Defining cell types and states with single-cell genomics
Open accessAbstract
A revolution in cellular measurement technology is under way: For the first time, we have the ability to monitor global gene regulation in thousands of individual cells in a single experiment. Such experiments will allow us to discover new cell types and states and trace their developmental origins. They overcome fundamental limitations inherent in measurements of bulk cell population that have frustrated efforts to resolve cellular states. Single-cell genomics and proteomics enable not only precise characterization of cell state, but also provide a stunningly high-resolution view of transitions between states. These measurements may finally make explicit the metaphor that C.H. Waddington posed nearly 60 years ago to explain cellular plasticity: Cells are residents of a vast “landscape” of possible states, over which they travel during development and in disease. Single-cell technology helps not only locate cells on this landscape, but illuminates the molecular mechanisms that shape the landscape itself. However, single-cell genomics is a field in its infancy, with many experimental and computational advances needed to fully realize its full potential.
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Conventional bulk biochemical assays of chromatin return the mean profile of their input cells, which due to Simpson's paradox is potentially representative of none of the cells therein.
“Conventional or ‘bulk’ biochemical assays of chromatin return the mean profile of their input cells, which due to Simpson’s paradox [G] is potentially representative of none of the cells therein157,158.”
From Towards a comprehensive catalogue of validated and target-linked human enhancers (2020) · cites this paper as [157]
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Yuste, R., Hawrylycz, M., Aalling, N., Aguilar-Valles, A., Arendt, D., Armañanzas, R., Ascoli, G. A., Bielza, C., Bokharaie, V., Bergmann, T. B., et al. (2020) · Nature Neuroscience · doi:10.1038/s41593-020-0685-8 · Cited by 32 · see citing works
Enhancer grammar of liver cell types and hepatocyte zonation states
González-Blas, C. B., Matetovici, I., Hillen, H., Taskiran, I. I., Vandepoel, R., Christiaens, V., Sansores-García, L., Verboven, E., Hulselmans, G., Poovathingal, S., et al. (2022) · doi:10.1101/2022.12.08.519575 · Cited by 5 · see citing works
- Authors
- Trapnell, C.
- Affiliations
- University of Washington (US)
- Corresponding author
- Trapnell, Cole
- ORCID
- Trapnell, Cole
- Venue
- Genome Research
- Publisher
- Cold Spring Harbor Laboratory
- Published
- 2015-10
- Volume
- 25
- Issue
- 10
- Pages
- 1491-1498
- ISSN
- 1088-9051 (ISSN-L)
- 1549-5469
- PMC
- PMC4579334
- OpenAlex
- W2178888844
- Cited by
- 813
- References
- 20
- Citations by year
- 2026: 80 · 2025: 68 · 2024: 84 · 2023: 69 · 2022: 74 · 2021: 104 · 2020: 93 · 2019: 80 · 2018: 57 · 2017: 47 · 2016: 50 · 2015: 1 · 2014: 2 · 2012: 1
- Type
- posted content
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Genome Research (publishedVersion)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- Funders
- Dale Frey Award
- Damon Runyon Cancer Research Foundation
- Alfred P. Sloan Foundation Fellowship
- 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 › Gene expression and cancer classification
- Keywords
- single-cell genomics, cell types, cell states, cellular plasticity, Waddington landscape, cellular heterogeneity, gene expression regulation, cell state transitions, developmental origins, single-cell proteomics
- MeSH terms
- Animals, Cells, Cytological Techniques, Humans, Genomics
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