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...
Saved in:
Published in | Scientific reports Vol. 10; no. 1; p. 19130 |
---|---|
Main Authors | , , , , , , |
Format | Journal Article |
Language | English |
Published |
England
Nature Publishing Group
05.11.2020
Nature Publishing Group UK |
Subjects | |
Online Access | Get full text |
Cover
Loading…
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. |
---|---|
Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 2045-2322 2045-2322 |
DOI: | 10.1038/s41598-020-76152-9 |