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Megabase Replication Domains Along the Human Genome: Relation to Chromatin Structure and Genome Organisation

  • Benjamin AuditEmail author
  • Lamia Zaghloul
  • Antoine Baker
  • Alain Arneodo
  • Chun-Long Chen
  • Yves d’Aubenton-Carafa
  • Claude Thermes
Part of the Subcellular Biochemistry book series (SCBI, volume 61)

Abstract

In higher eukaryotes, the absence of specific sequence motifs, marking the origins of replication has been a serious hindrance to the understanding of (i) the mechanisms that regulate the spatio-temporal replication program, and (ii) the links between origins activation, chromatin structure and transcription. In this chapter, we review the partitioning of the human genome into megabased-size replication domains delineated as N-shaped motifs in the strand compositional asymmetry profiles. They collectively span 28.3% of the genome and are bordered by more than 1,000 putative replication origins. We recapitulate the comparison of this partition of the human genome with high-resolution experimental data that confirms that replication domain borders are likely to be preferential replication initiation zones in the germline. In addition, we highlight the specific distribution of experimental and numerical chromatin marks along replication domains. Domain borders correspond to particular open chromatin regions, possibly encoded in the DNA sequence, and around which replication and transcription are highly coordinated. These regions also present a high evolutionary breakpoint density, suggesting that susceptibility to breakage might be linked to local open chromatin fiber state. Altogether, this chapter presents a compartmentalization of the human genome into replication domains that are landmarks of the human genome organization and are likely to play a key role in genome dynamics during evolution and in pathological situations.

Keywords

Wavelet Transform Replication Origin Nucleosome Position Open Chromatin Nucleosome Occupancy 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

We thank G. Chevereau, G. Guilbaud, O. Hyrien, H. Julienne, O. Rappailles and C. Vaillant for helpful discussions. This work was supported by ACI IMPBio2004, the PAI Tournesol and the Agence Nationale de la Recherche under project HUGOREP (ANR PCV 2005) and REFOPOL (ANR BLANC SVSE6).

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© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  • Benjamin Audit
    • 1
    • 2
    Email author
  • Lamia Zaghloul
    • 1
    • 2
  • Antoine Baker
    • 1
    • 2
  • Alain Arneodo
    • 1
    • 2
  • Chun-Long Chen
    • 3
  • Yves d’Aubenton-Carafa
    • 3
  • Claude Thermes
    • 3
  1. 1.Université de LyonLyonFrance
  2. 2.Laboratoire de Physique, CNRSEcole Normale Supérieure de LyonLyonFrance
  3. 3.Centre de Génétique Moléculaire, CNRSGif-sur-YvetteFrance

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