Ask about this productRelated genes to: HPRT1 Blocking Peptide
- Gene:
- HPRT1 NIH gene
- Name:
- hypoxanthine phosphoribosyltransferase 1
- Previous symbol:
- HPRT
- Synonyms:
- HGPRT
- Chromosome:
- Xq26.2-q26.3
- Locus Type:
- gene with protein product
- Date approved:
- 2001-06-22
- Date modifiied:
- 2018-02-13
Related products to: HPRT1 Blocking Peptide
Related articles to: HPRT1 Blocking Peptide
- Purines are a class of ubiquitous molecules required for fundamental processes in all cells. Purines are derived from two major sources: de novo synthesis, and salvage of preformed purine bases. The current studies provide evidence that the relative contributions of these two pathways change substantially as human induced pluripotent stem cells (iPSCs) differentiate into neurons. Expression of all genes in the de novo synthesis pathway decreases as pluripotent cells differentiate into neurons, but expression of the salvage pathway gene HPRT1 increases. This selective rise in HPRT1 gene expression corresponds with increased activity of its associated enzyme, hypoxanthine-guanine phosphoribosyltransferase (HGprt). Similar changes in the expression of genes for the de novo pathway genes and for HPRT1 were found in a public database of gene expression for human brain development. The consequences of eliminating HGprt-mediated recycling were also evaluated in human-derived iPSCs with null HPRT1 mutations and stock iPSC lines that have been gene-edited to contain a null HPRT1 mutation. The absence of HGprt had no apparent impact on early neuronal differentiation, through 60 days of in vitro differentiation. Biochemical studies of purine content showed that that the absence of HGprt had little impact on intracellular purines, although large amounts of its substrate (hypoxanthine) accumulated in the tissue culture medium. Neurons derived from iPSCs without HGprt appeared morphologically and neurochemically indistinguishable from neurons derived from iPSCs where HGprt was intact. Interrogation of the transcriptome using RNA sequencing (RNAseq) indicated that the absence of HGprt had no consistent impact on gene expression during differentiation. Overall, these results suggest HGprt does not have a large impact on early neuronal differentiation and may instead play a more important role in later neuronal differentiation or function. - Source: PubMed
Publication date: 2026/05/19
Grychowski LaurenSeifar FatemehOzel ErkinThite AnikaSutcliffe Diane JDinasarapu Ashok RHess Ellen JJinnah H A - Fluorescent reporter systems for protein expression enable real-time, dynamic, and single-cell visualization of gene expression in living cells, but lack sufficient sensitivity for detecting low-abundance proteins. Herein, we developed a signal-amplified split superfolder green fluorescent protein (sfGFP) reporter system: sfGFP was split into the GFP fragment driven by a constitutively strong promoter and a 20× tandem GFP tag controlled by weak promoters, with the incorporation of coiled-coil dimerization domains to facilitate fragment complementation. This design enhanced fluorescent signals by approximately 10-fold, significantly improving detection sensitivity and enabling clear visualization of green fluorescence even at extremely low mRNA levels. Application of this system to evaluate Tet-On inducible systems revealed substantial basal leakage in Tet-On 2G. Moreover, real-time monitoring of endogenous weakly promoters (e.g., VIM, HPRT1, GUSB) demonstrated that the fluorescent intensity was approximately 10-fold higher than that of conventional reporter systems. This platform provides a highly sensitive and versatile tool for weak promoter activity analysis, dynamic tracking of low-abundance genes, and investigation of cell types and states. - Source: PubMed
Lin ShuoYuan HuiLin ZiyiLi ShuangpengChi YueYin HaihuaZuo XiaCheng RuilinTang YuqianLuo ZihaoChen MinLiang YaoshunZhou XiaoqingTang ChengchengZou Qingjian - Reverse transcription quantitative real-time polymerase chain reaction is the gold standard for gene expression quantification. Yet, this method's accuracy heavily depends on choosing appropriate reference genes for data normalization. Reference genes must display stable expression levels across biological and experimental conditions to ensure accurate and meaningful results. - Source: PubMed
Publication date: 2026/04/24
Mengi Camur NazSeker BusranurKizildag FulyaYanik TulinAdams Michelle M - Patient-derived cell models of dystrophic myogenesis and differentiation are valuable preclinical tools for early and mutation-based assessment of candidate therapeutic approaches. Quantitative measurement of gene expression within such models plays a key role in these studies, but normalisation of RT-qPCR data requires a panel of validated stably expressed reference genes. This study aims to identify stable reference genes for RT-qPCR assays in three human derived muscle immortalized cell lines: one healthy WT (from a 16-year-old donor), and two dystrophic lines, DMD1 (from a 11-year-old patient carrying a stop codon mutation on exon 59) and DMD2, from a 14-year-old patient carrying an exon 48-50 deletion. We screened a pool of 14 candidate genes (ACTB, HPRT1, RPL13A, RPS18, GAPDH, ALAS1, UBC, YWHAZ, IPO8, PSMC4, HSP90AB1, NONO, CSNK2A2, AP3D1), investigating stability of expression from proliferation through to 11 days of myogenic differentiation. Data were analysed using four complementary approaches (Bestkeeper, geNorm, Normfinder and DeltaCt) to determine the most appropriate references both within and between cell lines. Our study shows that RPS18, UBC, YWHAZ scored highly across all comparisons, and we therefore suggest that these three genes represent an appropriate reference panel for these human myogenic cell lines, regardless of genotype or differentiation stage. - Source: PubMed
Publication date: 2026/03/13
Quarta RaffaellaBoccanegra BrigidaCristiano EnricaLadisa AlbertoConte ElenaOhana JessicaMouly VincentDe Luca AnnamariaHildyard JohnCappellari Ornella - Metabolic reprogramming is a hallmark of cancer. However, the precise mechanisms by which specific metabolic pathways drive prostate cancer (PCa) progression and shape the tumor microenvironment remain poorly defined. - Source: PubMed
Publication date: 2026/03/03
Nie XiangqianHe ZhenlinWang KunZhu DecaiLi WeiZhang LeiYu Ying