Differences in firing efficiency, chromatin, and transcription underlie the developmental plasticity of the Arabidopsis DNA replication origins

  1. Crisanto Gutierrez1
  1. 1Centro de Biologia Molecular Severo Ochoa, CSIC-UAM, Nicolas Cabrera 1, Cantoblanco, 28049 Madrid, Spain;
  2. 2Center for Research in Agricultural Genomics, CRAG (CSIC-IRTA-UAB-UB), Campus Universitat Autónoma de Barcelona, Bellaterra, Cerdanyola del Valles, 08193 Barcelona, Spain
  • Present addresses: 3ANFACO-CECOPESCA, Carretera de Colexio Universitario 16, Vigo 36310, Spain; 4Lineberger Comprehensive Cancer Center, Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA

  • Corresponding authors: cgutierrez{at}cbm.csic.es, ubastolla{at}cbm.csic.es
  • Abstract

    Eukaryotic genome replication depends on thousands of DNA replication origins (ORIs). A major challenge is to learn ORI biology in multicellular organisms in the context of growing organs to understand their developmental plasticity. We have identified a set of ORIs of Arabidopsis thaliana and their chromatin landscape at two stages of post-embryonic development. ORIs associate with multiple chromatin signatures including transcription start sites (TSS) but also proximal and distal regulatory regions and heterochromatin, where ORIs colocalize with retrotransposons. In addition, quantitative analysis of ORI activity led us to conclude that strong ORIs have high GC content and clusters of GGN trinucleotides. Development primarily influences ORI firing strength rather than ORI location. ORIs that preferentially fire at early developmental stages colocalize with GC-rich heterochromatin, but at later stages with transcribed genes, perhaps as a consequence of changes in chromatin features associated with developmental processes. Our study provides the set of ORIs active in an organism at the post-embryo stage that should allow us to study ORI biology in response to development, environment, and mutations with a quantitative approach. In a wider scope, the computational strategies developed here can be transferred to other eukaryotic systems.

    Footnotes

    • Received June 22, 2018.
    • Accepted February 25, 2019.

    This article is distributed exclusively by Cold Spring Harbor Laboratory Press for the first six months after the full-issue publication date (see http://genome.cshlp.org/site/misc/terms.xhtml). After six months, it is available under a Creative Commons License (Attribution-NonCommercial 4.0 International), as described at http://creativecommons.org/licenses/by-nc/4.0/.

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