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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Saliba, Antoine-Emmanuel, Westermann, Alexander J., Gorski, Stanislaw A., Vogel, Jörg·2014·Nucleic Acids Research

DOI 10.1093/nar/gku555PMC PMC4132710

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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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Authors: Saliba, A.-E., Westermann, A. J., Gorski, S. A., & Vogel, J.
Affiliations: University of Würzburg (DE)
Corresponding author: Vogel, Jörg
ORCID: Saliba, Antoine-Emmanuel
Westermann, Alexander J.
Gorski, Stanislaw A.
Vogel, Jörg
Venue: Nucleic Acids Research
Publisher: Oxford University Press (OUP)
Published: 2014-07-22
Volume: 42
Issue: 14
Pages: 8845-8860
ISSN: 0305-1048 (ISSN-L)
1362-4962
DOI: 10.1093/nar/gku555
PMC: PMC4132710
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: gold
doi.org
Licence: cc-by
creativecommons.org/licenses/by/4.0/ (vor, 805 d)
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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