Infertility is a reproductive health problem that attracts worldwide attention. Polycystic ovary syndrome (PCOS) is a major cause of female infertility and patients with obesity and PCOS are particularly common in clinical practice. Long non-coding RNA (lncRNAs) are a functional core in cells that regulate gene expression, transcription, and chromatin modification processes, and participate in epigenetics, cell cycle, and cell differentiation. LncRNAs are assumed to play a role in the occurrence and development of PCOS; however, their specific mechanism of action remains to be elucidated. High-throughput sequencing technology has been used to sequence and analyze lncRNAs in exosomes from the follicular fluid of patients with obesity and PCOS and those who underwent assisted reproductive therapy owing to male factors. Specific expression profiles of patients with obesity and PCOS were obtained and functional information analysis combined with a literature review were performed to screen for differentially expressed lncRNAs, which were validated using real-time reverse transcription quantitative polymerase chain reaction (RT-qPCR). High-throughput sequencing analysis revealed that compared to normal patients with male infertility, patients with obesity and PCOS had a total of 20 lncRNAs with significant expression differences in follicular fluid exosomes. Among them, 17 lncRNAs were upregulated and three were downregulated. Functional analysis showed that differentially expressed genes were mainly enriched in "cell metabolism," "cell adhesion," and other aspects: related gene pathways mainly involved Huntington's disease, Parkinson's disease, spliceosomes, non-alcoholic fatty liver disease, and ribosomes. Verification of differentially expressed lncRNAs revealed that the expression of lncRNAs TPT1-AS1, PTOV1-AS1, PTPRG-AS1, and SNHG14 in follicular fluid exosomes was consistent with the sequencing results. A preliminary differential expression profile of lncRNAs in exosomes of patients with obesity and PCOS was established by transcriptomic analysis of these individuals. Our bioinformatics analysis results may be applicable to further study of the impact mechanism involving obesity and PCOS. These differentially expressed lncRNAs maybe served as potential biomarkers for in-depth studies of the occurrence, development on Follicle quality and function for patients with PCOS in the future.
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