@article{LindgreenUmuLaietal.2014,
  author    = {Lindgreen, Stinus and Umu, Sinan Uğur and Lai, Alicia Sook-Wei and Eldai, Hisham and Liu, Wenting and McGimpsey, Stephanie and Wheeler, Nicole E. and Biggs, Patrick J. and Thomson, Nick R. and Barquist, Lars and Poole, Anthony M. and Gardner, Paul P.},
  title     = {Robust Identification of Noncoding RNA from Transcriptomes Requires Phylogenetically-Informed Sampling},
  series = {PLOS Computational Biology},
  volume    = {10},
  journal   = {PLOS Computational Biology},
  number    = {10},
  doi       = {10.1371/journal.pcbi.1003907},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-115259},
  pages     = {e1003907},
  year      = {2014},
  abstract  = {Noncoding RNAs are integral to a wide range of biological processes, including translation, gene regulation, host-pathogen interactions and environmental sensing. While genomics is now a mature field, our capacity to identify noncoding RNA elements in bacterial and archaeal genomes is hampered by the difficulty of de novo identification. The emergence of new technologies for characterizing transcriptome outputs, notably RNA-seq, are improving noncoding RNA identification and expression quantification. However, a major challenge is to robustly distinguish functional outputs from transcriptional noise. To establish whether annotation of existing transcriptome data has effectively captured all functional outputs, we analysed over 400 publicly available RNA-seq datasets spanning 37 different Archaea and Bacteria. Using comparative tools, we identify close to a thousand highly-expressed candidate noncoding RNAs. However, our analyses reveal that capacity to identify noncoding RNA outputs is strongly dependent on phylogenetic sampling. Surprisingly, and in stark contrast to protein-coding genes, the phylogenetic window for effective use of comparative methods is perversely narrow: aggregating public datasets only produced one phylogenetic cluster where these tools could be used to robustly separate unannotated noncoding RNAs from a null hypothesis of transcriptional noise. Our results show that for the full potential of transcriptomics data to be realized, a change in experimental design is paramount: effective transcriptomics requires phylogeny-aware sampling.},
  language  = {en}
}
@article{JaegerPernitzschRichteretal.2012,
  author    = {J{\"a}ger, Dominik and Pernitzsch, Sandy R. and Richter, Andreas S. and Backofen, Rolf and Sharma, Cynthia M. and Schmitz, Ruth A.},
  title     = {An archaeal sRNA targeting cis- and trans-encoded mRNAs via two distinct domains},
  series = {Nucleic Acids Research},
  volume    = {40},
  journal   = {Nucleic Acids Research},
  number    = {21},
  doi       = {10.1093/nar/gks847},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-134972},
  pages     = {10964-10979},
  year      = {2012},
  abstract  = {We report on the characterization and target analysis of the small (s) RNA\(_{162}\) in the methanoarchaeon Methanosarcina mazei. Using a combination of genetic approaches, transcriptome analysis and computational predictions, the bicistronic MM2441-MM2440 mRNA encoding the transcription factor MM2441 and a protein of unknown function was identified as a potential target of this sRNA, which due to processing accumulates as three stabile 5' fragments in late exponential growth. Mobility shift assays using various mutants verified that the non-structured single-stranded linker region of sRNA\(_{162}\) (SLR) base-pairs with the MM2440-MM2441 mRNA internally, thereby masking the predicted ribosome binding site of MM2441. This most likely leads to translational repression of the second cistron resulting in dis-coordinated operon expression. Analysis of mutant RNAs in vivo confirmed that the SLR of sRNA\(_{162}\) is crucial for target interactions. Furthermore, our results indicate that sRNA\(_{162}\)-controlled MM2441 is involved in regulating the metabolic switch between the carbon sources methanol and methylamine. Moreover, biochemical studies demonstrated that the 50 end of sRNA\(_{162}\) targets the 5'-untranslated region of the cis-encoded MM2442 mRNA. Overall, this first study of archaeal sRNA/mRNA-target interactions unraveled that sRNA\(_{162}\) acts as an antisense (as) RNA on cis- and trans-encoded mRNAs via two distinct domains, indicating that cis-encoded asRNAs can have larger target regulons than previously anticipated.},
  language  = {en}
}