Abstract
Polycystic ovary syndrome (PCOS) is an endocrine metabolic disorder that appears to have a genetic predisposition and a fetal origin. The fetal ovary has two major somatic cell types shown previously to be of different cellular origins and different morphologies and to differentially express 15 genes. In this study, we isolated the somatic gonadal ridge epithelial-like (GREL) cells (n = 7) and ovarian fetal fibroblasts (n = 6) by clonal expansion. Using qRT-PCR, we compared the gene expression levels of PCOS candidate genes with previous data on the expression levels in whole fetal ovaries across gestation. We also compared these levels with those in bovine adult ovarian cells including fibroblasts (n = 4), granulosa cells (n = 5) and surface epithelial cells (n = 5). Adult cell types exhibited clear differences in the expression of most genes. In fetal ovarian cells, DENND1A and ERBB3 had significantly higher expression in GREL cells. HMGA2 and TGFB1I1 tended to have higher expression in fetal fibroblasts than GREL cells. The other 19 genes did not exhibit differences between GREL cells and fetal fibroblasts and FBN3, FSHB, LHCGR, FSHR and ZBTB16 were very lowly expressed in GREL cells and fibroblasts. The culture of fetal fibroblasts in EGF-containing medium resulted in lower expression of NEIL2 but higher expression of MAPRE1 compared to culture in the absence of EGF. Thus, the two fetal ovarian somatic cell types mostly lacked differential expression of PCOS candidate genes.
Lay summary
Polycystic ovary syndrome (PCOS) is one of the most common reproductive problems. The cause is not known so there are no specific treatments or prevention strategies. We know it can be linked to issues that occur in the womb and that some people may be more likely to get PCOS due to their genetic makeup. Our recent studies showed that many of the genes linked to PCOS were found to be switched on in the fetal ovary and are likely to be involved in the development of the fetal ovary. In order to improve our understanding of PCOS, we need to identify the type of cells in the fetal ovary where these genes are switched on. In this study, we examined the PCOS genes in two types of cells that mature as the fetal ovary develops and found very little difference between them but bigger differences to their mature adult counterparts.
Introduction
Polycystic ovary syndrome (PCOS) is one of the most prevalent endocrine disorders, affecting approximately 10% of women of reproductive age (March et al. 2010, Bozdag et al. 2016). Women with PCOS are identified with hyperandrogenism and often exhibit male-like body or facial hair (Lizneva et al. 2016), menstrual irregularity and polycystic ovaries (Azziz 2018). Furthermore, PCOS is also associated with secondary complications, such as impaired glucose tolerance, type 2 diabetes, sleep disorders, increased anxiety and depression and potentially adverse cardiovascular diseases (Fauser et al. 2012, Haoula et al. 2012, Cooney et al. 2017, Fernandez et al. 2018, Teede et al. 2018).
The aetiology of PCOS is not completely understood. Studies on twins and families suggested a genetic basis for PCOS. Familial linkage studies and genome-wide association studies (GWAS) have led the genetic understanding of PCOS to a new era by identifying 19 loci associated with risk of PCOS (Jones & Goodarzi 2016, Day et al. 2018). The loci contain 25 PCOS candidate genes (FBN3, DENND1A, LHCGR, THADA, C9orf3/AOPOP, FSHR, HMGA2, INSR, RAB5B/SUOX, SUMO1P1, TOX3, YAP1, ERBB4, FSHB, GATA4, KRR1, RAD50, PLGRKT, ZBTB16, MAPRE1, FDFT1, IRF1, ARL14EP, ERBB3 and NEIL2) (Jones & Goodarzi 2016, Day et al. 2018). Moreover, studies on pregnant women with elevated levels of androgens and their offspring indicated that a female fetus exposed to elevated levels of androgens was at an increased risk of developing PCOS in later life, which supported the concept of a fetal or early postnatal origin of PCOS (Sir-Petermann et al. 2002, Filippou & Homburg 2017, Tata et al. 2018).
In the adult ovary, the follicular thecal cells are responsible for the synthesis of androgens utilising the enzyme cytochrome P450c17 (CYP17A1), and in PCOS ovaries, the thecal cells overexpress cytochrome P450c17 resulting in increased androgen production (Chang 2007, Rosenfield & Ehrmann 2016). When mature, the granulosa cells normally convert androgens to oestrogens under the regulation of gonadotrophins (Erickson et al. 1992, Kakuta et al. 2018). In vitro studies on PCOS ovaries found that granulosa cells from women with PCOS had reduced capacity for producing oestradiol and progesterone than normal granulosa cells (Erickson et al. 1992). Moreover, granulosa cells in PCOS ovaries appear to be abnormal in their survival and proliferation behaviour, with downregulated expression of proapoptotic factor and upregulated antiapoptotic factor (Das et al. 2008, Yuanyuan et al. 2019). Ovarian surface epithelium, an essentially single layer of epithelial cells covering the surface of the ovary, is androgen-responsive, and androgens can increase its cell proliferation and decrease cell apoptosis (Edmondson et al. 2002). However, elevated levels of androgens are associated with increased risk of ovarian epithelial cancer which can arise from ovarian surface epithelial cells (Thomas 1995, Schildkraut et al. 1996, Ose et al. 2017). PCOS ovaries tend to be fibrous, which is caused by excessive proliferation of fibroblasts and elevated deposition of extracellular matrix such as collagen type I (Zhou et al. 2017).
In terms of the origin of different cell types in the fetal ovary, fibroblasts are derived from the mesonephric stroma which penetrates from the mesonephros into the ovarian primordium and starts proliferating (Hummitzsch et al. 2013, Heeren et al. 2015, Hartanti et al. 2019, Hummitzsch et al. 2019). Granulosa cells and ovarian surface epithelial cells are believed to have a common precursor, the gonadal ridge epithelial-like (GREL) cell, which arises from the surface epithelium of the mesonephros (Hummitzsch et al. 2013). Later, in gestation, GREL cells differentiate into either pre-granulosa cells or surface epithelium (Hummitzsch et al. 2013). GREL cells close to the surface are separated from oogonia/oocytes by the proliferating and migrating stroma and develop into ovarian surface epithelium. GREL cells in the ovigerous cords are in close proximity to oocytes and develop into pregranulosa cells when the ovigerous cords break down and form follicles containing oocytes and GREL cells (Hummitzsch et al. 2013).
In our previous studies, we investigated a possible link between the genetic origins and fetal origins of PCOS in both bovine and human fetal ovaries. Initially, we examined the expression of FBN3 (Hatzirodos et al. 2011), which was identified by D19S884 microsatellite in familial linkage studies of PCOS (Stewart et al. 2006, Ewens et al. 2010), and members of TGFβ signalling pathway (Hatzirodos et al. 2011, Azumah et al. 2022). The results indicated that this signalling pathway may be involved in the fetal origin of PCOS (Hatzirodos et al. 2011). Subsequently, PCOS candidate genes identified by GWAS and additionally FBN3, TGFB1I1 and AR were examined in fetal ovaries (Hartanti et al. 2020b, Liu et al. 2020, Azumah et al. 2021). Nearly, all the candidate genes were expressed in the fetal ovary, and the expression pattern of each gene followed one of three patterns: some were expressed early in gestation, some late in gestation and some were expressed throughout gestation (Hartanti et al. 2020b, Liu et al. 2020). Expression of the early genes was highly correlated with each other and so were the late genes (Hartanti et al. 2020b, Liu et al. 2020). Similarly, in studies on the expression of cell-type-associated genes in the developing ovary (Hatzirodos et al. 2019, Hummitzsch et al. 2019), hierarchical clustering also exhibited three expression patterns across gestation and higher correlations between genes in the same cluster (Hatzirodos et al. 2019). We reasoned that the dynamic expression patterns reflect successive processes like expansion of stroma penetrating from the mesonephros into ovarian primordium and the formation of ovigerous cords early in gestation, and follicle formation, establishment of mature surface epithelium and the tunica albuginea late in gestation (Hummitzsch et al. 2013, Hartanti et al. 2020a).
In contrast to the fruitful studies of the fetal ovaries, microarray analysis of data from adult human ovaries found that among 25 PCOS candidate genes, only RAD50 was differentially and significantly higher expressed in PCOS ovaries compared with normal ovaries (Liu et al. 2020). So we considered that the PCOS genes expressed in the fetal ovaries maybe vulnerable to disturbance during gestation which possibly leads to a predisposition to PCOS in later life (Hartanti et al. 2020b, Liu et al. 2020). To obtain more information about the expression of PCOS genes in fetal ovaries, we examined the expression of PCOS candidate genes in cultured fetal GREL cells and fibroblasts isolated from bovine fetuses. These were less than 200 days of gestation to avoid differentiation of GREL cells into granulosa cells and ovarian surface epithelial cells. We also compared these results to the expression of these genes in isolated adult granulosa cells and ovarian surface epithelial cells and cultured adult fibroblasts. Additionally, we also compared these data to previous data on the expression levels in whole fetal ovaries across gestation.
Materials and methods
Animal use statement
The bovine ovaries used in this study were scavenged from animals that were being processed for human consumption and were not owned by the authors or their institutions. As such, the University of Adelaide’s Animal Ethics Committee only requires notification of this.
Collection of bovine fetal and adult ovaries
Fetuses from pregnant Bostaurus cows and ovaries from non-pregnant Bostaurus cows were collected at local abattoirs (Thomas Foods International, Murray Bridge, SA, Australia and Strath Meats, Strathalbyn, SA, Australia) and transported on ice in Hank’s balanced-salt solution (HBSS) with calcium and magnesium (HBSS+/+) to the laboratory. The gestational ages of the fetuses were estimated from the crown-rump length (CRL) (Russe 1983). Fetuses with a CRL < 8 cm underwent a sex determination as previously reported (Hummitzsch et al. 2013). The fetuses for isolation of fetal ovarian cells were at less than 200 days of gestation. Samples of whole fetal ovaries throughout gestation (n = 27) were from our previous study (Hartanti et al. 2020b) and collected from The Midfield Group, Warrnambool, Victoria, Australia.
Isolation of fetal ovarian GREL cells and fibroblasts
Purified GREL cells and fetal fibroblasts used in this study were isolated and cultured in our previous study (Liu et al. 2022). Briefly, fetal ovaries were removed from fetuses and digested in 10 mL of HBSS+/+ containing 1 mg/mL collagenase type I (Gibco) and 50 μg/mL DNase I (Sigma–Aldrich) at 37°C. The cell suspensions were seeded in 24-well plates which were coated with collagen type I (Sigma–Aldrich) at 250 cells per well. The cells were cultured in DMEM/F12 medium (Sigma–Aldrich, D8900) containing 5% fetal calf serum (Sigma–Aldrich), 100 IU/mL penicillin, 0.01% streptomycin sulfate (Gibco, 15140122) and 0.1% fungizone (Gibco, 15290-018) and 3 ng/mL human EGF (EGF; Sigma–Aldrich, E9644), and the culture medium was changed every 2 days. Clusters with cells of irregular polygonal shape and with clear visible nuclei as described in our previous study (Liu et al. 2022) were observed from day 2 onwards, and the largest purified and healthy clusters were selected on day 3 and day 4. A sterile blunt-ended glass Pasteur pipette was used to scrape and remove other cell types surrounding the selected clusters. Cells were collected from day 10 to day 14. In order to collect pure GREL cell and fetal fibroblast at the end of culture, clusters were scraped with a sterile blunt-ended glass Pasteur pipette and then culture media with the cells was transferred to a sterile Eppendorf tube. After centrifugation at 500 g for 5 min, the cell pellets were stored at −80°C. Under these culture conditions, GREL cells demonstrated significantly higher gene expression of GREL cell markers (KRT19 and PKP2) and fetal fibroblasts demonstrated higher gene expression of fibroblast markers (FBN1, COL1A1 and NR2F2), suggesting that the cells maintained their epithelial and fibroblast characters, respectively (Liu et al. 2022).
Isolation of adult ovarian cells
Samples of adult ovarian fibroblasts, ovarian surface epithelial cells and granulosa cells used in this study were collected in our previous study (Liu et al. 2022). Briefly, for fibroblasts, adult individual ovaries were cut into quarters, and tissue below the tunica albuginea (100–200 µm) was dissected out. It was digested in 10 mL of HBSS+/+ containing 1 mg/mL of collagenase type I and 50 μg/mL of DNase I at 37°C for 2 h. Cell suspensions were seeded in the same way as fetal ovarian cell suspension. When the culture dishes were 70% covered with cells, the fibroblasts were collected and cell pellets were stored at −80°C. For surface epithelial cells, individual adult ovaries were placed in a 60 mm-culture dish containing culture medium. The surface of the ovary was scraped with the blunt side of a scalpel blade. Culture medium containing ovarian surface epithelial cells from five to seven ovaries was centrifuged at 500 g for 5 min. Finally, the cell pellets were stored at −80°C until use. Granulosa cells were isolated from healthy antral follicles (9–12 mm). Follicles were cut off from the ovary with scissors and transferred to a dish containing 1 mL of HBSS−/−, and they were cut open. Granulosa cells were scraped with a blunt-ended Pasteur pipette. The cell suspension from each follicle was transferred into a sterile eppendorf tube and centrifuged at 500 g for 5 min. Finally, the cell pellets were stored at −80°C.
RNA isolation, cDNA synthesis and quantitative real-time PCR
RNA from granulosa cells, ovarian surface epithelial cells and adult fibroblasts was extracted using TrizolTM (Thermo Fisher Scientific) according to manufacturer’s instructions. RNA from GREL cells and fetal fibroblasts was extracted using RNAqueous micro kit (Thermo Fisher Scientific). RNA of 10 µg of each sample was treated with DNase I (Promega Australia/Life Technologies Australia Pty Ltd) for 20 min at 37°C. DNAse-treated RNA of 200 ng was used for cDNA synthesis as previously described (Hummitzsch et al. 2013, Liu et al. 2020).
Based on available RNA sequences in NCBI, PCR primers were designed to span introns using Primer3 plus and Net primer (PREMIER Biosoft, Palo Alto, CA, USA), software and primers are listed in Supplementary Table 1 (see section on supplementary materials given at the end of this article). Primer combinations were tested as previously described (Liu et al. 2020). The amplification conditions were 95°C for 15 s, then 60°C for 60 s for 40 cycles using Rotor Gene 6000 cycler (Q series, Qiagen GmbH). Ct values were determined using Rotor Gene 6000 software at a threshold of 0.05 normalised fluorescent unit. Gene expression values were determined using 2−ΔCt method, and ribosomal protein L32 (RPL32) and peptidylprolyl isomerase A (PPIA) were used as housekeeping genes in the examination of different cell types. We used negative controls of no reverse transcriptase in the cDNA synthesis and of no added RNA.
Treatment of bovine fetal fibroblasts
Fetal fibroblasts (160–198 days, n = 6) were cultured and treated with a number of growth factors and hormones as listed in Supplementary Table 2 (see section on supplementary materials given at the end of this article) in a previous experiment (Bastian et al. 2016) and the expression of PCOS genes were examined here. Briefly, bovine fetal fibroblasts were seeded at 30,000 cells/well in 24-well plates in DMEM/F12 medium containing 5% (v/v) fetal calf serum, 100 IU/mL penicillin, 0.01% streptomycin sulfate (Gibco, 15140122) and 0.1% fungizone at 38.5°C and 5% CO2. At 60–70% confluency, cells were treated with 5 or 20 ng/mL of TGFB1 for 18 h in DMEM/F12 medium containing 1% fetal calf serum and then harvested and stored at −80°C for analysis.
Statistical analysis
All statistical analyses were carried out using Microsoft Office Excel 365 (Microsoft Redmond) and IBM SPSS Statistics for Windows, version 25 (IBM Corp.). The 2−∆Ct data of gene expression in GREL cells and fetal fibroblasts was plotted as scatter plots using GraphPad Prism version 8.00 (GraphPad Software Inc.). To determine significant differences among adult fibroblasts, granulosa cells and ovarian surface epithelial cells, a one-way ANOVA and Tukey’s post hoc tests were conducted. To compare the difference between the control and the treatments of fetal fibroblasts, one-way ANOVA with Dunnett’s post hoc tests was conducted. Additionally, Student’s t-test was conducted to analyse the difference between GREL cells and fetal fibroblasts and the difference between fetal fibroblasts cultured with or without EGF.
Results
Presentation of gene expression data
In Figs. 1, 2, 3 and 4, we present expression data of 25 PCOS candidate genes and 3 other genes (AR, AMH and TGFB1I1) and group them based on their known expression pattern across gestation in each Figure. For each gene, the expression across gestation is presented, has been published previously (Hartanti et al. 2020b, Liu et al. 2020) and is acknowledged. We then present the expression in fetal fibroblasts and GREL cells and the statistical comparison between them. We then present the expression in adult fibroblasts, granulosa cells and ovarian surface epithelial cells and the statistical comparison between them. The data for each gene from gestation and from isolated cells in Figs. 1, 2, 3 and 4 are plotted on the same scale for direct comparisons. The mean levels of expression in isolated cells and statistical comparisons of fetal and adult cells are presented in Table 1. The individual data of expression in fetal fibroblasts and GREL cells across gestation are presented in a supplementary figure.
mRNA expression levels of genes expressed during early gestation. Scatter plots on the left in each subfigure show gene expression levels in fetal ovaries (n = 27) from our previous publications (Hartanti et al. 2020b, Liu et al. 2020). Gene expression levels in cultured GREL cells (n = 7) and fetal fibroblast (n = 6) are presented in the middle graph of each subfigure. Data of gene expression in adult fibroblasts (n = 4), granulosa cells (GC; n = 5) and ovarian surface epithelial cells (OSE; n = 5) are presented as mean ± s.e.m. (normalised to PPIA and RPL32) in the graph on the right side of each subfigure. Significant differences between the three adult cell types were determined by one-way ANOVA with Tukey’s post hoc test. *P < 0.05, **P < 0.01, ***P < 0.001.
Citation: Reproduction and Fertility 3, 4; 10.1530/RAF-22-0068
Relative gene expression of 2−ΔCt of genes presented as mean ± s.e.m. for each cell type. Comparisons are between fetal fibroblasts (n = 6) with adult fibroblasts (n = 4) and then between fetal GREL cells (n = 7) with adult ovarian surface epithelial cells (n = 5) or granulosa cells (n = 5).
| Gene | Fetal fibroblasts | Adult fibroblasts | Fetal GREL cells | Adult ovarian surface epithelial cells | Adult granulosa cells |
|---|---|---|---|---|---|
| HMGA2 | 0.007 ± 0.001 | 0.002 ± 0.000** | 0.003 ± 0.001 | 0.006 ± 0.004 | 0.000 ± 0.000*** |
| TOX3 | 0.005 ± 0.002 | 0.002 ± 0.001 | 0.010 ± 0.004 | 0.034 ± 0.004 | 0.000 ± 0.000*** |
| FBN3 | 0.000 ± 0.000 | 0.000 ± 0.000 | 0.000 ± 0.000 | 0.001 ± 0.001 | 0.000 ± 0.000 |
| GATA4 | 0.310 ± 0.026 | 0.113 ± 0.026*** | 0.233 ± 0.054 | 0.452 ± 0.060* | 0.265 ± 0.036 |
| ERBB3 | 0.000 ± 0.000 | 0.000 ± 0.000 | 0.001 ± 0.000 | 0.288 ± 0.047*** | 0.001 ± 0.000 |
| DENND1A | 0.075 ± 0.008 | 0.040 ± 0.010** | 0.101 ± 0.021 | 0.500 ± 0.068*** | 0.213 ± 0.024 |
| FSHB (exon 3) | 0.000 ± 0.000 | 0.000 ± 0.000 | 0.000 ± 0.000 | 0.000 ± 0.000 | 0.001 ± 0.000** |
| RAD50 | 0.109 ± 0.009 | 0.043 ± 0.010*** | 0.144 ± 0.031 | 0.161 ± 0.016 | 0.228 ± 0.052 |
| TGFB1I1 | 0.297 ± 0.047 | 0.118 ± 0.020** | 0.183 ± 0.051 | 0.159 ± 0.022 | 0.087 ± 0.031* |
| INSR | 0.040 ± 0.004 | 0.020 ± 0.002** | 0.035 ± 0.006 | 0.421 ± 0.073*** | 0.295 ± 0.024*** |
| AR | 0.028 ± 0.003 | 0.018 ± 0.002* | 0.019 ± 0.006 | 0.037 ± 0.005 | 0.052 ± 0.013* |
| FSHR | 0.001 ± 0.000 | 0.000 ± 0.000 | 0.000 ± 0.000 | 0.016 ± 0.005*** | 0.631 ± 0.105*** |
| ZBTB16 | 0.001 ± 0.000 | 0.001 ± 0.000 | 0.001 ± 0.000 | 0.074 ± 0.013** | 0.016 ± 0.005* |
| AMH | 0.023 ± 0.003 | 0.014 ± 0.003 | 0.017 ± 0.004 | 0.021 ± 0.011 | 0.130 ± 0.032** |
| IRF1 | 0.022 ± 0.008 | 0.055 ± 0.049 | 0.018 ± 0.004 | 0.172 ± 0.026*** | 0.024 ± 0.004 |
| PLGRKT | 0.076 ± 0.011 | 0.058 ± 0.015 | 0.059 ± 0.013 | 0.053 ± 0.010 | 0.052 ± 0.015 |
| C8H9orf3 | 0.029 ± 0.007 | 0.017 ± 0.004 | 0.033 ± 0.008 | 0.156 ± 0.047** | 0.049 ± 0.008 |
| KRR1 | 0.049 ± 0.008 | 0.018 ± 0.005** | 0.054 ± 0.011 | 0.241 ± 0.020*** | 0.085 ± 0.017 |
| RAB5B | 0.381 ± 0.077 | 0.144 ± 0.022* | 0.300 ± 0.063 | 0.671 ± 0.079** | 0.409 ± 0.062 |
| MAPRE1 | 0.431 ± 0.072 | 0.191 ± 0.030* | 0.346 ± 0.065 | 0.310 ± 0.075 | 0.328 ± 0.120 |
| FDFT1 | 0.237 ± 0.025 | 0.097 ± 0.020** | 0.285 ± 0.063 | 0.135 ± 0.019 | 0.565 ± 0.196 |
| NEIL2 | 0.003 ± 0.001 | 0.003 ± 0.002 | 0.007 ± 0.002 | 0.008 ± 0.002 | 0.006 ± 0.002 |
| YAP1 | 0.639 ± 0.105 | 0.343 ± 0.096* | 0.606 ± 0.125 | 0.768 ± 0.119 | 0.420 ± 0.030 |
| ARL14EP | 0.082 ± 0.009 | 0.091 ± 0.049 | 0.093 ± 0.026 | 0.122 ± 0.010 | 0.116 ± 0.030 |
| SUOX | 0.028 ± 0.003 | 0.008 ± 0.001*** | 0.022 ± 0.005 | 0.047 ± 0.002 | 0.032 ± 0.007 |
| ERBB4 | 0.005 ± 0.001 | 0.005 ± 0.001 | 0.008 ± 0.004 | 0.016 ± 0.003 | 0.004 ± 0.002 |
| LHCGR | 0.000 ± 0.000 | 0.001 ± 0.001 | 0.000 ± 0.000 | 0.002 ± 0.001 | 0.494 ± 0.303 |
| THADA | 0.033 ± 0.007 | 0.015 ± 0.002** | 0.048 ± 0.014 | 0.259 ± 0.030*** | 0.073 ± 0.010 |
Student’s t-test was used to analyse the differences between fetal fibroblasts with adult fibroblasts. One-way ANOVA with Tukey’s post hoc test was used to analyse the differences between GREL cells with adult ovarian surface epithelial cells or granulosa cells.
*P < 0.05, **P < 0.01, ***P < 0.001 report significant differences between the corresponding fetal cells with the adult cells.
Expression of PCOS candidate genes in fetal ovaries
The gene expression data were from our previous publications (Hartanti et al. 2020b, Liu et al. 2020). HMGA2, TOX3, FBN3, GATA4, ERBB3, DENND1A, FSHB and RAD50 were expressed in the early gestation and then declined (Fig. 1A-H), and the expression of these genes was negatively correlated with gestational age. The gene expression level of FSHB was determined with primers which targeted the sequences in exons 3. However, primers to exon 2 and exon 3, which could correctly amplify FSHB from anterior pituitary, failed to amplify FSHB from ovary samples (Hartanti et al. 2020b), suggesting that FSHB transcript in fetal ovary cannot encode or produce FSHB. However, we report on the FSHB exon 3 transcript as with GWAS analyses it is not always possible to assign the encoding of a full-length gene to explain the GWAS relationship with the disease. The expression levels of TGFB1I1, INSR, AR, FSHR, ZBTB16, AMH, IRF1 and PLGKRT were low in early gestation and gradually increased until the late stage of gestation (Fig. 2A-H). The other genes C8H9orf3, KRR1, RAB5B, MAPRE1, FDFT1, NEIL2, YAP1, ARL14EP, SUOX, ERBB4, LHCGR and THADA were expressed constantly throughout the gestation (Fig. 3A-F and Fig. 4A-F).
mRNA expression levels of genes expressed during late gestation. Scatter plots on the left in each subfigure show gene expression levels in fetal ovaries (n = 27) from our previous publications (Hartanti et al. 2020b, Liu et al. 2020). Gene expression levels in cultured GREL cells (n = 7) and fetal fibroblast (n = 6) are presented in the middle graph of each subfigure. Data of gene expression in adult fibroblasts (n = 4), granulosa cells (GC; n = 5) and ovarian surface epithelial cells (OSE; n = 5) are presented as mean ± s.e.m. (normalised to PPIA and RPL32). Significant differences between the three adult cell types were determined by one-way ANOVA with Tukey’s post hoc test. *P < 0.05, **P < 0.01, ***P < 0.001.
Citation: Reproduction and Fertility 3, 4; 10.1530/RAF-22-0068
mRNA expression levels of genes expressed throughout gestation. Scatter plots left in each subfigure of gene expression levels in fetal ovaries (n = 27) are from our previous publications (Hartanti et al. 2020b, Liu et al. 2020). Gene expression levels in cultured GREL cells (n = 7) and fetal fibroblast (n = 6) are presented in the middle graph of each subfigure. Data of gene expression in adult fibroblasts (n = 4), granulosa cells (GC; n = 5) and ovarian surface epithelial cells (OSE; n = 5) are presented as mean ± s.e.m. (normalised to PPIA and RPL32). Significant differences between the three adult cell types were determined by one-way ANOVA with Tukey’s post hoc test. *P < 0.05, ***P < 0.001.
Citation: Reproduction and Fertility 3, 4; 10.1530/RAF-22-0068
mRNA expression levels of genes expressed throughout gestation (continued). Scatter plots on the left in each subfigure show gene expression levels in fetal ovaries (n = 27) from our previous publications (Hartanti et al. 2020b, Liu et al. 2020). Gene expression levels in cultured GREL cells (n = 7) and fetal fibroblasts (n = 6) are presented in the middle graph of each subfigure. Data of gene expression in adult fibroblasts (n = 4), granulosa cells (GC; n = 5) and ovarian surface epithelial cells (OSE; n = 5) are presented as mean ± s.e.m. (normalised to PPIA and RPL32). Significant differences between the three adult cell types were determined by one-way ANOVA with Tukey’s post hoc test. *P < 0.05, **P < 0.01, ***P < 0.001.
Citation: Reproduction and Fertility 3, 4; 10.1530/RAF-22-0068
Expression of PCOS candidate genes in fetal ovarian cells
DENND1A and ERBB3 had significantly higher expression in GREL cells than fetal fibroblasts (Fig. 1E and F; P < 0.05 and P < 0.01). Even though there were no significant differences between GREL cells and fetal fibroblasts for HMGA2 and TGFB1I1 (Fig. 1A and 2A), fetal fibroblasts had the tendency to have higher HMGA2 and TGFB1I1 expression than GREL cells of the same gestational age (Supplementary Fig. 1A1 and B1). The other 19 genes did not present significant differences between GREL cells and fetal fibroblasts (Figs. 1-4). Gene expression of FBN3, ERBB3, FSHB, FSHR, ZBTB16 and LHCGR was hardly detectable in GREL or fetal fibroblasts (Figs. 1C, 1E, 1G, 2D, 2E and 4E). The gene expression in GREL cells and fetal fibroblasts was from fetuses younger than 200 days of gestation, which was shorter than from gene expression analyses in fetal ovaries examined throughout gestation.
Expression of PCOS candidate genes in adult ovarian cells
Gene expression levels of FSHR, AMH, LHCGR and a splice variant of FSHB exon 3 in adult granulosa cells were significantly higher than in fibroblasts and ovarian surface epithelial cells (Fig. 1G, 2D, 2F and 4E; P < 0.05, 0.01 or 0.001). In contrast, HMGA2 had a significantly lower expression in granulosa cells than adult fibroblasts and ovarian surface epithelial cells (Fig. 1A; P < 0.05, 0.01). TOX3, GATA4, ERBB3, DENND1A, IRF1, YAP1 and THADA were significantly higher in ovarian surface epithelial cells (Fig 1B, 1D-1F, 2G, 4A and 4F; P < 0.05, 0.01 or 0.001) than adult fibroblasts or granulosa cells. ERBB4 had a similar expression pattern but with no significant difference between adult fibroblasts and ovarian surface epithelial cells (Fig 4D; P > 0.05). INSR, ZBTB16, KRR1, RAB5B and SUOX were expressed significantly higher in both granulosa cells and ovarian surface epithelial cells than in adult fibroblasts (Fig 2B, 2E, 3B, 3C, and 4C; P < 0.05, 0.01 or 0.001). Similarly, RAD50 and C8H9orf3 had higher expression levels in either granulosa cells or ovarian surface epithelial cells than fibroblasts (Fig. 1H and 3A; P < 0.05, 0.01). FBN3, TGFB1I1, AR, PLGKRT, MAPRE1, FDFT1, NEIL2, and ARL14EP were expressed with no significant differences between the three adult cell types (Fig. 1C, 2A, 2C, 2H, 3D-3F and 4B; P > 0.05).
Fetal vs adult cells
HMGA2, GATA4, DENND1A, RAD50, TGFB1I1, INSR, AR, KRR1, RAB5B, MAPRE1, FDFT1, YAP1, SUOX and THADA were all more lowly expressed in adult than fetal fibroblasts (Table 1). GATA4, ERBB3, DENND1A, INSR, FSHR, ZBTB16, IRF1, C8H9orf3, KRR1, RAB5B and THADA were more highly expressed in ovarian surface epithelium than in GREL cells (Table 1). Gene expression of HMGA2, TOX3 and RAD50 was lower and expression of DENND1A, FSHB (exon 3), TGFB1I1, INSR, AR, FSHR, ZBTB16 and AMH was higher in the granulosa cells than in the GREL cells (Table 1).
Regulation of PCOS candidate genes in fetal fibroblast
We treated bovine fetal fibroblasts (n = 5 from 95, 101, 119, 135 and 232 days of gestation) from fetuses in second and third trimesters with different hormones, stimulators and growth factors separately (Supplementary Table 2) and determined their effects on the expression of eight PCOS candidate genes (ERBB3, ZBTB16, IRF1, PLGRKT, MAPRE1, FDFT1, NEIL2 and ARL14EP). The effects of these factors on other PCOS genes have been reported previously (Hartanti et al. 2020b) and effects of TGFB1 have been reported elsewhere (Hartanti et al. 2020b, Azumah et al. 2022). The current results demonstrated that apart from oestradiol (E2) and testosterone (T) of the factors tested (Supplementary Table 2) which increased the expression of ARL14EP (Supplementary Fig. 2E5; P < 0.05), other treatments had no significant effects on the gene expression (P > 0.05). In addition, we compared expression of genes in fetal fibroblasts cultured in EGF-containing medium (n = 6 from 51, 56, 73, 110, 127 and 177 days of gestation) with fetal fibroblasts cultured previously (Bastian et al. 2016) in medium without EGF and spanning similar times during gestation (n = 11 from 95, 101, 119, 135, 160, 165, 168, 170, 180, 198, 232 days of gestation). Fetal fibroblasts cultured in EGF-containing medium had lower expression of NEIL2 (Fig. 5A; P < 0.05) but higher expression of MAPRE1 (Fig. 5B; P < 0.05).
mRNA expression levels of eight newly examined PCOS candidate genes in fetal fibroblasts cultured in the presence or absence of EGF. Columns in white colour and black colours show gene expression in fetal fibroblasts cultured in the absence of EGF (n = 11) and in the presence of EGF (n = 6), respectively. Data of gene expression are presented as mean ± s.e.m. (normalised to PPIA and RPL32). Significantly differences between groups were determined by Student’s t-test. * P < 0.05.
Citation: Reproduction and Fertility 3, 4; 10.1530/RAF-22-0068
Discussion
This study reports on the expression of PCOS candidate genes in cultured fetal GREL cells and fetal fibroblasts from bovine fetuses younger than 200 days of gestation and compares these data to bovine ovarian fibroblasts, granulosa cells and surface epithelial cells isolated from adult ovaries as well as previously published data from whole fetal ovaries throughout the gestation (Hartanti et al. 2020b, Liu et al. 2020). Moreover, we determined the effects of different hormones and growth factors on the expression of PCOS candidate genes in order to identify potential regulators of those genes during the development of the fetal ovary.
Although many of the PCOS candidate genes were expressed in bovine fetal ovaries, FBN3, ERBB3, FSHB, LHCGR, FSHR and ZBTB16 levels were very low or hardly detectable in GREL cells and fetal fibroblasts isolated and cultured in vitro. Fibrillin 3 (FBN3), a structural component of extracellular matrix (Corson et al. 2004), previously showed a drastic decline in expression in in vitro cultures of bovine and human fetal ovarian fibroblasts (Bastian et al. 2016). ERBB3, a receptor in EGF receptor signalling pathways, was mainly expressed early in gestation of human and bovine fetal ovaries (Liu et al. 2020). In a study on mouse fetal gonads, ERBB3 was detected in primordial germ cells at 12.5 days post coitum, and the expression was downregulated at 14.5 days post coitum when primordial germ cells ceased to grow (Toyoda-Ohno et al. 1999). We assume that the decline of ERBB3 expression in the fetal ovary during gestation (Liu et al. 2020) resulted from the differentiation of primordial germ cells into oogonia/oocytes and the expansion of stroma in the fetal ovary (Hartanti et al. 2019). FSHB is normally expressed in the anterior pituitary; however, low expression of an alternative splice transcript from exon 3 of FSHB has been detected in the fetal ovary (Hartanti et al. 2020b). The absence of FSHB expression in GREL cells and fetal fibroblasts indicated that the potential transcriptional activity did not exist in either of the two fetal cell types examined. The receptors for two gonadotrophins, FSH and LH (FSHR and LHCGR), were expressed mostly in late gestation when folliculogenesis begins. This was in line with the observed lack of expression in our cultured fetal GREL cells and fetal fibroblasts which were both isolated from fetal ovaries from early and mid-gestation. LHCGR was exclusively expressed in adult granulosa cells and confirms findings of other studies in the same and other species (Cannon et al. 2009, Gulappa et al. 2017, Convissar et al. 2019). FSHR appeared to be additionally expressed in ovarian surface epithelial cells but at a lower level than in granulosa cells. FSHR has been identified previously in ovarian surface epithelial cells (Zheng et al. 1996, Bose 2008) and FSH has been shown to stimulate growth of ovarian surface epithelial cells (Choi et al. 2002). The lack of expression of FSHR and LHCGR in GREL cells suggests that they are not regulated by FSH or LH, and in any event, these hormones are not secreted until about third to half way through gestation (Lanciotti et al. 2018). In mouse granulosa cells, the progesterone receptor binds to an intron of ZBTB16 (Dinh et al. 2019) and expression of the progesterone receptor can induce the expression of ZBTB16 (Sriraman et al. 2010). Moreover, the progesterone receptor was also found to be expressed in human and non-human primate ovarian surface epithelial cells (Lau et al. 1999, Wright et al. 2011). Therefore, it could be that the expression of ZBTB16 in adult granulosa cells and ovarian surface epithelial cells would be relevant for the action of progesterone and the expression of ZBTB16 in the fetal ovary at the late stage of gestation is likely due to the formation of granulosa cells and ovarian surface epithelial cells.
HMGA2 and TGFB1I1 were the two genes which had the highest correlations with gestational age in developing bovine fetal ovaries (Hartanti et al. 2020b); HMGA2 was highly expressed in early and TGFB1I1 late in gestation. High mobility group A (HMGA1 and HMGA2) are small non-histone proteins which can bind DNA and modify the chromatin state. In the human ovary, HMGA2 was found to be overexpressed in ovarian carcinoma (Tagawa et al. 2010) and global gene analysis has revealed HMGA2-mediated tumourigenesis in the ovary (Wu et al. 2011). Moreover, the expression of HMGA2 induced cell proliferation with increased expression of cyclin B2 and cyclin E in umbilical cord blood-derived stromal cells and pituitary adenomas (De Martino et al. 2009, Yu et al. 2013). Likewise, fetal ovarian fibroblasts exhibited greater proliferation and higher gene expression of cyclin B2 and cyclin E than GREL cells (Liu et al. 2022), and fetal fibroblasts tended to have potentially higher expression of HMGA2. In the bovine fetal ovary, stroma exhibited a higher proliferation index early in gestation than in late gestation (Hartanti et al. 2019). Therefore, the high expression of HMGA2 in early gestation might be responsible for cell proliferation in the fetal ovary, which is critical to early organogenesis (Vignali & Marracci 2020). TGFB1I1 was expressed higher in late gestation and showed no differences among adult cell types. TGFB1I1 encodes the coactivator of androgen receptor (AR) and affects cell adhesion, growth and motility which are regulated by androgen (Leach et al. 2014). TGFB1I1 and other genes involved in TGFB1 signalling (TGFB2 and 3, LTBP2-4, TGFBR2 and 3) and AR, which was highly correlated with TGFB1I1, exhibited increased expression levels after 200 days of gestation (Hatzirodos et al. 2019, Hartanti et al. 2020b). TGFB1I1 gene expression was detected in adult human cumulus cells and it exhibited higher expression levels in normal cumulus cells than cumulus cells from PCOS ovaries (Haouzi et al. 2012). Therefore, TGFB1 signalling potentially is active during the later stages of gestation.
In the adult bovine ovarian cells, TOX3, GATA4, DENND1A and RAD50 were all predominantly expressed in epithelial cells (granulosa cells and ovarian surface epithelial cells). Combined with the higher expression of DENND1A in GREL cells, the declining expression of these four genes in the developing ovary may be due to the increasing proportion of fibroblasts and stroma during gestation (Hartanti et al. 2019). On the contrary, INSR, AMH and IRF1 which are also expressed predominantly in epithelial cells (granulosa cells and ovarian surface epithelial cells) increased in expression with increasing gestational age (Hartanti et al. 2020b). In the human ovary, AMH shows only weak expression in granulosa cells of primordial follicles but high expression levels in granulosa cells of secondary, pre-antral and small antral follicles (Weenen et al. 2004). INSR encodes the insulin receptor, and its expression in granulosa cells is essential for the differentiation of granulosa cells and ovulation (Sekulovski et al. 2020). Gene expression of IRF1 is found in primary cultured human ovarian surface epithelial cells (Zeimet et al. 2009), and IRF1 is involved in the regulation of the class II tumour-suppressor H-REV107-1 in human ovarian surface epithelial cells (Sers et al. 2002). Moreover, these three genes were not predominantly expressed in GREL cells. Therefore, we assume that GREL cells do not express AMH, INSR or IRF1 until they differentiate into granulosa cells or ovarian surface epithelial cells. Similarly, C8H9orf3, KRR1, RAB5B, YAP1, SUOX, ERBB4 and THADA demonstrated differences in adult cell types but were constantly expressed throughout the gestation, which indicated those genes did not exhibit differences during gestational stages until neonatal stage or adulthood. On the contrary, the expression of AR and PLGRKT in the fetal ovary was correlated with gestational age, but the expression of the two genes did not show significant differences among adult cell types. AR had a higher expression level in the fetal ovary during the third trimester than adult fibroblasts, ovarian surface epithelial cells and granulosa cells, which was consistent with the earlier comparison of AR expression in the fetal ovary and adult ovary (Hartanti et al. 2020b). Previous studies demonstrated that high levels of androgen from maternal sources during gestation could lead to a fetal origin of PCOS and result in PCOS in adolescence and adulthood (Sir-Petermann et al. 2002, Rosenfield & Ehrmann 2016, Walters 2016, Filippou & Homburg 2017). PLGRKT encodes the unique receptor of plasminogen, which is a precursor of plasmin, involved in the degradation of blood plasma clots, and is present in blood. Unlike AR, PLGRKT demonstrated consistent expression in the fetal ovary indicating that PLGRKT was expressed throughout the ovary since the ovarian vascular system was established when the vascularised stroma penetrated into the ovary (Hummitzsch et al. 2013). Similarly, MAPRE1, FDFT1, NEIL2 and ARL14EP were constantly expressed throughout gestation and exhibited no differences in adult cells. Perhaps, they are essential for the normal physiology of ovarian cells from early development of the ovary onwards.
The effects of 18 h of treatments by different hormones, stimulators and growth factors on the expression of PCOS genes in bovine fetal fibroblasts have been reported earlier (Hartanti et al. 2020b, Azumah et al. 2022), and the current study completes the reporting with a further eight PCOS candidate genes (ERBB3, ZBTB16, IRF1, PLGRKT, MAPRE1, FDFT1, NEIL2 and ARL14EP) examined. Overall, TGFB1 was by far the most important regulator, inhibiting 7 (INSR, C8H9orf3, RAD50, ERBB3, NEIL2, IRF1 and ZBTB16) of the 25 PCOS candidate genes (Azumah et al. 2022). We have also considered that TGFB1 action in the fetal ovary maybe important for the development of PCOS in later life as it also inhibits the expression of AR and stimulates its cofactor TGFB1I1 (Hartanti et al. 2020b).
In the current study, oestradiol and testosterone increased the expression of ARL14EP. We also compared the expression of genes in fetal fibroblasts cultured for long term previously (Liu et al. 2022) in EGF-containing medium with fetal fibroblasts cultured previously (Bastian et al. 2016) in medium without EGF. Fetal fibroblasts cultured in EGF-containing medium had lower expression of NEIL2 but higher expression of MAPRE1. The effects were relatively small but statistically significant and the physiological relevance is not clear at this stage.
Summary and conclusions
The fetal bovine ovary has two major somatic cell types shown previously to be of different cellular origins (Hummitzsch et al. 2013) and different morphologies and to differentially express 15 genes (Liu et al. 2022). Despite minimal differences between GREL cells and fetal fibroblasts being observed in the current study, there were differences with adult cells. While 14 genes were more lowly expressed in adult fetal fibroblasts than fetal fibroblasts, 11 genes were more highly expressed in ovarian surface epithelium than in GREL cells. Three genes were lower and eight genes higher in granulosa cells than in the GREL cells. One caveat of the current studies is that the cells had to be cultured to achieve purification, and as we showed here and previously, culture (Bastian et al. 2016) and the culture media influence the gene expression patterns, at least in ovarian fetal fibroblasts. Clearly, there is a need for a better system of purification of the two somatic cell types to be able to better identify expression patterns of PCOS genes in these cells in vivo. This is likely critical for a full understanding of the aetiology of PCOS.
Supplementary material
This is linked to the online version of the paper at https://doi.org/10.1530/RAF-220068.
Declaration of interest
R A A reports consultancy work for Ferring, Merck, IBSA, Roche Diagnostics, NeRRe Therapeutics and Sojournix Inc. The other authors of this manuscript have nothing to declare and no conflict of interest that could be perceived as prejudicing the impartiality of the research reported.
Funding
Funding was received from Adelaide University China Fee Scholarship (ML; https://www.csc.edu.cn/chuguo), Adelaide Graduate Research Scholarship (NAB; http://www.adelaide.edu.au/), Australia Awards Scholarship (MDH; https://www.dfat.gov.au/people-to-people/australia-awards/australia-awards-scholarships), Robinson Research Institute Career Development Fellowship (KH ; https://www.adelaide.edu.au/robinson-research-institute/) and Building On Ideas Grant (KH; https://www.adelaide.edu.au/robinson-research-institute/), National Health and Medical Research Council of Australia Centre for Research Excellence in the Evaluation, Management and Health Care Needs of Polycystic Ovary Syndrome (RJR; GTN1078444; https://www.nhmrc.gov.au/) and The Centre for Research Excellence on Women’s Health in Reproductive life (RJR and KH; GTN1171592; https://www.nhmrc.gov.au/) and the UK Medical Research Council (RAA; grant No. G1100357; https://mrc.ukri.org/). The funders did not play any role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Ethical approval
The bovine ovaries used in this study were scavenged from animals that were being processed for human consumption and were not owned by the authors or their institutions. As such the University of Adelaide’s Animal Ethics Committee only requires notification of this.
Author contribution statement
M L was involved in conceptualisation, formal analysis, investigation, methodology and writing. K H was involved in conceptualisation, formal analysis, funding acquisition, methodology, project administration, resources and editing. R J R was involved in conceptualisation, formal analysis, funding acquisition, methodology, project administration, resources, writing. R A A was involved in funding acquisition, writing, reviewing and editing. N A B and M H D were involved in methodology. H F I-R was involved in project administration and writing.
Acknowledgements
The authors thank Thomas Foods International (Murray Bridge, SA), Strath Meats (Strathalbyn, SA) and The Midfield Group (Warrnambool, VIC) for providing bovine tissues and Mrs Wendy M. Bonner for the collection of bovine fetal and adult ovaries.
References
Azumah R, Hummitzsch K, Hartanti MD, St John JC, Anderson RA & Rodgers RJ 2021 Analysis of upstream regulators, networks, and pathways associated with the expression patterns of polycystic ovary syndrome candidate genes during fetal ovary development. Frontiers in Genetics 12 762177. (https://doi.org/10.3389/fgene.2021.762177)
Azumah R, Liu M, Hummitzsch K, Bastian NA, Hartanti MD, Irving-Rodgers HF, Anderson RA & Rodgers RJ 2022 Candidate genes for polycystic ovary syndrome are regulated by TGFβ in the bovine foetal ovary. Human Reproduction 37 1244–1254. (https://doi.org/10.1093/humrep/deac049)
Azziz R 2018 Polycystic ovary syndrome. Obstetrics and Gynecology 132 321–336. (https://doi.org/10.1097/AOG.0000000000002698)
Bastian NA, Bayne RA, Hummitzsch K, Hatzirodos N, Bonner WM, Hartanti MD, Irving-Rodgers HF, Anderson RA & Rodgers RJ 2016 Regulation of fibrillins and modulators of TGFβ in fetal bovine and human ovaries. Reproduction 152 127–137. (https://doi.org/10.1530/REP-16-0172)
Bose CK 2008 Follicle stimulating hormone receptor in ovarian surface epithelium and epithelial ovarian cancer. Oncology Research 17 231–238. (https://doi.org/10.3727/096504008786111383)
Bozdag G, Mumusoglu S, Zengin D, Karabulut E & Yildiz BO 2016 The prevalence and phenotypic features of polycystic ovary syndrome: a systematic review and meta-analysis. Human Reproduction 31 2841–2855. (https://doi.org/10.1093/humrep/dew218)
Cannon JD, Seekallu SV, Vandevoort CA & Chaffin CL 2009 Association of luteinizing hormone receptor gene expression with cell cycle progression in granulosa cells. American Journal of Physiology. Endocrinology and Metabolism 296 E1392–E1399. (https://doi.org/10.1152/ajpendo.90965.2008)
Chang RJ 2007 The reproductive phenotype in polycystic ovary syndrome. Nature Clinical Practice. Endocrinology and Metabolism 3 688–695. (https://doi.org/10.1038/ncpendmet0637)
Choi KC, Kang SK, Tai CJ, Auersperg N & Leung PC 2002 Follicle-stimulating hormone activates mitogen-activated protein kinase in preneoplastic and neoplastic ovarian surface epithelial cells. Journal of Clinical Endocrinology and Metabolism 87 2245–2253. (https://doi.org/10.1210/jcem.87.5.8506)
Convissar S, Winston NJ, Fierro MA, Scoccia H, Zamah AM & Stocco C 2019 Sp1 regulates steroidogenic genes and LHCGR expression in primary human luteinized granulosa cells. Journal of Steroid Biochemistry and Molecular Biology 190 183–192. (https://doi.org/10.1016/j.jsbmb.2019.04.003)
Cooney LG, Lee I, Sammel MD & Dokras A 2017 High prevalence of moderate and severe depressive and anxiety symptoms in polycystic ovary syndrome: a systematic review and meta-analysis. Human Reproduction 32 1075–1091. (https://doi.org/10.1093/humrep/dex044)
Corson GM, Charbonneau NL, Keene DR & Sakai LY 2004 Differential expression of fibrillin-3 adds to microfibril variety in human and avian, but not rodent, connective tissues. Genomics 83 461–472. (https://doi.org/10.1016/j.ygeno.2003.08.023)
Das M, Djahanbakhch O, Hacihanefioglu B, Saridogan E, Ikram M, Ghali L, Raveendran M & Storey A 2008 Granulosa cell survival and proliferation are altered in polycystic ovary syndrome. Journal of Clinical Endocrinology and Metabolism 93 881–887. (https://doi.org/10.1210/jc.2007-1650)
Day F, Karaderi T, Jones MR, Meun C, He C, Drong A, Kraft P, Lin N, Huang H & Broer L et al.2018 Large-scale genome-wide meta-analysis of polycystic ovary syndrome suggests shared genetic architecture for different diagnosis criteria. PLoS Genetics 14 e1007813. 9https://doi.org/10.1371/journal.pgen.1007813)
De Martino I, Visone R, Wierinckx A, Palmieri D, Ferraro A, Cappabianca P, Chiappetta G, Forzati F, Lombardi G & Colao A et al.2009 HMGA proteins up-regulate CCNB2 gene in mouse and human pituitary adenomas. Cancer Research 69 1844–1850. (https://doi.org/10.1158/0008-5472.CAN-08-4133)
Dinh DT, Breen J, Akison LK, DeMayo FJ, Brown HM, Robker RL & Russell DL 2019 Tissue-specific progesterone receptor-chromatin binding and the regulation of progesterone-dependent gene expression. Scientific Reports 9 11966. (https://doi.org/10.1038/s41598-019-48333-8)
Edmondson RJ, Monaghan JM & Davies BR 2002 The human ovarian surface epithelium is an androgen responsive tissue. British Journal of Cancer 86 879–885. (https://doi.org/10.1038/sj.bjc.6600154)
Erickson GF, Magoffin DA, Garzo VG, Cheung AP & Chang RJ 1992 Granulosa cells of polycystic ovaries: are they normal or abnormal? Human Reproduction 7 293–299. (https://doi.org/10.1093/oxfordjournals.humrep.a137638)
Ewens KG, Stewart DR, Ankener W, Urbanek M, McAllister JM, Chen C, Baig KM, Parker SC, Margulies EH & Legro RS et al.2010 Family-based analysis of candidate genes for polycystic ovary syndrome. Journal of Clinical Endocrinology and Metabolism 95 2306–2315. (https://doi.org/10.1210/jc.2009-2703)
Fauser BC, Tarlatzis BC, Rebar RW, Legro RS, Balen AH, Lobo R, Carmina E, Chang J, Yildiz BO & Laven JS et al.2012 Consensus on women's health aspects of polycystic ovary syndrome (PCOS): the Amsterdam ESHRE/ASRM-Sponsored 3rd PCOS Consensus Workshop Group.Fertility & Sterility 97 28–38.(https://doi.org/10.1016/j.fertnstert.2011.09.024)
Fernandez RC, Moore VM, Van Ryswyk EM, Varcoe TJ, Rodgers RJ, March WA, Moran LJ, Avery JC, McEvoy RD & Davies MJ 2018 Sleep disturbances in women with polycystic ovary syndrome: prevalence, pathophysiology, impact and management strategies. Nature and Science of Sleep 10 45–64. (https://doi.org/10.2147/NSS.S127475)
Filippou P & Homburg R 2017 Is foetal hyperexposure to androgens a cause of PCOS? Human Reproduction Update 23 421–432. (https://doi.org/10.1093/humupd/dmx013)
Gulappa T, Menon B & Menon KMJ 2017 LHCGR expression during follicle stimulating hormone-induced follicle growth is negatively regulated by eukaryotic initiation factor 5A. Endocrinology 158 2672–2679. (https://doi.org/10.1210/en.2017-00113)
Haoula Z, Salman M & Atiomo W 2012 Evaluating the association between endometrial cancer and polycystic ovary syndrome. Human Reproduction 27 1327–1331. (https://doi.org/10.1093/humrep/des042)
Haouzi D, Assou S, Monzo C, Vincens C, Dechaud H & Hamamah S 2012 Altered gene expression profile in cumulus cells of mature MII oocytes from patients with polycystic ovary syndrome. Human Reproduction 27 3523–3530. (https://doi.org/10.1093/humrep/des325)
Hartanti MD, Hummitzsch K, Bonner WM, Bastian NA, Irving-Rodgers HF & Rodgers RJ 2020a Formation of the bovine ovarian surface epithelium during fetal development. Journal of Histochemistry and Cytochemistry 68 113–126. (https://doi.org/10.1369/0022155419896797)
Hartanti MD, Hummitzsch K, Irving-Rodgers HF, Bonner WM, Copping KJ, Anderson RA, McMillen IC, Perry VEA & Rodgers RJ 2019 Morphometric and gene expression analyses of stromal expansion during development of the bovine fetal ovary. Reproduction, Fertility, and Development 31 482–495. (https://doi.org/10.1071/RD18218)
Hartanti MD, Rosario R, Hummitzsch K, Bastian NA, Hatzirodos N, Bonner WM, Bayne RA, Irving-Rodgers HF, Anderson RA & Rodgers RJ 2020b Could perturbed fetal development of the ovary contribute to the development of polycystic ovary syndrome in later life? PLoS One 15 e0229351. (https://doi.org/10.1371/journal.pone.0229351)
Hatzirodos N, Bayne RA, Irving-Rodgers HF, Hummitzsch K, Sabatier L, Lee S, Bonner W, Gibson MA, Rainey WE & Carr BR et al.2011 Linkage of regulators of TGF-beta activity in the fetal ovary to polycystic ovary syndrome. FASEB Journal 25 2256–2265. (https://doi.org/10.1096/fj.11-181099)
Hatzirodos N, Hummitzsch K, Irving-Rodgers HF, Breen J, Perry VEA, Anderson RA & Rodgers RJ 2019 Transcript abundance of stromal and thecal cell related genes during bovine ovarian development. PLoS One 14 e0213575. (https://doi.org/10.1371/journal.pone.0213575)
Heeren AM, van Iperen L, Klootwijk DB, de Melo Bernardo A, Roost MS, Gomes Fernandes MM, Louwe LA, Hilders CG, Helmerhorst FM & van der Westerlaken LA et al.2015 Development of the follicular basement membrane during human gametogenesis and early folliculogenesis. BMC Developmental Biology 15 4. (https://doi.org/10.1186/s12861-015-0054-0)
Hummitzsch K, Hatzirodos N, Irving-Rodgers HF, Hartanti MD, Perry VEA, Anderson RA & Rodgers RJ 2019 Morphometric analyses and gene expression related to germ cells, gonadal ridge epithelial-like cells and granulosa cells during development of the bovine fetal ovary. PLoS One 14 e0214130. (https://doi.org/10.1371/journal.pone.0214130)
Hummitzsch K, Irving-Rodgers HF, Hatzirodos N, Bonner W, Sabatier L, Reinhardt DP, Sado Y, Ninomiya Y, Wilhelm D & Rodgers RJ 2013 A new model of development of the mammalian ovary and follicles. PLoS One 8 e55578. (https://doi.org/10.1371/journal.pone.0055578)
Jones MR & Goodarzi MO 2016 Genetic determinants of polycystic ovary syndrome: progress and future directions. Fertility and Sterility 106 25–32. (https://doi.org/10.1016/j.fertnstert.2016.04.040)
Kakuta H, Iguchi T & Sato T 2018 The involvement of granulosa cells in the regulation by gonadotropins of Cyp17a1 in theca cells. In Vivo 32 1387–1401. (https://doi.org/10.21873/invivo.11391)
Lanciotti L, Cofini M, Leonardi A, Penta L & Esposito S 2018 Up-to-date review about minipuberty and overview on hypothalamic-pituitary-gonadal axis activation in fetal and neonatal life. Frontiers in Endocrinology (Lausanne) 9 410. (https://doi.org/10.3389/fendo.2018.00410)
Lau KM, Mok SC & Ho SM 1999 Expression of human estrogen receptor-alpha and -beta, progesterone receptor, and androgen receptor mRNA in normal and malignant ovarian epithelial cells. Proceedings of the National Academy of Sciences of the United States of America 96 5722–5727. (https://doi.org/10.1073/pnas.96.10.5722)
Leach DA, Need EF, Trotta AP, Grubisha MJ, DeFranco DB & Buchanan G 2014 Hic-5 influences genomic and non-genomic actions of the androgen receptor in prostate myofibroblasts. Molecular and Cellular Endocrinology 384 185–199. (https://doi.org/10.1016/j.mce.2014.01.004)
Liu M, Hummitzsch K, Bastian NA, Hartanti MD, Wan Q, Irving-Rodgers HF, Anderson RA & Rodgers RJ 2022 Isolation, culture and characterisation of bovine ovarian fetal fibroblasts and gonadal ridge epithelial-like cells and comparison to their adult counterparts. PLoS One 17 e0268467. (https://doi.org/10.1371/journal.pone.0268467)
Liu M, Hummitzsch K, Hartanti MD, Rosario R, Bastian NA, Hatzirodos N, Bonner WM, Irving-Rodgers HF & Laven JSE et al.2020 Analysis of expression of candidate genes for polycystic ovary syndrome in adult and fetal human and fetal bovine ovaries. Biology of Reproduction 103 840–853. (https://doi.org/10.1093/biolre/ioaa119)
Lizneva D, Suturina L, Walker W, Brakta S, Gavrilova-Jordan L & Azziz R 2016 Criteria, prevalence, and phenotypes of polycystic ovary syndrome. Fertility and Sterility 106 6–15. (https://doi.org/10.1016/j.fertnstert.2016.05.003)
March WA, Moore VM, Willson KJ, Phillips DIW, Norman RJ & Davies MJ 2010 The prevalence of polycystic ovary syndrome in a community sample assessed under contrasting diagnostic criteria. Human Reproduction 25 544–551. (https://doi.org/10.1093/humrep/dep399)
Ose J, Poole EM, Schock H, Lehtinen M, Arslan AA, Zeleniuch-Jacquotte A, Visvanathan K, Helzlsouer K, Buring JE & Lee IM et al.2017 Androgens are differentially associated with ovarian cancer subtypes in the ovarian cancer cohort consortium. Cancer Research 77 3951–3960. (https://doi.org/10.1158/0008-5472.CAN-16-3322)
Rosenfield RL & Ehrmann DA 2016 The pathogenesis of polycystic ovary syndrome (PCOS): the hypothesis of PCOS as functional ovarian hyperandrogenism revisited. Endocrine Reviews 37 467–520. (https://doi.org/10.1210/er.2015-1104)
Russe I 1983 Oogenesis in cattle and sheep. Bibliotheca Anatomica 24 77–92.
Schildkraut JM, Schwingl PJ, Bastos E, Evanoff A & Hughes C 1996 Epithelial ovarian cancer risk among women with polycystic ovary syndrome. Obstetrics and Gynecology 88 554–559. (https://doi.org/10.1016/0029-7844(9600226-8)
Sekulovski N, Whorton AE, Shi M, Hayashi K & MacLean JA 2nd 2020 Periovulatory insulin signaling is essential for ovulation, granulosa cell differentiation, and female fertility. FASEB Journal 34 2376–2391. (https://doi.org/10.1096/fj.201901791R)
Sers C, Husmann K, Nazarenko I, Reich S, Wiechen K, Zhumabayeva B, Adhikari P, Schroder K, Gontarewicz A & Schafer R 2002 The class II tumour suppressor gene H-REV107-1 is a target of interferon-regulatory factor-1 and is involved in IFNgamma-induced cell death in human ovarian carcinoma cells. Oncogene 21 2829–2839. (https://doi.org/10.1038/sj.onc.1205377)
Sir-Petermann T, Maliqueo M, Angel B, Lara HE, Perez-Bravo F & Recabarren SE 2002 Maternal serum androgens in pregnant women with polycystic ovarian syndrome: possible implications in prenatal androgenization. Human Reproduction 17 2573–2579. (https://doi.org/10.1093/humrep/17.10.2573)
Sriraman V, Sinha M & Richards JS 2010 Progesterone receptor-induced gene expression in primary mouse granulosa cell cultures. Biology of Reproduction 82 402–412. (https://doi.org/10.1095/biolreprod.109.077610)
Stewart DR, Dombroski BA, Urbanek M, Ankener W, Ewens KG, Wood JR, Legro RS, Strauss JF 3rd, Dunaif A & Spielman RS 2006 Fine mapping of genetic susceptibility to polycystic ovary syndrome on chromosome 19p13.2 and tests for regulatory activity. Journal of Clinical Endocrinology and Metabolism 91 4112–4117. (https://doi.org/10.1210/jc.2006-0951)
Tagawa T, Morgan R, Cristea MC, Wakabayashi MT, Lin H, Wang Y, Chu P, Liu X, Ann D & Yen Y 2010 Comparison of HMGA2 expression in serous versus endometrioid subtypes of human ovarian carcinoma. Journal of Clinical Oncology 28 e15528. (https://doi.org/10.1200/jco.2010.28.15_suppl.e15528)
Tata B, Mimouni NEH, Barbotin AL, Malone SA, Loyens A, Pigny P, Dewailly D, Catteau-Jonard S, Sundstrom-Poromaa I & Piltonen TT et al.2018 Elevated prenatal anti-Mullerian hormone reprograms the fetus and induces polycystic ovary syndrome in adulthood. Nature Medicine 24 834–846. (https://doi.org/10.1038/s41591-018-0035-5)
Teede HJ, Misso ML, Costello MF, Dokras A, Laven J, Moran L, Piltonen T, Norman RJ & International PCOS Network 2018 Recommendations from the international evidence-based guideline for the assessment and management of polycystic ovary syndrome. Fertility and Sterility 110 364–379. (https://doi.org/10.1016/j.fertnstert.2018.05.004)
Thomas DP 1995 Clotting factor concentrated--whither purity? Thrombosis and Haemostasis 74 1604–1606. (https://doi.org/10.1055/s-0038-1649989)
Toyoda-Ohno H, Obinata M & Matsui Y 1999 Members of the ErbB receptor tyrosine kinases are involved in germ cell development in fetal mouse gonads. Developmental Biology 215 399–406. (https://doi.org/10.1006/dbio.1999.9482)
Vignali R & Marracci S 2020 HMGA genes and proteins in development and evolution. International Journal of Molecular Sciences 21. (https://doi.org/10.3390/ijms21020654)
Walters KA 2016 Androgens in polycystic ovary syndrome: lessons from experimental models. Current Opinion in Endocrinology, Diabetes, and Obesity 23 257–263. (https://doi.org/10.1097/MED.0000000000000245)
Weenen C, Laven JS, Von Bergh AR, Cranfield M, Groome NP, Visser JA, Kramer P, Fauser BC & Themmen AP 2004 Anti-Mullerian hormone expression pattern in the human ovary: potential implications for initial and cyclic follicle recruitment. Molecular Human Reproduction 10 77–83. (https://doi.org/10.1093/molehr/gah015)
Wright JW, Jurevic L & Stouffer RL 2011 Dynamics of the primate ovarian surface epithelium during the ovulatory menstrual cycle. Human Reproduction 26 1408–1421. (https://doi.org/10.1093/humrep/der057)
Wu J, Liu Z, Shao C, Gong Y, Hernando E, Lee P, Narita M, Muller W, Liu J & Wei JJ 2011 HMGA2 overexpression-induced ovarian surface epithelial transformation is mediated through regulation of EMT genes. Cancer Research 71 349–359. (https://doi.org/10.1158/0008-5472.CAN-10-2550)
Yu KR, Park SB, Jung JW, Seo MS, Hong IS, Kim HS, Seo Y, Kang TW, Lee JY & Kurtz A et al.2013 HMGA2 regulates the in vitro aging and proliferation of human umbilical cord blood-derived stromal cells through the mTOR/p70s6K signaling pathway. Stem Cell Research 10 156–165. (https://doi.org/10.1016/j.scr.2012.11.002)
Yuanyuan Z, Zeqin W, Xiaojie S, Liping L, Yun X & Jieqiong Z 2019 Proliferation of ovarian granulosa cells in polycystic ovarian syndrome is regulated by MicroRNA-24 by targeting wingless-type family member 2B (WNT2B) Medical Science Monitor 25 4553–4559. (https://doi.org/10.12659/MSM.915320)
Zeimet AG, Reimer D, Wolf D, Fiegl H, Concin N, Wiedemair A, Wolf AM, Rumpold H, Muller-Holzner E & Marth C 2009 Intratumoral interferon regulatory factor (IRF)-1 but not IRF-2 is of relevance in predicting patient outcome in ovarian cancer. International Journal of Cancer 124 2353–2360. (https://doi.org/10.1002/ijc.24214)
Zheng W, Magid MS, Kramer EE & Chen YT 1996 Follicle-stimulating hormone receptor is expressed in human ovarian surface epithelium and fallopian tube. American Journal of Pathology 148 47–53.
Zhou F, Shi LB & Zhang SY 2017 Ovarian fibrosis: A phenomenon of concern. Chinese Medical Journal 130 365–371. (https://doi.org/10.4103/0366-6999.198931)
