Biology subjects

Lipovich, L.

Publications and source records attributed to Lipovich, L..

3 recordsLinked to original sources

bioRxiv2026

Integrative Identification and Characterization of PCOS-Associated lncRNAs From the Interface of Genetic Association, Transcriptomics, and Gene Structure Evolution

BackgroundPolycystic ovary syndrome (PCOS) is a prevalent endocrine disorder and a leading cause of female infertility, with complex genetic, metabolic, and hormonal etiologies. Long non-coding RNAs (lncRNAs) have emerged as important regulators of diverse biological processes, yet their roles in PCOS remain underexplored. Here, we identified and characterized PCOS differentially expressed gene-associated lncRNAs (PDEGAL) with an integrative approach combining expression data, genetic association, and evolutionary analysis. MethodsThirty-three PCOS-associated protein-coding genes were obtained from our prior study, and all their nearby and overlapping lncRNAs were annotated. These candidates were analyzed using UCSC Genome Browser-mapped annotations and datasets, including NCBI RefSeq, GENCODE, GTEx, GWAS SNPs, and conservation, as well as the FANTOM5 cap analysis of gene expression (CAGE) promoter data, to assess their expression, regulatory potential, genetic variant overlaps, and evolutionary conservation. ResultsTwenty-three PDEGALs (18 antisense to, and 5 sharing bidirectional promoters with, known PCOS-associated protein-coding genes) were identified. 17 PDEGALs contained GWAS SNPs with statistically significant disease associations, 9 of which were associated with PCOS-related traits. 5 PDEGALs demonstrated expression in the KGN granulosa cell model of PCOS. Key gene structure element (KGSE) analysis revealed that most PDEGALs are primate-specific. Integrating four criteria--GTEx expression, GWAS SNPs, FANTOM promoterome, and KGSE conservation--highlighted HELLPAR as the only lncRNA fulfilling all four, while five others--PGR-AS1, MTOR-AS1, ENSG00000265179, ENSG00000256218, and LOC105377276--fulfilled three of the four criteria. ConclusionsWe have systematically identified candidate PCOS regulatory lncRNAs with convergent genetic, expression, and evolutionary evidence. These results provide a framework for functional validation and highlight lncRNAs as potential biomarkers and therapeutic targets in PCOS that function by regulating their nearby and overlapping protein-coding genes.

genomics↗

bioRxiv2024

Construction of a ceRNA network specific for granulosa cells in PCOS

BackgroundPolycystic ovary syndrome (PCOS) is a hormonal disease with a polygenic genetic model that occurs in 8 - 13% of women of reproductive age. In this study we constructed the granulose cell-specific competitive endogenous RNA (ceRNA) network in polycystic ovary syndrome. The ceRNA network analysis may provide novel insights into PCOS pathophysiology and identify potential therapeutic targets. Materials and methodsThe study included 6 women aged 26 to 34 years old: 3 women with PCOS and 3 women of the control group who underwent IVF procedure. Before RNA extraction GCs from three follicle samples of each group were collected and randomly pooled together as one mixed sample. Using RNA-sequencing we defined the microRNAs, lncRNAs and mRNAs expression profiles of GCs. The analysis of differential gene expression was performed using the DESeq v.1.39.0. The analysis of the interaction of microRNAs and lncRNAs was performed using RNAhybrid; of microRNAs and mRNAs - using the miRWalk database. Cytoscape 3.10.0 software was used to construct the ceRNA network. ResultsAs a result of the differential gene expression analysis using the DESeq package we identified 3 differentially expressed microRNAs in PCOS, 132 - lncRNAs and 564 - mRNAs. The final ceRNA network included 3 microRNAs, 105 lncRNAs and 252 mRNAs. ConclusionThis research underscores the importance of understanding ceRNA networks as a pathway for discovering biomarkers and developing treatments tailored to the unique challenges faced by individuals with PCOS. Further research is warranted to validate the identified interactions and explore their potential as diagnostic and therapeutic targets.

genetics↗

bioRxiv2020

A long noncoding RNA, LOC157273, is the effector transcript at the chromosome 8p23.1-PPP1R3B metabolic traits and type 2 diabetes risk locus

AimsCausal transcripts at genomic loci associated with type 2 diabetes are mostly unknown. The chr8p23.1 variant rs4841132, associated with an insulin resistant diabetes risk phenotype, lies in the second exon of a long non-coding RNA (lncRNA) gene, LOC157273, located 175 kilobases from PPP1R3B, which encodes a key protein regulating insulin-mediated hepatic glycogen storage in humans. We hypothesized that LOC157273 regulates expression of PPP1R3B in human hepatocytes. MethodsWe tested our hypothesis using Stellaris fluorescent in-situ hybridization to assess subcellular localization of LOC157273; siRNA knockdown of LOC157273, followed by RT-PCR to quantify LOC157273 and PPP1R3B expression; RNA-seq to quantify the whole-transcriptome gene expression response to LOC157273 knockdown and an insulin-stimulated assay to measure hepatocyte glycogen deposition before and after knockdown. ResultsWe found that siRNA knockdown decreased LOC157273 transcript levels by approximately 80%, increased PPP1R3B mRNA levels by 1.7-fold and increased glycogen deposition by >50% in primary human hepatocytes. An A/G heterozygous carrier (vs. three G/G carriers) had reduced LOC157273 abundance due to reduced transcription of the A allele and increased PPP1R3B expression and glycogen deposition. ConclusionWe show that the lncRNA LOC157273 is a negative regulator of PPP1R3B expression and glycogen deposition in human hepatocytes and the causal transcript at an insulin resistant type 2 diabetes risk locus.

genomics↗