Single-cell RNA-seq reveals dynamic paracrine control of cellular variation
Open accessAbstract
High-throughput single-cell transcriptomics offers an unbiased approach for understanding the extent, basis and function of gene expression variation between seemingly identical cells. Here we sequence single-cell RNA-seq libraries prepared from over 1,700 primary mouse bone-marrow-derived dendritic cells spanning several experimental conditions. We find substantial variation between identically stimulated dendritic cells, in both the fraction of cells detectably expressing a given messenger RNA and the transcript's level within expressing cells. Distinct gene modules are characterized by different temporal heterogeneity profiles. In particular, a 'core' module of antiviral genes is expressed very early by a few 'precocious' cells in response to uniform stimulation with a pathogenic component, but is later activated in all cells. By stimulating cells individually in sealed microfluidic chambers, analysing dendritic cells from knockout mice, and modulating secretion and extracellular signalling, we show that this response is coordinated by interferon-mediated paracrine signalling from these precocious cells. Notably, preventing cell-to-cell communication also substantially reduces variability between cells in the expression of an early-induced 'peaked' inflammatory module, suggesting that paracrine signalling additionally represses part of the inflammatory program. Our study highlights the importance of cell-to-cell communication in controlling cellular heterogeneity and reveals general strategies that multicellular populations can use to establish complex dynamic responses.
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Even cells of the same type can exhibit substantial heterogeneity, reflecting finer sub-types, regulated functional variation, or inherent stochasticity.
“even cells of the same ‘type’ can exhibit substantial heterogeneity, reflecting finer sub-types, regulated functional variation, or inherent stochasticity1–6”
From Revealing the vectors of cellular identity with single-cell genomics (2016) · cites this paper as [2]
Correlating the expression profiles of genes or proteins opens the way to elucidating the regulatory mechanisms that control them.
“In analogy to simple observational approaches for inferring gene regulation, correlating the expression profiles of genes or proteins opens the way to elucidating the regulatory mechanisms that control them2,3,41,169,170.”
From Revealing the vectors of cellular identity with single-cell genomics (2016) · cites this paper as [2]
Several studies have analyzed the covariation structure between transcripts or proteins across single cells to infer regulatory relations.
“Leveraging this insight, several studies have analyzed the covariation structure between transcripts or proteins across single cells to infer regulatory relations1–3,41,135,137,168–172.”
From Revealing the vectors of cellular identity with single-cell genomics (2016) · cites this paper as [2]
Prior work found that single-cell cellular and genomic features can be measured by methods like RNA-sequencing and remain well-preserved after microfluidic exposure.
“Previous studies have found that cellular and genomic properties of single cells can be measured using techniques such as RNA-sequencing and are well- preserved following exposure to microfluidic environments28.”
From Drug sensitivity of single cancer cells is predicted by changes in mass accumulation rate (2016) · cites this paper as [28]
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- Authors
- Shalek, A. K., Satija, R., Shuga, J., Trombetta, J. J., Gennert, D., Lu, D., Chen, P., Gertner, R. S., Gaublomme, J. T., Yosef, N., Schwartz, S., Fowler, B., Weaver, S., Wang, J., Wang, X., Ding, R., Raychowdhury, R., Friedman, N., Hacohen, N., Park, H., May, A. P., & Regev, A.
- Affiliations
- Broad Institute (US)
- Standard BioTools (United States) (US)
- Harvard University (US)
- Hebrew University of Jerusalem (IL)
- Corresponding author
- Satija, Rahul
- Park, Hongkun
- May, Andrew P.
- ORCID
- Venue
- Nature
- Published
- 2014-06
- Volume
- 510
- Issue
- 7505
- Pages
- 363-369
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC4193940
- OpenAlex
- W2140258573
- Cited by
- 1,000
- References
- 36
- Citations by year
- 2026: 30 · 2025: 66 · 2024: 77 · 2023: 74 · 2022: 73 · 2021: 75 · 2020: 74 · 2019: 98 · 2018: 96 · 2017: 103 · 2016: 110 · 2015: 97 · 2014: 23 · 2013: 1
- FWCI
- 45.48
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Digital Access to Scholarship at Harvard (DASH) (Harvard University) (submittedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- PMC
- Funders
- Howard Hughes Medical Institute
- National Institutes of Health (DP1OD003893, 1dp2od002230-01, DP1OD003958)
- National Human Genome Research Institute (P50HG006193)
- National Cancer Institute (DP1CA174427)
- National Institute of Allergy and Infectious Diseases (U54AI057159)
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (F32HD075541)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
- Keywords
- dendritic cells, paracrine signaling, cell-to-cell communication, gene expression heterogeneity, interferon, antiviral response, inflammation, bone marrow-derived dendritic cells, temporal gene expression dynamics
- MeSH terms
- Animals, Antigens, Viral, Base Sequence, Cell Communication, Dendritic Cells, Gene Expression Regulation, Immunity, RNA, Messenger, Interferon-beta, Paracrine Communication, Gene Expression Profiling, Principal Component Analysis, Microfluidic Analytical Techniques, Mice, Single-Cell Analysis
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