Dynamic changes in gene expression that occur during the period of spontaneous functional regression in the rhesus macaque corpus luteum

Abstract

Luteolysis of the corpus luteum (CL) during nonfertile cycles involves a cessation of progesterone (P4) synthesis (functional regression) and subsequent structural remodeling. The molecular processes responsible for initiation of luteal regression in the primate CL are poorly defined. Therefore, a genomic approach was used to systematically identify differentially expressed genes in the rhesus macaque CL during spontaneous luteolysis. CL were collected before [d 10-11 after LH surge, mid-late (ML) stage] or during (d 14-16, late stage) functional regression. Based on P4 levels, late-stage CL were subdivided into functional-late (serum P4 > 1.5 ng/ml) and functionally regressed late (FRL) (serum P4 < 0.5 ng/ml) groups (n = 4 CL per group). Total RNA was isolated, labeled, and hybridized to Affymetrix genome microarrays that contain elements representing the entire rhesus macaque transcriptome. With the ML stage serving as the baseline, there were 681 differentially expressed transcripts (>2-fold change; P < 0.05) that could be categorized into three primary patterns of expression: 1) increasing from ML through FRL; 2) decreasing from ML through FRL; and 3) increasing ML to functional late, followed by a decrease in FRL. Ontology analysis revealed potential mechanisms and pathways associated with functional and/or structural regression of the macaque CL. Quantitative real-time PCR was used to validate microarray expression patterns of 13 genes with the results being consistent between the two methodologies. Protein levels were found to parallel mRNA profiles in four of five differentially expressed genes analyzed by Western blot. Thus, this database will facilitate the identification of mechanisms involved in primate luteal regression.

Figure 1

Three general patterns of expression among differentially expressed genes. The 681 differentially expressed transcripts from the mid-late (ML) through functionally regressed late (FRL) stages were divided based on general expression patterns as depicted in these three heat maps. Group 1 includes transcripts that underwent an incremental increase in expression from the mid-late through functionally regressed late stages (382 transcripts). Group 2 includes transcripts that decreased in expression from the mid-late through functionally regressed late stages (218 transcripts). Group 3 includes transcripts that increased from the mid-late to functional late (FL) stages, then decreased in expression by the functionally regressed late stage (81 transcripts). Max, Maximum; Min, minimum.

Figure 2

Steroidogenic gene expression throughout the period of functional regression in the rhesus macaque CL. A, Genes involved in steroidogenesis are displayed in the heat map. Bold lettering indicates that mRNA for the corresponding gene met the criteria for differential expression (>2-fold change; ANOVA, P < 0.05). B, Q-PCR validation of microarray results for LHCGR, STAR, HSD3B2, and CYP19A1. Data were analyzed by ANOVA followed by comparison between groups using the Student-Newman-Keuls test. Uppercase letters denote significant differences (P < 0.05) for microarray data, and lowercase letters denote significant differences for Q-PCR data. FL, Functional late; FRL, functionally regressed late; Max, maximum; Min, minimum; ML, mid-late.

Figure 3

Divergent expression of cholesterol uptake, transport, and efflux genes. A, Genes involved in cholesterol uptake, transport, or efflux are displayed in the heat map. Bold lettering indicates that mRNA for the corresponding gene met the criteria for differential expression (>2-fold change; ANOVA, P < 0.05). B, Q-PCR validation of microarray results for LDLR, SCARB1, APOL2, APOL4, ABCA1, and ABCG1. Data were analyzed by ANOVA followed by comparison between groups using the Student-Newman-Keuls test. Uppercase letters denote significant differences (P < 0.05) for microarray data, and lowercase letters denote significant differences for Q-PCR data. FL, Functional late; FRL, functionally regressed late; Max, maximum; Min, minimum; ML, mid-late.

Figure 4

Q-PCR validation of microarray expression data for differentially expressed prostaglandin synthesis, metabolism, and signaling genes. Quantification of mRNA levels for HPGD (top panel), PTGES (middle panel), and PTGFR (bottom panel) by microarray and Q-PCR methodologies. Data were analyzed by ANOVA followed by comparison between groups using the Student-Newman-Keuls test. Uppercase letters denote significant differences (P < 0.05) for microarray data, and lowercase letters denote significant differences for Q-PCR data.

Figure 5

Differential expression of steroidogenic proteins. A, Western blots using samples pooled from CL collected at each stage. The bottom image is TUBB, which served as a loading control. In the HSD3B2 image, only the lower band of the doublet corresponds to HSD3B2 as determined previously (23). B, Levels of STAR, HSD3B2, and CYP19A1 from individual CL (n = 4 per stage) were normalized to TUBB, and the resultant ratio was analyzed by ANOVA followed by comparison between groups using the Student-Newman-Keuls test. Columns with different letters are significantly different (P < 0.05). FL, Functional late; FRL, functionally regressed late; ML, mid-late.

Figure 6

Differential expression of proteins involved in prostaglandin E2 synthesis and metabolism. A, Western blots using samples pooled from CL collected at each stage. The bottom image is TUBB, which served as a loading control. B, Levels of HPGD and PTGES from individual CL (n = 4 per stage) were normalized to TUBB, and the resultant ratio was analyzed by ANOVA followed by comparison between groups using the Student-Newman-Keuls test. Columns with different letters are significantly different (P < 0.05). FL, Functional late; FRL, functionally regressed late; ML, mid-late.