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Neural network and kinetic modelling of human genome replication reveal replication origin locations and strengths.
PLoS Comput Biol, 19(5):e1011138.
In human and other metazoans, the determinants of replication origin location andstrength are still elusive. Origins are licensed in G1 phase and fired in S phaseof the cell cycle, respectively. It is debated which of these two temporallyseparate steps determines origin efficiency. Experiments can independentlyprofile mean replication timing (MRT) and replication fork directionality (RFD)genome-wide. Such profiles contain information on multiple origins' propertiesand 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 highlyconsistent with each other but contain information at different spatial scales.Using neural networks, we infer an origin licensing landscape that, when insertedin an appropriate simulation framework, jointly predicts MRT and RFD data withunprecedented precision and underlies the importance of dispersive origin firing.We furthermore uncover an analytical formula that predicts intrinsic fromobserved origin efficiency combined with MRT data. Comparison of inferredintrinsic origin efficiencies with experimental profiles of licensed origins(ORC, MCM) and actual initiation events (Bubble-seq, SNS-seq, OK-seq, ORM) showthat intrinsic origin efficiency is not solely determined by licensingefficiency. Thus, human replication origin efficiency is set at both the originlicensing and firing steps.
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