Deciphering the Role of Phosphoglycerate Kinase 1 in Polycystic Ovarian Syndrome using Differential Gene Expression Analysis Approach

Abhishek Sengupta^1*, Priyanka Narad¹, Romasha Gupta¹ , Aayushi Gupta¹ and Nagma Abbasi²

¹Amity Institute of Biotechnology, Amity University, Noida, India.

²NextGen Lifesciences, New Delhi, India.

Corresponding Author E-mail: asengupta@amity.edu

Abstract: Polycystic Ovarian Syndrome (PCOS) is perhaps the most common Metabolic, Endocrine disorder characterized in females before menopause. PCOS majorly elevates Androgen (AR) levels and irregularities in menstrual cycles or can be morphologically seen as multiple cysts in the ovary. Patients with PCOS are more likely to develop obesity, cardiovascular disease, as well as insulin resistance. The etiology of this disease is still not known, but research suggests it can be due to environmental factors, lifestyle, or diet. According to a recent study, the glycolytic enzyme Phosphoglycerate Kinase 1 (PGK1) has an effective role in PCOS patients as it binds with AR, which is high gets expressed in PCOS patients. Thus, it can be a main causable factor for PCOS patients. The granulosa cells of the ovary provide nutrients to oocytes for development. The energy to the oocytes comes via cycle glycolysis. In PCOS patients, these granulosa cells show degradation. As a result, there may be a malfunction in the energy supply via granulosa cells, with Phosphoglycerate Kinase 1(PGK1) being one of the key glycolysis enzymes. And as the high levels of AR remain in proximity with disordered follicle development in PCOS. The actual significance of AR in the fertility of PCOS patients is still not known. Thus, we can have a close look at Androgen binding Receptors (ARs) and the role of PGK1. In this research, we analyzed single-cell RNA sequence data from Gene Expression Omnibus (GEO), including data from control Dihydrotestosterone (DHT) and PGK1-DHT of PCOS patients generated by deep sequencing in triplicate. Further, we explain the transcriptomic dynamics by co-expression network analysis and evaluate the differences between PCA and limmavoom analysis to discover which genes are differentially expressed. By calculating the p-value and performing gene ontology (GO) enrichment analysis, we were able to identify multiple genes with greater expression levels in the PGK1-DHT samples of PCOS patients, including insulin-related, glycolytic, tumor-associated, and apoptotic genes. We also carried out Functional enrichment and gene co-expression network analysis. Its biological, molecular, and cellular domain lies in the intracellular membrane-bound organelle. Gene co-expression network and functional enrichment found significant enrichment and highly differentially expressed genes in the intracellular cellular domain.

Keywords: Deep sequencing; Gene ontology; Glycolysis; Metabolic; Transcriptomic

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