Ramirez Christian, Perenthaler Elena, Lauria Fabio, Tebaldi Toma, Viero Gabriella
Department of Cellular, Computational and Integrative Biology (CIBIO), University of Trento, Trento, Italy.
Institute of Biophysics CNR Unit at Trento, Trento Italy.
RNA Biol. 2025 Dec;22(1):1-11. doi: 10.1080/15476286.2025.2506712. Epub 2025 Jun 29.
This review evaluates the current state of C/D snoRNA databases and prediction tools in relation to 2'-O-methylation (2'-O-Me). It highlights the limitations of existing resources in accurately annotating and predicting guide snoRNAs, particularly for newly identified 2'-O-Me sites. We emphasize the need for advanced computational approaches specifically tailored to 2'-O-Me to enable the discovery and functional analysis of snoRNAs. Given the growing importance of 2'-O-Me in areas such as cancer epitranscriptomics, ribosome biogenesis, and heterogeneity, existing tools remain inadequate. As 2'-O-Me gains recognition as a potential biomarker and therapeutic target, more sophisticated methods are urgently needed to improve snoRNA annotation and prediction, facilitating biomedical advancements.
本综述评估了C/D小核仁RNA（snoRNA）数据库和预测工具在2'-O-甲基化（2'-O-Me）方面的现状。它强调了现有资源在准确注释和预测引导性snoRNA方面的局限性，特别是对于新发现的2'-O-Me位点。我们强调需要专门针对2'-O-Me的先进计算方法，以实现snoRNA的发现和功能分析。鉴于2'-O-Me在癌症表观转录组学、核糖体生物发生和异质性等领域的重要性日益增加，现有工具仍然不足。随着2'-O-Me作为潜在生物标志物和治疗靶点得到认可，迫切需要更复杂的方法来改进snoRNA注释和预测，促进生物医学进步。
