bioRxivCell BiologyPreprint
Single-cell resolution of resection-dependent chromatin accessibility in response to DNA double-strand breaks reveals specific gene expression programs
Sarah CollinsiD, Anne-Laure Finoux, Coline ArnouldiD, Romane Carette, Vincent RocheriD, Gaëlle LegubeiD, Thomas ClouaireiD
Abstract
Chromatin structure is extensively modified and remodeled to allow for efficient signaling and repair of DNA double-strand breaks (DSBs), a process which is influenced by the nature and properties of the damaged locus or the repair pathway involved. However, the extent of cell-to-cell variability in these DSB-induced chromatin modifications remains poorly characterized. Here, we report how chromatin accessibility is reshuffled at the damaged locus at high resolution. Notably, we identify a long-range increase in chromatin accessibility which is dependent on functional resection. We report that resection-dependent chromatin remodeling events at individual damaged loci display significant heterogeneity in single cells which are only partly explained by the cell cycle, and can frequently be detected as asymmetric and unidirectional. Moreover, we identify strong transcriptional phenotypes upon sustained DNA damage as well as subpopulations of S and G2/M cells for which similar resection-dependent chromatin accessibility patterns occur simultaneously at multiple DSBs. These coordinated chromatin accessibility patterns at multiple DSBs are associated with specific gene expression programs, including DNA damage checkpoint signaling, inflammation and apoptosis. Altogether, our results highlight the heterogeneity in chromatin remodeling during DSB repair and suggest unexpected links between DNA end resection and specific gene expression programs mounted in response to genotoxic stress.
- organism: human
- assay: ATAC-seq
- assay: bulk RNA-seq
- research focus: chromatin & epigenetic regulation
- research focus: gene regulatory network inference
- research focus: differential expression
- approach: experimental assay
- approach: statistical model
- Citations
- 0
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