Neural network and kinetic modelling of human genome replication reveal replication origin locations and strengths.

In human and other metazoans, the determinants of replication origin location and strength are still elusive. Origins are licensed in G1 phase and fired in S phase of the cell cycle, respectively. It is debated which of these two temporally separate steps determines origin efficiency. Experiments can independently profile mean replication timing (MRT) and replication fork directionality (RFD) genome-wide. Such profiles contain information on multiple origins' properties and on fork speed. Due to possible origin inactivation by passive replication, however, observed and intrinsic origin efficiencies can markedly differ. Thus, there is a need for methods to infer intrinsic from observed origin efficiency, which is context-dependent. Here, we show that MRT and RFD data are highly consistent with each other but contain information at different spatial scales. Using neural networks, we infer an origin licensing landscape that, when inserted in an appropriate simulation framework, jointly predicts MRT and RFD data with unprecedented precision and underlies the importance of dispersive origin firing. We furthermore uncover an analytical formula that predicts intrinsic from observed origin efficiency combined with MRT data. Comparison of inferred intrinsic origin efficiencies with experimental profiles of licensed origins (ORC, MCM) and actual initiation events (Bubble-seq, SNS-seq, OK-seq, ORM) show that intrinsic origin efficiency is not solely determined by licensing efficiency. Thus, human replication origin efficiency is set at both the origin licensing and firing steps.

Developmental and cancer-associated plasticity of DNA replication preferentially targets GC-poor, lowly expressed and late-replicating regions.

The spatiotemporal program of metazoan DNA replication is regulated during development and altered in cancers. We have generated novel OK-seq, Repli-seq and RNA-seq data to compare the DNA replication and gene expression programs of twelve cancer and non-cancer human cell types. Changes in replication fork directionality (RFD) determined by OK-seq are widespread but more frequent within GC-poor isochores and largely disconnected from transcription changes. Cancer cell RFD profiles cluster with non-cancer cells of similar developmental origin but not with different cancer types. Importantly, recurrent RFD changes are detected in specific tumour progression pathways. Using a model for establishment and early progression of chronic myeloid leukemia (CML), we identify 1027 replication initiation zones (IZs) that progressively change efficiency during long-term expression of the BCR-ABL1 oncogene, being twice more often downregulated than upregulated. Prolonged expression of BCR-ABL1 results in targeting of new IZs and accentuation of previous efficiency changes. Targeted IZs are predominantly located in GC-poor, late replicating gene deserts and frequently silenced in late CML. Prolonged expression of BCR-ABL1 results in massive deletion of GC-poor, late replicating DNA sequences enriched in origin silencing events. We conclude that BCR-ABL1 expression progressively affects replication and stability of GC-poor, late-replicating regions during CML progression.