Dataset Information

Identification of Biomarkers for Predicting Ovarian Reserve of Primordial Follicle via Transcriptomic Analysis.

ABSTRACT: Ovarian reserve (OR) is mainly determined by the number of primordial follicles in the ovary and continuously depleted until ovarian senescence. With the development of assisted reproductive technology such as ovarian tissue cryopreservation and autotransplantation, growing demand has arisen for objective assessment of OR at the histological level. However, no specific biomarkers of OR can be used effectively in clinic nowadays. Herein, bulk RNA-seq datasets of the murine ovary with the biological ovarian age (BOA) dynamic changes and single-cell RNA-seq datasets of follicles at different stages of folliculogenesis were obtained from the GEO database to identify gene signature correlated to the primordial follicle pool. The correlations between gene signature expression and OR were also validated in several comparative OR models. The results showed that genes including Lhx8, Nobox, Sohlh1, Tbpl2, Stk31, and Padi6 were highly correlated to the OR of the primordial follicle pool, suggesting that these genes might be used as biomarkers for predicting OR at the histological level.

SUBMITTER: Liu L

PROVIDER: S-EPMC9174591 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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Identification of Biomarkers for Predicting Ovarian Reserve of Primordial Follicle <i>via</i> Transcriptomic Analysis.

Liu Li L Liu Biting B Li Ke K Wang Chunyan C Xie Yan Y Luo Ning N Wang Lian L Sun Yaoqi Y Huang Wei W Cheng Zhongping Z Liu Shupeng S

Frontiers in genetics 20220525

Ovarian reserve (OR) is mainly determined by the number of primordial follicles in the ovary and continuously depleted until ovarian senescence. With the development of assisted reproductive technology such as ovarian tissue cryopreservation and autotransplantation, growing demand has arisen for objective assessment of OR at the histological level. However, no specific biomarkers of OR can be used effectively in clinic nowadays. Herein, bulk RNA-seq datasets of the murine ovary with the biologic ...[more]

PMID: 35692832

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Project description:Ovarian primordial follicles are critical for female reproduction and comprise a finite pool of gametes arrested in development. A systems biology approach was used to identify regulatory gene networks essential for primordial follicle development. Transcriptional responses to eight different growth factors known to influence primordial follicles were used to construct a bionetwork of regulatory genes involved in primordial follicle development. Over 1500 genes were found to be regulated by the various growth factors and a network analysis identified critical gene modules involved in a number of signaling pathways and cellular processes. A set of 55 genes was identified as potential critical regulators of these gene modules, and a subnetwork associated with development was determined. Within the network two previously identified regulatory genes were confirmed (i.e. Pdgfa and Fgfr2) and a new factor was identified, connective tissue growth factor (CTGF). CTGF was tested in ovarian organ cultures and found to stimulate primordial follicle development. Therefore, the relevant gene network associated with primordial follicle development was validated and the critical genes and pathways involved in this process were identified. This is one of the first applications of network analysis to a normal developmental process. These observations provide insights into potential therapeutic targets for preventing ovarian disease and promoting female reproduction. For GSM509254-9: We used microarrays to determine genes expressed differentially between control and CTGF (connective tissue growth factor) treated P4 ovary. For GSM510028-65: We used microarrays to determine genes expressed differentially between control and growth factors treated P4 ovary and co-expressed in the same manner for P4 ovaries treated with 8 growth factors AMH, BMP4, GDNF, FGF2, FGF7, KITLG, LIF, PDGFab. For GSM509254-9: RNA samples from 3 control groups are compared to 3 CTGF treated ovary groups. For GSM510028-65: RNA samples from 14 control samples are compared to 3 growth factor treated ovary samples for each AMH, BMP4, GDNF, FGF2, FGF7, KITLG, LIF, PDGFab treatment.

Project description:Although many proteins have been shown to affect the transition of primordial follicles to the primary stage, factors regulating the formation of primordial follicles remains sketchy at best. Differentiation of somatic cells into early granulosa cells during ovarian morphogenesis is the hallmark of primordial follicle formation; hence, critical changes are expected in protein expression. We wanted to identify proteins, the expression of which would correlate with the formation of primordial follicles as a first step to determine their biological function in folliculogenesis. Proteins were extracted from embryonic (E15) and 8-day-old (P8) hamster ovaries and fractionated by two-dimensional gel electrophoresis. Gels were stained with Proteosilver, and images of protein profiles corresponding to E15 and P8 ovaries were overlayed to identify protein spots showing altered expression. Some of the protein spots were extracted from SyproRuby-stained preparative gels, digested with trypsin, and analyzed by mass spectrometry. Both E15 and P8 ovaries had high molecular weight proteins at acidic, basic, and neutral ranges; however, we focused on small molecular weight proteins at 4-7 pH range. Many of those spots might represent post-translational modification. Mass spectrometric analysis revealed the identity of these proteins. The formation of primordial follicles on P8 correlated with many differentially and newly expressed proteins. Whereas Ebp1 expression was downregulated in ovarian somatic cells, Sfrs3 expression was specifically upregulated in newly formed granulosa cells of primordial follicles on P8. The results show for the first time that the morphogenesis of primordial follicles in the hamster coincides with altered and novel expression of proteins involved in cell proliferation, transcriptional regulation, and metabolism. Therefore, formation of primordial follicles is an active process requiring differentiation of somatic cells into early granulosa cells and their interaction with the oocytes.

Dataset Information

Identification of Biomarkers for Predicting Ovarian Reserve of Primordial Follicle via Transcriptomic Analysis.

Publications

Identification of Biomarkers for Predicting Ovarian Reserve of Primordial Follicle <i>via</i> Transcriptomic Analysis.

Similar Datasets

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