Biology subjects

Eberle, M.

Publications and source records attributed to Eberle, M..

9 recordsLinked to original sources

bioRxiv2026

Portello: Making global assembly more effective for rare-disease whole genome sequencing

MotivationLong-read de novo assembly methods provide great potential to improve whole genome sequencing analysis for rare-disease, however these methods are typically under-utilized. Among the complications of an assembly-based approach is the difficulty of reviewing read evidence for assembly-based inferences, including access to read-based information on basecall qualities, methylation, and mosaic variants not captured in the assembly consensus. An additional complication is resolving conflicts in variant representation between assembly-based inferences and those based on conventional reference-based read-mapping pipelines. Here we propose a new assembly-based mapping approach, portello, which addresses both of these issues by transferring read mappings from the samples de novo assembly contigs onto a standard reference sequence. ResultsPortellos assembly-based mapping approach results in read-to-reference alignments that can be used by standard mapping-based variant callers without modification, resulting in improved accuracy due to higher-quality mapping. This approach also enables assembly and reference mapping-based inferences to be unified onto a consistent view of the sample, and enables direct review of read-level support for the assembly consensus in the context of a standard reference genome. To demonstrate portellos impact on variant calling, we show that DeepVariant calls from portello alignments remove 47% of small variant basecall errors found in calls made from conventional read mapping. We additionally demonstrate how portello alignments can improve visualization and interpretation of complex loci, including an example where a copy number gain in a segmental duplication region can be easily inferred from assembly-based mapping while interpretation of the same region from conventional read mapping remains impractical. Portello is also capable of directly phasing and haplotagging read alignments as part of the alignment transfer process, including for partially-phased assembly contig inputs where phasing blocks need to be delineated within each contig. AvailabilityThe portello source and pre-compiled binary is released on GitHub: https://github.com/PacificBiosciences/portello.

genomics↗

bioRxiv2025

Fishexplorer: A multimodal cellular atlas platform for neuronal circuit dissection in larval zebrafish

Understanding how neural circuits give rise to behavior requires comprehensive knowledge of neuronal morphology, connectivity, and function. Atlas platforms play a critical role in enabling the visualization, exploration, and dissemination of such information. Here, we present FishExplorer, an interactive and expandable community platform designed to integrate and analyze multimodal brain data from larval zebrafish. FishExplorer supports datasets acquired through light microscopy (LM), electron microscopy (EM), and X-ray imaging, all co-registered within a unified spatial coordinate system which enables seamless comparison of neuronal morphologies and synaptic connections. To further assist circuit analysis, FishExplorer includes a suite of tools for querying and visualizing connectivity at the whole-brain scale. By integrating data from recent large-scale EM reconstructions (presented in companion studies), FishExplorer enables researchers to validate circuit models, explore wiring principles, and generate new hypotheses. As a continuously evolving resource, FishExplorer is designed to facilitate collaborative discovery and serve the growing needs of the teleost neuroscience community.

neuroscience↗

bioRxiv2025

Correlative light and electron microscopy reveals the fine circuit structure underlying evidence accumulation in larval zebrafish

AbstractEvidence accumulation is a fundamental neural computation essential for adaptive behavior, yet its synaptic implementation remains unclear. Addressing this challenge critically depends on linking neural dynamics to circuit structure within the same brain. Here, we combine functional calcium imaging with large-scale ultrastructural electron microscopy (EM) to uncover the wiring logic of visual evidence accumulation in larval zebrafish. In a functionally imaged EM dataset of the anterior hindbrain, we identify conserved morphological cell types whose activity patterns define distinct computational roles. Bilateral inhibition, disinhibition, and recurrent connectivity emerge as key circuit motifs shaping these dynamics. To generalize our findings across animals, we develop a photoconversion-based pipeline to label and reconstruct functionally characterized neurons, enabling us to train a classifier that predicts functional identity from morphology alone. Applying this classifier to a second, whole-brain EM dataset lacking functional data reveals matching connectivity patterns, significantly augmenting its applicability for detailed circuit dissections. Based on these results, we develop and constrain a biophysically realistic neural network model that captures observed dynamics and yields predictions we tested and confirmed experimentally. Our work illustrates how hypothesis-driven connectomics can uncover the synaptic basis of sensory-motor computations and establishes a novel framework for cross-animal circuit dissection in the vertebrate brain.

neuroscience↗

bioRxiv2024

Peripheral CGRP engages brain-wide electrical network activity of migraine

BackgroundMigraine is a disorder of severe, recurrent headaches and debilitating sensory, cognitive and affective symptoms, often triggered by stress. Early life stress in childhood has been shown to increase the likelihood of migraine in adulthood in humans. Calcitonin-gene relate peptide (CGRP) has been shown to reliably and acutely induce migraine or migraine-like behavior in both humans and rodent models. Here we investigate the impact of early life stress and CGRP on migraine-related neural circuitry, as well as the impact of early life stress on CGRP-mediated migraine-like activity in order to better understand the mechanisms by which early life stress predisposes neural circuitry to migraine brain activity. MethodsWe implemented an early life stress paradigm in the outbred strain of mice, CD1. We evaluated the impact of peripheral CGRP on migraine-like behavior and employed multi-site in vivo neurophysiology in freely behaving mice. A changepoint analysis was used to dissect differences in individual CGRP-induced responses. ResultsWe found that early life stress exacerbated migraine-related behavioral and network physiology. CGRP alone caused disruptions in neural oscillatory activity across a network of brain regions including the anterior cingulate cortex (ACC), amygdala (AMY), thalamus (Po, VPM, and MDthal), and parabrachial nucleus (PBN). We found that power across the network was lowered within 10 minutes of peripheral CGRP exposure, which was sustained for [~]40-50 min. Coherence was mostly disrupted in amygdalar brain region pairings, and took on a shorter timecourse, with partial rescue of these responses by migraine abortive, sumatriptan. We found that early life stress exacerbated most of these responses, especially AMY-thalamic coherence pairings, although early life stress in the absence of CGRP demonstrated no impact on the network overall. We further identified individual mice with brain-network activity hypersusceptible to migraine. ConclusionsOur findings demonstrate that early life stress confers vulnerability to migraine, simultaneously impacting behavior and brain network activity responses to peripheral CGRP.

neuroscience↗

bioRxiv2023

Benchmarking of small and large variants across tandem repeats

Tandem repeats (TRs) are highly polymorphic in the human genome, have thousands of associated molecular traits, and are linked to over 60 disease phenotypes. However, their complexity often excludes them from at-scale studies due to challenges with variant calling, representation, and lack of a genome-wide standard. To promote TR methods development, we create a comprehensive catalog of TR regions and explore its properties across 86 samples. We then curate variants from the GIAB HG002 individual to create a tandem repeat benchmark. We also present a variant comparison method that handles small and large alleles and varying allelic representation. The 8.1% of the genome covered by the TR catalog holds [~]24.9% of variants per individual, including 124,728 small and 17,988 large variants for the GIAB HG002 TR benchmark. We work with the GIAB community to demonstrate the utility of this benchmark across short and long read technologies.

bioinformatics↗

bioRxiv2023

Transcriptomic Evaluation of Stress Vulnerability Network using Single Cell RNA-Seq in mouse Prefrontal Cortex

Increased vulnerability to stress is a major risk factor for the manifestation of several mood disorders, including major depressive disorder (MDD). Despite the status of MDD as a significant donor to global disability, the complex integration of genetic and environmental factors that contribute to the behavioral display of such disorders has made a thorough understanding of related etiology elusive. Recent developments suggest that a brain-wide network approach is needed, taking into account the complex interplay of cell types spanning multiple brain regions. Single cell RNA-sequencing technologies can provide transcriptomic profiling at the single-cell level across heterogenous samples. Furthermore, we have previously used local field potential oscillations and machine learning to identify an electrical brain network that is indicative of a predisposed vulnerability state. Thus, this study combined single cell RNA-sequencing (scRNA-Seq) with electrical brain network measures of the stress-vulnerable state, providing a unique opportunity to access the relationship between stress network activity and transcriptomic changes within individual cell types. We found especially high numbers of differentially expressed genes between animals with high and low stress vulnerability brain network activity in astrocytes and glutamatergic neurons but we estimated that vulnerability network activity depends most on GABAergic neurons. High vulnerability network activity included upregulation of microglia and mitochondrial and metabolic pathways, while lower vulnerability involved synaptic regulation. Genes that were differentially regulated with vulnerability network activity significantly overlapped with genes identified as having significant SNPs by human GWAS for depression. Taken together, these data provide the gene expression architecture of a previously uncharacterized stress vulnerability brain state, enabling new understanding and intervention of predisposition to stress susceptibility. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=91 SRC="FIGDIR/small/540705v2_ufig1.gif" ALT="Figure 1"> View larger version (38K): org.highwire.dtl.DTLVardef@1ebe036org.highwire.dtl.DTLVardef@cd2131org.highwire.dtl.DTLVardef@13e3519org.highwire.dtl.DTLVardef@1100e62_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2023

HiPhase: Jointly phasing small and structural variants from HiFi sequencing

BackgroundIn diploid organisms, phasing is the problem of assigning the heterozygous variants to one of two haplotypes. Reads from PacBio HiFi sequencing provide long, accurate observations that can be used as the basis for both calling and phasing variants. HiFi reads also excel at calling larger classes of variation such as structural variants. However, current phasing tools typically only phase small variants, leaving larger structural variants unphased. MethodsWe developed HiPhase, a tool that jointly phases SNVs, indels, and structural variants. The main benefits of HiPhase are 1) dual mode allele assignment for detecting structural variants, 2) a novel application of the A*-algorithm to phasing, and 3) logic allowing phase blocks to span breaks caused by alignment issues around reference gaps and homozygous deletions. ResultsIn our assessment, HiPhase produced an average phase block NG50 of 493 kb with 933 switchflip errors and fully phased 95.2% of genes, improving over the current state of the art. Additionally, HiPhase jointly phases SNVs, indels, and structural variants and includes innate multi-threading, statistics gathering, and concurrent phased alignment output generation. Availabilityhttps://github.com/PacificBiosciences/HiPhase

bioinformatics↗

bioRxiv2019

Validation of new tools to identify expanded repeats: an intronic pentamer expansion in RFC1 causes CANVAS

Genomic technologies such as Next Generation Sequencing (NGS) are revolutionizing molecular diagnostics and clinical medicine. However, these approaches have proven inefficient at identifying pathogenic repeat expansions. Here, we apply a collection of bioinformatics tools that can be utilized to identify either known or novel expanded repeat sequences in NGS data. We performed genetic studies of a cohort of 35 individuals from 22 families with a clinical diagnosis of cerebellar ataxia with neuropathy and bilateral vestibular areflexia syndrome (CANVAS). Analysis of whole genome sequence (WGS) data with five independent algorithms identified a recessively inherited intronic repeat expansion [(AAGGG)exp] in the gene encoding Replication Factor C1 (RFC1). This motif, not reported in the reference sequence, localized to an Alu element and replaced the reference (AAAAG)11 short tandem repeat. Genetic analyses confirmed the pathogenic expansion in 18 of 22 CANVAS families and identified a core ancestral haplotype, estimated to have arisen in Europe over twenty-five thousand years ago. WGS of the four RFC1 negative CANVAS families identified plausible variants in three, with genomic re-diagnosis of SCA3, spastic ataxia of the Charlevoix-Saguenay type and SCA45. This study identified the genetic basis of CANVAS and demonstrated that these improved bioinformatics tools increase the diagnostic utility of WGS to determine the genetic basis of a heterogeneous group of clinically overlapping neurogenetic disorders.

genetics↗

bioRxiv2018

Copy number variants in clinical WGS: deployment and interpretation for rare and undiagnosed disease

PurposeCurrent diagnostic testing for genetic disorders involves serial use of specialized assays spanning multiple technologies. In principle, whole genome sequencing (WGS) has the potential to detect all genomic mutation types on a single platform and workflow. Here we sought to evaluate copy number variant (CNV) calling as part of a clinically accredited WGS test.\n\nMethodsUsing a depth-based copy number caller we performed analytical validation of CNV calling on a reference panel of 17 samples, compared the sensitivity of WGS-based variants to those from a clinical microarray, and set a bound on precision using orthogonal technologies. We developed a protocol for family-based analysis, annotation, filtering, visualization of WGS based CNV calls, and deployed this across a clinical cohort of 79 rare and undiagnosed cases.\n\nResultsWe found that CNV calls from WGS are at least as sensitive as those from microarrays, while only creating a modest increase in the number of variants interpreted (~10 CNVs per case). We identified clinically significant CNVs in 15% of the first 79 cases analyzed. This pipeline also enabled identification of cases of uniparental disomy (UPD) and a 50% mosaic trisomy 14. Directed analysis of some CNVs enabled break-point level resolution of genomic rearrangements and phasing of de-novo CNVs.\n\nConclusionRobust identification of CNVs by WGS is possible within a clinical testing environment, and further developments will bring improvements in resolution of smaller and more complex CNVs.

genomics↗