G proteins and autocrine signaling differentially regulate gonadotropin subunit expression in pituitary gonadotrope.

Gonadotropin-releasing hormone (GnRH) acts at gonadotropes to direct the synthesis of the gonadotropins, follicle-stimulating hormone (FSH), and luteinizing hormone (LH). The frequency of GnRH pulses determines the pattern of gonadotropin synthesis. Several hypotheses for how the gonadotrope decodes GnRH frequency to regulate gonadotropin subunit genes differentially have been proposed. However, key regulators and underlying mechanisms remain uncertain. We investigated the role of individual G proteins by perturbations using siRNA or bacterial toxins. In LßT2 gonadotrope cells, FSHß gene induction depended predominantly on Gα(q/11), whereas LHß expression depended on Gα(s). Specifically reducing Gα(s) signaling also disinhibited FSHß expression, suggesting the presence of a Gα(s)-dependent signal that suppressed FSH biosynthesis. The presence of secreted factors influencing FSHß expression levels was tested by studying the effects of conditioned media from Gα(s) knockdown and cholera toxin-treated cells on FSHß expression. These studies and related Transwell culture experiments implicate Gα(s)-dependent secreted factors in regulating both FSHß and LHß gene expression. siRNA studies identify inhibinα as a Gα(s)-dependent GnRH-induced autocrine regulatory factor that contributes to feedback suppression of FSHß expression. These results uncover differential regulation of the gonadotropin genes by Gα(q/11) and by Gα(s) and implicate autocrine and gonadotrope-gonadotrope paracrine regulatory loops in the differential induction of gonadotropin genes.

Coupling of GnRH concentration and the GnRH receptor-activated gene program.

The initial waves of gene induction caused by GnRH in the LbetaT2 gonadotrope cell line have recently been identified using microarrays. We now investigate the relationship of the concentration of GnRH to the level of biosynthesis induced. Using an optimized custom cDNA microarray, we show that a large number of genes are induced in a concentration-dependent fashion. Detailed time course studies of the induction of six induced transcripts using quantitative real-time PCR suggest that the amplitude, but not the temporal pattern, depends on the concentration of GnRH. The early genes appear to show a delay in gene induction, followed by a linear phase of increase. The relationship of rate of synthesis and GnRH concentration was studied by mathematical modeling of the induction of two genes, gly96 and tis11. In both cases, only the rates of increase, but not the lag times, are influenced by the concentration of GnRH exposure. Western blot analyses for c-Jun and Egr1 show that the levels of nuclear protein for these transcription factors also depend on the concentration of GnRH. These studies indicate that, despite the complex signaling network connecting the receptor to the activated genes, the biosynthetic rate of RNA polymerase at induced genes is correlated with the concentration of GnRH at the GnRH receptor.

Accuracy and calibration of commercial oligonucleotide and custom cDNA microarrays.

We compared the accuracy of microarray measurements obtained with oligonucleotide arrays (GeneChip, Affymetrix) with a laboratory-developed cDNA array by assaying test RNA samples from an experiment using a paradigm known to regulate many genes measured on both arrays. We selected 47 genes represented on both arrays, including both known regulated and unregulated transcripts, and established reference relative expression measurements for these genes in the test RNA samples using quantitative reverse transcriptase real-time PCR (QRTPCR) assays. The validity of the reproducible (average coefficient of variation = 11.8%) QRTPCR measurements were established through application of a new mathematical model. The performance of both array platforms in identifying regulated and non-regulated genes was identical. With either platform, 16 of 17 definitely regulated genes were correctly identified, and no definitely unregulated transcript was falsely identified as regulated. Accuracy of the fold-change measurements obtained with each platform was assessed by determining measurement bias. Both platforms consistently underestimate the relative changes in mRNA expression between experimental and control samples. The bias observed with cDNA arrays was predictable for fold-changes <250-fold by QRTPCR and could be corrected by the calibration function F(c) = F(a(cDNA))(q), where F(a(cDNA)) is the microarray-determined fold-change comparing experimental with control samples, q is the correction factor and F(c) is the calibrated value. The bias observed with the commercial oligonucleotide arrays was less predictable and calibration was unfeasible. Following calibration, fold-change measurements generated by custom cDNA arrays were more accurate than those obtained by commercial oligonucleotide arrays. Our study demonstrates systematic bias of microarray measurements and identifies a calibration function that improves the accuracy of cDNA array data.