Recent advances in functional annotation and prediction of the epitranscriptome

RNA modifications, in particular N(6)-methyladenosine (m(6)A), participate in every stages of RNA metabolism and play diverse roles in essential biological processes and disease pathogenesis. Thanks to the advances in sequencing technology, tens of thousands of RNA modification sites can be identified in a typical high-throughput experiment; however, it remains a major challenge to decipher the functional relevance of these sites, such as, affecting alternative splicing, regulation circuit in essential biological processes or association to diseases. As the focus of RNA epigenetics gradually shifts from site discovery to functional studies, we review here recent progress in functional annotation and prediction of RNA modification sites from a bioinformatics perspective. The review covers naïve annotation with associated biological events, e.g., single nucleotide polymorphism (SNP), RNA binding protein (RBP) and alternative splicing, prediction of key sites and their regulatory functions, inference of disease association, and mining the diagnosis and prognosis value of RNA modification regulators. We further discussed the limitations of existing approaches and some future perspectives

Absolute quantification of exogenous stimuli-induced nucleic acid modification dynamics with LC-MS

Modifications of nucleic acids comply different functions and are involved in genome or-ganization, cell differentiation, silencing, structure stability and enzyme recognition. Modi-fication abundances can be regulated intrinsically, like the incorporation of cap modifica-tions on viral RNA to evade the host immune response, but also extrinsically as a cause of damage, which can result in mutations or translational defects. Either way, modifications are highly dynamic. It is of great importance to trace and quantify these changes in order to understand the underlying mechanisms, which may offer a more divers applica-bility of RNA therapeutics and even facilitate the establishment of personalized medicine. Mass Spectrometry is a common technique to examine nucleic acids. However, mass spectrometry per se offers solely a static insight into the versatile dynamics of nucleic acid modifications. In order to circumvent this obstacle, Nucleic Acid Isotope Labeling coupled Mass Spectrometry (NAIL-MS) was developed. This powerful technique allows for absolute quantification on the one hand and on the other hand for examination of modification dynamics originating from endogenous or exogenous actuators. In 2010, the stress-induced reprogramming of tRNA modification in S. cerevisiae was reported. However, the underlying mechanisms remained to be elucidated. Few years later, the dynamics of RNA modifications and mechanisms like dilution, degradation and (de-)modification could be identified by the application of NAIL-MS. The first part of my dissertation deals with the examination of the extent of damage-induced alterations on nucleic acids. Therefore, a novel biosynthetically produced stable isotope labeled internal standard (SILIS) was established, to avoid the interference of signals with isotopologues generated in the stable isotope labeled pulse-chase experiments. Furthermore, the L-methionine-[2H3]-methyl labeling in S. cerevisiae was optimized to achieve full efficient labeling and thus again avoiding signal interferences with isotopologues due to inefficient labeling. Additionally, the tandem size exclusion chromatography was developed, allowing the time efficient purification of 28S/25S, 18S rRNA and tRNA in a single step. The appli-cation of improved stable isotope labeling and the facilitated purification of RNA popula-tions allowed for the examination of the stress-induced alterations in the RNA modifica-tion profile of S. cerevisiae. Thereby, the knowledge on stress-induced reprogramming of tRNA modifications in yeast could be expanded. Original and new transcripts could be discerned and in addition endogenous methylation could be differentiated from damage induced methylation. It was shown, that stress-induced alterations occur on original tRNA transcripts, whereas new transcripts were not affected. Moreover, the fast decrease of damage-induced methylations on 25S, 18S rRNA and tRNA in S. cerevisiae was demon-strated. Additionally, the formation of base damage on 2’-O-methylated nucleosides in rRNA upon methyl methanesulfonate (MMS) exposure were detected and thereby novel damage products of MMS could be identified. Furthermore, the application of NAIL-MS was expanded to study the endogenous and damage-induced methylome on the genomic levels in S. cerevisiae and E. coli. In parallel to the aforementioned findings, the fast dis-appearance of damage-induced methylations in the genome and transcriptome of S. cerevisiae and E. coli was shown. Apart from that, m7dG and m7G could be identified as the main damage products in the genome and transcriptome of both organisms. In parallel to prokaryotes and eukaryotes, the modifications in viral RNA are highly dy-namic. RNA viruses have high mutation rates and their modification abundances can vary during infection. So, several mutants and variants of the RNA virus SARS-CoV-2 emerged since 2019. It is necessary to understand the characteristics of the viral genome and the differences in mutants and variants in order to identify novel drug targets and optimize the application of available therapeutics and vaccines. Our previous work on absolute quantification of nucleic acid modifications in various organisms showed the strength of our LC-MS based approach. In the course of this study it was aimed at inves-tigating the viral RNA modification profile in the different mutants and variants of SARS-CoV-2. The absolute quantification of RNA modifications and the comparison to pub-lished reports lead to the assumption that observed modification densities are highly de-pendent on the cultivation and infection conditions as well as the purification method and verification of sample integrity is crucial for valid analysis. As outlined above, less is known about the genome of SARS-CoV-2 in terms of internal modifications. While the cap modification of the 5’ end of the SARS-CoV-2 genome is confirmed from many sides and is ascribed to regulate the host innate immune response and the viral replication. Hence, a better understanding of the viral capping mechanism is required in order to limit its contagiousness. Besides the interest in biological capping processes, the investigations on cap modifications become more relevant nowadays be-cause of mRNA therapeutics. The cap modification on engineered mRNA is necessary to prevent immunogenicity, improve intercellular stability and translation efficiency. Thus, therapeutic mRNA is engineered to resemble mature and processed eukaryotic mRNA, including the 5’ cap and the 3’ poly A tail. Currently, there are only a few published LC-MS methods for detection of cap modifications. Nevertheless, these methods include labor intensive sample preparation, long analyses times and have moderate sensitivity. In the course of my dissertation, the development and optimization of a time efficient and highly sensitive LC-MS method for absolute quantification of cap modifications is pre-sented. It includes an extensive method development, optimizing chromatographic and mass spectrometric parameters under consideration of short analysis time, low detection and quantification limits. For absolute quantification of cap modifications, an in vitro tran-scribed cap-SILIS was generated. Furthermore, limits of detection and quantification as well as the dynamic range for size and amount of macromolecules to be analyzed were determined. The high sensitivity allows for the analysis of RNA from synthetic but also from biological sources. The time efficiency is aspirational for ecologic and economic rea-sons, thus making this method suitable for high throughput analyses and industry. The identification and quantification of RNA modifications is getting more important with the significance of RNA therapeutics. In this work, efficient LC-MS based tools to study the extent of nucleic acid modifications are described. Insight into the stress-dependent regulation of the genome and transcriptome of common model organisms is given and a powerful method to quantify cap modifications is presented. These techniques can be used to study nucleic acid dynamics in clinical studies but also for quality control of RNA therapeutics

Novel Algorithm Development for ‘NextGeneration’ Sequencing Data Analysis

In recent years, the decreasing cost of ‘Next generation’ sequencing has spawned numerous applications for interrogating whole genomes and transcriptomes in research, diagnostic and forensic settings. While the innovations in sequencing have been explosive, the development of scalable and robust bioinformatics software and algorithms for the analysis of new types of data generated by these technologies have struggled to keep up. As a result, large volumes of NGS data available in public repositories are severely underutilised, despite providing a rich resource for data mining applications. Indeed, the bottleneck in genome and transcriptome sequencing experiments has shifted from data generation to bioinformatics analysis and interpretation. This thesis focuses on development of novel bioinformatics software to bridge the gap between data availability and interpretation. The work is split between two core topics – computational prioritisation/identification of disease gene variants and identification of RNA N6 -adenosine Methylation from sequencing data. The first chapter briefly discusses the emergence and establishment of NGS technology as a core tool in biology and its current applications and perspectives. Chapter 2 introduces the problem of variant prioritisation in the context of Mendelian disease, where tens of thousands of potential candidates are generated by a typical sequencing experiment. Novel software developed for candidate gene prioritisation is described that utilises data mining of tissue-specific gene expression profiles (Chapter 3). The second part of chapter investigates an alternative approach to candidate variant prioritisation by leveraging functional and phenotypic descriptions of genes and diseases from multiple biomedical domain ontologies (Chapter 4). Chapter 5 discusses N6 AdenosineMethylation, a recently re-discovered posttranscriptional modification of RNA. The core of the chapter describes novel software developed for transcriptome-wide detection of this epitranscriptomic mark from sequencing data. Chapter 6 presents a case study application of the software, reporting the previously uncharacterised RNA methylome of Kaposi’s Sarcoma Herpes Virus. The chapter further discusses a putative novel N6-methyl-adenosine -RNA binding protein and its possible roles in the progression of viral infection