Biology subjects

Wedler, A.

Publications and source records attributed to Wedler, A..

5 recordsLinked to original sources

bioRxiv2025

RNA-seq derived sequence variations are excellent features for cell line identification

1Cell lines are indispensable models for analyzing molecular mechanisms underlying human diseases. However, incorrect annotation and cross-contamination can introduce severe bias in respective studies. Accordingly, various publishers request authentication of cell lines before publication. Short tandem repeat profiling is commonly used to verify cell line identity and purity but does not guarantee that published results are based on the samples tested by this method. In this study, we demonstrate that RNA-seq-derived sequence variation information is eligible for unambiguous cell line-specific clustering. Based on this finding, we propose methods for reliable cell line identification from RNA-seq data using supervised machine learning methods. In addition, we demonstrate the ability to detect cross-contamination of human cell lines. The presented methods are insensitive to different data pre-processing steps and quality measures. The proposed TopFracCCLE algorithm for cell line identification and detection of cross-contamination is available as R-script at https://github.com/HuettelmaierLab/topFracCCLE.

genomics↗

bioRxiv2025

CENTRA: Knowledge-Based Gene Contexuality Graphs Reveal Functional Master Regulators by Centrality and Fractality

Deciphering gene function via context-aware approaches is limited by various means. Especially static gene sets used in enrichment analyses and the lack of single-gene resolution in such analyses restrains the flexible association of genes with specific context. Here, we introduce CENTRA (Centrality-based Exploration of Network Topologies from Regulatory Assemblies), a framework that models gene contextuality through topic-specific gene co-occurrence networks derived from curated gene sets and associated literature. Using Latent Dirichlet Allocation on 12,045 abstracts linked to MSigDB C2 gene sets, we uncovered 27 biological topics and constructed corresponding topic-specific networks that reflect distinct biological states, perturbation conditions, and disease-related regulatory programs. Graph-topological metrics, including centrality, local fractality, and perturbation sensitivity, were computed for each gene to capture structural relevance within these topic-specific contexts. We demonstrate that topological profiles distinguish well-characterized regulators, identify emerging functional candidates, and reveal context-specific roles. Thereby, our framework enables the prioritization of understudied genes by assessing the robustness of their topological signatures across topic-specific networks. To support exploration of these results, we developed a publicly accessible interactive browser application, CENTRA, which enables dynamic navigation of networks and their functional annotations. CENTRA provides an interpretable, scalable framework for investigating context-dependent gene function and hypothesis generation, offering a novel entry point beyond traditional enrichment approaches. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=81 SRC="FIGDIR/small/662180v1_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@10e4eeorg.highwire.dtl.DTLVardef@125d5b4org.highwire.dtl.DTLVardef@f137aeorg.highwire.dtl.DTLVardef@7ea4e5_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2025

Loss of characteristic species across German federal states detected by repeated mapping of protected habitats

Identifying the winners and losers of biodiversity change within different habitat types requires systematic monitoring. While such data are still lacking in Germany, species trends could be derived from previously untapped sources. Here, we derive temporal trends in plant species from data of repeated habitat mapping programs of three German states from 1977-2021, both across all habitat types per state and within habitat types. Consistently negative trends were found across all states for species preferring heaths and semi-natural grasslands, moist to wet grasslands, and coastal and marine habitats, including many endangered species. Consistently positive trends were found for species preferring scrubs, copses and field hedges, and for non-native species. Trends within habitat types showed negative trends for species characteristic of those habitat types. While trends varied among states, the overall patterns were very similar. This points to ongoing habitat degradation and common drivers of biodiversity change in Germany.

ecology↗

bioRxiv2024

The long non-coding RNA FAM30A regulates the Musashi2-RUNX1 axis and is required for LSC function in AML cells

High expression of the long non-coding RNA (lncRNA) FAM30A has been previously associated with leukemic stem cell (LSC) activity and poor prognosis in both adult and paediatric acute myeloid leukaemia (AML) patients, yet it has not been functionally studied. This study provides the first cellular characterization of FAM30A focussing on an internal tandemly organised region, referred to as FAM30A repeats. FAM30A levels correlated with canonical AML LSC signatures and FAM30A depletion decreased cell viability as well as increased sensitivity to chemotherapeutics. It also inhibited colony formation, promoted granulocytic differentiation and abrogated leukemic engraftment in murine bone marrow in vivo. Overexpression of FAM30A repeats in this setting enhanced stemness, proliferation, chemoresistance, and engraftment thus highlighting the biological relevance of this region for LSC biology. On the molecular level, FAM30A repeats interact with the pro-LSC regulator Musashi-2 (MSI2), positively influencing expression of its targets including RUNX1 isoforms. We herein uncover that this FAM30A-MSI2-RUNX1 regulatory loop is of potential relevance for LSC maintenance in AML. These findings provide valuable insights into FAM30As cellular role and highlight its targeting potential for eliminating LSCs and improving treatment outcomes in AML patients.

cancer biology↗

bioRxiv2023

RAVER1 interconnects lethal EMT and miR/RISC activity by the control of alternative splicing

The RAVER1 protein was proposed to serve as a co-factor in guiding the PTBP-dependent control of alternative splicing (AS). Whether RAVER1 solely acts in concert with PTBPs and how it affects cancer cell fate remained elusive. Here we provide the first comprehensive investigation of RAVER1-controlled AS in cancer cell models and reveal a pro-oncogenic role of RAVER1 in tumor growth. This unravels that RAVER1 guides AS in synergy with PTBPs but more prominently serves PTBP1-independent roles in splicing. In cancer cells, one major function of RAVER1 is the control of proliferation and apoptosis, which involves the modulation of AS events within the miR/RISC pathway. Associated with this regulatory role, RAVER1 antagonizes lethal, TGFB-driven epithelial-mesenchymal-transition (EMT) by limiting TGFB signaling. RAVER1-modulated splicing events affect the insertion of protein interaction modules in factors guiding miR/RISC-dependent gene silencing. Most prominently, in all three human TNRC6 proteins, RAVER1 controls AS of GW-enriched motifs, which are essential for AGO2-binding. Disturbance of RAVER1-guided AS events in TNRC6 proteins and other facilitators of miR/RISC activity compromise miR/RISC activity which is essential to restrict TGFB signaling and lethal EMT.

molecular biology↗