E-Mail: sandra.triebel@uni-jena.de
Room: 4004
Phone: +49-3641-9-46485
Publications
2026
Triebel, Sandra; Lamkiewicz, Kevin; Eulenfeld, Tom; Marz, Manja
Reducing haystacks to needles – ViralClust: A Nextflow pipeline to cluster viral sequences Journal Article
In: bioRxiv, no. 2026.01.30.702815, 2026.
@article{nokey_100,
title = {Reducing haystacks to needles – ViralClust: A Nextflow pipeline to cluster viral sequences},
author = {Sandra Triebel and Kevin Lamkiewicz and Tom Eulenfeld and Manja Marz},
doi = {10.64898/2026.01.30.702815},
year = {2026},
date = {2026-06-11},
journal = {bioRxiv},
number = {2026.01.30.702815},
abstract = {Background The rapid accumulation of viral genome sequences presents major challenges for downstream analysis tools, including tools for multiple sequence alignments, phylogeny, and genome/alignment visualization, due to computational constraints and sampling biases caused by outbreak-driven over-representation. Selecting representative genomes through clustering offers a principled alternative to random subsampling, yet choosing appropriate clustering strategies remains non-trivial and context dependent.
Results Here, we present ViralClust, a modular Nextflow pipeline for bias-aware representative selection from large viral genome datasets. ViralClust integrates five distinct clustering algorithms (CD-HIT-EST, SUMACLUST, VSEARCH, MMSeqs2, and HDBSCAN) within a unified workflow, enabling direct comparison of clustering outcomes and flexible adaptation to diverse biological questions, considering a balanced phylogenic distribution of the selected sequences. We evaluated ViralClust on six RNA and DNA virus datasets ranging from 632 to 156,586 sequences and spanning genome lengths from 890 to 197,185 nucleotides. Across all datasets, clustering reduced dataset size by ∼95 % or more while preserving genetic diversity across species, genera, and families, and effectively mitigating biases introduced by outbreaks, partial genomes, and sequence orientation artifacts.
Conclusions By supporting whole-genome clustering and scalable representative selection, ViralClust enables efficient and reproducible downstream analyses that would otherwise be computationally infeasible. Our framework provides a flexible foundation for large-scale viral genomics and supports future applications in comparative analysis and virus classification.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Background The rapid accumulation of viral genome sequences presents major challenges for downstream analysis tools, including tools for multiple sequence alignments, phylogeny, and genome/alignment visualization, due to computational constraints and sampling biases caused by outbreak-driven over-representation. Selecting representative genomes through clustering offers a principled alternative to random subsampling, yet choosing appropriate clustering strategies remains non-trivial and context dependent.
Results Here, we present ViralClust, a modular Nextflow pipeline for bias-aware representative selection from large viral genome datasets. ViralClust integrates five distinct clustering algorithms (CD-HIT-EST, SUMACLUST, VSEARCH, MMSeqs2, and HDBSCAN) within a unified workflow, enabling direct comparison of clustering outcomes and flexible adaptation to diverse biological questions, considering a balanced phylogenic distribution of the selected sequences. We evaluated ViralClust on six RNA and DNA virus datasets ranging from 632 to 156,586 sequences and spanning genome lengths from 890 to 197,185 nucleotides. Across all datasets, clustering reduced dataset size by ∼95 % or more while preserving genetic diversity across species, genera, and families, and effectively mitigating biases introduced by outbreaks, partial genomes, and sequence orientation artifacts.
Conclusions By supporting whole-genome clustering and scalable representative selection, ViralClust enables efficient and reproducible downstream analyses that would otherwise be computationally infeasible. Our framework provides a flexible foundation for large-scale viral genomics and supports future applications in comparative analysis and virus classification.
Results Here, we present ViralClust, a modular Nextflow pipeline for bias-aware representative selection from large viral genome datasets. ViralClust integrates five distinct clustering algorithms (CD-HIT-EST, SUMACLUST, VSEARCH, MMSeqs2, and HDBSCAN) within a unified workflow, enabling direct comparison of clustering outcomes and flexible adaptation to diverse biological questions, considering a balanced phylogenic distribution of the selected sequences. We evaluated ViralClust on six RNA and DNA virus datasets ranging from 632 to 156,586 sequences and spanning genome lengths from 890 to 197,185 nucleotides. Across all datasets, clustering reduced dataset size by ∼95 % or more while preserving genetic diversity across species, genera, and families, and effectively mitigating biases introduced by outbreaks, partial genomes, and sequence orientation artifacts.
Conclusions By supporting whole-genome clustering and scalable representative selection, ViralClust enables efficient and reproducible downstream analyses that would otherwise be computationally infeasible. Our framework provides a flexible foundation for large-scale viral genomics and supports future applications in comparative analysis and virus classification.
Muston, Philippa; Triebel, Sandra; Nawrocki, Eric; Ontiveros-Palacios, Nancy; Jandalala, Isaac; Sweeney, Blake; Bateman, Alex; Marz, Manja; Petrov, Anton I.; Madrigal, Pedro
Viral non-coding RNA structure annotation and API-based data retrieval with Rfam and R2DT Journal Article
In: bioRxiv, no. 2026.05.10.724034, 2026.
@article{nokey_99,
title = {Viral non-coding RNA structure annotation and API-based data retrieval with Rfam and R2DT},
author = {Philippa Muston and Sandra Triebel and Eric Nawrocki and Nancy Ontiveros-Palacios and Isaac Jandalala and Blake Sweeney and Alex Bateman and Manja Marz and Anton I. Petrov and Pedro Madrigal},
doi = {10.64898/2026.05.10.724034},
year = {2026},
date = {2026-05-14},
journal = {bioRxiv},
number = {2026.05.10.724034},
abstract = {Rfam is a comprehensive database of non-coding RNA (ncRNA) families providing curated sequence alignments, consensus secondary structures, and covariance models for thousands of RNA families. The database is essential for identifying structured non-coding RNAs in newly sequenced genomes and understanding RNA structure-function relationships. Here we present computational protocols for automated ncRNA annotation of viral genomes, and for programmatic interaction with Rfam through its RESTful API. We showcase genome-wide RNA structure visualization from a genome sequence and from a multiple sequence alignment by generating comprehensive 2D structure diagrams using newly developed features in R2DT. We also present practical examples for retrieving family metadata, downloading alignments, accessing secondary structures, and searching user sequences from the Rfam API. These methods enable researchers in virology and RNA biology to integrate Rfam data into custom bioinformatics pipelines, comparative analyses, and machine learning workflows.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Rfam is a comprehensive database of non-coding RNA (ncRNA) families providing curated sequence alignments, consensus secondary structures, and covariance models for thousands of RNA families. The database is essential for identifying structured non-coding RNAs in newly sequenced genomes and understanding RNA structure-function relationships. Here we present computational protocols for automated ncRNA annotation of viral genomes, and for programmatic interaction with Rfam through its RESTful API. We showcase genome-wide RNA structure visualization from a genome sequence and from a multiple sequence alignment by generating comprehensive 2D structure diagrams using newly developed features in R2DT. We also present practical examples for retrieving family metadata, downloading alignments, accessing secondary structures, and searching user sequences from the Rfam API. These methods enable researchers in virology and RNA biology to integrate Rfam data into custom bioinformatics pipelines, comparative analyses, and machine learning workflows.
Triebel, Sandra; Eulenfeld, Tom; Ontiveros-Palacios, Nancy; Sweeney, Blake; Tautz, Norbert; Marz, Manja
First full-genome alignment representative for the genus Pestivirus Journal Article
In: RNA, vol. 32, iss. 3, pp. 311-327, 2026.
@article{nokey_77,
title = {First full-genome alignment representative for the genus \textit{Pestivirus}},
author = {Sandra Triebel and Tom Eulenfeld and Nancy Ontiveros-Palacios and Blake Sweeney and Norbert Tautz and Manja Marz},
doi = {10.1261/rna.080732.125},
year = {2026},
date = {2026-03-01},
urldate = {2025-05-27},
journal = {RNA},
volume = {32},
issue = {3},
pages = {311-327},
abstract = {Members of the genus Pestivirus (family Flaviviridae) comprise economically important livestock pathogens like classical swine fever virus (CSFV) and bovine viral diarrhea virus (BVDV). Research over recent years revealed 11 recognized and eight proposed species. The single-stranded, positive-sense RNA genome encodes one large polyprotein that is processed by viral and cellular proteases into 12 mature proteins. In addition to its protein-coding function, the RNA genome contains secondary structures critical for various stages of the viral life cycle. Some of these structures, including the internal ribosome entry site (IRES) and a 3′ stem–loop, essential for genome replication, have been studied in individual pestiviruses. Here, we present the first genome-wide multiple sequence alignment comprising all known pestivirus species (accepted and tentative) and a comprehensive analysis of phylogenetically conserved RNA secondary structures across the genus. Well-characterized elements, such as a 5′ stem–loop, the IRES, and the 3′ stem–loop SL I, were conserved in all pestiviruses, whereas additional 3′ untranslated region structures were conserved only in subsets of species. We identified 29 novel conserved RNA secondary structures within the protein-coding region, with thus far unresolved functional importance. A miR-17 binding site, previously described in species A, B, and C, was detected in ten additional species but absent in species K, S, Q, and R. We identified a putative long-distance RNA interaction between the IRES and the 3′ end of the genome. Together, these findings and the comprehensive MSA of all 19 pestivirus species provide a valuable resource for future research and diagnostic applications.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Members of the genus Pestivirus (family Flaviviridae) comprise economically important livestock pathogens like classical swine fever virus (CSFV) and bovine viral diarrhea virus (BVDV). Research over recent years revealed 11 recognized and eight proposed species. The single-stranded, positive-sense RNA genome encodes one large polyprotein that is processed by viral and cellular proteases into 12 mature proteins. In addition to its protein-coding function, the RNA genome contains secondary structures critical for various stages of the viral life cycle. Some of these structures, including the internal ribosome entry site (IRES) and a 3′ stem–loop, essential for genome replication, have been studied in individual pestiviruses. Here, we present the first genome-wide multiple sequence alignment comprising all known pestivirus species (accepted and tentative) and a comprehensive analysis of phylogenetically conserved RNA secondary structures across the genus. Well-characterized elements, such as a 5′ stem–loop, the IRES, and the 3′ stem–loop SL I, were conserved in all pestiviruses, whereas additional 3′ untranslated region structures were conserved only in subsets of species. We identified 29 novel conserved RNA secondary structures within the protein-coding region, with thus far unresolved functional importance. A miR-17 binding site, previously described in species A, B, and C, was detected in ten additional species but absent in species K, S, Q, and R. We identified a putative long-distance RNA interaction between the IRES and the 3′ end of the genome. Together, these findings and the comprehensive MSA of all 19 pestivirus species provide a valuable resource for future research and diagnostic applications.
2025
Eulenfeld, Tom; Triebel, Sandra; Marz, Manja
AnchoRNA: Full virus genome alignments through conserved anchor regions Journal Article
In: bioRxiv, 2025.
@article{nokey_67,
title = {AnchoRNA: Full virus genome alignments through conserved anchor regions},
author = {Tom Eulenfeld and Sandra Triebel and Manja Marz},
doi = {10.1101/2025.01.30.635689},
year = {2025},
date = {2025-12-15},
urldate = {2025-02-01},
journal = {bioRxiv},
abstract = {Multiple sequence alignment of full viral genomes can be challenging due to factors such as long sequences, large insertions/deletions (spanning several 100 nucleotides), large number of sequences, sequence divergence, and high computational complexity in particular when computing alignments based on RNA secondary structures. Standard alignment methods often face these issues, in particular when processing highly variable sequences or when specific phylogenetic analysis is required on selected subsequences.
We present an algorithm to determine high quality anchors that define partitions of sequences and guide the alignment of viral genomes to respect well conserved, and therefore functionally significant, regions. This new approach is implemented in the Python-based command line tool AnchoRNA, which is designed to identify conserved regions, or anchors, within coding sequences. By default, anchors are searched in translated coding sequences accounting for high mutation rates in viral genomes. AnchoRNA enhances the accuracy and efficiency of full-genome alignment by focusing on these crucial conserved regions. AnchoRNA guided alignments are systematically compared to the results of 3 alignment programs. Utilizing a dataset of 55 representative Pestivirus genomes, AnchoRNA identified 55 anchors that are used for guiding the alignment process. The incorporation of these anchors led to improvements across tested alignment tools, highlighting the effectiveness of AnchoRNA in enhancing alignment quality, especially in viral genomes.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Multiple sequence alignment of full viral genomes can be challenging due to factors such as long sequences, large insertions/deletions (spanning several 100 nucleotides), large number of sequences, sequence divergence, and high computational complexity in particular when computing alignments based on RNA secondary structures. Standard alignment methods often face these issues, in particular when processing highly variable sequences or when specific phylogenetic analysis is required on selected subsequences.
We present an algorithm to determine high quality anchors that define partitions of sequences and guide the alignment of viral genomes to respect well conserved, and therefore functionally significant, regions. This new approach is implemented in the Python-based command line tool AnchoRNA, which is designed to identify conserved regions, or anchors, within coding sequences. By default, anchors are searched in translated coding sequences accounting for high mutation rates in viral genomes. AnchoRNA enhances the accuracy and efficiency of full-genome alignment by focusing on these crucial conserved regions. AnchoRNA guided alignments are systematically compared to the results of 3 alignment programs. Utilizing a dataset of 55 representative Pestivirus genomes, AnchoRNA identified 55 anchors that are used for guiding the alignment process. The incorporation of these anchors led to improvements across tested alignment tools, highlighting the effectiveness of AnchoRNA in enhancing alignment quality, especially in viral genomes.
We present an algorithm to determine high quality anchors that define partitions of sequences and guide the alignment of viral genomes to respect well conserved, and therefore functionally significant, regions. This new approach is implemented in the Python-based command line tool AnchoRNA, which is designed to identify conserved regions, or anchors, within coding sequences. By default, anchors are searched in translated coding sequences accounting for high mutation rates in viral genomes. AnchoRNA enhances the accuracy and efficiency of full-genome alignment by focusing on these crucial conserved regions. AnchoRNA guided alignments are systematically compared to the results of 3 alignment programs. Utilizing a dataset of 55 representative Pestivirus genomes, AnchoRNA identified 55 anchors that are used for guiding the alignment process. The incorporation of these anchors led to improvements across tested alignment tools, highlighting the effectiveness of AnchoRNA in enhancing alignment quality, especially in viral genomes.
Ontiveros-Palacios, Nancy; Cooke, Emma; Nawrocki, Eric P.; Triebel, Sandra; Marz, Manja; Rivas, Elena; Griffiths-Jones, Sam; Petrov, Anton I.; Bateman, Alex; Sweeney, Blake
Rfam 15: RNA families database in 2025 Journal Article
In: Nucleic Acids Research, 2025.
@article{nokey_67,
title = {Rfam 15: RNA families database in 2025},
author = {Nancy Ontiveros-Palacios and Emma Cooke and Eric P. Nawrocki and Sandra Triebel and Manja Marz and Elena Rivas and Sam Griffiths-Jones and Anton I. Petrov and Alex Bateman and Blake Sweeney},
doi = {10.1093/nar/gkae1023},
year = {2025},
date = {2025-01-06},
urldate = {2024-11-11},
journal = {Nucleic Acids Research},
abstract = {The Rfam database, a widely used repository of non-coding RNA families, has undergone significant updates in release 15.0. This paper introduces major improvements, including the expansion of Rfamseq to 26 106 genomes, a 76% increase, incorporating the latest UniProt reference proteomes and additional viral genomes. Sixty-five RNA families were enhanced using experimentally determined 3D structures, improving the accuracy of consensus secondary structures and annotations. R-scape covariation analysis was used to refine structural predictions in 26 families. Gene Ontology (GO) and Sequence Ontology annotations were comprehensively updated, increasing GO term coverage to 75% of families. The release adds 14 new Hepatitis C Virus RNA families and completes microRNA family synchronization with miRBase, resulting in 1603 microRNA families. New data types, including FULL alignments, have been implemented. Integration with APICURON for improved curator attribution and multiple website enhancements further improve user experience. These updates significantly expand Rfam’s coverage and improve annotation quality, reinforcing its critical role in RNA research, genome annotation and the development of machine learning models. Rfam is freely available at https://rfam.org.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The Rfam database, a widely used repository of non-coding RNA families, has undergone significant updates in release 15.0. This paper introduces major improvements, including the expansion of Rfamseq to 26 106 genomes, a 76% increase, incorporating the latest UniProt reference proteomes and additional viral genomes. Sixty-five RNA families were enhanced using experimentally determined 3D structures, improving the accuracy of consensus secondary structures and annotations. R-scape covariation analysis was used to refine structural predictions in 26 families. Gene Ontology (GO) and Sequence Ontology annotations were comprehensively updated, increasing GO term coverage to 75% of families. The release adds 14 new Hepatitis C Virus RNA families and completes microRNA family synchronization with miRBase, resulting in 1603 microRNA families. New data types, including FULL alignments, have been implemented. Integration with APICURON for improved curator attribution and multiple website enhancements further improve user experience. These updates significantly expand Rfam’s coverage and improve annotation quality, reinforcing its critical role in RNA research, genome annotation and the development of machine learning models. Rfam is freely available at https://rfam.org.
2024
Triebel, Sandra; Lamkiewicz, Kevin; Ontiveros, Nancy; Sweeney, Blake; Stadler, Peter F.; Petrov, Anton I.; Niepmann, Michael; Marz, Manja
Comprehensive survey of conserved RNA secondary structures in full-genome alignment of Hepatitis C virus Journal Article
In: Scientific Reports, vol. 14, iss. 1, 2024.
@article{nokey_62,
title = {Comprehensive survey of conserved RNA secondary structures in full-genome alignment of Hepatitis C virus},
author = {Sandra Triebel and Kevin Lamkiewicz and Nancy Ontiveros and Blake Sweeney and Peter F. Stadler and Anton I. Petrov and Michael Niepmann and Manja Marz},
doi = {10.1038/s41598-024-62897-0},
year = {2024},
date = {2024-07-02},
urldate = {2024-07-02},
journal = {Scientific Reports},
volume = {14},
issue = {1},
abstract = {Hepatitis C virus (HCV) is a plus-stranded RNA virus that often chronically infects liver hepatocytes and causes liver cirrhosis and cancer. These viruses replicate their genomes employing error-prone replicases. Thereby, they routinely generate a large ‘cloud’ of RNA genomes (quasispecies) which—by trial and error—comprehensively explore the sequence space available for functional RNA genomes that maintain the ability for efficient replication and immune escape. In this context, it is important to identify which RNA secondary structures in the sequence space of the HCV genome are conserved, likely due to functional requirements. Here, we provide the first genome-wide multiple sequence alignment (MSA) with the prediction of RNA secondary structures throughout all representative full-length HCV genomes. We selected 57 representative genomes by clustering all complete HCV genomes from the BV-BRC database based on k-mer distributions and dimension reduction and adding RefSeq sequences. We include annotations of previously recognized features for easy comparison to other studies. Our results indicate that mainly the core coding region, the C-terminal NS5A region, and the NS5B region contain secondary structure elements that are conserved beyond coding sequence requirements, indicating functionality on the RNA level. In contrast, the genome regions in between contain less highly conserved structures. The results provide a complete description of all conserved RNA secondary structures and make clear that functionally important RNA secondary structures are present in certain HCV genome regions but are largely absent from other regions. Full-genome alignments of all branches of Hepacivirus C are provided in the supplement.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Hepatitis C virus (HCV) is a plus-stranded RNA virus that often chronically infects liver hepatocytes and causes liver cirrhosis and cancer. These viruses replicate their genomes employing error-prone replicases. Thereby, they routinely generate a large ‘cloud’ of RNA genomes (quasispecies) which—by trial and error—comprehensively explore the sequence space available for functional RNA genomes that maintain the ability for efficient replication and immune escape. In this context, it is important to identify which RNA secondary structures in the sequence space of the HCV genome are conserved, likely due to functional requirements. Here, we provide the first genome-wide multiple sequence alignment (MSA) with the prediction of RNA secondary structures throughout all representative full-length HCV genomes. We selected 57 representative genomes by clustering all complete HCV genomes from the BV-BRC database based on k-mer distributions and dimension reduction and adding RefSeq sequences. We include annotations of previously recognized features for easy comparison to other studies. Our results indicate that mainly the core coding region, the C-terminal NS5A region, and the NS5B region contain secondary structure elements that are conserved beyond coding sequence requirements, indicating functionality on the RNA level. In contrast, the genome regions in between contain less highly conserved structures. The results provide a complete description of all conserved RNA secondary structures and make clear that functionally important RNA secondary structures are present in certain HCV genome regions but are largely absent from other regions. Full-genome alignments of all branches of Hepacivirus C are provided in the supplement.
2023
Hufsky, Franziska; Abecasis, Ana B.; Babaian, Artem; Beck, Sebastian; Brierley, Liam; Dellicour, Simon; Eggeling, Christian; Elena, Santiago F.; Gieraths, Udo; Ha, Anh D.; Harvey, Will; Jones, Terry C.; Lamkiewicz, Kevin; Lovate, Gabriel L.; Lücking, Dominik; Machyna, Martin; Nishimura, Luca; Nocke, Maximilian K.; Renard, Bernard Y.; Sakaguchi, Shoichi; Sakellaridi, Lygeri; Spangenberg, Jannes; Tarradas-Alemany, Maria; Triebel, Sandra; Vakulenko, Yulia; Wijesekara, Rajitha Yasas; González-Candelas, Fernando; Krautwurst, Sarah; Pérez-Cataluña, Alba; Randazzo, Walter; Sánchez, Gloria; Marz, Manja
The International Virus Bioinformatics Meeting 2023 Journal Article
In: Viruses, vol. 15, iss. 10, 2023, ISSN: 1999-4915.
@article{nokey_47,
title = {The International Virus Bioinformatics Meeting 2023},
author = {Franziska Hufsky and Ana B. Abecasis and Artem Babaian and Sebastian Beck and Liam Brierley and Simon Dellicour and Christian Eggeling and Santiago F. Elena and Udo Gieraths and Anh D. Ha and Will Harvey and Terry C. Jones and Kevin Lamkiewicz and Gabriel L. Lovate and Dominik Lücking and Martin Machyna and Luca Nishimura and Maximilian K. Nocke and Bernard Y. Renard and Shoichi Sakaguchi and Lygeri Sakellaridi and Jannes Spangenberg and Maria Tarradas-Alemany and Sandra Triebel and Yulia Vakulenko and Rajitha Yasas Wijesekara and Fernando González-Candelas and Sarah Krautwurst and Alba Pérez-Cataluña and Walter Randazzo and Gloria Sánchez and Manja Marz},
doi = {10.3390/v15102031},
issn = {1999-4915},
year = {2023},
date = {2023-09-30},
urldate = {2023-09-30},
journal = {Viruses},
volume = {15},
issue = {10},
abstract = {The 2023 International Virus Bioinformatics Meeting was held in Valencia, Spain, from 24–26 May 2023, attracting approximately 180 participants worldwide. The primary objective of the conference was to establish a dynamic scientific environment conducive to discussion, collaboration, and the generation of novel research ideas. As the first in-person event following the SARS-CoV-2 pandemic, the meeting facilitated highly interactive exchanges among attendees. It served as a pivotal gathering for gaining insights into the current status of virus bioinformatics research and engaging with leading researchers and emerging scientists. The event comprised eight invited talks, 19 contributed talks, and 74 poster presentations across eleven sessions spanning three days. Topics covered included machine learning, bacteriophages, virus discovery, virus classification, virus visualization, viral infection, viromics, molecular epidemiology, phylodynamic analysis, RNA viruses, viral sequence analysis, viral surveillance, and metagenomics. This report provides rewritten abstracts of the presentations, a summary of the key research findings, and highlights shared during the meeting.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The 2023 International Virus Bioinformatics Meeting was held in Valencia, Spain, from 24–26 May 2023, attracting approximately 180 participants worldwide. The primary objective of the conference was to establish a dynamic scientific environment conducive to discussion, collaboration, and the generation of novel research ideas. As the first in-person event following the SARS-CoV-2 pandemic, the meeting facilitated highly interactive exchanges among attendees. It served as a pivotal gathering for gaining insights into the current status of virus bioinformatics research and engaging with leading researchers and emerging scientists. The event comprised eight invited talks, 19 contributed talks, and 74 poster presentations across eleven sessions spanning three days. Topics covered included machine learning, bacteriophages, virus discovery, virus classification, virus visualization, viral infection, viromics, molecular epidemiology, phylodynamic analysis, RNA viruses, viral sequence analysis, viral surveillance, and metagenomics. This report provides rewritten abstracts of the presentations, a summary of the key research findings, and highlights shared during the meeting.
Triebel, Sandra; Sachse, Konrad; Weber, Michael; Heller, Martin; Diezel, Celia; Hölzer, Martin; Schnee, Christiane; Marz, Manja
De novo genome assembly resolving repetitive structures enables genomic analysis of 35 European Mycoplasmopsis bovis strains Journal Article
In: BMC Genomics, vol. 24, iss. 1, no. 548, 2023, ISBN: 1471-2164.
@article{nokey_44,
title = {\textit{De novo} genome assembly resolving repetitive structures enables genomic analysis of 35 European \textit{Mycoplasmopsis bovis} strains},
author = {Sandra Triebel and Konrad Sachse and Michael Weber and Martin Heller and Celia Diezel and Martin Hölzer and Christiane Schnee and Manja Marz },
doi = {10.1186/s12864-023-09618-5},
isbn = {1471-2164},
year = {2023},
date = {2023-09-16},
urldate = {2023-09-16},
journal = {BMC Genomics},
volume = {24},
number = {548},
issue = {1},
abstract = {Mycoplasmopsis (M.) bovis, the agent of mastitis, pneumonia, and arthritis in cattle, harbors a small genome of approximately 1 Mbp. Combining data from Illumina and Nanopore technologies, we sequenced and assembled the genomes of 35 European strains and isolate DL422_88 from Cuba. While the high proportion of repetitive structures in M. bovis genomes represent a particular challenge, implementation of our own pipeline Mycovista (available on GitHub www.github.com/sandraTriebel/mycovista ) in a hybrid approach enabled contiguous assembly of the genomes and, consequently, improved annotation rates considerably. To put our European strain panel in a global context, we analyzed the new genome sequences together with 175 genome assemblies from public databases. Construction of a phylogenetic tree based on core genes of these 219 strains revealed a clustering pattern according to geographical origin, with European isolates positioned on clades 4 and 5. Genomic data allowing assignment of strains to tissue specificity or certain disease manifestations could not be identified. Seven strains isolated from cattle with systemic circular condition (SCC), still a largely unknown manifestation of M. bovis disease, were located on both clades 4 and 5. Pairwise association analysis revealed 108 genomic elements associated with a particular clade of the phylogenetic tree. Further analyzing these hits, 25 genes are functionally annotated and could be linked to a M. bovis protein, e.g. various proteases and nucleases, as well as ten variable surface lipoproteins (Vsps) and other surface proteins. These clade-specific genes could serve as useful markers in epidemiological and clinical surveys.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Mycoplasmopsis (M.) bovis, the agent of mastitis, pneumonia, and arthritis in cattle, harbors a small genome of approximately 1 Mbp. Combining data from Illumina and Nanopore technologies, we sequenced and assembled the genomes of 35 European strains and isolate DL422_88 from Cuba. While the high proportion of repetitive structures in M. bovis genomes represent a particular challenge, implementation of our own pipeline Mycovista (available on GitHub www.github.com/sandraTriebel/mycovista ) in a hybrid approach enabled contiguous assembly of the genomes and, consequently, improved annotation rates considerably. To put our European strain panel in a global context, we analyzed the new genome sequences together with 175 genome assemblies from public databases. Construction of a phylogenetic tree based on core genes of these 219 strains revealed a clustering pattern according to geographical origin, with European isolates positioned on clades 4 and 5. Genomic data allowing assignment of strains to tissue specificity or certain disease manifestations could not be identified. Seven strains isolated from cattle with systemic circular condition (SCC), still a largely unknown manifestation of M. bovis disease, were located on both clades 4 and 5. Pairwise association analysis revealed 108 genomic elements associated with a particular clade of the phylogenetic tree. Further analyzing these hits, 25 genes are functionally annotated and could be linked to a M. bovis protein, e.g. various proteases and nucleases, as well as ten variable surface lipoproteins (Vsps) and other surface proteins. These clade-specific genes could serve as useful markers in epidemiological and clinical surveys.
Spangenberg, Jannes; zu Siederdissen, Christian Höner; Žarković, Milena; Triebel, Sandra; Rose, Ruben; Christophersen, Christina Martínez; Paltzow, Lea; Hegab, Mohsen M.; Wansorra, Anna; Srivastava, Akash; Krumbholz, Andi; Marz, Manja
Magnipore: Prediction of differential single nucleotide changes in the Oxford Nanopore Technologies sequencing signal of SARS-CoV-2 samples Journal Article
In: bioRxiv, 2023.
@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 = {},
pubstate = {published},
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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.