@article{SharmaDugarHerbigetal.2013,
  author    = {Sharma, Cynthia M. and Dugar, Gaurav and Herbig, Alexander and F{\"o}rstner, Konrad U. and Heidrich, Nadja and Reinhardt, Richard and Nieselt, Kay},
  title     = {High-Resolution Transcriptome Maps Reveal Strain-Specific Regulatory Features of Multiple Campylobacter jejuni Isolates},
  series = {PLoS Genetics},
  journal   = {PLoS Genetics},
  doi       = {10.1371/journal.pgen.1003495},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-96610},
  year      = {2013},
  abstract  = {Campylobacter jejuni is currently the leading cause of bacterial gastroenteritis in humans. Comparison of multiple Campylobacter strains revealed a high genetic and phenotypic diversity. However, little is known about differences in transcriptome organization, gene expression, and small RNA (sRNA) repertoires. Here we present the first comparative primary transcriptome analysis based on the differential RNA-seq (dRNA-seq) of four C. jejuni isolates. Our approach includes a novel, generic method for the automated annotation of transcriptional start sites (TSS), which allowed us to provide genome-wide promoter maps in the analyzed strains. These global TSS maps are refined through the integration of a SuperGenome approach that allows for a comparative TSS annotation by mapping RNA-seq data of multiple strains into a common coordinate system derived from a whole-genome alignment. Considering the steadily increasing amount of RNA-seq studies, our automated TSS annotation will not only facilitate transcriptome annotation for a wider range of pro- and eukaryotes but can also be adapted for the analysis among different growth or stress conditions. Our comparative dRNA-seq analysis revealed conservation of most TSS, but also single-nucleotide-polymorphisms (SNP) in promoter regions, which lead to strain-specific transcriptional output. Furthermore, we identified strain-specific sRNA repertoires that could contribute to differential gene regulation among strains. In addition, we identified a novel minimal CRISPR-system in Campylobacter of the type-II CRISPR subtype, which relies on the host factor RNase III and a trans-encoded sRNA for maturation of crRNAs. This minimal system of Campylobacter, which seems active in only some strains, employs a unique maturation pathway, since the crRNAs are transcribed from individual promoters in the upstream repeats and thereby minimize the requirements for the maturation machinery. Overall, our study provides new insights into strain-specific transcriptome organization and sRNAs, and reveals genes that could modulate phenotypic variation among strains despite high conservation at the DNA level.},
  language  = {en}
}
@article{YuVogelFoerstner2018,
  author    = {Yu, Sung-Huan and Vogel, J{\"o}rg and F{\"o}rstner, Konrad U.},
  title     = {ANNOgesic: a Swiss army knife for the RNA-seq based annotation of bacterial/archaeal genomes},
  series = {GigaScience},
  volume    = {7},
  journal   = {GigaScience},
  doi       = {10.1093/gigascience/giy096},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-178942},
  year      = {2018},
  abstract  = {To understand the gene regulation of an organism of interest, a comprehensive genome annotation is essential. While some features, such as coding sequences, can be computationally predicted with high accuracy based purely on the genomic sequence, others, such as promoter elements or noncoding RNAs, are harder to detect. RNA sequencing (RNA-seq) has proven to be an efficient method to identify these genomic features and to improve genome annotations. However, processing and integrating RNA-seq data in order to generate high-resolution annotations is challenging, time consuming, and requires numerous steps. We have constructed a powerful and modular tool called ANNOgesic that provides the required analyses and simplifies RNA-seq-based bacterial and archaeal genome annotation. It can integrate data from conventional RNA-seq and differential RNA-seq and predicts and annotates numerous features, including small noncoding RNAs, with high precision. The software is available under an open source license (ISCL) at https://pypi.org/project/ANNOgesic/.},
  language  = {en}
}