Viktoria Philine Wagner

All Publications

• Characterizing expression changes in noncoding RNAs during aging and heterochronic parabiosis across mouse tissues. Nature biotechnology Wagner, V., Kern, F., Hahn, O., Schaum, N., Ludwig, N., Fehlmann, T., Engel, A., Henn, D., Rishik, S., Isakova, A., Tan, M., Sit, R., Neff, N., Hart, M., Meese, E., Quake, S., Wyss-Coray, T., Keller, A. 2023

  Abstract

  Molecular mechanisms of organismal and cell aging remain incompletely understood. We, therefore, generated a body-wide map of noncoding RNA (ncRNA) expression in aging (16 organs at ten timepoints from 1 to 27 months) and rejuvenated mice. We found molecular aging trajectories are largely tissue-specific except for eight broadly deregulated microRNAs (miRNAs). Their individual abundance mirrors their presence in circulating plasma and extracellular vesicles (EVs) whereas tissue-specific ncRNAs were less present. For miR-29c-3p, we observe the largest correlation with aging in solid organs, plasma and EVs. In mice rejuvenated by heterochronic parabiosis, miR-29c-3p was the most prominent miRNA restored to similar levels found in young liver. miR-29c-3p targets the extracellular matrix and secretion pathways, known to be implicated in aging. We provide a map of organism-wide expression of ncRNAs with aging and rejuvenation and identify a set of broadly deregulated miRNAs, which may function as systemic regulators of aging via plasma and EVs.

  View details for DOI 10.1038/s41587-023-01751-6

  View details for PubMedID 37106037

  View details for PubMedCentralID 3836174

• Ageing-associated small RNA cargo of extracellular vesicles. RNA biology Kern, F., Kuhn, T., Ludwig, N., Simon, M., Groger, L., Fabis, N., Aparicio-Puerta, E., Salhab, A., Fehlmann, T., Hahn, O., Engel, A., Wagner, V., Koch, M., Winek, K., Soreq, H., Nazarenko, I., Fuhrmann, G., Wyss-Coray, T., Meese, E., Keller, V., Laschke, M. W., Keller, A. 2023; 20 (1): 482-494

  Abstract

  Previous work on murine models and humans demonstrated global as well as tissue-specific molecular ageing trajectories of RNAs. Extracellular vesicles (EVs) are membrane vesicles mediating the horizontal transfer of genetic information between different tissues. We sequenced small regulatory RNAs (sncRNAs) in two mouse plasma fractions at five time points across the lifespan from 2-18months: (1) sncRNAs that are free-circulating (fc-RNA) and (2) sncRNAs bound outside or inside EVs (EV-RNA). Different sncRNA classes exhibit unique ageing patterns that vary between the fcRNA and EV-RNA fractions. While tRNAs showed the highest correlation with ageing in both fractions, rRNAs exhibited inverse correlation trajectories between the EV- and fc-fractions. For miRNAs, the EV-RNA fraction was exceptionally strongly associated with ageing, especially the miR-29 family in adipose tissues. Sequencing of sncRNAs and coding genes in fat tissue of an independent cohort of aged mice up to 27months highlighted the pivotal role of miR-29a-3p and miR-29b-3p in ageing-related gene regulation that we validated in a third cohort by RT-qPCR.

  View details for DOI 10.1080/15476286.2023.2234713

  View details for PubMedID 37498213

• miRNATissueAtlas2: an update to the human miRNA tissue atlas. Nucleic acids research Keller, A., Groger, L., Tschernig, T., Solomon, J., Laham, O., Schaum, N., Wagner, V., Kern, F., Schmartz, G. P., Li, Y., Borcherding, A., Meier, C., Wyss-Coray, T., Meese, E., Fehlmann, T., Ludwig, N. 2021

  Abstract

  Small non-coding RNAs (sncRNAs) are pervasive regulators of physiological and pathological processes. We previously developed the human miRNA Tissue Atlas, detailing the expression of miRNAs across organs in the human body. Here, we present an updated resource containing sequencing data of 188 tissue samples comprising 21 organ types retrieved from six humans. Sampling the organs from the same bodies minimizes intra-individual variability and facilitates the making of a precise high-resolution body map of the non-coding transcriptome. The data allow shedding light on the organ- and organ system-specificity of piwi-interacting RNAs (piRNAs), transfer RNAs (tRNAs), microRNAs (miRNAs) and other non-coding RNAs. As use case of our resource, we describe the identification of highly specific ncRNAs in different organs. The update also contains 58 samples from six tissues of the Tabula Muris collection, allowing to check if the tissue specificity is evolutionary conserved between Homo sapiens and Mus musculus. The updated resource of 87252 non-coding RNAs from nine non-coding RNA classes for all organs and organ systems is available online without any restrictions (https://www.ccb.uni-saarland.de/tissueatlas2).

  View details for DOI 10.1093/nar/gkab808

  View details for PubMedID 34570238

• Encyclopedia of tools for the analysis of miRNA isoforms BRIEFINGS IN BIOINFORMATICS Schmartz, G., Kern, F., Fehlmann, T., Wagner, V., Fromm, B., Keller, A. 2021; 22 (4)

  Abstract

  RNA sequencing data sets rapidly increase in quantity. For microRNAs (miRNAs), frequently dozens to hundreds of billion reads are generated per study. The quantification of annotated miRNAs and the prediction of new miRNAs are leading computational tasks. Now, the increased depth of coverage allows to gain deeper insights into the variability of miRNAs. The analysis of isoforms of miRNAs (isomiRs) is a trending topic, and a range of computational tools for the analysis of isomiRs has been developed. We provide an overview on 27 available computational solutions for the analysis of isomiRs. These include both stand-alone programs (17 tools) and web-based solutions (10 tools) and span a publication time range from 2010 to 2020. Seven of the tools were published in 2019 and 2020, confirming the rising importance of the topic. While most of the analyzed tools work for a broad range of organisms or are completely independent of a reference organism, several tools have been tailored for the analysis of human miRNA data or for plants. While 14 of the tools are general analysis tools of miRNAs, and isomiR analysis is one of their features, the remaining 13 tools have specifically been developed for isomiR analysis. A direct comparison on 20 deep sequencing data sets for selected tools provides insights into the heterogeneity of results. With our work, we provide users a comprehensive overview on the landscape of isomiR analysis tools and in that support the selection of the most appropriate tool for their respective research task.

  View details for DOI 10.1093/bib/bbaa346

  View details for Web of Science ID 000709466800104

  View details for PubMedID 33313643

• miRTargetLink 2.0-interactive miRNA target gene and target pathway networks NUCLEIC ACIDS RESEARCH Kern, F., Aparicio-Puerta, E., Li, Y., Fehlmann, T., Kehl, T., Wagner, V., Ray, K., Ludwig, N., Lenhof, H., Meese, E., Keller, A. 2021; 49 (W1): W409-W416

  Abstract

  Which genes, gene sets or pathways are regulated by certain miRNAs? Which miRNAs regulate a particular target gene or target pathway in a certain physiological context? Answering such common research questions can be time consuming and labor intensive. Especially for researchers without computational experience, the integration of different data sources, selection of the right parameters and concise visualization can be demanding. A comprehensive analysis should be central to present adequate answers to complex biological questions. With miRTargetLink 2.0, we develop an all-in-one solution for human, mouse and rat miRNA networks. Users input in the unidirectional search mode either a single gene, gene set or gene pathway, alternatively a single miRNA, a set of miRNAs or an miRNA pathway. Moreover, genes and miRNAs can jointly be provided to the tool in the bidirectional search mode. For the selected entities, interaction graphs are generated from different data sources and dynamically presented. Connected application programming interfaces (APIs) to the tailored enrichment tools miEAA and GeneTrail facilitate downstream analysis of pathways and context-annotated categories of network nodes. MiRTargetLink 2.0 is freely accessible at https://www.ccb.uni-saarland.de/mirtargetlink2.

  View details for DOI 10.1093/nar/gkab297

  View details for Web of Science ID 000672775800052

  View details for PubMedID 34009375

  View details for PubMedCentralID PMC8262750