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Single-cell Transcriptomes and Follicular Fluid Proteomics of Ovine Atretic Follicles Reveal the Underlying Mechanisms of Oocyte Degeneration

ABSTRACT: Background: In mammals, female fertility is determined by the outcome of follicular development (ovulation or atresia). Follicular atresia is a complex physiological process that results in the degeneration of oocytes from the ovary. However, the molecular mechanisms of oocyte degeneration and key protein markers of follicular atresia remain unclear. In this study, we explored the complex transcriptional regulatory mechanisms and protein profiles in oocytes and follicular fluid in atretic follicle stages using single-cell RNA sequencing and tandem mass tag proteomics. Results: First, through paired analysis of different follicle development stages, we identified 175 atresia-specific genes and eight candidate oocyte-secreted factors, including PKG1, YTHDF2, and MYC. Meanwhile, we also characterized unique features of the oocyte transcriptional landscape in the atretic follicle stage that displayed cell death-related transcriptional changes and mechanisms, such as autophagy (TBK1 and IRS4), necroptosis (PKR), and apoptosis (MARCKS). Moreover, we identified atresia-specific genes, namely FTH1, TF, and ACSL4, which may participate in regulation of oocyte ferroptosis in atretic follicles through a series of mechanisms including ferritinophagy, ferritin transport, and lipid metabolism. Additionally, we uncovered 333 differentially expressed proteins that may coordinate follicular atresia and revealed key pathways, such as negative regulation of angiogenesis, metabolic pathways, and transcription and mRNA splicing, that lead to oocyte degeneration. Finally, by combining transcriptome and proteomics analyses, we identified two oocyte-secreted biomarkers, PGK1 and ANGPT2, that may be associated with follicular atresia. Conclusions: In conclusion, our work provides a comprehensive characterization of oocyte degeneration in ovine atretic follicles, which provides a basis for establishing an oocyte quality evaluation system and understanding the mechanism of follicular atresia in sheep, as well as an important reference for in vitro production of embryos.

ORGANISM(S): Ovis aries

PROVIDER: GSE268651 | GEO | 2024/06/05

REPOSITORIES: GEO

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Project description:Folliculogenesis corresponds to the development of follicles leading to either ovulation or degeneration (a process called atresia). Even if atresia involves an apoptosis process, this mechanism is not well understood. The objective of this experiment was : 1) to analyse gene expression in pig granulosa cells of ovarian follicles during atresia using transcriptome analysis with a 9 024 cDNAs microarray, 2) the identification of gene networks involved in pig ovarian follicular atresia. Granulosa cells were isolated from atretic follicles (small, medium or large). Gene expression was analysed by hybridization of nylon cDNA microarrays. The images were quantified using Bzscan software and the data were managed with BASE software. Statistical analysis was performed using R software. Keywords: pig ovary, folliculogenesis, atresia, gene expression, cDNA microarray, bio-analysis Calibrated follicles were isolated from porcine ovaries after ovariectomy (24h ou 96h after the end of progestagen treatment: Regumate 18 days, 20 mg/days). The follicular status was determined by histological criteria using Feulgen coloration (Monget et al. 1993, Besnard et al. 1996). Healthy follicle is characterized by frequent mitosis and pyknosis absence in granulosa cells. Presence of frequent pyknotic bodies in granulosa cells and no mitosis were allocated to atretic cells. Two cross-classified biological factors of pig ovarian follicles are considered : 1) the stage of development of the follicular growth : small (1-2 mm of diameter), medium (3 mm) and large (>5 mm) follicles; 2) the follicular status: healthy (S1) vs beginning (A2) or advanced (A3) atresia. Gene expression was analysed by hybridization of nylon cDNA microarrays (GPL3729). After hybridisation the data analysis using BASE software and statistical analysis was performed to identify regulated genes. For each of three follicle class and three follicle status combination 4 biological replicates were considered. Total 36 membranes were first hybridized with a vector oligonucleotide labeled (T7 probe 5'-taatacgactcactataggga-3') with gamma33P ATP at 42Â°C during 12h to determine the quality of the spotting process. After being washed, the arrays were exposed 6 or 24 hours to radioisotopic-sensitive imaging plates (BAS-2025, Fujifilm, Raytest France S.A.R.L., Courbevoie, France). The imaging plates were scanned thereafter with a phosphor imaging system at a 25 ÃÂµm resolution (BAS-5000, Fujifilm, Raytest France S.A.R.L., Courbevoie, France). Data were acquired with help of a microarray image processing software - AGScan (Cathelin, 2006, http://mulcyber.toulouse.inra.fr/projects/agscan/). Fixed circle segmentation, i.e. a grid process with a fixed spot diameter was applied. The hybridization images were quantified by the extraction of the intensity for each spot. Arrays images and data were stored using BASE software (Saal LH, Troein C, Vallon-Christersson J, Gruvberger S, Borg A, and Peterson C. BioArray Software Environment (BASE): a platform for comprehensive management and analysis of microarray data. Genome Biol 3: SOFTWARE0003, 2002) adapted by Sigenae (http://www.sigenae.org) for analysis and storage of radioactitive microarray data

Project description:In mammals, ovarian folliculogenesis leading to the ovulation of completely mature oocytes is a long and complex process that is regulated at different levels. The mechanisms that underlie the selection of one or several dominant follicles as well as the regulation of the number of ovulating follicles are largely unknown. In this project, we proposed to study the genetic determinism that underlies the difference of ovulation rate between species (cattle and pigs), by studying two processes that exist in ovary: follicular development and follicular atresia. Towards this purpose, we made a comparative transcriptomics study on granulosa cells. Pig and cattle comparison was achieved by a transcriptome analysis with a 9K nylon pig microarray (GPL3729) on granulosa cells from either small healthy antral follicles (SHF), small atretic follicles (SAF) or large healthy antral follicles (LHF). The images were quantified using AGscan software and the data were managed with BASE software. Statistical analysis was performed using R software. Transcriptomic analysis on pig and cattle evidenced 997 differentially expressed genes (FDR1%) between the three follicle classes and/or the two species. This research project which implicated three laboratories from INRA: "Laboratoire de Genetique Cellulaire" (UMR444-LGC) , "Station d'Amelioration Genetique des Animaux" (UR 631-SAGA) and "Physiologie des Comportements et de la reproduction" (UMR 85-PRC) benefited from both European funding through SABRE project and French ANR funding through GenOvul project. Keywords: transcriptome analysis, pig, cattle, ovary, folliculogenesis, gene expression, cDNA microarray The data were obtained from 34 RNA samples: 10 small healthy follicles samples (6 for sows and 4 for cows), 13 small atretic follicles samples (7 for sows and 6 for cows) and 11 samples for large healthy follicles (6 for sows and 5 for cows). They were hybridized on a 9K pig nylon microarray (GPL3729).

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Single-cell Transcriptomes and Follicular Fluid Proteomics of Ovine Atretic Follicles Reveal the Underlying Mechanisms of Oocyte Degeneration

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