Computational 3D genome modeling

Computational 3D genome modeling

Annaël Brunet, Tharvesh M. Liyakat Ali

Computational methods to infer 3D structural views of the genome in the nuclear space can reveal spatial relationships between genomic regions that are not visible in the under­lying data. Physics-based modeling infers genome fold­ing principles based on physical properties of chromatin. Other genome-modeling approaches consider interaction probabilities between genomic domains determined from e.g. Hi-C data, to infer a 3D positioning of these domains. Analysis of the models provides insights into 3D genome conformation. Spatial genome investigations can also generate hypotheses testable in a wet-lab. For a recent review from our lab, see Sekelja et al. 2016 Genome Biol.

We are developing computational methods and tools for 3D structural modeling of the genome at multiple scales and using interaction probabilities and polymer physics approaches.

Ongoing research

  • Computational methods for 3D and 4D modeling of genome architecture
  • Relationships between 3D chromatin folding, nuclear architecture, epigenetic states and gene expression potential in time-series

Recent achievements