Publications

@article{nokey_88,

title = {Nanopore sequencing-derived methylation biomarker prediction for methylation-specific PCR in patients with head and neck squamous cell carcinoma},

author = {Daria Meyer and Anne Hennig and Anna-Bawany Hums and Orlando Guntinas-Lichius and Martina Schmitz and Manja Marz },

doi = {10.1186/s13148-025-01960-7},

year  = {2025},

date = {2025-09-13},

journal = {Clinical Epigenetics},

volume = {17},

abstract = {DNA methylation of CpG islands is altered in cancer cells. Hypermethylation of single CpG islands in the promoter regions of tumor-suppressor genes occurs already in the early stages of cancer. These methylation changes are cancer-type specific and therefore can serve as early cancer biomarker. Identifying good and reliable biomarkers is crucial for the development of diagnostic tests and their application in clinical practice and remains the most significant challenge to date.},

keywords = {cancer, nanopore, nucleic acid modifications},

pubstate = {published},

tppubtype = {article}

}

@article{nokey_73,

title = {diffONT: predicting methylation-specific PCR biomarkers based on nanopore sequencing data for clinical application},

author = {Daria Meyer and Emanuel Barth and Laura Wiehle and Manja Marz},

doi = {10.1101/2025.02.17.638597},

year  = {2025},

date = {2025-02-20},

urldate = {2025-02-20},

journal = {bioRxiv},

abstract = {DNA methylation is known to act as biomarker applicable for clinical diagnostics, especially in cancer detection. Methylation-specific PCR (MSP) is a widely used approach to screen patient samples fast and efficiently for differential methylation. During MSP, methylated regions are selectively amplified with specific primers. With nanopore sequencing, knowledge about DNA methylation is generated during direct DNA sequencing, without any need for pretreatment of the DNA. Multiple methods, mainly developed for whole-genome bisulfite sequencing (WGBS) data, exist to predict differentially methylated regions (DMRs) in the genome. However, the predicted DMRs are often very large, and not sufficiently discriminating to generate meaningful results in MSP creating a gap between theoretical cancer marker research and practical application, as no tool currently provides methylation difference predictions tailored for PCR-based diagnostics. Here we present diffONT, which predicts differentially methylated primer regions, directly suitable for MSP primer design and thus allowing a direct translation into practical approaches. diffONT takes into account (i) the specific length of primer and amplicon regions, (ii) the fact that one condition should be unmethylated, and (iii) a minimal required amount of differentially methylated cytosines within the primer regions. Based on two nanopore sequencing data sets we compared the results of diffONT to metilene, DSS and pycoMeth. We show that the regions predicted by diffONT are more specific towards hypermethylated regions and more usable for MSP. diffONT accelerates the design of methylation-specific diagnostic assays, bridging the gap between theoretical research and clinical application.Competing Interest Statement. The authors have declared no competing interest.},

keywords = {cancer, DNA / genomics, nanopore, nucleic acid modifications, software},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Unlocking the Full Potential of Nanopore Sequencing: Tips, Tricks, and Advanced Data Analysis Techniques},

author = {Daria Meyer and Winfried Göttsch and Jannes Spangenberg and Bettina Stieber and Sebastian Krautwurst and Martin Hoelzer and Christian Brandt and Joerg Linde and Christian {Höner zu Siederdissen} and Akash Srivastava and Milena Zarkovic and Damian Wollny and Manja Marz},

doi = {10.1101/2023.12.06.570356},

year  = {2025},

date = {2025-01-27},

urldate = {2025-01-27},

journal = {bioRxiv},

abstract = {Nucleic acid sequencing is the process of identifying the sequence of DNA or RNA, with DNA used for genomes and RNA for transcriptomes. Deciphering this information has the potential to greatly advance our understanding of genomic features and cellular functions. In comparison to other available sequencing methods, nanopore sequencing stands out due to its unique advantages of processing long nucleic acid strands in real time, within a small portable device, enabling the rapid analysis of samples in diverse settings. Evolving over the past decade, nanopore sequencing remains in a state of ongoing development and refinement, resulting in persistent challenges in protocols and technology. This article employs an interdisciplinary approach, evaluating experimental and computational methods to address critical gaps in our understanding in order to maximize the information gain from this advancing technology. Here we present both overview and analysis of all aspects of nanopore sequencing by providing statistically supported insights. Thus, we aim to provide fresh perspectives on nanopore sequencing and give comprehensive guidelines for the diverse challenges that frequently impede optimal experimental outcomes.},

keywords = {differential expression analysis, DNA / genomics, nanopore, nucleic acid modifications},

pubstate = {published},

tppubtype = {article}

}

@article{nokey_79,

title = {The RMaP challenge of predicting RNA modifications by nanopore sequencing},

author = {Jannes Spangenberg and Stefan Mündnich and Anne Busch and Stefan Pastore and Anna Wierczeiko and Winfried Goettsch and Vincent Dietrich and Leszek P. Pryszcz and Sonia Cruciani and Eva Maria Novoa and Kandarp Joshi and Ranjan Perera and Salvatore Di Giorgio and Paola Arrubarrena and Irem Tellioglu and Chi-Lam Poon and Yuk Kei Wan and Jonathan Göke and Andreas Hildebrandt and Christoph Dieterich and Mark Helm and Manja Marz and Susanne Gerber and Nicolo Alagna},

doi = {10.1038/s42004-025-01507-0},

year  = {2024},

date = {2024-12-04},

urldate = {2024-12-04},

journal = {Communications Chemistry},

volume = {8},

issue = {1},

abstract = {The field of epitranscriptomics is undergoing a technology-driven revolution. During past decades, RNA modifications like N6-methyladenosine (m6A), pseudouridine (ψ), and 5-methylcytosine (m5C) became acknowledged for playing critical roles in cellular processes. Direct RNA sequencing by Oxford Nanopore Technologies (ONT) enabled the detection of modifications in native RNA, by detecting noncanonical RNA nucleosides properties in raw data. Consequently, the field’s cutting edge has a heavy component in computer science, opening new avenues of cooperation across the community, as exchanging data is as impactful as exchanging samples. Therefore, we seize the occasion to bring scientists together within the RNA Modification and Processing (RMaP) challenge to advance solutions for RNA modification detection and discuss ideas, problems and approaches. We show several computational methods to detect the most researched mRNA modifications (m6A, ψ, and m5C). Results demonstrate that a low prediction error and a high prediction accuracy can be achieved on these modifications across different approaches and algorithms. The RMaP challenge marks a substantial step towards improving algorithms’ comparability, reliability, and consistency in RNA modification prediction. It points out the deficits in this young field that need to be addressed in further challenges.},

keywords = {machine learning, nanopore, nucleic acid modifications, RNA / transcriptomics},

pubstate = {published},

tppubtype = {article}

}

@article{nokey_74,

title = {Nanopore sequencing enables novel detection of deuterium incorporation in DNA},

author = {Christian {Höner zu Siederdissen} and Jannes Spangenberg and Kevin Bisdorf and Sebastian Krautwurst and Akash Srivastava and Manja Marz and Martin Taubert},

doi = {10.1016/j.csbj.2024.09.027},

year  = {2024},

date = {2024-10-03},

urldate = {2024-10-03},

journal = {Computational and Structural Biotechnology Journal},

volume = {23},

abstract = {Identifying active microbes is crucial to understand their role in ecosystem functions. Metabolic labeling with heavy, non-radioactive isotopes, i.e., stable isotope probing (SIP), can track active microbes by detecting heavy isotope incorporation in biomolecules such as DNA. However, the detection of heavy isotope-labeled nucleotides directly during sequencing has, to date, not been achieved. In this study, Oxford nanopore sequencing was utilized to detect heavy isotopes incorporation in DNA molecules. Two isotopes widely used in SIP experiments were employed to label a bacterial isolate: deuterium (D, as D2O) and carbon-13 (13C, as glucose). We hypothesize that labeled DNA is distinguishable from unlabeled DNA by changes in the nanopore signal. To verify this distinction, we employed a Bayesian classifier trained on signal distributions of short oligonucleotides (k-mers) from labeled and unlabeled sequencing reads. Our results show a clear distinction between D-labeled and unlabeled reads, based on changes in median and median absolute deviation (MAD) of the nanopore signals for different k-mers. In contrast, 13C-labeled DNA cannot be distinguished from unlabeled DNA. For D, the model employed correctly predicted more than 85% of the reads. Even when metabolic labeling was conducted with only 30% D2O, 80% of the obtained reads were correctly classified with a 5% false discovery rate. Our work demonstrates the feasibility of direct detection of deuterium incorporation in DNA molecules during Oxford nanopore sequencing. This finding represents a first step in establishing the combined use of nanopore sequencing and SIP for tracking active organisms in microbial ecology.},

keywords = {bacteria, DNA / genomics, machine learning, metagenomics, nanopore, nucleic acid modifications},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Magnipore: Prediction of differential single nucleotide changes in the Oxford Nanopore Technologies sequencing signal of SARS-CoV-2 samples},

author = {Jannes Spangenberg and Christian {Höner zu Siederdissen} and Milena Žarković and Sandra Triebel and Ruben Rose and Christina Martínez Christophersen and Lea Paltzow and Mohsen M. Hegab and Anna Wansorra and Akash Srivastava and Andi Krumbholz and Manja Marz},

doi = {10.1101/2023.03.17.533105},

year  = {2023},

date = {2023-03-17},

urldate = {2023-03-17},

journal = {bioRxiv},

abstract = {Oxford Nanopore Technologies (ONT) allows direct sequencing of ribonucleic acids (RNA) and, in addition, detection of possible RNA modifications due to deviations from the expected ONT signal. The software available so far for this purpose can only detect a small number of modifications. Alternatively, two samples can be compared for different RNA modifications. We present Magnipore, a novel tool to search for significant signal shifts between samples of Oxford Nanopore data from similar or related species. Magnipore classifies them into mutations and potential modifications. We use Magnipore to compare SARS-CoV-2 samples. Included were representatives of the early 2020s Pango lineages (n=6), samples from Pango lineages B.1.1.7 (n=2, Alpha), B.1.617.2 (n=1, Delta), and B.1.529 (n=7, Omicron). Magnipore utilizes position-wise Gaussian distribution models and a comprehensible significance threshold to find differential signals. In the case of Alpha and Delta, Magnipore identifies 55 detected mutations and 15 sites that hint at differential modifications. We predicted potential virus-variant and variant-group-specific differential modifications. Magnipore contributes to advancing RNA modification analysis in the context of viruses and virus variants.},

keywords = {coronavirus, nanopore, nucleic acid modifications, RNA / transcriptomics, software, viruses},

pubstate = {published},

tppubtype = {article}

}

@article{Viehweger:19a,

title = {Direct RNA nanopore sequencing of full-length coronavirus genomes provides novel insights into structural variants and enables modification analysis.},

author = {Adrian Viehweger and Sebastian Krautwurst and Kevin Lamkiewicz and Ramakanth Madhugiri and John Ziebuhr and Martin Hölzer and Manja Marz},

doi = {10.1101/gr.247064.118},

year  = {2019},

date = {2019-08-22},

urldate = {2019-08-22},

journal = {Genome Res},

volume = {29},

pages = {1545-1554},

publisher = {Cold Spring Harbor Laboratory},

abstract = {Sequence analyses of RNA virus genomes remain challenging owing to the exceptional genetic plasticity of these viruses. Because of high mutation and recombination rates, genome replication by viral RNA-dependent RNA polymerases leads to populations of closely related viruses, so-called “quasispecies.” Standard (short-read) sequencing technologies are ill-suited to reconstruct large numbers of full-length haplotypes of (1) RNA virus genomes and (2) subgenome-length (sg) RNAs composed of noncontiguous genome regions. Here, we used a full-length, direct RNA sequencing (DRS) approach based on nanopores to characterize viral RNAs produced in cells infected with a human coronavirus. By using DRS, we were able to map the longest (∼26-kb) contiguous read to the viral reference genome. By combining Illumina and Oxford Nanopore sequencing, we reconstructed a highly accurate consensus sequence of the human coronavirus (HCoV)-229E genome (27.3 kb). Furthermore, by using long reads that did not require an assembly step, we were able to identify, in infected cells, diverse and novel HCoV-229E sg RNAs that remain to be characterized. Also, the DRS approach, which circumvents reverse transcription and amplification of RNA, allowed us to detect methylation sites in viral RNAs. Our work paves the way for haplotype-based analyses of viral quasispecies by showing the feasibility of intra-sample haplotype separation. Even though several technical challenges remain to be addressed to exploit the potential of the nanopore technology fully, our work illustrates that DRS may significantly advance genomic studies of complex virus populations, including predictions on long-range interactions in individual full-length viral RNA haplotypes.},

keywords = {assembly, coronavirus, nanopore, nucleic acid modifications, RNA / transcriptomics, viruses},

pubstate = {published},

tppubtype = {article}

}

@article{Lechner:13,

title = {The correlation of genome size and DNA methylation rate in metazoans},

author = {Marcus Lechner and Manja Marz and Christian Ihling and Andrea Sinz and Peter F Stadler and Veiko Krauss},

doi = {10.1007/s12064-012-0167-y},

year  = {2012},

date = {2012-11-07},

urldate = {2012-11-07},

journal = {Theory Biosci},

volume = {132},

pages = {47--60},

abstract = {Total DNA methylation rates are well known to vary widely between different metazoans. The phylogenetic distribution of this variation, however, has not been investigated systematically. We combine here publicly available data on methylcytosine content with the analysis of nucleotide compositions of genomes and transcriptomes of 78 metazoan species to trace the evolution of abundance and distribution of DNA methylation. The depletion of CpG and the associated enrichment of TpG and CpA dinucleotides are used to infer the intensity and localization of germline CpG methylation and to estimate its evolutionary dynamics. We observe a positive correlation of the relative methylation of CpG motifs with genome size. We tested this trend successfully by measuring total DNA methylation with LC/MS in orthopteran insects with very different genome sizes: house crickets, migratory locusts and meadow grasshoppers. We hypothesize that the observed correlation between methylation rate and genome size is due to a dependence of both variables from long-term effective population size and is driven by the accumulation of repetitive sequences that are typically methylated during periods of small population sizes. This process may result in generally methylated, large genomes such as those of jawed vertebrates. In this case, the emergence of a novel demethylation pathway and of novel reader proteins for methylcytosine may have enabled the usage of cytosine methylation for promoter-based gene regulation. On the other hand, persistently large populations may lead to a compression of the genome and to the loss of the DNA methylation machinery, as observed, e.g., in nematodes.},

keywords = {DNA / genomics, evolution, insects, nucleic acid modifications, phylogenetics},

pubstate = {published},

tppubtype = {article}

}