TY - JOUR
AU - Spicer, L. J.
AB - ABSTRACT Insulin-like growth factor-I in conjunction with gonadotropins are important stimulators of mitosis and ovarian steroid production by granulosa and thecal cells, which are required for normal oocyte development and hormonal feedback signaling to the hypothalamus and pituitary. However, a comprehensive evaluation of the changes in gene expression induced by IGF-I has not been conducted. Our objective was to characterize granulosa cell gene expression in response to IGF-I treatment. Porcine granulosa cells were pooled in 4 biological replicates and treated with FSH (baseline) or FSH+IGF-I for 24 h in vitro. The RNA was collected and hybridized to 8 Affymetrix Porcine GeneChips (Affymetrix, Santa Clara, CA) in a paired design. Differentially regulated gene sequence element sets (P < 0.01) were used as queries in the UniGene database searching for annotated genes. Abundance of messenger RNA (mRNA) for genes differentially expressed in the microarray analysis was determined through multiplex assays of one-step real-time reverse transcription-PCR and further analyzed under a statistical model including the fixed effect of treatment. A total of 388 gene sequence element sets were differentially expressed, and 42 matched annotated genes in the UniGene database. Of the 3 upregulated target genes selected for further quantitative reverse transcription-PCR analysis, only FGF receptor 2 III c (FGFR2IIIc) mRNA abundance was significantly increased by IGF-I. Of the 3 downregulated target genes selected for further analysis, only thrombospondin-1 (THBS1) mRNA abundance was significantly decreased by IGF-I. Further study revealed that neither FSH nor estradiol affected the IGF-I-induced suppression of THBS1 mRNA abundance. These results provide the first comprehensive assessment of IGF-I-induced gene expression in granulosa cells and will contribute to a better understanding of the molecular mechanisms of IGF-I regulation of follicular development. Involvement of FGFR2IIIc and THBS1 in mediating IGF-I-induced granulosa cell steroidogenesis and proliferation during follicular development is novel, but their specific roles will require further elucidation. INTRODUCTION Coordinated synthesis of steroids by follicular cells is dependent on the cooperative actions of gonadotropins, growth factors, and proinflammatory cytokines (Richards et al., 2002). In particular, IGF synergize with gonadotropins to stimulate ovarian steroidogenesis (Giudice, 1992; Spicer and Echternkamp, 1995; Spicer and Aad, 2007). In nonprimate mammals, including rodents, pigs, and cattle, IGF-I is the predominate IGF synthesized by granulosa cells (Poretsky et al., 1999; Spicer and Chamberlain, 2000). Regarding follicular selection and dominance, these processes are controlled, in part by the amount of free or biologically available IGF-I and -II within the follicle regulated by IGFBP (Stewart et al., 1996; Spicer, 2004). Indeed, free IGF-I is greater in dominant compared with subordinate follicles of cattle (Ginther et al., 2003; Rivera and Fortune, 2003; Santiago et al., 2005). However, a comprehensive evaluation of the changes in gene expression within granulosa cells induced by IGF-I has not been conducted. In porcine granulosa cell cultures, IGF-I increases mitogenesis, steroidogenic acute regulatory protein (StAR) messenger RNA (mRNA) abundance, and steroid production, and decreases apoptosis (Spicer and Echternkamp, 1995; Balasubramanian et al., 1997; Guthrie et al., 1998). Furthermore, IGF-I synergizes with FSH to enhance granulosa cell steroidogenesis (Spicer and Echternkamp, 1995; Balasubramanian et al., 1997; Spicer et al., 2002) via increasing side-chain cleavage enzyme (CYP11A1), 3β-hydroxysteroid dehydrogenase (3βHSD), aromatase (CYP19A1), and luteinizing hormone receptor (LHR) expression (Hirakawa et al., 1999; Ranzenigo et al., 2008). However, the various cellular changes that are altered by IGF-I are not completely understood. Therefore, our objective was to characterize granulosa cell gene expression in response to IGF-I treatment. MATERIALS AND METHODS Animal Care and Use Committee approval was not obtained for this study because the samples were obtained from a federally inspected slaughter facility. Cell Culture Ovaries were obtained from peripubertal, nonpregnant gilts slaughtered at a nearby commercial abattoir and were treated as described previously (Spicer and Hammond, 1989; Ranzenigo et al., 2008). Briefly, after transport on ice-cold saline (0.15 M NaCl) to the laboratory (approximately 30 min), the ovaries were washed 3 times in saline, immersed in 70% ethanol for 30 s, and washed again 3 times with saline. Small follicles (1 to 5 mm diameter) were aspirated aseptically with 25-gauge needles and 3-mL syringes; granulosa cells were recovered by centrifugation at 291 × g at 4°C for 7 min and washed 3 times with 7 mL of serum-free medium. At each wash, cells were separated from medium via centrifugation at 291 × g for 5 min at 4°C to isolate them. The medium was a 1:1 mixture of DMEM and Ham's F12 containing 0.12 mM gentamicin and 38.5 mM sodium bicarbonate. After the last centrifugation, the supernatant was recovered and replaced with 2 mL of enzyme-containing medium (1 mg/mL of DNase and 2.5 mg/mL of collagenase) to prevent clumping of cells (Spicer et al., 2002). The number of viable cells was determined using the trypan blue exclusion method, and between 2 and 6 × 105 viable cells in 20 to 30 μL of medium were added to each well of 24-well Falcon multiwell plates (Becton Dickinson, Lincoln Park, NJ) containing 1 mL of medium. Cell cultures were kept at 38.5°C in a humidified 95% air-5% CO2 environment, and medium was changed every 24 h. To attain an optimal attachment, cells were maintained in the presence of 5% fetal calf serum (FCS) and 5% porcine serum (PS) for the first 48 h of culture. The Dulbecco's Modified Eagle Medium, Ham's F12, and FCS were obtained from Sigma Chemical Co. (St. Louis, MO); PS was purchased from Sera Care Life Sciences Inc. (Oceanside, CA). After 48 h of culture, granulosa cells were washed twice with 0.5 mL of serum-free medium, and incubation continued in serum-free medium for 1 d containing 500 ng/mL of testosterone as an estradiol precursor (Spicer et al., 2002) and 30 ng/mL of FSH with 0 or 30 ng/mL of IGF-I (FSH only and FSH+IGF-I, respectively). A second set of experiments evaluated the effect of pubertal state on IGF-I- and FSH-induced estradiol production by granulosa cells. Granulosa cells from small (1 to 5 mm) follicles were collected from prepubertal (no luteal structures) or postpubertal (presence of luteal structures) gilts and cultured for 48 h in the presence of 5% FCS and PS. Then cells were washed and incubated in serum-free medium containing 500 ng/mL of testosterone, IGF-I (0, 30 ng/mL), FSH (0, 30 ng/mL), or a combination of these for an additional 48 h. Medium was collected for determination of estradiol concentrations and cell numbers enumerated as described previously (Ranzenigo et al., 2008). In a third set of experiments, granulosa cells from small (1 to 5 mm) follicles were cultured as described earlier and then treated for an additional 24 h with FSH (0, 30 ng/mL) or estradiol (0, 300 ng/mL) in the absence or presence of 30 ng/mL of IGF-I and RNA collected for reverse transcription-PCR (RT-PCR). These doses of hormones were selected based on previous in vitro studies showing them to be stimulatory to steroidogenesis and proliferation of granulosa cells (Spicer et al., 2002; Aad et al., 2006; Ranzenigo et al., 2008). Testosterone was obtained from Steraloids (Wilton, NH); IGF-I (recombinant human) was purchased from R&D Systems (Minneapolis, MN); and ovine FSH was obtained from Scripps Laboratories (San Diego, CA). RNA Extraction Granulosa cells were lysed in 0.5 mL of TRIzol Reagent (Life Technologies Inc., Gaithersburg, MD). The RNA was extracted as described by Voge et al. (2004). Briefly, lysed cells were transferred to 1.5-mL Eppendorf tubes and then incubated in TRIzol for 5 min at ambient temperature (approximately 22°C); next, 0.10 mL of chloroform (Sigma Chemical Co.) was added and each sample vortexed for 15 s. Following a 3-min incubation at ambient temperature, samples were centrifuged (3,500 × g) for 30 min at 4°C, the upper aqueous phase was transferred to a new Eppendorf tube. Then, RNA was precipitated with 0.25 mL of isopropyl alcohol (Pierce Chemical Co., Rockford, IL), gently mixed by hand and then incubated at ambient temperature for 10 min, followed by centrifugation at 3,500 × g for 10 min at 4°C; the supernatant was then removed and the RNA pellet washed with 0.5 mL of 75% ethanol solution and then centrifuged as before for 5 min; ethanol supernatant was removed and RNA pellet allowed to dry for 5 min at ambient temperature. Then, the RNA was redissolved in 10 μL of TE buffer (10 mM Tris-Cl, 1 mM EDTA; pH 7.4). Quantity of RNA was determined spectrophotometrically at 260 nm using the NanoDrop ND-1000 (NanoDrop Technologies, Wilmington, DE). Samples were then stored at −80°C until used for microarray analysis. Aliquots of the samples were prepared and saved for further RT-PCR analysis to validate results from the microarray analysis. Microarray Analysis Affymetrix Porcine GeneChips (Affymetrix, Santa Clara, CA) containing 23,937 probe sets, which interrogate approximately 23,256 transcripts from 20,201 S. scrofa genes, were used. A total of 8 chips were hybridized with RNA extracted from 4 biological replicates of the same number of granulosa cell pools in a paired design for the 2 treatments described previously (FSH only and FSH+IGF-I). The processing of the RNA including RNA purification and hybridization of microarray slides was performed by the University of Tulsa Microarray Core Facility. Affymetrix GeneChip Operating Software (GCOS version 1.1.1, Affymetrix) was used to quantitate each GeneChip. The summary intensities for each probe were loaded into DNA-Chip Analyzer (dChip), version 1.3 for normalization, standardization, and analysis. Arrays were inspected for obvious contamination or noticeable difference in overall brightness. Array outliers occur when the fitted expression for the entire probe set has an unusually high SE (≥3 SD away from its corresponding mean) when compared with the other chips. If more than 5% of probe sets are flagged as array outliers, then the whole chip is considered of suspect quality. Accordingly, no tissue was rehybridized to a new array nor was any array dropped from analysis. On the other hand, outlier percentages ranged from 0.02 to 0.14% (single outliers are probes of unusual intensity), and they were treated as missing values in subsequent analysis. The percentage of genes with present detection calls according to the GCOS software ranged from 70.94 to 73.31% (Table 1). Table 1. Intensities, percent present, and outliers for each Affymetrix Porcine GeneChips (Affymetrix, Santa Clara, CA) utilized during the microarray analysis Array  Median intensity (unnormalized)1  Present detection call,2 %  Array outlier,3 %  Single outlier,4 %  Pooled sample 1 treated with FSH only  103  71.16  0.04  0.02  Pooled sample 1 treated with FSH + IGF-I  101  70.94  0.02  0.02  Pooled sample 2 treated with FSH only  101  72.36  0.00  0.02  Pooled sample 2 treated with FSH + IGF-I  104  73.31  0.02  0.14  Pooled sample 3 treated with FSH only  92  72.40  0.06  0.03  Pooled sample 3 treated with FSH + IGF-I  95  72.74  0.01  0.02  Pooled sample 4 treated with FSH only  109  71.72  0.02  0.02  Pooled sample 4 treated with FSH + IGF-I  109  73.27  0.01  0.03  Array  Median intensity (unnormalized)1  Present detection call,2 %  Array outlier,3 %  Single outlier,4 %  Pooled sample 1 treated with FSH only  103  71.16  0.04  0.02  Pooled sample 1 treated with FSH + IGF-I  101  70.94  0.02  0.02  Pooled sample 2 treated with FSH only  101  72.36  0.00  0.02  Pooled sample 2 treated with FSH + IGF-I  104  73.31  0.02  0.14  Pooled sample 3 treated with FSH only  92  72.40  0.06  0.03  Pooled sample 3 treated with FSH + IGF-I  95  72.74  0.01  0.02  Pooled sample 4 treated with FSH only  109  71.72  0.02  0.02  Pooled sample 4 treated with FSH + IGF-I  109  73.27  0.01  0.03  1Unnormalized median target intensity for each chip. Before analysis in Affymetrix GeneChip Operating Software (GCOS version 1.1.1, Affymetrix), intensity for each chip was normalized by adjusting the brightness of each chip to be comparable with the median intensity (i.e., pooled sample 1 treated with FSH only). 2Detection call percentage refers to the percentage of target genes that were identified present for each chip. 3This column represents the percentage of individual outliers for each chip. Five percent or greater of individual probe set outliers would indicate an array of poor quality. 4Single outliers are solitary probes of unusual intensity within a chip. View Large Table 1. Intensities, percent present, and outliers for each Affymetrix Porcine GeneChips (Affymetrix, Santa Clara, CA) utilized during the microarray analysis Array  Median intensity (unnormalized)1  Present detection call,2 %  Array outlier,3 %  Single outlier,4 %  Pooled sample 1 treated with FSH only  103  71.16  0.04  0.02  Pooled sample 1 treated with FSH + IGF-I  101  70.94  0.02  0.02  Pooled sample 2 treated with FSH only  101  72.36  0.00  0.02  Pooled sample 2 treated with FSH + IGF-I  104  73.31  0.02  0.14  Pooled sample 3 treated with FSH only  92  72.40  0.06  0.03  Pooled sample 3 treated with FSH + IGF-I  95  72.74  0.01  0.02  Pooled sample 4 treated with FSH only  109  71.72  0.02  0.02  Pooled sample 4 treated with FSH + IGF-I  109  73.27  0.01  0.03  Array  Median intensity (unnormalized)1  Present detection call,2 %  Array outlier,3 %  Single outlier,4 %  Pooled sample 1 treated with FSH only  103  71.16  0.04  0.02  Pooled sample 1 treated with FSH + IGF-I  101  70.94  0.02  0.02  Pooled sample 2 treated with FSH only  101  72.36  0.00  0.02  Pooled sample 2 treated with FSH + IGF-I  104  73.31  0.02  0.14  Pooled sample 3 treated with FSH only  92  72.40  0.06  0.03  Pooled sample 3 treated with FSH + IGF-I  95  72.74  0.01  0.02  Pooled sample 4 treated with FSH only  109  71.72  0.02  0.02  Pooled sample 4 treated with FSH + IGF-I  109  73.27  0.01  0.03  1Unnormalized median target intensity for each chip. Before analysis in Affymetrix GeneChip Operating Software (GCOS version 1.1.1, Affymetrix), intensity for each chip was normalized by adjusting the brightness of each chip to be comparable with the median intensity (i.e., pooled sample 1 treated with FSH only). 2Detection call percentage refers to the percentage of target genes that were identified present for each chip. 3This column represents the percentage of individual outliers for each chip. Five percent or greater of individual probe set outliers would indicate an array of poor quality. 4Single outliers are solitary probes of unusual intensity within a chip. View Large Following the dChip method of invariant set normalization (Li and Hung Wong, 2001), the chip with the median intensity value was used as the baseline against which the brightness of the remaining chips were adjusted to be at a comparable level. Chip number 1 had the median intensity value at 103 and was used as the baseline for the remaining 7 chips (Table 1). Standardization was conducted by calculating model-based expression indices using the Perfect Match-only model of dChip. Additional modeling reduces the variance of expression level estimates by accounting for probe differences. Expression data are typically highly skewed because the median is much less than the mean. Therefore, to approximate a normal distribution within each gene, the data were log base 2 transformed. The transformation improves statistical performance of the analyses, even when the methods are fairly robust to departures from normality. The log base 2 scale is advantageous because each unit then equals a 2-fold difference. Thus, for example, the log base 2 value of 5 is 2-fold greater than 4; 3 is 2 × 2 = 4-fold less than 5, and so on. Statistical Tests. Paired t-tests were calculated using dChip to evaluate differences between treatments. A critical P-value of 0.01 was considered as the criterion to select a significant fold change in gene expression between treatments. Also, the false discovery rate was utilized to restrict the list of candidate genes, deleting those with an absent detection call. This led to a final result of 388 significant probe sets. Functional Annotation. The Database for Annotation, Visualization, and Integrated Discovery (DAVID), a Web-accessible program (http://david.abcc.ncifcrf.gov/) that integrates functional genomic annotations with intuitive graphical summaries (Dennis et al., 2003) was utilized to explore the biological knowledge associated with the statistically significant probe sets from the microarray chips. The Affymetrix probe identification was used as the identifier for each probe, followed by functional annotation clustering from DAVID. Target Gene Identification. Statistically significant probes from the paired comparison were further used in a search for annotated genes in the UniGene database of the National Center for Biotechnology Information (NCBI) Web site (http://www.ncbi.nlm.nih.gov/sites/entrez). Based on novelty and lack of any previous reported IGF-I induced expression, 6 target genes were further selected for study and validation of their expression in the cell types studied, which were identified as follows: serotonin 2 B receptor (HTR2B), FGF receptor 2IIIc (FGFR2IIIc), and frizzled 8 (FZD8), which were upregulated when comparing between FSH only and FSH+IGF-I treated samples in the microarray analysis; and thrombospondin-1 (THBS1), contactin 4 (CNTN4), and integrin β 8 (ITGβ8), which were downregulated. Quantitative One-Step Real-Time RT-PCR The differential expression of target genes mRNA was quantified using RNA from the same cell pools that were utilized in the microarray experiment, after the one step, real-time RT-PCR reaction for Taqman Gold RT-PCR Kit (Applied Biosystems Inc., Foster City, CA), as described previously (Spicer and Aad, 2007; Ranzenigo et al., 2008), and using the ABI PRISM 7500 Sequence Detection System (Applied Biosystems Inc.), located at the Oklahoma State University DNA/ Protein Core Facility. Primers and fluorescent probes for quantitative RT-PCR were designed using Primer Express software (Applied Biosystems Inc.) and the PrimerQuest interface of Integrated DNA Technologies Inc. (Coralville, IA). Available porcine sequences for ITGβ8 (accession no. AY496299) and THBS1 (accession no. AY773342) in GenBank (http://www.ncbi.nlm.nih.gov/sites/entrez) were analyzed using the Primer Express program to determine optimum primer and probe locations (Table 2). Table 2. Sequences and characteristics for primers (forward and reverse) and probes for real-time reverse transcription-PCR amplification of target genes Affymetrix ID1  Target gene2  Sequence, forward/reverse/probe3  Melting temperature, °C  Amplicon size, bp  Ssc.16145.1.S1_at  HTR2B  GCCCTGCCTGGTTATTTCTT  55.5  137      GAATGCTGTAGCTCGTGAGT  54.7        CTGCATCCATCATGCATCTTTGTGCC  61.6    Ssc.15839.1.S1_at  FGFR2IIIc  CCACGGACAAAGAAATTGAGG  54.1  129      CTGGCAGAACTGTCAACCAT  55.3        ACGTGCTTGGCGGGTAATTCTATTGGGA  63.3    Ssc.10434.1.S1_at  FZD8  GGATTCCACGGTTTGGGTAT  55.7  110      CCTCTAAGGTAAGAAACCCGT  53.8        TGTTTGTTTACTTAAGGCATCTGCCTGGTC  61.4    Ssc.23798.1.S1_at  ITGβ8  ATCAGATCAACAAGCATGGAACA  54.8  94      TTCCTTGAACAGCAAAGATGACA  54.9        CCTCCCTAGGCCAACTTTCAGAAAAATTAATAGACAA  69.0    Ssc.6864.1.A1_at  CNTN4  AGCTGTGTTCCTTTCTTAGTTT  52.2  170      GATTACATATGCTAGATCACTGG  50.5        AGTTCCCAACCCCAGTGTAAATGATA  58.0    Ssc.26702.1.A1_at  THBS1  CCCATCATGCCCTGCTCTAA  57.1  87      CCAGCCATCGTCAGCAGAGT  59.6        ACAGTTCCTGATGGAGAATGCTGCCCTC  70.0    Affymetrix ID1  Target gene2  Sequence, forward/reverse/probe3  Melting temperature, °C  Amplicon size, bp  Ssc.16145.1.S1_at  HTR2B  GCCCTGCCTGGTTATTTCTT  55.5  137      GAATGCTGTAGCTCGTGAGT  54.7        CTGCATCCATCATGCATCTTTGTGCC  61.6    Ssc.15839.1.S1_at  FGFR2IIIc  CCACGGACAAAGAAATTGAGG  54.1  129      CTGGCAGAACTGTCAACCAT  55.3        ACGTGCTTGGCGGGTAATTCTATTGGGA  63.3    Ssc.10434.1.S1_at  FZD8  GGATTCCACGGTTTGGGTAT  55.7  110      CCTCTAAGGTAAGAAACCCGT  53.8        TGTTTGTTTACTTAAGGCATCTGCCTGGTC  61.4    Ssc.23798.1.S1_at  ITGβ8  ATCAGATCAACAAGCATGGAACA  54.8  94      TTCCTTGAACAGCAAAGATGACA  54.9        CCTCCCTAGGCCAACTTTCAGAAAAATTAATAGACAA  69.0    Ssc.6864.1.A1_at  CNTN4  AGCTGTGTTCCTTTCTTAGTTT  52.2  170      GATTACATATGCTAGATCACTGG  50.5        AGTTCCCAACCCCAGTGTAAATGATA  58.0    Ssc.26702.1.A1_at  THBS1  CCCATCATGCCCTGCTCTAA  57.1  87      CCAGCCATCGTCAGCAGAGT  59.6        ACAGTTCCTGATGGAGAATGCTGCCCTC  70.0    1Probe set ID from Affymetrix (Santa Clara, CA). 2Target genes: HTR2B, Serotonin receptor 2B; FGFR2IIIc, fibroblast growth factor receptor 2IIIc; FZD8, frizzled homolog 8; ITGβ8, Integrin β 8; CNTN4, contactin 4 homolog; THBS1, thrombospondin-1. 3Forward and reverse primers, and fluorescent probe for each target gene. View Large Table 2. Sequences and characteristics for primers (forward and reverse) and probes for real-time reverse transcription-PCR amplification of target genes Affymetrix ID1  Target gene2  Sequence, forward/reverse/probe3  Melting temperature, °C  Amplicon size, bp  Ssc.16145.1.S1_at  HTR2B  GCCCTGCCTGGTTATTTCTT  55.5  137      GAATGCTGTAGCTCGTGAGT  54.7        CTGCATCCATCATGCATCTTTGTGCC  61.6    Ssc.15839.1.S1_at  FGFR2IIIc  CCACGGACAAAGAAATTGAGG  54.1  129      CTGGCAGAACTGTCAACCAT  55.3        ACGTGCTTGGCGGGTAATTCTATTGGGA  63.3    Ssc.10434.1.S1_at  FZD8  GGATTCCACGGTTTGGGTAT  55.7  110      CCTCTAAGGTAAGAAACCCGT  53.8        TGTTTGTTTACTTAAGGCATCTGCCTGGTC  61.4    Ssc.23798.1.S1_at  ITGβ8  ATCAGATCAACAAGCATGGAACA  54.8  94      TTCCTTGAACAGCAAAGATGACA  54.9        CCTCCCTAGGCCAACTTTCAGAAAAATTAATAGACAA  69.0    Ssc.6864.1.A1_at  CNTN4  AGCTGTGTTCCTTTCTTAGTTT  52.2  170      GATTACATATGCTAGATCACTGG  50.5        AGTTCCCAACCCCAGTGTAAATGATA  58.0    Ssc.26702.1.A1_at  THBS1  CCCATCATGCCCTGCTCTAA  57.1  87      CCAGCCATCGTCAGCAGAGT  59.6        ACAGTTCCTGATGGAGAATGCTGCCCTC  70.0    Affymetrix ID1  Target gene2  Sequence, forward/reverse/probe3  Melting temperature, °C  Amplicon size, bp  Ssc.16145.1.S1_at  HTR2B  GCCCTGCCTGGTTATTTCTT  55.5  137      GAATGCTGTAGCTCGTGAGT  54.7        CTGCATCCATCATGCATCTTTGTGCC  61.6    Ssc.15839.1.S1_at  FGFR2IIIc  CCACGGACAAAGAAATTGAGG  54.1  129      CTGGCAGAACTGTCAACCAT  55.3        ACGTGCTTGGCGGGTAATTCTATTGGGA  63.3    Ssc.10434.1.S1_at  FZD8  GGATTCCACGGTTTGGGTAT  55.7  110      CCTCTAAGGTAAGAAACCCGT  53.8        TGTTTGTTTACTTAAGGCATCTGCCTGGTC  61.4    Ssc.23798.1.S1_at  ITGβ8  ATCAGATCAACAAGCATGGAACA  54.8  94      TTCCTTGAACAGCAAAGATGACA  54.9        CCTCCCTAGGCCAACTTTCAGAAAAATTAATAGACAA  69.0    Ssc.6864.1.A1_at  CNTN4  AGCTGTGTTCCTTTCTTAGTTT  52.2  170      GATTACATATGCTAGATCACTGG  50.5        AGTTCCCAACCCCAGTGTAAATGATA  58.0    Ssc.26702.1.A1_at  THBS1  CCCATCATGCCCTGCTCTAA  57.1  87      CCAGCCATCGTCAGCAGAGT  59.6        ACAGTTCCTGATGGAGAATGCTGCCCTC  70.0    1Probe set ID from Affymetrix (Santa Clara, CA). 2Target genes: HTR2B, Serotonin receptor 2B; FGFR2IIIc, fibroblast growth factor receptor 2IIIc; FZD8, frizzled homolog 8; ITGβ8, Integrin β 8; CNTN4, contactin 4 homolog; THBS1, thrombospondin-1. 3Forward and reverse primers, and fluorescent probe for each target gene. View Large To find primers and probes for HTR2B, FGFR2IIIc, FZD8, and CNTN4, target sequences from the Affymetrix GeneChip for each gene were used in a search for consensus sequences in the NCBI database using the Basic Local Alignment Search Tool (BLAST) interface (http://www.ncbi.nlm.nih.gov/BLAST/; Altschul et al., 1990). Then, conserved regions between the target sequences and similar sequences found in the database were identified and used to design the oligonucleotides in the PrimerQuest interface. A search using the BLAST interface was performed to ensure the specificity of the designed primers and probes and to assure that they were not designed from any homologous regions, coding for other genes. As described previously (Voge et al., 2004; Spicer and Aad, 2007), ribosomal 18S rRNA control kit (Applied Biosystems Inc.) was used as a housekeeping gene to normalize samples for any variation in RNA loading. Based on preliminary optimization results, 50 or 100 ng of total RNA was amplified in a total reaction volume of 25 μL consisting of 200 nM forward primer, 200 nM reverse primer, and 200 nM fluorescent (FAM/TAMRA) probe for each target gene; 10 nM of 18S rRNA primers and 100 nM of the 18S rRNA VIC-labeled probe, along with 12.5-μL TaqMan Master Mix without uracil N-glycosylase; and 1 U Multiscribe with RNase inhibitor (Applied Biosystems Inc.). Thermal cycling conditions were set to 30 min at 48.8°C for reverse transcription and 95°C for 10 min for AmpliTaq Gold activation and were finished with 45 cycles at 95°C for 15 s for denaturing and 60°C for 1 min for annealing and extension. Relative quantification of target gene expression was evaluated using the comparative threshold cycle method as described previously (Voge et al., 2004; Aad et al., 2006). Briefly, abundance of mRNA was estimated setting an arbitrary threshold (CT) on the FAM or VIC curves in the geometric portion of the RT-PCR amplification plot after examining the log view. Then, the ΔCT was determined by subtracting the 18S rRNA CT from the target gene CT value. Next, for each target gene the ΔΔCT was determined by subtracting the greatest ΔCT (the least expressed unknown) from all other ΔCT values. Fold changes in mRNA levels were calculated as being equal to 2−ΔΔCT. Statistical Analysis Fold changes in mRNA levels for each of the target genes selected from the microarray analysis were log-transformed [log(x + 1)] and then analyzed using the MIXED procedure (SAS Institute Inc., Cary, NC) under a statistical model including the fixed effect of treatment (FSH only or FSH+IGF-I), and as a random effect the experimental pool from which RNA was originally collected. Data are presented as least squares means and SE. To compare the expression patterns determined through quantitative RT-PCR with those determined using microarray analysis, the ratio of the greatest to the least treatment least squares mean for transformed fold changes was obtained. If the mean for the FSH-only treatment was the greatest, then a negative value was assigned to the ratio. Conversely, a positive value was assigned to the ratio if the mean from the FSH+IGF-I treatment was the greatest. Each cell culture experiment was performed 3 times with different pools of granulosa cells collected from 4 or more ovaries for each pool. Treatment effects and interactions were assessed using the GLM procedure (SAS Institute Inc.). Main effects were treatment, experiment, and their interaction. Each well was a replicate and each experiment contained 3 replicates per treatment. Estradiol production was expressed as pg/105 cells per 24 h, and cell numbers at the termination of the experiment were used for this calculation. Specific differences in steroid production and mRNA abundance between treatments were determined using the Fisher's protected LSD procedure (Ott, 1977). RESULTS Microarray Analysis Significant gene sequence element sets (P < 0.01) ranged from 1.83 to −1.91 fold change, with 145 elements upregulated, and 243 downregulated. Functional annotation of these 388 statistically significant gene sequences through DAVID led to the identification of 2 clusters for upregulated sequences and 5 clusters for downregulated sequences (Table 3). Biological processes such as receptor and signal transducer activity, cell communication, purine nucleotide binding, ion transport, and cell metabolism were among the biological terms detected in these clusters. Three gene sequence elements were identified as particular genes related to specific molecular pathways in the KEGG resource (http://www.genome.jp/kegg/): H+ transporting ATP synthase (accession number CAB94728), which showed a 1.22 fold change and intervenes in mitochondrial oxidative phosphorylation (Maak et al., 2001); and the catalytic subunit of G-β-γ-activated phosphatidy-ilinositol-4, 5-biphosphate 3-kinase (accession number CAA71731), which showed 1.22 fold change and is related to activation of phosphoinositide 3-kinases (Stephens et al., 1997) in several molecular pathways such as inositol phosphate metabolism, phosphatidylinositol signaling system, apoptosis, focal adhesion, toll-like receptor signaling pathway, jakstat signaling pathway, T cell receptor signaling pathway, B cell receptor signaling pathway, Fc epsilon response induction signaling pathway, leukocyte transendothelial migration, regulation of actin cytoskeleton, and insulin signaling pathway. And Janus kinase-1 (accession number 397202), which had −1.20 fold change and is a member of the nonreceptor tyrosine kinase family (Ihle and Kerr, 1995). Table 3. Functional annotation clustering of significant probes from Affymetrix Porcine GeneChips (Affymetrix, Santa Clara, CA) analysis of porcine granulosa cells treated with FSH only or FSH+IGF-I Cluster (ES)1  Biological terms (number of genes involved)  Annotation for upregulated sequences  1 (0.62)  Receptor activity (3), signal transducer activity (3), molecular transducer activity (3), receptor (3)  2 (0.43)  Cytoplasm (3), intracellular part (3), intracellular (3), cell part (4), cell (4)  Annotation for downregulated sequences  3 (0.49)  Signal transduction (5), cell communication (5), receptor activity (3), receptor (3), molecular transducer activity (3), signal transducer activity (3)  4 (0.46)  Transferase activity (5), signal transduction (5), cell communication (5), membrane (7), catalytic activity (8), macromolecule metabolic process (6), biopolymer metabolic process (4), cell (9), cell part (9), transferase (3), primary metabolic process (6), phosphoprotein (3), organelle (4), intracellular organelle (4), protein metabolic process (3), membrane bound organelle (3), intracellular membrane bound organelle (3), intracellular part (4), metabolic process (6), intracellular (4), cellular process (7), binding (7), cellular metabolic process (4)  5 (0.42)  Purine ribonucleotide binding (3), ribonucleotide binding (3), purine nucleotide binding (3), nucleotide binding (3)  6 (0.28)  Transport (3), establishment of localization (3), localization (3)  7 (0.07)  Intrinsic to membrane (3), integral to membrane (3), membrane part (3)  Cluster (ES)1  Biological terms (number of genes involved)  Annotation for upregulated sequences  1 (0.62)  Receptor activity (3), signal transducer activity (3), molecular transducer activity (3), receptor (3)  2 (0.43)  Cytoplasm (3), intracellular part (3), intracellular (3), cell part (4), cell (4)  Annotation for downregulated sequences  3 (0.49)  Signal transduction (5), cell communication (5), receptor activity (3), receptor (3), molecular transducer activity (3), signal transducer activity (3)  4 (0.46)  Transferase activity (5), signal transduction (5), cell communication (5), membrane (7), catalytic activity (8), macromolecule metabolic process (6), biopolymer metabolic process (4), cell (9), cell part (9), transferase (3), primary metabolic process (6), phosphoprotein (3), organelle (4), intracellular organelle (4), protein metabolic process (3), membrane bound organelle (3), intracellular membrane bound organelle (3), intracellular part (4), metabolic process (6), intracellular (4), cellular process (7), binding (7), cellular metabolic process (4)  5 (0.42)  Purine ribonucleotide binding (3), ribonucleotide binding (3), purine nucleotide binding (3), nucleotide binding (3)  6 (0.28)  Transport (3), establishment of localization (3), localization (3)  7 (0.07)  Intrinsic to membrane (3), integral to membrane (3), membrane part (3)  1ES = enrichment score, calculated as the geometric mean (in -log scale) of P-values of members in a corresponding annotation cluster, the greater the better (http://david.abcc.ncifcrf.gov/). View Large Table 3. Functional annotation clustering of significant probes from Affymetrix Porcine GeneChips (Affymetrix, Santa Clara, CA) analysis of porcine granulosa cells treated with FSH only or FSH+IGF-I Cluster (ES)1  Biological terms (number of genes involved)  Annotation for upregulated sequences  1 (0.62)  Receptor activity (3), signal transducer activity (3), molecular transducer activity (3), receptor (3)  2 (0.43)  Cytoplasm (3), intracellular part (3), intracellular (3), cell part (4), cell (4)  Annotation for downregulated sequences  3 (0.49)  Signal transduction (5), cell communication (5), receptor activity (3), receptor (3), molecular transducer activity (3), signal transducer activity (3)  4 (0.46)  Transferase activity (5), signal transduction (5), cell communication (5), membrane (7), catalytic activity (8), macromolecule metabolic process (6), biopolymer metabolic process (4), cell (9), cell part (9), transferase (3), primary metabolic process (6), phosphoprotein (3), organelle (4), intracellular organelle (4), protein metabolic process (3), membrane bound organelle (3), intracellular membrane bound organelle (3), intracellular part (4), metabolic process (6), intracellular (4), cellular process (7), binding (7), cellular metabolic process (4)  5 (0.42)  Purine ribonucleotide binding (3), ribonucleotide binding (3), purine nucleotide binding (3), nucleotide binding (3)  6 (0.28)  Transport (3), establishment of localization (3), localization (3)  7 (0.07)  Intrinsic to membrane (3), integral to membrane (3), membrane part (3)  Cluster (ES)1  Biological terms (number of genes involved)  Annotation for upregulated sequences  1 (0.62)  Receptor activity (3), signal transducer activity (3), molecular transducer activity (3), receptor (3)  2 (0.43)  Cytoplasm (3), intracellular part (3), intracellular (3), cell part (4), cell (4)  Annotation for downregulated sequences  3 (0.49)  Signal transduction (5), cell communication (5), receptor activity (3), receptor (3), molecular transducer activity (3), signal transducer activity (3)  4 (0.46)  Transferase activity (5), signal transduction (5), cell communication (5), membrane (7), catalytic activity (8), macromolecule metabolic process (6), biopolymer metabolic process (4), cell (9), cell part (9), transferase (3), primary metabolic process (6), phosphoprotein (3), organelle (4), intracellular organelle (4), protein metabolic process (3), membrane bound organelle (3), intracellular membrane bound organelle (3), intracellular part (4), metabolic process (6), intracellular (4), cellular process (7), binding (7), cellular metabolic process (4)  5 (0.42)  Purine ribonucleotide binding (3), ribonucleotide binding (3), purine nucleotide binding (3), nucleotide binding (3)  6 (0.28)  Transport (3), establishment of localization (3), localization (3)  7 (0.07)  Intrinsic to membrane (3), integral to membrane (3), membrane part (3)  1ES = enrichment score, calculated as the geometric mean (in -log scale) of P-values of members in a corresponding annotation cluster, the greater the better (http://david.abcc.ncifcrf.gov/). View Large Further search for annotated genes in the UniGene database allowed the identification of 42 gene sequence elements matching annotated genes, sequences, or both in the NCBI database (Table 4); 15 were significantly upregulated (up to 1.46 fold change) and 27 were down-regulated (down to −1.91 fold change). Six target genes were selected from the group of 42, 3 of them being upregulated, 5-hydroxytryptamine (serotonin) receptor 2B (HTR2B), FGFR2IIIc, and FZD8, (1.34, 1.32, and 1.22 fold change, respectively); and 3 downregulated, THBS1, CNTN4, and ITGβ8 (−1.91, −1.74, and −1.41 fold change, respectively). Table 4. National Center for Biotechnology Information sequences related to statistically significant probes from paired comparisons between FSH only and FSH+IGF-I treated porcine granulosa cells Probe set1  Fold change2  Related sequence3  Cluster4  Ssc.33.1.S1_at  1.46  NM_213999.2, Sus scrofa dual oxidase 2 (DUOX2), messenger RNA (mRNA)    Ssc.4014.1.S1_at  1.34  NP_071360.1 - mannosidase, β A, lysosomal-like [Homo sapiens]    Ssc.16145.1.S1_at  1.34  Z48174 HTR2B: Serotonin 2B receptor Z48174.1  1, 2  Ssc.15839.1.S1_at  1.32  AJ439896.1, S. scrofa partial mRNA for FGF receptor 2IIIc  1  Ssc.6670.1.A1_at  1.30  NP_036451.2 - LIV-1 protein, estrogen regulated [H. sapiens]    Ssc.16085.1.A1_at  1.27  AF100454.1, S. scrofa non-receptor tyrosine kinase Tyk2 mRNA  1  Ssc.2965.2.A1_at  1.24  Transcribed locus, strongly similar to NP_060933.2 hypothetical protein LOC55846 [H. sapiens]    Ssc.11109.1.S1_at  1.22  NM_213939.1, S. scrofa catalytic subunit of G-β-gamma-activated (phosphoinositide-3-kinase catalytic gamma polypeptide; PIK3CG), mRNA  2  Ssc.10434.1.S1_at  1.22  Mus musculus, sp:Q61091 - FZD8_MOUSE Frizzled 8 precursor    Ssc.21987.1.A1_at  1.20  AY789133.1, S. scrofa interferon-related developmental regulator 1 (IFRD1) mRNA    Ssc.3869.1.A1_at  1.20  DQ508262.1, S. scrofa breed Meishan hypothetical protein mRNA    Ssc.24081.1.S1_at  1.20  Transcribed locus, strongly similar to NP_940909.1 hypothetical protein LOC345757 [H. sapiens]    Ssc.22090.1.A1_at  1.13  NP_005105.1 - heparan sulfate D-glucosaminyl 3-O-sulfotransferase 1 precursor; heparin-glucosamine 3-O-sulfotransferase [H. sapiens]    Ssc.19150.1.S1_s_at  1.09  Transcribed locus, strongly similar to NP_001025706.1 BH3 interacting domain death agonist [S. scrofa]  2  Ssc.9970.1.A1_at  1.08  ATP5I, ATP synthase, H+ transporting, mitochondrial F0 complex, subunit E  2  Ssc.1414.2.S1_at  −1.10  NCOA1, nuclear receptor coactivator 1  3, 4  Ssc.14094.1.A1_at  −1.11  SARA2, SAR1a gene homolog 2  3, 4, 5, 6  Ssc.23103.1.S1_at  −1.12  fxyd2, FXYD domain containing ion transport regulator 2  4, 6  Ssc.13255.1.A1_at  −1.12  Transcribed locus, strongly similar to XP_001475797.1 PREDICTED: similar to Serine/arginine repetitive matrix protein 2 [M. musculus]  4  Ssc.15975.1.A1_at  −1.13  MTR, 5-methyltetrahydrofolate-homocysteine methyltransferase  4  Ssc.2488.2.S1_at  −1.17  DQ243691.2, S. scrofa FOXO3A (FOXO3A) mRNA    Ssc.235.2.S1_at  −1.18  CAST, calpastatin  4  Ssc.16068.1.A1_at  −1.19  LOC396792 olfactory receptor  3, 4, 7  Ssc.328.1.S1_at  −1.20  NM_214114.1, S. scrofa Janus kinase 1 (JAK1), mRNA  3, 4, 5  Ssc.14478.1.S1_at  −1.21  U96100.1, S. scrofa immunoglobulin E epsilon chain precursor, mRNA    Ssc.17370.1.A1_at  −1.21  H. sapiens, sp:P35368 - A1AB_HUMAN Alpha-1B adrenergic receptor    Ssc.6510.1.A1_at  −1.21  Transcribed locus, strongly similar to XP_525862.1 PREDICTED: similar to hypothetical protein FLJ37440 [Pan troglodytes]    Ssc.1511.1.S1_a_at  −1.22  Transcribed locus, strongly similar to NP_079034.3 agmatine ureohydrolase (agmatinase) [H. sapiens]  4, 7  Ssc.21161.1.S1_at  −1.25  NP_006789.1 - UDP glycosyltransferase 2 family, polypeptide A1; UDP glucuronosyltransferase 2 family, polypeptide A1 [H. sapiens]    Ssc.5118.1.S1_at  −1.26  Transcribed locus, strongly similar to NP_001001488.2 ATPase, class I, type 8B, member 1 [M. musculus]  4, 5, 6  Ssc.16056.1.A1_at  −1.27  AF141957.1, S. scrofa glycerol-3-phosphate dehydrogenase G3PD (G3PD) mRNA  4  Ssc.17787.1.S1_at  −1.28  AB087963.1, S. scrofa TCR-a mRNA for T cell receptor α chain    Ssc.28326.1.S1_at  −1.28  AY626239.1, S. scrofa UDP-N-acetylglucosamine:a-1,3-D-mannoside β-1,4-N- acetylglucosaminyltransferase IV-like protein mRNA  4  Ssc.27892.2.S1_at  −1.32  DQ492686.1, S. scrofa zinc finger protein 216 mRNA    Ssc.2408.1.S1_at  −1.33  H. sapiens, pir:G02273 - G02273 LIV-1 protein - human    Ssc.12267.1.A1_at  −1.34  H. sapiens, pir:A48043 - A48043 ubiquinol–cytochrome-c reductase    Ssc.19518.1.S1_at  −1.35  H. sapiens, pir:A55943 - A55943 1-phosphatidylinositol-4,5-bisphosphate phosphodiesterase    Ssc.16328.1.S1_at  −1.38  AB191304.1, S. scrofa COL5A2 mRNA for procollagen α 2 (V)    Ssc.23798.1.S1_at  −1.41  AY496299.1, S. scrofa integrin β 8 mRNA  3, 4, 7  Ssc.29330.1.S1_at  −1.68  Transcribed locus, strongly similar to XP_525795.1 PREDICTED: hypothetical protein XP_525795 [P. troglodytes]    Ssc.6864.1.A1_at  −1.74  AY090737, contactin 4 (CNTN4) mRNA [H. sapiens]    Ssc.26702.1.A1_at  −1.91  AY773342.1, S. scrofa thrombospondin-1 (THBS1) mRNA    Probe set1  Fold change2  Related sequence3  Cluster4  Ssc.33.1.S1_at  1.46  NM_213999.2, Sus scrofa dual oxidase 2 (DUOX2), messenger RNA (mRNA)    Ssc.4014.1.S1_at  1.34  NP_071360.1 - mannosidase, β A, lysosomal-like [Homo sapiens]    Ssc.16145.1.S1_at  1.34  Z48174 HTR2B: Serotonin 2B receptor Z48174.1  1, 2  Ssc.15839.1.S1_at  1.32  AJ439896.1, S. scrofa partial mRNA for FGF receptor 2IIIc  1  Ssc.6670.1.A1_at  1.30  NP_036451.2 - LIV-1 protein, estrogen regulated [H. sapiens]    Ssc.16085.1.A1_at  1.27  AF100454.1, S. scrofa non-receptor tyrosine kinase Tyk2 mRNA  1  Ssc.2965.2.A1_at  1.24  Transcribed locus, strongly similar to NP_060933.2 hypothetical protein LOC55846 [H. sapiens]    Ssc.11109.1.S1_at  1.22  NM_213939.1, S. scrofa catalytic subunit of G-β-gamma-activated (phosphoinositide-3-kinase catalytic gamma polypeptide; PIK3CG), mRNA  2  Ssc.10434.1.S1_at  1.22  Mus musculus, sp:Q61091 - FZD8_MOUSE Frizzled 8 precursor    Ssc.21987.1.A1_at  1.20  AY789133.1, S. scrofa interferon-related developmental regulator 1 (IFRD1) mRNA    Ssc.3869.1.A1_at  1.20  DQ508262.1, S. scrofa breed Meishan hypothetical protein mRNA    Ssc.24081.1.S1_at  1.20  Transcribed locus, strongly similar to NP_940909.1 hypothetical protein LOC345757 [H. sapiens]    Ssc.22090.1.A1_at  1.13  NP_005105.1 - heparan sulfate D-glucosaminyl 3-O-sulfotransferase 1 precursor; heparin-glucosamine 3-O-sulfotransferase [H. sapiens]    Ssc.19150.1.S1_s_at  1.09  Transcribed locus, strongly similar to NP_001025706.1 BH3 interacting domain death agonist [S. scrofa]  2  Ssc.9970.1.A1_at  1.08  ATP5I, ATP synthase, H+ transporting, mitochondrial F0 complex, subunit E  2  Ssc.1414.2.S1_at  −1.10  NCOA1, nuclear receptor coactivator 1  3, 4  Ssc.14094.1.A1_at  −1.11  SARA2, SAR1a gene homolog 2  3, 4, 5, 6  Ssc.23103.1.S1_at  −1.12  fxyd2, FXYD domain containing ion transport regulator 2  4, 6  Ssc.13255.1.A1_at  −1.12  Transcribed locus, strongly similar to XP_001475797.1 PREDICTED: similar to Serine/arginine repetitive matrix protein 2 [M. musculus]  4  Ssc.15975.1.A1_at  −1.13  MTR, 5-methyltetrahydrofolate-homocysteine methyltransferase  4  Ssc.2488.2.S1_at  −1.17  DQ243691.2, S. scrofa FOXO3A (FOXO3A) mRNA    Ssc.235.2.S1_at  −1.18  CAST, calpastatin  4  Ssc.16068.1.A1_at  −1.19  LOC396792 olfactory receptor  3, 4, 7  Ssc.328.1.S1_at  −1.20  NM_214114.1, S. scrofa Janus kinase 1 (JAK1), mRNA  3, 4, 5  Ssc.14478.1.S1_at  −1.21  U96100.1, S. scrofa immunoglobulin E epsilon chain precursor, mRNA    Ssc.17370.1.A1_at  −1.21  H. sapiens, sp:P35368 - A1AB_HUMAN Alpha-1B adrenergic receptor    Ssc.6510.1.A1_at  −1.21  Transcribed locus, strongly similar to XP_525862.1 PREDICTED: similar to hypothetical protein FLJ37440 [Pan troglodytes]    Ssc.1511.1.S1_a_at  −1.22  Transcribed locus, strongly similar to NP_079034.3 agmatine ureohydrolase (agmatinase) [H. sapiens]  4, 7  Ssc.21161.1.S1_at  −1.25  NP_006789.1 - UDP glycosyltransferase 2 family, polypeptide A1; UDP glucuronosyltransferase 2 family, polypeptide A1 [H. sapiens]    Ssc.5118.1.S1_at  −1.26  Transcribed locus, strongly similar to NP_001001488.2 ATPase, class I, type 8B, member 1 [M. musculus]  4, 5, 6  Ssc.16056.1.A1_at  −1.27  AF141957.1, S. scrofa glycerol-3-phosphate dehydrogenase G3PD (G3PD) mRNA  4  Ssc.17787.1.S1_at  −1.28  AB087963.1, S. scrofa TCR-a mRNA for T cell receptor α chain    Ssc.28326.1.S1_at  −1.28  AY626239.1, S. scrofa UDP-N-acetylglucosamine:a-1,3-D-mannoside β-1,4-N- acetylglucosaminyltransferase IV-like protein mRNA  4  Ssc.27892.2.S1_at  −1.32  DQ492686.1, S. scrofa zinc finger protein 216 mRNA    Ssc.2408.1.S1_at  −1.33  H. sapiens, pir:G02273 - G02273 LIV-1 protein - human    Ssc.12267.1.A1_at  −1.34  H. sapiens, pir:A48043 - A48043 ubiquinol–cytochrome-c reductase    Ssc.19518.1.S1_at  −1.35  H. sapiens, pir:A55943 - A55943 1-phosphatidylinositol-4,5-bisphosphate phosphodiesterase    Ssc.16328.1.S1_at  −1.38  AB191304.1, S. scrofa COL5A2 mRNA for procollagen α 2 (V)    Ssc.23798.1.S1_at  −1.41  AY496299.1, S. scrofa integrin β 8 mRNA  3, 4, 7  Ssc.29330.1.S1_at  −1.68  Transcribed locus, strongly similar to XP_525795.1 PREDICTED: hypothetical protein XP_525795 [P. troglodytes]    Ssc.6864.1.A1_at  −1.74  AY090737, contactin 4 (CNTN4) mRNA [H. sapiens]    Ssc.26702.1.A1_at  −1.91  AY773342.1, S. scrofa thrombospondin-1 (THBS1) mRNA    1Probe set identification from Affymetrix Porcine GeneChip (Affymetrix, Santa Clara, CA). 2Fold change calculated as the ratio of the mean intensity of FSH+IGF-I and FSH only treated paired samples. 3Related sequence in National Center for Biotechnology Information database. 4Functional cluster (Table 3) based on DAVID Functional Annotation Tool (http://david.abcc.ncifcrf.gov/). View Large Table 4. National Center for Biotechnology Information sequences related to statistically significant probes from paired comparisons between FSH only and FSH+IGF-I treated porcine granulosa cells Probe set1  Fold change2  Related sequence3  Cluster4  Ssc.33.1.S1_at  1.46  NM_213999.2, Sus scrofa dual oxidase 2 (DUOX2), messenger RNA (mRNA)    Ssc.4014.1.S1_at  1.34  NP_071360.1 - mannosidase, β A, lysosomal-like [Homo sapiens]    Ssc.16145.1.S1_at  1.34  Z48174 HTR2B: Serotonin 2B receptor Z48174.1  1, 2  Ssc.15839.1.S1_at  1.32  AJ439896.1, S. scrofa partial mRNA for FGF receptor 2IIIc  1  Ssc.6670.1.A1_at  1.30  NP_036451.2 - LIV-1 protein, estrogen regulated [H. sapiens]    Ssc.16085.1.A1_at  1.27  AF100454.1, S. scrofa non-receptor tyrosine kinase Tyk2 mRNA  1  Ssc.2965.2.A1_at  1.24  Transcribed locus, strongly similar to NP_060933.2 hypothetical protein LOC55846 [H. sapiens]    Ssc.11109.1.S1_at  1.22  NM_213939.1, S. scrofa catalytic subunit of G-β-gamma-activated (phosphoinositide-3-kinase catalytic gamma polypeptide; PIK3CG), mRNA  2  Ssc.10434.1.S1_at  1.22  Mus musculus, sp:Q61091 - FZD8_MOUSE Frizzled 8 precursor    Ssc.21987.1.A1_at  1.20  AY789133.1, S. scrofa interferon-related developmental regulator 1 (IFRD1) mRNA    Ssc.3869.1.A1_at  1.20  DQ508262.1, S. scrofa breed Meishan hypothetical protein mRNA    Ssc.24081.1.S1_at  1.20  Transcribed locus, strongly similar to NP_940909.1 hypothetical protein LOC345757 [H. sapiens]    Ssc.22090.1.A1_at  1.13  NP_005105.1 - heparan sulfate D-glucosaminyl 3-O-sulfotransferase 1 precursor; heparin-glucosamine 3-O-sulfotransferase [H. sapiens]    Ssc.19150.1.S1_s_at  1.09  Transcribed locus, strongly similar to NP_001025706.1 BH3 interacting domain death agonist [S. scrofa]  2  Ssc.9970.1.A1_at  1.08  ATP5I, ATP synthase, H+ transporting, mitochondrial F0 complex, subunit E  2  Ssc.1414.2.S1_at  −1.10  NCOA1, nuclear receptor coactivator 1  3, 4  Ssc.14094.1.A1_at  −1.11  SARA2, SAR1a gene homolog 2  3, 4, 5, 6  Ssc.23103.1.S1_at  −1.12  fxyd2, FXYD domain containing ion transport regulator 2  4, 6  Ssc.13255.1.A1_at  −1.12  Transcribed locus, strongly similar to XP_001475797.1 PREDICTED: similar to Serine/arginine repetitive matrix protein 2 [M. musculus]  4  Ssc.15975.1.A1_at  −1.13  MTR, 5-methyltetrahydrofolate-homocysteine methyltransferase  4  Ssc.2488.2.S1_at  −1.17  DQ243691.2, S. scrofa FOXO3A (FOXO3A) mRNA    Ssc.235.2.S1_at  −1.18  CAST, calpastatin  4  Ssc.16068.1.A1_at  −1.19  LOC396792 olfactory receptor  3, 4, 7  Ssc.328.1.S1_at  −1.20  NM_214114.1, S. scrofa Janus kinase 1 (JAK1), mRNA  3, 4, 5  Ssc.14478.1.S1_at  −1.21  U96100.1, S. scrofa immunoglobulin E epsilon chain precursor, mRNA    Ssc.17370.1.A1_at  −1.21  H. sapiens, sp:P35368 - A1AB_HUMAN Alpha-1B adrenergic receptor    Ssc.6510.1.A1_at  −1.21  Transcribed locus, strongly similar to XP_525862.1 PREDICTED: similar to hypothetical protein FLJ37440 [Pan troglodytes]    Ssc.1511.1.S1_a_at  −1.22  Transcribed locus, strongly similar to NP_079034.3 agmatine ureohydrolase (agmatinase) [H. sapiens]  4, 7  Ssc.21161.1.S1_at  −1.25  NP_006789.1 - UDP glycosyltransferase 2 family, polypeptide A1; UDP glucuronosyltransferase 2 family, polypeptide A1 [H. sapiens]    Ssc.5118.1.S1_at  −1.26  Transcribed locus, strongly similar to NP_001001488.2 ATPase, class I, type 8B, member 1 [M. musculus]  4, 5, 6  Ssc.16056.1.A1_at  −1.27  AF141957.1, S. scrofa glycerol-3-phosphate dehydrogenase G3PD (G3PD) mRNA  4  Ssc.17787.1.S1_at  −1.28  AB087963.1, S. scrofa TCR-a mRNA for T cell receptor α chain    Ssc.28326.1.S1_at  −1.28  AY626239.1, S. scrofa UDP-N-acetylglucosamine:a-1,3-D-mannoside β-1,4-N- acetylglucosaminyltransferase IV-like protein mRNA  4  Ssc.27892.2.S1_at  −1.32  DQ492686.1, S. scrofa zinc finger protein 216 mRNA    Ssc.2408.1.S1_at  −1.33  H. sapiens, pir:G02273 - G02273 LIV-1 protein - human    Ssc.12267.1.A1_at  −1.34  H. sapiens, pir:A48043 - A48043 ubiquinol–cytochrome-c reductase    Ssc.19518.1.S1_at  −1.35  H. sapiens, pir:A55943 - A55943 1-phosphatidylinositol-4,5-bisphosphate phosphodiesterase    Ssc.16328.1.S1_at  −1.38  AB191304.1, S. scrofa COL5A2 mRNA for procollagen α 2 (V)    Ssc.23798.1.S1_at  −1.41  AY496299.1, S. scrofa integrin β 8 mRNA  3, 4, 7  Ssc.29330.1.S1_at  −1.68  Transcribed locus, strongly similar to XP_525795.1 PREDICTED: hypothetical protein XP_525795 [P. troglodytes]    Ssc.6864.1.A1_at  −1.74  AY090737, contactin 4 (CNTN4) mRNA [H. sapiens]    Ssc.26702.1.A1_at  −1.91  AY773342.1, S. scrofa thrombospondin-1 (THBS1) mRNA    Probe set1  Fold change2  Related sequence3  Cluster4  Ssc.33.1.S1_at  1.46  NM_213999.2, Sus scrofa dual oxidase 2 (DUOX2), messenger RNA (mRNA)    Ssc.4014.1.S1_at  1.34  NP_071360.1 - mannosidase, β A, lysosomal-like [Homo sapiens]    Ssc.16145.1.S1_at  1.34  Z48174 HTR2B: Serotonin 2B receptor Z48174.1  1, 2  Ssc.15839.1.S1_at  1.32  AJ439896.1, S. scrofa partial mRNA for FGF receptor 2IIIc  1  Ssc.6670.1.A1_at  1.30  NP_036451.2 - LIV-1 protein, estrogen regulated [H. sapiens]    Ssc.16085.1.A1_at  1.27  AF100454.1, S. scrofa non-receptor tyrosine kinase Tyk2 mRNA  1  Ssc.2965.2.A1_at  1.24  Transcribed locus, strongly similar to NP_060933.2 hypothetical protein LOC55846 [H. sapiens]    Ssc.11109.1.S1_at  1.22  NM_213939.1, S. scrofa catalytic subunit of G-β-gamma-activated (phosphoinositide-3-kinase catalytic gamma polypeptide; PIK3CG), mRNA  2  Ssc.10434.1.S1_at  1.22  Mus musculus, sp:Q61091 - FZD8_MOUSE Frizzled 8 precursor    Ssc.21987.1.A1_at  1.20  AY789133.1, S. scrofa interferon-related developmental regulator 1 (IFRD1) mRNA    Ssc.3869.1.A1_at  1.20  DQ508262.1, S. scrofa breed Meishan hypothetical protein mRNA    Ssc.24081.1.S1_at  1.20  Transcribed locus, strongly similar to NP_940909.1 hypothetical protein LOC345757 [H. sapiens]    Ssc.22090.1.A1_at  1.13  NP_005105.1 - heparan sulfate D-glucosaminyl 3-O-sulfotransferase 1 precursor; heparin-glucosamine 3-O-sulfotransferase [H. sapiens]    Ssc.19150.1.S1_s_at  1.09  Transcribed locus, strongly similar to NP_001025706.1 BH3 interacting domain death agonist [S. scrofa]  2  Ssc.9970.1.A1_at  1.08  ATP5I, ATP synthase, H+ transporting, mitochondrial F0 complex, subunit E  2  Ssc.1414.2.S1_at  −1.10  NCOA1, nuclear receptor coactivator 1  3, 4  Ssc.14094.1.A1_at  −1.11  SARA2, SAR1a gene homolog 2  3, 4, 5, 6  Ssc.23103.1.S1_at  −1.12  fxyd2, FXYD domain containing ion transport regulator 2  4, 6  Ssc.13255.1.A1_at  −1.12  Transcribed locus, strongly similar to XP_001475797.1 PREDICTED: similar to Serine/arginine repetitive matrix protein 2 [M. musculus]  4  Ssc.15975.1.A1_at  −1.13  MTR, 5-methyltetrahydrofolate-homocysteine methyltransferase  4  Ssc.2488.2.S1_at  −1.17  DQ243691.2, S. scrofa FOXO3A (FOXO3A) mRNA    Ssc.235.2.S1_at  −1.18  CAST, calpastatin  4  Ssc.16068.1.A1_at  −1.19  LOC396792 olfactory receptor  3, 4, 7  Ssc.328.1.S1_at  −1.20  NM_214114.1, S. scrofa Janus kinase 1 (JAK1), mRNA  3, 4, 5  Ssc.14478.1.S1_at  −1.21  U96100.1, S. scrofa immunoglobulin E epsilon chain precursor, mRNA    Ssc.17370.1.A1_at  −1.21  H. sapiens, sp:P35368 - A1AB_HUMAN Alpha-1B adrenergic receptor    Ssc.6510.1.A1_at  −1.21  Transcribed locus, strongly similar to XP_525862.1 PREDICTED: similar to hypothetical protein FLJ37440 [Pan troglodytes]    Ssc.1511.1.S1_a_at  −1.22  Transcribed locus, strongly similar to NP_079034.3 agmatine ureohydrolase (agmatinase) [H. sapiens]  4, 7  Ssc.21161.1.S1_at  −1.25  NP_006789.1 - UDP glycosyltransferase 2 family, polypeptide A1; UDP glucuronosyltransferase 2 family, polypeptide A1 [H. sapiens]    Ssc.5118.1.S1_at  −1.26  Transcribed locus, strongly similar to NP_001001488.2 ATPase, class I, type 8B, member 1 [M. musculus]  4, 5, 6  Ssc.16056.1.A1_at  −1.27  AF141957.1, S. scrofa glycerol-3-phosphate dehydrogenase G3PD (G3PD) mRNA  4  Ssc.17787.1.S1_at  −1.28  AB087963.1, S. scrofa TCR-a mRNA for T cell receptor α chain    Ssc.28326.1.S1_at  −1.28  AY626239.1, S. scrofa UDP-N-acetylglucosamine:a-1,3-D-mannoside β-1,4-N- acetylglucosaminyltransferase IV-like protein mRNA  4  Ssc.27892.2.S1_at  −1.32  DQ492686.1, S. scrofa zinc finger protein 216 mRNA    Ssc.2408.1.S1_at  −1.33  H. sapiens, pir:G02273 - G02273 LIV-1 protein - human    Ssc.12267.1.A1_at  −1.34  H. sapiens, pir:A48043 - A48043 ubiquinol–cytochrome-c reductase    Ssc.19518.1.S1_at  −1.35  H. sapiens, pir:A55943 - A55943 1-phosphatidylinositol-4,5-bisphosphate phosphodiesterase    Ssc.16328.1.S1_at  −1.38  AB191304.1, S. scrofa COL5A2 mRNA for procollagen α 2 (V)    Ssc.23798.1.S1_at  −1.41  AY496299.1, S. scrofa integrin β 8 mRNA  3, 4, 7  Ssc.29330.1.S1_at  −1.68  Transcribed locus, strongly similar to XP_525795.1 PREDICTED: hypothetical protein XP_525795 [P. troglodytes]    Ssc.6864.1.A1_at  −1.74  AY090737, contactin 4 (CNTN4) mRNA [H. sapiens]    Ssc.26702.1.A1_at  −1.91  AY773342.1, S. scrofa thrombospondin-1 (THBS1) mRNA    1Probe set identification from Affymetrix Porcine GeneChip (Affymetrix, Santa Clara, CA). 2Fold change calculated as the ratio of the mean intensity of FSH+IGF-I and FSH only treated paired samples. 3Related sequence in National Center for Biotechnology Information database. 4Functional cluster (Table 3) based on DAVID Functional Annotation Tool (http://david.abcc.ncifcrf.gov/). View Large Quantitative One-Step Real-Time RT-PCR Abundance of mRNA for the target genes detected as up- and downregulated in the microarray experiment was validated through one-step real-time RT-PCR. Then a simple comparison of the fold changes estimated from the microarray analysis and RT-PCR was performed. Fold change was calculated relative to the level of expression in samples from pig granulosa cells treated with FSH only. Microarray Upregulated Genes. Expression patterns for genes detected as upregulated in the microarray analysis were consistent with the quantitative analysis (Figure 1). The fold changes detected in the microarrays for HTR2B, FGFR2IIIc, and FZD8 were 1.34, 1.41, and 1.22, respectively, whereas in the quantitative analysis using real-time RT-PCR the estimated fold changes were 1.00, 1.32, and 2.11, respectively. However, the difference in level of expression between treatments was significant (P < 0.05) only for FG-FR2IIIc (Table 5). Figure 1. View largeDownload slide Comparison of fold changes in mRNA expression detected through Affymetrix Porcine GeneChip (Affymetrix, Santa Clara, CA) microarray analysis and one-step real-time reverse transcription-PCR (RT-PCR) analysis of RNA obtained from porcine granulosa cells treated with FSH only or FSH+IGF-I. All fold changes from the microarray analysis are statistically significant (P < 0.01). Statistical significance of fold changes estimated through RT-PCR analysis is indicated as NS = not significant (P > 0.05); *P < 0.05; **P < 0.01. Target genes: HTR2B, serotonin receptor 2B; FGFR2IIIc, fibroblast growth factor receptor 2IIIc; FZD8, frizzled homolog 8; THBS1, thrombospondin-1; ITGβ8, integrin β 8; CNTN4, contactin 4 homolog. Figure 1. View largeDownload slide Comparison of fold changes in mRNA expression detected through Affymetrix Porcine GeneChip (Affymetrix, Santa Clara, CA) microarray analysis and one-step real-time reverse transcription-PCR (RT-PCR) analysis of RNA obtained from porcine granulosa cells treated with FSH only or FSH+IGF-I. All fold changes from the microarray analysis are statistically significant (P < 0.01). Statistical significance of fold changes estimated through RT-PCR analysis is indicated as NS = not significant (P > 0.05); *P < 0.05; **P < 0.01. Target genes: HTR2B, serotonin receptor 2B; FGFR2IIIc, fibroblast growth factor receptor 2IIIc; FZD8, frizzled homolog 8; THBS1, thrombospondin-1; ITGβ8, integrin β 8; CNTN4, contactin 4 homolog. Table 5. Least squares means (±SE) for the natural log of the relative abundance of messenger RNA for up and downregulated genes evaluated using reverse transcription-PCR in porcine granulosa cells receiving 2 hormonal treatments, FSH only or FSH+IGF-I     Treatment  Regulation  Target gene1  FSH only  FSH+IGF-I  Upregulated  HTR2B  1.92 ± 0.11  1.92 ± 0.12    FGFR2IIIc  1.32 ± 0.18a  1.86 ± 0.20b    FZD8  1.08 ± 0.42  2.28 ± 0.26  Downregulated  THBS1  1.85 ± 0.12b  1.04 ± 0.13a    ITGβ8  6.15 ± 0.55a  9.15 ± 0.57b    CNTN4  1.71 ± 0.53  2.80 ± 0.45      Treatment  Regulation  Target gene1  FSH only  FSH+IGF-I  Upregulated  HTR2B  1.92 ± 0.11  1.92 ± 0.12    FGFR2IIIc  1.32 ± 0.18a  1.86 ± 0.20b    FZD8  1.08 ± 0.42  2.28 ± 0.26  Downregulated  THBS1  1.85 ± 0.12b  1.04 ± 0.13a    ITGβ8  6.15 ± 0.55a  9.15 ± 0.57b    CNTN4  1.71 ± 0.53  2.80 ± 0.45  a,bRelative abundance mean values within target gene without a common superscript are different (P < 0.05). 1Target genes: HTR2B, serotonin receptor 2B; FGFR2IIIc, fibroblast growth factor receptor 2IIIc; FZD8, frizzled homolog 8; THBS1, thrombospondin-1; ITGβ8, integrin β 8; CNTN4, contactin 4 homolog. View Large Table 5. Least squares means (±SE) for the natural log of the relative abundance of messenger RNA for up and downregulated genes evaluated using reverse transcription-PCR in porcine granulosa cells receiving 2 hormonal treatments, FSH only or FSH+IGF-I     Treatment  Regulation  Target gene1  FSH only  FSH+IGF-I  Upregulated  HTR2B  1.92 ± 0.11  1.92 ± 0.12    FGFR2IIIc  1.32 ± 0.18a  1.86 ± 0.20b    FZD8  1.08 ± 0.42  2.28 ± 0.26  Downregulated  THBS1  1.85 ± 0.12b  1.04 ± 0.13a    ITGβ8  6.15 ± 0.55a  9.15 ± 0.57b    CNTN4  1.71 ± 0.53  2.80 ± 0.45      Treatment  Regulation  Target gene1  FSH only  FSH+IGF-I  Upregulated  HTR2B  1.92 ± 0.11  1.92 ± 0.12    FGFR2IIIc  1.32 ± 0.18a  1.86 ± 0.20b    FZD8  1.08 ± 0.42  2.28 ± 0.26  Downregulated  THBS1  1.85 ± 0.12b  1.04 ± 0.13a    ITGβ8  6.15 ± 0.55a  9.15 ± 0.57b    CNTN4  1.71 ± 0.53  2.80 ± 0.45  a,bRelative abundance mean values within target gene without a common superscript are different (P < 0.05). 1Target genes: HTR2B, serotonin receptor 2B; FGFR2IIIc, fibroblast growth factor receptor 2IIIc; FZD8, frizzled homolog 8; THBS1, thrombospondin-1; ITGβ8, integrin β 8; CNTN4, contactin 4 homolog. View Large Microarray Downregulated Genes. For genes detected as downregulated in the microarray analysis, the same pattern of expression was detected only for THBS1 (−1.91 and −1.78 fold change for microarray and quantitative analysis, respectively), whereas ITGβ8 and CNTN4, with −1.41 and −1.74 fold change in the microarray analysis, respectively, showed positive fold changes in the quantitative analysis of 1.49 and 1.64, respectively (Figure 1). However, the differences in relative level of expression between treatments were significant (P < 0.01) only for THBS1 and ITGβ8 (Table 5). Effect of Sexual Maturity of Gilt on Granulosa Cell Response to FSH and IGF-I. Pubertal state had no effect (P > 0.1) on estradiol response of granulosa cells to IGF-I or FSH (Figure 2). Both IGF-I and FSH stimulated estradiol production by severalfold (P < 0.01), and this response did not differ between prepubertal and postpubertal gilts (Figure 2). Figure 2. View largeDownload slide Effect of stage of puberty on IGF-I- and FSH-induced estradiol production by granulosa cells. Granulosa cells from small (1 to 5 mm) follicles were collected from prepubertal (solid bars) or post-pubertal (hatched bars) gilts and cultured for 48 h in the presence of 5% fetal calf serum (FCS) and porcine serum (PS). Cells were washed and incubated in the presence FSH (0, 30 ng/mL), IGF-I (0, 30 ng/ mL), or both for an additional 48 h. Values are means of 3 separate experiments (±SEM). a,bMeans without a common letter differ (P < 0.05). Figure 2. View largeDownload slide Effect of stage of puberty on IGF-I- and FSH-induced estradiol production by granulosa cells. Granulosa cells from small (1 to 5 mm) follicles were collected from prepubertal (solid bars) or post-pubertal (hatched bars) gilts and cultured for 48 h in the presence of 5% fetal calf serum (FCS) and porcine serum (PS). Cells were washed and incubated in the presence FSH (0, 30 ng/mL), IGF-I (0, 30 ng/ mL), or both for an additional 48 h. Values are means of 3 separate experiments (±SEM). a,bMeans without a common letter differ (P < 0.05). Effect of FSH and Estradiol on IGF-I-Induced Suppression of THBS1. Granulosa cells were cultured for 48 h in the presence of 5% FCS and PS, and then cells were washed and incubated with FSH (0, 30 ng/mL) or estradiol (0, 300 ng/mL) without or with 30 ng/mL of IGF-I for 24 h, and RNA was collected. Real-time PCR revealed that IGF-I decreased (P < 0.05) abundance of THBS1 mRNA by 42 to 51%, whereas neither FSH nor estradiol affected (P > 0.10) basal or IGF-I-induced inhibition of THBS1 mRNA (Figure 3). Figure 3. View largeDownload slide Effect of FSH and estradiol on THBS1 messenger RNA (mRNA) inhibited by IGF-I in granulosa cells. Granulosa cells from small (1 to 5 mm) follicles were cultured for 48 h in the presence of 5% fetal calf serum (FCS) and porcine serum (PS), and then cells were washed and incubated in the presence of FSH (0, 30 ng/mL) or estradiol (E2; 0, 300 ng/mL) without (hatched bars) or with 30 ng/mL of IGF-I (solid bars) for 24 h. Cellular RNA was extracted and real-time reverse transcription-PCR conducted. Values are means of 3 separate experiments (±SEM) and normalized to constitutively expressed 18S ribosomal RNA. a,bMeans without a common letter differ (P < 0.05). Figure 3. View largeDownload slide Effect of FSH and estradiol on THBS1 messenger RNA (mRNA) inhibited by IGF-I in granulosa cells. Granulosa cells from small (1 to 5 mm) follicles were cultured for 48 h in the presence of 5% fetal calf serum (FCS) and porcine serum (PS), and then cells were washed and incubated in the presence of FSH (0, 30 ng/mL) or estradiol (E2; 0, 300 ng/mL) without (hatched bars) or with 30 ng/mL of IGF-I (solid bars) for 24 h. Cellular RNA was extracted and real-time reverse transcription-PCR conducted. Values are means of 3 separate experiments (±SEM) and normalized to constitutively expressed 18S ribosomal RNA. a,bMeans without a common letter differ (P < 0.05). DISCUSSION Overall Changes in Gene Transcription Analysis by DNA microarray has become a widely used tool for generating information on a genomic scale, producing massive quantities of gene expression and other functional genomics data. In the present study, the use of Affymetrix Porcine GeneChips microarrays allowed the detection of statistically significant differences in expression for 388 gene sequence elements in cultured porcine granulosa cells receiving 2 hormonal treatments (FSH only or FSH+IGF-I) with a fair degree of confidence and a range of fold change in the level of expression between hormonal treatments from 1.83 to −1.91. When the 388 gene sequence elements were organized into functional categories, signal transduction molecules, factors associated with cellular metabolism, transcription factors, cell adhesion molecules, cell surface antigens, ion channels, and expressed sequence tags were among the groups of gene sequence elements with altered mRNA abundance. After a search for annotated genes in the UniGene database, 42 gene sequence elements were related to annotated genes, sequences, or both in the NCBI database. Several of the differentially expressed genes were known IGF-I-response genes. For example, one of the identified upregulated genes (1.08 fold change) associated with cellular metabolism was the phosphoinositide-3-kinase catalytic gamma polypeptide (PIK3CG), whose protein catalytic activity is involved in the insulin and IGF-I signaling pathway (Poretsky et al., 1999; Wood and Strauss, 2002; Laviola et al., 2007) and the regulation of StAR in granulosa cells (Seto-Young et al., 2007). Although not statistically significant, our microarray analysis showed the same pattern of expression as previously reported in response to FSH and IGF-I treatment of granulosa cells in vitro for several genes related to steroidogenesis, namely, StAR (3.05-fold increase; Balasubramanian et al., 1997), low-density lipoprotein receptor (LDLR; 1.75-fold increase; LaVoie et al., 1999), 3-hydroxy-3-methylglutaryl coenzyme A reductase (HMG-CoA; 2.27 fold increase; Maitra et al., 1995), CYP11A1 (1.08 fold increase; Winters et al., 1998), LHR (2.62 fold increase; Hirakawa et al., 1999), CYP19A1 (1.05 fold increase; Ranzenigo et al., 2008), and 3βHSD (1.08-fold increase; deMoura et al., 1997). However, 6 novel target genes not previously reported as IGF-I-responsive genes were selected from the group of 42 to be verified by RT-PCR, 3 of them being up-regulated: FGFR2IIIc, FZD8, and HTR2B (1.32, 1.22, and 1.34 fold change, respectively); and 3 downregulated: THBS1, ITGβ8, and CNTN4 (−1.91, −1.41, and −1.74 fold change, respectively). Of the 3 upregulated target genes selected for further quantitative RT-PCR analysis, only FGFR2IIIc mRNA abundance was significantly increased by IGF-I. Of the 3 downregulated target genes selected for further analysis, only THBS1 mRNA abundance was significantly decreased by IGF-I. Quantitative real-time RT-PCR is a reliable tool whose results usually agree with those from microarray experiments (Rajeevan et al., 2001). However, there have been studies where microarray results related to pattern of gene expression are not supported by those from real-time RT-PCR (Friedmann et al., 2005; Turner et al., 2007). Several causes have been proposed to lead to such discrepancies. For example, it is possible that specific expression of a gene could be defined as absent on the microarray experiment, but can be demonstrated by the more sensitive RT-PCR technique. Friedmann et al. (2005) indicates that there is an intrinsic variability in the affinity of labeled samples to the corresponding probes on the microarray, which undoubtedly can affect the fold difference in gene activity between experimental groups. Furthermore, microarray results are influenced by array production, RNA extraction, probe labeling, hybridization conditions, and image analysis (Rajeevan et al., 2001). Selected Upregulated Gene FGF Receptor 2 III c (FGFR2IIIc). The fibro-blast growth factor (FGF) family consists of numerous polypeptides numbered as FGF 1 to 22 (Zhang et al., 2006) that are potent regulators of cell proliferation and differentiation of a wide range of cell types (reviewed by Galzie et al., 1997). The FGF show a strong affinity for heparin and heparin-like glycosaminoglycans, as well as a central core of 140 AA that are highly homologous between different family members (Powers et al., 2000). Interestingly, heparin-glucosamine 3-O-sulfotransferase was also upregulated by IGF-I in the present study. This enzyme is responsible for the production of heparan sulfate proteoglycans (Liu et al., 1996), which are present in follicular fluid at several stages of follicle development (Grimek et al., 1984) and negatively correlated with estradiol concentrations (Bushmeyer et al., 1985). Although not well characterized within the ovary, basic FGF (FGF2) and its receptors (FGFR-2, FGFR-3, and FGFR-4) have been found to be present during follicular development (van Wezel et al., 1995; Ben-Haroush et al., 2005). The biological activities of FGF are mediated through high affinity tyrosine kinase receptors (FGFR1 to FGFR4) and heparan sulfate proteoglycan low affinity receptors (Powers et al., 2000). The FGFR are characterized by the presence of 2 or 3 immunoglobulin-like domains in the extracellular region and a tyrosine kinase domain in the intracellular region of the receptor. Alternative splicing in the extracellular region of FGFR1 to FGFR3 generates receptor variants (IIIb and IIIc) with different binding affinities and utilization dependent upon cell lineage (Zhang et al., 2006). The FGF2 activates the splice variant FGFR2IIIc and FGFR1IIIc but not FG-FR2IIIb, whereas FGF7 binds and activates only the FGFR2IIIb in epithelial cells, and acidic FGF exhibit a broader interaction with multiple isoforms (Ornitz et al., 1996). We found that FGFR2IIIc mRNA was upregulated by 32 to 41% in porcine granulosa cells treated with FSH+IGF-I vs. FSH alone, and this pattern of expression was detected in both the microarray analysis and quantitative one-step real-time RT-PCR. An environment with elevated concentrations of free IGF-I is characteristic of large healthy follicles (Spicer and Echternkamp, 1995; Spicer, 2004). The FGF2, produced by theca cells (Berisha et al., 2006), is a powerful mitogen in granulosa cells (Gospodarowicz et al., 1977) and inhibits apoptotic granulosa cell death (Tilly et al., 1992). In cultured ovarian granulosa cells, FGF2 inhibits FSH-dependent induction of LHR (Mondschein and Schomberg, 1981) and FSH (but not basal)-supported aromatization (Adashi et al., 1988; Vernon and Spicer, 1994), and stimulates progesterone production (Baird and Hsueh, 1986). Thus, it seems feasible that IGF-I may enhance FGF2 effects through induction of FG-FR2IIIc during early follicular development, enhancing mitogenesis (Gospodarowicz et al., 1977) and preventing premature differentiation (Adashi et al., 1988) in granulosa cells. In prepubertal gilts treated with equine chorionic gonadotropin, the expression of FGF2 mRNA in granulosa cells is increased in medium and large follicles, and a parallel expression for FGFR1 mRNA is observed in theca cells (Shimizu et al., 2002) giving support to the hypothesis that FGF2 and its receptor are hormonally regulated during the estrous cycle of the gilt. In cattle, mRNA expression for FGFR2IIIb splice variant was relatively high in granulosa cells during final growth of follicles, whereas in theca cells it showed a weak signal (Berisha et al., 2004). In contrast, the FGFR2II-Ic splice variant showed a relatively high expression without significant changes in both theca interna and granulosa cells during final follicular growth, indicating cell-specific regulation of the FGF2R may occur (Berisha et al., 2006). The FGFR4 and the c splice form of FGFR3, which are known to be preferentially activated by FGF8, have been detected in theca and in granulosa cells of antral follicles, respectively (Buratini et al., 2005). Furthermore, FGFR3c mRNA abundance is positively correlated with follicular estradiol content, and addition of FSH but not IGF-I to cultured bovine granulosa cells increases expression of FGFR3c (Buratini et al., 2005). Thus, evidence from several studies indicates that ovarian expression of FGF and their receptors are regulated in response to gonadotropins and intraovarian factors, such as IGF-I, and that species and cell-specific differences likely exist in expression patterns within growing follicles. Selected Downregulated Gene THBS1. The thrombospondins (THBS) constitute a family of 5 multidomain glycoproteins, of which THBS1 and -2 are grouped in the same class and have high structural homology. The THBS-3 to -5 belong to a separate isoform class, with significant structural differences and variation in the procollagen homology region compared with THBS1 and -2, which function in cell-cell and cell-matrix interactions and are potent inhibitors of angiogenesis (Greenaway et al., 2005). The cellular effects of the THBS are mediated by cell-surface receptors CD36 and integrin-associated protein (IAP, also known as CD47; Gao et al., 1996). The THBS are synthesized by several matrix-forming cells and incorporated into their extracellular matrix, supporting cell growth and proliferation controlling cell adhesion and growth (Dreyfus et al., 1992). Thus, the THBS may be important inhibitors of angiogenesis, primarily through their inhibition of proangiogenic genes such as vascular endothelial growth factor (VEGF; Lawler, 2002; Ribatti et al., 2007). Indeed, Greenaway et al. (2007) found that THBS1 knockout mice had a 3-fold increase in ovarian blood vessel density and an increased number of preantral and antral follicles, but with a reduced size compared with wild-type controls. Whether a reduction in THBS1 alters ovulation rate will require further study. The THBS1-bound VEGF is internalized to granulosa and endothelial cells for further catabolism of the complex via low density lipoprotein receptor-related protein-1 (Margosio et al., 2003; Greenaway et al. 2007). The VEGF is a potent mitogen and survival factor (Pauli et al., 2005; Ribatti et al., 2007), and thus, THBS1 downregulation could also account at least in part, for the increased cell survival and proliferation during follicular development. In the present study, IGF-I significantly downregulated THBS1 mRNA in cultured porcine granulosa cells by 42 to 51%, and this effect was evident in both microarray and one-step real-time RT-PCR analysis. Moreover, we found that FSH and estradiol had no effect on basal or IGF-I-inhibited THBS1 mRNA abundance in small follicle granulosa cells. Similarly, FSH had no effect on THBS1 mRNA abundance in cultured rat granulosa cells, whereas LH increased THBS1 mRNA abundance (Petrik et al., 2002). In contrast, FSH but not LH treatment in vitro increased THBS1 protein production by bovine granulosa cells (Greenaway et al., 2005), indicating species differences may exist in terms of the hormonal control of THBS1 production by granulosa cells. Because THBS1 and angiogenic factors are inversely related during follicular development (Greenaway et al., 2007), IGF-I-induced downregulation of THBS1 gene expression may contribute to vascular remodeling in growing follicles by factors such as VEGF (Martelli et al., 2006), whose proangiogenic actions are known to be regulated by THBS1 (Greenaway et al., 2007; Ribatti et al., 2007). The THBS1 also degrades matrix-associated FGF2 (Margosio et al., 2003). Thus, with an IGF-I-induced increase in FGFR2IIIc and decrease in THBS1, angiogenesis would be favored. In the ovary, THBS are found in the basement membrane separating granulosa cells from theca cells in developing ovarian follicles of mice (O'Shea and Dixit, 1988), and greater in small than medium and large bovine follicles (Greenaway et al., 2005). Recently, Thomas et al., (2008) found that THBS1 mRNA and protein in granulosa cells of tertiary follicles increased during atresia in marmosets. In the rat ovary, THBS1 is expressed in the early part of the ovarian cycle, whereas THBS2 is expressed in the late preovulatory, early luteal phase of the cycle (Petrik et al., 2002). In addition, Petrik et al. (2002) showed that in cultured granulosa cells from rats treated with diethylstilbestrol and induced to differentiate with FSH, 8-bromo-cAMP (8-Br-cAMP) or forskolin, THBS1 production and binding was drastically reduced compared with undifferentiated cells. Our studies are the first to indicate estradiol has no direct effect on THBS1 gene expression in granulosa cells. Consistent with the present results, estradiol had no effect on THBS1 mRNA abundance in cultured endometrial epithelial cells (Navarro et al., 2003). Because THBS1 and its receptor, IAP, have been localized to human granulosa and large luteal cells, but not to theca and small luteal cells, the interaction between ligand and receptor may contribute to autocrine control of follicular function (Higuchi et al., 1999). Collectively, the previous and present studies are consistent with the idea that hormonally induced vascularization in the early stages of follicular development occurs to optimize granulosa cell proliferation and follicular growth. Our study is first to show that this mechanism may be induced by IGF-I. In summary, differences in expression of 388 genes involved in several biological processes were observed in granulosa cells in response to IGF-I. These results provide the first comprehensive assessment of IGF-I-induced gene expression in granulosa cells and will lead to a better understanding of the molecular mechanisms of IGF-I regulation of follicular development. 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Receptor specificity of the fibroblast growth factor family: The complete mammalian FGF family. J. Biol. Chem.  281: 15694– 15700. Google Scholar CrossRef Search ADS PubMed  Footnotes 1 This work was supported in part by Universidad Autonoma de Chihuahua, Chihuahua, Mexico; Programa de Mejoramiento del Profesorado (PROMEP), the faculty development program of the Mexican Secretaria de Education Publica; and Consejo Nacional de Ciencia y Tecnologia (CONACYT); and the Oklahoma State University Agricultural Experiment Station. 2 Assistance provided by D. Allen, L. Hulsey, and D. Lagaly at Oklahoma State University is gratefully acknowledged. Eun-Soo Han at the University of Tulsa Microarray Core Facility for microarray assistance, Kim Brock at the Oklahoma State University Swine Farm for care of gilts, and the Oklahoma State University Recombinant DNA/Protein Core Facility for use of their equipment are also gratefully acknowledged. Approved for publication by the director, Oklahoma Agric. Exp. Sta. (project H-2510). Copyright 2009 Journal of Animal Science
TI - Microarray analysis of insulin-like growth factor-I-induced changes in messenger ribonucleic acid expression in cultured porcine granulosa cells: Possible role of insulin-like growth factor-I in angiogenesis,
JF - Journal of Animal Science
DO - 10.2527/jas.2008-1222
DA - 2009-06-01
UR - https://www.deepdyve.com/lp/oxford-university-press/microarray-analysis-of-insulin-like-growth-factor-i-induced-changes-in-si2aLhbs6l
SP - 1921
EP - 1933
VL - 87
IS - 6
DP - DeepDyve
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