CCAAT/Enhancer-Binding Proteins α and β Regulate Ovulation and Gene Expression via Dose- and Stage-Dependent Mechanisms

Abstract

The preovulatory luteinizing hormone (LH) surge orchestrates complex cellular and molecular events leading to ovulation. CCAAT/enhancer-binding proteins α and β (C/EBPα/β) are transcription factors acutely induced by the LH surge and crucial for ovulation and granulosa cell luteinization. However, biological processes (BPs) and their regulatory mechanisms downstream of C/EBPα/β in the preovulatory ovary are not completely understood. To address this knowledge gap, we generated Cebpa/bfl/fl;Pgr-Cre mutants and compared them with Cebpa/bfl/fl;Cyp19a1-Cre mutant female mice: Cebpa/bfl/fl;Cyp19a1-Cre mutants have undetectable levels of C/EBPα/β throughout the preovulatory stages and do not ovulate, aligning with previous reports; and Cebpa/bfl/fl;Pgr-Cre mutants present gradual depletion of C/EBPα/β during the late preovulatory stage and a reduced ovulation rate. Comparison of these two models indicates that sustained expression of C/EBPα/β throughout the preovulatory stages is necessary for successful ovulation and provides a unique opportunity to interrogate gene regulatory mechanisms by C/EBPα/β during different preovulatory time windows and the effect of dysregulating C/EBPα/β on ovulation-associated BPs. Our study revealed that C/EBPα/β regulate gene expression and distinct biological functions such as vascular remodeling via dose- and preovulatory stage-dependent mechanisms. These findings shed new light on the intricate mechanisms of gene regulation by C/EBPα/β downstream of the LH surge.

Keywords: C/EBPα; C/EBPβ; gene expression; ovulation; transcription factor; vascular remodeling.

Figure 1.

Conditional depletion of Cebpa/b at different stages of follicle growth by Cyp19a1-Cre vs Pgr-Cre led to different ovulation outcomes. A, Schematic diagram of follicle development and the generation of Cebp-C and Cebp-P mutants. The timing of expression for each Cre recombinase is indicated in the diagram. B, Breeding assay of WT, Cebp-C, and Cebp-P mutants (n = 4). C, Superovulation studies of WT, Cebp-C, and Cebp-P mutants (n = 8-9). D, Hematoxylin-eosin staining shows the ovarian histology of WT, Cebp-C, and Cebp-P mutants at 24 hours post hCG. Scale bar = 200 μm. CL, corpus luteum; F, follicle. E, RT-qPCR shows the mRNA levels of Cebpa and Cebpb in GCs collected from WT, Cebp-C, and Cebp-P mutants before and after hCG treatment (n = 5). F, Western blot shows C/EBPβ levels in GCs collected from WT, Cebp-C, and Cebp-P mutants after hCG treatment (n = 5). Quantitative data in this figure are presented as mean ± SD. B and C, One-way ANOVA and E and F, 2-way ANOVA with Tukey multiple comparisons test were used for statistical analysis. Bars without common superscripts are statistically different (P < .05).

Figure 2.

The expression levels of Cebpa/b in individual preovulatory follicles are correlated with ovulation outcome. A, RT-qPCR shows the mRNA levels of selected genes in GCs and CL collected from WT, Cebp-C, or Cebp-P mutants at 24 hours post hCG (n = 5). B, Immunofluorescence staining of C/EBPβ in mouse ovaries of WT, Cebp-C, and Cebp-P mutants at 8 hours post hCG (n = 3-4). Scale bar = 200 μm. C, RT-qPCR shows the mRNA levels of Cebpa and Cebpb in individual follicles collected from WT and Cebp-P mutants at 8 to 9 hours post hCG (n = 3). Dots in the same column are from the same ovary. D, Coefficient of variation analysis in C. Quantitative data in this figure are presented as mean ± SD. One-way ANOVA with Tukey multiple comparisons test was used for statistical analysis in A and C (left and middle panel). Multiple two-tailed unpaired t test was used for statistical analysis in C and D. Arcsine square root-transformed data in D were used to meet the assumptions of the t test. Bars without common superscripts are statistically different (P < .05). ***P < .001.

Figure 3.

C/EBPα/β regulate biological processes critical to ovulation via dose- and preovulatory stage–dependent mechanisms. A, Volcano plots show the DEGs in GCs from Cebp-C (left panel) and Cebp-P (right panel) mutants to WT at 8 hours post hCG (n = 3) (DEGs: log2 fold change >1; P < .05). B, Venn diagram shows the overlap between DGEs of Cebp-C and Cebp-P mutants in A. C, Heat maps show K-means clustering of all DEGs in B. The colors in the map represent robust Z Score–normalized values for DEGs: Blue indicates the lowest expression, white indicates intermediate expression, and red indicates the highest expression. The genes of each cluster were subjected to a biological process GO enrichment analysis, and the top enriched GO terms for each cluster are shown. D, Volcano plots show the DEGs in GCs from Cebp-C (left panel) and Cebp-P (right panel) mutants to WT at 12 hours post hCG (n = 3). E, Venn diagram shows the relationship between DGEs of Cebp-C and Cebp-P mutants in D. F, Heat maps show K-means clustering of all DEGs in E. The genes of each cluster were subjected to a biological process GO enrichment analysis, and the top enriched GO terms for each cluster are shown.

Figure 4.

C/EBPα/β regulate ovulation gene expression by dose- and preovulatory stage–dependent mechanisms. A, RT-qPCR shows the mRNA expression levels of selected ovulation-related genes in granulosa cells collected from WT, Cebp-C, and Cebp-P mutants before and after hCG treatment (n = 5). B, RT-qPCR shows the mRNA levels of selected genes in individual follicles collected from WT and Cebp-P mutants at 8 to 9 hours post hCG (n = 3). Quantitative data in this figure are presented as mean ± SD. Two-way ANOVA with Tukey multiple comparisons test was used for statistical analysis in A. Bars without common superscripts are statistically different (P < .05). Pearson correlation coefficient was used for correlation analysis in B. r and P values are indicated in the figure.

Figure 5.

C/EBPα/β regulate ovarian vascular remodeling during the preovulatory period. A, Representative whole-mount 3-D projection images of cleared ovaries with blood vessels labeled by lectin conjugated with Alexa 649 (white) from WT and Cebp-P mutants at 12 hours post hCG (n = 3). Colored asterisk: representative preovulatory follicles outlined by the same color. Red arrowhead: abnormal large blood vessels in ovaries of Cebp-P mutants that are not observed in WT. Capillary clearing is labeled by a red circle. Scale bar = 250 μm. B, RT-qPCR shows the mRNA expression levels of selected vascular remodeling-related genes in granulosa cells collected from WT, Cebp-C, and Cebp-P mutants before and after hCG treatment (n = 5). Quantitative data in this figure are presented as mean ± SD. Two-way ANOVA with Tukey multiple comparisons test was used for statistical analysis in B. Bars without common superscripts are statistically different (P < .05).

Figure 6.

C/EBPα/β mediate gene regulation in granulosa cells via diverse mechanism during the preovulatory period. A, Pan-cistromics analysis shows the proportion of differentially expressed genes in Fig. 3A that contain binding sites for C/EBPα or C/EBPβ within the EPR (TSS-7.5 kb, TSS + 2.5 kb) based on ChIP-seq data from various tissue types. B, UMAPs show the clustering and identification of 14 different cell clusters based on chromatin accessibility from snATAC-seq of ovaries from WT, Cebp-C, and Cebp-P mutants at 8 hours post hCG. Upper left: combined clustering of all genotypes; upper right: WT; lower left: Cebp-C; lower right: Cebp-P (WT: n = 2; Cebp-C: n = 3; Cebp-P: n = 3). C to E, UMAP visualization colored by log2-normalized gene scores, demonstrating the cell cluster-specific chromatin accessibility (top panels) and genome tracks (lower panels) for C, Apln; D, Vegfa; and E, Ptgs2 in cell clusters 1 to 4 in as B. Gene scores are calculated as log2(norm counts + 1).