MiRNAs expression profiling of rat ovaries displaying PCOS with insulin resistance - PubMed (original) (raw)

MiRNAs expression profiling of rat ovaries displaying PCOS with insulin resistance

Chunren Zhang et al. Arch Gynecol Obstet. 2020 Nov.

Abstract

Purpose: The present study established microRNA (miRNA) expression profiles for rat ovaries displaying polycystic ovary syndrome (PCOS) with insulin resistance and explored the underlying biological functions of differentially expressed miRNAs.

Methods: A PCOS with insulin resistance rat model was created by administering letrozole and a high-fat diet. Total RNA was extracted from the ovaries of PCOS with insulin resistance rats and normal rats. Three ovaries from each group were used to identify differentially expressed miRNAs by deep sequencing. A hierarchical clustering heatmap and volcano plot were used to display the pattern of differentially expressed miRNAs. Gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were conducted to explore the potential target genes of the differentially expressed miRNAs and identify their putative biological function. Nine of the differentially expressed miRNAs were selected for validation by Real-time Quantitative PCR (qRT-PCR).

Results: A total of 58 differentially expressed miRNAs were identified in the rat ovaries exhibiting PCOS with insulin resistance compared with control ovaries, including 23 miRNAs that were upregulated and 35 miRNAs that were downregulated. GO and KEGG pathway analyses revealed that the predicted target genes were related to metabolic processes, cellular processes, and metabolic pathways. Furthermore, qRT-PCR confirmed that miR-3585-5p and miR-30-5p were significantly upregulated and miR-146-5p was downregulated in the ovaries of PCOS with insulin resistance rats compared with the controls.

Conclusion: These results indicate that differentially expressed miRNAs in rat ovaries may be involved in the pathophysiology of insulin resistance in PCOS. Our study may be beneficial in establishing miRNAs as novel diagnostic and therapeutic biomarkers for insulin resistance in PCOS.

Keywords: High-throughput sequencing; Insulin resistance; MicroRNAs; Polycystic ovary syndrome.

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Conflict of interest statement

The authors declare no potential conflicts of interest.

Figures

Fig.1

Fig.1

Change in estrous cycles and morphology of ovaries of rats from the LEHF-induced PCOS with insulin resistance and the groups. a Changes in estrous cycle between the LEHF and CON groups. b Morphological changes in the rat ovarian tissues as detected by H&E. LEHF letrozole and high-fat diet group, D diestrus, P proestrus, E estrus, M metestrus

Fig.2

Fig.2

Changes in blood sugar and hormone levels between the LEHF and CON groups. a Comparison of weight between the two groups. b The values of FBG, FINS and HOMA-IR were determined for the two groups. c The LH, FSH, E2, T and P levels were determined for the two groups. *P < 0.05; **P < 0.01. FBG fasting blood glucose, FINS fasting insulin, HOMA-IR homeostasis model assessment of insulin resistance, FSH follicle stimulating hormone, LH luteinizing hormone, E2 estradiol, T testosterone, P progesterone

Fig.3

Fig.3

Differentially expressed miRNAs were identified by deep sequencing. A hierarchical clustering heatmap (a) and a volcano plot (b) were used to display the differentially expressed miRNA patterns between the two groups

Fig.4

Fig.4

Gene ontology (GO) and KEGG pathway analysis for predicted targets of the differentially expressed miRNAs

Fig.5

Fig.5

Validation of the miRNAs in the rat ovaries between the two groups by qRT-PCR. The expression of four upregulated miRNAs (miR-3585-5p, miR-200-3p, miR-30-5p and miR-134-3p) and five downregulated miRNAs (miR-132-3p, miR-146-5p, miR-21-5p, miR-124-3p and miR-122-5p) identified by deep sequencing were determined. *P < 0.05; **P < 0.01

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