TY  - JOUR
A1  - Lindgreen, Stinus
A1  - Umu, Sinan Uğur
A1  - Lai, Alicia Sook-Wei
A1  - Eldai, Hisham
A1  - Liu, Wenting
A1  - McGimpsey, Stephanie
A1  - Wheeler, Nicole E.
A1  - Biggs, Patrick J.
A1  - Thomson, Nick R.
A1  - Barquist, Lars
A1  - Poole, Anthony M.
A1  - Gardner, Paul P.
T1  - Robust Identification of Noncoding RNA from Transcriptomes Requires Phylogenetically-Informed Sampling
JF  - PLOS Computational Biology
N2  - 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.
KW  - protein families database
KW  - small nucleolar RNAs
KW  - bacterial genomes
KW  - comparative genomics
KW  - dark-matter
KW  - homology search
KW  - archaea
KW  - sequence
KW  - alignment
KW  - insights
Y1  - 2014
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-115259
VL  - 10
IS  - 10
ER  - 
TY  - JOUR
A1  - Jäger, Dominik
A1  - Pernitzsch, Sandy R.
A1  - Richter, Andreas S.
A1  - Backofen, Rolf
A1  - Sharma, Cynthia M.
A1  - Schmitz, Ruth A.
T1  - An archaeal sRNA targeting cis- and trans-encoded mRNAs via two distinct domains
JF  - Nucleic Acids Research
N2  - 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.
KW  - strain
KW  - escherichia coli
KW  - methanosarcina mazei GO1
KW  - methanol methyltransferase isozymes
KW  - small nucleolar RNAs
KW  - acetivorans C2A
KW  - antisense RNAs
KW  - GO1
KW  - transcriptional regulator
KW  - translational initiation
KW  - pyrococcus furiosus
Y1  - 2012
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-134972
VL  - 40
IS  - 21
ER  -