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细菌中 sRNAs 及其靶标的计算预测。

Computational prediction of sRNAs and their targets in bacteria.

机构信息

Faculty of Engineering, Department of Computer Sciences, University of Freiburg, Freiburg Initiative in Systems Biology, Freiburg, Germany.

出版信息

RNA Biol. 2010 Jan-Feb;7(1):33-42. doi: 10.4161/rna.7.1.10655. Epub 2010 Jan 13.

Abstract

There is probably no major adaptive response in bacteria which does not have at least one small RNA (sRNA) as part of its regulatory network controlling gene expression. Thus, prokaryotic genomes encode dozens to hundreds of these riboregulators. Whereas the identification of putative sRNA genes during initial genome annotation is not yet common practice, their prediction can be done subsequently by various methods and with variable efficacy, frequently relying on comparative genome analysis. A large number of these sRNAs interact with their mRNA targets by antisense mechanisms. Yet, the computational identification of these targets appears to be challenging because frequently the partial and incomplete sequence complementarity is difficult to evaluate. Here we review the computational approaches for detecting bacterial sRNA genes and their targets, and discuss the current and future challenges that this exciting field of research is facing.

摘要

在控制基因表达的调节网络中,细菌可能没有哪种主要的适应性反应不至少有一个小 RNA(sRNA)。因此,原核基因组编码数十到数百种这些核糖开关。虽然在最初的基因组注释过程中识别推定的 sRNA 基因还不是常见的做法,但可以通过各种方法进行后续预测,其效果也各不相同,通常依赖于比较基因组分析。这些 sRNA 中有大量通过反义机制与它们的 mRNA 靶标相互作用。然而,由于部分和不完全的序列互补性难以评估,因此计算识别这些靶标似乎具有挑战性。在这里,我们回顾了用于检测细菌 sRNA 基因及其靶标的计算方法,并讨论了这个令人兴奋的研究领域目前和未来面临的挑战。

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