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. 2024 Jan 30:15:1346260.
doi: 10.3389/fendo.2024.1346260. eCollection 2024.

Differential age-related transcriptomic analysis of ovarian granulosa cells in Kazakh horses

Wanlu Ren  1 , Jianwen Wang  1   2 , Yaqi Zeng  1 , Tongliang Wang  1 , Jun Meng  1   2 , Xinkui Yao  1   2
Affiliations

Differential age-related transcriptomic analysis of ovarian granulosa cells in Kazakh horses

Wanlu Ren et al. Front Endocrinol (Lausanne). .

Abstract

Introduction: The Kazakh horse, renowned for its excellence as a breed, exhibits distinctive reproductive traits characterized by early maturity and seasonal estrus. While normal reproductive function is crucial for ensuring the breeding and expansion of the Kazakh horse population, a noteworthy decline in reproductive capabilities is observed after reaching 14 years of age.

Methods: In this study, ovarian granulosa cells (GCs) were meticulously collected from Kazakh horses aged 1, 2, 7, and above 15 years old (excluding 15 years old) for whole transcriptome sequencing.

Results: The analysis identified and selected differentially expressed mRNAs, lncRNAs, miRNAs, and circRNAs for each age group, followed by a thorough examination through GO enrichment analysis. The study uncovered significant variations in the expression profiles of mRNAs, lncRNAs, miRNAs, and circRNAs within GCs at different stages of maturity. Notably, eca-miR-486-3p and miR-486-y exhibited the highest degree of connectivity. Subsequent GO, KEGG, PPI, and ceRNA network analyses elucidated that the differentially expressed target genes actively participate in signaling pathways associated with cell proliferation, apoptosis, and hormonal regulation. These pathways include but are not limited to the MAPK signaling pathway, Hippo signaling pathway, Wnt signaling pathway, Calcium signaling pathway, Aldosterone synthesis and secretion, Cellular senescence, and NF-kappa B signaling pathway-essentially encompassing signal transduction pathways crucial to reproductive processes.

Discussion: This research significantly contributes to unraveling the molecular mechanisms governing follicular development in Kazakh horses. It establishes and preliminarily validates a differential regulatory network involving lncRNA-miRNA-mRNA, intricately associated with processes such as cell proliferation, differentiation, and apoptosis and integral to the developmental intricacies of stromal follicles. The findings of this study provide a solid theoretical foundation for delving deeper into the realm of reproductive aging in Kazakh mares, presenting itself as a pivotal regulatory pathway in the context of horse ovarian development.

Keywords: PPI; ceRNA; horse; ovarian granulosa cell; whole transcriptome.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Schematic diagram of sample collection (All mares subjected to surgery for follicular fluid collection received a 14-day intravenous treatment. Daily disinfection and dressing changes were performed at the surgical site. Please refer to the attached document for information on the drugs used.).
Figure 2
Figure 2
Statistics of differentially expressed mRNAs in each comparison group. (A) mRNAs Venn diagram of differences between groups; (B) mRNAs statistical histogram of differences among groups.
Figure 3
Figure 3
LncRNA identification and analysis. (A) Venn diagram illustrating lncRNA coding potential; (B) Bar Chart displaying lncRNA types.
Figure 4
Figure 4
Statistics of differentially expressed LncRNAs in each comparison group. (A) LncRNAs Venn diagram of differences between groups; (B) LncRNAs statistical histogram of differences among groups.
Figure 5
Figure 5
Statistics of differentially expressed miRNAs in each comparison group. (A) miRNAs Venn diagram of differences between groups; (B) miRNAs statistical histogram of differences among groups.
Figure 6
Figure 6
Statistics of differentially expressed circRNAs in each comparison group. (A) circRNAs Venn diagram of differences between groups; (B) circRNAs statistical histogram of differences among groups.
Figure 7
Figure 7
Venn diagrams of: (A) the shared differentially expressed mRNAs in Group A vs Group D, Group B vs Group D, and Group C vs Group D; (B) the shared differentially expressed lncRNAs in Group A vs Group D, Group B vs Group D, and Group C vs Group D; (C) the shared differentially expressed miRNAs in Group A vs Group D, Group B vs Group D, and Group C vs Group D; (D) the shared differentially expressed circRNAs in Group A vs Group D, Group B vs Group D, and Group C vs Group D.
Figure 8
Figure 8
GO enrichment analysis of differentially expressed mRNAs. (A) Group A vs Group B; (B) Group A vs Group C; (C) Group A vs Group D; (D) Group B vs Group C; (E) Group B vs Group D; (F) Group C vs Group D.
Figure 9
Figure 9
KEGG enrichment analysis of differentially expressed mRNAs. (A) Group A vs Group B; (B) Group A vs Group C; (C) Group A vs Group D; (D) Group B vs Group C; (E) Group B vs Group D; (F) Group C vs Group D.
Figure 10
Figure 10
(A) Antisense GO enrichment analysis of differentially expressed lncRNAs target gene. (B) Antisense KEGG enrichment analysis of differentially expressed lncRNAs target gene. (C) CIS GO enrichment analysis of differentially expressed lncRNAs target gene. (D) CIS KEGG enrichment analysis of differentially expressed lncRNAs target gene. (E) Trans GO enrichment analysis of differentially expressed lncRNAs target gene (F) Trans KEGG enrichment analysis of differentially expressed lncRNAs target gene.
Figure 11
Figure 11
GO enrichment analysis of differentially expressed miRNAs target gene. (A) Group A vs Group B; (B) Group A vs Group C; (C) Group A vs Group D; (D) Group B vs Group C; (E) Group B vs Group D; (F) Group C vs Group D.
Figure 12
Figure 12
KEGG enrichment analysis of differentially expressed miRNAs target gene. (A) Group A vs Group B; (B) Group A vs Group C; (C) Group A vs Group D; (D) Group B vs Group C; (E) Group B vs Group D; (F) Group C vs Group D.
Figure 13
Figure 13
GO enrichment analysis of differentially expressed circRNAs target gene. (A) Group A vs Group B; (B) Group A vs Group C; (C) Group A vs Group D; (D) Group B vs Group C; (E) Group B vs Group D; (F) Group C vs Group D.
Figure 14
Figure 14
KEGG enrichment analysis of differentially expressed circRNAs target gene. (A) Group A vs Group B; (B) Group A vs Group C; (C) Group A vs Group D; (D) Group B vs Group C; (E) Group B vs Group D; (F) Group C vs Group D.
Figure 15
Figure 15
RT-qPCR verification of differently expressed mRNAs.
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References

    1. Fan H, He J, Bai Y, He Q, Zhang T, Zhang J, et al. . Baicalin improves the functions of granulosa cells and the ovary in aged mice through the mTOR signaling pathway. J Ovarian Res (2022) 15((1):34. doi: 10.1186/s13048-022-00965-7 - DOI - PMC - PubMed
    1. Ginther OJ, Beg MA, Donadeu FX, Bergfelt DR. Mechanism of follicle deviation in monovular farm species. Anim Reprod Sci (2003) 78(3-4):239–57. doi: 10.1016/S0378-4320(03)00093-9 - DOI - PubMed
    1. Matsuda F, Inoue N, Manabe N, Ohkura S. Follicular growth and atresia in mammalian ovaries: regulation by survival and death of granulosa cells. J Reprod Dev (2012) 58(1):44–50. doi: 10.1262/jrd.2011-012 - DOI - PubMed
    1. Li Q, Du X, Wang L, Shi K, Li Q. TGF-β1 controls porcine granulosa cell states: A miRNA-mRNA network view. THERIOGENOLOGY (2021) 160:50–60. doi: 10.1016/j.theriogenology.2020.11.001 - DOI - PubMed
    1. Zhang X, Yu T, Guo X, Zhang R, Lin P. Ufmylation regulates granulosa cell apoptosis via ER stress but not oxidative stress during goat follicular atresia. THERIOGENOLOGY (2021) 169(1):47–55. doi: 10.1016/j.theriogenology.2021.04.009 - DOI - PubMed

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