Bifurcation analysis of single-cell gene expression data reveals epigenetic landscape
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Significance: Characterization of cellular heterogeneity and hierarchy are important tasks in developmental biology and may help overcome drug resistance in treatment of cancer and other diseases. Single-cell technologies provide a powerful tool for detecting rare cell types and cell-fate transition events, whereas traditional gene expression profiling methods can be used only to measure the average behavior of a cell population. However, the lack of suitable computational methods for single-cell data analysis has become a bottleneck. Here we present a method with the focuses on automatically detecting multilineage transitions and on modeling the associated changes in gene expression patterns. We show that our method is generally applicable and that its applications provide biological insights into developmental processes.
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The cell cycle often has an enormous impact on cellular gene expression, and this impact can extend to other processes and be affected by them.
“The cell cycle often has an enormous impact on cellular gene expression146,149,150 (although some87 have challenged this view), but this impact can extend to other processes, and in turn be affected by them.”
From Revealing the vectors of cellular identity with single-cell genomics (2016) · cites this paper as [149]
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- Authors
- Marco, E., Karp, R. L., Guo, G., Robson, P., Hart, A. H., Trippa, L., & Yuan, G.-C.
- Affiliations
- Harvard University (US)
- Boston Children's Hospital (US)
- National University of Singapore (SG)
- La Trobe University (AU)
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2014-12-15
- Volume
- 111
- Issue
- 52
- Pages
- E5643-50
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC4284553
- OpenAlex
- W2001246746
- Cited by
- 268
- References
- 61
- Citations by year
- 2026: 6 · 2025: 18 · 2024: 9 · 2023: 8 · 2022: 19 · 2021: 19 · 2020: 26 · 2019: 35 · 2018: 40 · 2017: 47 · 2016: 30 · 2015: 11
- FWCI
- 12.02
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- HHS | NIH | National Human Genome Research Institute (NHGRI) (R21HG006778)
- 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 › Developmental Biology and Gene Regulation
- Keywords
- bifurcation analysis, single-cell gene expression, SCUBA, cell lineage reconstruction, cell differentiation, epigenetic landscape, mouse embryo development, Nanog, hematopoietic development, B cell development, stochastic differential equations, nonlinear dynamics, lineage bias, transcription factors
- MeSH terms
- Nanog Homeobox Protein, Animals, B-Lymphocytes, Cell Differentiation, Embryo, Mammalian, Hematopoiesis, Humans, Models, Biological, Stochastic Processes, Homeodomain Proteins, Gene Expression Regulation, Developmental, Epigenesis, Genetic, Mice
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