Plasma extracellular vesicle miRNAs as potential biomarkers of superstimulatory response in cattle

The ability to predict superstimulatory response would be a beneficial tool in assisted reproduction. Using small RNAseq technology, we profiled extracellular vesicle microRNA (EV-miRNA) abundance in the blood plasma of heifers exhibiting variable responses to superstimulation. Estrous synchronized...

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Published inScientific reports Vol. 10; no. 1; p. 19130
Main Authors Gad, Ahmed, Sánchez, José María, Browne, John A, Nemcova, Lucie, Laurincik, Jozef, Prochazka, Radek, Lonergan, Pat
Format Journal Article
LanguageEnglish
Published England Nature Publishing Group 05.11.2020
Nature Publishing Group UK
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Summary:The ability to predict superstimulatory response would be a beneficial tool in assisted reproduction. Using small RNAseq technology, we profiled extracellular vesicle microRNA (EV-miRNA) abundance in the blood plasma of heifers exhibiting variable responses to superstimulation. Estrous synchronized crossbred beef heifers (n = 25) were superstimulated and blood samples were collected from each heifer on Day 7 of consecutive unstimulated (U) and superstimulated (S) cycles. A subset of high (H) and low (L) responders was selected depending on their response to superstimulation and EV-miRNA profiles were analysed at both time-points in each heifer. Approximately 200 known miRNAs were detected in each sample with 144 commonly detected in all samples. A total of 12 and 14 miRNAs were dysregulated in UH vs. UL and in SH vs. SL heifers, respectively. Interestingly, miR-206 and miR-6517 exhibited the same differential expression pattern in H compared to L heifers both before and after superstimulation. Pathway analysis indicated that circadian rhythm and signaling pathways were among the top pathways enriched with genes targeted by dysregulated miRNAs in H vs. L responding heifers. In conclusion, heifers with divergent ovarian responses exhibited differential expression of plasma EV-miRNAs which may be used as a potential biomarker to predict superstimulation response.
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ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-020-76152-9