Biology subjects

Auer, F.

Publications and source records attributed to Auer, F..

11 recordsLinked to original sources

bioRxiv2026

T-Rex: Standardized Analysis of Germline Variants in Whole-Exome Sequencing Trios

Whole-exome sequencing (WES) enables the identification of rare germline variants contributing to pediatric diseases. Trio-based sequencing, comparing affected children with their parents, is particularly effective for rare disease genetics. However, WES data analysis requires bioinformatics expertise, varies across institutions, and is often incompatible with clinical workflows. We developed T-Rex (Trio Rare variant analysis of EXomes), a cross-platform desktop application that enables the standardized and local analysis of WES germline Trio data without the need for programming knowledge. T-Rex integrates state-of-the-art tools for alignment, dual-variant calling (GATK HaplotypeCaller + VarScan2), annotation (SNPEff/SNPSift), rare-variant filtering based on population frequencies (gnomAD), and family-based statistical testing, including the Transmission Disequilibrium Test with multiple-testing correction. Benchmarking of the dual-caller strategy on the Genome in a Bottle Ashkenazim Trio demonstrates high precision (99.2%) while maintaining robust sensitivity (91.1%). User testing (n=13) confirmed quick learning across clinicians and researchers. Application to a cohort of n=121 pediatric cancer Trio datasets, filtering for rare protein-coding variants (MAF[≤]0.1% in gnomAD v4.0), validated all assessable previously reported pathogenic variants. Overall, T-Rex enables clinicians to robustly analyze WES Trio data in compliance with data protection regulations without requiring additional software licenses. As one of the first platforms for comprehensive WES Trio analysis that requires no programming expertise while providing clinical-grade, end-to-end workflows, T-Rex facilitates collaborative research between clinics and reduces reliance on external providers. Implementation and AvailabilityThe source code is available on GitHub (https://github.com/SaraLuisaReh/trex). The fully precompiled app is available on Zenodo (https://zenodo.org/records/19135262).

bioinformatics↗

bioRxiv2026

Diverging routes of oligodendrocyte recruitment in adaptive and regenerative myelination

Myelination by oligodendrocytes is dynamically regulated throughout life, supporting axon and circuit function during development, activity-dependent plasticity and repair after injury. How new oligodendrocytes are recruited from their lifelong pool of oligodendrocyte precursor cells (OPCs) in these distinct contexts remains unclear. Using high-resolution in vivo imaging in zebrafish, we directly compared activity-induced and demyelination-induced oligodendrogenesis under otherwise matched conditions. Although enhanced motor activity and demyelination both increased oligodendrocyte production, OPCs activated strikingly different transcriptional programmes. Demyelination, but not enhanced activity, induced acute expression of differentiation-associated genes, including the G-protein-coupled receptor Gpr17. Fate-tracking using a Gpr17 knock-in reporter revealed that all newly formed oligodendrocytes arise from Gpr17-positive states. In the healthy CNS, these states emerged exclusively through proliferation-linked OPC divisions, whereas demyelination unlocked a distinct, proliferation-independent conversion of homeostatic OPCs into Gpr17-positive, differentiation-primed cells. Our findings demonstrate the existence of diverging context-dependent routes of OPC recruitment engaged in adaptive and regenerative myelination.

neuroscience↗

bioRxiv2025

Oligodendrocytes support functional development of subcortical premotor neurons and navigation

Oligodendrocytes and the myelin they produce are required for proper balance behaviors in adult vertebrates. If, when, and how they shape the functional development of vestibular (balance) circuits and associated behaviors is unclear. We first adopted a pharmacological approach to investigate the contribution of oligodendrocytes across early development of larval zebrafish (Danio rerio). Disruption of oligodendrogenesis reduces the number of oligodendrocytes near vestibular neurons across development, but only impacts vertical navigation -- a behavior requiring vestibular function -- in older larvae. Correspondingly, we found that midbrain premotor neurons in the vertical navigation circuit only decreased their responses to tilts at later ages. In contrast, we found that the vestibulo-ocular reflex was unaffected by drug treatment, and that body-tilt responses in the underlying hindbrain vestibular neurons and their target extraocular motor neurons were unchanged. Targeted photoablation of oligodendrocytes in the anterior hindbrain replicated our pharmacological findings, selectively disrupting vertical navigation in older animals. By dissociating where and when developmentally-disrupted oligodendrogenesis impacts neuronal function and behavior, our work takes a major step towards understanding how oligodendrocytes enable the maturation of sensorimotor behaviors.

neuroscience↗

bioRxiv2024

A brainstem circuit for gravity-guided vertical navigation

The sensation of gravity anchors our perception of the environment and is crucial for navigation. However, the neural circuits that transform gravity into commands for navigation are undefined. We first determined that larval zebrafish (Danio rerio) navigate vertically by maintaining a consistent heading across a series of upward climb or downward dive bouts. Gravity-blind mutant fish swim with more variable heading and excessive veering, leading to inefficient vertical navigation. After targeted photoablation of ascending vestibular neurons and spinal projecting midbrain neurons, but not vestibulospinal neurons, vertical navigation was impaired. These data define a sensorimotor circuit that uses evolutionarily-conserved brainstem architecture to transform gravitational signals into persistent heading for vertical navigation. The work lays a foundation to understand how vestibular inputs allow animals to move efficiently through their environment.

neuroscience↗

bioRxiv2023

Purkinje Cells Control Posture in Larval Zebrafish (Danio rerio)

Cerebellar dysfunction leads to postural instability. Recent work in freely moving rodents has transformed investigations of cerebellar contributions to posture. However, the combined complexity of terrestrial locomotion and the rodent cerebellum motivate new approaches to perturb cerebellar function in simpler vertebrates. Here, we adapted a validated chemogenetic tool (TRPV1/capsaicin) to describe the role of Purkinje cells -- the output neurons of the cerebellar cortex -- as larval zebrafish swam freely in depth. We achieved both bidirectional control (activation and ablation) of Purkinje cells while performing quantitative high-throughput assessment of posture and locomotion. Activation modified postural control in the pitch (nose-up/nose-down) axis. Similarly, ablations disrupted pitch-axis posture and fin-body coordination responsible for climbs. Postural disruption was more widespread in older larvae, offering a window into emergent roles for the developing cerebellum in the control of posture. Finally, we found that activity in Purkinje cells could individually and collectively encode tilt direction, a key feature of postural control neurons. Our findings delineate an expected role for the cerebellum in postural control and vestibular sensation in larval zebrafish, establishing the validity of TRPV1/capsaicin-mediated perturbations in a simple, genetically-tractable vertebrate. Moreover, by comparing the contributions of Purkinje cell ablations to posture in time, we uncover signatures of emerging cerebellar control of posture across early development. This work takes a major step towards understanding an ancestral role of the cerebellum in regulating postural maturation.

neuroscience↗

bioRxiv2023

Scalable Apparatus to Measure Posture and Locomotion (SAMPL): a high-throughput solution to study unconstrained vertical behavior in small animals

Balance and movement are impaired in a wide variety of neurological disorders. Recent advances in behavioral monitoring provide unprecedented access to posture and loco-motor kinematics, but without the throughput and scalability necessary to screen candidate genes / potential therapeutics. We present a powerful solution: a Scalable Apparatus to Measure Posture and Locomotion (SAMPL). SAMPL includes extensible imaging hardware and low-cost open-source acquisition software with real-time processing. We first demonstrate that SAMPLs hardware and acquisition software can acquire data from D. melanogaster, C.elegans, and D. rerio as they move vertically. Next, we leverage SAMPLs throughput to rapidly (two weeks) gather a new zebrafish dataset. We use SAMPLs analysis and visualization tools to replicate and extend our current understanding of how zebrafish balance as they navigate through a vertical environment. Next, we discover (1) that key kinematic parameters vary systematically with genetic background, and (2) that such background variation is small relative to the changes that accompany early development. Finally, we simulate SAMPLs ability to resolve differences in posture or vertical navigation as a function of effect size and data gathered - key data for screens. Taken together, our apparatus, data, and analysis provide a powerful solution for laboratories using small animals to investigate balance and locomotor disorders at scale. More broadly, SAMPL is both an adaptable resource for laboratories looking process video-graphic measures of behavior in real-time, and an exemplar of how to scale hardware to enable the throughput necessary for screening.

neuroscience↗

bioRxiv2022

Tilt In Place Microscopy (TIPM): a simple, low-cost solution to image neural responses to body rotations

Animals use information about gravity and other destabilizing forces to balance and navigate through their environment. Measuring how brains respond to these forces requires considerable technical knowledge and/or financial resources. We present a simple alternative: Tilt In Place Microscopy (TIPM). TIPM is a low-cost and non-invasive way to measure neural activity following rapid changes in body orientation. Here we used TIPM to study vestibulospinal neurons in larval zebrafish during and immediately after roll tilts. Vestibulospinal neurons responded with reliable increases in activity that varied as a function of ipsilateral tilt amplitude. TIPM differentiated tonic (i.e. sustained tilt) from phasic responses, revealing coarse topography of stimulus sensitivity in the lateral vestibular nucleus. Neuronal variability across repeated sessions was minor relative to trial-to-trial variability, allowing us to use TIPM for longitudinal studies of the same neurons across two developmental timepoints. There, we observed global increases in response strength, and systematic changes in the neural representation of stimulus direction. Our data extend classical characterization of the body tilt representation by vestibulospinal neurons and establish TIPMs utility to study the neural basis of balance, especially in developing animals. Significance StatementVestibular sensation influences everything from navigation to interoception. Here we detail a straight-forward, validated and nearly-universal approach to image how the nervous system senses and responds to body tilts. We use our new method to replicate and expand upon past findings of tilt sensing by a conserved population of spinal-projecting vestibular neurons. The simplicity and broad compatibility of our approach will democratize the study of the brains response to destabilization, particularly across development.

neuroscience↗

bioRxiv2021

Data-dependent visualization of biological networks in the web-browser with NDExEdit

Networks are a common methodology used to capture increasingly complex associations between biological entities. They serve as a resource of biological knowledge for bioinformatics analyses, and also comprise the subsequent results. However, the interpretation of biological networks is challenging and requires suitable visualizations dependent on the contained information. The most prominent software in the field for the visualization of biological networks is Cytoscape, a desktop modeling environment also including many features for analysis. A further challenge when working with networks is their distribution. Within a typical collaborative workflow, even slight changes of the network data force one to repeat the visualization step as well. Also, just minor adjustments to the visual representation not only need the networks to be transferred back and forth. Collaboration on the same resources requires specific infrastructure to avoid redundancies, or worse, the corruption of the data. A well-established solution is provided by the NDEx platform where users can upload a network, share it with selected colleagues or make it publicly available. NDExEdit is a web-based application where simple changes can be made to biological networks within the browser, and which does not require installation. With our tool, plain networks can be enhanced easily for further usage in presentations and publications. Since the network data is only stored locally within the web browser, users can edit their private networks without concerns of unintentional publication. The web tool is designed to conform to the Cytoscape Exchange (CX) format as a data model, which is used for the data transmission by both tools, Cytoscape and NDEx. Therefore the modified network can be exported as a compatible CX file, additionally to standard image formats like PNG and JPEG. Author summaryRelations in biological research are often visualized as networks. For instance, if two proteins interact with each other during a certain process, the corresponding network would show two nodes connected by one edge. But the fact that the interaction between the two exists, may not be enough. With established software solutions like Cytoscape we can add all the information we have about our nodes and their interaction to our data foundation. Furthermore, we can change the visual appearance of our nodes and their interaction based on this information. For example, if our network contains 20 nodes, that all interact with each other, but the strength of these interactions each range between 0 and 1, we can illustrate that by making the edges wider for strong interactions and slimmer for weak interactions. Thus, our visualization is enriched with valuable information. As of now these data-dependent modifications can only be made with a desktop client. We introduce NDExEdit, a web-based solution for visualization changes to networks that conform to the CX data format. It allows us to import networks directly from the NDEx platform and apply changes to the visualization - including all types of mappings, one of which was briefly described above.

bioinformatics↗

bioRxiv2021

Clusters of neuronal Neurofascin prefigure node of Ranvier position along single axons

The spacing of nodes of Ranvier crucially affects conduction properties along myelinated axons. It has been assumed that node position is primarily driven by the growth of myelin sheaths. Here, we reveal an additional mechanism of node positioning that is driven by the axon. We show through longitudinal live imaging of node formation dynamics that stable clusters of the cell adhesion molecule Neurofascin A accumulate at specific sites along axons prior to myelination. While some of these clusters change position upon encounter with growing myelin sheaths, others restrict sheath extension and are therefore predictive of future node position. Animals that lack full-length Neurofascin A showed increased internodal distances and less regular spacing of nodes along single axons. Together, our data reveal the existence of an axonal mechanism to position its nodes of Ranvier that does not depend on regulation of myelin sheath length.

neuroscience↗

bioRxiv2020

Explaining decisions of Graph Convolutional Neural Networks: patient-specific molecular subnetworks responsible for metastasis prediction in breast cancer

MotivationContemporary deep learning approaches show cutting-edge performance in a variety of complex prediction tasks. Nonetheless, the application of deep learning in healthcare remains limited since deep learning methods are often considered as non-interpretable black-box models. Layer-wise Relevance Propagation (LRP) is a technique to explain decisions of deep learning methods. It is widely used to interpret Convolutional Neural Networks (CNNs) applied on image data. Recently, CNNs started to extend towards non-euclidean domains like graphs. Molecular networks are commonly represented as graphs detailing interactions between molecules. Gene expression data can be assigned to the vertices of these graphs. In other words, gene expression data can be structured by utilizing molecular network information as prior knowledge. Graph-CNNs can be applied to structured gene expression data, for example, to predict metastatic events in breast cancer. Therefore, there is a need for explanations showing which part of a molecular network is relevant for predicting an event, e.g. distant metastasis in cancer, for each individual patient. ResultsWe extended the procedure of LRP to make it available for Graph-CNN and tested its applicability on a large breast cancer dataset. We present Graph Layer-wise Relevance Propagation (GLRP) as a new method to explain the decisions made by Graph-CNNs. We demonstrate a sanity check of the developed GLRP on a hand-written digits dataset, and then applied the method on gene expression data. We show that GLRP provides patient-specific molecular subnetworks that largely agree with clinical knowledge and identify common as well as novel, and potentially druggable, drivers of tumor progression. As a result this method could be potentially highly useful on interpreting classification results on the individual patient level, as for example in precision medicine approaches or a molecular tumor board. Availabilityhttps://gitlab.gwdg.de/UKEBpublic/graph-lrp https://frankkramer-lab.github.io/MetaRelSubNetVis/ Contacttim.beissbarth@bioinf.med.uni-goettingen.de

bioinformatics↗

bioRxiv2019

Functionally Distinct Subgroups of Oligodendrocyte Precursor Cells Integrate Neural Activity and Execute Myelin Formation

Recent reports revealed heterogeneity of oligodendrocyte precursor cells (OPCs). It remains unclear if heterogeneity reflects different types of cells with distinct functions, or rather transiently acquired states of cells with the same function. By integrating lineage formation of individual OPC clones, single-cell transcriptomics, calcium imaging and manipulation of neural activity, we show that OPCs in the zebrafish spinal cord can be divided into two functionally distinct entities. One subgroup forms elaborate networks of processes and exhibits a high degree of calcium signalling, but infrequently differentiates, despite contact to permissive axons. Instead, these OPCs divide in an activity and calcium dependent manner to produce another subgroup with higher process motility and less calcium signaling, which readily differentiates. Our data show that OPC subgroups are functionally diverse in responding to neurons and reveal that activity regulates proliferation of a subset of OPCs that is distinct from the cells that generate differentiated oligodendrocytes.

neuroscience↗