Dynamic microRNA expression profiles in goat ovarian tissues before and after pregnancy

This study performed transcriptome sequencing of ovarian tissues from JG goats at three key reproductive stages-non-pregnant (8 mo old, M8), pregnant (10 mo old, M10), and postpartum (12 mo old, M12). A total of 93 differentially expressed (DE) miRNAs were identified across all libraries, with the M8 vs. M10 group having the largest number (34 upregulated and 47 downregulated; |log₂ fold change| > 1, FDR < 0.05). These stage-specific DE miRNAs were clustered into four groups, with their target genes primarily enriched in signaling pathways such as Wnt, JAK-STAT, PI3K-Akt, VEGF, and steroid biosynthesis, which are important factors influencing ovarian cell activity, hormone secretion, angiogenesis, and embryonic development. Real-time quantitative polymerase chain reaction verification showed that the expression patterns of the 9 selected DE miRNAs were consistent with the sequencing data. Additionally, through the joint analysis of DE miRNAs and mRNAs, a co-expression network associated with ovarian reproductive function changes was constructed, ultimately highlighting 11 key miRNAs. Dual-luciferase reporter assays further confirmed the direct targeting relationships between core miR-432-5p and CPT1B, as well as miR-455-3p and PLXNB1. In summary, this study revealed the dynamic changes in ovarian miRNA expression profiles from pre-pregnancy to postpartum and their potential molecular mechanisms, providing theoretical support and key molecular targets for miRNAs in reproductive regulation, with significant implications for improving reproductive efficiency in livestock.

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Publication Details

Journal
Journal of Animal Science
Published
2025-01-01
DOI
https://doi.org/10.1093/jas/skaf187
Primary Topic
MicroRNA in disease regulation
Type
article
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article

Dynamic microRNA expression profiles in goat ovarian tissues before and after pregnancy

Jiaqing Hu, J. S. Liang, Ying Wei, Tianle Chao et al.
Journal of Animal Science
MicroRNA in disease regulation
article

Dynamic microRNA expression profiles in goat ovarian tissues before and after pregnancy

Jiaqing Hu, J. S. Liang, Ying Wei, Tianle Chao, Jianmin Wang, Lu Zhang, Yanyan Wang, Qing Li, Peipei He
article en

Abstract

This study performed transcriptome sequencing of ovarian tissues from JG goats at three key reproductive stages-non-pregnant (8 mo old, M8), pregnant (10 mo old, M10), and postpartum (12 mo old, M12). A total of 93 differentially expressed (DE) miRNAs were identified across all libraries, with the M8 vs. M10 group having the largest number (34 upregulated and 47 downregulated; |log₂ fold change| > 1, FDR < 0.05). These stage-specific DE miRNAs were clustered into four groups, with their target genes primarily enriched in signaling pathways such as Wnt, JAK-STAT, PI3K-Akt, VEGF, and steroid biosynthesis, which are important factors influencing ovarian cell activity, hormone secretion, angiogenesis, and embryonic development. Real-time quantitative polymerase chain reaction verification showed that the expression patterns of the 9 selected DE miRNAs were consistent with the sequencing data. Additionally, through the joint analysis of DE miRNAs and mRNAs, a co-expression network associated with ovarian reproductive function changes was constructed, ultimately highlighting 11 key miRNAs. Dual-luciferase reporter assays further confirmed the direct targeting relationships between core miR-432-5p and CPT1B, as well as miR-455-3p and PLXNB1. In summary, this study revealed the dynamic changes in ovarian miRNA expression profiles from pre-pregnancy to postpartum and their potential molecular mechanisms, providing theoretical support and key molecular targets for miRNAs in reproductive regulation, with significant implications for improving reproductive efficiency in livestock.

Journal of Animal ScienceVol. 103
Ministry of Agriculture and Rural Affairs (CN), Shandong Agricultural University (CN)
Good health and well-being
Openalex Percentile: Top 78%
MicroRNA in disease regulation
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