Applied Bioinformatics for ncRNA Characterization - Case Studies Combining Next Generation Sequencing & Genomics

Non-coding RNAs (ncRNAs) present a diverse class of functional molecules inherent in virtually all forms of cellular life. Besides the canonical protein-encoding mRNAs the role of these abundant transcripts has been overlooked for decades. Defined by their highly conserved structure ncRNAs are resis...

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Bibliographic Details
Main Author: Thölken, Clemens
Contributors: Lechner, Marcus (Dr.) (Thesis advisor)
Format: Dissertation
Language:English
Published: Philipps-Universität Marburg 2018
Pharmazeutische Chemie
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Summary:Non-coding RNAs (ncRNAs) present a diverse class of functional molecules inherent in virtually all forms of cellular life. Besides the canonical protein-encoding mRNAs the role of these abundant transcripts has been overlooked for decades. Defined by their highly conserved structure ncRNAs are resistant to degradation and perform various regulatory functions. Despite the poor sequence conservation, comparative genomics can be employed to identify homologous ncRNAs based on their structure in related species. Through the availability of next generation sequencing techniques, a rich corpus of datasets is available which grants a detailed look into cellular processes. The combination of genomic and transcriptomic data allows for a detailed understanding of molecular mechanism as well as characterization of individual gene functions and their evolution. However, analytical processing of modern high-throughput data is only made viable through optimized bioinformatic algorithms and reproducible automation pipelines. This thesis consists of four major parts highlighting the diverse roles of ncRNAs concerning the transcription process viewed from different vantage points. The first part concerns an unusually long untranslated region in Rhodobacter which harbors a ncRNA that regulates the expression of the downstream division cell wall cluster. Second, the degradation of 6S RNA in Bacillus subtilis is experimentally reconstructed to shed light on this final part of the RNA life cycle. This ncRNA is ubiquitous among bacteria and known to be a global transcription regulator itself. Next, the focus moves to the eukaryotic system and RNase P, an ancient ribozyme that is involved in tRNA maturation. Due to differences in composition with an optional RNA and multiple protein subunits, its phylogenetic distribution and deviant characteristics throughout the eukaryotic lineage are examined in order to trace its evolution. Finally, a diverse subgroup of non-translated RNAs are circRNAs which recently received increased attention due to their abundance in neural tissue. Resulting from post-transcriptional back-splicing events circRNAs compete with their host gene for expression. In a zoological study of social insects circRNA were for the first time identified in honeybees. The goal was to find task-related differences in circRNA expression between nurse bees and foragers and thus pinpoint potential functions of these elusive ncRNAs. The combination of genomic methods and transcriptomic data makes in-depth functional analysis of ncRNAs possible and enables us to understand the molecular mechanisms on multiple levels. Through structural predictions a riboswitch like transcriptional control of UpsM was revealed that is unique to Rhodobacteraceae. Transcriptomic analysis exposed that 6S RNA is primarily processed by RNase J1 for maturation and degraded at internal loops by RNase Y. Evolutionary comparison of organellar RNase P revealed that the RNA subunit is potentially less conserved than thought while organellar proteinonly variants are widespread potentially due to horizontal gene transfer. In the case of circRNA, an entire group of ncRNAs was characterized in the social model organism of honeybees and evidence of at least one gene where circRNA levels are significantly reduced during nurse-to-forager transition could be shown. Moreover, an unexpected link between elevated DNA methylation and RNA circularization was discovered. The bioinformatic findings in all of these cases provide a foundation for further experimental research and illustrate how scientific endeavors cannot be automated completely but require rigorous investigation with customized tools.
Physical Description:164 Pages
DOI:https://doi.org/10.17192/z2019.0047