Biology subjects

Diensthuber, G.

Publications and source records attributed to Diensthuber, G..

3 recordsLinked to original sources

bioRxiv2025

Long-read transcriptome-wide RNA structure maps using DMS-FIRST-seq

RNA modifications induce reverse transcription (RT) errors in an enzyme- and context-dependent manner, enabling transcriptome-wide mapping and RNA structure probing. We present FIRST-seq, a flexible, cost-effective nanopore cDNA method that avoids second-strand synthesis and PCR, making it compatible with any RT enzyme and enabling single-nucleotide resolution RT signature analysis. Benchmarking multiple RT enzymes and buffers identified conditions that reduce premature termination and enhance error detection. Coupled with DMS probing, FIRST-seq accurately detects m1A and m3C at unpaired sites, recapitulating known RNA structures in vitro and in vivo. FIRST-seq offers a versatile platform for profiling chemical-induced and natural RNA modifications using long-read sequencing.

molecular biology↗

bioRxiv2024

SeqTagger, a rapid and accurate tool to demultiplex direct RNA nanopore sequencing datasets

Nanopore direct RNA sequencing (DRS) enables direct measurement of RNA molecules, including their native RNA modifications, without prior conversion to cDNA. However, commercial methods for molecular barcoding of multiple DRS samples are lacking, and community-driven efforts, such as DeePlexiCon, are not compatible with newer RNA chemistry flowcells and the latest-generation GPU cards. To overcome these limitations, we introduce SeqTagger, a rapid and robust method that can demultiplex direct RNA sequencing datasets with 99% precision and 95% recall. We demonstrate the applicability of SeqTagger in both RNA002/R9.4 and RNA004/RNA chemistries and show its robust performance both for long and short RNA libraries, including custom libraries that do not contain standard poly-(A) tails, such as Nano-tRNAseq libraries. Finally, we demonstrate that increasing the multiplexing up to 96 barcodes yields highly accurate demultiplexing models. SeqTagger can be executed in a standalone manner or through the MasterOfPores NextFlow workflow. The availability of an efficient and simple multiplexing strategy improves the cost-effectiveness of this technology and facilitates the analysis of low-input biological samples.

genomics↗

bioRxiv2023

Enhanced detection of RNA modifications and mappability with high-accuracy nanopore RNA basecalling models

In recent years, nanopore direct RNA sequencing (DRS) has established itself as a valuable tool for studying the epitranscriptome, due to its ability to detect multiple modifications within the same full-length native RNA molecules. While RNA modifications can be identified in the form of systematic basecalling errors in DRS datasets, N6-methyladenosine (m6A) modifications produce relatively low errors compared to other RNA modifications, limiting the applicability of this approach to m6A sites that are modified at high stoichiometries. Here, we demonstrate that the use of alternative RNA basecalling models, trained with fully unmodified sequences, increases the error signal of m6A, leading to enhanced detection and improved sensitivity even at low stoichiometries. Moreover, we find that high-accuracy alternative RNA basecalling models can show up to 97% median basecalling accuracy, outperforming currently available RNA basecalling models, which show 91% median basecalling accuracy. Notably, the use of high-accuracy basecalling models is accompanied by a significant increase in the number of mapped reads -especially in shorter RNA fractions- and increased basecalling error signatures at pseudouridine ({Psi}) and N1-methylpseudouridine (m1{Psi}) modified sites. Overall, our work demonstrates that alternative RNA basecalling models can be used to improve the detection of RNA modifications, read mappability and basecalling accuracy in nanopore DRS datasets.

genomics↗