Biology subjects

Gschwind, A. R.

Publications and source records attributed to Gschwind, A. R..

10 recordsLinked to original sources

bioRxiv2026

mV2G: a multiomic atlas for tissue-specific variant-to-gene prioritization

The multiomic Variant-to-Gene (mV2G, https://mv2g.hbliulab.org) is a comprehensive atlas that integrates diverse functional genomic evidence to prioritize tissue-specific variant-to-gene (V2G) associations. While genome-wide association studies (GWAS) have identified millions of associations between genetic variants and diseases, translating these findings into biological mechanisms remains challenging because >90% of variants reside in noncoding regions. Existing V2G resources provide complementary regulatory evidence but are fragmented and often lack tissue-specific interpretation. To address this challenge, we constructed the mV2G atlas by integrating 24 types of functional genomic evidence across 50 human tissues, including molecular quantitative trait loci, enhancer-gene predictions, three-dimensional chromatin interactions, and experimental validation. The atlas contains 188,634,118 evidence-supported V2G pairs involving 13,618,039 variants and 69,521 genes. We further developed a unified tissue-specific V2G prioritization framework and prioritized 1,530,420 high-confidence functional V2G pairs involving 1,131,316 unique variants, with 87% exhibiting tissue-specificity. The mV2G atlas provides searchable variant- and gene-centered interfaces, an interactive browser for visualizing variants, target genes, cis-regulatory elements, and chromatin states, as well as downloadable datasets. By integrating complementary regulatory evidence into a unified framework, mV2G provides an accessible resource for interpreting the functional and phenotypic impact of genomic variation in relevant tissues for human diseases. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=78 SRC="FIGDIR/small/743997v1_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@ac8319org.highwire.dtl.DTLVardef@1d31920org.highwire.dtl.DTLVardef@169225org.highwire.dtl.DTLVardef@1d4dc02_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

bioRxiv2026

PerturbPlan: An analytical framework for designing Perturb-seq experiments

CRISPR screens with single-cell RNA-seq readouts provide a powerful tool for characterizing the functions of noncoding elements and genes. However, designing these experiments to balance statistical power and cost is challenging, given the large number of design parameters. The only available tool for this purpose is a simulation-based power calculator, but it is computationally costly and requires high-performance computing to run. We derive a novel analytical formula for the power to detect perturbation-expression associations, recapitulating power estimates from the simulation-based tool while reducing runtime by up to seven orders of magnitude. This acceleration unlocks the possibility of interactive single-cell CRISPR screen design. Accordingly, we develop PerturbPlan, an interactive web application built on the analytical power formula. PerturbPlan helps users address 11 design questions for two types of single-cell CRISPR screens, Perturb-seq and targeted Perturb-seq (TAP-seq). We apply PerturbPlan to carry out a comparative analysis of three recent Perturb-seq designs, demonstrating how optimal design varies across experiments of different scales. We also use PerturbPlan to quantify the cost savings of a recent TAP-seq study relative to a hypothetical Perturb-seq study assaying the same perturbations, illustrating how the tool can inform decisions about targeted versus whole-transcriptome readouts. In sum, PerturbPlan is the first tool to facilitate flexible and interactive design of well-powered single-cell CRISPR screen experiments.

genomics↗

bioRxiv2026

Genome-scale mapping of variant, enhancer and gene function in primary human CD4+ T cells

CD4+ T cells harbor a disproportionate enrichment of immune disease risk loci and represent the primary cellular context for immune disease biology, yet the genes and regulatory programs these variants affect remain largely unknown. We combined targeted Perturb-seq of 1,032 cis-regulatory elements (CREs) overlapping 4,724 variants across 14 immune diseases with genome-wide Perturb-seq of all expressed genes in primary human CD4+ T cells, spanning 4.1 million cells. We identified 626 CRE-gene pairs, and connected CRE targets to downstream regulatory cascades. At the TYK2 and DEXI/CLEC16A loci, we resolved target genes and linked noncoding variants to inflammatory and metabolic programs. Across diseases, we revealed that dispersed variants converged on shared and disease-specific programs. Our work provides a framework for tracing variant-to-CRE-to-gene-to-network in disease-relevant primary cells.

genetics↗

bioRxiv2025

Innate immune responses to Plasmodium falciparum disrupt the blood-brain barrier

Plasmodium falciparum accumulation at the blood-brain barrier (BBB) is a hallmark of cerebral malaria, a life-threatening complication. Conversely, the contribution of the immune response to vascular injury has long been debated. Here, we studied the role of innate immune cells as potential effectors of vascular damage using a human in vitro 3D-BBB model. Parasite-stimulated immune cells from malaria-naive donors increased adhesion to microvessels, at least partly through LFA-1. This caused barrier disruption and inflammatory activation of BBB cells. Secretion of TNF-, IFN-{gamma}, and granzyme B by monocytes, NK and {gamma}{delta} T cells correlated with vascular injury, and accumulation of immune cells was required for local barrier damage. Our computational analysis disentangled pathogenic mechanisms driven specifically by either P. falciparum parasite or immune cells, as well as shared pathways. These findings demonstrate how vascular-immune interactions may contribute to vascular injury in cerebral malaria and point towards the potential of immunomodulatory therapeutics.

immunology↗

bioRxiv2025

An unbiased survey of distal element-gene regulatory interactions with direct-capture targeted Perturb-seq

Identifying the impact of distal regulatory elements on gene expression is a core challenge in human genetics. Large-scale CRISPR screens have not captured lower effect size element-gene interactions due to selection bias and limited statistical power. We developed a framework for highly powered CRISPR screens, consisting of Direct-Capture Targeted Perturb-seq (DC-TAP-seq), unbiased target selection, and a pipeline accounting for statistical power. Surveying 10,000 random distal element-gene pairs revealed most element-gene interactions have effect sizes <10%, which were virtually undetectable in prior studies. Most interactions occur within 100kb, many elements bind CTCF without classical enhancer chromatin, and housekeeping genes have similar frequencies of distal regulatory elements but with weaker effects. We also highlight limitations of predictive models and suggest that new models consider elements with smaller effect sizes. Our study provides an expanded view of distal regulatory elements and a framework for building more comprehensive maps of distal regulation.

genomics↗

bioRxiv2024

Mapping enhancer-gene regulatory interactions from single-cell data

Mapping enhancers and their target genes in specific cell types is crucial for understanding gene regulation and human disease genetics. However, accurately predicting enhancer-gene regulatory interactions from single-cell datasets has been challenging. Here, we introduce a new family of classification models, scE2G, to predict enhancer-gene regulation. These models use features from single-cell ATAC-seq or multiomic RNA and ATAC-seq data and are trained on a CRISPR perturbation dataset including >10,000 evaluated element-gene pairs. We benchmark scE2G models against CRISPR perturbations, fine-mapped eQTLs, and GWAS variant-gene associations and demonstrate state-of-the-art performance at prediction tasks across multiple cell types and categories of perturbations. We apply scE2G to build maps of enhancer-gene regulatory interactions in heterogeneous tissues and interpret noncoding variants associated with complex traits, nominating regulatory interactions linking INPP4B and IL15 to lymphocyte counts. The scE2G models will enable accurate mapping of enhancer-gene regulatory interactions across thousands of diverse human cell types.

genetics↗

bioRxiv2024

Cohesin-mediated 3D contacts tune enhancer-promoter regulation

Enhancers are key drivers of gene regulation thought to act via 3D physical interactions with the promoters of their target genes. However, genome-wide depletions of architectural proteins such as cohesin result in only limited changes in gene expression, despite a loss of contact domains and loops. Consequently, the role of cohesin and 3D contacts in enhancer function remains debated. Here, we developed CRISPRi of regulatory elements upon degron operation (CRUDO), a novel approach to measure how changes in contact frequency impact enhancer effects on target genes by perturbing enhancers with CRISPRi and measuring gene expression in the presence or absence of cohesin. We systematically perturbed all 1,039 candidate enhancers near five cohesin-dependent genes and identified 34 enhancer-gene regulatory interactions. Of 26 regulatory interactions with sufficient statistical power to evaluate cohesin dependence, 18 show cohesin-dependent effects. A decrease in enhancer-promoter contact frequency upon removal of cohesin is frequently accompanied by a decrease in the regulatory effect of the enhancer on gene expression, consistent with a contact-based model for enhancer function. However, changes in contact frequency and regulatory effects on gene expression vary as a function of distance, with distal enhancers (e.g., >50Kb) experiencing much larger changes than proximal ones (e.g., <50Kb). Because most enhancers are located close to their target genes, these observations can explain how only a small subset of genes -- those with strong distal enhancers -- are sensitive to cohesin. Together, our results illuminate how 3D contacts, influenced by both cohesin and genomic distance, tune enhancer effects on gene expression.

molecular biology↗

bioRxiv2023

An encyclopedia of enhancer-gene regulatory interactions in the human genome

Identifying transcriptional enhancers and their target genes is essential for understanding gene regulation and the impact of human genetic variation on disease1-6. Here we create and evaluate a resource of >13 million enhancer-gene regulatory interactions across 352 cell types and tissues, by integrating predictive models, measurements of chromatin state and 3D contacts, and large-scale genetic perturbations generated by the ENCODE Consortium7. We first create a systematic benchmarking pipeline to compare predictive models, assembling a dataset of 10,411 element-gene pairs measured in CRISPR perturbation experiments, >30,000 fine-mapped eQTLs, and 569 fine-mapped GWAS variants linked to a likely causal gene. Using this framework, we develop a new predictive model, ENCODE-rE2G, that achieves state-of-the-art performance across multiple prediction tasks, demonstrating a strategy involving iterative perturbations and supervised machine learning to build increasingly accurate predictive models of enhancer regulation. Using the ENCODE-rE2G model, we build an encyclopedia of enhancer-gene regulatory interactions in the human genome, which reveals global properties of enhancer networks, identifies differences in the functions of genes that have more or less complex regulatory landscapes, and improves analyses to link noncoding variants to target genes and cell types for common, complex diseases. By interpreting the model, we find evidence that, beyond enhancer activity and 3D enhancer-promoter contacts, additional features guide enhancer-promoter communication including promoter class and enhancer-enhancer synergy. Altogether, these genome-wide maps of enhancer-gene regulatory interactions, benchmarking software, predictive models, and insights about enhancer function provide a valuable resource for future studies of gene regulation and human genetics.

genomics↗

bioRxiv2020

Single-cell analyses reveal SARS-CoV-2 interference with intrinsic immune response in the human gut

ObjectiveExacerbated pro-inflammatory immune response contributes to COVID-19 pathology. Despite the evidence about SARS-CoV-2 infecting the human gut, little is known about the importance of the enteric phase of SARS-CoV-2 for the viral lifecycle and for the development of COVID-19-associated pathologies. Similarly, it remains unknown whether the innate immune response triggered in this organ to combat viral infection is similar or distinct compared to the one triggered in other organs. DesignWe exploited human ileum- and colon-derived organoids as a non-transformed culture model supporting SARS-CoV-2 infection. We characterized the replication kinetics of SARS-CoV-2 in intestinal epithelial cells and correlated the expression of the viral receptor ACE2 with infection. We performed conventional and targeted single-cell transcriptomics and multiplex single-molecule RNA fluorescence in situ hybridization and used IFN-reporter bioassays to characterize the response of primary human intestinal epithelial cells to SARS-CoV-2 infection. ResultsWe identified a subpopulation of enterocytes as the prime target of SARS-CoV-2. We found the lack of positive correlation between susceptibility to infection and the expression of ACE2 and revealed that SARS-CoV-2 downregulates ACE2 expression upon infection. Infected cells activated strong proinflammatory programs and produced interferon, while expression of interferon-stimulated genes was limited to bystander cells due to SARS-CoV-2 suppressing the autocrine action of interferon in infected cells. ConclusionOur findings reveal that SARS-CoV-2 curtails the immune response in primary human intestinal epithelial cells to promote its replication and spread and this highlights the gut as a proinflammatory reservoir that should be considered to fully understand SARS-CoV-2 pathogenesis. Significance of the studyWhat is already known about this subject? O_LICOVID-19 patients have gastrointestinal symptoms which likely correlates with SARS-CoV-2 infection of the intestinal epithelium C_LIO_LISARS-CoV-2 replicates in human intestinal epithelial cells. C_LIO_LIIntestinal organoids are a good model to study SARS-CoV-2 infection of the gastrointestinal tract C_LIO_LIThere is a limited interferon response in human lung epithelial cells upon SARS-CoV-2 infection. C_LI What are the new findings? O_LIA specific subpopulation of enterocytes are the prime targets of SARS-CoV-2 infection of the human gut. C_LIO_LIThere is a lack of correlation between ACE2 expression and susceptibility to SARS-CoV-2 infection. SARS-CoV-2 downregulates ACE2 expression upon infection. C_LIO_LIHuman intestinal epithelium cells produce interferon upon SARS-CoV-2 infection. C_LIO_LIInterferon acts in a paracrine manner to induce interferon stimulated genes that control viral infection only in bystander cells. C_LIO_LISARS-CoV-2 actively blocks interferon signaling in infected cells. C_LI How might it impact on clinical practice in the foreseeable future? O_LIThe absence of correlation between ACE2 levels and susceptibility suggest that medications influencing ACE2 levels (e.g. high blood pressure drugs) will not make patients more susceptible to SARS-CoV-2 infection. C_LIO_LIThe restricted cell tropism and the distinct immune response mounted by the GI tract, suggests that specific cellular restriction/replication factors and organ specific intrinsic innate immune pathways can represent unique therapeutic targets to treat COVD-19 patients by considering which organ is most infected/impacted by SARS-CoV-2. C_LIO_LIThe strong pro-inflammatory signal mounted by the intestinal epithelium can fuel the systemic inflammation observed in COVID-19 patients and is likely participating in the lung specific pathology. C_LI

immunology↗

bioRxiv2020

Combined transient ablation and single cell RNA sequencing reveals the development of medullary thymic epithelial cells

Medullary thymic epithelial cells (mTECs) play a critical role in central immune tolerance by mediating negative selection of autoreactive T cells through the collective expression of the peripheral self-antigen compartment, including tissue-specific antigens (TSAs). Recent work has shown that gene expression patterns within the mTEC compartment are remarkably heterogenous and include multiple differentiated cell states. To further define mTEC development and medullary epithelial lineage relationships, we combined lineage tracing and recovery from transient in vivo mTEC ablation with single cell RNA-sequencing. The combination of bioinformatic and experimental approaches revealed a non-stem transit-amplifying population of cycling mTECs that preceded Aire expression. Based on our findings, we propose a branching model of mTEC development wherein a heterogeneous pool of transit-amplifying cells gives rise to Aire- and Ccl21a-expressing mTEC subsets. We further use experimental techniques to show that within the Aire-expressing developmental branch, TSA expression peaked as Aire expression decreased, implying Aire expression must be established before TSA expression can occur. Collectively, these data provide a higher order roadmap of mTEC development and demonstrate the power of combinatorial approaches leveraging both in vivo models and high-dimensional datasets.

immunology↗