps from single-cell trapping to gene expression analysis: (step 1) cells are retained individually in microfabricated chambers (each cell is indicated with a black arrowhead); (step 2) cells are lysed and RNA is reverse transcribed; (step 3) detection and analysis is achieved by digital PCR. Adapted with permission from (85,86). Copyright 2013 American Chemical Society. (ii) Representation of a microfluidic system that integrates all steps necessary for sorting extremely rare cancer cells from whole blood: (step 1) red blood cells (RBCs) are separated from white blood cells based on their size and (step 2) rare cells are further isolated from the stream of white blood cells by magnetophoresis. Adapted from (75). Reprinted by permission from Macmillan Publishers Ltd on behalf of Nature Protocols, copyright 2014. (D) Laser capture microdissection. (i) Cells of interest are identified in a stained section of rat cervical dorsal root ganglia (indicated by black arrowheads), (ii) cut with a UV laser and (iii) transferred onto a membrane. Scale bar 200 μm. Adapted from (82). Reprinted by permission from Macmillan Publishers Ltd on behalf of Nature Medicine, copyright 1999.
Figure 1. Methods to isolate single cells. (A) Principle of fluorescence-activated cell sorting. A stream of droplets, each containing a single cell, passes through an excitation laser beam and the fluorescence signal emerging from each cell is analyzed by a multispectral detector. If the emitted fluorescence signal gates in the preset window, the respective cell will be sorted into a multi-well plate. (B) Optofluidic-based cell handling. (i) A cell suspension is arrayed in a plate, each well containing a single cell. (ii) A laser, also called an optical tweezer, is used to manipulate each individual cell. Adapted from (62). Reprinted by permission from Macmillan Publishers Ltd on behalf of Scientific Reports, copyright 2013. (C) Two examples of emerging microfluidics-based cell sorting technologies. (i) A microfluidic system integrates all steps from single-cell trapping to gene expression analysis: (step 1) cells are retained individually in microfabricated chambers (each cell is indicated with a black arrowhead); (step 2) cells are lysed and RNA is reverse transcribed; (step 3) detection and analysis is achieved by digital PCR. Adapted with permission from (85,86). Copyright 2013 American Chemical Society. (ii) Representation of a microfluidic system that integrates all steps necessary for sorting extremely rare cancer cells from whole blood: (step 1) red blood cells (RBCs) are separated from white blood cells based on their size and (step 2) rare cells are further isolated from the stream of white blood cells by magnetophoresis. Adapted from (75). Reprinted by permission from Macmillan Publishers Ltd on behalf of Nature Protocols, copyright 2014. (D) Laser capture microdissection. (i) Cells of interest are identified in a stained section of rat cervical dorsal root ganglia (indicated by black arrowheads), (ii) cut with a UV laser and (iii) transferred onto a membrane. Scale bar 200 μm. Adapted from (82). Reprinted by permission from Macmillan Publishers Ltd on behalf of Nature Medicine, copyright 1999.CC BY · PubMed Central
Figure 2. Existing methods to prepare sequencing libraries from a single cell. The methods differ with respect to the strategy used to amplify cDNA that is obtained by oligo(dT)- or/and random-primed reverse transcription. (A) Universal primers are inserted at the 3′ end along with the reverse transcription initiation oligonucleotide and at the 5′ end of the initial RNA molecules after reverse transcription via either (i) poly(A) tailing at the 3′ end of the first cDNA strand or (ii) template-switching mechanism involving a template-switching oligonucleotide (TSO). (B) During cDNA synthesis, a T7 RNA polymerase primer can be integrated that enables the further amplification of RNA via in vitro transcription. This results in an antisense RNA (aRNA) that can be subjected to library preparation and sequencing. (C) Alternatively, after cDNA synthesis and chromosomal DNA degradation, cDNA can be circularized and amplified by a technique referred to as rolling circle amplification using the Phi29 polymerase.
Figure 2. Existing methods to prepare sequencing libraries from a single cell. The methods differ with respect to the strategy used to amplify cDNA that is obtained by oligo(dT)- or/and random-primed reverse transcription. (A) Universal primers are inserted at the 3′ end along with the reverse transcription initiation oligonucleotide and at the 5′ end of the initial RNA molecules after reverse transcription via either (i) poly(A) tailing at the 3′ end of the first cDNA strand or (ii) template-switching mechanism involving a template-switching oligonucleotide (TSO). (B) During cDNA synthesis, a T7 RNA polymerase primer can be integrated that enables the further amplification of RNA via in vitro transcription. This results in an antisense RNA (aRNA) that can be subjected to library preparation and sequencing. (C) Alternatively, after cDNA synthesis and chromosomal DNA degradation, cDNA can be circularized and amplified by a technique referred to as rolling circle amplification using the Phi29 polymerase.CC BY · PubMed Central
Figure 3. Strand specificity and barcoding strategies. (A) Using a template-switching mechanism, a restriction site together with the universal priming sequence can be integrated at the 5′ end of the initial RNA transcript. Likewise biotin can be introduced at both the 3′ and 5′ ends via the use of biotinylated primers. Upon binding to streptavidin beads, enzymatic cleavage will lead to the selection of only the 5′-most fragments for library construction. In addition, during template switching cellular and/or molecular barcodes can be integrated. (B) Alternatively using in vitro transcription, 3′ ends can be selected after ligation of 3′ and 5′ adaptors to fragmented RNA in order to selectively prime PCR amplification of only the 3′-most fragments. The oligo(dT) primer is used to introduce cellular and/or molecular barcodes.
Figure 3. Strand specificity and barcoding strategies. (A) Using a template-switching mechanism, a restriction site together with the universal priming sequence can be integrated at the 5′ end of the initial RNA transcript. Likewise biotin can be introduced at both the 3′ and 5′ ends via the use of biotinylated primers. Upon binding to streptavidin beads, enzymatic cleavage will lead to the selection of only the 5′-most fragments for library construction. In addition, during template switching cellular and/or molecular barcodes can be integrated. (B) Alternatively using in vitro transcription, 3′ ends can be selected after ligation of 3′ and 5′ adaptors to fragmented RNA in order to selectively prime PCR amplification of only the 3′-most fragments. The oligo(dT) primer is used to introduce cellular and/or molecular barcodes.CC BY · PubMed Central
Figure 4. Envisioned strategies for nanopore-based RNA-seq. Left: while a single-stranded RNA stretch is translocated through a hemolysin pore in a membrane, each ribobase could be detected by measuring current changes between the cis (−) and trans (+) compartment divided by the lipid bilayer. Right: single-stranded RNA is cleaved by polynucleotide phosphorylase (PNPase) and each released ribobase could be read separately by measuring the current between the cis (−) and trans (+) compartment. Nanopore drawing is reproduced from (169) by permission from Macmillan Publishers Ltd on behalf of Scientific Reports, copyright 2013. RNA exosequencing principle is adapted with permission from (167) and copyright 2013 American Chemical Society.
Figure 4. Envisioned strategies for nanopore-based RNA-seq. Left: while a single-stranded RNA stretch is translocated through a hemolysin pore in a membrane, each ribobase could be detected by measuring current changes between the cis (−) and trans (+) compartment divided by the lipid bilayer. Right: single-stranded RNA is cleaved by polynucleotide phosphorylase (PNPase) and each released ribobase could be read separately by measuring the current between the cis (−) and trans (+) compartment. Nanopore drawing is reproduced from (169) by permission from Macmillan Publishers Ltd on behalf of Scientific Reports, copyright 2013. RNA exosequencing principle is adapted with permission from (167) and copyright 2013 American Chemical Society.CC BY · PubMed Central

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Research works printed but not linked: 4

  1. 10.1038/nmeth.2639 · DOI · Paper page
  2. Trapnell C. Cacchiarelli D. Grimsby J. Pokharel P. Li S. Morse M. Lennon N.J. Livak K.J. Mikkelsen T.S. Rinn J.L. The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells. Nat. Biotechnol 2014;32. · DOI · Paper page
  3. 10.1371/journal.pone.0021208 · DOI
  4. 10.1038/nature12352 · DOI · Paper page

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Metadata

Authors
Saliba, A.-E., Westermann, A. J., Gorski, S. A., & Vogel, J.
Affiliations
University of Würzburg (DE)
Corresponding author
Vogel, Jörg
Venue
Nucleic Acids Research
Published
2014-07-22
Volume
42
Issue
14
Pages
8845-8860
ISSN
  • 0305-1048 (ISSN-L)
  • 1362-4962
OpenAlex
W2069295116
Cited by
847
References
167
Citations by year
2026: 38 · 2025: 81 · 2024: 92 · 2023: 78 · 2022: 74 · 2021: 69 · 2020: 58 · 2019: 63 · 2018: 67 · 2017: 91 · 2016: 84 · 2015: 46 · 2014: 6
FWCI
7.00
Type
journal article
Language
en
Open access
Locations
  • Nucleic Acids Research (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • MDC Repository (Max-Delbrueck-Center for Molecular Medicine) (acceptedVersion)
  • Online Publication Service of Würzburg University (Würzburg University) (submittedVersion, cc-by)
Funders
  • Deutsche Forschungsgemeinschaft
  • Bundesministerium für Bildung und Forschung
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 › Gene expression and cancer classification
Keywords
single-cell RNA sequencing, single-cell transcriptomics, cell-to-cell variability, transcriptional landscape
MeSH terms
Cell Separation, Sequence Analysis, RNA, Gene Expression Profiling, Single-Cell Analysis, High-Throughput Nucleotide Sequencing

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