CREB1 Is Involved in miR-134-5p-Mediated Endometrial Stromal Cell Proliferation, Apoptosis, and Autophagy.

Based on the results of BMPR-IB polymorphism genotyping, a total of sixteen pluriparous ewes with FecB BB genotypes and four pluriparous FecB B+ were selected from Jiangsu Xilaiyuan Ecological Agriculture Co., Ltd. (Taizhou, China). The selected ewes were approximately three years old and were similar in weight. Ewes were divided into LP_HBB (LP, luteal phase; high prolificacy, each record of litter size = 3; n = 4; body weight of pre-slaughter: [47.98 ± 1.24] kg), LP_LBB/LP_LB+ (low prolificacy, each record of litter size = 1; n = 4; body weight of pre-slaughter: [52.05 ± 2.95] kg/[53.03 ± 4.69] kg), FP_HBB (FP, follicular phase; high prolificacy, each record of litter size = 3; n = 4; body weight of pre-slaughter: [47.43 ± 2.64] kg), FP_LBB (low prolificacy, each record of litter size = 1; n = 4; body weight of pre-slaughter: [51.05 ± 4.80] kg) groups based on identical litter size numbers of three records. The sheep utilized in this investigation were provided with unrestricted access to water and food under natural lighting conditions. Female sheep received synchronized estrus treatment, which involved the initial insertion of a vaginal sponge for a duration of 11 days. The estrus status of the ewes was assessed daily through interactions with a ram. Finally, ewes were slaughtered separately within 12 h after the detection of estrus (follicular phase) and on the ninth day (luteal phase), and the lateral endometrium was opened longitudinally to collect the endometrium from one side of the uterine horn. Female reproductive organs (hypothalamus, pituitary, uterus, oviduct, and ovary) were also collected for tissue expression pattern analysis. All samples were immediately stored at −80 °C. The other uterine horn was immersed in a 4% paraformaldehyde (PFA) solution for 24 h and subsequently embedded in paraffin for further analysis. In addition, intensive blood collection was performed before the sheep were slaughtered, as previously described [ 85 ]. The results of the BMPR-IB polymorphism genotyping are shown in Figure S5 . The uterus coefficient was determined by weighing the intact uterine organ and by dividing it by the total body weight of each ewe. To quantify uterine gland density, 6 μm sections were subjected to staining using hematoxylin and eosin (H&E) following established protocols. For each sample, 5 randomly selected fields were imaged at 20× magnification using a Nikon microscope (ECLIPSE Ti, Tokyo, Japan). Gland counts per 20× field were determined via manual scoring using ImageJ software in a blinded fashion. For microvessel density (MVD) quantification, adjacent serial sections were immunostained with a primary CD34 antibody using a standard streptavidin-biotin horseradish peroxidase method. Five areas were randomly selected under the Nikon microscope (ECLIPSE Ti, Tokyo, Japan). Any brown endothelial cell or cell mass that could be easily distinguished from the adjacent tissues was defined as a single microvessel [ 86 ]. Endometrial DGI was quantified by examining the entire uterine section using a Nikon microscope (ECLIPSE Ti, Tokyo, Japan). The glandular epithelium was distinctly cavated and was regarded as DGI, and the number of DGI in the whole uterus of each sheep in the luteal phase was counted (see Figure S6A for the schematic diagram). The schematic diagrams of the LE thickness and myometrial thickness analysis are shown in Figure S6B,C , and ten positions were evenly selected for analysis. Analysis of endometrium thickness: To assess the thickness of sheep endometria, the endometrial thickness (ET) was calculated using the formula ET = 2A/(P1 + P2) [ 87 , 88 ]. The calculated area (A) is the total endometrial area on a uterine cross-section. The calculated inner perimeter (P1) was measured by tracing the lumen and the endometrium–myometrium interface. The outer perimeter (P2) was determined by tracing this interface (as shown in Figure S6D ). All the measurements were determined using the ImageJ software (National Institute of Health, Bethesda, MD, USA). The total RNA was extracted from twelve Hu sheep endometrial tissues in the luteal phase using the TRIzol reagent (Thermo Scientific, Waltham, MA, USA). The RNA quantity and purity were assessed using NanoDrop ND-1000 (NanoDrop, Wilmington, DE, USA), and only RNA samples with RIN (RNA integrity) > 7 were used for sequencing. To prepare the samples of RNA-seq, we utilized a Ribo-Zero™ rRNA Removal Kit (Illumina, San Diego, CA, USA) to deplete ribosomal RNA from ~5 µg of total RNA per sample. The NEB Next ® Ultra Directional RNA LibraryPrep Kit for Illumina ® (NEB, Ipswich, MA, USA) was employed to construct the strand-specific RNA-seq libraries. Then, paired-ended sequencing was performed using an Illumina NovaSeq 6000 Sequencing System to generate paired-end 150 bp reads, with a sequencing depth of at least 12 million reads per sample (LC-Bio Technology Co., Ltd., Hangzhou, China). Raw data from nine Hu sheep endometrial tissues in the follicular phase were derived from previous laboratory sequencing data [ 40 ]. The generated data underwent quality assessment using the Fast QC tool (version 0.10.1) and were aligned to the reference genome for clean reads data. Differentially expressed genes (DEGs) were identified using at least 1.5 fold changes and p -value < 0.05. Volcano plots, the enrichment analysis of Gene Ontology (GO), and the Kyoto Encyclopedia of Genes and Genomes (KEGG) can be carried out using the OmicStudio tools ( http://www.omicstudio.cn/tools , accessed on 3 July 2023). Volcano plots were generated from significantly regulated genes. The enrichment of relevant GO terms and KEGG pathways was considered significantly enriched when their adjusted p -value were below 0.05. The total RNA was extracted in accordance with the manufacturer’s Trizol protocol (Invitrogen, Waltham, CA, USA). RNA concentration and purity were assessed via spectrophotometry (A260/280 > 1.8). Total RNA (1 μg) was reverse-transcripted using the HiScript II 1st Strand cDNA Synthesis Kit (+gDNA wiper) (37 °C for 15 min, 85 °C for 5 s) or the miRNA 1st Strand cDNA Synthesis Kit (by stem-loop) (25 °C for 5 min, and 50 °C for 15 min, followed by 85 °C for 5 min) (Vazyme, Nanjing, China). Genomic DNA was removed prior to the first strand cDNA synthesis (42 °C for 2 min). The qRT-PCR was performed on a QuantStudio™ 7 Real-Time PCR system (Applied Biosystems, Foster, CA, USA) using the PerfectStart ® Green qPCR SuperMix (+Dye II) (TransGen Biotech, Beijing, China) (94 °C for 30 s, and 40 cycles of 94 °C for 5 s, 60 °C for 30 s, followed by 95 °C for 15 s, 60 °C for 1 min, and 95 °C for 15 s). The expression levels of candidate mRNAs and miRNAs were initially normalized to those of ACTB and U6, respectively, and the 2 −ΔΔCt method was employed for calculating the expression levels. The PCR specificity was verified by melt curve analysis. The primers employed in this study can be found in Table S16 . Total protein was extracted from the ESCs using RIPA lysis buffer (Invitrogen, Waltham, CA, USA) containing protease and phosphatase inhibitor cocktail (Beyotime, Haimen, China) and quantified using a BCA kit (Beyotime, Haimen, China) as per the manufacturer’s protocol; 30 µg of total protein was resolved using 12% sodium dodecyl sulfate-polyacrylamide gels and subsequently transferred in Tris-glycine buffer at a voltage of 100 V for 1 h. Membranes were blocked by incubating them in a 5% non-fat milk solution in Tris-HCL buffer with Tween-20 (TBST) for 1 h at room temperature. Subsequently, the primary antibodies were incubated overnight at 4 °C, followed by the application of the secondary antibodies at room temperature for 1 h (the antibody dilutions adhered to the specifications provided in Table S17 ). The chemiluminescence detection kit (Biosharp, Guangzhou, China) was utilized for protein band visualization with an electroluminescence detection system (Bio-RAD, Hercules, CA, USA). ImageJ software (National Institute of Health, Bethesda, MD, USA) was employed to quantify the intensity of the protein bands, and Tubulin was used for normalizing the target proteins. The sections of reproductive axis tissue (hypothalamus, pituitary, oviduct, ovary, and uterus) were obtained from paraffin tissue blocks previously embedded in the laboratory. Consecutive sections containing the largest hypothalamic area were selected according to the ovine brain atlas [ 89 ]. The IHC analysis was performed using established methodologies as previously described [ 90 ]. Briefly, the wax was removed from each section by employing xylene and a series of gradually concentrated ethanol solutions. To quench the endogenous peroxidase activity, a 10-minute incubation was performed in methanol containing 3% hydrogen peroxide. The procedure for antigen retrieval involved exposing the tissue sections to a 5-minute microwave treatment in a citrate buffer solution. To minimize non-specific binding sites, we employed a 5% solution of bovine serum albumin (BSA) for blocking purposes. Subsequently, the tissue sections were incubated overnight at 4 °C with polyclonal rabbit antibodies against CD34/CREB1 (as specified in Table S17 ). After the incubation period, the sections were washed three times using phosphate-buffered saline (PBS) and then exposed to the appropriate secondary antibody (as listed in Table S17 ) at room temperature for 1 h. Relevant experiments were conducted by substituting the primary antibody with PBS as controls. Sections were developed with 3–3′-diaminobenzidine (DAB) (Boster, Guangzhou, China) for 5 min. After rinsing the sections with distilled water, a counterstaining procedure was performed using hematoxylin (Boster, Guangzhou, China). The sections were then air-dried and sealed with neutral resin. Imaging was performed using a Pannoramic MIDI digital sliDE scanner (3DHISTECH) at 20× magnification, and images were analyzed using SlideViewer software (Version 2.5). The serum levels of E2, P4, PRL, and PLGF were measured using commercial ELISA kits according to the manufacturer’s instructions (Kmaels Co., Ltd., Shanghai, China). Absorbance at 450 nm was used to quantify hormone levels from the standard curves. The intra- and inter-assay CVs were 10% and 15%, respectively. The limits of detection were 1.0 pg/mL (E2), 0.1 ng/mL (P4), 1.0 ng/mL (PRL) and 1.0 pg/mL (PLGF). The isolation, purification, and identification methods of ESCs follow our laboratory’s previous methods [ 60 ] ( Figure S7 ). The stored cells were cultured in Dulbecco’s Modified Eagle Medium: F12 (DMEM/F12) (Thermofisher, Waltham, MA, USA), with 10% fetal bovine serum (FBS) (Gibco, Gland Island, NY, USA) and 1% penicillin-streptomycin solution (Gibco). Our laboratory’s 293T cells (human embryonic kidney cells) were cultured in a DMEM medium (Thermofisher) with 10% FBS and 1% penicillin-streptomycin. They were all cultured at 37 °C in an atmosphere of 5% CO 2 . The relative plasmid or oligonucleotide was transfected into ESCs and 293T cells using Lipofectamine 3000 (Invitrogen, Waltham, MA, USA) following the manufacturer’s protocol. Briefly, 4 × 10 5 cells per well were seeded in 12-well plates and transfected at 70–80% confluency with plasmid DNA or small interfering RNAs (siRNAs). The transfection efficiency of Lipofectamine 3000 was optimized by transfecting a GFP expression plasmid and visualizing GFP expression by fluorescence microscopy 24 h post-transfection. In ESCs, transfection with 2 μL Lipofectamine 3000 and 1 μg plasmid DNA resulted in >50% GFP-positive cells. In 293T cells, >80% of cells expressed GFP under these conditions. The siRNAs of CREB1 (si-CREB1 1# and si-CREB1 2#), miR-134-5p mimics/inhibitors, and corresponding negative controls (NC) were purchased from GenePharma (Shanghai, China). The CREB1 overexpression plasmid (pEX3-CREB1) and empty vector (pEX3-NC) were purchased from Tsingke Biotechnology Co., Ltd. (Beijing, China). The CREB1 3′UTR containing the miR-134-5p binding site was cloned downstream of Renilla in the pmirGLO luciferase reporter vector. Mutations in the miR-134-5p-binding sites in the CREB1 3′UTR sequence were generated using a Mutagenesis Kit (Vazyme, Nanjing, China). The sequences of siRNAs, mimics, or inhibitors are listed in Table S18 . The ESCs were washed three times with PBS and then fixed in 4% PFA for 15 min at room temperature. Subsequently, permeabilization was performed using 0.1% Triton X-100 for 30 min. Non-specific binding sites were blocked with 3% BSA. Then, the ESCs were incubated overnight at 4 °C with appropriate primary antibodies (as indicated in Table S17 ). Negative controls were subjected to incubation with normal FBS instead of the primary antibody. After three washes with PBS, the cells were incubated at room temperature for 1 h with a secondary antibody conjugated to Alexa Fluor 594/488. Then, the cell nuclei were stained with 4, 6-diamidino-2-phenylindole (DAPI) (Beyotime, Haimen, China), and the cells were washed three times with PBS. Immunofluorescence was visualized using a Nikon Eclipse Ti inverted epifluorescence microscope using a 20× objective and NIS Elements imaging software (Version 4.10). The assessment of cell viability was conducted using the Cell Counting Kit-8 (CCK-8) assay provided by Vazyme (Nanjing, China). The CCK-8 assay was performed by adding 10 μL of CCK8 reagent to individual wells of a 96-well plate, followed by incubation at 37 °C for a duration of 2 h. After the incubation period, the optical density at 450 nm was measured using a microplate reader (51119200, Thermo Scientific, Waltham, MA, USA). The assessment of cell proliferation was evaluated by 5-Ethynyl-2′-deoxyuridine (EdU) incorporation assay using an Alexa Fluor 555/488-ClickiT EdU Assay Kit (Keygen Biotech, Nanjing, China). Briefly, the ESCs (2 × 10 5 cells per well) were seeded on glass coverslips in a 24-well plate and subjected to different transfection treatments. After 24 h, a working solution of EdU was added at a concentration of 50 μM. Subsequently, the cells underwent three washes with Dulbecco’s Phosphate-Buffered Saline (DPBS) and then fixed with 4% PFA for 30 min. A rinse with a glycine solution (2 mg/mL) was performed for 5 min. After removing the glycine solution, cells were permeabilized in DPBS containing 0.5% Triton X-100 for 20 min. Following three additional washes in DPBS, Hoechst 33342 dye was used to stain cell nuclei. Finally, an antifade medium was applied to cover the images before capturing them using a laser scanning confocal microscope (LSM700META, Carl Zeiss, Berlin, Germany) under identical conditions. ZEN software (Version 2.6, Carl Zeiss, Berlin, Germany) was used to save and export the pictures. According to the manufacturer’s instructions, propidium iodide (PI) staining (Keygen Biotech, Nanjing, China) was used to label the ESCs for cell cycle analysis. The DNA content was evaluated using flow cytometry (Beckman Coulter, Brescia, CA, USA), and the distribution cycle was quantified utilizing FlowJo software (Version 10.6.2, TreeStar, Ashland, OR, USA). Apoptotic cells were detected using Annexin V FITC/PI staining. Initially, the transfected ESCs were washed three times with ice-cold PBS and then resuspended in 100 µL of binding buffer. Annexin V-FITC (5 µL, 20 mg/mL) and PI (10 µL, 50 mg/mL) (BD Biosciences, Franklin Lakes, NJ, USA) were added and incubated for 15 min under ambient conditions. Subsequently, 400 µL of binding buffer was added, and the cells were analyzed via flow cytometry using a Becton Dickinso FACS Calibur (Ashland, OR, USA). The apoptosis rates were determined using the FlowJo software (TreeStar) by analyzing the cellular distribution in quadrants Q2 (late apoptotic) and Q3 (early apoptotic). The 293T cells were cultured in 24-well plates at a seeding density of 2 × 10 5 cells per well. Co-transfected was performed using Lipofectamine 3000 regeant (Invitrogen, Waltham, CA, USA) to introduce the NC/miR-134-5p mimics and the luciferase reporter vector containing the 3′-UTR region of CREB1. Renilla luciferase was used as an internal control. After a transfection period of 48 h, luciferase activities were quantified using the Dual-Luciferase Reporter Assay System (Vazyme, Nanjing, China) according to the manufacturer’s operating instructions. At least three biological replicates were used in each experiment. Prior to analysis, data normality was confirmed using the Kolmogorov–Smirnov goodness-of-fit test. Student’s t -test was employed for two groups, while one-way analysis of variance (ANOVA) was used for multiple groups. If data violated assumptions of homoscedasticity, nonparametric Mann–Whitney U test or Kruskal–Wallis H test with Dunn’s post hoc test were used instead. Statistical analyses were conducted using SPSS 23.0 (IBM, Armonk, NY, USA) and GraphPad Prism 8.0 (Inc., San Diego, CA, USA). The data were presented as the mean ± standard error of the mean (SEM), which was calculated based on at least three independent experiments. Differences with p -value < 0.05 were considered statistically significant, whereas differences with p -value < 0.01 were deemed markedly statistically significant.

Fertility plays a pivotal role in the economic aspect of sheep production. Hu sheep, a native Chinese breed, have garnered attention for their precocious puberty, year-round estrus, and high fecundity (average litter size 2.06) [ 1 , 2 ]. To date, several major fecundity genes, including the bone morphogenetic protein receptor IB ( BMPR-IB ) gene [ 3 , 4 ], the bone morphogenetic protein 15 ( BMP15 ) gene [ 5 , 6 ], and the growth differentiation factor 9 ( GDF9 ) gene [ 7 , 8 ], have been discovered. Among these genes, FecB is recognized as the first major gene linked to prolificacy and multiple births in sheep. This arises from a point mutation at A746G in BMPR-IB , leading to an amino acid mutation from glutamine to arginine [ 9 , 10 ]. According to previously published literature, FecB mutations exert cumulation effects on ovulation number and litter size in sheep; for example, possessing one copy of FecB mutation increases ovulation number by 1.5 and litter size by 1, whereas having two copies of FecB mutation increases ovulation number by 3 and litter size by 1.5, respectively [ 11 ]. However, some Hu sheep carrying the FecB BB genotype also give birth to single lambs. Thus, we speculated that factors other than the BB genotype mutation of BMPR-IB may influence the litter size in Hu sheep. Key processes in mammalian reproduction include ovarian follicular dynamics, ovulation, luteinization, luteolysis, and endometrial remodeling [ 12 , 13 , 14 ]. Research on ovine fecundity has largely focused on ovarian function [ 15 , 16 , 17 ]. However, uterine function also plays a critical role in prolificacy. The uterus is an important site for embryo implantation, and good endometrial receptivity and normal maternal fetal recognition are closely related to fertility. The sheep estrous cycle averages 16–17 days, comprising follicular and luteal phases distinguished by ovarian morphology and hormone secretion [ 18 ]. The endometrium undergoes a repeated cycle of proliferation, differentiation, and repair to prepare the embryo for successful implantation and maintenance of pregnancy under the control of the ovarian steroidal hormones estrogen (E2) and progesterone (P4) [ 19 , 20 ]. The endometrium is regenerated and differentiated in the follicular phase, whereas its metabolic demands shift in the luteal phase [ 21 ]. Throughout the preimplantation period, embryonic growth is sustained by maternal uterine secretions comprising a diverse array of nutrients including proteins, amino acids, pyruvate, lactate, carbohydrates, and fatty acids [ 22 , 23 , 24 , 25 ]. In addition, hormones, cytokines, transcription factors, adhesion molecules, and glycoproteins act on the endometrium, regulate endometrial function, and promote interactions between the endometrium and embryo [ 26 , 27 , 28 , 29 , 30 , 31 , 32 ]. The critical roles of the uterus in supporting embryo development highlight this organ as a potential source of valuable prolificacy genes. Therefore, a comprehensive understanding of the molecular mechanisms governing uterine-related functions is of paramount importance when investigating reproduction in female sheep. Endometrial receptivity is a prerequisite for successful embryo implantation and pregnancy [ 33 ]. Studies have shown that unsound endometrial receptivity leads to embryo loss during preimplantation, which is an important reason for the low litter size of farm animals [ 34 ]. The transcription factor cAMP response element-binding protein-1 ( CREB1 ), as an important target for multiple signaling pathways, was reported to be markedly dysregulated in endometriosis (EMS) patients [ 35 , 36 ]. Endometrial receptivity has been found to decline in patients clinically diagnosed with EMS [ 37 ]. Therefore, we speculate that dysregulation of CREB1 may affect endometrial receptivity. In addition, endometrial thickness, uterine blood flow, and uterine gland development can be used as indicators of uterine receptivity [ 38 , 39 ]. Our previous studies compared the endocrinology and endometrial morphology of high-fertility Hu sheep ( FecB BB genotype) and low-fertility Hu sheep ( FecB BB / FecB B+ genotype) in the follicular phase [ 40 ]. In the present study, we first analyzed the endocrinology and endometrial morphology of three groups of Hu sheep (LP_HBB, LP_LBB, and LP_LB+) in the luteal phase. Then, RNA sequencing (RNA-seq) was utilized to analyze the changes in gene expression profiles in Hu sheep endometrium during the luteal phase and follicle–luteum transformation process. CREB1 , which has a targeting-binding relationship with miR-134-5p, significantly affected the expression level of endometrial receptivity marker genes, promoted the proliferation of endometrial stromal cells (ESCs), and inhibited their apoptosis and autophagy. Our results contribute to the overall improvement of sheep breeding in China and provide valuable insights into the regulatory mechanisms governing the fertility of Hu sheep. Moreover, elucidating the signals that control uterine receptivity and preimplantation could enable the diagnosis and identification of the causes underlying pregnancy loss. This knowledge can also be applied to enhance pregnancy rates in domestic animals and humans.

Hu sheep in the LP_HBB group displayed greater uterine gland density compared to the LP_LBB and LP_LB+ groups ( Figure 1 A,C). The uterine coefficient was higher in the LP_HBB of the Hu sheep group than that in the LP_LB+ group but not in the LP_LBB group ( Figure 1 B). The number of uterine caruncles was higher in the LP_HBB of the Hu sheep group than that in the LP_LBB group but not in the LP_LB+ group ( Figure 1 I). There were no significant differences among the three groups, including endometrial microvascular D (MVD), endometrial ductal gland invaginations (DGI), luminal epithelium (LE) thickness, endometrial thickness, and myometrial thickness ( Figure 1 D–H). Moreover, the level of serum progesterone (P4) was lower in both the LP_HBB and LP_LBB groups of Hu sheep compared to those in the LP_LB+ group ( Figure S1A ). In contrast to the trend for the level of P4, serum placental growth factor (PLGF) appeared to be highest in the LP_HBB group of sheep, followed by the LP_LBB group, and lowest in the LP_LB+ group ( Figure S1D ). There were no differences in the serum levels of estrogen (E2) and prolactin (PRL) in the three groups of Hu sheep ( Figure S1B,C ). By sequencing, we found 378 (245 upregulated and 133 downregulated), 768 (421 upregulated and 347 downregulated), and 1413 (504 upregulated and 909 downregulated) DEGs in LP_HBB VS LP_LBB, LP_HBB VS LP_LB+, and LP_LBB VS LP_LB+, respectively ( Figure S2A–C and Tables S1–S3 ). Functional annotation and analysis were performed using GO ( Tables S4–S6 ) and KEGG ( Figure S2D–F and Tables S7–S9 ). In addition, we conducted a conjoint analysis of laboratory data from the follicular phase with novel data from the luteal phase and found that 9359 (2241 upregulated and 7118 downregulated), 8661 (1981 upregulated and 6680 downregulated), and 8743 (2185 upregulated and 6558 downregulated) DEGs in FP_HBB VS LP_HBB, FP_LBB VS LP_LBB, and FP_LB+ VS LP_LB+ groups, respectively ( Figure S3A–C ), and functional annotation and analysis were performed using GO ( Tables S10–S12 ) and KEGG ( Figure S3D–F and Tables S13–S15 ). These results reveal multiple biological processes and pathways that have the potential to contribute to endometrial receptivity establishment, including, in particular, the GO pathway, i.e., proteolysis, apoptosis, cell proliferation, and cell differentiation, as well as the KEGG pathway, i.e., cell cycle, MAPK, estrogen, and cGMP-PKG signaling pathway. Some key node genes closely related to endometrial receptivity were screened by performing Protein–Protein Interaction Networks (PPI) analysis, including BMP2 , CREB1 , ESR2 , IGF2 , PPP2R2A , PTGS2 , SMAD1 , SMAD2 , STAT3 , and WNT6 ( Figure S4 ). Then, we detected their expression changes in the follicle-luteal transformation process using qRT-PCR and found that BMP2 , CREB1 , ESR2 , IGF2 , PTGS2 , and WNT6 were differentially expressed ( Figure 2 A). Among them, CREB1 has been reported to be closely related to endometriosis and ovarian hormone secretion, and therefore, we selected CREB1 as the object of the following research. The results of qRT-PCR also displayed that CREB1 was expressed at higher levels in the FP_HBB group than in the FP_LBB and FP_LB+ groups, but there was no difference in the LP_HBB, LP_LBB, and LP_LB+ groups ( Figure 2 B,C). To investigate the role of CREB1 in regulating female reproductive processes, we designed specific short interfering RNAs that target CREB1 and constructed an overexpression vector. We discovered that CREB1 siRNAs effectively suppressed its expression, and the overexpression vector significantly increased its expression ( Figure 2 D–G). Interference with CREB1 significantly reduced the mRNA expression levels of PTGS2 , PRL , LIF , HOXA11 , OPN , and VEGF , whereas overexpression of CREB1 significantly increased the mRNA expression levels of PTGS2 , LIF , MMP9 , and BMP2 ( Figure 2 H,I). In addition, the results of immunohistochemistry (IHC) showed that the CREB1 protein was present in all reproductive tissues of ewes, including the hypothalamus, pituitary, oviduct, ovary, and uterus ( Figure 2 J). The CREB1 positive signals have been widely observed in the hypothalamus and pituitary tissues. In the oviduct, the CREB1 protein was present in the glandular epithelium, luminal epithelium, and cilia. In the follicles, no detectable presence of CREB1 was observed in oocytes from the primordial follicle stage onwards, oocyte cytoplasm, and granulosa cells around primary and secondary follicles, whereas a weakly CREB1 positive signal was detected in granulosa cells and theca cells of tertiary follicles. In the uterus, CREB1 was widely expressed in the endometrial luminal epithelium, glandular epithelium, endometrial stroma, and myometrium. Moreover, CREB1 was observed to have the highest expression in the hypothalamus, followed by the uterus, and the lowest expression in the oviduct ( Figure 2 K). Finally, the cellular localization of CREB1 was detected in ESCs by using IF, and the results displayed that the nucleus predominantly contained the majority of it, whereas a minor presence was observed in the cytoplasm ( Figure 2 L). CREB1 interference significantly suppressed cell proliferation, as evidenced by the results obtained from the CCK8 and EdU assays, whereas CREB1 overexpression promoted cell proliferation ( Figure 3 A–C). Compared to the controls, cell cycle research revealed that CREB1 interference increased the proportion of cells in the G0/G1 phase, decreased the proportion of cells in the S phase, and weakly reduced the proportion of cells in the G2/M phase ( Figure 3 D). CREB1 overexpression had contrasting effects on the number of cells in the G0/G1 and S phase ( Figure 3 F). However, consistent with CREB1 interference, CREB1 overexpression also decreased the proportion of cells in the G2/M phase ( Figure 3 F). The results of qRT-PCR revealed that CREB1 interference resulted in a significant reduction in the mRNA expression levels of PCNA , CCND1 , CCND2 , CCND3 , and CCNA1 , except for the significant upregulation of CDK6 , whereas CREB1 overexpression increased the mRNA expression of these genes, except for the significant downregulation of PCNA ( Figure 3 E,G). The Western blotting analysis revealed that CREB1 interference reduced the protein expression levels of PCNA, CDK2, CDK4, CDK6, and CCND1 compared to the negative group, whereas CREB1 overexpression promoted the protein expression of these proteins except CDK6 ( Figure 3 H,I). Compared with the controls, CREB1 interference significantly promoted the apoptosis rate, whereas CREB1 overexpression had the opposite effect ( Figure 4 A,B). The results of qRT-PCR revealed that CREB1 interference increased the mRNA and protein expression of BAX and BCL2 but had no effect on the ratio of BAX/BCL2 ( Figure 4 C,G,H). Moreover, the mRNA expression of CASP3 was also upregulated after CREB1 interference ( Figure 4 C). CREB1 overexpression decreased the mRNA levels of BAX and BAX / BCL2 ratio while increasing the mRNA expression of BCL2 ( Figure 4 D). The Western blotting analysis revealed that CREB1 overexpression led to an increase in BCL2 protein levels and a reduction in the BAX/BCL2 ratio ( Figure 4 I,J). Autophagy and apoptosis are related at multiple levels and are important for maintaining cell homeostasis. Their interactions can be summarized into three types: cooperative, antagonistic, and facilitating. In this study, several important genes/proteins involved in the regulation of autophagy were also examined. The qRT-PCR analysis revealed that the mRNA levels of LC3B , Beclin-1 , ATG5 , and ATG7 were significantly upregulated after interference with CREB1 , whereas the mRNA levels of LC3A , LC3B , and Beclin-1 were significantly downregulated, and the mRNA expression of P62 was remarkably upregulated after overexpression of CREB1 ( Figure 4 E,F). Further Western blot analysis revealed that the ratio of LC3-II/LC3-I, Beclin-1, and ATG7 was significantly upregulated, and the protein expression of P62 was moderately downregulated after interference with CREB1 ( Figure 4 G,H). On the contrary, the protein levels of Beclin-1 and ATG7 were significantly downregulated, and the protein levels of P62 were largely upregulated after overexpression of CREB1 ( Figure 4 I,J). After analyzing the online databases (TargetScan, microT, ENCORI, and miRDB), miR-134-5p was identified as a potential miRNA that targets the CREB1 gene ( Figure 5 A). Subsequently, we performed an analysis to investigate the association between miR-134-5p and CREB1 expression levels. Our findings unveiled a significant negative correlation between them ( Figure 5 B). MiRanda and RNAhybrid analyses revealed a putative seed sequence match between miR-134-5p and the 3′UTR region of CREB1 ( Figure 5 C,D). To explore the potential targeted binding relationship between miR-134-5p and CREB1 , the putative binding site of miR-134-5p within the 3’UTR region of CREB1 was cloned into a luciferase reporter ( Figure 5 E). The results demonstrated a significant decrease in luciferase activities of the CREB1 wild-type reporter upon transfection with miR-134-5p mimics compared to the control reporter. Importantly, the restoration of luciferase activities was observed upon modification the sequence of CREB1 ( Figure 5 F). Although the mRNA level of CREB1 did not change, the protein level of CREB1 was markedly reduced after miR-134-5p upregulation in ESCs ( Figure 5 G,H). Repression of miR-134-5p, conversely, resulted in an increase in both the mRNA and protein levels of CREB1 ( Figure 5 G,H). To investigate the regulatory role of miR-134-5p in female reproductive regulation, we overexpressed or inhibited miR-134-5p in sheep ESCs, and the expression of miR-134-5p was significantly upregulated or downregulated, respectively ( Figure 6 A,B). The overexpression of miR-134-5p increased the percentages of active and proliferating ESCs compared to control mimics, whereas miR-134-5p had the opposite effect ( Figure 6 C-F). Further research found that miR-134-5p overexpression increased the proportion of cells in the G0/G1 phase and decreased the proportion of cells in the S phase, with the converse changes observed upon miR-134-5p inhibition ( Figure 6 G,I). At the same time, miR-134-5p overexpression led to a significant decrease in the mRNA expression levels of CDK4 , CCND1 , CCND2 , and CCNA1 ( Figure 6 H). Inhibiting miR-134-5p significantly upregulated the mRNA expression of PCNA and CCNA1 ( Figure 6 J). The results of Western blotting revealed that overexpression of miR-134-5p significantly decreased the protein expression of PCNA, CDK2, CDK4, CDK6, and CCND1, whereas the inhibition of miR-134-5p increased the protein expression of CDK2 ( Figure 6 K–M). Compared with the controls, miR-134-5p overexpression significantly increased the apoptosis rate, and miR-134-5p interference had the opposite effect at the same time ( Figure 7 A,C). The results of qRT-PCR revealed that miR-134-5p overexpression increased the mRNA expression of BAX , BCL2 , CASP3 , and CASP9 but had no effect on the BAX / BCL2 ratio, whereas miR-134-5p interference decreased the mRNA expression of BAX , CASP9 , and the BAX / BCL2 ratio ( Figure 7 B,D). The additional results of Western blotting revealed that miR-134-5p overexpression resulted in the downregulation of BCL2 protein expression and upregulation of the BAX/BCL2 ratio, whereas miR-134-5p interference showed the opposite results ( Figure 7 G–I). Then, we detected the expression levels of genes and proteins involved in cell autophagy. The results of qRT-PCR showed that miR-134-5p overexpression increased the mRNA expression of LC3B , ATG5 , and ATG7 , while miR-134-5p interference decreased the mRNA expression of LC3A , LC3B , Beclin-1 , ATG7 , and increased the mRNA expression of P62 ( Figure 7 E,F). Further Western blotting analysis showed that miR-134-5p overexpression resulted in the upregulation of LC3-II, Beclin-1, ATG5, and ATG7 protein levels, an increased LC3-II/LC3-I ratio and a reduction in P62 protein levels ( Figure 7 G,H). Conversely, miR-134-5p interference showed an obviously opposite trend ( Figure 7 G,I). To further validate the involvement of miR-134-5p in regulating the positive effects of CREB1 in ESCs, pEX3-CREB1 was used to treat miR-134-5p-overexpressing ESCs. The results showed that the upregulation of CREB1 counteracted the decrease in cell viability and proliferation ability induced by miR-134-5p ( Figure 8 A–C). Furthermore, the upregulation of CREB1 also mitigated the miR-134-5p-induced G0/G1 phase arrest ( Figure 8 D,E). The overexpression of CREB1 , as expected, attenuated cell apoptosis induced by transformation with miR-134-5p mimics ( Figure 8 F,G). Moreover, qRT-PCR and Western blotting assays confirmed our previous results ( Figure 8 H–J).

Fecundity is one of the most important economic factors in sheep breeding and reproduction [ 9 ]. Ovulation rate and endometrial receptivity are two of the most crucial factors that influence fecundity. However, very few studies have been performed on the endometrial receptivity linked to ewe fecundity. In the present study, we found that in the luteal phase, high-fertility Hu sheep had a higher uterine coefficient, a richer uterine gland density, and a larger number of uterine caruncles than low-fertility Hu sheep. Ten genes associated with endometrial receptivity were considered in this study. In recent reports, the roles of CREB1 in mediating the development of endometriosis have been noteworthy [ 35 , 36 , 41 ]. Gain-of-function and loss-of-function assays revealed that CREB1 markedly affected the expression level of endometrial receptivity marker genes in ESCs, promoted endometrial stromal cell proliferation, and inhibited cell apoptosis and autophagy. Further mechanistic exploration revealed that CREB1 expression was regulated by miR-134-5p in ESCs. Correspondingly, these data suggested that miR-134-5p-mediated CREB1 might participate in the formation of endometrial receptivity by regulating the function of ESCs. The presence of uterine glands and their secretions play a crucial role in facilitating the establishment of uterine receptivity and the successful implantation of blastocysts [ 42 ]. Moreover, the endometrial microvessels and uterine volume are two critical indexes to evaluate endometrial receptivity [ 43 , 44 ]. Consistent with our findings in the follicular phase [ 40 ], we found that the uterine gland density and uterine coefficient of high-fertility Hu sheep were higher than that of low-fertility Hu sheep in our study, which is essential for enhancing the secretion ability of the endometrium, forming greater fetal capacity, and rich nutrition supply to maintain large litters. As reported, Lawrenz et al. demonstrated that the expression of the PLGF gene was higher in the endometrium of women with successful implantation compared to women who had a good endometrium but failed implantation [ 45 ]. In addition, it has been reported that human cytotrophoblast cells promoted endothelial cell survival and vascular remodeling by secreting PLGF, and its expression was firmly correlated with MVD in the evaluation of pathological angiogenesis [ 46 ]. As a result, the high-fertility Hu sheep may have greater angiogenesis, which is mainly due to the influence of the maternal placenta. To some extent, these data demonstrate that the endometrial receptivity of high-fertility Hu sheep was better than that of low-fertility Hu sheep. Previous studies have reported several key pathways that are closely related to sheep reproductive performance, including the MAPK, Wnt, ECM-receptor interaction, cGMP-PKG, Calcium, and cAMP signaling pathways [ 40 , 47 , 48 , 49 , 50 , 51 , 52 , 53 ]. In our KEGG pathway analysis, we also screened these pathways. Then, a number of important genes that are closely related to fertility and uterine receptivity were focused on, including BMP2 , CREB1 , ESR2 , IGF2 , PPP2R2A , PTGS2 , SMAD1 , SMAD2 , STAT3 , and WNT6 . Luo et al. reported that BMP2 played an important role in human endometrial remodeling by increasing the expression of IGFBP3 and MMP2 [ 54 ]. Smad1/5 cKO mice showed endometrial receptivity defects and perturbed embryo implantation, and Smad2/3 cKO mice showed endometrial disorders, sterility, and uterine cancer [ 55 , 56 ]. In humans, studies on CREB1 and ESR2 showed that they indirectly promoted the development of endometriosis [ 36 , 57 , 58 ]. A recent study indicated that the proper preparation of the uterus for implantation requires the sequential activation of uterine epithelial IGF1R by stromal IGF1 and embryonic IGF2 [ 59 ]. PPP2R2A has been demonstrated to promote implantation of embryos in vitro and in vivo, respectively, via Ppp2r2a knockout mice and function gain and loss assays of PPP2R2A in sheep ESCs [ 60 , 61 ]. PTGS2 was reported to be more abundant in repeat breeder cows (RBC) than in non-RBC and is involved in the regulation of some protein markers in the in vitro endometrial receptivity of endometrial epithelial cells (EEC) in dairy goats [ 62 , 63 ]. Hiraoka et al. reported that the collaborative regulation of uterine receptivity and embryo attachment involves distinct pathways utilized by epithelial and stromal STAT3, resulting in synergistic effects [ 64 ]. WNT6 demonstrated a higher abundance in polytocous Hu sheep than in monotocous Hu sheep and promoted uterine gland organogenesis by regulating the cell process of endometrial epithelial cells [ 40 , 65 ]. These events suggest that the above genes may contribute to the differences in litter size by regulating the establishment of endometrial receptivity in Hu sheep. Compared with normal endometrial tissues, CREB1 has a higher expression level in ectopic endometrial tissues, and it affects endometrial cell motility, growth, and invasion under endometriosis (EMS) [ 35 , 36 ]. In addition, patients with clinically diagnosed EMS typically have reduced endometrial receptivity, expressed as abnormal expression of endometrial genes, sex hormone receptors, and cell adhesion molecules [ 37 ]. In our experiments, a significantly higher expression of CREB1 was observed during the follicular phase in comparison to the luteal phase. Combined with previous research, we suspected that lower expression of CREB1 is more likely to maintain good uterine receptibility in the luteal phase. However, interference with CREB1 significantly downregulated the expression level of several key genes regulating endometrial receptivity, including PTGS2 , PRL , LIF , HOXA11 , OPN , VEGF , MMP9 , and BMP2 [ 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 , 74 ], which seems to be contrary to previous assumptions. The reason may be that the establishment of endometrial receptivity is itself a very complex process, and the downstream molecule changes caused by different phases are not consistent. In cellular experiments, we observed that silencing of CREB1 suppressed the proliferation of ESCs by blocking the G1 transition to the S phase. Available evidence indicates that CREB1 activation positively regulates cell survival by regulating some cyclins, which were observed in our present studies, such as CDK2 , CDK4 , CDK6 , and CCND1 [ 75 , 76 , 77 ]. Moreover, our results showed that CREB1 affected the apoptosis in ESCs mainly via the regulation of the BAX/BCL2 ratio, which directly determines the openness of various channels in the mitochondrial outer membrane [ 78 ]. Consistent with our observations, Zhang et al. found that knockdown of CREB1 promoted apoptosis in mouse granulosa cells in combination with a decrease in BCL2 and an increase in BAX [ 77 ]. In a study of therapeutics targeting cancers, mTOR activation triggered CREB1 phosphorylation and accumulation, and inhibiting CREB1 led to a decrease in ATG7 , which is a key factor in autophagy regulation [ 79 ]. In the present study, the opposite trend of ATG7 was observed in our results after CREB1 knockdown. Several studies have reported inconsistent effects of CREB1 on cancer cells and normal cells, which may explain the discrepancy between our results and those of other researchers. However, our detection methods for apoptosis and autophagy are not comprehensive enough due to the specificity of the sheep species, and the application of model animals will provide the possibility to further explore the deep molecular mechanisms of CREB1. Although we have some limitations in the detection method, our present results are sufficient to conclude that CREB1 positively affected the function of ESCs by promoting the G1 to S phase transition and inhibiting apoptosis and autophagy. The miRNA-meditated regulation of mRNAs has a significant influence on endometrial function. The inhibition of NDRG1 by miR-182-5p in humans, for instance, leads to the disruption of embryo implantation via the activation of the NF-κB/ZEB1/E-cadherin pathway [ 80 ]. Additionally, miR-182 aids in receptive endometrium development in dairy goats by downregulating PTN expression [ 81 ]. The regulatory association between miR-134-5p and CREB1 was elucidated via the integration of bioinformatics prediction, qRT-PCR analysis, Western blotting techniques, and luciferase reporter assays. The miR-134-5p has also been identified as a potential circulating biomarker for endometriosis [ 82 ], and the relationship between CREB1 and miR-134-5p has been extensively documented in the existing literature. Yang et al. showed that miR-134-5p directly targets CREB1 to reduce infarct-induced cardiomyocyte apoptosis [ 83 ]. Consistent with these observations, our data suggested that the upregulation of CREB1 mitigated the detrimental effects induced by miR-134-5p overexpression in ESCs. Therefore, miR-134-5p was involved in regulating the function of ESCs by modulating CREB1 expression. Currently, miRNA is mainly regulated at four levels: epigenetic, transcriptional, post-transcriptional, and degradation. At the transcriptional level, the transcription factor (TF)-miRNA interaction network has been extensively studied. For example, Okada et al. found that the transcription factor p53 can negatively regulate miR-34a expression. Additionally, the presence of miR-34a can suppress the expression of the p53 negative regulator HDM4, thus forming a positive feedback pathway, which is conducive to the formation of tumors [ 84 ]. Therefore, miR-134-5p may also be regulated by CREB1, and the two form positive and negative feedback loops to work together.

In conclusion, we have shown that it was relatively easier to establish excellent endometrial receptivity in high-fertility Hu sheep compared to low-fertility Hu sheep. The results of transcriptome sequencing suggested some vital genes were involved in the establishment of endometrial receptivity. Importantly, the preliminary investigation suggests that the influence of CREB1 on the fertility of ewes represents a promising and hitherto unexplored determinant. It was regulated by miR-134-5p and may contribute to the establishment of endometrial receptivity by modulating the function of ESCs. Notwithstanding the positive outcomes observed, it is imperative to acknowledge certain limitations inherent in this study. For the in vitro experiments, a single cell type was exclusively utilized, disregarding potential intercellular interactions or paracrine signaling mechanisms. In addition, future in vivo validation is needed to confirm these conclusions. Despite its limitations, the present study provides crucial support for comprehending the regulatory mechanism of CREB1 mediating endometrial receptivity and provides an effective platform for studying the regulation mechanism of fertility in sheep.