Faculty of Bioengineering and Bioinformatics, Lomonosov Moscow State University, 119234 Moscow, Russia.
Institute of Bioengineering, Research Center of Biotechnology, Russian Academy of Science, 117312 Moscow, Russia.
Int J Mol Sci. 2020 Jan 28;21(3):830. doi: 10.3390/ijms21030830.
Long noncoding RNAs (lncRNAs) play a key role in many cellular processes including chromatin regulation. To modify chromatin, lncRNAs often interact with DNA in a sequence-specific manner forming RNA:DNA triple helices. Computational tools for triple helix search do not always provide genome-wide predictions of sufficient quality. Here, we used four human lncRNAs (MEG3, DACOR1, TERC and HOTAIR) and their experimentally determined binding regions for evaluating triplex parameters that provide the highest prediction accuracy. Additionally, we combined triplex prediction with the lncRNA secondary structure and demonstrated that considering only single-stranded fragments of lncRNA can further improve DNA-RNA triplexes prediction.
长链非编码 RNA（lncRNA）在许多细胞过程中发挥着关键作用，包括染色质调节。为了修饰染色质，lncRNA 通常以序列特异性的方式与 DNA 相互作用，形成 RNA:DNA 三螺旋。三螺旋搜索的计算工具并不总是能够提供足够高质量的全基因组预测。在这里，我们使用了四个人类 lncRNA（MEG3、DACOR1、TERC 和 HOTAIR）及其实验确定的结合区域，以评估提供最高预测准确性的三螺旋参数。此外，我们将三螺旋预测与 lncRNA 二级结构相结合，并证明仅考虑 lncRNA 的单链片段可以进一步提高 DNA-RNA 三螺旋预测的准确性。
