Scholarlink

<p>Long noncoding RNAs (lncRNAs) are promising biomarkers, but their accurate quantification by qPCR requires stable endogenous controls. In the present study, we aimed to identify suitable reference lncRNAs for normalization in whole-blood samples. We profiled the expression of 84 lncRNAs and eight commonly used mRNA reference genes by RT-qPCR in samples from 182 individuals. Transcript stability was assessed using three widely applied algorithms: geNorm, NormFinder and BestKeeper. Twenty-nine lncRNAs met predefined expression criteria: consistent detection across all samples, a maximum quantification cycle (Cq) below 33 and a median Cq below 30. Among these, TUG1 consistently ranked as the most stable candidate across all algorithms. FGD5–AS1 and ZFAS1 were also selected based on high stability rankings. We next evaluated the effectiveness of different normalization strategies, comparing them to the gold-standard method, i.e. mean-centering. We included both the selected lncRNAs and eight commonly used mRNA reference genes. TUG1 alone achieved a reduction in expression variability comparable to mean-centering and superior to all other tested strategies, including combinations of multiple reference lncRNAs and mRNAs. Moreover, TUG1 expression showed a minimal association with clinical variables and outcomes. TUG1 was consistently identified among the lncRNAs with the highest expression levels and lowest variability across four independent external RNA-seq datasets. Our findings identify TUG1 as the most stable candidate in this cohort and suggest that it may represent a promising and cost-effective endogenous control for lncRNA quantification in whole-blood studies.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

TUG1: a potential endogenous reference gene for long noncoding RNA quantification in blood-based studies

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年12月30日

查看全文
  • Carlos Rodríguez-Muñoz,
  • Anna Vila,
  • Sally Santisteve,
  • Anna Sánchez-Cucó,
  • Iván D. Benítez,
  • María C. García-Hidalgo,
  • Marta Molinero,
  • Manel Perez-Pons,
  • Anna Moncusí-Moix,
  • Ferran Barbé,
  • Jessica González,
  • David de Gonzalo-Calvo

摘要

Long noncoding RNAs (lncRNAs) are promising biomarkers, but their accurate quantification by qPCR requires stable endogenous controls. In the present study, we aimed to identify suitable reference lncRNAs for normalization in whole-blood samples. We profiled the expression of 84 lncRNAs and eight commonly used mRNA reference genes by RT-qPCR in samples from 182 individuals. Transcript stability was assessed using three widely applied algorithms: geNorm, NormFinder and BestKeeper. Twenty-nine lncRNAs met predefined expression criteria: consistent detection across all samples, a maximum quantification cycle (Cq) below 33 and a median Cq below 30. Among these, TUG1 consistently ranked as the most stable candidate across all algorithms. FGD5–AS1 and ZFAS1 were also selected based on high stability rankings. We next evaluated the effectiveness of different normalization strategies, comparing them to the gold-standard method, i.e. mean-centering. We included both the selected lncRNAs and eight commonly used mRNA reference genes. TUG1 alone achieved a reduction in expression variability comparable to mean-centering and superior to all other tested strategies, including combinations of multiple reference lncRNAs and mRNAs. Moreover, TUG1 expression showed a minimal association with clinical variables and outcomes. TUG1 was consistently identified among the lncRNAs with the highest expression levels and lowest variability across four independent external RNA-seq datasets. Our findings identify TUG1 as the most stable candidate in this cohort and suggest that it may represent a promising and cost-effective endogenous control for lncRNA quantification in whole-blood studies.