Ask about this productRelated genes to: POLR3GL Blocking Peptide
- Gene:
- POLR3GL NIH gene
- Name:
- RNA polymerase III subunit G like
- Previous symbol:
- -
- Synonyms:
- flj32422, MGC3200
- Chromosome:
- 1q21.1
- Locus Type:
- gene with protein product
- Date approved:
- 2005-02-02
- Date modifiied:
- 2019-03-01
Related products to: POLR3GL Blocking Peptide
Related articles to: POLR3GL Blocking Peptide
- Mathematical models are powerful tools that can be used to advance our understanding of complex diseases. Autoimmune disorders such as systemic lupus erythematosus (SLE) are highly heterogeneous and require high-resolution mechanistic approaches. In this work, we present ONIDsc, a single-cell regulatory network inference model designed to elucidate immune-related disease mechanisms in SLE. - Source: PubMed
Publication date: 2025/07/24
Tejero Elena MerinoVaz Dwain JudeBarturen GuillermoRivas-Torrubia MaríaAlarcón-Riquelme Marta EKolch WalterMatallanas David - RNA polymerase III (RNA Pol III)-related disorders (POLR3-RDs) are a group of clinical entities characterized by causal variants in genes encoding RNA Pol III subunits, including POLR3A, POLR3B, POLR1C, POLR1D, POLR3D, POLR3E, POLR3F, POLR3GL, POLR3H, and POLR3K. These typically cause developmental phenotypes affecting the central nervous system; the eyes; connective tissues including bones, teeth, and endocrine axes; and the reproductive system. Similar phenotypes can be caused by variants in separate subunit genes (multigenic). In contrast, variants in the same gene can cause different phenotypes (pleiotropy), making genotype-phenotype correlation challenging. POLR3-RDs, though individually rare, have never been analyzed collectively. To bridge this gap, we developed an extensive database encompassing all published and unpublished cases of POLR3-RDs and conducted the first comprehensive genotype-phenotype correlation study across their entire spectrum. This work contributed new cases, representing 13% of all documented cases in the literature, along with 31 novel variants, accounting for 8% of all identified variants. This database was constructed by systematically reviewing the literature and integrating data from patients under the care of our international network of collaborators. The dataset includes genotype curation, bioinformatics, prior publications, and individual patient outcome information. By leveraging these comprehensive data, we were able to establish clear genotype-phenotype correlations for some pathogenic variants, which will help provide optimal clinical care and genetic counseling (including insights into disease phenotypes and progression) and offer valuable guidance for future clinical trial design and patient stratification. - Source: PubMed
Publication date: 2025/07/18
Michell-Robinson Mackenzie APerrier StefanieGauthier SamuelDerksen AlexaSabbagh QuentinGirbig MathiasMisiaszek Agata DPizzino Amy MRenaud Deborah LDe Assis Pereira DaniloOkuda PaolaKaroleska Luciana MaestriKeller StephanieChong KarenGauquelin LaurenceBrais BernardLeube BarbaraGrider TiffanyShy Michael ESchüle RebeccaMinnerop MartinaBertini EnricoNicita FrancescoTonduti DavideMüller Christoph WVanderver AdelineWolf Nicole IBernard Geneviève - Wiedemann-Rautenstrauch syndrome (neonatal progeroid syndrome) is an ultra-orphan disease from the group of premature aging syndromes with an autosomal recessive type of inheritance associated with mutations in the POLR3A, POLR3B, and POLR3GL genes encoding RNA polymerase III. The incidence of the disease is currently unknown. We present the first clinical description in Russian Federation of a patient 7 years 6 months old with Wiedemann-Rautenstrauch syndrome (compound heterozygous mutations in POLR3A gene) with progeroid features, adentia, growth retardation (height SDS -3,41, height velocity SDS -2,47), underweight (BMI SDS -6,20), and generalized lipodystrophy. The article presents the observation of the patient for 1.5 years, the world experience of dynamic follow-up of patients with neonatal progeroid syndrome, differential diagnosis, as well as recommendations for the management of patients with this syndrome. Given the lack of specific treatment to date, patients are observed by a multidisciplinary team of physicians. - Source: PubMed
Publication date: 2023/10/08
Kungurtseva A LPopovich A VTikhonovich Y VVitebskaya A V - RNA polymerase III (Pol III) subunit RPC7α, which is encoded by in humans, has been linked to both tumor growth and metastasis. Accordantly, high expression is a negative prognostic factor in multiple cancer subtypes. To date, the mechanisms underlying upregulation have remained poorly defined. We performed a large-scale genomic survey of mRNA and chromatin signatures to predict drivers of expression in cancer. Our survey uncovers positive determinants of expression, including a gene-internal super-enhancer bound with multiple transcription factors (TFs) that promote expression, as well as negative determinants that include gene-internal DNA methylation, retinoic-acid induced differentiation, and MXD4-mediated disruption of expression. We show that novel TFs identified in our survey, including ZNF131 and ZNF207, functionally enhance expression, whereas MXD4 likely obstructs MYC-driven expression of and other growth-related genes. Integration of chromatin architecture and gene regulatory signatures identifies additional factors, including histone demethylase KDM5B, as likely influencers of gene activity. Taken together, our findings support a model in which expression is determined with multiple factors and dynamic regulatory programs, expanding our understanding of the circuitry underlying upregulation and downstream consequences in cancer. - Source: PubMed
Publication date: 2023/10/15
Cheng RuiyingZhou SihangK C RajendraLizarazo SimonMouli LeelaJayanth AnshitaLiu QingVan Bortle Kevin - Currently, the role of liquid-liquid phase separation (LLPS) in cancer has been preliminarily explained. However, the significance of LLPS in breast cancer is unclear. In this study, single cell sequencing datasets GSE188600 and GSE198745 for breast cancer were downloaded from the GEO database. Transcriptome sequencing data for breast cancer were downloaded from UCSC database. We divided breast cancer cells into high-LLPS group and low-LLPS group by down dimension clustering analysis of single-cell sequencing data set, and obtained differentially expressed genes between the two groups. Subsequently, weighted co-expression network analysis (WGCNA) was performed on transcriptome sequencing data, and the module genes most associated with LLPS were obtained. COX regression and Lasso regression were performed and the prognostic model was constructed. Subsequently, survival analysis, principal component analysis, clinical correlation analysis, and nomogram construction were used to evaluate the significance of the prognostic model. Finally, cell experiments were used to verify the function of the model's key gene, PGAM1. We constructed a LLPS-related prognosis model consisting of nine genes: POLR3GL, PLAT, NDRG1, HMGB3, HSPH1, PSMD7, PDCD2, NONO and PGAM1. By calculating LLPS-related risk scores, breast cancer patients could be divided into high-risk and low-risk groups, with the high-risk group having a significantly worse prognosis. Cell experiments showed that the activity, proliferation, invasion and healing ability of breast cancer cell lines were significantly decreased after knockdown of the key gene PGAM1 in the model. Our study provides a new idea for prognostic stratification of breast cancer and provides a novel marker: PGAM1. - Source: PubMed
Publication date: 2023/06/19
Xie JiahengChen LiangWu DanLiu ShengxuanPei ShengbinTang QikaiWang YueOu MengmengZhu ZhechenRuan ShujieWang MingShi Jingping