Skip to main content
Download PDF

Identification of functional circRNAs regulating ovarian follicle development in goats

BMC Genomics volume 25, Article number: 893 (2024) Cite this article

Abstract

Barkground

Circular RNAs (circRNAs) play important regulatory roles in a variety of biological processes in mammals. Multiple birth-traits in goats are affected by several factors, but the expression and function of circRNAs in follicular development of goats are not clear. In this study, we aimed to investigate the possible regulatory mechanisms of circRNA and collected five groups of large follicles (Follicle diameter > 6 mm) and small follicles (1 mm < Follicle diameter < 3 mm) from Leizhou goats in estrus for RNA sequencing.

Results

RNA sequencing showed that 152 circRNAs were differentially expressed in small and large follicles. Among them, 101 circRNAs were up-regulated in large follicles and 51 circRNAs were up-regulated in small follicles. GO and KEGG enrichment analyses showed that parental genes of the differential circRNAs were significantly enriched in important pathways, such as ovarian steroidogenesis, GnRH signaling pathway, animal autophagy and oxytocin signalling pathway. BioSignal analysis revealed that 152 differentially expressed circRNAs could target 91 differential miRNAs including miR-101 family (chi-miR-101-3p, chi-miR-101-5p), miR-202 family (chi-miR-202-5p, chi-miR-202-3p),60 circRNAs with translation potential. Based on the predicted sequencing results, the ceRNA networks chicirc_008762/chi-miR-338-3p/ARHGAP18 and chicirc_040444/chi-miR-338-3p/STAR were constructed in this study. Importantly, the new gene circCFAP20DC was first discovered in goats. The EDU assay and flow cytometry results indicated that circCFAP20DC enhanced the proliferation of follicular granulosa cells(GCs). Real-time quantitative PCR and western blotting assays showed that circCFAP20DC activated the Retinoblastoma(RB) pathway and promoted the progression of granulosa cells from G1 to S phase.

Conclusion

Differential circRNAs in goat size follicles may have important biological functions for follicular development. The novel gene circCFAP20DC activates the RB pathway, promoting the progression of GCs from G1 to S phase. This, in turn, enhances the proliferation of follicular GCs in goats.

Peer Review reports

Background

Goat meat has excellent characteristics of high protein, low fat and low cholesterol, which is in line with modern people’s healthy consumption concept. It occupies an increasing market share in meat, so goat farming has gradually developed into an important aspect of the livestock industry. The litter size is a crucial factor in determining the scale of goat farming and significantly constrains its development. This trait is influenced by a combination of environmental, nutritional, and genetic factors, with genetic factors playing a particularly decisive role [1,2,3,4,5]. The follicle, serving as the fundamental functional unit of the ovary, is intricately linked to litter size, and its capacity to produce a large number of oocytes is pivotal for the generation of multiple births [6]. The ovarian follicle, serving as the fundamental functional unit of the ovary, plays a crucial role in determining litter size. Studies have indicated that only a minuscule fraction, less than 1%, of follicles within mammalian ovaries successfully undergo ovulation, with the remaining 99% undergoing atresia [7]. During an estrous cycle, rodents and pigs can ovulate up to several dozen eggs, while goats typically ovulate between one and three [8, 9]. Therefore, the production of a substantial number of oocytes is vital for the potential of multiple births. Furthermore, ovulation is contingent upon the development of a follicle from its primary stage to full maturity [10]. Consequently, the generation of a substantial number of dominant follicles is pivotal for facilitating multiple births and enhancing swift reproductive rates in goats.

Circular RNAs are a class of circular closed structures without a 5’ end cap and a 3’ end ployA tail, which are derived from linear mRNA reverse shear and are commonly expressed in eukaryotes and were first identified in plant-like viruses in 1976 [11,12,13,14]. It is because of the closed-loop structure that circular RNA exhibits greater stability than linear RNA and is less susceptible to degradation. With the development of high-throughput sequencing and biotechnology, more and more studies have found that cyclic RNA plays an important role in mammalian reproduction. Guo found that circINHA binds to miR-10a-5p and acts as a ceRNA to promote proliferation and inhibit apoptosis of porcine GCs [15], Wang found that circSLC41A1 enhanced SRSF1 expression through competitive binding to miR-9820-5p, thereby inhibiting GCs apoptosis and follicular atresia in pig [16]. However, little is known about the role of circular RNA in the regulation of follicle development in goats, and exploring the mystery will certainly provide new insights into the improvement of reproductive performance in goats, which deserves further study.

The Leizhou black goat is a superior breed of meat goat native to the Leizhou Peninsula in Guangdong Province, China. These goats typically give birth to two litters annually, with each litter averaging two offspring. The average weight for adult males is 40 kg, while for adult females it is 30 kg. Additionally, the Leizhou goat is noted for its resistance to high temperatures and humidity, early sexual maturity, and the superior quality of its meat and hide. This breed boasts a breeding legacy of over 1200 years in China and is recognized as a key goat breed supporting the rural revitalization strategy in the northwest regions of Guangdong and Hainan [17]. However, as a result of prolonged absence of scientific breeding practices and proper feeding management techniques, the exceptional traits of this breed have deteriorated, leading to a decrease in the scale of breeding. To achieve a rapid and high-quality expansion of Leizhou goats, it is crucial to investigate their remarkable ability to produce multiple births. In order to reveal the molecular mechanism of multiple births in Leizhou goats, we compared the expression levels of circRNAs in large and small follicles of Leizhou goats for the first time and further mined functional circRNAs. These analyses not only set the theoretical groundwork for comprehending the molecular mechanisms underlying follicular development in goats but also generated fundamental data for the preservation of indigenous breed resources and the identification of candidate genes associated with goat fertil.

Methods

Sample collection

Five empty pregnant healthy Leizhou goats from Guangdong Experimental Goat Farm were selected as test animals, all of which were 2 years old and had three lactations, and were euthanized within 24 h after estrus identification. The procedure involves first intravenously injecting sumianxin at a dosage of 0.1 g/kg, followed by intravenous injection of Potassium Chloride at a dosage of 10 mg per animal, until the goats are completely deceased. Ovaries were collected from each goat immediately after euthanasia, and large follicles (follicle diameter > 6 mm) and small follicles (1 mm < follicle diameter < 3 mm) were isolated. Each goat contributed one large follicle (15 A, 16 A, 17 A, 19 A, 20 A) to the large follicle group and 2–3 small follicles (15 H, 16 H, 17 H, 19 H, 20 H) to the small follicle group, with five biological replicates for each group.

cDNA library preparation

RNA was extracted from small and large follicles of goat ovaries by adding TRIzol (Invitrogen, USA) to a freeze mill, its purity and integrity were determined by Nanophotometer® Spectrophotometer (IMPLEN, USA) and 1% agarose electrophoresis, respectively. Each sample was enriched with 3 µg of RNA as starting material, rRNA was removed with the rRNA removal kit (Illumina, USA). The RNA was broken to 200–300 bp fragments by ion interruption. The first strand of cDNA is synthesized by random primers and reverse transcriptase (Invitrogen, USA). DNA polymerase and RNase H (NEB, USA) are used to synthesize the second strand cDNA and dTTP is replaced by dUTP to greatly improve the accuracy of the results. Following library construction, PCR amplification was employed for library fragment enrichment, and libraries were selected based on fragment size (ranging from 300 to 400 bp). Subsequently, the library quality was evaluated using an Agilent 2100 Bioanalyzer, and fluorescence quantification was conducted to determine the total library concentration and effective library concentration. Finally, these libraries underwent Next-Generation Sequencing (NGS) using the Illumina HiSeq sequencing platform with Paired-end (PE) sequencing.

circRNA identification and differential analysis

To identify circRNAs using find_circ, the 5’ end and 3’ end of unmatched reference genome reads (referred to as 5’ Anchor and 3’ Anchor, respectively) are realigned to the reference genome based on Bowtie2 matching. If these sequences align at opposite positions, it suggests the presence of a circRNA. A circRNA is considered when the Anchor sequences can precisely map the reference genome up to the junction and exhibit a shearing pattern consistent with AG-GT at the junction site. The expression levels of circRNAs were normalized using TPM (transcripts per kilobase million mapped). Differential expression analysis of circRNAs was conducted using DESeq, with criteria for identifying differentially expressed genes set as an expression fold difference |log2FoldChange| > 1 and a significant P-value < 0.05.

ceRNA network prediction

Prediction of miRNA target genes using miRanda on newly identified circRNAs for miRNA target gene prediction. Thirteen out of the top 20 significantly differentiated circRNAs could be matched to differential miRNAs with opposite expression trends, further combining with previous mRNA sequencing data to construct a possible circRNA-miRNA-mRNA ceRNA regulatory network.

circRNA source gene enrichment analysis

GO functional enrichment analysis firstly mapped all circRNA source genes to each term of the gene ontology database, calculates the number of differential circRNA source genes in each term, and used the whole genome as the background to calculate the term with significant enrichment of differential circRNA source genes using the hypergeometric distribution. The KEGG enrichment analysis first counted the number of differentially expressed circRNA source genes at different levels of each KEGG pathway, then identified the metabolic pathways and signaling pathways in which differentially expressed circRNA source genes were mainly involved. Next, the pathways with significant enrichment of differentially expressed circRNA source genes were calculated using hypergeometric distribution in the context of the whole genome.

Prediction of circRNA translation potential

The presence or absence of ORF was detected using the open reading frame finder (ORF finder; http://www.bioinformatics.org/sms2/orf_find.html) [18] and CPAT (coding potential assessment tool; http://rna-cpat.sourceforge.net/) [19]. The presence of m6A modification sites was detected using the sequence-based RNA adenosine methylation site predictor (SRAMP; http://www.cuilab.cn/sramp/) [20]. The presence of IRES was predicted using the internal ribosome entry site finder (IRES finder; https://github.com/xiaofengsong/IRESfinder) [21].

PCR, DNA sequencing, real-time qPCR validation

RNA was extracted from goat ovary using TRIzol reagent (TaKaRa, Japan) and then cDNA was synthesized using PrimeScript™ RT reagent Kit (TaKaRa, Japan), reaction system: 5×PrimeScript Buffer 2 µL, PrimeScript RT Enzyme Mix I 0.5 µl, Oligo dT Primer (50 µM) 0.5 µl, Random 6 mers (100 µM) 0.5 µl, Total RNA 1 µl, RNase Free dH2O 5.5 µl, reaction conditions: 37℃ for 15 min, 85℃ for 5 s. Then the PCR reaction was carried out with specific primers, amplification system: 2×Pro Taq Master Mix 12.5 µl, cDNA 1 µl, upstream primer 0.5 µl, downstream primer 0.5 µl, amplification conditions: 95 ℃ for 3 min, 95 ℃ for 30 s, 60 ℃ for 30 s, 72 ℃ for 30 s, 34 cycles, 72 ℃ for 5 min, and 4 ℃ storage. Finally, the circular characterization of circRNA was performed by 1% agarose gel electrophoresis and Sanger sequencing.

The qPCR was performed with Tap Pro Universal SYBR qPCR Master Mix kit (Vazyme, China) and the amplification program was as follows: 95 ℃ 30s, 95 ℃ 10 s, 60 ℃ 30 s,95 ℃ 15 s, 60 ℃ 60 s, 95 ℃ 15 s. Amplification system: 2×Tap Pro Universal SYBR qPCR Master Mix 10 µl, upstream primer 0.4 µl, downstream primer 0.4 µl, cDNA 1 µl, ddH2O 8.2 µl. GAPDH was used as the internal reference gene, and the expression between samples was compared by 2−ΔΔCt. The primers used in this study are shown in Supplementary Table S1.

TA clone

The full-length sequence of circCFAP20DC was amplified according to the high-fidelity enzyme kit PrimeSTAR® Max DNA Polymerase (Takara, China). The target fragments were recovered using FastPure Gel DNA Extraction Mini Kit (Vazyme, China) after tailing the amplified products with ploy A using Taq DNA polymerase (Accurate Bioiogy, China). The pMD 19-T Vector was ligated to the full-length sequence of circCFAP20DC according to the instructions of pMD™ 19-T Vector Cloning Kit (Takara, China), transformed, coated, and sent to the company for sequencing after picking out single clones.

RNase R treatment

Total RNA was extracted from goat ovarian granulosa cells using TRlzol (Takara, China) according to the manufacturer’s instructions. Total RNA was digested with GSPure® RNase R Kit (Geneseed, China) and mRNA and circRNA were synthesized with Evo M-MLV RT Reaction Mix Ver.2 Kit (Accurate Bioiogy, China), and analyzed by real-time polymerase chain reaction using Taq Pro Universal SYBR qPCR Master Mix (Vazyme, China).

Vector construction and lentiviral packaging

The lentiviral vector was selected as the backbone, and the full-length sequence of circCFAP20DC was homologously recombined into pLC5-ciR (Geneseed, China) using the Hieff Clone® Plus One Step Cloning Kit (Yeasen, China), and named as pLC5-circCFAP20DC. Isolated goat granulosa cells were cultured in medium containing 90% DMEM/F12, 10% FBS,1% PS. The viral supernatants were obtained at 48 h and 72 h by co-transfecting pLC5-circCFAP20DC, psPAX2, pMD2.G into 293T cells with Lipofectamine 3000 reagent (Thermo Fisher Scientific, USA). Subsequently, the virus was concentrated using the Universal Virus Concentration Kit (Beyotime, China) and stored in a -80 °C refrigerator as a powerful tool for subsequent transduction of goat granulosa cells. In the cellular experiments, the circCFAP20DC group was the circCFAP20DC overexpression group and the NC group was the control group. Each group was three biological replicates.

Nucleoplasmic isolation

1 × 107 goat ovarian granulosa cells were collected, and nuclear and cytoplasmic RNA were extracted according to the instructions of FastPure Cytoplasmic & Nuclear RNA purification Kit (ECOTOP, China). The extracted RNA was reverse transcribed into cDNA using Evo M-MLV RT Reaction Mix Ver.2 (Accurate Bioiogy, China) kit, and then subjected to real-time fluorescence quantitative PCR using Taq Pro Universal SYBR qPCR Master Mix (Vazyme, China) to detect the subcellular localization of circCFAP20DC.

EdU cell proliferation

The logarithmic growth phase cells were taken and inoculated in 96-well plates at 4 × 104 cells, and lentivirus infection was performed on the next day. After 72 h, 100µM EDU solution was added and incubated for 2 h, and then cell proliferation assay was carried out according to the instructions of Cell-LightTM EDU Apollo In Vitro Kit (RIBOBIO, China).

Cell cycle assays

Goat granulocytes were plated in 6-well plates and were subjected to lentiviral infection once they reached 50% confluence. At 72 h post-infection, the cells were processed following the guidelines of the Cell Cycle Assay Kit (Red Fluorescence) (Elabscience, China).After overnight incubation, the assay was performed on the machine and the red fluorescence at the excitation wavelength of 488 nm was recorded.

Western blot

Goat granulosa cells were spread in 6-well plates, and lentivirus infection was performed when the cells grew to 50%, and protein was extracted at 72 h. Firstly, the 6-well plate was placed on ice, washed with PBS, 200 µl RIPA Lysis Buffer (Beyotime, China) was added to each well, lysed on ice for 5 min, centrifuged at 4℃ for 10 min, and the supernatant was aspirated and added to 5×SDS-PAGE loading buffer (Solarbio, China) and boiled at 100℃ for 10 min. The protein was separated by 10% Acr-Bis SDS-PAGE and transferred to polyvinylidene difluoride membrane (Merck, German), incubated with the corresponding primary antibody overnight (The PVDF membranes containing the target protein were cut into strips and then incubated with the primary antibody, using protein marks as a reference standard) and then added with the corresponding secondary antibody for 1 h. The protein bands were detected by chemiluminescent substrate.

Statistical analysis

Two sample groups or multiple sample groups were analyzed by t-test and one-way anove, respectively, with three biological replicates set up for all experimental subgroups, and all data were presented in the form of mean ± standard deviation and analyzed and plotted using GraphPad Prism (version 9.0). The significance thresholds for differences were P < 0.05 for *, P < 0.01 for ** and P < 0.001 for ***.

Results

Sequencing analysis of circRNA in large and small follicles

The sequencing data demonstrated that the Q20 values for both the large follicle group and the small follicle group exceeded 95%, while the Q30 values were above 90% (Supplementary Table S2). Moreover, the alignment of anchor sequences for circRNA detection to the goat genome surpassed 80% (Supplementary Table S3), suggesting a relatively high accuracy of the sequencing data in this study. A total of 10,070 circRNAs were identified in this investigation, displaying a length distribution ranging from 200 nt to 100,000 nt, predominantly clustering around 500 nt (Fig. 1A). The taxonomic annotation of circRNAs revealed that circRNAs were mainly composed of exon (Fig. 1C). Furthermore, the expression levels of circRNAs were generally low (Fig. 1D), with chromosome pairs 1, 3, 10, and 11 being the main producers of circRNAs among the 30 chromosome pairs in goats (Fig. 1B).

Fig. 1
figure 1

Identification of follicular circRNAs in goats. A, Length distribution of circRNAs. B, Chromosomal distribution of circRNAs. C, Types of reverse splicing of circRNAs. D, Distribution of circRNAs expression

Full size image

Differential expression analysis of circRNA in large and small follicles

Differential analysis of circRNA expression was conducted using DEseq. A total of 152 differentially expressed circRNAs were identified, with 101 being down-regulated and 51 up-regulated in small follicles compared to large follicles (Fig. 2A) (Supplementary Table S4). Cluster analysis was used to draw heat maps to determine the differential expression pattern of circRNAs under different experimental conditions (Fig. 2B), and it can be seen that the quality of the sequencing data is reliable.

Fig. 2
figure 2

Differential expression of circRNA in small and large follicles. A, Volcano map of differentially expressed circRNAs. B, Clustering map of differentially expressed circRNAs

Full size image

Enrichment analysis of circRNA parental genes

GO and KEGG enrichment analysis was performed on the genes of origin of the differential circRNAs (Supplementary Table S5), thus demonstrating the possible differential gene functions of the samples. GO analysis revealed significant enrichment of 272 terms (P < 0.05) across Biological Process, Cellular Component, and Molecular Function (Supplementary Table S6). The top ten terms in each section are depicted in Fig. 3B. Notably, terms such as regulation of TOR signaling (GO:0032006), regulation of RNA splicing (GO:0043484), TOR signaling (GO:0031929), and reproductive behavior (GO:0019098) were identified as potentially closely associated with follicle development. Furthermore, biological processes represented 65% of the top 20 pathways that were significantly enriched in the GO analysis, suggesting a potential indication that differential circRNAs could serve crucial biological functions. (Fig. 3A). KEGG results showed that a total of 173 pathways were involved (Supplementary Table S7), with 28 terms significantly enriched (P < 0.05), mainly in Human Diseases, Metabolism, and Organismal Systems (Fig. 3D). Among the top 20 pathways significantly enriched in KEGG (Fig. 3C), Autophagy-animal (chx04140), Oxytocin signaling pathway (chx04921), Ovarian steroidogenesis (chx04913), AMPK signaling pathway (chx04152), GnRH signaling pathway (chx04912) may play important roles in follicular development.

Fig. 3
figure 3

Functional enrichment analysis of parental genes for circRNAs. A, GO enrichment analysis of the first 20 pathways. B, The first ten pathways of biological processes, cellular components and molecular functions in GO enrichment analysis. C. Top 20 terms for KEGG enrichment analysis. D. Bar graph of significantly enriched pathways in KEGG analysis

Full size image

Analysis of circRNA-miRNA-mRNA network interactions

Circular RNAs (circRNAs) have the capability to sequester miRNAs, thereby inhibiting miRNA function, which in turn leads to the facilitation of mRNA expression. Consequently, the prediction of miRNA target genes for newly identified circRNAs can facilitate a more in-depth exploration of circRNA function. In this study, the miRanda software was employed to predict circRNA target genes. The results unveiled reciprocal targeting relationships between 10,059 circRNAs and 436 miRNAs (Supplementary Table S8), with 152 significantly different circRNAs found to target 91 significantly different miRNAs. The interaction regulatory networks of 13 selected circRNAs are illustrated in Fig. 4A. Additionally, potential competing endogenous RNA (ceRNA) regulatory networks, such as chicirc_008762-chi-miR-338-3p-ARHGAP18, chicirc_040444-chi-miR-338-3p-STAR, and chicirc_013056-chi-miR-29c-3p-JAK3, were identified through screening (Supplementary Table S9).

Prediction of the translational function of circRNAs

There are two primary translation mechanisms for circular RNAs containing open reading frames: one relies on the presence of internal ribosomal entry sites (IRES), while the other is dependent on the presence of N6-methyladenosine residues (m6A). In this study, a total of 82 differentially expressed circRNAs were initially predicted to harbor open reading frames using the Open Reading Frame Finder (ORF finder). Subsequently, these circRNAs underwent further prediction through the Coding Potential Assessment Tool (CPAT) and the intersecting analysis led to the identification of 56 circRNAs with open reading frames (Supplementary Table S10). The results from IRES finder prediction indicated that 28 circRNAs relied on IRES (Internal Ribosome Entry Sites), among which 8 circRNAs, such as chicirc_038635 and chicirc_001861 (Score > 0.7), were identified as potential candidates for subsequent research focus (Supplementary Table S11). Moreover, the Sequence-based RNA Adenosine Methylation Site Predictor predicted 32 circRNAs that depend on the presence of N6-methyladenosine (m6A) residues (with very high confidence as a criterion), including 8 circRNAs like chicirc_03451 and chicirc_0164391 (Score > 0.7) that could be prioritized for further investigation (Supplementary Table S12). By considering the intersection of these two translation mechanisms, the analysis revealed a total of 15 circRNAs that may potentially utilize both translation mechanisms (Fig. 4B).

QPCR validation of circRNAs

To validate the reliability of the circRNAs data obtained from RNA-seq, three differentially expressed circRNAs were randomly chosen, and their relative expression in small and large follicles was confirmed using quantitative real-time polymerase chain reaction (qPCR). The qPCR results demonstrated a high level of agreement with the RNA-seq sequencing data (Fig. 4C).

Fig. 4
figure 4

Prediction and quantitative validation of circRNAs function. A, CeRNA network construction. Orange is circRNA, cyan is miRNA, blue is mRNA; arrows facing down are downregulated in small follicles, arrows facing up are upregulated in small follicles. B, Prediction of circRNA translation potential. IRES is dependent on the presence of an internal ribosome entry site to initiate translation, and m6A is dependent on the presence of N6-methyladenosine residues to initiate translation. C, QPCR validation of differential expression of circRNAs in sequencing data

Full size image

Identification and functional validation of circCFAP20DC involved in follicular development

The chicirc_040444 with significant difference and high expression was selected from the sequencing data for identification and functional validation. It is formed by reverse splicing cyclization of exons 5, 6, and 7 of the CFAP20DC gene on goat chromosome 22 (Fig. 5D), which was named circCFAP20DC. In this study, we attempted to investigate the cyclic nature of circCFAP20DC. Firstly, full-length primers were designed to amplify the full-length and cloned into T vector for sanger sequencing (Fig. 5B), and the sequencing results proved that the full-length sequence of circCFAP20DC was consistent with the high-throughput sequencing sequence (Fig. 5F). Subsequently, PCR amplification was carried out using cDNA and gDNA as templates with convergent and divergent primers, respectively, and its parental gene CFAP20DC was used as a control, and the results showed that only the cDNA group could amplify bands when amplified with the divergent primers, whereas the cDNA and gDNA groups could amplify fragments of the same size when amplified with the convergent primers, indicating that circCFAP20DC exists in a circular form (Fig. 5A). In addition RT-qPCR analysis after treatment of total RNA from goat granulosa cells with RNase R showed that circCFAP20DC is much less susceptible to degradation compared to linear GAPDH (Fig. 5E). Nucleoplasmic separation assays demonstrated that circCFAP20DC is predominantly located in the nucleus (Fig. 5C). These findings demonstrate that circCFAP20DC is a true circular RNA.

Fig. 5
figure 5

Identification of circCFAP20DC. A, Convergent primer, divergent primer amplification. B, CircCFAP20DC full-length amplification. C, Nucleoplasmic separation to verify the subcellular localisation of circCFAP20DC and GAPDH as a localised cytoplasmic control. D, Ring-forming mechanism of circCFAP20DC. E, RNase R digestion assay to validate the stability of circCFAP20DC. F, Comparison of circCFAP20DC full-length sequences, Query is sequenced sequence, Sbjct is amplified sequence

Full size image

The overexpression of circCFAP20DC in goat granulosa cells was found, through EDU assay, to significantly enhance the proliferation of goat granulosa cells (Fig. 6A). Furthermore, flow cytometry analyses revealed that the overexpression of circCFAP20DC led to a notable increase in the proportion of goat follicular granulosa cells in the S phase and a significant decrease in the proportion in the G1 phase (Fig. 6B). These results suggest that circCFAP20DC can facilitate the transition of granulosa cells from the G1 phase to the S phase.

Fig. 6
figure 6

Phenotypic effects of circCFAP20DC overexpression on goat granulosa cells. A, EDU detects the proliferative effect of circCFAP20DC overexpression on goat granulosa cells. B, Effect of circCFAP20DC overexpression on the cell cycle of goat granulosa cells detected by flow cytometry

Full size image

Following the overexpression of circCFAP20DC in goat granulosa cells, total RNA was extracted and RT-qPCR was conducted to analyze marker indicators associated with proliferation and apoptosis. The results demonstrated significant upregulation of proliferation-related genes PCNA, MCM4, and MCM6 (Fig. 7A-C), with MCM7 showing a tendency towards upregulation (Fig. 7D). Additionally, cell cycle-related genes CCNE1, CCNE2, and CDK2 exhibited significant upregulation (Fig. 7E-G), along with transcription factor-related genes E2F1 and E2F2 (Fig. 7H-I). These findings suggest that circCFAP20DC may interact with the cell cycle to enhance the proliferation of goat granulosa cells.

Fig. 7
figure 7

QPCR detection of PCNA(A), MCM4(B), MCM6(C), MCM7(D), CCNE1(E), CCNE2(F), CDK2(G), E2F1(H), E2F2(I) expression levels after circCFAP20DC overexpression

Full size image

Subsequent protein validation revealed a significant upregulation in the expression of PCNA and MCM6 in the circCFAP20DC overexpression group (Fig. 8A). Importantly, the levels of p-RB/RB, CDK2, and CCNE2 were also significantly increased (Fig. 8B), providing strong evidence that circCFAP20DC plays a crucial role in facilitating the transition from the G1 phase to the S phase in goat granulosa cells.

Fig. 8
figure 8

Changes in protein levels after overexpression of circCFAP20DC. A, Changes in PCNA and MCM6 at the protein level. B, Changes in cell cycle-related genes at the protein level

Full size image

Discussion

The reproductive performance of goats has always been a top priority in goat breeding, and the improvement of reproductive performance will bring huge economic benefits to the farming industry. Gene regulation is an important factor affecting reproductive performance, it was found that genes such as BMPR-1B [22], BMP15 [23], GDF9 [24], FSHR, FSHβ [25] affect the development of ovaries and follicles in mammals. The advent of high-throughput sequencing technology has sparked a surge of research interest in circRNAs as a type of regulatory RNA, with studies demonstrating their abundant presence in various species including humans [26], mouse [27], pig [28], cattle [29]and others. Recent studies in goats have shown that circRNAs play important regulatory roles in chorionic villus fibers, mammary epithelial cells, endometrial epithelial cells, and skeletal muscle development [30,31,32,33]. Moreover, Liu et al. established a circRNA expression profile of goat ovarian tissues and identified circRNAs as key players in the transition from the follicular phase to the luteal phase [34]. Nevertheless, research on circRNAs governing follicular development in goats is still in its nascent stage, necessitating more comprehensive transcriptomic studies to elucidate the molecular mechanisms that regulate lambing traits in goats. Such endeavors will hold immense significance for the advancement of animal husbandry practices.

The development of follicles from primordial follicles to mature follicles, leading up to ovulation and luteal development, is precisely regulated, and the production of a substantial number of dominant follicles plays a critical role in facilitating prolific and rapid reproduction in goats. Therefore, to investigate the regulatory role of circular RNAs in reproductive performance in Leizhou goats, we conducted transcriptome sequencing of large and small follicles from Leizhou goats. The sequencing results showed that there were 152 differentially expressed circRNAs in large and small follicles, which may indicate that circRNAs play an important regulatory role in follicle development. All 29 chromosomes of the goat can be reverse-sheared to generate circRNAs of varying lengths and different types. Moreover, miRanda predictions indicated that a single circRNA can target and bind multiple miRNAs, and reciprocally, a single miRNA can target and bind multiple circRNAs, underscoring the intricate complexity and functional diversity of circRNAs in eukaryotes. Unfortunately, the overall expression abundance of circRNAs tends to be low, possibly attributed to competition with mRNAs for expression.

We identified 28 significantly enriched pathways through KEGG enrichment analysis, which may play a role in the regulation of follicular development. Notably, the significantly enriched KEGG pathway includes Ovarian steroidogenesis, with CYP19A1 being among the host genes associated with its circRNA. The CYP19A1 gene belongs to the cytochrome P450 family and is essential for E2 synthesis in ovarian granulosa cells according to a previous study [35]. In goats, CYP19A1 potentially influences lambing traits by affecting granulosa cell proliferation, hormone secretion, and the expression of candidate genes associated with multiple birth traits [36]. In sheep, high-density SNP arrays revealed CYP19A1 as a candidate gene associated with the multiparous trait [37]. Therefore, we hypothesized that circRNAs reverse-sheared from CYP19A1 may also play a crucial regulatory role in goat reproductive performance. Notably, according to the sequencing data, we observed significant differential expression of chicirc_004004, derived from CYP19A1, in small and large follicles, suggesting its potential regulatory involvement in follicular development. Gonadotropin-releasing hormone (GnRH), primarily produced by the hypothalamus, stimulates the secretion of luteinizing hormone (LH) and follicle-stimulating hormone (FSH), which regulate sex hormone production via target cells or organs, thereby influencing reproductive performance [38]. As research progressed, it was discovered that, in addition to the hypothalamus, GnRH and its receptors were also found to be present in vertebrate ovaries and serve as significant regulators of follicular development [39, 40]. In the KEGG analysis of our study, the GnRH signaling pathway was found to be significantly enriched. Additionally, the expression of chicirc_045200, derived from the shearing of its parent gene, exhibited highly significant differences between large and small follicles, with notably higher expression levels in large follicles. This suggests a potential role in the selection of dominant follicles; however, further experiments are required to validate this hypothesis.

Interestingly, the animal autophagic pathway was significantly enriched in KEGG and genes significantly associated with this pathway were DEPTOR, PRKAA2. PRKAA2 encodes the alpha 2 catalytic subunit of AMP-activated protein kinase (AMPK) [41], which plays an important regulatory role in intracellular glucose and fatty acid metabolism and protein synthesis, and is also essential for reproductive function in females [42]. It was found that circCPM could directly bind to miR-21-3p in the cytoplasm and increase the expression of PRKAA2, which promoted the autophagic process and thus enhanced drug resistance in gastric cancer [43]. In Sarda Sheep, the variation of PRKAA2 gene was closely associated with lactose concentration [44]. Meanwhile, we found that PRKAA2 reverse shear produces chicirc_040992 according to the sequencing data, and it is highly significantly differentially expressed in small and large follicles. Therefore, chicirc_040992 most likely has an important role in follicle development. In mammals, DEPTOR can regulate the activity of the mTOR pathway and is involved in a variety of molecular pathways such as cell growth, apoptosis, autophagy and ER stress response [45,46,47]. Wang et al. [48]found that autophagic activity was regulated by DEPTOR expression, and that decreased DEPTOR protein decreased autophagy in myeloma cells, while high DEPTOR expression had the opposite effect. Agrawal et al. [49] showed that DEPTOR is a novel stemness factor that promotes pluripotency and self-renewal in ESCs by inhibiting mTOR signaling. The sequencing results revealed that DEPTOR reverse shearing produced two circRNAs, and the specific role of these circRNAs in goat follicle development remains to be investigated.

In the GO analysis, the significantly enriched pathway focused on reproductive behavior, which is associated with the gene SERPINE2. The reverse shear of SERPINE2 produced 12 circRNAs, with 6 of them showing highly significant differential expression in small and large follicles. This suggests that SERPINE2-associated circRNAs may play an alternative role in follicular development in goats. SERPINE2 belongs to the serine protease inhibitor (SERPIN) superfamily and is involved in the regulation of fibrinolysis, coagulation, inflammation, cell mobility, cell differentiation and apoptosis. Studies have indicated that high levels of exogenously supplemented SERPINE2 can impair cumulus expansion and oocyte maturation in mice [50]. Li et al. also found that the expression level of SERPINE2 in human mature oocytes was significantly lower than that in immature oocytes [51]. Cao et al. identified a strong positive correlation between estradiol and SERPINE2 in cattle, suggesting a role for SERPINE2 in the regulation of bovine follicular atresia [52]. Bedard et al. noted a high expression trend of SERPINE2 in dominant bovine follicles, supporting the hypothesis that increased SERPINE2 expression may contribute to follicular growth [53]. Furthermore, the majority of these differentially expressed circRNAs exhibit lengths greater than 400 bp and less than 1000 bp. Additionally, limited research has been conducted on the role of SERPINE2 in goat reproduction, indicating a potential avenue for further investigation into its function.

The sponge adsorption of circRNAs to miRNAs has emerged as a focal point in circRNA research [54]. In this sequencing analysis, we utilized miRanda to predict that a total of 436 miRNAs could bind to circRNAs, revealing instances where a single circRNA can bind to multiple miRNAs, underscoring the versatility of circRNA functionality. These interactions encompass various miRNA families such as the miR-101 family (chi-miR-101-3p, chi-miR-101-5p), miR-202 family (chi-miR-202-5p, chi-miR-202-3p), miR-324 family (miR-324-3p, miR-324-5p), among others. Studies in goats have demonstrated that miR-101-3p can modulate key proteins PI3K, PTEN, AKT, and mTOR within the PI3K-AKT pathway through STC1, thus impeding proliferation and fostering apoptosis of goat granulosa cells [55]; miR-202-5p has been shown to induce apoptosis and inhibit proliferation of granulosa cells [56]; and overexpression of miR-324-3p significantly impedes granulosa cell proliferation [57]. Additionally, miR-130a-3p, miR-1271-3p, miR-10b, and miR-29 are also pivotal in regulating proliferation and apoptosis of goat granulosa cells [58,59,60,61]. Our sequencing data predicts that 952 circRNAs can potentially interact with the target of miR-324-3p, 694 circRNAs with the target of miR-101-3p, and 590 circRNAs with the target of miR-202-5p. Notably, 14 differentially expressed circRNAs target miR-202-5p, 13 differentially expressed circRNAs target miR-101-3p, and 18 differentially expressed circRNAs target miR-324-3p. Therefore, it is speculated that the study of ceRNA network of circRNAs on Leizhou goats is promising.

CircRNA is traditionally regarded as a non-coding RNA; however, the perception changed following the discovery that circ-ZNF609 in myofibroblasts encodes proteins, challenging this conventional notion [62]. In this investigation, predictions were formulated based on two circRNA translation mechanisms, leading to the identification of 28 circRNAs reliant on internal ribosomal entry site (IRES), and 32 circRNAs dependent on N6-methyladenosine (m6A) residues. While the number of circRNAs potentially possessing translational functionality is relatively limited, this revelation opens up a new avenue of research into goat circRNAs, offering a theoretical foundation for understanding the reproductive mechanisms in goats.

In this study, we identified the novel circular RNA circCFAP20DC, which is formed by the reverse splicing cyclization of exons 5, 6, and 7 of the CFAP20DC gene. The reverse splice site and full-length sequence of circCFAP20DC were validated using PCR, TA cloning, and Sanger sequencing, confirming the existence of circCFAP20DC in goats. Additionally, an RNase R assay further confirmed the stability of circCFAP20DC and revealed its increased resistance to degradation compared to linear RNA. Nucleoplasmic separation assays probed the subcellular localization of circCFAP20DC and determined that it was mainly located in the nucleus. This is in keeping with Zhang et al.‘s research strategy on circRNAs [63]. To enhance the transfection efficiency of circCFAP20DC in goat granulosa cells, lentiviral vectors were constructed and packaged into viral liquid for cell infection. The results demonstrated a successful overexpression of circCFAP20DC by approximately 200-fold, significantly improving the transfection efficiency of circRNAs compared to transfection using liposomes [64, 65]. This lays the groundwork for further functional studies.

The EDU assay revealed that circCFAP20DC significantly enhanced the proliferation of goat granulosa cells. Furthermore, the cell cycle assay demonstrated a notable increase in the proportion of goat granulosa cells in the S-phase upon circCFAP20DC treatment, corroborating the EDU results and providing additional evidence of circCFAP20DC’s role in promoting cell proliferation. Subsequent RNA extraction post-circCFAP20DC overexpression followed by qPCR analysis showed a significant upregulation of PCNA, MCM4, MCM6, and a tendency towards upregulation of MCM7. PCNA is known to be crucial in DNA synthesis and repair [66], while interference with MCM6 has been shown to block the G1/S phase transition in neuroblastoma cells, thereby inhibiting cell proliferation [67]. MCM4 serves as a proliferation marker and is closely associated with cell cycle E expression [68]. Inhibition of MCM4 or MCM7 has been linked to reduced yolk protein levels in migratory locusts, hindering oocyte maturation and ovarian growth [69]. The observed trend in granulosa cell proliferation following circCFAP20DC overexpression aligns with these previous findings. Upon circCFAP20DC overexpression, key transcription factor-related genes E2F1 and E2F2 were significantly upregulated. E2F1 and E2F2 are pivotal regulators of the G1/S transition in cells [70]. In glioma cells, inhibition of E2F1 suppresses proliferation [71], whereas its overexpression promotes proliferation and metastasis in clear cell renal cell carcinoma [72]. This suggests that circCFAP20DC may modulate the cell cycle to enhance goat granulosa cell proliferation. More importantly, at the protein level, p-RB (Ser807/811), CDK2, and CCNE2 were significantly upregulated in the circCFAP20DC overexpression group. Previous studies have indicated that the CDK2/CCNE1 complex activates RB phosphorylation, leading to the release of activated E2F1, thereby facilitating cell cycle progression and proliferation [73]. Consistent with these findings, our study suggests that circCFAP20DC promotes RB phosphorylation to release the E2F protein family, ultimately stimulating granulosa cell proliferation.

In conclusion, this study has identified differentially expressed circRNAs in goat follicles of varying sizes, suggesting a potential key role in goat follicle development. Furthermore, the newly discovered circCFAP20DC in goats demonstrates a significant biological effect by promoting the transition of goat granulosa cells from the G1 phase to the S phase, subsequently enhancing their proliferation. However, the specific mechanism underlying the action of circCFAP20DC requires further and more comprehensive investigation.

Conclusions

In conclusion, this study aimed to investigate circRNAs that may influence follicular development in goats. The findings revealed that host genes containing differentially expressed circRNAs in goat-sized follicles were significantly enriched in ovarian steroidogenesis, the GnRH signaling pathway, the Oxytocin signaling pathway, animal autophagy pathways, and reproductive behavior. These differentially expressed circRNAs were inferred to have a substantial impact on follicular development. Furthermore, it was predicted that 152 significantly differentiated circRNAs could target 91 significantly differentiated miRNAs to exert ceRNA action, and 60 circRNAs exhibited translational potential. Additionally, the novel circular RNA circCFAP20DC was identified for the first time and demonstrated to potentially act on the RB regulatory pathway, promoting the G1 to S phase progression of goat granulosa cells and thereby facilitating their proliferation.

Data availability

The raw sequence data reported in this paper have been deposited in the Genome Sequence Archive in National Genomics Data Center, China National Center for Bioinformation / Beijing Institute of Genomics, Chinese Academy of Sciences (GSA: CRA015398) that are publicly accessible at https://ngdc.cncb.ac.cn/gsa.

References

  1. Angulo C, Chavez-Infante L, Reyes-Becerril M, Angulo M, Romero-Geraldo R, Llinas-Cervantes X, et al. Immunostimulatory and antioxidant effects of supplemental feeding with macroalga Sargassum spp. on goat kids. Trop anim Health pro. 2020;52(4):2023–33.

    Article  Google Scholar 

  2. Arnal M, Robert-Granie C, Larroque H. Diversity of dairy goat lactation curves in France. J Dairy sci. 2018;101(12):11040–51.

    Article  CAS  PubMed  Google Scholar 

  3. Chen Q, Huang Y, Wang Z, Teng S, Hanif Q, Lei C, et al. Whole-genome resequencing reveals diversity and selective signals in Longlin goat. Gene. 2021;771:145371.

    Article  CAS  PubMed  Google Scholar 

  4. Liu N, Cui W, Chen M, Zhang X, Song X, Pan C. A 21-bp indel within the LLGL1 gene is significantly associated with litter size in goat. Anim Biotechnol. 2021;32(2):213–8.

    Article  CAS  PubMed  Google Scholar 

  5. Zhang Y, Cui W, Yang H, Wang M, Yan H, Zhu H, et al. A novel missense mutation (L280V) within POU1F1 gene strongly affects litter size and growth traits in goat. Theriogenology. 2019;135:198–203.

    Article  CAS  PubMed  Google Scholar 

  6. McGee EA, Hsueh AJ. Initial and cyclic recruitment of ovarian follicles. Endocr Rev. 2000;21(2):200–14.

    CAS  PubMed  Google Scholar 

  7. Zhou J, Peng X, Mei S. Autophagy in Ovarian Follicular Development and Atresia. Int J Biol Sci. 2019;15(4):726–37.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Skinner MK. Regulation of primordial follicle assembly and development. Hum Reprod Update. 2005;11(5):461–71.

    Article  PubMed  Google Scholar 

  9. Liu J, Guo CH, Fu JJ, Liu DW, Liu GB, Sun BL, et al. Identification and functional analysis of circRNAs during Goat Follicular Development. Int J Mol Sci. 2024;25(14):7548.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Hu J, Dong J, Zeng Z, Wu J, Tan X, Tang T, et al. Using exosomal miRNAs extracted from porcine follicular fluid to investigate their role in oocyte development. BMC Vet Res. 2020;16(1):485.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Chen L, Wang C, Sun H, Wang J, Liang Y, Wang Y, et al. The bioinformatics toolbox for circRNA discovery and analysis. Brief Bioinform. 2021;22(2):1706–28.

    Article  CAS  PubMed  Google Scholar 

  12. Liu CX, Chen LL. Circular RNAs: characterization, cellular roles, and applications. Cell. 2022;185(12):2016–34.

    Article  CAS  PubMed  Google Scholar 

  13. Luo HL, Pi J, Zhang JA, Yang EZ, Xu H, Luo H, et al. Circular RNA TRAPPC6B inhibits intracellular Mycobacterium tuberculosis growth while inducing autophagy in macrophages by targeting microRNA-874-3p. Clin Transl Immunol. 2021;10(2):e1254.

    Article  CAS  Google Scholar 

  14. Sanger HL, Klotz G, Riesner D, Gross HJ, Kleinschmidt AK. Viroids are single-stranded covalently closed circular RNA molecules existing as highly base-paired rod-like structures. Proc Natl Acad Sci USA. 1976;73(11):3852–6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Guo T, Zhang J, Yao W, Du X, Li Q, Huang L, et al. CircINHA resists granulosa cell apoptosis by upregulating CTGF as a ceRNA of miR-10a-5p in pig ovarian follicles. BBA-Gene Regul Mech. 2019;1862(10):194420.

    CAS  Google Scholar 

  16. Wang H, Zhang Y, Zhang J, Du X, Li Q, Pan Z. circSLC41A1 resists porcine granulosa cell apoptosis and follicular atresia by promoting SRSF1 through mir-9820-5p sponging. Int J Mol Sci. 2022;23(3):1234.

  17. Sun LQ, Guo GL, Wu JY, Zhang L. The complete mitochondrial genome of Leizhou goat Capra hircus (Bovidae; Caprinae). Mitochondrial Dna A. 2016;27(2):1169–70.

    Article  CAS  Google Scholar 

  18. Rombel IT, Sykes KF, Rayner S, Johnston SA. ORF-FINDER: a vector for high-throughput gene identification. Gene. 2002;282(1–2):33–41.

    Article  CAS  PubMed  Google Scholar 

  19. Wang L, Park HJ, Dasari S, Wang S, Kocher JP, Li W. CPAT: Coding-Potential Assessment Tool using an alignment-free logistic regression model. Nucleic Acids Res. 2013;41(6):e74.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Zhou Y, Zeng P, Li YH, Zhang Z, Cui Q. SRAMP: prediction of mammalian N6-methyladenosine (m6A) sites based on sequence-derived features. Nucleic Acids Res. 2016;44(10):e91.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Zhao J, Wu J, Xu T, Yang Q, He J, Song X, IRESfinder. Identifying RNA internal ribosome entry site in eukaryotic cell using framed k-mer features. J Genet Genomics. 2018;45(7):403–6.

    Article  PubMed  Google Scholar 

  22. Medina-Montes A, Carrillo-Gonzalez DF, Hernandez-Herrea DY. Association of a genetic polymorphism in the BMPR-1B gene, and non-genetic factors with the natural prolificacy of the colombian-haired sheep. Trop Anim Health Pro. 2021;53(2):206.

    Article  Google Scholar 

  23. Galloway SM, Gregan SM, Wilson T, McNatty KP, Juengel JL, Ritvos O, et al. Bmp15 mutations and ovarian function. Mol Cell Endocrinol. 2002;191(1):15–8.

    Article  CAS  PubMed  Google Scholar 

  24. Wang F, Chu M, Pan L, Wang X, He X, Zhang R et al. Polymorphism detection of GDF9 gene and its association with litter size in Luzhong mutton sheep (Ovis aries). Animals-Basel. 2021;11(2):123.

  25. Zi XD, Huang L, Wang Y, Lu JY. Comparative messenger RNA expression of FSHbeta, LHbeta, FSHR, LHR, and ERbeta in high and low prolific goat breeds. Anim Biotechnol. 2013;24(4):307–11.

    Article  CAS  PubMed  Google Scholar 

  26. Li Y, Zhao J, Yu S, Wang Z, He X, Su Y, et al. Extracellular vesicles long RNA sequencing reveals abundant mRNA, circRNA, and lncRNA in human blood as potential biomarkers for Cancer diagnosis. Clin Chem. 2019;65(6):798–808.

    Article  CAS  PubMed  Google Scholar 

  27. Cao M, Zhang L, Wang JH, Zeng H, Peng Y, Zou J, et al. Identifying circRNA-associated-ceRNA networks in retinal neovascularization in mice. Int J Med Sci. 2019;16(10):1356–65.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Feng H, Yousuf S, Liu T, Zhang X, Huang W, Li A, et al. The comprehensive detection of miRNA and circRNA in the regulation of intramuscular and subcutaneous adipose tissue of Laiwu pig. Sci Rep-UK. 2022;12(1):16542.

    Article  CAS  Google Scholar 

  29. Liu R, Liu X, Bai X, Xiao C, Dong Y. Identification and characterization of circRNA in Longissimus Dorsi of different breeds of cattle. Front Genet. 2020;11:565085.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Zhu Y, Wang Y, Zhao J, Shen J, Wang Z, Bai M, et al. CircRNA-1967 participates in the differentiation of goat SHF-SCs into hair follicle lineage by sponging mir-93-3p to enhance LEF1 expression. Anim Biotechnol. 2023;34(3):482–94.

    Article  PubMed  Google Scholar 

  31. Zhang M, Ma L, Liu Y, He Y, Li G, An X, Cao B. CircRNA-006258 Sponge-Adsorbs miR-574-5p to Regulate Cell Growth and Milk Synthesis via EVI5L in Goat Mammary Epithelial Cells. Genes-Basel. 2020; 11(7).

  32. Zhang L, Liu X, Che S, Cui J, Liu Y, An X, et al. CircRNA-9119 regulates the expression of prostaglandin-endoperoxide synthase 2 (PTGS2) by sponging miR-26a in the endometrial epithelial cells of dairy goat. Reprod Fert Develop. 2018;30(12):1759–69.

    Article  CAS  Google Scholar 

  33. Ling Y, Zheng Q, Zhu L, Xu L, Sui M, Zhang Y, et al. Trend analysis of the role of circular RNA in goat skeletal muscle development. BMC Genomics. 2020;21(1):220.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Liu Y, Zhou Z, He X, Jiang Y, Ouyang Y, Hong Q, et al. Differentially expressed circular RNA Profile signatures identified in Prolificacy Trait of Yunshang Black Goat Ovary at Estrus Cycle. Front Physiol. 2022;13:820459.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Quirk SM, Cowan RG, Harman RM. The susceptibility of granulosa cells to apoptosis is influenced by oestradiol and the cell cycle. J Endocrinol. 2006;189(3):441–53.

    Article  CAS  PubMed  Google Scholar 

  36. Zhang Y, Chen X, Zhou Z, Tian X, Yang P, Fu K. CYP19A1 may influence lambing traits in goats by regulating the Biological function of Granulosa cells. Animals-Basel. 2022;12(15):234.

  37. Wang Y, Niu Z, Zeng Z, Jiang Y, Jiang Y, Ding Y et al. Using high-density SNP array to reveal selection signatures related to prolificacy in Chinese and Kazakhstan Sheep breeds. Animals-Basel. 2020;10(9):1593.

  38. Lee VH, Lee LT, Chow BK. Gonadotropin-releasing hormone: regulation of the GnRH gene. Febs J. 2008;275(22):5458–78.

    Article  CAS  PubMed  Google Scholar 

  39. Li H, Guo Y, Zhang G, Deng J, Fischer H, Craig LB, et al. Gonadotrophin-releasing hormone receptor autoantibodies induce polycystic ovary syndrome-like features in a rat model. Exp Physiol. 2021;106(4):902–12.

    Article  CAS  PubMed  Google Scholar 

  40. Chen Q, Duan J, Wu H, Li J, Jiang Y, Tang H, et al. Expression dynamics of gonadotropin-releasing hormone-I and its mutual regulation with luteinizing hormone in chicken ovary and follicles. Gen Comp Endocr. 2019;270:96–102.

    Article  CAS  PubMed  Google Scholar 

  41. Lin L, Flisikowski K, Schwarzenbacher H, Scharfe M, Severitt S, Blocker H, et al. Characterization of the porcine AMPK alpha 2 catalytic subunitgene (PRKAA2): genomic structure, polymorphism detection and association study. Anim Genet. 2010;41(2):203–7.

    Article  CAS  PubMed  Google Scholar 

  42. Griffiths RM, Pru CA, Behura SK, Cronrath AR, McCallum ML, Kelp NC, et al. AMPK is required for uterine receptivity and normal responses to steroid hormones. Reproduction. 2020;159(6):707–17.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Fang L, Lv J, Xuan Z, Li B, Li Z, He Z, et al. Circular CPM promotes chemoresistance of gastric cancer via activating PRKAA2-mediated autophagy. Clin Transl Med. 2022;12(1):e708.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Pazzola M, Vacca GM, Paschino P, Bittante G, Dettori ML. Novel Genes Associated with Dairy Traits in Sarda Sheep. Animals-Basel. 2021; 11(8).

  45. Yoon MS, Rosenberger CL, Wu C, Truong N, Sweedler JV, Chen J. Rapid mitogenic regulation of the mTORC1 inhibitor, DEPTOR, by phosphatidic acid. Mol Cell. 2015;58(3):549–56.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Weng Z, Shen X, Zheng J, Liang H, Liu Y. Structural basis of DEPTOR to Recognize Phosphatidic Acid using its Tandem DEP domains. J Mol Biol. 2021;433(13):166989.

    Article  CAS  PubMed  Google Scholar 

  47. Catena V, Fanciulli M. Deptor: not only a mTOR inhibitor. J Exp Clin Canc Res. 2017;36(1):12.

    Article  Google Scholar 

  48. Wang J, Chen J, Qiu D, Zeng Z. Regulatory role of DEPTOR–mediated cellular autophagy and mitochondrial reactive oxygen species in angiogenesis in multiple myeloma. Int J Mol Med. 2021;47(2):643–58.

    Article  PubMed  Google Scholar 

  49. Agrawal P, Reynolds J, Chew S, Lamba DA, Hughes RE. DEPTOR is a stemness factor that regulates pluripotency of embryonic stem cells. J Biol Chem. 2014;289(46):31818–26.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Lu CH, Lee RK, Hwu YM, Lin MH, Yeh LY, Chen YJ, et al. Involvement of the serine protease inhibitor, SERPINE2, and the urokinase plasminogen activator in cumulus expansion and oocyte maturation. PLoS ONE. 2013;8(8):e74602.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Li SH, Lin MH, Hwu YM, Lu CH, Yeh LY, Chen YJ, et al. Correlation of cumulus gene expression of GJA1, PRSS35, PTX3, and SERPINE2 with oocyte maturation, fertilization, and embryo development. Reprod Biol Endocrin. 2015;13:93.

    Article  Google Scholar 

  52. Cao M, Nicola E, Portela VM, Price CA. Regulation of serine protease inhibitor-E2 and plasminogen activator expression and secretion by follicle stimulating hormone and growth factors in non-luteinizing bovine granulosa cells in vitro. Matrix Biol. 2006;25(6):342–54.

    Article  CAS  PubMed  Google Scholar 

  53. Bedard J, Brule S, Price CA, Silversides DW, Lussier JG. Serine protease inhibitor-E2 (SERPINE2) is differentially expressed in granulosa cells of dominant follicle in cattle. Mol Reprod Dev. 2003;64(2):152–65.

    Article  CAS  PubMed  Google Scholar 

  54. Chen LL. The expanding regulatory mechanisms and cellular functions of circular RNAs. Nat Rev Mol Cell Bio. 2020;21(8):475–90.

    Article  CAS  Google Scholar 

  55. An X, Ma H, Liu Y, Li F, Song Y, Li G, et al. Effects of Mir-101-3p on goat granulosa cells in vitro and ovarian development in vivo via STC1. J Anim Sci Biotechno. 2020;11:102.

    Article  CAS  Google Scholar 

  56. Ding Q, Jin M, Wang Y, Liu J, Kalds P, Wang Y et al. Transactivation of mir-202-5p by Steroidogenic factor 1 (SF1) induces apoptosis in Goat Granulosa cells by targeting TGFbetaR2. Cells-Basel. 2020;9(2):402.

  57. Liu Y, Chen Y, Zhou Z, He X, Tao L, Jiang Y, et al. Chi-mir-324-3p regulates Goat Granulosa Cell Proliferation by Targeting DENND1A. Front Vet Sci. 2021;8:732440.

    Article  PubMed  PubMed Central  Google Scholar 

  58. Zhu L, Jing J, Qin S, Zheng Q, Lu J, Zhu C, et al. miR-130a-3p regulates steroid hormone synthesis in goat ovarian granulosa cells by targeting the PMEPA1 gene. Theriogenology. 2021;165:92–8.

    Article  CAS  PubMed  Google Scholar 

  59. Liu Y, Zhou Z, He X, Tao L, Jiang Y, Lan R, et al. Integrated analyses of miRNA-mRNA expression profiles of ovaries reveal the crucial interaction networks that regulate the prolificacy of goats in the follicular phase. BMC Genomics. 2021;22(1):812.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Peng JY, An XP, Fang F, Gao KX, Xin HY, Han P, et al. MicroRNA-10b suppresses goat granulosa cell proliferation by targeting brain-derived neurotropic factor. Domest Anim Endocrin. 2016;54:60–7.

    Article  CAS  Google Scholar 

  61. Wang P, Liu S, Zhu C, Duan Q, Jiang Y, Gao K, et al. MiR-29 regulates the function of goat granulosa cell by targeting PTX3 via the PI3K/AKT/mTOR and Erk1/2 signaling pathways. J Steroid Biochem. 2020;202:105722.

    Article  CAS  Google Scholar 

  62. Legnini I, Di Timoteo G, Rossi F, Morlando M, Briganti F, Sthandier O, et al. Circ-ZNF609 is a circular RNA that can be translated and functions in Myogenesis. Mol Cell. 2017;66(1):22–37.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Zhang S, Wang X, Chen G, Tong L, Dai T, Wang L, et al. CircRNA Galntl6 sponges miR-335 to ameliorate stress-induced hypertension through upregulating Lig3 in rostral ventrolateral medulla. Redox Biol. 2023;64:102782.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Wu J, Zhang S, Yue B, Zhang S, Jiang E, Chen H, et al. CircRNA profiling reveals CircPPARgamma modulates adipogenic differentiation via sponging miR-92a-3p. J Agr Food Chem. 2022;70(22):6698–708.

    Article  CAS  Google Scholar 

  65. Yue B, Yang H, Wu J, Wang J, Ru W, Cheng J, et al. circSVIL regulates bovine myoblast development by inhibiting STAT1 phosphorylation. Sci China Life Sci. 2022;65(2):376–86.

    Article  CAS  PubMed  Google Scholar 

  66. Gu L, Lingeman R, Yakushijin F, Sun E, Cui Q, Chao J, et al. The Anticancer activity of a first-in-class small-molecule Targeting PCNA. Clin Cancer Res. 2018;24(23):6053–65.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Gu Y, Hu X, Liu X, Cheng C, Chen K, Wu Y, et al. MCM6 indicates adverse tumor features and poor outcomes and promotes G1/S cell cycle progression in neuroblastoma. BMC Cancer. 2021;21(1):784.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Choy B, LaLonde A, Que J, Wu T, Zhou Z. MCM4 and MCM7, potential novel proliferation markers, significantly correlated with Ki-67, Bmi1, and cyclin E expression in esophageal adenocarcinoma, squamous cell carcinoma, and precancerous lesions. Hum Pathol. 2016;57:126–35.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. Guo W, Wu Z, Song J, Jiang F, Wang Z, Deng S, et al. Juvenile hormone-receptor complex acts on mcm4 and mcm7 to promote polyploidy and vitellogenesis in the migratory Locust. Plos Genet. 2014;10(10):e1004702.

    Article  PubMed  PubMed Central  Google Scholar 

  70. Clijsters L, Hoencamp C, Calis J, Marzio A, Handgraaf SM, Cuitino MC, et al. Cyclin F controls cell-cycle transcriptional outputs by directing the degradation of the three activator E2Fs. Mol Cell. 2019;74(6):1264–77.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Xiao B, Tan L, He B, Liu Z, Xu R. MiRNA-329 targeting E2F1 inhibits cell proliferation in glioma cells. J Transl Med. 2013;11:172.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. Shen D, Gao Y, Huang Q, Xuan Y, Yao Y, Gu L, et al. E2F1 promotes proliferation and metastasis of clear cell renal cell carcinoma via activation of SREBP1-dependent fatty acid biosynthesis. Cancer Lett. 2021;514:48–62.

    Article  CAS  PubMed  Google Scholar 

  73. Zhou M, Yang Z, Wang D, Chen P, Zhang Y. The circular RNA circZFR phosphorylates rb promoting cervical cancer progression by regulating the SSBP1/CDK2/cyclin E1 complex. J Exp Clin Canc Res. 2021;40(1):48.

    Article  CAS  Google Scholar 

Download references

Acknowledgements

The authors are sincerely grateful for the fund support from Guangdong Province and the experimental farm at South China Agricultural University.

Funding

This research was supported by the Modern Agricultural Industrial Technology System of Guangdong Province (grant number 2023KJ127), and the Guangdong-Guangxi Cooperative Technology Special Envoys Team Project (E230257).

Author information

Authors and Affiliations

  1. Herbivore Laboratory, College of Animal Science, South China Agricultural University, Guangzhou, 510642, China

    Jie Liu, Guanghang Feng, Conghui Guo, Zhihan Li, Dewu Liu, Guangbin Liu, Baoli Sun, Yongqing Guo, Ming Deng & Yaokun Li

  2. State Key Laboratory of Livestock and Poultry Breeding, Guangdong Key Laboratory of Animal Breeding and Nutrition, Institute of Animal Science, Guangdong Academy of Agricultural Sciences, Guangzhou, 510640, China

    Xian Zou

  3. National Joint Engineering Research Center, South China Agricultural University, Guangzhou, 510642, China

    Jie Liu, Guanghang Feng, Conghui Guo, Zhihan Li, Dewu Liu, Guangbin Liu, Baoli Sun, Yongqing Guo, Ming Deng & Yaokun Li

  4. Guangdong Key Laboratory of Agricultural Animal Genomics and Molecular Breeding, South China Agricultural University, Guangzhou, 510642, China

    Jie Liu, Guanghang Feng, Conghui Guo, Zhihan Li, Dewu Liu, Guangbin Liu, Baoli Sun, Yongqing Guo, Ming Deng & Yaokun Li

Authors
  1. Jie Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Guanghang Feng
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Conghui Guo
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Zhihan Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Dewu Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Guangbin Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Xian Zou
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Baoli Sun
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Yongqing Guo
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Ming Deng
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Yaokun Li
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

JL, YKL, YQG and CHG conceived and designed the study; JL, GHF, ZHL, YQG, GBLand CHG performed the experiments; MD, DWL and XZ organized the database and performed the statistical analysis; JL, YKL, wrote the manuscript; JL, DWL and ZHL visualized the results; YQG and BLS revised the manuscript.

Corresponding author

Correspondence to Yaokun Li.

Ethics declarations

Ethics approval and consent to participate

All research protocols were approved by the Animal Protection and Ethics Committee of South China Agricultural University (License No. SYXK-2018-0123). In addition, all experiments were conducted in accordance with the guidelines of South China Agricultural University.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note

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

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material 1

Supplementary Material 2: Supplementary Table S1 Primer sequences used in the experiment

Supplementary Material 3: Supplementary Table S2 Statistics of sequencing downstream data

Supplementary Material 4: Supplementary Table S3 Unmapped Reads Recompare Statistics

Supplementary Material 5: Supplementary Table S4 Differential expression of circRNAs in small and large follicles

Supplementary Material 6: Supplementary Table S5 Parental genes for circRNAs

Supplementary Material 7: Supplementary Table S6 Pathways generated by GO enrichment analysis

Supplementary Material 8: Supplementary Table S7 Pathways generated by KEGG enrichment analysis

Supplementary Material 9: Supplementary Table S8 Targeted miRNAs for circRNAs

Supplementary Material 10: Supplementary Table S9 Construction of circRNA-miRNA-mRNA ceRNA network

Supplementary Material 11: Supplementary Table S10 CircRNAs containing open reading frames

Supplementary Material 12: Supplementary Table S11 Predicted circRNAs that rely on IRES to initiate translation

Supplementary Material 13: Supplementary Table S12 Predicted circRNAs that rely on m6A to initiate translation

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Liu, J., Feng, G., Guo, C. et al. Identification of functional circRNAs regulating ovarian follicle development in goats. BMC Genomics 25, 893 (2024). https://doi.org/10.1186/s12864-024-10834-w

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12864-024-10834-w

Keywords

BMC Genomics

ISSN: 1471-2164

Contact us