Biology subjects

Hewel, C.

Publications and source records attributed to Hewel, C..

6 recordsLinked to original sources

bioRxiv2024

Direct RNA sequencing (RNA004) allows for improved transcriptome assessment and near real-time tracking of methylation for medical applications

Direct RNA sequencing (DRS) is a nanopore-based technique for analyzing RNA in its native form, promising breakthroughs in diagnostics and biomarker development. Coupled to RNA002 sequencing chemistry, its clinical implementation has been challenging due to low throughput, low accuracy, and lack of large-scale RNA-modification models. In this study, we evaluate the improvements achieved by pairing the latest RNA004 chemistry with novel modified-base-calling models for pseudouridine and N6-methyladenosine using diverse RNA samples from cell lines, synthetic oligos, and human blood. Finally, we present the first clinical application of DRS by confirming the loss of RNA methylation in a patient carrying truncating mutations in the methyltransferase METTL5. Conclusively, the combined use of RNA004 chemistry with the base-calling models significantly improved the throughput, accuracy, and site-specific detection of modifications. From this perspective, we offer an outlook on the potential suitability of DRS for use in routine diagnostics, the first comprehensive benchmark of human peripheral blood and quality assessments of RNA therapeutics.

bioinformatics↗

bioRxiv2023

Nanopore adaptive sampling of a metagenomic sample derived from a human monkeypox case

In 2022, a series of human monkeypox cases in multiple countries led to the largest and most widespread outbreak outside the known endemic areas. Genomic surveillance is of utmost importance to control such outbreaks. To this end, we performed Nanopore Whole Genome Sequencing of a local monkeypox sample on a PromethION 24. Adaptive sampling was applied for in silico depletion of the human host genome, allowing for the enrichment of low abundance viral DNA without a priori knowledge of sample composition. Nanopore sequencing allowed for high viral genome coverage, tracking of sample composition during sequencing, strain determination, and preliminary assessment of mutational pattern. Nanopore sequencing is a highly versatile method to characterize a virus in real-time without pre-sequencing target enrichment.

microbiology↗

bioRxiv2019

5’ tRNA halves are highly expressed in the primate hippocampus and sequence-specifically regulate gene expression

Fragments of mature tRNAs have long been considered as mere degradation products without physiological function. However, recent reports show that tRNA fragments (tRFs) play prominent roles in diverse cellular processes across a wide spectrum of species. Contrasting the situation in other small RNA pathways the mechanisms behind these effects appear more diverse, more complex and are generally less well understood. In addition, surprisingly little is known about the expression profiles of tRFs across different tissues and species. Here, we provide an initial overview of tRF expression in different species and tissues, revealing very high tRF-levels particularly in the primate hippocampus. We further modulated the regulation capacity of selected tRFs in human cells by transfecting synthetic tRF mimics (\"overexpression\") or antisense-RNAs (\"inhibition\") and identified differentially expressed transcripts based on RNAseq. We then used a novel k-mer mapping approach to dissect the underlying targeting rules, demonstrating that 5 tRNA halves (5 tRHs) silence genes in a sequence-specific manner, while the most efficient target sites align to the mid-region of the 5 tRH and are located within the CDS or 3 UTR of the target. This amends previous observations that tRFs guide Argonaut proteins to silence their targets via a miRNA-like 5 seed match and suggests a yet unknown mechanism of regulation. Finally, our data suggests that some 5 tRHs are also able to sequence-specifically stabilize mRNAs as upregulated mRNAs are also significantly enriched for 5 tRH target sites.

molecular biology↗

bioRxiv2018

Imputation of posterior linkage probability relations reveals a significant influence of structural 3D constraints on linkage disequilibrium

Genetic association studies have become increasingly important in unraveling the genetics of diseases or complex traits. Despite their value for modern genetics, conflicting conclusions often arise through the difficulty of confirming and replicating experimental results. We argue that this problem is largely based on the application of statistical relation measures that are not appropriate for genomic data analysis and demonstrate that the standard measures used for Genome-wide association studies or genomics linkage analysis bear a statistic bias. This may come from the violation of underlying assumptions (such as independence or stationarity) as well as from other conceptual limitations in the measures or relations, such as missing invariance with respect to coding or the inability to reflect latent factors. Attempts to introduce unbiased relation measures that avoid these limitations are usually computationally expensive and do not scale for large data sizes being typical for genomics applications.\n\nTo tackle these problems, we propose a straightforwardly computable relation measure called Linkage Probability (LP). This measure provides the posterior probability of a relation between two categorical data sets and considers potential biases from latent variables. We compare several aspects of popular relation measures through an illustrative example and human genomics data. We demonstrate that the application of LP to the analysis of Single Nucleotide Polymorphisms (SNP) reveals latent 3D steric effects within 1D SNP data, that approximate to chromatin loops captured by high resolution Hi-C maps.

bioinformatics↗

bioRxiv2018

Conserved and ubiquitous expression of piRNAs and PIWI genes in mollusks antedates the origin of somatic PIWI/piRNA expression to the root of bilaterians

PIWI proteins and a specific class of small non-coding RNAs, termed Piwi interacting RNAs (piRNAs), suppress transposon activity in animals on the transcriptional and post-transcriptional level, thus protecting genomes from detrimental insertion mutagenesis. While in vertebrates the PIWI/piRNA system appears to be restricted to the germline, somatic expression of piRNAs directed against transposons is widespread in arthropods, likely representing the ancestral state for this phylum. Here, we show that somatic expression of PIWI genes and piRNAs directed against transposons is conserved in mollusks, suggesting that somatic PIWI/piRNA expression was already realized in an early bilaterian ancestor. We further describe lineage specific adaptations regarding transposon composition of piRNA clusters and show that different piRNA clusters are dynamically expressed during oyster development. Finally, bioinformatics analyses suggest that different populations of piRNAs participate in the ping-pong amplification loop in a tissue specific manner.

evolutionary biology↗

bioRxiv2017

unitas: the universal tool for annotation of small RNAs

BackgroundNext generation sequencing is a key technique in small RNA biology research that has led to the discovery of functionally different classes of small non-coding RNAs in the past years. However, reliable annotation of the extensive amounts of small non-coding RNA data produced by high-throughput sequencing is time-consuming and requires robust bioinformatics expertise. Moreover, existing tools have a number of shortcomings including a lack of sensitivity under certain conditions, limited number of supported species or detectable sub-classes of small RNAs.\n\nResultsHere we introduce unitas, an out-of-the-box ready software for complete annotation of small RNA sequence datasets, supporting the wide range of species for which non-coding RNA reference sequences are available in the Ensembl databases (currently more than 800). unitas combines high quality annotation and numerous analysis features in a user-friendly manner. A complete annotation can be started with one simple shell command, making unitas particularly useful for researchers not having access to a bioinformatics facility. Noteworthy, the algorithms implemented in unitas are on par or even outperform comparable existing tools for small RNA annotation that base on available ncRNA sequence information.\n\nConclusionsunitas brings together annotation and analysis features that hitherto required the installation of numerous different bioinformatics tools which can pose a challenge for the non-expert user. With this, unitas overcomes the problem of read normalization. Moreover, the high quality of sequence annotation and analysis, paired with the ease of use, make unitas a valuable tool for researchers in all fields connected to small RNA biology.

bioinformatics↗