Computational prediction of sRNAs and their targets in bacteria

被引:85
作者
Backofen, Rolf [1 ]
Hess, Wolfgang R. [2 ]
机构
[1] Univ Freiburg, Freiburg Initiat Syst Biol, Fac Engn, Dept Comp Sci,Chair Bioinformat, Freiburg, Germany
[2] Univ Freiburg, Freiburg Initiat Syst Biol, Fac Biol, Genet & Expt Bioinformat Grp, Freiburg, Germany
关键词
algorithms; bacteria; comparative genomics; compensatory mutations; non-coding RNA; regulatory RNA; small RNA; SMALL NONCODING RNAS; BASE-PAIRING PROBABILITIES; ESCHERICHIA-COLI; PSEUDOMONAS-AERUGINOSA; SECONDARY STRUCTURE; PARTITION-FUNCTION; SINORHIZOBIUM-MELILOTI; COMPARATIVE GENOMICS; FUNCTIONAL RNAS; ENCODING GENES;
D O I
10.4161/rna.7.1.10655
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
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.
引用
收藏
页码:33 / 42
页数:10
相关论文
共 76 条
[1]   RNA-RNA interaction prediction and antisense RNA target search [J].
Alkan, C ;
Karakoç, E ;
Nadeau, JH ;
Sahinalp, SC ;
Zhang, KH .
JOURNAL OF COMPUTATIONAL BIOLOGY, 2006, 13 (02) :267-282
[2]  
ALTSCHUL SF, 1990, J MOL BIOL, V215, P403, DOI 10.1006/jmbi.1990.9999
[3]   Identification of bacterial small non-coding RNAs: experimental approaches [J].
Altuvia, Shoshy .
CURRENT OPINION IN MICROBIOLOGY, 2007, 10 (03) :257-261
[4]   Secondary structure prediction of interacting RNA molecules [J].
Andronescu, M ;
Zhang, ZC ;
Condon, A .
JOURNAL OF MOLECULAR BIOLOGY, 2005, 345 (05) :987-1001
[5]   Novel small RNA-encoding genes in the intergenic regions of Escherichia coli [J].
Argaman, L ;
Hershberg, R ;
Vogel, J ;
Bejerano, G ;
Wagner, EGH ;
Margalit, H ;
Altuvia, S .
CURRENT BIOLOGY, 2001, 11 (12) :941-950
[6]   fhlA repression by OxyS RNA:: Kissing complex formation at two sites results in a stable antisense-target RNA complex [J].
Argaman, L ;
Altuvia, S .
JOURNAL OF MOLECULAR BIOLOGY, 2000, 300 (05) :1101-1112
[7]   Two distinct types of 6S RNA in Prochlorococcus [J].
Axmann, Ilka M. ;
Holtzendorff, Julia ;
Voss, Bjoern ;
Kensche, Philip ;
Hess, Wolfgang R. .
GENE, 2007, 406 (1-2) :69-78
[8]   Identification of cyanobacterial non-coding RNAs by comparative genome analysis [J].
Axmann, IM ;
Kensche, P ;
Vogel, J ;
Kohl, S ;
Herzel, H ;
Hess, WR .
GENOME BIOLOGY, 2005, 6 (09)
[9]   The impact of microRNAs on protein output [J].
Baek, Daehyun ;
Villen, Judit ;
Shin, Chanseok ;
Camargo, Fernando D. ;
Gygi, Steven P. ;
Bartel, David P. .
NATURE, 2008, 455 (7209) :64-U38
[10]   Probing the structure of RNAIII, the Staphylococcus aureus agr regulatory RNA, and identification of the RNA domain involved in repression of protein A expression [J].
Benito, Y ;
Kolb, FA ;
Romby, P ;
Lina, G ;
Etienne, J ;
Vandenesch, F .
RNA, 2000, 6 (05) :668-679