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Journal of Ovarian Research logoLink to Journal of Ovarian Research
. 2025 Dec 13;19:17. doi: 10.1186/s13048-025-01926-6

Screening and analysis of plasma small extracellular vesicle MiRNAs at various estrous cycle phases of goat

Shuaixiang Mao 1,#, Min Mao 1,#, Biwei Hou 1, Jinge Qiu 1, Yaokun Li 1, Baoli Sun 1, Yongqing Guo 1, Ming Deng 1, Dewu Liu 1,✉, Guangbin Liu 1,✉
PMCID: PMC12817739  PMID: 41390413

Abstract

Small extracellular vesicle are extracellular vesicles secreted by cells into the extracellular space. They contain proteins, lipids, and RNA, which are transferred to neighboring or distant cells through intercellular communication, thereby influencing the recipient cells. Plasma components at different stages of the estrous cycle can affect follicular development, oocyte maturation, and fertilization in animals. To investigate the role of plasma small extracellular vesicle miRNAs in physiological processes such as follicular development, oocyte maturation, and ovulation in goats, we conducted small RNA sequencing on plasma small extracellular vesicle derived from nine samples: three from the estrus phase, three from the post-estrus phase, and three from the interestrus phase, representing different stages of the estrous cycle. We identified 20 differentially expressed miRNAs in plasma small extracellular vesicle between the estrus and post-estrus phases, 11 between the post-estrus and interestrus phases, and 11 between the estrus and interestrus phases. The miRNAs specifically expressed at each estrous cycle stage may serve as biomarkers for diagnosis. GO and KEGG enrichment analyses of the predicted target genes of these miRNAs revealed that they are primarily enriched in pathways related to AMPK, MAPK, calcium signaling, cell adhesion, neurotrophic factors, estrogen signaling, and ovarian steroid synthesis. These findings provide insights into the impact of plasma small extracellular vesicles miRNAs at different stages of the estrous cycle on female animal reproduction.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13048-025-01926-6.

Introduction

Goats are important farm animals and have the widest geographical distribution among all types of livestock. They provide meat, milk, fur, and other products for human consumption, meeting people’s needs in daily life and production [1, 2]. Reproduction is a crucial aspect of goat farming, and studying the physiological changes that occur during the goat estrous cycle can help accurately determine estrous status. This understanding provides a scientific basis for timely artificial insemination and enhances reproductive efficiency [3]. By identifying differentially expressed miRNAs in goat plasma during various estrous phases, we can reveal potential factors influencing estrus from multiple perspectives. This, in turn, offers a theoretical foundation for further research on the estrous cycle in mammals. Blood plasma extracellular miRNA plays a role in various reproductive processes, such as follicle development, oocyte maturation, and embryo implantation, reflecting the organism’s physiological status. Nevertheless, research on the changes in blood plasma extracellular miRNA during different stages of the goat estrus cycle (estrus phase, post-estrus phase, and inter-estrus phase) is lacking. Studies in mammals such as humans, cattle, pigs, and mice have shown that, although extracellular vesicles in uterine or fallopian tube fluids exhibit species-specific differences in composition and function, they all undergo significant changes in protein and nucleic acid components during the estrous (or menstrual) cycle. Collectively, these vesicles are involved in regulating endometrial receptivity and embryonic development [4–8]. These findings reveal that extracellular vesicle-mediated intercellular communication is a conserved core mechanism in mammalian reproductive regulation. Employing high-throughput sequencing to explore extracellular miRNAs in blood plasma that affect the estrus cycle of dairy goats can enhance our understanding of the genetic factors influencing goat estrus. Small extracellular vesicle are double-layered extracellular vesicles formed by fusion between multivesicular bodies and the plasma membrane. They have diameters ranging 30–150 nm and appear as cups or discs when viewed under a transmission electron microscope (TEM) [9–11]. As intercellular communication carriers, small extracellular vesicle can release their contents, such as lipids, proteins, and nucleic acids, to recipient cells through endocytosis or internalization by membrane fusion [12]. The role of small extracellular vesicles miRNAs in cellular communication is divided into two: one is to negatively regulate and influence the expression level of target genes, and the other is to act as ligands that bind to toll-like receptors and activate immune cells [13]. Studies have shown that the miRNA profiles in exosomes differ from those in their parent cells, indicating that miRNAs are actively loaded into or sorted within these vesicles [14, 15]. Studies on human small extracellular vesicle miRNAs found that plasma small extracellular vesicles miRNA during pregnancy can be used as a marker for preeclampsia [16]. Small extracellular vesicle isolated from semen can influence sperm quality and antioxidant capacity [17], and those derived from placental derivatives can be utilized as biomarkers for pregnancy diagnosis [18]. The expression level of small extracellular vesicles miRNA changes under different physiological conditions. For example, the expression level of miR-21 in serum small extracellular vesicle is lower among healthy donors than among patients with glioblastoma [19, 20]. Although small extracellular vesicles miRNAs have been widely studied, research on small extracellular vesicles miRNAs in the estrous cycle of goats is relatively limited. During the estrous cycle of goats, a series of physiological changes take place in their body. The hypothalamus secretes GnRH, a key factor in regulating the estrous cycle, and receives signals from inside and outside the body. After a series of complex integrations, the hypothalamus acts on the pituitary gland to stimulate the secretion of follicle-stimulating hormone (FSH) and luteinizing hormone (LH) [21, 22]. The proteins, enzymes, and metabolites in plasma can cause changes in the levels of hormones such as gonadotropins, progesterone, and estrogen, thus significantly regulating the estrous cycle of female animals [23, 24]. These plasma components control hormone levels and influence follicular development, ovulation, and other related aspects. Therefore, understanding the mechanisms underlying this regulation can provide a theoretical basis for the reproductive management and health protection of animals. This study investigated the estrous cycle stages of Chuanzhong Black goats by measuring fluctuations in plasma levels of FSH and LH hormones. TEM and Western blotting were subsequently employed to successfully isolate plasma small extracellular vesicle. Following this, transcriptome technology was utilized to analyze the differential miRNAs in plasma small extracellular vesicle at various stages of the estrous cycle in goats. The objective was to examine the alterations in plasma small extracellular vesicles miRNAs throughout the different stages of the estrous cycle, thereby providing new insights and references for understanding the physiological changes that occur during the goat estrous cycle.

Materials and methods

Experimental animals and sample collection

Nine nanny goats of Chuanzhong black goats aged between 2 and 3 years old that were healthy and had lambed more than twice and two buck goats aged between 2 and 4 years old with normal libido and robust body condition were selected. The test animals were provided with free access to water and received regular feeding. Controlled Internal Drug Release (CIDR) devices combined with Prostaglandin (PG) were used to induce synchronized estrus in nine Chuanzhong black nanny goats. The buck goat test method was employed to detect whether the nanny goats were in estrus. The test nanny goats were examined for estrus daily from 6:00 to 7:00 in the morning and from 5:00 to 6:00 in the evening, with each test lasting 1 h. The time when the nanny goats accepted the buck goats’ mounting was recorded as the estrus period (0 h), 36 h after the mounting was recorded as the post-estrus period (36 h), and 12 d after mounting was recorded as the inter-estrus period (12 d). Observation of two consecutive estrus conditions revealed that the estrous cycle of the Chuanzhong black goats was generally 14–21 days. Blood was collected from the jugular vein of goats using EDTA blood collection tubes. Nine nanny goats in estrus, post-estrus, and diestrum were selected. Volume 15 mL of blood was collected from each goat and centrifuged at 1000 × g and 4 °C for 10 min to collect the plasma, which was then stored in liquid nitrogen for future use.

Determination of the plasma concentrations of FSH and LH

FSH and LH concentrations in the plasma of Chuanzhong black goats were measured using radioimmunoassay in the Northern Institute of Biotechnology, Beijing, China.

Small extracellular vesicles preparation

A 2 mL plasma sample was thawed on ice, transferred to a new sterile centrifuge tube, and centrifuged at 2,000 × g for 30 min. The supernatant was centrifuged at 10,000 × 4 g for 45 min and at 12,000×g and 4 °C for 30 min. The supernatant was collected and filtered using a 0.22 μm filter membrane to eliminate impurities larger than 200 nm. The filtrate was transferred to a sterile ultracentrifugation tube and centrifuged twice at 120,000×g and 4 °C for 70 min [25]. The supernatant was discarded, and the small extracellular vesicle were precipitated with 200 µL of 1× PBS for resuspension and stored in the refrigerator at − 80 °C for later use.

Morphology of small extracellular vesicle observed using TEM

In brief, 20 µL of small extracellular vesicle resuspension was incubated for 10 min on a copper mesh. After incubation, the residual liquid was absorbed with blotting paper. For small extracellular vesicle staining, the copper mesh was dropwise added with 2% uranyl acetate and incubated for 10 min at room temperature. After incubation, the residual liquid was absorbed with blotting paper and the sample was left to dry at room temperature for 10 h [26]. Finally, the small extracellular vesicle morphology was observed under a TEM.

Nanoparticle size analysis of small extracellular vesicle particle size and concentration

The sample pool of the particle size analyzer was thoroughly cleaned with purified water, and the baseline value was adjusted. Extrinsic body weight suspension was diluted from 10 µL to 30 µL. After the instrument performance test with standard products had qualified, the small extracellular vesicle sample was taken [27]. The particle size and concentration of small extracellular vesicle were determined after sample analysis.

Small extracellular vesicles protein quantification

In brief, 50 µL of small extracellular vesicle weight suspension and RIPA Ш lysate were mixed in a 1:1 ratio. The mixture was placed on ice for 10 min for lysis, vigorously shaken using a vortexer five times for 2 min each time, and then centrifuged at 13,000 rpm and 4 °C for 5 min. Finally, the supernatant was collected. Standard proteins were prepared using the BSA working solution following the manufacturer’s instructions [28]. The total protein concentration of small extracellular vesicle collected during estrus (n = 3), post-estrus (n = 3), and inter-estrus (n = 3) was determined using the BCA Protein Assay Kit.

Western blot analysis

Proteins were extracted from the isolated sEVs using RIPA lysis buffer supplemented with protease inhibitors, followed by centrifugation to remove insoluble debris. Total proteins extracted from small extracellular vesicle were added to the gel, the protein loading amount per well is 20 µg, separated by 10% polyacrylamide gel electrophoresis, and then transferred to a PVDF membrane. The protein blot was incubated overnight at 4 °C with primary antibodies (TSG101 and CD63), followed by incubation with HRP-labeled secondary antibodies at room temperature for 1 h [29]. ECL luminescent reagents were applied to the PVDF membranes, which were then exposed for imaging using an exposimeter.

Illumina Small-RNA sequencing and data analysis

Total RNA was isolated from the plasma small extracellular vesicle during estrus (n = 3), post-estrus (n = 3), and inter-estrus (n = 3) using QIAZOL Reagent. The concentration of RNA was measured using Nanodrop and Agilent 2100, its integrity was assessed with Agilent 2100, and its purity was evaluated through agarose gel electrophoresis and Agilent 2100. After passing quality control, the NEBNext® Multiplex Small RNA Sample Prep Kit for Illumina (NEB, USA) was utilized to construct the small RNA library. After preparation, the libraries were checked and then sequenced using Illumina SE50. The small RNAs were aligned with the miRBase, Rfam, and Repbase databases using Bowtie software [30]. The filtered data were subsequently aligned with the miRNAs to analyze their expression and distribution on the reference sequences. The criteria for sequencing miRNA expression levels were estimated per million transcripts based on the results after normalization [31]. The groups were identified for differential expression using DESeq2 in the R language, and differentially abundant genes were screened based on the criteria of fold change > 1.5 or < 0.667 with P < 0.05. Small RNA library construction and high-throughput sequencing were conducted by Novogene (Beijing, China).

Bioinformatics analysis

Target gene prediction for the differentially abundant miRNAs was performed by intersecting two software programs, miRanda and RNAhybrid, to establish the relationship between the miRNAs and their target genes. Functional enrichment analysis of differential abundant miRNAs was conducted using GO [32] and KEGG [33]. The network diagram was visualized with Cytoscape (v3.10.1) software.

Statistical analysis of data

The experimental data were preliminarily processed using Excel software, analyzed with one-way ANOVA in GraphPad Prism software (V9.0.0), and plotted. The results were expressed as mean ± standard deviation (mean ± SD). The t-test was used to determine significant difference between the two groups [34]. P < 0.05 was considered statistically significant.

Validation of MiRNA expression via RT-qPCR

Total RNA was isolated from estrous (n = 3), late estrous (n = 3), and inter-estrous (n = 3) plasma small extracellular vesicle using QIAZOL Reagent. MiRNA samples were reverse-transcribed using the poly(A) tailing method following the instructions for the miDETECTA TrackTM miRNA qRT-PCR Starter Kit. The overexpression efficiency of miRNA was validated using the stem-loop method for reverse transcription with U6 as a reference gene. Fluorescence quantification was then performed using a 20 µL volume in a real-time quantitative PCR system. The thermal cycling parameters were as follows: tap enzyme activation at 95 °C for 10 min, PCR template denaturation at 95 °C for 5 s, annealing at 60 °C for 20 s, and extension at 70 °C for 10 s for 40 cycles, followed by a final extension step at 72 °C for 3 min. Upstream primers for miRNAs were designed based on the miRbase sequences (downstream universal primers were provided by the kits), and primers for validating the relevant primer information were supplied by Guangzhou RIBO Biotechnology. The relative expression of the target genes was analyzed using the 2−∆∆Ct method.

Results

Detection of FSH and LH concentrations in plasma

The LH concentration in the plasma of goats at post-estrus was significantly higher than those at estrus and inter-estrus (P < 0.05). The difference in LH concentration between estrus and inter-estrus was not significant (P > 0.05). The pattern of FSH and LH changes was consistent with previous studies [35–37], indicating that the collected plasma samples reflect the characteristics of the estrous cycle in goats (Figs. 1A, B, Supplementary Table S1,Table S11).

Fig. 1.

Fig. 1

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Hormone secretion pattern during the estrous cycle. A Plasma LH and FSH concentrations during the estrous cycle. B In the figure, 0 h, 36 h, and 12 d represent the estrus period, post-estrus period, and diestrus period, respectively. “*” indicates significant difference (P < 0.05), and “ns” indicates no significant difference (P > 0.05). Data are presented as mean ± standard deviation (SD)

Identification of plasma small extracellular vesicle

First, the morphology of plasma small extracellular vesicle was observed using TEM. The plasma small extracellular vesicle appeared as saucer-like or disk-like double-layer membrane structure, which is consistent with the morphological characteristics of small extracellular vesicle observed by electron microscopy (Fig. 2A). In addition, the expression of small extracellular vesicle markers was detected by Western blot. The results indicated that the isolated plasma small extracellular vesicle were abundant in small extracellular vesicle markers CD63 and TSG101, confirming successful isolation from plasma for further studies (Fig. 2B).

Fig. 2.

Fig. 2

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Identification of small extracellular vesicle isolated from plasma after ultracentrifugation. A Transmission electron microscopy (TEM) images of plasma small extracellular vesicle and (B) Protein imprint of known small extracellular vesicles markers (TSG101 and CD63), “↑” indicates extracellular vesicles

Nanoparticle size tracking and analysis of particle size distribution

To investigate the characteristics of small extracellular vesicle in different estrous cycle stages, we utilized nanoparticle size tracking to analyze the particle size distribution of small extracellular vesicle. During the estrous (0 h), post-estrus (36 h), and inter-estrus (12 d) periods in goats, we observed that most of the extracellular vesicles (96%) had a size ranging from 30 nm to 200 nm. This value meets the requirements for the size range of extracellular vesicles. The average size and number of particles of plasma small extracellular vesicle were 95.28 ± 1.95 nm and 10.61 × 10^9 ± 1.43 particles/mL, respectively, in the 0 h group; 98.00 ± 4.64 nm and 16.13 × 10^9 ± 5.19 particles/mL, respectively, in the 36 h group; and 96.06 ± 4.66 nm and 11.26 × 10^9 ± 3.16 particles/mL, respectively, in the 12 d group (three biological replicates per group). In addition, the average number of plasma small extracellular vesicle in the 36 h group was higher than that in the 0 h and 12 d groups (Figs. 3A–D).

Fig. 3.

Fig. 3

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Nanoparticle tracking analysis of plasma small extracellular vesicle size distribution and average particle number at different estrous cycle stages. A Size distribution of plasma small extracellular vesicle during estrus, (B) post-estrus, and (C) diestrus. D Average particle number of small extracellular vesicle during estrus, post-estrus, and diestrus (n = 3)

Quality detection of MiRNA sequencing data

From the plasma extracellular vesicles of goats during estrus, post-estrus, and inter-estrus periods, nine miRNA libraries were generated. The average number of raw reads for the nine libraries was 13,348,952.44, and the average effective rate was 98.26%. Q20 and Q30 represent the percentage of qualified bases when the probability of detecting an erroneous base is 1% and 0.1%, respectively. In this study, the proportion of Q20 in all samples was higher than 98.5%, and that of Q30 was higher than 95% with an average proportion of 96.23%, surpassing 85%. This finding indicates that the sequencing data have high accuracy and good quality and can be used for subsequent analysis (Supplementary Table S2).

MiRNA analysis of plasma small extracellular vesicle in different estrous cycle stages

Differential abundance analysis of plasma extracellular vesicle miRNAs was conducted for the estrus (0 h), post-estrus (36 h), and inter-estrus (12 d) periods in goats. Volcano plot results revealed 20 differentially abundant miRNAs between the estrus (0 h) and post-estrus (36 h), with 14 miRNAs significantly upregulated and 6 miRNAs significantly downregulated. In addition, miR-215-5p, miR-192-5p, miR-122, and miR-107-3p exhibited extremely significant differences between the estrus and post-estrus periods (P < 0.01) (Fig. 4A). Between the post-estrus (36 h) and inter-estrus periods (12 d), 11 differentially abundant miRNAs were identified, including 4 significantly downregulated and 7 significantly upregulated miRNAs. Furthermore, miR-200c was significantly upregulated during the inter-estrus period (P < 0.01) (Fig. 4B). Eleven differentially abundant miRNAs were found between the estrus (0 h) and inter-estrus periods (12 d), with 7 miRNAs significantly upregulated and 4 miRNAs significantly downregulated. MiR-200c and miR-150 showed extremely significant differences between the estrus and post-estrus periods (P < 0.01) (Fig. 4C). These differentially abundant miRNAs at various estrous stages may play an important role in regulating the estrous cycle in goats (Supplementary Table S3).

Fig. 4.

Fig. 4

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Differential miRNA analysis of plasma small extracellular vesicle at different estrous cycle stages. A Volcano plot showing the differential abundance of miRNAs between estrus and post-estrus. B between post-estrus and diestrus, and (C) between estrus and diestrus

Target gene prediction of plasma small extracellular vesicles differential MiRNAs at different estrous cycle stages

The intersection of two software programs, miRanda and RNAhybrid, was utilized for predicting differential miRNA target genes to establish the correspondence between differentially abundant miRNAs and their target genes in plasma extracellular vesicles at various estrous cycle stages. Between the estrus (0 h) and post-estrus periods (36 h), the differentially abundant miRNAs were predicted to have 200 target genes, including AXL, TRIP13, FOXF2, FOXJ1, WDR1, and GRAMD1B (Fig. 5, Supplementary Table S4).

Fig. 5.

Fig. 5

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Construction of predicted target gene regulatory network for differentially abundant miRNAs between estrus and post-estrus

Between the post-estrus (36 h) and inter-estrus periods (12 d), the differentially abundant miRNAs were predicted to have 121 target genes, including PPARD, PCSK4, ADGRG1, SPESP1, and OSBPL7 (Supplementary Figure S1, Supplementary Table S4).

Between the estrus (0 h) and inter-estrus periods (12 d), the differentially abundant miRNAs were predicted to have 142 target genes, including FSHR, PPARD, FOXF2, PLAU, and SEC61A1 (Supplementary Figure S2, Supplementary Table S4).

Functional enrichment analysis of the target genes of plasma small extracellular vesicles differential mirnas at different estrous cycle stages

To comprehend the biological functions of differentially expressed plasma small extracellular vesicles miRNAs during various estrous cycle stages in goat ovarian development, we performed functional enrichment analysis on their predicted target genes. Gene ontology (GO) functional enrichment analysis was conducted on the target genes of 20 differentially abundant miRNAs during estrus and post-estrus periods. A total of 4083 GO terms were found to be enriched. In particular, 828 GO terms were significantly enriched (P < 0.05), including 689 terms related to biological processes, 35 terms related to cellular components, and 104 terms related to molecular functions. The genes of interest pertaining to biological processes primarily participated in reproductive processes, reproduction, metabolic process, biological regulation, biological adhesion, and positive regulation of biological processes. Those associated with molecular functional regulation were predominantly enriched in structural molecular activity, catalytic activity, transcriptional regulator activity, molecular functional regulator activity, and translation regulator activity. Finally, those related to cellular components were primarily enriched in protein-containing complexes and cellular anatomical entities (Figs. 6 A and B, Supplementary Table S5).

We also conducted KEGG enrichment analysis on the target genes of 20 differentially abundant miRNAs during estrus and post-estrus periods. The results revealed the enrichment of 207 KEGG pathways. Among them, 14 were significantly enriched (P<0.05), including pathways such as the “Sulfur relay system,” “Wnt signaling pathway,” “GABAergic synapse,” and “Insulin secretion” (Figs. 6C–D, Supplementary Table S6).

Fig. 6.

Fig. 6

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GO and KEGG analyses of the predicted target genes for differential abundant miRNAs between estrus and post-estrus. A GO annotation of genes in BP, CC, and MFs. B Bubble plot for the GO enrichment of differentially abundant miRNAs. C Circular plot for the KEGG pathway enrichment of differentially abundant miRNAs. D Bubble plot for the KEGG enrichment of differentially abundant miRNAs

GO functional enrichment analysis was performed on the target genes of 11 differentially abundance miRNAs during the post-estrus and diestrus periods, revealing an enrichment of 2784 GO terms. In particular, 473 GO terms were significantly enriched (P < 0.05), including 399 terms related to biological processes, 20 terms related to cellular components, and 54 terms related to molecular functions. In terms of biological processes, the genes were highly enriched in locomotion, reproductive process, reproduction, developmental process, and multicellular organismal process. In terms of molecular function, the genes showed significant enrichment in general transcription initiation factor activity, molecular carrier activity, molecular function regulator, and molecular adaptor activity. In terms of cellular component, the genes were predominantly enriched in cellular anatomical entity and protein-containing complex (Supplementary Figures S3A–B, Supplementary Table S7).

We also conducted KEGG enrichment analysis on the target genes of 11 differentially abundance miRNAs during the post-estrus and diestrus periods and discovered the enrichment of 154 KEGG pathways. Among them, 27 were significantly enriched (P < 0.05), including the “cGMP-PKG signaling pathway,” “GnRH signaling pathway,” “Oxytocin signaling pathway,” and “Fc gamma R-mediated phagocytosis” (Supplementary Figures S3C–D, Supplementary Table S8).

GO functional enrichment analysis was performed on the target genes of 11 differentially abundance miRNAs during the estrus and diestrus periods, revealing an enrichment of 2531 GO terms. In particular, 282 GO terms were significantly enriched (P < 0.05), including 176 terms related to biological processes, 46 terms related to cellular components, and 60 terms related to molecular functions. In terms of biological processes, the genes were highly enriched in the positive regulation of biological process, reproductive process, reproduction, metabolic process, and multicellular organismal process. In terms of molecular functions, the genes were highly enriched in molecular function regulator, transporter activity, structural molecule activity, and binding. In terms of cellular components, the genes were highly enriched in cellular anatomical entity and protein-containing complex (Supplementary Figures S4A–B, Supplementary Table S9).

We also conducted KEGG enrichment analysis on the target genes of 11 differentially abundance miRNAs during the estrus and diestrus periods, revealing the enrichment of 146 KEGG pathways. Among them, 7 were significantly enriched (P < 0.05), including pathways such as the “AMPK signaling pathway,” “Neomycin, kanamycin, and gentamicin biosynthesis,” “NF-kappa B signaling pathway,” and “Alcoholic liver disease” (Supplementary Figures S4C–D, Supplementary Table S10).

MiRNA expression verified by RT-qPCR

U6 was used as a reference gene to validate the accuracy of the sequencing results. We randomly selected six differentially abundant miRNAs, namely, chi-miR-150, chi-miR-122, chi-miR-342-3p, chi-miR-99a-5p, chi-miR-192-5p, and chi-miR-215-5p. Using RT-qPCR, we verified the expression of these differentially abundant miRNAs in plasma small extracellular vesicle during estrus, post-estrus, and diestrus (nine biological replicates per group). The quantitative PCR results were consistent with the trends observed in the sequencing data, thereby confirming the reliability of the sequencing results (Fig. 7).

Fig. 7.

Fig. 7

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Validation of small extracellular vesicles Differential miRNA Expression by RT-qPCR.TPM (Transcript per Kilobase per Million mapped reads), The expression levels of eight selected miRNAs (chi-miR-150, -194, -215-5p, -342-3p, -192-5p, -99a-5p, and -122) at three time points (0 h, 36 h, and 12 d) were measured by qPCR (left Y-axis, relative expression) and RNA-seq (right Y-axis, TPM values). Data are presented as mean values (n = 3 for both qPCR and RNA-seq) to illustrate expression trends. The parallel trends observed between the two methods confirm the reliability of the RNA-seq data. Note that statistical significance for differences between time points was not assessed, as this figure serves for methodological validation

Discussion

Small extracellular vesicles are lipid-coated vesicles abundant in plasma, with potential applications in drug delivery, inflammation regulation, and as biomarkers [38–40]. In this study, the particle concentrations of extracellular vesicles in goat plasma during the estrus, late estrus, and interestrus phases were 10.61 × 10^9 ± 1.42, 16.13 × 10^9 ± 5.19, and 11.26 × 10^9 ± 3.16 particles/mL, respectively. The average particle diameter and concentration of extracellular vesicles in late estrus plasma were higher than those in the estrus and interestrus phases, suggesting that hormones may regulate vesicle size distribution. Previous studies have shown that hormones can induce changes in the size distribution of fallopian tube extracellular vesicles at different stages of the mouse estrous cycle [41].

The period from estrus to post-estrus is a stage when ovarian follicles and oocytes in female animals rapidly develop and ovulate. The granulosa cells in the follicular fluid provide a stable internal environment for oocyte development. In this study, 20 differentially abundant miRNAs were identified in plasma-derived small extracellular vesicle during estrus and post-estrus in goats. Compared with estrus, post-estrus caused the upregulation of 14 miRNAs and the downregulation of 6 miRNAs. Among these differentially abundant miRNAs in plasma-derived small extracellular vesicle, miR-122, miR-192-5p, miR-342-3p, miR-29-3p, and miR-15a-5p [42–44] are related to reproduction in female animals. The miRNAs expressed only in post-estrus include miR-381, miR-30b-p, miR-48a-p, miR-196a, miR-504, and miR-767. This finding suggests that these post-estrus-specific miRNAs may serve as potential biomarkers for diagnosing estrus and post-estrus periods. In rat ovaries, miR-122 has been shown to regulate granulosa cell development [42]. Inhibiting miR-342-3p expression during oocyte maturation in vitro leads to an increased expression of Dnmt1 [45], thereby suppressing oocyte maturation. Research also suggested that miR-342-3p can regulate the proliferation, migration, and invasion of granulosa cells and may serve as a potential biomarker for embryo implantation [46, 47]. Its overexpression in human follicular fluid can inhibit granulosa cell proliferation through the PI3K-AKT-mTOR signaling pathway [48]. Therefore, the miRNAs carried by plasma-derived small extracellular vesicle, including miR-122, miR-342-3p, and miR-15a-5p, are associated with oocyte development in goats during estrus and post-estrus. Enrichment analysis of the target genes of differentially abundant miRNAs between estrus and post-estrus revealed that heparin-binding EGF-like growth factor (HBEGF), AXL and FOXJ1 were enriched in signaling pathways such as the GnRH signaling pathway, steroid hormone secretion, and ovarian development. HBEGF is released through the activation of matrix metalloproteinases. HBEGF activates EGF-R phosphorylation by stimulating Src and induces ERK-dependent transcription factors c-fos and c-jun in an ERK-dependent manner [49]. Activating the ERK pathway can promote the release of LH and FSH hormones, which may be associated with an increase in LH. AXL belongs to the TAM family of receptor tyrosine kinases, which comprises three structurally and functionally related receptors [50]. AXL deficiency in mice can impair the sex hormone-induced gonadotropin surge in GnRH neurons, leading to abnormal estrous cycles [51]. AXL receptors can also serve as novel regulators of GnRH receptor signaling transduction [52]. AXL is a target gene of miR-34a, indicating that miR-34a may regulate GnRH receptor signaling transduction by targeting AXL and thereby influence the estrous cycle in goats. FOXJ1 belongs to the Fox gene family and plays a complex and crucial role in development, organogenesis, immune system regulation, and malignant tumor progression [53]. The classical Yap/TEAD signal consists of transcription factors such as FOXJ1 and downstream genes including Jun, indicating its important role in the transcriptional regulation of gonadotropin-encoding genes [54]. novel_1 can target FOXJ1 to regulate the transcription of genes encoding gonadotropins.

The estrous cycle of female animals is influenced by steroid hormones, which are key regulatory factors in follicle development [55]. After ovulation, the residual follicle forms the corpus luteum and secretes progesterone, which gradually increases during the late estrus phase. In the absence of pregnancy, prostaglandins secreted by the uterus induce luteolysis, causing progesterone levels to decline and thereby initiating the development of new follicles [56]. In this study, 11 differentially expressed miRNAs were identified in small plasma extracellular vesicles of goats between the estrus and interestrus phases, with 7 miRNAs upregulated and 4 downregulated during interestrus. Notably, miR-181c-3p and miR-301b were exclusively expressed during interestrus, potentially serving as biomarkers to distinguish the two phases. Additionally, the differential expression of miR-130a-3p and miR-200c in these vesicles was associated with estrogen and progesterone synthesis. MiR-130a-3p overexpression in goat ovarian granulosa cells can inhibit the secretion of estradiol and progesterone by targeting PMEPA1 [57]. In this study, the miR-130a-3p in plasma small extracellular vesicle was significantly upregulated in the inter-estrus period, suggesting its relation to the secretion of estrogen and progesterone. MiR-200c expression is significantly higher in endometrial cancer cells than in normal endometrial cells. Estrogen increases the expression level of miR-200c by binding to the estrogen receptor and inhibiting PTENP1 and PTEN. This activation subsequently triggers the PI3K-AKT pathway, promoting the proliferation of endometrial cancer cells [58]. In this study, the miR-200c carried by plasma small extracellular vesicle was significantly upregulated, indicating its close correlation with estrogen secretion. Enrichment analysis of the target genes of differentially abundant miRNAs between the post-estrus and inter-estrus periods revealed the enrichment of SOHLH1 and GNA11 in oocyte development, reproductive processes, and GnRH signaling pathway. SOHLH1 is a crucial gene in oocyte differentiation, regardless of meiosis. It coordinates with SOHLH2 to regulate oocyte differentiation without affecting meiosis I [59]. SOHLH1 is an oocyte-specific transcription factor expressed in primordial and primary follicle stages, and its loss can affect follicle development by influencing primordial follicle assembly in the ovary [60, 61]. SOHLH1 is also a target gene of novel_110, indicating that novel_110 may regulate follicle development by targeting SOHLH1. Prior to luteinization, GNA11 is expressed in the anterior pituitary lobe and ovarian granulosa cells of female mice [62]. The downregulation of GNAQ mediated by CYP19 in granulosa cells reduces ovulation because the granulosa cell-luteinizing hormone receptor is activated by GNA11 following follicle rupture and ovulation [63]. GNA11 is a target gene of miR-145-5p, suggesting that miR-145-5p may regulate the luteinizing hormone receptor by targeting GNA11.

Follicular maturation progresses through five stages, from primordial to mature follicles, with the transition from the interestrus to estrus phase corresponding to the development of tertiary follicles into mature follicles. This process is primarily driven by interactions between oocytes and granulosa cells [64, 65]. In this study, we identified 11 differentially expressed miRNAs in the plasma exosomes of goats during the estrus and interestrus phases. Compared to estrus, the interestrus phase exhibited seven upregulated and four downregulated miRNAs. Five miRNAs, including miR-181c-3p and miR-449a-5p, were exclusively expressed during estrus and may serve as biomarkers to distinguish between the two stages. Furthermore, the differentially expressed miR-200c and miR-99a-5p are associated with follicular development. The dysfunction of granulosa cells in polycystic ovary syndrome is closely related to the formation of abnormal follicles. In females with polycystic ovary syndrome, the significantly upregulated miR-200c inhibits the proliferation of KGN cells by targeting PTEN [66]. MiR-99a is a regulatory factor in ovarian follicle development, including meiotic resumption [67], and can regulate the mechanism of cell survival in the seasonal changes of bovine ovaries through small extracellular vesicle [68]. Enrichment analysis of the target genes of differentially abundant miRNAs between the estrous and post-estrus periods revealed the enrichment of adiponectin receptor 2 (ADIPOR2) in the AMPK signaling pathway. ADIPOR2 is widely distributed in reproductive organs and central nervous system tissues [69] and affects the reproductive system through its central effects on the hypothalamic–pituitary–gonadal axis and by influencing oxytocin secretion [70, 71]. ADIPOR2 is a target gene of miR-150, indicating that miR-150 may regulate follicular development by targeting ADIPOR2, thereby influencing oxytocin and GnRH production in the hypothalamus.

Conclusions

This study first identified the characteristics of plasma small extracellular vesicle and then analyzed the differential abundance of miRNAs at various estrous cycle stages using small RNA-seq. Results revealed 20, 11, and 11 differentially abundant miRNAs in plasma small extracellular vesicle between the estrous and post-estrus periods, between the post-estrus and inter-estrus periods, and between the estrous and inter-estrus periods, respectively. Further analysis of the predicted target genes of these miRNAs showed enrichment in signaling pathways such as AMPK, MAPK, calcium, cell adhesion, neurotrophic factors, estrogen, and ovarian steroid synthesis, indicating their potential involvement in follicular development, granulosa cell proliferation, and oocyte maturation. These findings can help clarify the impact of plasma small extracellular vesicle miRNAs on ovarian function and reproduction during different estrous cycle stages.

Supplementary Information

Supplementary Material 1. (12.2MB, zip)

Acknowledgments

Institutional review board statement

The animal studies were approved by Ethics Committees of the Laboratory Animal Center of South China Agricultural University (permit number: SYXK-2018-0123). The studies were conducted in accordance with the local legislation and institutional requirements. Written informed consent was obtained from the owners for the participation of their animals in this study.

Authors’ contributions

Conceptualization, S.M. and M.M.; methodology, S.M., B.H., J.Q.; software, Y.G.; validation, Y.L., B.S. and M.D.; formal analysis, D.L.; investigation, G.L.; resources, G.L.; writing—original draft preparation, B.H.; writing—review and editing, S.M.; visualization, M.M.; supervision, G.L.; project administration, D.L.; funding acquisition, G.L. and D.L. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by Science and Technology Program from Forestry Administration of Guangdong Province (2023KJCX004); The project of the Department of Agriculture and Rural Affairs of Guangdong Province (2024-XPY-00-008).

Data availability

The datasets supporting the conclusions of this article are included within the article and its additional files.

Declarations

Competing interests

The authors declare no competing interests.

Footnotes

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Shuaixiang Mao and Min Mao contributed equally to this work.

Contributor Information

Dewu Liu, Email: dwliu@scau.edu.cn.

Guangbin Liu, Email: gbliu@scau.edu.cn.

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Supplementary Materials

Supplementary Material 1. (12.2MB, zip)

Data Availability Statement

The datasets supporting the conclusions of this article are included within the article and its additional files.

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