Transcriptome profiling of the theca interna in transition from small to large antral ovarian follicles

Abstract

The theca interna layer of the ovarian follicle forms during the antral stage of follicle development and lies adjacent to and directly outside the follicular basal lamina. It supplies androgens and communicates with the granulosa cells and the oocyte by extracellular signaling. To better understand developmental changes in the theca interna, we undertook transcriptome profiling of the theca interna from small (3-5 mm, n = 10) and large (9-12 mm, n = 5) healthy antral bovine follicles, representing a calculated >7-fold increase in the amount of thecal tissue. Principal Component Analysis and hierarchical classification of the signal intensity plots for the arrays showed no clustering of the theca interna samples into groups depending on follicle size or subcategories of small follicles. From the over 23,000 probe sets analysed, only 76 were differentially expressed between large and small healthy follicles. Some of the differentially expressed genes were associated with processes such as myoblast differentiation, protein ubiquitination, nitric oxide and transforming growth factor β signaling. The most significant pathway affected from our analyses was found to be Wnt signaling, which was suppressed in large follicles via down-regulation of WNT2B and up-regulation of the inhibitor FRZB. These changes in the transcriptional profile could have been due to changes in cellular function or alternatively since the theca interna is composed of a number of different cell types it could have been due to any systematic change in the volume density of any particular cell type. However, our study suggests that the transcriptional profile of the theca interna is relatively stable during antral follicle development unlike that of granulosa cells observed previously. Thus both the cellular composition and cellular behavior of the theca interna and its contribution to follicular development appear to be relatively constant throughout the follicle growth phase examined.

Figure 1. Unsupervised PCA of arrays for thecal cells from small and large healthy follicles.

The graph is a scatter plot of the values for the first (X) and second (Y) principal components based on the correlation matrix of the total normalized array intensity data. Abbreviations are thecal small healthy rounded (TSHR), thecal small healthy columnar (TSHC) and thecal large healthy (TLH).

Figure 2. Measurement of gene expression by qRT-PCR.

The data are shown as the mean ± SEM (n = 7 for small follicle group, n = 4 for large follicle group). qRT-PCR values were determined from the mean of the ratio of 2^−ΔCt of the target genes to cyclophilin A (PPIA) and glyceraldehyde phosphate dehydrogenase (GAPDH), and the microarray values are signal intensities (normalized but not log transformed). Significantly different results for qRT-PCR were determined by Student's t-test. The P values for the microarray results are corrected for multiple testing using the FDR (*P<0.05, **P<0.01 and ***P<0.001).

Figure 3. Top canonical pathways mapped in IPA (A) and GO terms (B) classified under biological process.

In (A) the bar chart on the left represents the percentage of genes from the data set that map to each canonical pathway showing those which are up regulated (in red) and down regulated (in blue) in theca of large with respect to small healthy follicles. The line chart on the right ranks these pathways derived for the same data set, from the highest to lowest degree of association based on the value of a right-tailed Fisher's exact t test. In (B) the bar chart on the left represents the percentage of genes from the data set that map to each GO term showing those which are differentially regulated (in blue) in theca of large with respect to small healthy follicles. The line chart on the right ranks these pathways derived for the same data set, from the highest to lowest degree of association using the Benjamini-Yuketeli test for multiple corrections (bottom to top in graphs on right).

Figure 4. The two most significant gene networks mapped in IPA.

The networks were generated in IPA using triangle connectivity based on focus genes (those present in our data set) and built up according to the number of interactions between a single prospective gene and others in the existing network, and the number of interactions the prospective genes have outside this network with other genes as determined by IPA . Network A (score = 39), shows interactions between LTBP1, LTBP2, COL14A1 and TNXBI indicating extracellular matrix signalling and network B (score = 28), shows involvement of Wnt pathway members WNT2B and FRZB. Interactions between molecules, and the degree and direction of regulation are indicated with up- (red) or down-regulation (green) and increasing color intensity with degree of fold change.