Sun Qing, Wang Hao, Tao Shiheng, Xi Xuguang
College of Life Sciences, Northwest A&F University, Yangling, Shaanxi, China.
Bioinformatics Center, Northwest A&F University, Yangling, Shaanxi, China.
Microbiol Spectr. 2023 Feb 27;11(2):e0392822. doi: 10.1128/spectrum.03928-22.
Telomeres are regions of tandem repeated sequences at the ends of linear chromosomes that protect against DNA damage and chromosome fusion. Telomeres are associated with senescence and cancers and have attracted the attention of an increasing number of researchers. However, few telomeric motif sequences are known. Given the mounting interest in telomeres, an efficient computational tool for the detection of the telomeric motif sequence of new species is needed since experimental-based methods are costly in terms of time and effort. Here, we report the development of TelFinder, an easy-to-use and freely available tool for the detection of telomeric motif sequences from genomic data. The vast quantity of readily available genomic data makes it possible to apply this tool to any species of interest, which will undoubtedly inspire studies requiring telomeric repeat information and improve the utilization of these genomic data sets. We have tested TelFinder on telomeric sequences available in the Telomerase Database, and the detection accuracy reaches 90%. In addition, variation analyses in telomere sequences can be performed by TelFinder for the first time. The telomere variation preference of different chromosomes and even at the ends of the chromosome can provide clues regarding the underlying mechanisms of telomeres. Overall, these results shed new light on the divergent evolution of telomeres. Telomeres are reported to be highly correlated with the cell cycle and aging. As a result, research on telomere composition and evolution has become more and more urgent. However, using experimental methods to detect telomeric motif sequences is slow and costly. To combat this challenge, we developed TelFinder, a computational tool for the detection of the telomere composition only using genomic data. In this study, we showed that a lot of complicated telomeric motifs could be identified by TelFinder only using genomic data. In addition, TelFinder can be used to check variation analyses in telomere sequences, which could lead to a deeper understanding of telomere sequences.
端粒是线性染色体末端的串联重复序列区域，可防止DNA损伤和染色体融合。端粒与衰老和癌症相关，已吸引了越来越多研究人员的关注。然而，已知的端粒基序序列很少。鉴于对端粒的兴趣日益增加，由于基于实验的方法在时间和精力方面成本高昂，因此需要一种高效的计算工具来检测新物种的端粒基序序列。在此，我们报告了TelFinder的开发，这是一种易于使用且免费提供的工具，用于从基因组数据中检测端粒基序序列。大量现成的基因组数据使得将该工具应用于任何感兴趣的物种成为可能，这无疑将激发需要端粒重复信息的研究，并提高这些基因组数据集的利用率。我们已在端粒酶数据库中可用的端粒序列上测试了TelFinder，检测准确率达到90%。此外，TelFinder首次可以进行端粒序列的变异分析。不同染色体甚至染色体末端的端粒变异偏好可以为端粒的潜在机制提供线索。总体而言，这些结果为端粒的分歧进化提供了新的线索。据报道，端粒与细胞周期和衰老高度相关。因此，对端粒组成和进化的研究变得越来越迫切。然而，使用实验方法检测端粒基序序列缓慢且成本高昂。为应对这一挑战，我们开发了TelFinder，这是一种仅使用基因组数据检测端粒组成的计算工具。在本研究中，我们表明仅使用基因组数据，TelFinder就可以识别许多复杂的端粒基序。此外，TelFinder可用于检查端粒序列的变异分析，这可能会导致对端粒序列有更深入的了解。
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