MIRA: joint regulatory modeling of multimodal expression and chromatin accessibility in single cells
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Abstract
Rigorously comparing gene expression and chromatin accessibility in the same single cells could illuminate the logic of how coupling or decoupling of these mechanisms regulates fate commitment. Here we present MIRA, probabilistic multimodal models for integrated regulatory analysis, a comprehensive methodology that systematically contrasts transcription and accessibility to infer the regulatory circuitry driving cells along cell state trajectories. MIRA leverages topic modeling of cell states and regulatory potential modeling of individual gene loci. MIRA thereby represents cell states in an efficient and interpretable latent space, infers high-fidelity cell state trees, determines key regulators of fate decisions at branch points and exposes the variable influence of local accessibility on transcription at distinct loci. Applied to epidermal differentiation and embryonic brain development from two different multimodal platforms, MIRA revealed that early developmental genes were tightly regulated by local chromatin landscape whereas terminal fate genes were titrated without requiring extensive chromatin remodeling.
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SCENIC+, FigR and MIRA model joint variation across paired transcriptomic and scATAC-seq measurements to link enhancers to genes and identify transcription factors that drive cellular decisions.
“These include SCENIC+176, functional inference of gene regulation (FigR)177, and probabilistic multimodal models for integrated regulatory analysis (MIRA)178, which model joint variation across paired transcriptomic and scATAC-seq measurements to link enhancers to genes and to identify transcription factors that drive cellular decisions.”
From The technological landscape and applications of single-cell multi-omics (2023) · cites this paper as [178]
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“Large isotype counts can be detected in outlier cells, which should then be removed.”
BackgroundThe technological landscape and applications of single-cell multi-omics
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- Authors
- Lynch, A. W., Theodoris, C. V., Long, H. W., Brown, M., Liu, X. S., & Meyer, C. A.
- Affiliations
- Dana-Farber Cancer Institute (US)
- Boston Children's Hospital (US)
- Brigham and Women's Hospital (US)
- Harvard University (US)
- Corresponding author
- Liu, X. Shirley
- Meyer, Clifford A.
- ORCID
- Venue
- Nature Methods
- Published
- 2022-09
- Volume
- 19
- Issue
- 9
- Pages
- 1097-1108
- ISSN
- 1548-7091 (ISSN-L)
- 1548-7105
- PMC
- PMC9517733
- OpenAlex
- W4294805059
- Cited by
- 80
- References
- 63
- Citations by year
- 2026: 23 · 2025: 22 · 2024: 20 · 2023: 13 · 2022: 2
- FWCI
- 4.65
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Licence
- Locations
- Nature Methods (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- U.S. Department of Health & Human Services | NIH | National Cancer Institute (U24CA237617)
- U.S. Department of Health & Human Services | NIH | National Institute of General Medical Sciences (T32GM007748)
- 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 Chromatin Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
- Keywords
- chromatin accessibility, gene expression, fate commitment, topic modeling, epidermal differentiation, embryonic brain development, chromatin remodeling
- MeSH terms
- Cell Differentiation, Chromatin, Gene Expression Regulation, Developmental, Embryonic Development
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