Detection of genes associated with developmental competence of bovine oocytes.

The developmental competence of oocytes is acquired progressively during folliculogenesis and is linked to follicular size. It has been documented that oocytes originating from larger follicles exhibit a greater ability to develop to the blastocyst stage. The differences in cytoplasmic factors such as mRNA transcripts could explain the differences in oocyte developmental potential. We used bovine oligonucleotide microarrays to characterize differences between the gene expression profiles of germinal vesicle stage (GV) oocytes with greater developmental competence from medium follicles (MF) and those with less developmental competence from small follicles (SF). After normalizing the microarray data, our analysis found differences in the level of 60 transcripts (≥1.4 fold), corresponding to 49 upregulated and 11 downregulated transcripts in MF oocytes compared to SF oocytes. The gene expression data were classified according to gene ontology, the majority of the genes were associated with the regulation of transcription, translation, the cell cycle, and mitochondrial activity. A subset of 16 selected genes was validated for GV oocytes by quantitative real-time RT-PCR; significant differences (P˂0.01) were found in the level of TAF1A, MTRF1L, ATP5C1, UBL5 and MAP3K13 between the MF and SF oocytes. After maturation the transcript level remained stable for ATP5F1, BRD7, and UBL5 in both oocyte categories. The transcript level of another 13 genes substantially dropped in the MF and/or SF oocytes. It can be concluded that the developmental competence of bovine oocytes and embryos may be a quantitative trait dependent on small changes in the transcription profiles of many genes. Copyright © 2016 Elsevier B.V. All rights reserved.

Citation

Lucie Nemcova, Denisa Jansova, Katerina Vodickova-Kepkova, Petr Vodicka, Michal Jeseta, Marie Machatkova, Jiri Kanka. Detection of genes associated with developmental competence of bovine oocytes. Animal reproduction science. 2016 Mar;166:58-71

PMID: 26811294

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