Unveiling the role of chromosome structure morphology on gene function through chromosome conformation analysis
Single-cell chromosome conformations vary significantly among individual cells. We introduce a two-step dimensionality reduction method for density-based, unsupervised clustering of single-cell 3D chromosome structures from simulations or multiplexed 3D-FISH imaging. Our method clusters up to half of all structures into 5-12 prevalent conformational states per chromosome. These states are distinguished by subdivisions into chromosome territory domains, whose boundary locations influence subnuclear positions and speckle associations of certain genes and establish long-range structural variations of more than 10 Mb. Territory domain boundaries are found at few sequence locations, shared among cell types and often situated at syntenic breakpoints.
Authors
- Lorenzo Boninsegna (ORCID: https://orcid.org/0000-0003-4529-3567)
- Frank Alber (ORCID: https://orcid.org/0000-0003-1981-8390)
- Aslı Yıldırım (ORCID: https://orcid.org/0000-0002-5654-3093)
- Yuxiang Zhan
Institutions
- QB3 (US)
- University of Southern California (US)
- University of California, Los Angeles (US)
- Quantitative BioSciences (US)
Publication Details
- Journal
- Genome biology
- Published
- 2025-02-13
- DOI
- https://doi.org/10.1186/s13059-024-03472-8
- Citations
- 3
- Primary Topic
- Single-cell and spatial transcriptomics
- Type
- article
- Field-Weighted Citation Impact
- 2.42
Funders
- National Institutes of Health