Biology subjects

Waldl, M.

Publications and source records attributed to Waldl, M..

5 recordsLinked to original sources

bioRxiv2024

tRNA expression and modification landscapes, and their dynamics during zebrafish embryo development

tRNA genes exist in multiple copies in the genome of all organisms across the three domains of life. Besides the sequence differences across tRNA copies, extensive post-transcriptional modification adds a further layer to tRNA diversification. Whilst the crucial role of tRNAs as adapter molecules in protein translation is well established, whether all tRNA are actually expressed, and whether the differences across isodecoders play any regulatory role is only recently being uncovered. Here we built upon recent developments in the use of NGS-based methods for RNA modification detection and developed tRAM-seq, an experimental protocol and in silico analysis pipeline to investigate tRNA expression and modification. Using tRAM-seq we analysed the full ensemble of nucleo-cytoplasmic and mitochondrial tRNAs during embryonic development of the model vertebrate zebrafish. We show that the repertoire of tRNAs changes during development, with an apparent major switch in tRNA isodecoder expression and modification profile taking place around the start of gastrulation. Taken together, our findings suggest the existence of a general reprogramming of the expressed tRNA pool, possibly gearing the translational machinery for distinct stages of the delicate and crucial process of embryo development.

molecular biology↗

bioRxiv2023

Modeling Kinetics of RNA RNA Interactions on Direct Paths

MotivationRNA-RNA interactions play essential roles in gene regulation and are controlled by both thermodynamics and kinetics. State-of-the-art tools predict thermodynamically optimal RNA-RNA interactions, but they neglect kinetic effects. While folding kinetics of single RNAs have been successfully modeled using transition systems between conformations, analogous approaches for RNA-RNA interactions quickly lead to infeasibly large systems. Novel models with controlled system size are required to overcome these limitations and enable computational analysis of RNA- RNA interaction kinetics. Such methods have the potential to improve our understanding of the governing principles of RNA-RNA interaction formation and improve target prediction tools. ResultsWe propose a targeted interaction kinetics model that focuses on a given candidate interaction structure, and further limits the state space by considering only direct paths. This allows us to describe interaction formation as a Markov process on the limited state space and to study which properties are relevant for interaction formation. By comparing experimentally confirmed sRNA-mRNA interactions in E. coli with a randomized background, we show that native interactions are indeed kinetically favored and identify key features, such as seed accessibility and folding energy barrier. Using a machine learning classifier, we identified most-informative combinations of interaction features with respect to the kinetic behavior of native RNA-RNA interactions. Our kinetics model enables the efficient computation of various features that can be used to evaluate genome-wide target predictions by kinetic criteria. Beyond immediate practical improvements, our results contribute to long-standing general questions such as the influence of initial contact site accessibility. Availability and implementationRRIkinDP is available as free software on GitHub at https://github.com/mwaldl/RRIkinDP. Contactmaria@tbi.univie.ac.at

bioinformatics↗

bioRxiv2022

Cyclization studies of Japanese encephalitis virus non-coding RNA terminal regions.

Numerous viruses utilize essential long-range RNA-RNA genome interactions, specifically flaviviruses. Using Japanese encephalitis virus (JEV) as a model system, we computationally predicted and then biophysically validated and characterized its long-range RNA-RNA genomic interaction. Using multiple RNA computation assessment programs, we determine the primary RNA-RNA interacting site among JEV isolates and numerous related viruses. Following in vitro transcription of RNA, we provide, for the first time, characterization of an RNA-RNA interaction using multi-angle light scattering (SEC-MALS) and analytical ultra-centrifugation (AUC). Next, we report the first RNA-RNA interaction study quantified by microscale thermophoresis (MST), demonstrating that the 5 and 3 TR of JEV interact with nM affinity, which is significantly reduced when the conserved cyclization sequence is not present. Furthermore, we perform computational kinetic analyses validating the cyclization sequence as the primary driver of this RNA-RNA interaction. Finally, we examined the 3-dimensional structure of the interaction using small-angle X-ray scattering, revealing a flexible yet stable interaction. This pathway can be adapted and utilized to study various viral and human long-non-coding RNA-RNA interactions, and determine their binding affinities, a critical pharmacological property of designing potential therapeutics. Graphical Abstract O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY

biochemistry↗

bioRxiv2019

Bi-Alignments as Models of Incongruent Evolution of RNA Sequence and Structure

RNA molecules may experience independent selection pressures on their sequence and (secondary) structure. Structural features then may be preserved without maintaining their exact position along the sequence. In such cases, corresponding base pairs are no longer formed by homologous bases, leading to the incongruent evolutionary conservation of sequence and structure. In order to model this phenomenon, we introduce bi-alignments as a superposition of two alignments: one modeling sequence homology; the other, structural homology. We show that under natural assumptions on the scoring functions, bi-alignments form a special case of 4-way alignments, in which the incongruencies are measured as indels in the pairwise alignment of the two alignment copies. A preliminary survey of the Rfam database suggests that incongruent evolution of RNAs is not a very rare phenomenon.\n\nAvailabilityOur software is freely available at https://github.com/s-will/BiAlign

bioinformatics↗

bioRxiv2018

TERribly Difficult: Searching for Telomerase RNAs in Saccharomycetes

AbstractThe telomerase RNA in yeasts is large, usually > 1,000 nt, and contains functional elements that have been extensively studied experimentally in several disparate species. Nevertheless, they are very difficult to detect by homology-based methods and so far have escaped annotation in the majority of the genomes of Saccharomycotina. This is a consequence of sequences that evolve rapidly at nucleotide level, are subject to large variations in size, and are highly plastic with respect to their secondary structures. Here we report on a survey that was aimed at closing this gap in RNA annotation. Despite considerable efforts and the combination of a variety of different methods, it was only partially successful. While 27 new telomerase RNAs were identified, we had to restrict our efforts to the subgroup Saccharomycetacea because even this narrow subgroup was diverse enough to require different search models for different phylogenetic subgroups. More distant branches of the Saccharomycotina still remain without annotated telomerase RNA.

bioinformatics↗