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Genome-Wide Mapping of Human DNA Replication by Optical Replication Mapping Supports a Stochastic Model of Eukaryotic Replication

Weitao Wang, Kyle Klein, Karel Proesmans, Hongbo Yang, View ORCID ProfileClaire Marchal, Xiaopeng Zhu, Tyler Borrman, Alex Hastie, View ORCID ProfileZhiping Weng, View ORCID ProfileJohn Bechhoefer, View ORCID ProfileChun-Long Chen, View ORCID ProfileDavid M. Gilbert, View ORCID ProfileNicholas Rhind
doi: https://doi.org/10.1101/2020.08.24.263459
Weitao Wang
1Institut Curie, PSL Research University, CNRS UMR 3244, Paris, France
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Kyle Klein
2Florida State University, Department of Biological Science, Tallahassee, FL, USA
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Karel Proesmans
3Simon Fraser University, Department of Physics, Burnaby, British Columbia, Canada
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Hongbo Yang
4Northwestern University, Feinberg School of Medicine, Chicago, Department of Biochemistry and Molecular Genetics, Illinois, USA
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Claire Marchal
2Florida State University, Department of Biological Science, Tallahassee, FL, USA
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Xiaopeng Zhu
5Carnegie Mellon University, Computational Biology Department, Pittsburgh, PA, USA
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Tyler Borrman
6University of Massachusetts Medical School, Program in Bioinformatics and Integrated Biology, Worcester, MA, USA
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Alex Hastie
7Bionano Genomics, San Diego, CA, USA
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Zhiping Weng
6University of Massachusetts Medical School, Program in Bioinformatics and Integrated Biology, Worcester, MA, USA
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John Bechhoefer
3Simon Fraser University, Department of Physics, Burnaby, British Columbia, Canada
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  • For correspondence: johnb@sfu.ca chunlong.chen@curie.fr gilbert@sdbri.org nick.rhind@umassmed.edu
Chun-Long Chen
1Institut Curie, PSL Research University, CNRS UMR 3244, Paris, France
8Sorbonne University, Paris, France
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  • For correspondence: johnb@sfu.ca chunlong.chen@curie.fr gilbert@sdbri.org nick.rhind@umassmed.edu
David M. Gilbert
2Florida State University, Department of Biological Science, Tallahassee, FL, USA
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  • For correspondence: johnb@sfu.ca chunlong.chen@curie.fr gilbert@sdbri.org nick.rhind@umassmed.edu
Nicholas Rhind
9University of Massachusetts Medical School, Department of Biochemistry and Molecular Pharmacology, Worcester, MA, USA
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  • For correspondence: johnb@sfu.ca chunlong.chen@curie.fr gilbert@sdbri.org nick.rhind@umassmed.edu
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Abstract

DNA replication is regulated by the location and timing of replication initiation. Therefore, much effort has been invested in identifying and analyzing the sites of human replication initiation. However, the heterogeneous nature of eukaryotic replication kinetics and the low efficiency of individual initiation site utilization in metazoans has made mapping the location and timing of replication initiation in human cells difficult. A potential solution to the problem of human replication mapping is single-molecule analysis. However, current approaches do not provide the throughput required for genome-wide experiments. To address this challenge, we have developed Optical Replication Mapping (ORM), a high-throughput single-molecule approach to map newly replicated DNA, and used it to map early initiation events in human cells. The single-molecule nature of our data, and a total of more than 2000-fold coverage of the human genome on 27 million fibers averaging ~300 kb in length, allow us to identify initiation sites and their firing probability with high confidence. In particular, for the first time, we are able to measure genome-wide the absolute efficiency of human replication initiation. We find that the distribution of human replication initiation is consistent with inefficient, stochastic initiation of heterogeneously distributed potential initiation complexes enriched in accessible chromatin. In particular, we find sites of human replication initiation are not confined to well-defined replication origins but are instead distributed across broad initiation zones consisting of many initiation sites. Furthermore, we find no correlation of initiation events between neighboring initiation zones. Although most early initiation events occur in early-replicating regions of the genome, a significant number occur in late-replicating regions. The fact that initiation sites in typically late-replicating regions have some probability of firing in early S phase suggests that the major difference between initiation events in early and late replicating regions is their intrinsic probability of firing, as opposed to a qualitative difference in their firing-time distributions. Moreover, modeling of replication kinetics demonstrates that measuring the efficiency of initiation-zone firing in early S phase suffices to predict the average firing time of such initiation zones throughout S phase, further suggesting that the differences between the firing times of early and late initiation zones are quantitative, rather than qualitative. These observations are consistent with stochastic models of initiation-timing regulation and suggest that stochastic regulation of replication kinetics is a fundamental feature of eukaryotic replication, conserved from yeast to humans.

Competing Interest Statement

Alex Hastie is an employee of Bionano Genomics.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC 4.0 International license.
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Posted April 14, 2021.
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Genome-Wide Mapping of Human DNA Replication by Optical Replication Mapping Supports a Stochastic Model of Eukaryotic Replication
Weitao Wang, Kyle Klein, Karel Proesmans, Hongbo Yang, Claire Marchal, Xiaopeng Zhu, Tyler Borrman, Alex Hastie, Zhiping Weng, John Bechhoefer, Chun-Long Chen, David M. Gilbert, Nicholas Rhind
bioRxiv 2020.08.24.263459; doi: https://doi.org/10.1101/2020.08.24.263459
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Genome-Wide Mapping of Human DNA Replication by Optical Replication Mapping Supports a Stochastic Model of Eukaryotic Replication
Weitao Wang, Kyle Klein, Karel Proesmans, Hongbo Yang, Claire Marchal, Xiaopeng Zhu, Tyler Borrman, Alex Hastie, Zhiping Weng, John Bechhoefer, Chun-Long Chen, David M. Gilbert, Nicholas Rhind
bioRxiv 2020.08.24.263459; doi: https://doi.org/10.1101/2020.08.24.263459

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