Dynamic regulation of origin firing factors links CDK activity to dormant origin activation
Hossain, M. S.; Sansam, C. G.; Wittig, K. A.; Noble, T. D.; Boyd, K. A.; Sansam, C. L.
Show abstract
Dormant replication origins help ensure complete genome duplication when replication forks stall, yet how these origins are activated remains poorly understood. Here, we identify a novel regulatory mechanism by which cyclin-dependent kinase (CDK) activity controls the abundance and chromatin recruitment of the origin firing factors TRESLIN and MTBP to promote dormant origin activation. Inhibition of WEE1 kinase during S phase increases CDK activity, which blocks the PCNA-dependent degradation of TRESLIN and enhances its chromatin association along with MTBP. This increased loading is required for elevated helicase recruitment and DNA synthesis under CDK-hyperactive conditions. These effects are reversed by CDK inhibition and depend on both TRESLIN and MTBP. We define a conserved sequence within TRESLIN required for its CDK-sensitive degradation. Significantly, the recruitment of TRESLIN-MTBP and loading of helicase exceed levels observed in unperturbed S phase, supporting a model in which dormant origin firing is actively upregulated through CDK-mediated stabilization of the initiation machinery. These findings uncover a new control point in replication origin usage with implications for genome stability and therapeutic kinase inhibition.
Matching journals
The top 4 journals account for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
- The Consequences of Differential Origin Licensing Dynamics in Distinct Chromatin Environments 97%
- The PIN1-p38-CtIP signaling axis protects stalled replication forks from deleterious degradation 97%
- SUMO protease and proteasome recruitment at the nuclear periphery differently affect replication dynamics at arrested forks. 96%
Similar papers in this journal
"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.