High-precision mapping of nuclear pore-chromatin interactions reveals new principles of genome organization at the nuclear envelope
Hetzer, M. W.; tyagi, s.; Chen, F.; Huang, J.
Show abstract
The role of nuclear pore complexes (NPCs) in genome organization remains poorly characterized due to technical limitations in probing genome-wide protein-DNA interactions specific to the nuclear periphery. Here, we developed a new sensitive method, NPC-DamID, which combines in vitro reconstitution of nuclear import and DamID technology. The fixation-free method identifies chromatin interactions at the NPCs in intact nuclei from cells and tissues. We found that NPCs are preferentially associated with common and hierarchically arranged super-enhancers (SEs) across multiple cell types. We also uncovered phase-separated condensates at NPCs that compartmentalize and concentrate transcriptional coactivators and structural proteins at SE-regulated genes. Our results support NPCs as anchoring sites for SE regulatory hubs and cell-type-specific transcriptional control.
Matching journals
The top 4 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Beyond A and B Compartments: how major nuclear locales define nuclear genome organization and function 96%
- Imaging analysis of six human histone H1 variants reveals universal enrichment of H1.2, H1.3, and H1.5 at the nuclear periphery and nucleolar H1X presence 96%
- Single-molecule imaging of chromatin remodelers reveals role of ATPase in promoting fast kinetics of target search and dissociation from chromatin 95%
Similar papers in this journal
- Rapid depletion of CTCF and cohesin proteins reveals dynamic features of chromosome architecture. 96%
- Mod(mdg4) variants repress telomeric retrotransposonHeT-A by blocking subtelomeric enhancers 95%
- Suppression of liquid-liquid phase separation by 1,6-hexanediol partially compromises the 3D genome organization in living cells 95%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.