A Dynamic Shift in Estrogen Receptor Expression During Granulosa Cell Differentiation in the Ovary.

This study uncovers a dynamic shift in estrogen receptor expression during granulosa cell (GC) differentiation in the ovary, highlighting a transition from estrogen receptor alpha (ESR1) to estrogen receptor beta (ESR2). Using a transgenic mouse model with Esr1-iCre-mediated Esr2 deletion, we demonstrate that ESR2 expression is absent in GCs derived from ESR1-expressing ovarian surface epithelium (OSE) cells. Single-cell analysis of the OSE-GC lineage reveals a developmental trajectory from Esr1-expressing OSE cells to Foxl2-expressing pre-GCs, culminating in GCs exclusively expressing Esr2. Transcriptome analyses identified vasculature-derived TGFβ1 ligands as key regulators of this transition. Supporting this, TGFβ1 treatment of cultured embryonic ovaries reduced Esr1 expression while promoting Esr2 expression. This study underscores the capability of GCs to switch from ESR1 to ESR2 expression as a fundamental aspect of normal differentiation.

estrogen receptors, ovary, granulosa cells, cell lineage Nuclear estrogen receptors (ESR), essential mediators of the classical functions of 17β-estradiol (E2), are categorized into 2 distinct types: ESR1 (estrogen receptor alpha, ERα) and ESR2 (ERβ). These receptors regulate cell proliferation and differentiation across various organs under diverse physiological and pathological conditions, a role that has been extensively studied over the past 3 decades (1-5). Research involving selective ESR agonists/antagonists (6) and genetically modified mice (7) has primarily identified ESR1 as the key mediator of E2's effects. Nonetheless, both receptor subtypes are widely expressed in estrogen-responsive organs, often localized to distinct cell types. For instance, in the hypothalamus, gonadotropin-releasing hormone (GnRH) neurons predominantly express ESR2, while kisspeptin neurons express ESR1 (8, 9). Similarly, in adult ovaries, ESR2 is predominantly found in granulosa cells (GCs), whereas ESR1 is localized to the surface epithelium (OSE), interstitial cells, and theca cells (10-12). Recent studies have highlighted the importance of not only the individual roles of E2 through ESR1 or ESR2, but also the significance of their simultaneous activation or specific temporal sequences (13-20). However, the question of whether both receptors can coexist within the same cell remains a major focus of ongoing investigation. Activation of ESR1 and ESR2 often results in opposing effects on cell proliferation, apoptosis, and tumor progression (21-24). This dichotomy is exemplified in the “yin-yang” hypothesis (22, 23), which suggests that while ESR1 generally promotes cell proliferation, ESR2 acts as a physiological brake, inhibiting cell proliferation or even inducing apoptosis. A key role of ESR2 within the ovary is to regulate the activation of primordial follicles, ensuring that activation occurs at the appropriate time and preventing premature or excessive activation (25-27). Dysregulated expression of either receptor can lead to serious health issues. For instance, hormone-dependent tumors, including breast and prostate cancers, often display altered expressions of these receptors, contributing to disease progression (28, 29). In normal breast tissue, fewer than 10% of epithelial cells express ESR1; however, in breast tumors, 50% to 80% of epithelial cells exhibit ESR1 expression (30). Moreover, anti-hormonal therapies targeting ESR1 are frequently used to treat breast cancer patients with ESR1-positive cancer cells (31, 32). In prostate cancer, ESR2 mediates the protective effects of E2 by inhibiting proliferation, promoting differentiation, and inducing apoptosis (33). Conversely, ESR1 contributes to the detrimental effects of E2, including aberrant proliferation, inflammation, and the development of malignancy (33, 34). Ablation of ESR2 expression in mice has been shown to induce pituitary and ovarian tumors with 100% penetrance within 2 years (35). Furthermore, in a mouse model of endometriosis, selective activation of ESR2 resulted in a reduction or even complete regression of lesions in 40% to 75% of cases (36). Given these findings, there is growing interest in the therapeutic potential of ESR2 activation (37-41). Drugs specifically targeting ESR2 are being explored as treatments for conditions such as endometriosis and breast cancer (36, 42). In the developing embryonic rat ovary, ESR1 expression decreases gradually until postnatal day (PND) 12, whereas ESR2 expression increases thereafter (43). During embryonic development, ESR1 is expressed in interstitial cells and OSE, while ESR2 is barely expressed in any of the ovarian cells (44). After birth, ESR2 expression increases in GCs (43, 44), suggesting that ESR1 and ESR2 are expressed in different subsets of ovarian cells in a time-dependent manner. Mork et al (45) proposed the existence of 2 distinct waves of GC differentiation in the embryonic ovary, demonstrating that GCs from the second wave originate from the OSE and that these OSE-derived cells express the GC marker Forkhead Box L2 (FOXL2). Rastetter et al (46) and Stevant et al (47) discovered that OSE-derived cells express the marker gene Leucine Rich Repeat Containing G Protein-Coupled Receptor 5 (LGR5) and subsequently differentiate into FOXL2+ pre-granulosa cells (pre-GCs). Recent studies using single-cell RNA sequencing (scRNA-seq) in human cells have confirmed the presence of ESR1 in pre-GCs of the human fetal ovary (48). Based on these findings, we hypothesized that during ovarian development, cells within the GC lineage undergo a transition from expressing ESR1 to expressing ESR2. This implies that ESR1-expressing cells in the OSE can differentiate into GCs that eventually express only ESR2. To test this hypothesis, we employed a transgenic Esr1-iCre mouse model to selectively delete Esr2 in the GCs of the ovarian follicle. Our study confirmed a switch from ESR1 to ESR2 expression within the GC lineage, with vasculature-derived transforming growth factor β1 (TGFβ1) identified as a contributing factor to this transition.

Ethics Statement All mice used were on a C57BL/6 genetic background, bred at the University of Illinois Division of Animal Resources, and maintained under controlled lighting (14 hours light/10 hours dark) with continuous access to food and water. This study was carried out in accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health. Animal protocols were approved by the University of Illinois Animal Care and Use Committee (Protocols #14222 and #17185), and all efforts were made to minimize animal suffering. Animal models generated in this study will be made readily available to the research community. Animals Previously, we developed transgenic mouse lines that express an improved Cre (iCre) recombinase under the regulation of the natural Esr1 (a gene that encodes Esr1, a mouse homolog of human ESR1) promoter (49). The Esr1-iCre (Esr1iCre/wt; B6(Cg)-Esr1tm1.1(iCre)Jako/J) mouse line was then crossed with another mouse line with floxed Esr2 (Esr2flox/flox) (13). Successive back-crossings of the resulting heterozygote (Esr1iCreEsr2flox/wt) mice with Esr2flox/flox mice resulted in a double mouse line that is deficient of Esr2 expression in the Esr1-lineage cells (Esr1iCre/wtEsr2flox/flox or Esr1-Esr2KO). In order to track ESR1-lineage cells, Esr1-iCre (Esr1iCre/wt) mice were crossbred with Ai9tdTomato (B6129S6-Gt(ROSA)26Sortm9(CAG-tdTomato)Hze/J) mice (50), and from the resulting Esr1iCre/wtAi9tdTomato mice, ESR1-lineage-specific fluorescence signals were observed under the microscope. Mouse genotypes were determined by polymerase chain reaction (PCR). Tissue from ear pinna was obtained by an ear punch and DNA was extracted with an Easy DNA kit (Invitrogen, Carlsbad, CA) according to the manufacturer's instructions. Amplification of the floxed Esr2 gene was performed as previously described (13). Also, hetero- or homozygous for Esr1-iCre was determined as previously described (49). PCR amplicons were run on a 2% agarose gel with GelRed (Biotium, No. 41003) at 100 mV for 25 minutes and visualized under UV light. To detect ESR2, Esr2-iCre (Esr2iCre/wt; B6(Cg)-Esr2tm1.1(icre)Jako/J) mouse line was used (51). Mouse genotypes were determined as described above. Ovulatory Capacity Measurement and Fertility Assay To characterize the reproductive phenotype of wild-type (WT) and Esr1-Esr2KO, ovulatory capacity measurement and fertility assay were performed after PND 25. Female mice were superovulated by intraperitoneal injection of 5 IU pregnant mare's serum gonadotropin (Sigma-Aldrich, No. G4877), and 48 hours later, the mice were injected with 5 IU human chorionic gonadotropin (hCG; Sigma-Aldrich, No. CG10). The mice were euthanized at 20 hours and 48 hours after injection of hCG for quantification of ovulated oocytes and observation for corpora lutea, respectively. Ovulated oocytes were collected from the oviduct. Fertility of 2- to 4-month-old WT and Esr1-Esr2KO (Esr1iCre/wtEsr2flox/flox) mice was determined by housing a proven breeder male with one Esr1-Esr2KO and one WT female for 10 days. Cages were inspected daily for the presence and size of litter. The outcome of the fertility test was determined after 30 days. Percent fertility was calculated as the number of females that gave birth divided by the total number of females in the group. Real-Time PCR The expression levels of Esr1 and/or Esr2 mRNA in the GCs isolated from PND 25 WT and Esr1-Esr2KO mice by follicle puncture method and in vitro cultured ovaries were determined by real-time PCR (RT-PCR). Total RNA was extracted using RNAqueous®-Micro Kit (Invitrogen, No. AM1931) according to the manufacturer's protocol. Concentrations of RNA were measured with a NanoDrop 1000 spectrophotometer (Thermo Fisher Scientific) and diluted to equal concentrations. RNA was reverse transcribed using a high-capacity cDNA reverse transcription kit (Applied Biosystems, No. 4368814). PCR reactions were performed with Power SYBR® Green PCR Master Mix (Applied Biosystems, No. 4367659) according to the manufacturer's protocol. Target specific PCR primers were used for quantification of Rpl19 (housekeeping; product size: 73 bp; 5′-CCT GAA GGT CAA AGG GAA TGT-3′ and 5′-GTC TGC CTT CAG CTT GTG GAT-3′), Esr1 (product size: 167 bp; 5′-GCC AAG GAG ACT CGC TAC TG-3′ and 5′-CTC CGG TTC TTG TCA ATG GT-3′), Esr2 (product size: 176 bp; 5′-CAG AGA GAC CCT GAA GAG GA-3′ and 5′-CCT TGA ATG CTT CTT TTA AA-3′), Foxl2 (product size: 143 bp; 5′- AAC ACC GGA GAA ACC AGA CC-3′ and 5′- CGT AGA ACG GGA ACT TGG CT-3′), and Inha (product size: 122 bp; 5′-GGG GAT CCT GGA ATA AGG CG-3′ and 5′-GTG GCA CCT GTA GCT GGG AA-3′) mRNA levels. Fluorescence was measured using the ABI prism 7500 quantitative real-time thermocycler (Applied Biosystems). The delta delta Ct (ΔΔCt) method was used to calculate the relative expression level. Ct values of each sample were retrieved then, 2 raised to the power of negative delta delta Ct (2^−ΔΔCt) was calculated. Results were expressed as fold differences in relative gene expression to the control group. To represent the fold change of the experimental group relative to the control group, the mean of the control group was normalized to 1. The same normalization factor was then applied consistently across all experimental results. The melt-curve analysis takes place after a quantitative PCR (qPCR) run and serves to verify that the fluorescence detected during the run comes from a single amplicon. Then, the PCR product was subjected to electrophoresis to confirm the presence of a single band of the designed size. Single-Cell RNA-seq Library Preparation and Library Preprocessing Ovaries were collected from 4 animals at embryonic day 16.5 (E16.5), PND7, and PND14 to investigate the differential gene expression in individual ovarian cell types. Ovaries from the same age group were pooled and dissociated by collagenase, following previously described protocols (52). Briefly, ovaries were removed, cut into small pieces, transferred to 2 mL of collagenase digestion solution containing 3.5 U of collagenase type I (Invitrogen, No. 17100-017), 1000 U of deoxyribonuclease I (Sigma-Aldrich, No. D4527), and 40 mg of bovine serum albumin (BSA) (Sigma-Aldrich, No. 017K0723) in Medium 199 (Hanks’ Balanced Salts; Life Technologies, No. 12350-039), then placed in a water bath at 37 °C for 30 minutes. After incubation, tissues were further dissociated by repeatedly passing them through an 18-G needle attached to a 3-mL syringe. Then, the digested tissue suspension was filtered through a 40-μm filter, centrifuged at 300g for 5 minutes, then resuspended in 1 mL of phosphate-buffered saline (PBS) containing 1% BSA. Single-cell suspensions with a viability of > 90% by Trypan Blue staining on the TC20 Automated Cell Counter (Bio-Rad Laboratories, No. 1450102) were converted into individually barcoded cDNA libraries with the Single-Cell 3′ Chromium kit version 2 from 10X Genomics (No. PN-120267) following the manufacturer's protocols. The 10X Chromium instrument separates thousands of single cells into gel bead emulsions that add a barcode to the mRNA from individual cells. Following ds-cDNA synthesis, individually barcoded libraries compatible with the Illumina chemistry were constructed. The final libraries were quantitated on Qubit and the average size was determined on the AATI Fragment Analyzer (Advanced Analytics). Libraries were pooled evenly, and the final pool was diluted to 5 nM concentration and further quantitated by qPCR on a Bio-Rad CFX Connect Real-Time System (Bio-Rad Laboratories). The final library pool was sequenced on a 2 × 150 nt lane of an Illumina HiSeq 4000. Base-calling and demultiplexing of raw data were done with the mkfastq command of the software Cell Ranger 2.2.0 (10x Genomics). Single-cell expression was initially analyzed using the Cell Ranger Single Cell Software Suite (v2.1.1) to perform quality control, sample de-multiplexing, barcode processing, and single-cell 3′ gene counting. Sequencing reads were aligned to the UCSC mm10 mouse transcriptome using the Cell Ranger suite with default parameters. Samples were merged using Cellranger aggregate function with default parameters. A total of 459, 510, and 585 single cells were analyzed from 3 different samples of ovarian cells from E16.5, PND 7, and PND 14, respectively. Mean raw reads per cell were 256 281, 222 746, and 199 636 in each sample. Median genes per cell were 3667, 3696, and 3332 in each sample. Further analysis was performed in R (v3.5) using the cellrangerRkit (v2.2.0), Seurat package (v3.0.0), and Monocle package (v2.8.0) (53, 54). Single-Cell RNA-seq Data Analysis The analysis in this section was performed using Seurat package (53). Feature barcode matrices from each data set were imported using Read10x and CreateSeuratObject functions. For each cell, a minimum expression of 200 genes was applied to filtered uninformative cells. For each gene, a minimum of 3 cells expression was applied. After log-normalization using NormalizeData function, we selected highly variable genes based on the average expression and dispersion per gene using FindVariableGenes function with parameters x.low.cutoff = 0.01, x.high.cutoff = 3, and y.cutoff = 0.5. Dimensionality reduction and visualization for the 10x data were performed using t-distributed stochastic neighbor embedding (t-SNE) for cells (55). The first 10 principal components of the high-variance genes were used as input for the t-SNE algorithm with the following default settings. Clustering on the t-SNE embedding was performed using FindClusters function with “resolution = 0.6.” Cells were labeled by their group name, E16.5, PND 7, and PND 14. Ovarian cell types were determined by known cell type-specific marker genes (47, 56). Cell type-specific differential gene expression was determined by FindMarkers function and visualized by Featureplot. Differential gene expression between clusters was tested by default “bimod” likelihood ratio test using FindMarkers function (cutoff, avg_logFC > 0.25, avg_logFC < −0.25, p_val_adj < 0.05) (53, 57). Cell trajectory by pseudotime was performed by Monocle package. Feature barcode matrices from each data set were imported using load_cellranger_matrix and newCellDataSet() functions with lowerDetectionLimit = 0.5. Cells were filtered by detectGenes function with min_expr = 0.1. Data was standardized to Z-distribution. Dimensionality reduction and visualization for the 10x data were performed using t-SNE for cells (55). The first 10 principal components of the high-variance genes were used as input for the t-SNE algorithm with the following default settings. Clustering was performed by the clusterCells function. After adding vector to phenotypic data using the differentialGeneTest function, cells were grouped by cell type. After isolating OSE-GC cells from the data, dimensionality reduction was performed using DDRTree for cell trajectory. Lgr5+ cells were assigned as a root state using the orderCells function. Results were visualized using plot_cell_trajectory and plot_cell_clusters functions. General Histology, Immunohistochemistry, and Immunofluorescence Mice were humanely euthanized by CO2 asphyxiation followed by cervical dislocation. Collected tissue was immediately fixed in 4% paraformaldehyde for 24 hours. Tissues were washed with ethanol, processed, and embedded in paraffin wax. Paraffin-embedded tissue blocks were sectioned 6 μm thickness. For general histological observation, slides were stained with hematoxylin and eosin staining. Immunolabeling of ESR2 was done in the following manner: deparaffinization was followed by heat-induced antigen retrieval in 10mM sodium citrate buffer (pH 6.0), then tissues were then immersed in cold PBS and treated with 0.5% Triton-X in PBS for 15 minutes. Endogenous peroxide was quenched with 3% H2O2 in methanol and incubated in 3% BSA for 10 minutes. Tissue slides were incubated overnight with in-house anti-ESR2 antibody (58, 59), secondary biotinylated rabbit anti-chicken antibody (Thermo Fisher Scientific, No. 31720, RRID:AB_228383), and avidin-biotin complex solution (Vector labs, No. PK-6100, RRID:AB_2336819) at room temperature for 1 hour. Antibody washes were done with a 0.1% Nonidet P 40 substituent solution (Sigma-Aldrich, No. 74385) in PBS. 3,3′-diaminobenzidine (DAB; Vector Labs, No. SK-4100) was applied until color optimally developed. Immunolabeling of FOXL2 and ESR1 was done in the following manner: deparaffinization was followed by heat-induced antigen retrieval in 10mM sodium citrate buffer (pH 6.0), endogenous peroxide quenching in 3% H2O2, and antibody and endogenous biotin blockage by 5% rabbit/goat serum with avidin (200 μL/1 mL; Vector Labs, No. SP-2001). Tissue slides were incubated with anti-FOXL2 antibody (Abcam, No. ab5096, RRID:AB_304750) and/or anti-ESR1 antibody (Millipore-Sigma, No. 06-935, RRID:AB_310305), and secondary biotinylated goat anti-rabbit or rabbit anti-goat antibody (Vector labs, No. PK-6101/PK-6105, RRID:AB_2336820/AB_2336824) and avidin-biotin complex solution (Vector labs, No. PK-6100) at room temperature. DAB solution was applied until color optimally developed. Slides were then counter-stained with hematoxylin, mounted, and imaged with an Olympus BX51 microscope (Olympus). For immunofluorescence labeling of TdTomato, FOXL2, and ESR1 in the embryonic ovary, paraffin-embedded tissue blocks were sectioned at 6 μm thickness. After hydration, immunolabeling of each antibody was done in the following manner: heat-induced antigen retrieval in 10mM Tris-EDTA buffer (pH 9.0), endogenous peroxide quenching in 3% H2O2, and blockage by 5% donkey serum. Slides were incubated with the anti-tdTomato antibody (LSBio, No. LS-C340696, RRID:AB_2819022), anti-FOXL2 antibody (Abcam, No. ab5096), or anti-ESR1 antibody (Millipore-Sigma, No. 06-935) diluted 1:100 in 2.5% normal donkey serum in a humidified chamber overnight at 4 °C. After washing 3 times, nuclear staining and mounting were conducted with ProLong Gold (Invitrogen, No. P36930) containing DAPI. Slides were observed under an A1 confocal microscope (Nikon) equipped imaging system. For immunofluorescence labeling of CRE, TGFβ1 and ESR1 in embryonic ovaries, ovaries from E16.5 and E18.5 were fixed with 4% paraformaldehyde (pH 7.4) and transferred to 30% sucrose solution overnight. The samples then froze in the optimal cutting temperature compound. Sections were taken at 7 μm by using cryostat. Frozen slide sections were fixed with 4% PFA at room temperature for 20 minutes, washed with PBS twice for 5 minutes, and permeabilized with 0.1% tween-20 at room temperature for 20 minutes. After washing with PBS 3 times for 5 minutes, samples were incubated in 2% BSA in PBS solution for 1 hour at room temperature. Then, samples were incubated with primary antibodies (anti-PECAM1, BD Pharmingen, No. 553370, RRID:AB_396660; anti-FOXL2, Abcam, No. ab5096, RRID:AB_304750; anti-TGFB1, Thermo Fisher Scientific, No. PA1-9574, RRID:AB_2201915; anti-ESR1, Millipore-Sigma, No. 06-935, RRID:AB_310305; anti-CRE, Cell Signaling, No. 15036, RRID:AB_2798694) at 4 °C overnight. After washing with PBS 3 times for 5 minutes, they were incubated with secondary antibody (Donkey Anti-rat IgG (H + L)-Alexa Fluor 488, Invitrogen, No. A-21208, RRID:AB_141709; Donkey Anti-chicken IgY (H + L)-Alexa Fluor 647, Jackson Immunoresearch, No. 703-605-155, RRID:AB_2340379; Donkey Anti-rabbit IgG (H + L)-Cy5, Jackson Immunoresearch, No. 711-175-152, RRID:AB_2340607; Donkey Anti-goat IgG (H + L)-Alexa Fluor 546, Invitrogen, No. A-11056, RRID:AB_2534103) for 1 hour at room temperature in dark conditions. After washing with PBS 3 times for 5 minutes, they were mounted with antifade reagent. Slides were observed using Zeiss LSM710 confocal microscope (Carl Zeiss AG). Gonad Isolation and Culture Gonads were isolated from E18.5 female mice. A total of 16 ovaries, collected from 8 fetuses, were washed with PBS then divided in half using a fine needle and cultured in Ham's F-12/DMEM (1:1) media containing 10% charcoal-stripped FBS, 27.5 µg/mL transferrin, 5 U/mL penicillin, and 5 µg/mL streptomycin. Recombinant Mouse TGFβ1 (10 ng/mL; R&D systems, No. 7666-MB), LY-2157299 (TGFβ receptor I inhibitor; 10 μM; R&D systems, No. 6956), or their combination were added to the gonad culture. After 3 hours, cultured tissues were collected and kept at −70 °C until use. The experiment was conducted in 3 separate rounds, and a total of 10 ovarian cultures per group were used. Image Analysis/Immunostaining Quantification To compare the co-localization of ESR1 and FOXL2 in different regions of the E16.5 ovary, the Colocalization Finder plugin in ImageJ (NIH) open-source software was utilized (60). The results were expressed as an average total signal intensity in the measured area and overlap coefficient (r). For the quantification of TGFβ1-ir, a relative intensity of fluorescence was measured from 3 different regions of the medulla, intermediate, and cortex of ovaries at E16.5 and E18.5. The average measurements of the medulla, intermediate, and cortex regions for each sample were calculated and used as the result value for each individual. The fluorescence measurement was performed in an identical area (72 × 60 µm) for each region. The acquired images were processed and analyzed using the ImageJ (NIH) open-source software. Both experiments were conducted using the middle part (the widest tissue section from the entire serial section) of the left ovaries obtained from 3 different individuals per group. Statistical Analysis All sample sizes can be found in figure legends. Data analyses were performed using Microsoft Excel, GraphPad Prism, and SPSS version 18.0. Continuous data were tested for normal distribution by a Shapiro-Wilk test. All normally distributed continuous data were analyzed with parametric tests (Student t test or one-way ANOVA with Tukey post hoc test). Data are graphically presented as the mean and SD or standard error of the mean. Statistical significance was accepted when P values were lower than 0.05.

Granulosa Cells Originate From ESR1+ Lineage Cells The potential derivation of GCs from ESR1+ lineage cells during ovarian development in mice was investigated using a double transgenic mouse model, Esr1iCreAi9. This model was created by crossbreeding Esr1iCre mice (49) with Ai9tdTomato mice (50). In Esr1iCreAi9 mice, red fluorescent protein (RFP) is expressed in the cytoplasm of ESR1+ lineage cells, initiating at the onset of ESR1 expression and persisting even after its cessation. Examination of the developing ovary at embryonic day (E) 16.5 revealed RFP expression in OSE cells and a subset of FOXL2+ GC lineage cells (Fig. 1A), thereby confirming the ESR1+ origin of GCs. Notably, at E16.5, double immunostaining with antibodies against ESR1 and FOXL2 showed that some FOXL2+ cells co-expressed ESR1, while others did not (Fig. 1B). Given that FOXL2+ cells differentiate into GCs, these findings suggest that a specific subset of GC lineage cells expressing ESR2 may originate from ESR1+ lineage cells. The co-localization of ESR1 and FOXL2 was compared in the cortex, intermediate, and medullary regions. The analysis revealed that the expression intensity of FOXL2 was highest in the medullary region, whereas ESR1 was most strongly expressed in the cortex region. The co-localization of ESR1 and FOXL2 was found to be highest in the medullary region (Fig. 1C). These results indicate that at E16.5, the cells expressing FOXL2 are still expressing ESR1 in the medullary region of the ovary. However, ESR2 expression was absent in FOXL2-positive cells prior to PND4 but became detectable from PND4 onward (Supplementary Fig. S1) (61), consistent with previous findings (10). This observation supports the hypothesis that the transition from ESR1 to ESR2 expression in the GC lineage cells expressing FOXL2 might occur through a discontinuous process. ESR1+ Lineage-Specific Esr2 Deletion Ablates ESR2 Expression in GCs The hypothesis that GCs originate from ESR1+ lineage cells was tested using mice in which the Esr2 gene was selectively deleted in the ESR1+ lineage. This strain of mice was created by crossbreeding a floxed Esr2 (Esr2flox) strain of mice (14) with an Esr1iCre strain that expresses Cre recombinase under the endogenous promoter of the Esr1 gene (49). The resulting mouse (Esr1iCre/Esr2flox/flox) was named Esr1-Esr2KO for Esr1-driven Esr2 knockout (KO). Ovarian analysis of Esr1-Esr2KO mice revealed the presence of multiple follicle stages; however, neither Esr2 mRNA nor ESR2 protein was detected in the entire GC population (Fig. 2A and 2B). This finding strongly supports the conclusion that the majority of GCs originate from the ESR1+ cell lineage. The absence of ESR2 expression in female Esr1-Esr2KO mice was corroborated by comparing their reproductive phenotypes with those of global Esr2KO mice (62). As established, ESR2 expression in GCs is crucial for ovulation (62, 63). Consequently, Esr1-Esr2KO female mice exhibited infertility (Fig. 2C), lacked corpora lutea in their ovaries (Fig. 2D), and failed to ovulate upon exogenous gonadotropin administration (Fig. 2E). These results further show that the ESR2 expression in GCs is essential for ovulation and fertility. Collectively, the evident absence of ESR2 expression in GCs and the reproductive phenotypes of Esr1-Esr2KO mice provide direct and compelling evidence supporting the derivation of GCs from ESR1+ lineage cells. Esr1 + Ovarian Surface Epithelial Cells Contribute to the Esr2+ GC Population In the fetal mouse ovary, a distinct subset of Lgr5+ OSE cells migrates toward germ cells, actively contributing to the formation of primordial follicles (45, 47, 64). To explore whether this OSE-GC lineage undergoes the ESR1 to ESR2 transition, we employed scRNA-seq to analyze the temporal expression patterns of Esr1 and Esr2 genes within this lineage at E16.5, postnatal day 7 (PND7), and PND14. At E16.5, 2 major stromal somatic cell types were identified: Foxl2+ pre-GCs and Col1a2+ interstitial cells (Fig. 3A and 3B). Within the OSE cells (Krt18+), 2 subpopulations were observed: Lgr5+ and Lgr5−. Notably, some Foxl2+ pre-GCs were Lgr5+, while others were Lgr5−. By PND7, the majority of anti-Müllerian hormone-positive (Amh+) GCs, a marker for GCs, expressed Esr2, with a minority still expressing Esr1. Concurrently, most Lgr5+ OSE cells predominantly expressed Esr1 rather than Esr2 (Fig. 3C and 3D). This analysis highlights a developmental trajectory where Lgr5+ OSE cells contribute to GC lineage, with a dynamic shift in estrogen receptor expression from ESR1 to ESR2 occurring as the cells differentiate and mature. At E16.5, approximately 23% of ovarian somatic cells were OSE (Krt18+) co-expressing Lgr5, but this population decreased to 8% by PND7 (Supplementary Fig. S2) (61). Similarly, the proportion of cells co-expressing Foxl2 and Lgr5 declined from 22% at E16.5% to 3% at PND7. These findings indicate that while Lgr5 is expressed at similar frequencies in OSE and pre-GC at E16.5, its expression progressively diminishes in the GC lineage by PND7. Quantitative analysis of cells co-expressing the OSE marker Krt18 and the GC marker Foxl2 showed that 81% and 84% of Krt18-expressing cells expressed Foxl2 at E16.5 and PND7, respectively. These findings indicate that over 80% of OSE-derived cells differentiate into GC lineage. In the same analysis, approximately 30% of Krt18-expressing cells at E16.5 expressed Esr1, of which 75% co-expressed Foxl2. By PND7, around 66% of Krt18-expressing cells were positive for Esr1, with 40% of these co-expressing Foxl2. This suggests that during the transition from fetal to postnatal ovarian development, the proportion of Esr1-expressing cells derived from OSE increases, while the proportion of cells co-expressing Esr1 and Foxl2 decreases, reflecting the differentiation of OSE-derived cells into the GC lineage. By PND7, approximately 70% of Foxl2+ GC lineage cells co-expressed Esr2, whereas Esr2 expression was absent in Foxl2+ cells at E16.5. These observations suggest that GC differentiation may involve 3 sequential stages: (i) co-expression of Esr1 and Foxl2; (ii) expression of Foxl2 only; and finally, (iii) expression of Foxl2 and Esr2 (Supplementary Fig. S2) (61). By PND14, Esr1 mRNA was detected in Cyp17a1+ theca cells and certain interstitial cells, while the Amh+ GC cluster largely lacked Esr1 expression. Lgr5+ OSE cells continued to express Esr1, consistent with the pattern observed in the PND7 ovary. Notably, Esr2 expression was exclusively found in Amh+ GCs and was absent in all other cell types (Fig. 3E and 3F). These findings collectively reveal a distinct and mutually exclusive expression pattern of Esr1 and Esr2 within the GC lineage, highlighting the dynamic transitions in estrogen receptor expression during ovarian development. The scRNA-seq data obtained from various developmental stages were consolidated into a unified dataset. A comprehensive clustering analysis, based on gene expression profiles, was then performed to map the different states of OSE-derived GC populations onto a single integrated plot. This amalgamated representation effectively distinguished various cell types: OSE cells (Krt18+), theca cells (Cyp17a1+), germ cells (Sycp1+), immune cells (Lyz2+), endothelial cells (Icam2+), and erythroblasts/erythrocytes (Alas2+). Focusing on pre-GCs (Lgr5+) and differentiated GCs (Amh+), a detailed analysis was performed to explore the temporal dynamics of Esr1 and Esr2 expression throughout the development of the GC lineage. (Fig. 4A and 4B). OSE-derived GC lineage cells were isolated (Fig. 4C) and classified into 7 distinct differentiation stages based on their unique gene expression signatures (Fig. 4D). The temporal expression patterns of Esr1 and Esr2 were examined across these clusters, with theca and germ cells used as controls for differential gene expression analysis. The results showed that Esr1 expression was restricted to Lgr5+ OSE/pre-GC-2 and −3 clusters. Conversely, GC-1, −2, and −3 clusters expressing Esr2 did not show any Esr1 expression (Fig. 4D). Intriguingly, the Lgr5+ OSE/pre-GC-1 cluster, while positive for Lgr5, lacked Esr1, indicating potential heterogeneity in the timing of ESR1 loss or the retention of an undifferentiated state among OSE-GC lineage cells. Further sub-clustering of OSE-GC cells revealed 2 distinct Lgr5+ cell types: Esr1+Foxl2− and Esr1−Foxl2+ (Fig. 4E). These observations suggest a possible divergence in the differentiation pathways of OSE cells into GCs. Some cells rapidly adopt the GC fate, characterized by Foxl2 expression, while others retain an undifferentiated state, marked by prolonged Lgr5 expression. To explore this possibility further, an unbiased projection of OSE-GC cell fate was executed using single-cell trajectory and pseudotime calculations based on differential gene expression among the clusters. In this analysis, OSE cells were designated as the origin of pre-GC cells (45). The cell trajectory delineated that Esr1-expressing OSE cells differentiated into 2 distinct Foxl2+ lineages (Fig. 4F). Lineage-1 cells exhibited a rapid upregulation of Foxl2 and Esr2, indicating swift progression to the GC fate. In contrast, lineage-2 cells displayed a more gradual increase in Foxl2 and Esr2, with sustained Lgr5 expression, suggesting they remained in an undifferentiated OSE/pre-GC state despite being Esr1+ (Fig. 4G). To cross-validate the results, previously published large-scale scRNA-seq data were reanalyzed and compared with the results of this study (64). This analysis confirmed that some OSE cells (Krt18+) in the perinatal ovary express the GC lineage marker Foxl2. Additionally, pseudotime trajectory analysis of the same dataset indicated a differentiation of cells from Krt18+Esr1+ to Krt18+Esr1+Foxl2+, ultimately leading to Foxl2+Esr2+ cells. These findings support our conclusion that Esr1+ OSE cells differentiate into Esr2+ GCs during the perinatal ovarian development (Supplementary Fig. S3) (61). In summary, these data demonstrate that a subset of Esr1+Lgr5+ OSE cells specifically differentiates into the Esr2+Foxl2+ GC lineage. Meanwhile, Esr1+Lgr5+ OSE cells persist in an undifferentiated state for an extended period. This finding highlights a nuanced and dynamic trajectory within the OSE-GC cell fate continuum. Endothelial Cells Express TGFβ Through scRNA-seq analysis, we observed that Lgr5+Esr1+ pre-GCs follow distinct differentiation pathways. Some of these cells advance to become Foxl2+Esr2+ GCs, while others remain undifferentiated (Fig. 4F and 4G). This variation in the timing of Foxl2 expression led us to hypothesize that a proximal paracrine factor may facilitate the transition from Esr1+ pre-GCs to Esr2+ GCs. During fetal development, primordial germ cells migrate into the nascent ovary, which consists mainly of OSE and stromal cells. These germ cells undergo mitotic proliferation and form germ cell cysts. Concurrently, vascular expansion from the mesonephros infiltrates the medullary region of the ovary, creating a denser medullary vasculature compared to the cortex (65-67). This stage of development features a heterogeneous follicle distribution, with advanced-stage follicles predominantly in the medulla and primordial follicles concentrated in the cortex (68). Given this structural organization, we hypothesized that the vasculature, including endothelial cells or blood-derived factors, might act as a paracrine signal promoting the differentiation of pre-GCs. To investigate this, we re-clustered scRNA-seq data from E16.5 ovaries into undifferentiated OSE cells (Esr1+Lgr5+Foxl2low) and differentiating cells (Esr1−Lgr5−Foxl2high) (Supplementary Fig. S4A) (61). This refined analysis identified transforming growth factor β1 (TGFβ1) as expressed in endothelial cells, suggesting that TGFβ signaling could serve as a paracrine factor facilitating the differentiation of pre-GCs into GCs during ovarian development (Supplementary Fig. S4B) (61). Notably, Gdf9, a member of the TGFβ family produced by oocytes (69, 70), was identified within the germ cell cluster, while the mRNA for TGFβ receptors, Tgfbr1, Tgfbr2, and Tgfbr3 were robustly expressed in pre-GCs and GCs, with Tgfbr1 showing the highest expression (Supplementary Fig. S5) (61). Interestingly, at E16.5, germ cells did not express TGFβ family members, including Gdf9 and Bmp15. Instead, TGFβ1 and other family members were expressed by endothelial cells and erythroblasts/erythrocytes. Notably, Tgfbr1, the receptor for TGFβ1, was present in both pre-GCs and germ cells (Supplementary Fig. S6) (61). These findings suggest that TGFβ1, released from the vasculature, may act as a paracrine factor influencing the differentiation of pre-GCs from Esr1-expressing to Esr2-expressing cells. To investigate the spatial relationships among differentiating GCs, endothelial cells, and TGFβ1 expression, we examined the localization of endothelial cells (PECAM1+), GCs (FOXL2+), and TGFβ1 in embryonic ovaries. At E16.5, substantial TGFβ1 immunoreactivity (ir) was observed surrounding blood vessels, with a higher density in the medullary region compared to the cortex (Fig. 5). By E18.5, TGFβ1-ir was prominently present in GCs adjacent to blood vessels, with increased accumulation in the medullary region. Quantitative analysis showed the highest TGFβ1-ir intensity in the medulla, corresponding with well-developed vasculature and robust FOXL2 expression. Notably, TGFβ1-ir was absent in the ovarian cortex at E18.5. These observations suggest a spatiotemporal correlation between vascular development and TGFβ1 localization during fetal ovarian development. By PND4, TGFβ1-ir had diffused into the cortex, aligning with the emergence of follicles containing FOXL2+ GCs (Supplementary Fig. S7) (61). Importantly, in the medulla, where TGFβ1-ir is most prevalent, ESR1 expression is significantly reduced or absent (Supplementary Fig. S8) (61). These findings support the hypothesis that TGFβ1 serves as a paracrine factor that facilitates the transition from Esr1 to Esr2 in the GC lineage. TGFβ1 Exerts a Dual Effect on Cultured Embryonic Ovaries by Concurrently Reducing Esr1 Expression While Elevating Esr2 Levels In the fetal ovary at E16.5, Tgfb1 was expressed in endothelial cells and erythroblasts/erythrocytes, while Gdf9 and Bmp15 were not detected in any cell types (Supplementary Fig. S6) (61). These observations suggest that TGFβ1, a key component of TGFβ signaling, may play a more critical role in the fetal ovary than GDF9 or BMP15. To explore the potential regulatory role of TGFβ1-TGFβ receptor signaling on Esr1 and Esr2 expression, we cultured embryonic ovaries (E18.5) with recombinant mouse TGFβ1 or TGFβ1 in combination with LY-2157299, a TGFβ1 receptor inhibitor. Ovaries treated with TGFβ1 alone exhibited significantly reduced Esr1 mRNA levels and elevated Esr2 mRNA levels compared to the vehicle control. Conversely, the levels of Esr1 and Esr2 mRNA in ovaries treated with the TGFβR1 inhibitor were similar to those in the vehicle control group (Fig. 6). These results indicate that TGFβ1 may play a significant role in the transition from Esr1 to Esr2 within the GC lineage of the developing ovary. Meanwhile, no change in the expression of Foxl2 was observed in the same sample. However, TGFβ1 increased the expression of Inha (inhibin subunit alpha), a gene specifically expressed in GC (47, 56), by more than 2-fold on average. This effect was reversed by the treatment with a TGFβ inhibitor. These results suggest that TGFβ1 not only induces the expression of Esr2 but also promotes GC differentiation.

In many estrogen-responsive tissues, ESR1 and ESR2 are typically expressed in distinct cell types (8-12, 43). Notably, cells expressing one receptor often exhibit responses to estrogen that are opposite to those of cells expressing the other receptor (23). Estrogen receptor switching has been observed in conditions like endometriosis (71). This raises a significant question: can this cellular transition occur naturally during tissue development? In this study, we identified a pattern in normal ovarian tissue where cells in the GC lineage initially express Esr1 but lose this receptor expression during differentiation, concurrently acquiring Esr2 expression (Fig. 7). While the exact mechanisms underlying the mutually exclusive expression of ESR1 and ESR2 have not yet been fully elucidated, it appears that the induction of one receptor may require the suppression of the other, a phenomenon also observed in human endometriotic stromal cells (72). The biological significance of the ESR1 to ESR2 shift in differentiating pre-GCs is not yet fully understood. However, this transition may be pivotal in regulating the proliferation of GC lineage cells. ESR1 activation is associated with cell proliferation, while ESR2 activation tends to inhibit mitosis (22, 23). Thus, the shift from ESR1 to ESR2 could help maintain primordial follicles in a dormant state until they are recruited for growth (25-27, 73-75). This hypothesis aligns with the well-established roles of ESR1 and ESR2, where ESR1 promotes proliferation and ESR2 exerts an anti-proliferative effect in many estrogen-responsive tissues (76, 77). In mature ovaries, where GCs are crucial for estrogen production, expression of ESR1 rather than ESR2 might predispose GCs to uncontrolled proliferation, as evidenced by the prevalence of ESR1+ cells in GC tumors (78). The results confirm that recombinant TGFβ1 treatment in cultured mouse embryonic ovaries leads to a decrease in Esr1 expression, consistent with previous findings on this growth factor. This is evident in the inhibitory effect of TGFβ ligands on the proliferation of MCF7 cells (79) through direct inhibition of Esr1 gene transcription (80). Furthermore, TGFβ1's effects contrast with those of estrogen, which typically promotes cell proliferation (81), while TGFβ signaling inhibitors increase ESR1 expression in primary mammary epithelial cells and bronchiol epithelial cells (82-84). The transition from primordial to primary follicles, and their subsequent responsiveness to follicle-stimulating hormone (FSH), is driven by TGFβ-induced activation of SMAD2/3 in GCs (85, 86). In neonatal ovaries of SMAD3-deficient mice, GC proliferation is notably impaired, and TGFβ1-deficient mice exhibit a 34% reduction in germ cells compared to wild-type littermates (87-89). Within the TGFβ superfamily, which includes TGFβ, Activin, BMP, GDF, and Nodal, the phosphorylation of SMAD2/3 is mediated by their binding to Type I/II TGFβ receptors (90, 91). Once phosphorylated, SMAD2/3 forms a heteromeric complex with SMAD4, translocates to the nucleus, and binds to the SMAD-binding element on target gene promoters (92, 93). In fetal ovarian GCs, the activated SMAD complex induces the expression of Foxl2 (92). However, our results demonstrated that TGFβ1 treatment did not induce Foxl2 expression in the cultured embryonic (E18.5) gonad ovary. Two possible explanations may account for this outcome. First, TGFβ1-alone might be insufficient to induce Foxl2 expression under the given culture conditions. Second, the induction of Foxl2 by TGFβ1 may occur earlier than E18.5, the stage at which the experiment was conducted. Notably, FOXL2 was observed to be robustly expressed in the E16.5 ovary. Nonetheless, the TGFβ1-driven increase in Esr2 and Inha expression indicates that TGFβ1 may play a role in GC lineage specification by promoting the expression of GC-specific genes. However, further investigation is needed to elucidate the underlying mechanisms, which were beyond the scope of this study. Previous studies have shown that GDF9 and BMP15, through interactions with TGFβ receptors on GCs, play key roles in regulating gene expression, cell proliferation, and follicular dormancy (74, 75). Our single-cell transcriptome analysis of E16.5 ovaries revealed that Bmp15 and Gdf9 were not expressed in GCs during the formation of follicles, which were characterized by Foxl2 and Esr2 expression. In contrast, TGFβ1 was detected in vascular endothelial cells and erythroblasts/erythrocytes (Supplementary Fig. S5 and S6) (61). Thus, TGFβ1 from the vasculature appears to be the primary ligand activating TGFβ receptors in prenatal ovarian cells. TGFβ1 is considered a key activator of SMAD2/3 signaling in the ovary (94, 95). Since FOXL2 and ESR2 are expressed in differentiated GCs and robust ESR2 expression depends on SMAD2/3 activation (96), TGFβ1 likely promotes GC differentiation shortly after birth by inducing SMAD2/3-mediated ESR2 expression. FOXL2 is also implicated in maintaining ESR2 expression in these cells (96). Additionally, SMAD3 has been reported to counteract ESR1 activity by suppressing its transcriptional effects (97). Consistent with this, SMAD3-deficient mice exhibit decreased Esr2 and increased Esr1 expression compared to WT littermates (88). This suggests that TGFβ1 may inhibit ESR1-mediated pathways while enhancing ESR2 expression in differentiating GCs. Notably, ESR1 has been shown to suppress the activity, stability, and transcriptional function of SMAD3 (98, 99). Therefore, the reduced ESR1 expression may support sustained FOXL2 and ESR2 expression, facilitating the transition from pre-GCs to fully differentiated GCs. In summary, TGFβ1 appears to create an environment conducive to stable Esr2 expression in GC lineage by reducing ESR1 transcriptional activity and promoting Esr2 expression through SMAD activation. However, the specific mechanisms underlying these processes were beyond the scope of this study. In addition to the finding that ovarian cells transition from ESR1 to ESR2 expression during development, this study also uncovered 2 distinct branches within the GC lineage. In the fetal mouse ovary, cells similar to the gonadal ridge epithelium migrate from the mesonephros to the primitive ovary's gonadal ridge epithelium. Concurrently, pre-GCs arise in the medullary region rather than in the cortex (45, 100, 101). As development advances, Lgr5-expressing differentiating OSE cells begin to express pre-GC markers such as Foxl2. These cells migrate toward germ cells, surround them, and contribute to the formation of primordial follicles (46, 102). LGR5, originally identified as a stem cell marker in the intestinal crypt, is also prominently expressed in OSE cells and is known for its stem-cell-like properties. Recent studies highlight that LGR5+ fetal ovarian cells can differentiate into GCs and other somatic cells within the ovary (46, 102). Consistent with these findings, the study identified 2 distinct lineages. Lineage-1 showed a notable increase in Foxl2 and Esr2 expression, coupled with a decrease in Lgr5, indicating differentiation. Cells in lineage-1 ultimately expressed Amh and Esr2, marking their maturation into differentiated GCs associated with primary and secondary follicles. Toward the end of the pseudotime axis, most cells expressed Foxl2, though not all Foxl2+ cells concurrently exhibited Esr2 expression. This suggests that Esr2 expression in GCs might continue to rise gradually even after PND14. Alternatively, Foxl2-expressing cells might differentiate into cell types other than GCs that express Esr2, as recent studies have shown that Foxl2+ cells in the ovary can differentiate into both GCs and theca-interstitial cells at PND14 (56). In contrast, cells in lineage-2 did not express Amh or Esr2, indicating they remained in a pre-GC state. These results underscore that lineage-2 cells also originate from Lgr5+ OSE cells, highlighting the heterogeneity and diverse developmental trajectories within the GC lineage. Finally, this study establishes a clear link between local vascular development and selective GC differentiation from LGR5+ OSE cells. Single-cell RNA sequencing data from perinatal ovaries revealed that Icam2+ endothelial cells in the embryonic ovary expressed Tgfb1 (Fig 4, and Supplementary Fig. S5 and S6) (61). Our findings highlight a high density of vasculature and TGFβ1 ligands in the medullary region of the perinatal ovary, whereas the cortical regions, which contain undifferentiated GCs and primordial follicles, exhibited less vascular development and minimal TGFβ1 expression. This observation aligns with the asymmetric development of vasculature in the medulla-cortex axis of female gonads (66, 103, 104), with blood vessels developing close to germ cell cysts (105). The expansion of vascular structures toward the cortical region and localized TGFβ1 secretion may promote FOXL2 expression by activating SMAD2/3 and reducing ESR1 levels in GC lineage cells (92, 96, 97). FOXL2, in turn, induces ESR2 expression in developing GCs (96, 106). In support, Li et al demonstrated the vasculature's role in GC differentiation (107), where Notch signals from the vasculature inhibit medullary GC differentiation, and a progressive increase in the Notch-downstream gene Hes1 was observed during fetal ovarian development. Additionally, Notch and TGFβ signaling synergize to induce downstream genes such as Hes1 in neural stem cells (108), suggesting that medullary TGFβ ligand distribution may contribute to Notch signaling in the developing ovary. In summary, the perinatal ovarian vasculature, through TGFβ1 signaling, likely plays a crucial role in reducing ESR1 expression in OSE-derived pre-GCs and promoting their differentiation into ESR2+ GCs. However, the presented study did not determine whether TGFβ promotes GC differentiation, which in turn upregulates Esr2 expression, or if it upregulates Esr2 expression, thereby inducing GC differentiation. Based on the temporal sequence of gene expression changes observed from cell trajectory analysis, it is suggested that TGFβ promotes the differentiation of GCs expressing Foxl2. Subsequently, the expression of Esr2 may be induced through the functions of TGFβ, FOXL2, and other regulators. The transition from ESR1 to ESR2 expression within a cell likely leads to a profound shift in estrogen-induced signaling at the cellular level. The functional differences between ESR1 and ESR2 stem primarily from 2 key activities: 1) the recruitment of distinct co-transcription factors to estrogen response elements within target gene promoters, and 2) ESR2's antagonistic role in the transcriptional regulation of ESR1 downstream genes, such as Activator protein 1 (AP-1) (42, 109). Recent research underscores the clinical importance of ESR2 expression in cancer treatment (37-40) where selective ESR2 activation is being explored as a potential targeted therapy for various cancers, including breast cancer (42). Given the established roles of TGFβ1 in cancer cells, it may be valuable to re-examine previous studies through the lens of the ESR1/ESR2 ratio, which could provide new insights into therapeutic approaches. In conclusion, our data demonstrate a transition from Esr1 to Esr2 expression in the ovarian GC lineage, with paracrine signals like TGFβ1 playing a crucial role in regulating this switch. The evidence of ESR expression transition within a cell lineage, along with further investigation into the underlying mechanisms, could offer new avenues for manipulating this transition to treat estrogen-related pathological conditions. Acknowledgments We extend our gratitude to Dr. Gustafsson (University of Houston, Houston, USA) for generously providing the anti-ESR2 antibody. We also thank Dr. C. L. Wright, Dr. C. J. Fields, Dr. J. Drnevich, and Dr. M. Tseng, all from the Roy J. Carver Biotechnology Center and HPCBio at the University of Illinois at Urbana-Champaign, for their invaluable assistance with single-cell RNA sequencing and data analysis. Abbreviations - Amh anti-Müllerian hormone - BSA bovine serum albumin - E16.5 embryonic day 16.5 - E2 17β-estradiol - ESR1 estrogen receptor alpha (ERα) - ESR2 estrogen receptor beta (ERβ) - FOX Forkhead Box - GC granulosa cell - hCG human chorionic gonadotropin - ir immunoreactivity - KO knockout - LGR5 Leucine Rich Repeat Containing G Protein-Coupled Receptor 5 - OSE ovarian surface epithelium - PBS phosphate-buffered saline - PCR polymerase chain reaction - PND postnatal day - qPCR quantitative polymerase chain reaction - RFP red fluorescent protein - scRNA-seq single-cell RNA sequencing - TGFβ transforming growth factor β - t-SNE t-distributed stochastic neighbor embedding - WT wild-type Contributor Information Chan Jin Park, Department of Comparative Biosciences, College of Veterinary Medicine, University of Illinois at Urbana-Champaign, Urbana, IL 61802, USA; Epivara, Inc., Research Park, Champaign, IL 61820, USA. Ji-Eun Oh, Department of Comparative Biosciences, College of Veterinary Medicine, University of Illinois at Urbana-Champaign, Urbana, IL 61802, USA. PoChing Lin, Department of Comparative Biosciences, College of Veterinary Medicine, University of Illinois at Urbana-Champaign, Urbana, IL 61802, USA. Sherry Zhou, Epivara, Inc., Research Park, Champaign, IL 61820, USA. Mary Bunnell, Department of Comparative Biosciences, College of Veterinary Medicine, University of Illinois at Urbana-Champaign, Urbana, IL 61802, USA. Emmanuel Bikorimana, Department of Comparative Biosciences, College of Veterinary Medicine, University of Illinois at Urbana-Champaign, Urbana, IL 61802, USA. Michael J Spinella, Department of Comparative Biosciences, College of Veterinary Medicine, University of Illinois at Urbana-Champaign, Urbana, IL 61802, USA. Hyunjung Jade Lim, Department of Veterinary Medicine, Konkuk University, Gwangjin-gu, Seoul 05029, Korea. CheMyong J Ko, Department of Comparative Biosciences, College of Veterinary Medicine, University of Illinois at Urbana-Champaign, Urbana, IL 61802, USA. Funding This research was supported by Eunice Kennedy Shriver National Institute of Child Health and Human Development grants HD071875 and HD094296 to C.J.K. Author Contributions C.J.P., J.O., and C.J.K. designed and performed experiments, analyzed and interpreted data, and wrote the manuscript. P.L., S.Z., and M.B. performed experiments and analyzed data. E.B. and M.J.S. performed experiments, analyzed and interpreted data. H.J.L. designed experiments and interpreted data. All authors edited and approved the final manuscript. Disclosures The authors have nothing to disclose. Data Availability Original data generated and analyzed during this study are included in this published article or in the data repositories listed in the References. Further information and requests for resources and reagents should be directed to and will be fulfilled by the Lead Contact, CheMyong Jay Ko ([email protected]). The raw sequencing data reported in this study have been deposited in the Gene Expression Omnibus under accession number GSE242218. R scripts generated for the analysis are available on GitHub (https://github.com/cjpark85/Mouse_Perinatal_Ovary_scRNAseq).

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Figure. 10.6084/m9.figshare.27170565.v1. [DOI] [PMC free article] [PubMed] Data Availability Statement Original data generated and analyzed during this study are included in this published article or in the data repositories listed in the References. Further information and requests for resources and reagents should be directed to and will be fulfilled by the Lead Contact, CheMyong Jay Ko ([email protected]). The raw sequencing data reported in this study have been deposited in the Gene Expression Omnibus under accession number GSE242218. R scripts generated for the analysis are available on GitHub (https://github.com/cjpark85/Mouse_Perinatal_Ovary_scRNAseq).