@phdthesis{Bemm2018, author = {Bemm, Felix Mathias}, title = {Genetic foundation of unrivaled survival strategies - Of water bears and carnivorous plants -}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-157109}, school = {Universit{\"a}t W{\"u}rzburg}, year = {2018}, abstract = {All living organisms leverage mechanisms and response systems to optimize reproduction, defense, survival, and competitiveness within their natural habitat. Evolutionary theories such as the universal adaptive strategy theory (UAST) developed by John Philip Grime (1979) attempt to describe how these systems are limited by the trade-off between growth, maintenance and regeneration; known as the universal three-way trade-off. Grime introduced three adaptive strategies that enable organisms to coop with either high or low intensities of stress (e.g., nutrient deficiency) and environmental disturbance (e.g., seasons). The competitor is able to outcompete other organisms by efficiently tapping available resources in environments of low intensity stress and disturbance (e.g., rapid growers). A ruderal specism is able to rapidly complete the life cycle especially during high intensity disturbance and low intensity stress (e.g., annual colonizers). The stress tolerator is able to respond to high intensity stress with physiological variability but is limited to low intensity disturbance environments. Carnivorous plants like D. muscipula and tardigrades like M. tardigradum are two extreme examples for such stress tolerators. D. muscipula traps insects in its native habitat (green swamps in North and South Carolina) with specialized leaves and thereby is able to tolerate nutrient deficient soils. M. tardigradum on the other side, is able to escape desiccation of its terrestrial habitat like mosses and lichens which are usually covered by a water film but regularly fall completely dry. The stress tolerance of the two species is the central study object of this thesis. In both cases, high througput sequencing data and methods were used to test for transcriptomic (D. muscipula) or genomic adaptations (M. tardigradum) which underly the stress tolerance. A new hardware resource including computing cluster and high availability storage system was implemented in the first months of the thesis work to effectively analyze the vast amounts of data generated for both projects. Side-by-side, the data management resource TBro [14] was established together with students to intuitively approach complex biological questions and enhance collaboration between researchers of several different disciplines. Thereafter, the unique trapping abilities of D. muscipula were studied using a whole transcriptome approach. Prey-dependent changes of the transcriptional landscape as well as individual tissue-specific aspects of the whole plant were studied. The analysis revealed that non-stimulated traps of D. muscipula exhibit the expected hallmarks of any typical leaf but operates evolutionary conserved stress-related pathways including defense-associated responses when digesting prey. An integrative approach, combining proteome and transcriptome data further enabled the detailed description of the digestive cocktail and the potential nutrient uptake machinery of the plant. The published work [25] as well as a accompanying video material (https://www.eurekalert.org/pub_releases/ 2016-05/cshl-fgr042816.php; Video credit: S{\"o}nke Scherzer) gained global press coverage and successfully underlined the advantages of D. muscipula as experimental system to understand the carnivorous syndrome. The analysis of the peculiar stress tolerance of M. tardigradum during cryptobiosis was carried out using a genomic approach. First, the genome size of M. tardigradum was estimated, the genome sequenced, assembled and annotated. The first draft of M. tardigradum and the workflow used to established its genome draft helped scrutinizing the first ever released tardigrade genome (Hypsibius dujardini) and demonstrated how (bacterial) contamination can influence whole genome analysis efforts [27]. Finally, the M. tardigradum genome was compared to two other tardigrades and all species present in the current release of the Ensembl Metazoa database. The analysis revealed that tardigrade genomes are not that different from those of other Ecdysozoa. The availability of the three genomes allowed the delineation of their phylogenetic position within the Ecdysozoa and placed them as sister taxa to the nematodes. Thereby, the comparative analysis helped to identify evolutionary trends within this metazoan lineage. Surprisingly, the analysis did not reveal general mechanisms (shared by all available tardigrade genomes) behind the arguably most peculiar feature of tardigrades; their enormous stress tolerance. The lack of molecular evidence for individual tardigrade species (e.g., gene expression data for M. tardigradum) and the non-existence of a universal experimental framework which enables hypothesis testing withing the whole phylum Tardigrada, made it nearly impossible to link footprints of genomic adaptations to the unusual physiological capabilities. Nevertheless, the (comparative) genomic framework established during this project will help to understand how evolution tinkered, rewired and modified existing molecular systems to shape the remarkable phenotypic features of tardigrades.}, subject = {B{\"a}rtierchen}, language = {en} } @phdthesis{Terhoeven2020, author = {Terhoeven, Niklas}, title = {Genomics of carnivorous Droseraceae and Transcriptomics of Tobacco pollination as case studies for neofunctionalisation of plant defence mechanisms}, doi = {10.25972/OPUS-18971}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-189712}, school = {Universit{\"a}t W{\"u}rzburg}, year = {2020}, abstract = {Plants have evolved many mechanisms to defend against herbivores and pathogens. In many cases, these mechanisms took other duties. One example of such a neofunction- alisation would be carnivory. Carnivory evolved from the defence against herbivores. Instead of repelling the predator with a bitter taste, the plant kills it and absorbs its nutrients. A second example can be found in the pollination process. Many of the genes involved here were originally part of defence mechanisms against pathogens. In this thesis, I study these two examples on a genomic and transcriptomic level. The first project, Genomics of carnivorous Droseraceae, aims at obtaining annotated genome sequences of three carnivorous plants. I assembled the genome of Aldrovanda vesiculosa, annotated those of A. vesiculosa, Drosera spatulata and Dionaea muscipula and com- pared their genomic contents. Because of the high repetitiveness of the D. muscipula genome, I also developed reper, an assembly free method for detection, classification and quantification of repeats. With that method, we were able to study the repeats without the need of incorporating them into a genome assembly. The second large project investigates the role of DEFL (defensin-like) genes in pollen tube guidance in tobacco flowers. We sequenced the transcriptome of the SR1 strain in different stages of the pollination process. I assembled and annotated the transcriptome and searched for differentially expressed genes. We also used a method based on Hidden- Markov-Models (HMM) to find DEFLs, which I then analysed regarding their expression during the different stages of fertilisation. In total, this thesis results in annotated genome assemblies of three carnivorous Droser- aceae, which are used as a foundation for various analyses investigating the roots of car- nivory, insights into the role of DEFLs on a transcriptomic level in tobacco pollination and a new method for repeat identification in complex genomes.}, subject = {Droseraceae}, language = {en} } @phdthesis{Yu2019, author = {Yu, Sung-Huan}, title = {Development and application of computational tools for RNA-Seq based transcriptome annotations}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-176468}, school = {Universit{\"a}t W{\"u}rzburg}, year = {2019}, abstract = {In order to understand the regulation of gene expression in organisms, precise genome annotation is essential. In recent years, RNA-Seq has become a potent method for generating and improving genome annotations. However, this Approach is time consuming and often inconsistently performed when done manually. In particular, the discovery of non-coding RNAs benefits strongly from the application of RNA-Seq data but requires significant amounts of expert knowledge and is labor-intensive. As a part of my doctoral study, I developed a modular tool called ANNOgesic that can detect numerous transcribed genomic features, including non-coding RNAs, based on RNA-Seq data in a precise and automatic fashion with a focus on bacterial and achaeal species. The software performs numerous analyses and generates several visualizations. It can generate annotations of high-Resolution that are hard to produce using traditional annotation tools that are based only on genome sequences. ANNOgesic can detect numerous novel genomic Features like UTR-derived small non-coding RNAs for which no other tool has been developed before. ANNOgesic is available under an open source license (ISCL) at https://github.com/Sung-Huan/ANNOgesic. My doctoral work not only includes the development of ANNOgesic but also its application to annotate the transcriptome of Staphylococcus aureus HG003 - a strain which has been a insightful model in infection biology. Despite its potential as a model, a complete genome sequence and annotations have been lacking for HG003. In order to fill this gap, the annotations of this strain, including sRNAs and their functions, were generated using ANNOgesic by analyzing differential RNA-Seq data from 14 different samples (two media conditions with seven time points), as well as RNA-Seq data generated after transcript fragmentation. ANNOgesic was also applied to annotate several bacterial and archaeal genomes, and as part of this its high performance was demonstrated. In summary, ANNOgesic is a powerful computational tool for RNA-Seq based annotations and has been successfully applied to several species.}, subject = {Genom}, language = {en} }