Abstract

Objective To construct the expression profiles of microRNA (miRNA) and mRNA in ovarian granulosa cells in patients with polycystic ovary syndrome (PCOS) in search of the molecular markers of PCOS. Methods A standard length scheme was used to collect ovarian granulosa cells of PCOS patients (PCOS group) and normal ovulating women (control group) who received in vitro fertilization/intracytoplasmic sperm injection (IVF/ICSI) in the Reproductive Medicine Center of the Affiliated Hospital of Inner Mongolia Medical University from 2017 to 2018, integrate high-throughput mRNA and miRNA expression profiles, and the biological processes involved in differential expression genes were analyzed through Gene Ontogy's functional enrichment and KEGG Pathway. At the same time, the core regulatory network during the pathogenesis of PCOS was constructed by using the relationship between miRNA target regulatory genes, and PCOS-related mRNAs and miRNAs were predicted. Results Compared with control group, 66 miRNAs with differential expression were screened in POCS group, among which 42 miRNAs were up-regulated and 24 miRNAs were down-regulated. Totally 416 differentially expressed genes were screened by transcription profiling, among which 236 genes were up-regulated and 180 genes were down-regulated (P<0.05, |log2FC|≥2). Highly significantly differentially expressed miRNAs (miRNA-26b, miRNA-423-3p, miRNA-219a, miRNA-326, miRNA-3928-3p and miRNA-194-5p) were associated with 107 differentially targeted genes by joint analysis, with significant differences (P<0.01). These target genes involve many functions such as ion transport, cell adhesion and inflammatory reactions, and multiple signal pathways such as mitogen-activated protein kinase (MAPK), Wnt and phosphateidy-linositol-3-kinase/serine-threonine kinase (PI3K-Akt). Conclusion The expression of miRNA and its regulatory target genes in ovarian granulosa cells in patients with PCOS are closely related to their pathophysiological processes. Key words: Polycystic ovary syndrome; High-throughput sequencing; Ovarian granulosa cells; mRNA; MicroRNAs

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