@phdthesis{MikaGospodorz2022,
  author    = {Mika-Gospodorz, Bozena},
  title     = {Development and application of bioinformatics tools for analysis of dual RNA-seq experiments},
  doi       = {10.25972/OPUS-28126},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-281264},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2022},
  abstract  = {Dual RNA-seq captures both host and pathogen transcriptomes at the site of infection, facilitating an exploration of processes that play an essential role in pathogenesis and the host defense. This work presents an application of this technique to explore processes occurring during the infection of the human endothelial cells with two clinical isolates of Orientia tsutsugamushi (Ot) — the causative agent of scrub typhus. Combining comparative genomics, transcriptomics, and proteomics, we investigated the transcriptional architecture of Ot and identified non-coding RNAs, operon structures, and widespread antisense transcription, that may have a role in regulation of repetitive genes that are abundant in the Ot genome. In addition, the comparative analysis of bacterial and eukaryotic transcriptomes allowed us to investigate factors that drive the difference in virulence between Karp and UT176 and the host response to these two Ot strains. The host and pathogen transcriptional profiles in each dual RNA-seq study are obtained in‑silico by adopting tools developed for RNA-seq data analysis. The Dualrnaseq pipeline presented in the second part of this work is the first publicly available, highly reproducible, scalable, and user‑friendly workflow developed for processing dual RNA‑seq data of any eukaryotic and bacterial organisms with a reference genome and annotation. It provides three mapping and quantification strategies: (i) alignment-based mapping of reads onto the chimeric genome with STAR followed by counting of uniquely mapped reads with HTSeq; (ii) a fast transcriptome quantification method handling multi‑mapped reads (Salmon with Selective Alignment); (iii) and Salmon alignment-based mode which uses a STAR‑derived alignment combined with Salmon quantification. Performing an initial benchmark analysis of the employed methods we provided recommendations ensuring accurate estimation of host and pathogen transcript expression.},
  subject      = {Transkriptomanalyse},
  language  = {en}
}