PLoS Computational BiologyBioinformaticsPeer-reviewed journal article
ChromoTrace: Reconstruction of 3D Chromosome Configurations by Super-Resolution Microscopy
Carl BartoniD, Sandro MorganellaiD, Øyvind Ødegård‐FougneriD, Stephanie AlexanderiD, Jonas RiesiD, Tomas W. FitzgeraldiD, Jan EllenbergiD, Ewan BirneyiD
Abstract
MotivationThe three-dimensional structure of chromatin plays a key role in genome function, including gene expression, DNA replication, chromosome segregation, and DNA repair. Furthermore the location of genomic loci within the nucleus, especially relative to each other and nuclear structures such as the nuclear envelope and nuclear bodies strongly correlates with aspects of function such as gene expression. Therefore, determining the 3D position of the 6 billion DNA base pairs in each of the 23 chromosomes inside the nucleus of a human cell is a central challenge of biology. Recent advances of super-resolution microscopy in principle enable the mapping of specific molecular features with nanometer precision inside cells. Combined with highly specific, sensitive and multiplexed fluorescence labeling of DNA sequences this opens up the possibility of mapping the 3D path of the genome sequence in situ.\n\nResultsHere we develop computational methodologies to reconstruct the sequence configuration of all human chromosomes in the nucleus from a super-resolution image of a set of fluorescent in situ probes hybridized to the genome in a cell. To test our approach we develop a method for the simulation of chromatin packing in an idealized human nucleus. Our reconstruction method, ChromoTrace, uses suffix trees to assign a known linear ordering of in situ probes on the genome to an unknown set of 3D in situ probe positions in the nucleus from super-resolved images using the known genomic probe spacing as a set of physical distance constraints between probes. We find that ChromoTrace can assign the 3D positions of the majority of loci with high accuracy and reasonable sensitivity to specific genome sequences. By simulating spatial resolution, label multiplexing and noise scenarios we assess algorithm performance under realistic experimental constraints. Our study shows that it is feasible to achieve chromosome-wide reconstruction of the 3D DNA path in chromatin based on super-resolution microscopy images.
- organism: human
- assay: imaging
- research focus: trajectory inference
- research focus: dimensionality reduction
- approach: statistical model
- Citations
- 6
- FWCI
- 0.36
- Field percentile
- top 47%
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