Barra Jasmine, Leucci Eleonora
Laboratory for Molecular Cancer Biology, Department of Oncology, KU LeuvenLeuven, Belgium.
Center for Cancer Biology, VIBLeuven, Belgium.
Front Mol Biosci. 2017 Jul 11;4:45. doi: 10.3389/fmolb.2017.00045. eCollection 2017.
Non-coding RNA sequences outnumber the protein-coding genes in the human genome, however our knowledge of their functions is still limited. RNA-binding proteins follow the transcripts, including non-coding RNAs, throughout their life, regulating not only maturation, nuclear export, stability and eventually translation, but also RNA functions. Therefore, development of sophisticated methods to study RNA-protein interactions are key to the systematic characterization of lncRNAs. Although mostly applicable to RNA-protein interactions in general, many approaches, especially the computational ones, need adjustment to be adapted to the length and complexity of lncRNA transcripts. Here we critically review all the wet lab and computational methods to study lncRNA-protein interactions and their potential to clarify the dark side of the genome.
非编码RNA序列在人类基因组中比蛋白质编码基因数量更多，然而我们对其功能的了解仍然有限。RNA结合蛋白在整个生命周期中跟踪转录本，包括非编码RNA，不仅调节成熟、核输出、稳定性以及最终的翻译，还调节RNA功能。因此，开发复杂的方法来研究RNA-蛋白质相互作用是lncRNA系统表征的关键。尽管许多方法大多普遍适用于RNA-蛋白质相互作用，尤其是计算方法，但需要进行调整以适应lncRNA转录本的长度和复杂性。在这里，我们批判性地综述了所有用于研究lncRNA-蛋白质相互作用的湿实验室方法和计算方法，以及它们阐明基因组暗面的潜力。
