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Physiol. Genomics 33: 193-204, 2008. First published February 19, 2008; doi:10.1152/physiolgenomics.00274.2007
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Received 21 November 2007; accepted in final form 15 February 2008.
Physiological Genomics 33:193-204 (2008)
1094-8341/08 $8.00 © 2008 American Physiological Society

Differential expression of signal transduction factors in ovarian follicle development: a functional role for betaglycan and FIBP in granulosa cells in cattle

N. Forde1, M. Mihm2, M. J. Canty1, A. E. Zielak1, P. J. Baker2, S. Park1, P. Lonergan1, G. W. Smith3, P. M. Coussens3, J. J. Ireland3 and A. C. O. Evans1

1 School of Agriculture Food Science and Veterinary Medicine and the Conway Institute for Biomolecular and Biomedical Research, College of Life Sciences, University College Dublin, Belfield, Dublin, Ireland
2 Division of Cell Sciences, Faculty of Veterinary Medicine, University of Glasgow, Glasgow, United Kingdom
3 Department of Animal Science and Center for Animal Functional Genomics, Michigan State University, East Lansing, Michigan


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 GRANTS
 REFERENCES
 
Ovarian follicles develop in groups yet individual follicles follow different growth trajectories. This growth and development are regulated by endocrine and locally produced growth factors that use a myriad of receptors and signal transduction pathways to exert their effects on theca and granulosa cells. We hypothesize that differential growth may be due to differences in hormonal responsiveness that is partially mediated by differences in expression of genes involved in signal transduction. We used the bovine dominant follicle model, microarrays, quantitative real-time PCR and RNA interference to examine this. We identified 83 genes coding for signal transduction molecules and validated a subset of them associated with different stages of the follicle wave. We suggest important roles for CAM kinase-1 and EphA4 in theca cells and BCAR1 in granulosa cells for the development of dominant follicles and for betaglycan and FIBP in granulosa cells of regressing subordinate follicles. Inhibition of genes for betaglycan and FIBP in granulosa cells in vitro suggests that they inhibit estradiol production in regressing subordinate follicles.

signaling; RNA interference; fibroblast growth factor intracellular binding protein


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 GRANTS
 REFERENCES
 
FOLLICLES DEVELOP IN A wave-like pattern in a number of species including cattle and humans (23, 39, 41). A follicle wave is characterized by the synchronous growth of a cohort of antral follicles, one of which is selected to become the dominant follicle, while all other follicles regress and undergo apoptosis at various stages of the wave. The growth of follicles is regulated by endocrine hormones and locally produced growth factors. The main hormones/growth factors of interest are the gonadotrophins [luteinizing hormone (LH) and follicle stimulating hormone (FSH)], members of the transforming growth factor (TGF)-β superfamily (including activins, inhibins, and follistatin), FGF family members and the insulin-like growth factor (IGF) system including the IGFs, their binding proteins and binding protein proteases (21, 29, 45). Follicle growth is also reliant on the steroidogenic capacity of individual follicles and the production of high levels of estradiol is a major characteristic of the dominant follicle compared with subordinate follicles (25, 26).

These numerous extracellular hormones act by binding to specific receptors, and activation of multiple signaling pathways to either promote the growth of the dominant follicle or suppress and cause regression of the subordinate follicles. A well known example of this is the signaling of FSH and LH through their respective receptors to increase cAMP and activation of protein kinase A (PKA) (36, 37), both of which promote cellular growth and proliferation. The actions of some other signal transduction pathways have been studied in relation to ovarian follicle development. For example, death of subordinate and nonovulatory dominant follicles is mediated via proapoptotic pathways and granulosa cell survival is mediated in part by PKA, PKB, PKC, and MAP kinase signaling pathways (27, 38).

The above examples of cell signaling are by no means exhaustive and the full extent of the complex interplay of signaling in ovarian follicles remains to be described. Here we develop the hypothesis that differential growth of ovarian follicles is associated with the expression of genes for signal transduction factors and that these genes have a role in follicle function. The first aim was to utilize microarray analysis and quantitative real-time PCR (Q-RT-PCR) to determine the differential expression of genes with signal transducer activity and/or genes involved in signal transduction (GO identifiers GO:0004871 and GO:0007165, respectively) that may be involved in enhancing or reducing the steroidogenic capacity of ovarian follicles. Secondly, to determine the functional significance of two of these genes utilizing RNA interference in granulosa cell cultured in vitro and measuring the effect knockdown of these genes has on steroid production.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
 DISCUSSION
 GRANTS
 REFERENCES
 
Experiment 1: Differential Gene Expression
In this experiment microarrays were used to detect differential expression of genes involved in signal transduction in dominant compared with subordinate follicles; Q-RT-PCR was used to validate differential expression.

Animals and tissue processing.
Four normal cycling cross-bred beef heifers were synchronized with a luteolytic dose of prostaglandin (Prosolovin, Intervet, Ireland). All animals were observed for estrus behavior every 4–8 h and follicle development was monitored daily by transrectal ultrasonography. Animals were ovariectomized by colpotomy (14) between days 2.5 and 3.5 of the estrous cycle, and all follicles >4 mm in diameter were dissected from the ovaries. To ensure the dominant and largest subordinate follicle were chosen for the microarray experiment the follicle diameter for all follicles >4 mm were measured and follicular fluid aspirated. Both estradiol and progesterone assays were performed on the follicular fluid to ensure that the classification of the dominant and largest subordinate follicle for each animal was correct. Granulosa cells were scraped from the theca layer by a glass scraper. The theca layer was then peeled away from the stroma with a forceps. The theca enriched layer and the granulosa cells were then stored in RNAlater (Ambion, Huntingdon, UK) and snap frozen in liquid nitrogen. RNA was extracted using the TRIzol (Molecular Research Center) extraction method as per manufacturer's instructions and as previously described (16).

Microarray analysis and Q-RT-PCR.
Detection of differential gene expression between the dominant and first largest subordinate follicle was carried out by a validated BOTL4 DNA microarray analysis as previously described (17). Genes that were detected as being differentially expressed with signal transduction or signal transducing activity (GO identities: GO:0007165 and GO:0004871) were noted, and the differential expression of a subset of genes was validated by Q-RT-PCR. Primers for all genes were designed using Primer Express Software (Perkin Elmer) and synthesized by Invitrogen Life Technologies (Table 1). All forward and reverse primers for all genes were chosen as close to the 3' end as possible and used at a final concentration of 900 nM each. β-Actin was used as the normalizer gene as previously published (5, 17, 19, 38, 40, 48, 49). cDNA was synthesized from total RNA from each individual follicle as previously described (9), and all Q-RT-PCR was carried out in duplicate on 96-well plates (Stratagene Mx3000P). The quantity of both RNA and cDNA were measured using a NanoDrop ND-100 (NanoDrop Technologies) spectrophotometer. Each well contained 12.5 µl of SYBER Green PCR Mastermix (Stratagene), 20 ng of cDNA, along with the predetermined primer concentrations and RNase and DNase-free water to ensure each well contained a final volume of 25 µl. A total of 50 PCR cycles was performed to ensure the threshold crossing point was achieved, and fluorescence was monitored continuously throughout the reaction. The inclusion of a dissociation curve ensured specificity of amplification.


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  		Table 1. Gene name abbreviation and forward and reverse primer sequence (depicted in 5' to 3' direction) for genes with signal transducing activity (GO identities: GO:0007165 and GO:0004871) used in Q-RT-PCR

 
Experiment 2: Gene Expression During Different Stages of the Follicle Wave
In this experiment, signal transduction genes that were significant different between dominant and subordinate follicles using Q-RT-PCR from experiment 1 were chosen for Q-RT-PCR analysis in dominant and subordinate follicles at three different stages of the follicle wave.

Animals and tissue processing.
The estrous cycles of fifteen normally cycling cows (Charolais x Limousin, 26–40 mo of age) were synchronized using progesterone releasing intravaginal devices (PRID, CEVA Animal Health) for 10 days. On day 9 a 3 ml prostaglandin was administered, and cows were checked for estrus behavior every 12 h. The onset of estrus was designated as day 0 of the estrous cycle. Daily transrectal ultrasonography was used to monitor ovarian follicle development and cattle were randomly assigned to be slaughtered at the time of 1) follicle wave emergence, 2) dominant follicle selection, or 3) dominance of the first follicle wave, which corresponded to approximately days 1.5, 2.5, or 3.5 of the cycle, respectively. Follicles were recovered, and the theca enriched layer and granulosa cells were separated and stored as described for experiment 1.

Category assignment.
Animals were assigned to groups based on the stage of the follicle wave they were recovered at (19, 38). In brief, animals were assigned to the dominance group (n = 7) when there was a clear dominant follicle present with the greatest diameter and follicular fluid estradiol concentrations that were at least twice as high as the next largest follicle. Animals were assigned to the selection group (n = 4) when the largest follicle (dominant follicle) had estradiol concentrations that were between 1.5 and 2 times greater than the next largest follicle. Animals were assigned to the emergence group (n = 4) when differences among follicles were small and did not satisfy the above criteria. In all groups, the follicles were ranked based on follicle diameter and follicular fluid estradiol concentrations [the dominant (or putative dominant) follicle had the highest followed by the first and second subordinate follicles] (1, 10, 16, 19, 42).

Tissue processing and Q-RT-PCR.
RNA was extracted from theca and granulosa cells of the three largest follicles per animal, cDNA was synthesized, and Q-RT-PCR was carried out as described in experiment 1. Q-RT-PCR was carried out on a subset of genes from experiment 1 to determine the relative expression levels of these genes as steroid production changes in follicles from different stages of the follicle wave. In addition to this subset of genes, mRNA for the CYP19A (Aromatase a marker gene) and the LH receptor (LHCGR) was measured using previously described primer sets (17). The relative expression of these marker genes further indicated the status of follicles during the follicle wave.

Experiment 3: RNA Interference in Granulosa Cells In Vitro
In experiments 1 and 2 the expression patterns of specific signaling genes associated with both dominant and subordinate follicles were determined. In experiment 3, RNA interference was performed on granulosa cells in vitro to determine the functional significance of two genes associated with subordinate follicle regression.

Tissue collection.
Unless stated all chemicals were supplied from Sigma (Poole, UK). Bovine ovaries were collected from a local abattoir and stored on ice in McCoy's M199 media supplemented with 1x antibiotic/antimycotic solution. Follicles between 3 and 5 mm in diameter were dissected from the ovaries and washed with 70% ethanol. Follicular fluid was aspirated, and follicles were hemisected in PBS. Granulosa cells were scraped off each half of the follicle with a sterile inoculation loop and cells from ~20 follicles were pooled in 5 ml of McCoy's 5a media supplemented with 0.1% BSA, 1x antibiotic/antimycotic solution, 3 mM L-glutamine, 20 mM HEPES, 5 µg/ml transferrin, 5 ng/ml sodium selenite, 10 ng/ml insulin, 10 ng/ml IGF-1 (LR3), and 1 µg/ml androstenedione. Cells were then spun at 100 g for 10 min, supernatant was removed, and 5 ml of supplemented McCoy's 5a media was added, and the wash step was repeated (24). The cell pellet was then resuspended in 1–2 ml of culture media.

Cell plating.
Prior to the RNA interference experiment granulosa cells were cultured in vitro with 0, 0.33, and 1.0 ng/ml of ovine FSH to determine optimum culture conditions and the expression levels of betaglycan and fibroblast growth factor-1 intracellular binding protein (FIBP) and also to determine the steroidogenic capacity of these cells. Cells were also cultured for 24, 48, 72, and 96 h. Cell viability was ascertained using the trypan blue exclusion method (30). Once the culture system was optimized cells were then plated out in a 24-well plate with 500,000 viable cells per well in 500 µl of culture media and 0.33 ng/ml of ovine pituitary FSH (Pituitary Hormones and Antisera Ctr.). Cells were incubated in humid air with 5% CO2 at 37 °C for 48 h.

siRNA transfection.
Cells were transfected at time of plating using DharmaFECT 1 (Dharmacon). Cells were either treated with 1) control media and no FSH; 2) 0.33 ng/ml FSH; 3) FSH and DharmaFECT 1; 4) FSH, DharmaFECT 1, and either the siRNA for betaglycan; or 5) the siRNA for FIBP. All siRNAs were produced by Dharmacon SMART pool (Dharmacon). All siRNAs were designed against the bovine sequences for the gene of interest. To ensure that the siRNAs were specifically knocking down each gene of interest, mRNA expression levels for betaglycan were measured in cells cultured with FIBP siRNAs and vice versa. We changed 250 µl of media 24 h after transfection and replaced it with new media, transfection reagent, and siRNA where applicable. Cells were harvested 48 h postplating, and cell viability was determined by the trypan blue method. Samples were then spun at 1,000 g for 10 min, and supernatant was removed and stored for hormone analysis at –80°C. Cell pellets were resuspended in 500 µl of TRIzol reagent (Invitrogen), snap frozen in liquid nitrogen, and stored at –80°C for later determination of relative levels of gene expression.

Tissue processing and Q-RT-PCR.
To determine if betaglycan and FIBP were knocked down, Q-RT-PCR was performed as described above. Briefly, RNA was extracted from cells using the TRIzol reagent and DNase treated (DNA-free Ambion). cDNA was synthesized, and Q-RT-PCR was carried out in duplicate on 96-well plates (Stratagene Mx3000P) with 50 ng of cDNA, 12.5 µl of SYBR Green PCR Mastermix (Stratagene). Primer sequences and concentrations were used as described above, and RNase/DNase-free water was added to make a final volume of 25 µl per well. A dissociation curve was also included at the end of the PCR cycles.

Hormone Assays
Estradiol concentrations in follicular fluid and culture media were measured using a validated RIA (Adaltis) (35). All follicular fluid was diluted 1:100 or 1:1,000 in PBS prior to assay. The intra-assay coefficients of variation (CVs) were 7.4, 8.9, and 13.2, and the interassay CVs (n = 3) were 15.6, 16.1, and 15.8% for low, medium, and high reference samples, respectively. Progesterone concentrations in culture media were measured in one fluoroimmunoassay (AutoDELFIA Progesterone; Wallac, Turku, Finland) (15). Prior to assay only the follicular fluid was diluted 1:100 in PBS. The intra-assay CVs were 2.8 and 2.1% for the low and medium reference samples.

Statistical Analysis
In experiment 1, the 2–{Delta}{Delta}CT method (31) was used to analyze the Q-RT-PCR data. The relative expression level for each of our genes of interest was calculated relative to β-actin (normalizer). Once the genes were normalized the abundance of mRNA was calculated by dividing the dominant value by the subordinate value to give the fold change difference. The subordinate follicle was assigned a value of 1, and a Student's t-test was carried out to determine the significance of the genes by comparing the dominant follicle value to the subordinate follicle.

In experiment 2, data analysis was carried out on the expression level of our genes of interest relative to β-actin. The relative expression level for each gene of interest was compared among the three largest follicles for each animal within each specific stage of the follicle wave and also between the three different stages of the wave using ANOVA and multiple comparisons were made using the least significance difference (LSD) test (SAS version 8.2 SAS institute, Cary, NC). Follicular fluid hormone concentrations and follicle diameter were also analyzed using the ANOVA and LSD tests as described.

In experiment 3, data were analyzed with the mRNA expression levels considered relative to the expression of the control samples at the zero time point. Comparisons between selected treatments were done using paired Student's t-test. Estradiol and progesterone concentrations from the cell culture media were compared using the paired Student's t-test.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
DISCUSSION
 GRANTS
 REFERENCES
 
Experiment 1: Differential Gene Expression
Diameter and follicular fluid estradiol concentrations were greater (P < 0.04) in the dominant (9.8 ± 1.0 mm, 132.2 ± 38.5 ng/ml) compared with the largest subordinate follicle (7.6 ± 0.6 mm, 24.1 ± 12.1 ng/ml) (17).

Of the 441 array features classed as having signal transducer activity (GO identities: GO:0007165 and GO:0004871), 45 were differentially expressed in dominant compared with subordinate follicles in granulosa cells and 38 in theca cells (see Tables 2 and 3) in the dominant compared with subordinate follicles. Primers were designed against 12 of the genes and aromatase in the granulosa cells, and 10 in the theca cells to examine differential expression in dominant compared with subordinate follicles. In the granulosa cells eight genes were shown to be differentially expressed by Q-RT-PCR including marker genes for aromatase and the LH receptor. These two marker genes and breast cancer antiestrogen resistance 1 (BCAR1) had higher (P < 0.05) expression in the dominant compared with the subordinate follicles while betaglycan (TGFBRIII), FIBP, SIPA1, PPID, and RANGAP1 expression was higher (P < 0.05) in the subordinate compared with the dominant follicle. In the theca cells, eight genes were differentially expressed and included FRAP1, GNAI3, Ca2+-calmodulin-dependent kinase-1 (CAMK1), FIBP, STX5, WNT2B, DGCR2, and FMNL3 mRNA expression levels were higher in the dominant compared with the subordinate follicle (P < 0.05) and ephrin (EPH) EPHA4 expression was increased in the subordinate compared with the dominant follicle (P < 0.05, Table 3) (See Tables 2 and 3 for full-length names of genes).


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  		Table 2. Relative expression (±SE) of genes with signal transducing activity (GO:0007165 and GO:0004871) in granulosa and theca cells of dominant compared with the largest subordinate follicle in heifers (n = 4) determined by microarray and Q-RT-PCR analysis

 

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  		Table 3. Relative expression (±SE) of genes with signal transducing activity (GO:0007165 and GO:0004871) in GC and TC of dominant compared with the largest subordinate follicle in heifers (n = 4) determined by microarray analysis

 
Experiment 2: Gene Expression During Different Stages of the Follicle Wave
From the follicles at the emergence stage of the follicle wave, follicle diameter was greater in the putative dominant compared with the second largest subordinate follicle, and there was no significant difference in follicular fluid estradiol concentrations among all three follicles (Fig. 1). The dominant follicle in the selection group had a higher (P < 0.05) follicular fluid estradiol concentration and diameter (P < 0.05) compared with the two largest subordinate follicles. At the dominance stage of the wave, follicular fluid estradiol concentrations and follicle diameter were different among all three follicle types (P < 0.05), being greatest in the dominant, intermediate in the largest subordinate, and lowest in the second largest subordinate follicle (Fig. 1).


Figure 1
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  		Fig. 1. Mean (± SE) follicle diameter (A) measured after dissection and follicular fluid estradiol concentration (B) for the dominant (solid bars) and the 1st and 2nd largest subordinate follicles (open and gray bars, respectively) at different stages of the follicle wave (emergence n = 4, selection n = 4, dominance n = 7). abcP < 0.05 among follicles within stages.

 
We examined the expression of 14 of the genes, which were found to be differentially expressed in dominant compared with subordinate follicle in experiment 1 (See Table 2, P < 0.05 for Q-RT-PCR) at different stages of the follicle wave in experiment 2. However, genes coding for RANGAP1 and PPID in the granulosa and TGFBR2, GNAI3, and WNT2B in the theca cells were not differentially expressed at any of the different stages of the follicle wave in this experiment (data not reported). In the granulosa cells, mRNA for aromatase (CYP19A, Fig. 2A) was higher in the putative dominant follicle at the emergence stage and the dominant follicle at the dominance stage compared with the first and second largest subordinate follicles (P < 0.05). At the selection stage there is a difference in the dominant and second largest subordinate follicle. There was also an increase in expression levels of aromatase among dominant follicles across the stages of the follicle wave (P < 0.05). mRNA for the LH receptor was higher (P < 0.05) in the dominant follicle than the subordinate follicles at the dominance stage of the wave but was similar (P > 0.05) among follicles within other stages of the wave (Fig. 2B). mRNA for the LH receptor increased (P < 0.05) in the dominant follicle from the emergence to the dominance stages of the wave (Fig. 2B). Levels of mRNA for the FSH receptor were similar among follicle types and stages of the wave except at the dominance stage, where they were higher in the dominant follicle than the two subordinate follicles (Fig. 2D). Betaglycan mRNA expression levels in granulosa cells were increased (P < 0.05) in the two largest subordinate follicles at the dominant stage of the wave compared with the dominant follicle and the expression levels in the subordinate follicles increased (P < 0.05) as the follicle wave progressed (Fig. 2C). FIBP expression was higher (P < 0.05) in the granulosa cells of subordinate follicles at the dominance stage of the wave compared with the dominant follicle, and again the expression increased in the subordinate follicles as the wave progressed. There was more (P < 0.05) mRNA for BCAR1 in the granulosa cells of the dominant follicle compared with the subordinate follicles at the dominance stage of the follicle wave, and levels of mRNA for BCAR1 increased across the stages of the follicle wave in the dominant and second largest follicles (Fig. 2F).


Figure 2
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  		Fig. 2. Levels of mRNA (± SE) for aromatase (A), luteinizing hormone receptor (LHR, B), betaglycan (C), follicle stimulating hormone receptor (FSHR, D), fibroblast growth factor-1 intracellular binding protein (FIBP, E), and breast cancer antiestrogen resistance-1 gene (BCAR1, F) in the granulosa cells of the 3 largest follicles (dominant, black bars; 1st subordinate, open bars; 2nd subordinate, gray bars) from the emergence (n = 4), selection (n = 4), and dominance (n = 7) stages of the follicle wave. All expression levels given are relative to β-actin (normalizer). abcP < 0.05 among follicles within stages, xyzP < 0.05 among similar follicles across stages of the follicle wave.

 
In theca cells at both the selection and dominance stages of the follicle wave CAMK1 expression was greater (P < 0.05) in the dominant follicle compared with the two largest subordinate follicles and compared with levels in the dominant follicle at the emergence stage of the wave (Fig. 3A). There were few differences among follicles within stages of the follicle wave for levels of mRNA for EphA4 and FIBP in theca cells; however, levels did increase (P < 0.05) in the dominant follicle from the emergence to the dominance stages of the wave (Fig. 3, B and C).


Figure 3
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  		Fig. 3. Levels of mRNA (± SE) for Ca2+-calmodulin-dependent kinase-1 (CAMK1, A), ephrin (Eph) A4 (B), and FIBP (C) in the theca cells of the 3 largest follicles (dominant, black bars; 1st subordinate, open bars; 2nd subordinate, gray bars) from the emergence (n = 4), selection (n = 4), and dominance (n = 7) stages of the follicle wave. All expression levels given are relative to β-actin (normalizer). abcP < 0.05 among follicles within stages, xyzP < 0.05 among similar follicles across stages of the follicle wave.

 
Experiment 3: siRNA in Granulosa Cell Culture. Optimization of granulosa cell culture system.
The secretion of estradiol per 10,000 viable cells increased (P < 0.05) over time in cells treated with 0.33 ng of FSH compared with the blank at time zero (Fig. 4A). Over the same time course progesterone concentrations increased (P < 0.05) with the addition of 0.33 ng/ml and 1.0 ng/ml of FSH (Fig. 4B). The estradiol-to-progesterone ratio (E2:P4) also decreased (P < 0.05) relative to the time zero blank after 48 h of culture and this decrease was more marked the longer the cells were kept in culture (Fig. 4C). There were no significant changes in FIBP expression over the length of the granulosa cell culture even with the addition of different concentrations of FSH and betaglycan expression levels changed as length of time in culture increased (Fig. 5).


Figure 4
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  		Fig. 4. Mean (± SE) estradiol concentration (E2, A), progesterone concentration (P4, B), and estradiol-to-progesterone (E2:P4) ratio (per 10,000 viable cells; C) from 0 to 96 h in primary culture of granulosa cells in serum-free media with no follicle stimulating hormone (FSH, black bars), with 0.33 ng/ml FSH (open bars), or 1.0 ng FSH/ml (gray bars). *Significant differences (P < 0.05) compared with the time zero (n = 3).

 

Figure 5
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  		Fig. 5. Mean (± SE) mRNA levels of aromatase (A), betaglycan (B), and FIBP (C) relative to β-actin from 0 to 96 h in primary culture of granulosa cells in serum-free media with no ovine FSH (solid bars) with 0.33 ng/ml FSH (open bars) or 1.0 ng/ml FSH (gray bars). *Significant differences (P < 0.05) compared with the time zero (n = 3).

 
siRNA in granulosa cell culture system.
The expression level of betaglycan was decreased (P < 0.05) by approximately a 70% (Fig. 6A) in cells treated with the siRNA for betaglycan. There was no decrease in betaglycan expression levels in cells treated with the siRNA for FIBP showing that the siRNA designed against betaglycan specifically knocked-down betaglycan and that the knockdown was not an off target effect. The physiological consequences of knocking down betaglycan were determined by measuring steroid production from the granulosa cells. The concentrations of estradiol and progesterone in the cell culture media were not significantly different between cells in which betaglycan knockdown had occurred compared with blanks (Fig. 6, B and C); however, there was an increase in the E2:P4 in cells with betaglycan knockdown compared with those with no treatment and cells treated with FSH and DharmaFECT 1 (Fig. 6D). FIBP mRNA expression level was knocked down (P < 0.05) compared with blank cells and cells treated with FSH, DharmaFECT 1, and the siRNA for betaglycan (our positive control siRNA) (Fig. 7A). This knockdown of FIBP mRNA led to an increase (P < 0.05) in estradiol production compared with all controls and also led to an increase in E2:P4 in FIBP knockdown cells (Fig. 7, B and D).


Figure 6
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  		Fig. 6. Mean (± SE) levels of mRNA for betaglycan relative to β-actin (A), E2 concentration expressed per 10,000 viable cells (B), P4 concentration expressed per 10,000 viable cells (C), E2:P4 (D) at 48 h of primary culture of granulosa cells in serum-free media in control media only (solid bars, control), media plus 0.33 ng FSH (striped lines, FSH), media plus 0.33 ng FSH plus the transfection reagent DharmaFECT 1 [black spotted bars, transfection reagent control (TRC)], media plus 0.33 ng FSH plus DharmaFECT 1 plus siRNA for FIBP (white spotted bars, FIBP siRNA), media plus 0.33 ng FSH plus DharmaFECT 1, siRNA for betaglycan (open bars, betaglycan siRNA). *Significant differences (P < 0.05) compared with betaglycan siRNA treated cells (n = 6).

 

Figure 7
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  		Fig. 7. Mean (± SE) levels of mRNA for FIBP relative to β-actin (A), E2 concentration expressed per 10,000 viable cells (B), P4 concentration expressed per 10,000 viable cells (C), E2:P4 (D) at 48 h of primary culture of granulosa cells in serum-free media in control media only (solid bars, control), media plus 0.33 ng FSH (striped lines, FSH), media plus 0.33 ng FSH plus the transfection reagent DharmaFECT 1 (black spotted bars, TRC), media plus 0.33 ng FSH plus DharmaFECT 1 plus siRNA for betaglycan (white spotted bars, betaglycan siRNA), media plus 0.33 ng FSH plus DharmaFECT 1, siRNA for FIBP (open bars, FIBP siRNA). *Significant differences (P < 0.05) compared with FIBP siRNA treated cells (n = 6).

 

   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
GRANTS
 REFERENCES
 
Using DNA microarrays our study has identified 83 genes classified as having signal transducing properties or being involved in signal transduction (as specified by Gene Ontology identities: GO:0007165 and GO:0004871) that were differentially expressed between dominant and subordinate follicles in theca or granulosa cells. Of these 83 genes, 13 in granulosa cells and 10 genes in theca cells were shown to be differentially expressed using Q-RT-PCR. The discrepancies between the microarray data and the Q-RT-PCR data reflect the nature of the older generation of cDNA microarrays; this phenomenon has been previously described by other users of the BOTL4 array (17, 33). Newer generation of microarrays such as the Affymetrix microarray have shown a much more robust degree of correlation between microarray and Q-RT-PCR findings. Nonetheless, we used the microarray approach to discover potentially important genes (Tables 2 and 3) and confirmed (Figs. 2 and 3) and validated (Figs. 6 and 7) their function in further experiments. The knockdown of both betaglycan and FIBP was demonstrated in granulosa cells cultured in vitro using siRNA. This knockdown lead to a increase in the E2:P4 ratio and a decrease in estradiol secretion and E2:P4 ratio, respectively, in betaglycan and FIBP knockdown cells respectively leading to an increase in the steroidogenic capacity of these granulosa cells cultured in vitro.

The reliability of the dominant follicle model has been confirmed by the measurement of a number of marker genes (aromatase, LHR, and FSHR). During the follicle wave, there is a switch in dependency from FSH in the emergence stage to LH dependency (45). This switch in hormone dependency is propagated through the expression of LH receptors on the granulosa cells which allows the dominant follicle to continue estradiol production and thus growth in a low FSH environment. In our study we confirmed that mRNA for LH receptors was higher in the dominant follicle compared with the subordinate follicle at the Dominant stage of the wave. We have also shown that the mRNA expression levels increase in the granulosa cells of the dominant (or putative dominant) follicle across the days of the follicle wave in agreement with other studies (16, 33, 46, 47). Further validating our model we have shown that the expression of aromatase increases in granulosa cells as the follicle wave progresses (47).

In theca cells we have identified two previously undescribed genes that are potentially involved in ovarian follicle development. Firstly, there was an increase in mRNA for CAMK1 in the theca cells of dominant follicle compared with the largest subordinate follicles at the Selection and, to a greater extent, at the dominant stage of the follicle wave. CAMK1 is a calcium binding protein that is highly conserved in mammals (12) and it is involved in second messenger systems in a variety of cell types. We also detected differences in EphA4 in theca cells of dominant compared with subordinate follicles. EphA4 is a receptor tyrosine kinase and a class A type receptor. It is a member of the ephrin family and binds both class A and class B ephrins (22). Although there is no previous evidence of the ephrin family and its function in follicle development, it has been shown that EphA4 has a role to play in cell-cell adhesion via the cadherin family of molecules (11). This suggests that EphA4 may promote the growth of the dominant follicle as it is upregulated in the dominant follicle over the stages of the follicle wave. In granulosa cells, we found more mRNA for BCAR1 in the dominant follicle at the dominance stage of the wave in granulosa cells compared with subordinate follicles, but equally there was a significant increase in expression levels of BCAR1 in the dominant follicle as the follicle wave progressed. BCAR1 has been shown to promote cell proliferation in human estrogen-dependent breast cells, even in the presence of antiestrogens (6, 44). It is possible that BCAR1 plays a similar role in regulation of growth and proliferation of the cells of the dominant follicle.

We found more mRNA for betaglycan (TGFBR3) in the granulosa cells of the two largest subordinate follicles than the dominant follicles at the Dominance stage of the follicle wave. Also, expression of betaglycan in the two largest subordinate follicles increased as the follicle wave progressed. Betaglycan binds TGF-β in a heteromeric complex. This complex then binds TGF-βRI and allows the phosphorylation of the type I receptor (50). It has been shown that betaglycan also binds to inhibin, associates with activin receptor II, and prevents the binding of activin and its downstream signaling mechanisms. The binding of inhibin ligands to betaglycan enhances the binding to the activin type II receptor and in this way enhances the antagonistic effect inhibins have on activin and its promotion of granulosa cell proliferation (28). It has been shown in cultured bovine granulosa cells that the addition of activin can increase the production of estradiol and aromatase activity, both of which are markers of healthy growing follicles. Other evidence for the promotion of follicle development by activin A is through the FSH and/or IGF-I stimulation of estradiol in granulosa cells in vitro, suggesting that FSH may act through activin A in the stimulation of estradiol in growing healthy follicles (28). Loss of betaglycan in adult tissues is associated with the development of renal (13) and endometrial carcinomas (18), indicating that betaglycan functions as a regulator/ inhibitor of growth in tissue in general, and the loss of this can lead to proliferation of cancerous cells. It is possible to suggest that in follicles betaglycan acts via binding inhibin and antagonizing activin leading to a retardation of the growth of the follicle. Successful knockdown of mRNA for betaglycan leads to an increase in E2:P4 in the culture media. This, coupled with the expression data, points toward a role for betaglycan in the demise of the subordinate follicles through either a direct inhibition of granulosa cell proliferation or an indirect action by hindering the production of estradiol and/or promoting the production of progesterone.

In granulosa cells we have shown that FIBP is more highly expressed in the two largest subordinate follicles at the dominance stage of the wave compared with the dominant follicle (Fig. 2). To investigate the role FIBP has in granulosa cell function we knocked down FIBP mRNA in granulosa cells in vitro. This knockdown of FIBP mRNA led to a fourfold increase in estradiol production and to an increase in E2:P4 in vitro. FIBP is a member of the FGF family of ligands and receptors and was identified in a yeast-two hybrid system as binding to acidic fibroblast growth factor (FGF1). Members of this family are responsible for exerting a number of different biological effects such as mitogenesis, differentiation, and/or DNA binding and cell survival (32, 43), depending on what cell type they are acting on. Various members of the FGF family have been detected in ovarian follicles (3, 4, 8, 34). FGF 1, 2, 7, and 8 have been detected in both theca and granulosa cells of ovarian follicles, with the ligands FGF7 and FGF10 have been detected in theca cells of primordial, primary, and secondary follicles (2, 8). The receptors for these ligands (FGFR2 splice variants IIIb and IIIc) are expressed in both theca and granulosa cells of follicles (2), with FGFR2B detectable in granulosa cells cultured in vitro (8). Other receptors for the FGF ligand family have been detected in both theca and granulosa cells (FGFR3c) and in theca cells only (FGFR4) (7). The addition of FGF7 and FGF10 to granulosa cells cultured in vitro reduce aromatase activity and estradiol production, respectively (8, 34). If these ligands are binding to the FGFR2 in granulosa cells and reduce the steroidogenic capacity of the cells without having an effect on the growth and proliferation of the cells, this may indicate why in our study FIBP expression increased in subordinate follicles as the follicle wave progressed. There are no significant differences in expression levels of FGF1 in granulosa cell from follicles with varying estrogenic capacity (2). Binding of FIBP to FGF1 accentuates the function of FGF1. If FGF1 has the same effect on steroidogenesis as FGF7 and FGF10 have shown then we postulate that FIBP could enhance the ability of FGF1 to reduce steroid production in granulosa cells. These data from the literature coupled with our RNA interference study, in which knockdown of FIBP leads to an increase in estradiol production by granulosa cells cultured in vitro, point to a role in suppression of the steroidogenic and thus the "health" of the subordinate follicles in a follicle wave. We suggest that FIBP in granulosa cells is involved in the suppression of estradiol production in subordinate follicles and that increased growth and estradiol production by the dominant follicle requires that they maintain FIBP expression at low levels.

In summary, using microarrays 83 novel signaling genes were identified, a subset were validated using Q-RT-PCR and changes in expression of these genes at different stages of the follicle wave were characterized. We suggest important roles for CAMK1 and EphA4 in theca cells and BCAR1 in granulosa cells of development of dominant follicles and for betaglycan and FIBP in granulosa cells of regressing subordinate follicles. Inhibition of genes for betaglycan and FIBP in granulosa cells in vitro suggests that they inhibit estradiol production in regressing subordinate follicles.


   GRANTS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 GRANTS
REFERENCES
 
This was study was funded by a Science Foundation Ireland grant (02/IN1/B78) to A. C. O. Evans and P. Lonergan (the opinions, findings and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the Science Foundation Ireland).


   ACKNOWLEDGMENTS
 
We thank Pat Duffy and Dimitrios Rizos for technical assistance; Ciara O'Meara, Kate Ryan, Sean Fair, Deidre Corcoran, and Anna Zielak for help with the animal work and tissue collection; Janet Ireland for help with the microarray study; Niamh Hynes for help with the hormone assays; and Lynne, Anna, and Janette with help with the cell culture work.


   FOOTNOTES
 
Address for reprint requests and other correspondence: A. C. O. Evans, Univ. College Dublin, Veterinary Sciences Cntr., Belfield, Dublin 4, Ireland (e-mail: alex.evans{at}ucd.ie).

Article published online before print. See web site for date of publication (http://physiolgenomics.physiology.org).


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 GRANTS
 REFERENCES
 

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