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Computational prediction of sRNAs and their targets in bacteria

期刊

RNA BIOLOGY
卷 7, 期 1, 页码 33-42

出版社

TAYLOR & FRANCIS INC
DOI: 10.4161/rna.7.1.10655

关键词

algorithms; bacteria; comparative genomics; compensatory mutations; non-coding RNA; regulatory RNA; small RNA

资金

  1. BMBF [0313921]
  2. German Research Foundation [SPP1258]
  3. Sensory and regulatory RNAs in Prokaryotes [2544/4-1, 2168/2-1]

向作者/读者索取更多资源

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.

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