@article{LiWongNongetal.2014,
  author    = {Li, Lei and Wong, Hin-chung and Nong, Wenyan and Cheung, Man Kit and Law, Patrick Tik Wan and Kam, Kai Man and Kwan, Hoi Shan},
  title     = {Comparative genomic analysis of clinical and environmental strains provides insight into the pathogenicity and evolution of Vibrio parahaemolyticus},
  series = {BMC Genomics},
  volume    = {15},
  journal   = {BMC Genomics},
  number    = {1135},
  issn      = {1471-2164},
  doi       = {10.1186/1471-2164-15-1135},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-118080},
  year      = {2014},
  abstract  = {Background: Vibrio parahaemolyticus is a Gram-negative halophilic bacterium. Infections with the bacterium could become systemic and can be life-threatening to immunocompromised individuals. Genome sequences of a few clinical isolates of V. parahaemolyticus are currently available, but the genome dynamics across the species and virulence potential of environmental strains on a genome-scale have not been described before. Results: Here we present genome sequences of four V. parahaemolyticus clinical strains from stool samples of patients and five environmental strains in Hong Kong. Phylogenomics analysis based on single nucleotide polymorphisms revealed a clear distinction between the clinical and environmental isolates. A new gene cluster belonging to the biofilm associated proteins of V. parahaemolyticus was found in clincial strains. In addition, a novel small genomic island frequently found among clinical isolates was reported. A few environmental strains were found harboring virulence genes and prophage elements, indicating their virulence potential. A unique biphenyl degradation pathway was also reported. A database for V. parahaemolyticus (http://kwanlab.bio.cuhk.edu.hk/vp webcite) was constructed here as a platform to access and analyze genome sequences and annotations of the bacterium. Conclusions: We have performed a comparative genomics analysis of clinical and environmental strains of V. parahaemolyticus. Our analyses could facilitate understanding of the phylogenetic diversity and niche adaptation of this bacterium. "},
  language  = {en}
}
@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}
}