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Reproduction, Fertility and Development Reproduction, Fertility and Development Society
Vertebrate reproductive science and technology
RESEARCH ARTICLE

113 EXPRESSION PROFILING OF NONCODING microRNAs IN BOVINE GRANULOSA CELLS OF PREOVULATORY DOMINANT FOLLICLE USING DEEP SEQUENCING

S. Gebremedhn A , I. Ahmad A , D. Salilew-Wondim A , S. Sahadevan A , M. Hoelker A , F. Rings A , J. Udin A , E. Tholen A , C. Looft A , K. Schellander A and D. Tesfaye A
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Institute of Animal Science, University of Bonn, Bonn, Germany

Reproduction, Fertility and Development 26(1) 170-171 https://doi.org/10.1071/RDv26n1Ab113
Published: 5 December 2013

Abstract

In cattle, follicles grow in a wave-like pattern, with typically 2 or 3 waves per oestrous cycle. During each wave, one follicle of a cohort becomes dominant (DF), whereas the remaining subordinate follicles (SF) in the cohort undergo atresia. If the endocrine conditions are appropriate (low progesterone), the dominant follicle goes on to ovulate. In order to unravel the molecular mechanisms associated with ovulation and follicular atresia, here we aimed to investigate the expression of short regulatory microRNA (miRNA) in granulosa cells of DF and SF using deep sequencing. For this, Simmental heifers (n = 7) were synchronized according to standard protocols and slaughtered at Day 19 of the oestrous cycle. Follicles were categorized as DF (≥12 mm; n = 5) and SF (≤10 mm; n = 78). Granulosa cells from both follicle groups were used for total RNA (enriched with miRNA) isolation using miRNeasy mini kit (Qiagen GmbH, Hilden, Germany). The RNA concentration and integrity were measured using Nano Drop 8000 spectrophotometer (Nano Drop, Wilmington, DE, USA) and Agilent, 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA), respectively. Libraries were constructed by GATC BioTech AG (Konstanz, Germany) and sequenced on Illumina HISEqn 2000. Prediction of both known and novel miRNA was done using miRDeep2 software packages. Quantification of differentially expressed miRNA was done using R software and DESEqn 2 packages. The MiRNA with log2 fold change difference ≥1, P-value ≤0.05, and false discovery rate of ≤0.1 were considered to be significant. Results showed that 318 and 322 known miRNA were detected in DF and SF, respectively. It was shown that 28 miRNA including bta-miR-122, bta-miR-139, and bta-miR-375, and 35 others including bta-miR-138, bta-miR-20b, and bta-miR-33a were uniquely detected in DF and SF, respectively. In addition to the known annotated miRNA, 20 and 24 novel miRNA were detected in DF and SF, respectively. Expression analysis revealed that 65 miRNA were differentially expressed in granulosa cells of SF compared with DF. Thirty miRNA including bta-miR-409a (involved in cell death by targeting genes BCL2l11, BIRC5, and PTEN) and bta-miR-335 (involved in cell proliferation, migration, and differentiation) are up-regulated in SF, whereas 35 miRNA including the miR-183 cluster (bta-mir-183, bta-miR-182, and bta-mir-96) involved in apoptosis inhibition are down-regulated in SF. The pathway analysis of potential target genes of differentially expressed miRNA is found to be involved in pathways, namely Wnt signalling, MAPK signalling, TGF-β signaling, and other pathways related to cell proliferation and apoptosis. In conclusion, the presence of stage-specific miRNA in granulosa cells support the potential role of miRNA in posttranscriptional regulation of genes during follicular development, mainly ovulation and follicular atresia.