Mammalian Genome

, Volume 20, Issue 9–10, pp 664–673 | Cite as

Effect of IVF and laser zona dissection on DNA methylation pattern of mouse zygotes

  • Dominika D. Peters
  • Konstantin Lepikhov
  • Karsten Rodenacker
  • Susan Marschall
  • Auke Boersma
  • Peter Hutzler
  • Hagen Scherb
  • Jörn Walter
  • Martin Hrabé de AngelisEmail author


In vitro fertilization (IVF) and zona pellucida laser microdissection-facilitated IVF (Laser-IVF) are presently routine procedures in human assisted reproduction. The safety of these methods at the epigenetic level is not fully understood. Studies on mouse Laser-IVF embryos provide evidence that the use of Laser-IVF leads to reduced birth rate, indicating a potential harm of this technique for the embryo. Hence, the aim of this study was to examine the difference in DNA methylation pattern between IVF- and Laser-IVF-derived mouse zygotes. We examined two experimental groups of C3HeB/FeJ oocytes: (1) zona-intact and (2) laser-microdissected oocytes that were fertilized in vitro with freshly collected spermatozoa. Zygotes were fixed 5, 8, and 12 h after fertilization, and indirect immunofluorescence staining was studied using an anti-5-methylcytidine (5-MeC) antibody. The fluorescence intensities of paternal and maternal pronuclei were evaluated using the computer-assisted analysis of digital images. In addition, we performed a semiquantitative RT-PCR analysis of the presence of transcripts of three developmental marker genes, Oct4, Dab2, and Dnmt3b, in IVF- and Laser-IVF-derived blastocysts. We observed no significant differences in methylation status of the paternal genome and in the transcripts of the developmental marker genes after IVF and Laser-IVF. In conclusion, epigenetic patterns and early embryonic development are not altered by laser-assisted IVF techniques and another explanation must be sought for the poor implantation rates observed in mice.


Zona Pellucida Inner Cell Mass Laser Microdissection Post Fertilization Paternal Genome 
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.



This work was supported by the European Commission under FP6, by EMMA inf (RII3-CT-2004-506455) to MHdA and by a grant from the National Genome Research Network, NGFN + (01GS0850), to MHdA. We thank Stefanie Dunst, Monika Beschorner, Andrea Bäßler, Alexander Huber, and Bernhard Rey for excellent technical assistance. We are grateful to John Favor for valuable comments on this manuscript.


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Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • Dominika D. Peters
    • 1
  • Konstantin Lepikhov
    • 3
  • Karsten Rodenacker
    • 2
  • Susan Marschall
    • 1
  • Auke Boersma
    • 1
  • Peter Hutzler
    • 4
  • Hagen Scherb
    • 2
  • Jörn Walter
    • 3
  • Martin Hrabé de Angelis
    • 1
    Email author
  1. 1.Institute of Experimental GeneticsHelmholtz Zentrum München, German Research Center for Environmental Health (GmbH)NeuherbergGermany
  2. 2.Institute of Biomathematics and BiometryHelmholtz Zentrum München, German Research Center for Environmental Health (GmbH)NeuherbergGermany
  3. 3.Department of Natural Sciences – Technical Faculty III FR 8.3, Biological Sciences, Institute of Genetics/EpigeneticsUniversity of SaarlandSaarbrückenGermany
  4. 4.Institute of PathologyHelmholtz Zentrum München, German Research Center for Environmental Health (GmbH)NeuherbergGermany

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