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REPRODUCTIONRESEARCH Changes in granulosa cells’ gene expression associated with increased oocyte competence in bovine Anne-Laure Nivet, Christian Vigneault1, Patrick Blondin1 and Marc-Andre´ Sirard De´partement des sciences animales, Pavillon INAF, Faculte´ des sciences de l’agriculture et de l’alimentation, Centre de recherche en biologie de la reproduction, Universite´ Laval, Quebec, Quebec, Canada G1V 0A6 and 1L’Alliance Boviteq, Saint-Hyacinthe, Quebec, Canada Correspondence should be addressed to M-A Sirard; Email: [email protected] Abstract One of the challenges in mammalian reproduction is to understand the basic physiology of oocyte quality. It is believed that the follicle status is linked to developmental competence of the enclosed oocyte. To explore the link between follicles and competence in cows, previous research at our laboratory has developed an ovarian stimulation protocol that increases and then decreases oocyte quality according to the timing of oocyte recovery post-FSH withdrawal (coasting). Using this protocol, we have obtained the granulosa cells associated with oocytes of different qualities at selected times of coasting. Transcriptome analysis was done with Embryogene microarray slides and validation was performed by real-time PCR. Results show that the major changes in gene expression occurred from 20 to 44 h of coasting, when oocyte quality increases. Secondly, among upregulated genes (20–44 h), 25% were extracellular molecules, highlighting potential granulosa signaling cascades. Principal component analysis identified two patterns: one resembling the competence profile and another associated with follicle growth and atresia. Additionally, three major functional changes were identified: i) the end of follicle growth (BMPR1B, IGF2, and RELN), involving interactions with the extracellular matrix (TFPI2); angiogenesis (NRP1), including early hypoxia, and potentially oxidative stress (GFPT2, TF, and VNN1) and ii) apoptosis (KCNJ8) followed by iii) inflammation (ANKRD1). This unique window of analysis indicates a progressive hypoxia during coasting mixed with an increase in apoptosis and inflammation. Potential signaling pathways leading to competence have been identified and will require downstream testing. This preliminary analysis supports the potential role of the follicular differentiation in oocyte quality both during competence increase and decrease phases. Reproduction (2013) 145 555–565 Introduction granulosa/follicular gene expression may be associated with developmental competence of the enclosed oocyte The understanding of the variability of oocyte quality is in bovines (Robert et al. 2001), rats (Jiang et al. 2010), particularly important in large mono-ovulating species and humans (Assidi et al. 2008, 2010, Hamel et al. 2008, such as cows, horses, and humans. There is a general 2010). In our previous experiment, it was observed consensus that oocyte quality is best during a natural that an improved developmental rate was obtained cycle, although several good-quality oocytes can some- with a hormonal treatment consisting of 3 days of times be obtained during stimulated treatments. The bovine species coupled with an efficient in vitro stimulation using FSH plus a coasting period of 44 h maturation–IVF system offer a good research tool to (Blondin et al. 2002). address the effects of follicular growth and dynamics on More recently, it was shown that the best period for oocyte quality. Indeed, it is ethically possible to ovum pick up (OPU) ranges from 44 to 68 h after the last hormonally manipulate the different parameters of FSH injection and is associated with an average blastocyst follicular maturation and then assess the related quality rate of 70% in cows, with some 33% of animals reaching of the oocytes obtained using the same females 100% (Nivet et al. 2011; Supplementary Table 1). In the repeatedly and the same bull. above experiment, early (20 h) and late (92 h) recovery In cattle, the follicle status has a significant effect on time illustrates that the competence window is maximal oocyte quality, and through several protocols, it has been between two states of lower competence. Based on this demonstrated that hormonal pretreatment of ovaries phenotypic observation, the current experiment was with gonadotropins can improve oocyte quality in a designed to analyze the granulosa cell transcriptome time-regulated manner (Blondin et al. 1996, 1997, in relation to the three periods of competence: early, 2002). In parallel, we and others have observed that optimal, and late recovery. q 2013 Society for Reproduction and Fertility DOI: 10.1530/REP-13-0032 ISSN 1470–1626 (paper) 1741–7899 (online) Online version via www.reproduction-online.org Downloaded from Bioscientifica.com at 09/26/2021 05:13:04AM via free access 556 A-L Nivet and others Results Real-time PCR Microarray analysis and principal component analysis Confirmation of the microarray data analysis was performed by real-time PCR with 11 different transcripts Principal component analysis (PCA) was performed selected according to their significant changes during based on intensity data (log2) at each treatment (20, 44, the coasting period, their profiles, and known function 68, and 92 h). In this PCA, genes are considered as in or out of the ovary. Genes were also selected for variables and coasting periods as samples. Considering being potential biomarkers of the competence period. the log2 (signal intensity) for each gene symbol, three The chosen candidate genes were transferrin (TF), new variables, called principal components, were insulin-like growth factor 2 (IGF2), reelin (RELN), identified (linearly, Supplementary Figure 1A, and 3D potassium inwardly rectifying channel, subfamily J, view, Supplementary Figure 1B, see section on supple- member 8 (KCNJ8), tissue factor pathway inhibitor 2 mentary data given at the end of this article). These new (TFPI2), bone morphogenetic protein receptor, type IB variables were not correlated and permitted the (BMP1RB), neuropilin 1 (NRP1), ankyrin repeat domain definition of several general patterns significant for global 1(ANKRD1), annexin A1 (ANXA1), glutamine-fructose- changes in gene expression. One clear observation is that 6-phosphate transaminase 2 (GFPT2), and vanin 1 two patterns resembled the blastocyst or development (VNN1). Real-time PCR results confirmed the fluctuation pattern while the third one was not related to compe- profiles observed in microarray data analysis, although tence, thereby allowing interesting groupings of related some changes were not significant for the four different genes. time points (Fig. 2A and B). Functions associated with these potential markers were identified and are sum- Microarray-positive probes and fold change analysis marized in Fig. 3. Using data with a significant ANOVA P value !0.05, a fold change of 1.5, and a false discovery rate of 0.1, there DAVID functional annotation and ingenuity pathway were 820 probes showing differential expression from 20 analysis to 44 h (2.6% of the potential positive probes) (Fig. 1). Data upload into the ingenuity pathway analysis (IPA) Among them, 508 probes were over-expressed and 312 program permitted the identification of extracellular were under-expressed. This represented the biggest molecules upregulated at 44 h compared with 20 h, i.e. change in 24 h during the experiment, as there were during the period of increasing competence. Some of 509 and 498 probes for 44–68 and 68–92 h respectively. them have known receptors that are reported to be This indicates that granulosa cells are significantly expressed in the ovary (Table 1). affected by the coasting regimen and that most changes IPA also allows the identification of predicted occur within the first 2 days of FSH withdrawal. Between activated transcription factors. We have performed 44 and 68 h of coasting, as well as between 68 and this analysis with the differentially expressed genes for 92 h, the proportion of probes associated with transcripts the following contrasts: 20–44, 44–68, and 68–92 h differentially expressed (fold change O1.5 and false (Supplementary Figure 2, see section on supplementary discovery rate !0.1) decreased to 1.6%. data given at the end of this article). Using information 100.0 from the literature (Sirotkin 2011), we could assign ovarian function for some of those genes. The functions 99.5 associated with each contrast (20–44, 44–68, and 68–92 h) are cell death, cellular movement, cellular 99.0 growth and proliferation, cell-to-cell signaling, and 98.5 interaction (Supplementary Figure 2). For each contrast (20–44, 44–68, and 68–92 h), gene 98.0 symbols associated with fold changes (FC) O1.5 or !K1.5 (P!0.05 and false discovery rate (FDR) !0.1) 97.5 were uploaded to the Database for Annotation, Visual- 97.0 ization and Integrated Discovery (DAVID) functional Proportion of probes (%) annotation tool. For the 20–44, 44–68 and 68–92 h 96.5 contrasts, seven groups of functions were similar. These global groups are inflammation (relative DAVID scores 20–44 h 44–68 h 68–92 h (significant when O1.3) from 7.9 to 9.9), angiogenesis (5.6–7.7), Smad/transforming growth factor 1 (SMAD/ Figure 1 Proportion of probes differentially expressed over time. White bars: probes associated with transcripts not differentially expressed; TGFB1) signaling (1.7–4.7), cell death/apoptosis gray bars: probes associated with positive fold changes; black bars: (2.4–3.9), coagulation (3.5–5.7), cell movement probes associated with negative fold changes. (2–3.3),