The proteome, not the transcriptome, predicts that oocyte superovulation affects embryonic phenotypes in mice.


Journal

Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288

Informations de publication

Date de publication:
09 12 2021
Historique:
received: 16 07 2021
accepted: 26 11 2021
entrez: 10 12 2021
pubmed: 11 12 2021
medline: 1 2 2022
Statut: epublish

Résumé

Superovulation is the epitome for generating oocytes for molecular embryology in mice, and it is used to model medically assisted reproduction in humans. However, whether a superovulated oocyte is normal, is an open question. This study establishes for the first time that superovulation is associated with proteome changes that affect phenotypic traits in mice, whereas the transcriptome is far less predictive. The proteins that were differentially expressed in superovulated mouse oocytes and embryos compared to their naturally ovulated counterparts were enriched in ontology terms describing abnormal mammalian phenotypes: a thinner zona pellucida, a smaller oocyte diameter, increased frequency of cleavage arrest, and defective blastocyst formation, which could all be verified functionally. Moreover, our findings indicate that embryos with such abnormalities are negatively selected during preimplantation, and ascribe these abnormalities to incomplete ovarian maturation during the time of the conventional superovulation, since they could be corrected upon postponement of the ovulatory stimulus by 24 h. Our data place constraints on the common view that superovulated oocytes are suitable for drawing general conclusions about developmental processes, and underscore the importance of including the proteins in a modern molecular definition of oocyte quality.

Identifiants

pubmed: 34887460
doi: 10.1038/s41598-021-03054-9
pii: 10.1038/s41598-021-03054-9
pmc: PMC8660899
doi:

Substances chimiques

Proteome 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

23731

Informations de copyright

© 2021. The Author(s).

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Auteurs

Leila Taher (L)

Institute of Biomedical Informatics, Graz University of Technology, Stremayrgasse 16/I, 8010, Graz, Austria. leila.taher@tugraz.at.

Steffen Israel (S)

Max Planck Institute for Molecular Biomedicine, Roentgenstrasse 20, 48149, Muenster, Germany.

Hannes C A Drexler (HCA)

Max Planck Institute for Molecular Biomedicine, Roentgenstrasse 20, 48149, Muenster, Germany.

Wojciech Makalowski (W)

Institute of Bioinformatics, Faculty of Medicine, University of Münster, Niels Stensen Str. 14, 48149, Münster, Germany.

Yutaka Suzuki (Y)

Department of Medical Genome Sciences, Graduate School of Frontier Sciences, University of Tokyo, Kashiwa, Chiba, 277-8562, Japan.

Georg Fuellen (G)

Institute for Biostatistics and Informatics in Medicine and Aging Research (IBIMA), Rostock University Medical Center, Ernst-Heydemann-Strasse 8, 18057, Rostock, Germany. fuellen@uni-rostock.de.

Michele Boiani (M)

Max Planck Institute for Molecular Biomedicine, Roentgenstrasse 20, 48149, Muenster, Germany. mboiani@mpi-muenster.mpg.de.

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