Androgen receptor coregulator long noncoding RNA CTBP1-AS is associated with polycystic ovary syndrome in Kashmiri women.
TL;DR: The mean expression level of CTBP1-AS was found to be significantly higher in the PCOS women than in the healthy controls, and high expression of CTBA-AS is a risk factor for PCOS in Kashmiri women.
Abstract: Polycystic ovary syndrome (PCOS) is one of the most common reproductive, endocrine, and metabolic disorder in premenopausal women. Even though the pathophysiology of PCOS is complex and obscure, the disorder is prominently considered as the syndrome of hyperandrogenism. C-Terminal binding protein 1 antisense (CTBP1-AS) acts as a novel androgen receptor regulating long noncoding RNA (lncRNA). Therefore, the present study was aimed to establish the possible association of androgen receptor regulating long noncoding RNA CTBP1-AS with PCOS. A total of 178 subjects including 105 PCOS cases and 73 age-matched healthy controls were recruited for the study. The anthropometric, hormonal, and biochemical parameters of all subjects were analyzed. Total RNA was isolated from peripheral venous blood and expression analysis was done by quantitative real-time PCR. The correlation analysis was performed to evaluate the association between and various clinical parameters and lncRNA CTBP1-AS expression. The mean expression level of CTBP1-AS was found to be significantly higher in the PCOS women than in the healthy controls (-lnCTBP1-AS, 4.23 ± 1.68 versus 1.24 ± 0.29, P < 0.001). Furthermore, subjects with higher expression level of CTBP1-AS had significantly higher risk of PCOS compared to subjects with low levels of CTBP1-AS expression (actual OR = 11.36, 95% CI = 5.59–23.08, P < 0.001). The area under receiver operator characteristic (ROC) curve was 0.987 (SE 0.006, 95% CI 0.976–0.99). However, lncRNA CTBP1-AS was found to have no association with different clinical characteristics of PCOS. In conclusion, androgen receptor coregulating lncRNA CTBP1-AS is associated with PCOS women and high expression of CTBP1-AS is a risk factor for PCOS in Kashmiri women
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TL;DR: This review looked at lncRNAs and their molecular targets in the pathogenesis of signaling pathways, with a focus on diseases caused by long-term inflammation and the characteristics of the metabolic syndrome.
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TL;DR: HLA-F-AS1 may inhibit the maturation of miR-613 in PCOS to promote ovarian granulosa cell proliferation and inhibit cell apoptosis.
Abstract: ABSTRACT MicroRNA-613 (miR-613) inhibits granulosa cell proliferation, suggesting its involvement in polycystic ovary syndrome (PCOS). We predicted that long non-coding RNA (lncRNA) HLA-F antisense RNA 1 (HLA-F-AS1) could interact with premature miR-613. We then explored the crosstalk between HLA-F-AS1 and miR-613 in PCOS. In this study, follicular fluid donated by 58 healthy controls and 58 PCOS patients was used to analyze the expression of HLA-F-AS1 and miR-613 (mature and premature). The direct interaction between HLA-F-AS1 and premature miR-613 was evaluated by RNA pull-down assay. Overexpression of both HLA-F-AS1 and miR-613 was achieved in granulosa cells to assess their interactions. Cell proliferation and apoptosis were detected with BrdU assay and cell apoptosis assay, respectively. We found that miR-613 was highly expressed in PCOS, while HLA-F-AS1 was downregulated in PCOS. HLA-F-AS1 directly interacted with premature miR-613, and overexpression of HLA-F-AS1 increased the expression levels of premature miR-613, but decreased the expression levels of mature miR-613. HLA-F-AS1 increased ovarian granulosa cell proliferation and inhibited cell apoptosis. MiR-613 played an opposite role and suppressed the role of HLA-F-AS1. Therefore, HLA-F-AS1 may inhibit the maturation of miR-613 in PCOS to promote ovarian granulosa cell proliferation and inhibit cell apoptosis. GRAPHICAL ABSTRACT
1 citations
01 Jan 2024
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TL;DR: This protocol provides an overview of the comparative CT method for quantitative gene expression studies and various examples to present quantitative gene Expression data using this method.
Abstract: Two different methods of presenting quantitative gene expression exist: absolute and relative quantification. Absolute quantification calculates the copy number of the gene usually by relating the PCR signal to a standard curve. Relative gene expression presents the data of the gene of interest relative to some calibrator or internal control gene. A widely used method to present relative gene expression is the comparative C(T) method also referred to as the 2 (-DeltaDeltaC(T)) method. This protocol provides an overview of the comparative C(T) method for quantitative gene expression studies. Also presented here are various examples to present quantitative gene expression data using this method.
20,580 citations
TL;DR: Since the 1990 NIH-sponsored conference on polycystic ovary syndrome, it has become appreciated that the syndrome encompasses a broader spectrum of signs and symptoms of ovarian dysfunction than those defined by the original diagnostic criteria.
8,217 citations
Cold Spring Harbor Laboratory1, University of California, Irvine2, California Institute of Technology3, Florida State University College of Arts and Sciences4, Yale University5, Wellcome Trust Sanger Institute6, Norwegian University of Science and Technology7, Affymetrix8, University of North Carolina at Chapel Hill9, University of Lausanne10, University of Geneva11, Genome Institute of Singapore12, Stanford University13, Pompeu Fabra University14
TL;DR: Evidence that three-quarters of the human genome is capable of being transcribed is reported, as well as observations about the range and levels of expression, localization, processing fates, regulatory regions and modifications of almost all currently annotated and thousands of previously unannotated RNAs that prompt a redefinition of the concept of a gene.
Abstract: Eukaryotic cells make many types of primary and processed RNAs that are found either in specific subcellular compartments or throughout the cells. A complete catalogue of these RNAs is not yet available and their characteristic subcellular localizations are also poorly understood. Because RNA represents the direct output of the genetic information encoded by genomes and a significant proportion of a cell's regulatory capabilities are focused on its synthesis, processing, transport, modification and translation, the generation of such a catalogue is crucial for understanding genome function. Here we report evidence that three-quarters of the human genome is capable of being transcribed, as well as observations about the range and levels of expression, localization, processing fates, regulatory regions and modifications of almost all currently annotated and thousands of previously unannotated RNAs. These observations, taken together, prompt a redefinition of the concept of a gene.
4,450 citations
TL;DR: The function of lncRNAs in developmental processes, such as in dosage compensation, genomic imprinting, cell differentiation and organogenesis, with a particular emphasis on mammalian development are described.
Abstract: Genomes of multicellular organisms are characterized by the pervasive expression of different types of non-coding RNAs (ncRNAs). Long ncRNAs (lncRNAs) belong to a novel heterogeneous class of ncRNAs that includes thousands of different species. lncRNAs have crucial roles in gene expression control during both developmental and differentiation processes, and the number of lncRNA species increases in genomes of developmentally complex organisms, which highlights the importance of RNA-based levels of control in the evolution of multicellular organisms. In this Review, we describe the function of lncRNAs in developmental processes, such as in dosage compensation, genomic imprinting, cell differentiation and organogenesis, with a particular emphasis on mammalian development.
2,464 citations
TL;DR: The lncRNA landscape characterized here may shed light on normal biology and cancer pathogenesis and may be valuable for future biomarker development.
Abstract: Long noncoding RNAs (lncRNAs) are emerging as important regulators of tissue physiology and disease processes including cancer. To delineate genome-wide lncRNA expression, we curated 7,256 RNA sequencing (RNA-seq) libraries from tumors, normal tissues and cell lines comprising over 43 Tb of sequence from 25 independent studies. We applied ab initio assembly methodology to this data set, yielding a consensus human transcriptome of 91,013 expressed genes. Over 68% (58,648) of genes were classified as lncRNAs, of which 79% were previously unannotated. About 1% (597) of the lncRNAs harbored ultraconserved elements, and 7% (3,900) overlapped disease-associated SNPs. To prioritize lineage-specific, disease-associated lncRNA expression, we employed non-parametric differential expression testing and nominated 7,942 lineage- or cancer-associated lncRNA genes. The lncRNA landscape characterized here may shed light on normal biology and cancer pathogenesis and may be valuable for future biomarker development.
2,209 citations