ORCID Profile
0000-0001-6587-6394
Current Organisations
Robert Koch Institute
,
Freie Universität Berlin
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Publisher: Cold Spring Harbor Laboratory
Date: 30-03-2023
DOI: 10.1101/2023.03.29.534691
Abstract: Direct RNA sequencing (dRNA-seq) on the Oxford Nanopore Technologies (ONT) platforms can produce reads covering up to full-length gene transcripts while containing decipherable information about RNA base modifications and poly-A tail lengths. Although many published studies have been exploring and expanding the potential of dRNA-seq, the sequencing accuracy and error patterns remain understudied. We present the first comprehensive evaluation of accuracy and systematic errors in dRNA-seq data from erse species, as well as synthetic RNA. Deletions significantly outnumbered mismatches/insertions, while the median read accuracy exhibited species-level variation. In addition to homopolymer errors, we observed systematic biases across nucleotides and heteropolymeric motifs in all species. In general, cytosine/uracil-rich regions were more likely to be erroneous than guanines/adenines. Moreover, the systematic errors were strongly dependent on local sequence contexts. By examining raw signal data, we identified underlying signal-level features potentially associated with the error patterns. While read quality scores approximated error rates at base and read levels, failure to detect DNA adapters may lead to data loss. By comparing distinct basecallers, we reason that some sequencing errors are attributable to signal insufficiency rather than algorithmic (base-calling) artefacts. Lastly, we discuss the implications of such error patterns for downstream applications of dRNA-seq data.
Publisher: Elsevier BV
Date: 09-2021
Publisher: Springer Science and Business Media LLC
Date: 28-03-2022
DOI: 10.1038/S41594-022-00746-2
Abstract: RNA dimerization is the noncovalent association of two human immunodeficiency virus-1 (HIV-1) genomes. It is a conserved step in the HIV-1 life cycle and assumed to be a prerequisite for binding to the viral structural protein Pr55 Gag during genome packaging. Here, we developed functional analysis of RNA structure-sequencing (FARS-seq) to comprehensively identify sequences and structures within the HIV-1 5′ untranslated region (UTR) that regulate this critical step. Using FARS-seq, we found nucleotides important for dimerization throughout the HIV-1 5′ UTR and identified distinct structural conformations in monomeric and dimeric RNA. In the dimeric RNA, key functional domains, such as stem-loop 1 (SL1), polyadenylation signal (polyA) and primer binding site (PBS), folded into independent structural motifs. In the monomeric RNA, SL1 was reconfigured into long- and short-range base pairings with polyA and PBS, respectively. We show that these interactions disrupt genome packaging, and additionally show that the PBS–SL1 interaction unexpectedly couples the PBS with dimerization and Pr55 Gag binding. Altogether, our data provide insights into late stages of HIV-1 life cycle and a mechanistic explanation for the link between RNA dimerization and packaging.
Publisher: Oxford University Press (OUP)
Date: 05-03-2018
DOI: 10.1093/NAR/GKY152
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 11-2022
Publisher: PeerJ
Date: 22-07-2019
DOI: 10.7717/PEERJ.7053
Abstract: Muscle fibre cross-sectional area (CSA) is an important biomedical measure used to determine the structural composition of skeletal muscle, and it is relevant for tackling research questions in many different fields of research. To date, time consuming and tedious manual delineation of muscle fibres is often used to determine the CSA. Few methods are able to automatically detect muscle fibres in muscle fibre cross-sections to quantify CSA due to challenges posed by variation of brightness and noise in the staining images. In this paper, we introduce the supervised learning-computer vision combined pipeline (SLCV), a robust semi-automatic pipeline for muscle fibre detection, which combines supervised learning (SL) with computer vision (CV). SLCV is adaptable to different staining methods and is quickly and intuitively tunable by the user. We are the first to perform an error analysis with respect to cell count and area, based on which we compare SLCV to the best purely CV-based pipeline in order to identify the contribution of SL and CV steps to muscle fibre detection. Our results obtained on 27 fluorescence-stained cross-sectional images of varying staining quality suggest that combining SL and CV performs significantly better than both SL-based and CV-based methods with regards to both the cell separation- and the area reconstruction error. Furthermore, applying SLCV to our test set images yielded fibre detection results of very high quality, with average sensitivity values of 0.93 or higher on different cluster sizes and an average Dice similarity coefficient of 0.9778.
Publisher: Public Library of Science (PLoS)
Date: 11-04-2019
Publisher: Springer Science and Business Media LLC
Date: 03-08-2015
DOI: 10.1038/NMETH.3490
Abstract: RNA regulates many biological processes however, identifying functional RNA sequences and structures is complex and time-consuming. We introduce a method, mutational interference mapping experiment (MIME), to identify, at single-nucleotide resolution, the primary sequence and secondary structures of an RNA molecule that are crucial for its function. MIME is based on random mutagenesis of the RNA target followed by functional selection and next-generation sequencing. Our analytical approach allows the recovery of quantitative binding parameters and permits the identification of base-pairing partners directly from the sequencing data. We used this method to map the binding site of the human immunodeficiency virus-1 (HIV-1) Pr55(Gag) protein on the viral genomic RNA in vitro, and showed that, by analyzing permitted base-pairing patterns, we could model RNA structure motifs that are crucial for protein binding.
No related grants have been discovered for Max von Kleist.