title: Hi-C Chromatin Interaction Networks Predict Co-expression in the Mouse Cortex.
abstract: The three dimensional conformation of the genome in the cell nucleus influences important biological processes such as gene expression regulation. Recent studies have shown a strong correlation between chromatin interactions and gene co-expression. However, predicting gene co-expression from frequent long-range chromatin interactions remains challenging. We address this by characterizing the topology of the cortical chromatin interaction network using scale-aware topological measures. We demonstrate that based on these characterizations it is possible to accurately predict spatial co-expression between genes in the mouse cortex. Consistent with previous findings, we find that the chromatin interaction profile of a gene-pair is a good predictor of their spatial co-expression. However, the accuracy of the prediction can be substantially improved when chromatin interactions are described using scale-aware topological measures of the multi-resolution chromatin interaction network. We conclude that, for co-expression prediction, it is necessary to take into account different levels of chromatin interactions ranging from direct interaction between genes (i.e. small-scale) to chromatin compartment interactions (i.e. large-scale).
authors.affiliation: Delft Bioinformatics Lab, Delft University of Technology, Delft, The Netherlands.
authors.forename: Sepideh
authors.initials: S
authors.lastname: Babaei
authors.affiliation: Delft Bioinformatics Lab, Delft University of Technology, Delft, The Netherlands; Division of Image Processing, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands.
authors.forename: Ahmed
authors.initials: A
authors.lastname: Mahfouz
authors.affiliation: Delft Bioinformatics Lab, Delft University of Technology, Delft, The Netherlands; Department of Clinical Genetics, VU University Medical Center, Amsterdam, The Netherlands.
authors.forename: Marc
authors.initials: M
authors.lastname: Hulsman
authors.affiliation: Division of Image Processing, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands; Department of Intelligent Systems, Delft University of Technology, Delft, The Netherlands.
authors.forename: Boudewijn P F
authors.initials: BP
authors.lastname: Lelieveldt
authors.affiliation: Delft Bioinformatics Lab, Delft University of Technology, Delft, The Netherlands.
authors.forename: Jeroen
authors.initials: J
authors.lastname: de Ridder
authors.affiliation: Delft Bioinformatics Lab, Delft University of Technology, Delft, The Netherlands.
authors.forename: Marcel
authors.initials: M
authors.lastname: Reinders
mesh_terms: D000818:Animals; D002467:Cell Nucleus / Q000235:genetics; D002540:Cerebral Cortex / Q000378:metabolism / Q000502:physiology*; D002843:Chromatin / Q000235:genetics* / Q000378:metabolism / Q000648:ultrastructure; D002875:Chromosomes; D005786:Gene Expression Regulation; D016678:Genome; D008297:Male; D051379:Mice; D008810:Mice, Inbred C57BL; D008957:Models, Genetic; D013329:Structure-Activity Relationship
chemical_list: D002843:Chromatin