@article{WeisschuhMayerStrometal.2016, author = {Weisschuh, Nicole and Mayer, Anja K. and Strom, Tim M. and Kohl, Susanne and Gl{\"o}ckle, Nicola and Schubach, Max and Andreasson, Sten and Bernd, Antje and Birch, David G. and Hamel, Christian P. and Heckenlively, John R. and Jacobson, Samuel G. and Kamme, Christina and Kellner, Ulrich and Kunstmann, Erdmute and Maffei, Pietro and Reiff, Charlotte M. and Rohrschneider, Klaus and Rosenberg, Thomas and Rudolph, G{\"u}nther and V{\´a}mos, Rita and Vars{\´a}nyi, Bal{\´a}zs and Weleber, Richard G. and Wissinger, Bernd}, title = {Mutation Detection in Patients with Retinal Dystrophies Using Targeted Next Generation Sequencing}, series = {PLoS ONE}, volume = {11}, journal = {PLoS ONE}, number = {1}, doi = {10.1371/journal.pone.0145951}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-167398}, pages = {e0145951}, year = {2016}, abstract = {Retinal dystrophies (RD) constitute a group of blinding diseases that are characterized by clinical variability and pronounced genetic heterogeneity. The different nonsyndromic and syndromic forms of RD can be attributed to mutations in more than 200 genes. Consequently, next generation sequencing (NGS) technologies are among the most promising approaches to identify mutations in RD. We screened a large cohort of patients comprising 89 independent cases and families with various subforms of RD applying different NGS platforms. While mutation screening in 50 cases was performed using a RD gene capture panel, 47 cases were analyzed using whole exome sequencing. One family was analyzed using whole genome sequencing. A detection rate of 61\% was achieved including mutations in 34 known and two novel RD genes. A total of 69 distinct mutations were identified, including 39 novel mutations. Notably, genetic findings in several families were not consistent with the initial clinical diagnosis. Clinical reassessment resulted in refinement of the clinical diagnosis in some of these families and confirmed the broad clinical spectrum associated with mutations in RD genes.}, language = {en} } @phdthesis{Pahlavan2019, author = {Pahlavan, Pirasteh}, title = {Integrated Systems Biology Analysis; Exemplified on Potyvirus and Geminivirus interaction with \(Nicotiana\) \(benthamiana\)}, doi = {10.25972/OPUS-15341}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-153412}, school = {Universit{\"a}t W{\"u}rzburg}, year = {2019}, abstract = {Viral infections induce a significant impact on various functional categories of biological processes in the host. The understanding of this complex modification of the infected host immune system requires a global and detailed overview on the infection process. Therefore it is essential to apply a powerful approach which identifies the involved components conferring the capacity to recognize and respond to specific pathogens, which in general are defeated in so-called compatible virus-plant infections. Comparative and integrated systems biology of plant-virus interaction progression may open a novel framework for a systemic picture on the modulation of plant immunity during different infections and understanding pathogenesis mechanisms. In this thesis these approaches were applied to study plant-virus infections during two main viral pathogens of cassava: Cassava brown streak virus and African cassava mosaic virus. Here, the infection process was reconstructed by a combination of omics data-based analyses and metabolic network modelling, to understand the major metabolic pathways and elements underlying viral infection responses in different time series, as well as the flux activity distribution to gain more insights into the metabolic flow and mechanism of regulation; this resulted in simultaneous investigations on a broad spectrum of changes in several levels including the gene expression, primary metabolites, and enzymatic flux associated with the characteristic disease development process induced in Nicotiana benthamiana plants due to infection with CBSV or ACMV. Firstly, the transcriptome dynamics of the infected plant was analysed by using mRNA-sequencing, in order to investigate the differential expression profile according the symptom developmental stage. The spreading pattern and different levels of biological functions of these genes were analysed associated with the infection stage and virus entity. A next step was the Real-Time expression modification of selected key pathway genes followed by their linear regression model. Subsequently, the functional loss of regulatory genes which trigger R-mediated resistance was observed. Substantial differences were observed between infected mutants/transgenic lines and wild-types and characterized in detail. In addition, we detected a massive localized accumulation of ROS and quantified the scavenging genes expression in the infected wild-type plants relative to mock infected controls. Moreover, we found coordinated regulated metabolites in response to viral infection measured by using LC-MS/MS and HPLC-UV-MS. This includes the profile of the phytohormones, carbohydrates, amino acids, and phenolics at different time points of infection with the RNA and DNA viruses. This was influenced by differentially regulated enzymatic activities along the salicylate, jasmonate, and chorismate biosynthesis, glycolysis, tricarboxylic acid cycle, and pentose phosphate pathways, as well as photosynthesis, photorespiration, transporting, amino acid and fatty acid biosynthesis. We calculated the flux redistribution considering a gradient of modulation for enzymes along different infection stages, ranging from pre-symptoms towards infection stability. Collectively, our reverse-engineering study consisting of the generation of experimental data and modelling supports the general insight with comparative and integrated systems biology into a model plant-virus interaction system. We refine the cross talk between transcriptome modification, metabolites modulation and enzymatic flux redistribution during compatible infection progression. The results highlight the global alteration in a susceptible host, correlation between symptoms severity and the alteration level. In addition we identify the detailed corresponding general and specific responses to RNA and DNA viruses at different stages of infection. To sum up, all the findings in this study strengthen the necessity of considering the timing of treatment, which greatly affects plant defence against viral infection, and might result in more efficient or combined targeting of a wider range of plant pathogens.}, language = {en} } @article{SickelAnkenbrandGrimmeretal.2015, author = {Sickel, Wiebke and Ankenbrand, Markus J. and Grimmer, Gudrun and Holzschuh, Andrea and H{\"a}rtel, Stephan and Lanzen, Jonathan and Steffan-Dewenter, Ingolf and Keller, Alexander}, title = {Increased efficiency in identifying mixed pollen samples by meta-barcoding with a dual-indexing approach}, series = {BMC Ecology}, volume = {15}, journal = {BMC Ecology}, number = {20}, doi = {10.1186/s12898-015-0051-y}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-125730}, year = {2015}, abstract = {Background Meta-barcoding of mixed pollen samples constitutes a suitable alternative to conventional pollen identification via light microscopy. Current approaches however have limitations in practicability due to low sample throughput and/or inefficient processing methods, e.g. separate steps for amplification and sample indexing. Results We thus developed a new primer-adapter design for high throughput sequencing with the Illumina technology that remedies these issues. It uses a dual-indexing strategy, where sample-specific combinations of forward and reverse identifiers attached to the barcode marker allow high sample throughput with a single sequencing run. It does not require further adapter ligation steps after amplification. We applied this protocol to 384 pollen samples collected by solitary bees and sequenced all samples together on a single Illumina MiSeq v2 flow cell. According to rarefaction curves, 2,000-3,000 high quality reads per sample were sufficient to assess the complete diversity of 95\% of the samples. We were able to detect 650 different plant taxa in total, of which 95\% were classified at the species level. Together with the laboratory protocol, we also present an update of the reference database used by the classifier software, which increases the total number of covered global plant species included in the database from 37,403 to 72,325 (93\% increase). Conclusions This study thus offers improvements for the laboratory and bioinformatical workflow to existing approaches regarding data quantity and quality as well as processing effort and cost-effectiveness. Although only tested for pollen samples, it is furthermore applicable to other research questions requiring plant identification in mixed and challenging samples.}, language = {en} } @article{HornKellerHildebrandtetal.2016, author = {Horn, Hannes and Keller, Alexander and Hildebrandt, Ulrich and K{\"a}mpfer, Peter and Riederer, Markus and Hentschel, Ute}, title = {Draft genome of the \(Arabidopsis\) \(thaliana\) phyllosphere bacterium, \(Williamsia\) sp. ARP1}, series = {Standards in Genomic Sciences}, volume = {11}, journal = {Standards in Genomic Sciences}, number = {8}, doi = {10.1186/s40793-015-0122-x}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-146008}, year = {2016}, abstract = {The Gram-positive actinomycete \(Williamsia\) sp. ARP1 was originally isolated from the \(Arabidopsis\) \(thaliana\) phyllosphere. Here we describe the general physiological features of this microorganism together with the draft genome sequence and annotation. The 4,745,080 bp long genome contains 4434 protein-coding genes and 70 RNA genes. To our knowledge, this is only the second reported genome from the genus \(Williamsia\) and the first sequenced strain from the phyllosphere. The presented genomic information is interpreted in the context of an adaptation to the phyllosphere habitat.}, language = {en} } @article{WolfKuonenDandekaretal.2015, author = {Wolf, Beat and Kuonen, Pierre and Dandekar, Thomas and Atlan, David}, title = {DNAseq workflow in a diagnostic context and an example of a user friendly implementation}, series = {BioMed Research International}, journal = {BioMed Research International}, number = {403497}, doi = {10.1155/2015/403497}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-144527}, year = {2015}, abstract = {Over recent years next generation sequencing (NGS) technologies evolved from costly tools used by very few, to a much more accessible and economically viable technology. Through this recently gained popularity, its use-cases expanded from research environments into clinical settings. But the technical know-how and infrastructure required to analyze the data remain an obstacle for a wider adoption of this technology, especially in smaller laboratories. We present GensearchNGS, a commercial DNAseq software suite distributed by Phenosystems SA. The focus of GensearchNGS is the optimal usage of already existing infrastructure, while keeping its use simple. This is achieved through the integration of existing tools in a comprehensive software environment, as well as custom algorithms developed with the restrictions of limited infrastructures in mind. This includes the possibility to connect multiple computers to speed up computing intensive parts of the analysis such as sequence alignments. We present a typical DNAseq workflow for NGS data analysis and the approach GensearchNGS takes to implement it. The presented workflow goes from raw data quality control to the final variant report. This includes features such as gene panels and the integration of online databases, like Ensembl for annotations or Cafe Variome for variant sharing.}, language = {en} }