tRNAscan-SE has been widely used for transfer RNA (tRNA) gene prediction for over twenty years, developed just as the first genomes were decoded. With the massive increase in quantity and phylogenetic diversity of genomes, the accurate detection and functional prediction of tRNAs has become more challenging. Utilizing a vastly larger training set, we created nearly one hundred specialized isotype- and clade-specific models, greatly improving tRNAscan-SE’s ability to identify and classify both typical and atypical tRNAs. We employ a new comparative multi-model strategy where predicted tRNAs are scored against a full set of isotype-specific covariance models, allowing functional prediction based on both the anticodon and the highest-scoring isotype model. Comparative model scoring has also enhanced the program's ability to detect tRNA-derived SINEs and other likely pseudogenes. For the first time, tRNAscan-SE also includes fast and highly accurate detection of mitochondrial tRNAs using newly developed models. Overall, tRNA detection sensitivity and specificity is improved for all isotypes, particularly those utilizing specialized models for selenocysteine and the three subtypes of tRNA genes encoding a CAU anticodon. These enhancements will provide researchers with more accurate and detailed tRNA annotation for a wider variety of tRNAs, and may direct attention to tRNAs with novel traits.

中文翻译：

---

tRNAscan-SE 2.0：改进的转移 RNA 基因检测和功能分类

tRNAscan-SE 已被广泛用于转移 RNA (tRNA) 基因预测二十多年，正如第一个基因组被解码时开发的。随着基因组数量和系统发育多样性的大量增加，tRNA的准确检测和功能预测变得更具挑战性。利用更大的训练集，我们创建了近百个专门的同种型和进化枝特异性模型，大大提高了 tRNAscan-SE 识别和分类典型和非典型 tRNA 的能力。我们采用了一种新的比较多模型策略，其中预测的 tRNA 对全套同种型特异性协方差模型进行评分，允许基于反密码子和得分最高的同种型模型进行功能预测。比较模型评分也增强了该计划 s 检测 tRNA 衍生的 SINE 和其他可能的假基因的能力。tRNAscan-SE 还首次包括使用新开发的模型快速、高度准确地检测线粒体 tRNA。总体而言，所有同种型的 tRNA 检测灵敏度和特异性都得到了提高，特别是那些使用专门模型检测硒代半胱氨酸和编码 CAU 反密码子的 tRNA 基因的三种亚型的那些。这些改进将为研究人员提供更准确、更详细的 tRNA 注释，用于更广泛的 tRNA，并可能将注意力集中到具有新特征的 tRNA。特别是那些利用硒代半胱氨酸和编码 CAU 反密码子的 tRNA 基因的三种亚型的专门模型的人。这些改进将为研究人员提供更准确、更详细的 tRNA 注释，用于更广泛的 tRNA，并可能将注意力集中到具有新特征的 tRNA。特别是那些利用硒代半胱氨酸和编码 CAU 反密码子的 tRNA 基因的三种亚型的专门模型的人。这些改进将为研究人员提供更准确、更详细的 tRNA 注释，用于更广泛的 tRNA，并可能将注意力集中到具有新特征的 tRNA。