Biology subjects

Maliskova, L.

Publications and source records attributed to Maliskova, L..

9 recordsLinked to original sources

bioRxiv2026

Spatial Orchestration of Skin Fibrosis by a CD8+ T cell-Myofibroblast Axis

Fibrosing skin diseases are highly morbid conditions with diverse clinical and histopathologic features. Prior work, primarily in systemic sclerosis (SSc), has yielded mixed data regarding the immune drivers of fibrosis, as well as the identity and spatial localization of pro-fibrotic fibroblast cell subsets. Here, we focus on morphea and eosinophilic fasciitis (EF), which cause more acutely inflammatory skin fibrosis. Using multimodal single-nucleus and spatial transcriptomics, we find that effector CD8+ T cells are highly enriched in fibrotic skin. These cells are particularly abundant in inflammatory tissue domains bordering fibrotic stroma, which are marked by expression of interferon-{gamma} stimulated genes. Inflammatory domains feature a loss of local homeostatic fibroblast populations and replacement with ADAM12-expressing inflammatory fibroblasts and myofibroblasts, which co-localize closely with CD8+ T cells. All subtypes of morphea featured similar patterns of CD8+ T-cell-associated fibro-inflammatory zonation and fibroblast transformation, suggesting that shared mechanisms can drive fibrosis across stromal compartments of skin. We apply these findings to a large publicly available scleroderma dataset and find that similar processes occur in SSc. Mechanistically, ablation of CD8+ T cells in mice ameliorates bleomycin-driven inflammation and fibrosis, as does fibroblast-intrinsic abrogation of IFN-{gamma} signaling. These data establish CD8+ T cell-driven fibrogenesis as a key feature of fibrosing skin diseases and raise the prospect of targeting CD8+ T cells in autoimmune fibrosis more broadly. One sentence summarySpatial profiling of morphea-spectrum diseases reveals CD8 T cells as key drivers of fibrosis through fibroblast IFN-{gamma} signaling.

immunology↗

bioRxiv2024

CRISPR tiling deletion screens reveal functional enhancers of neuropsychiatric risk genes and allelic compensation effects (ACE) on transcription

Precise transcriptional regulation is critical for cellular function and development, yet the mechanism of this process remains poorly understood for many genes. To gain a deeper understanding of the regulation of neuropsychiatric disease risk genes, we identified a total of 39 functional enhancers for four dosage-sensitive genes, APP, FMR1, MECP2, and SIN3A, using CRISPR tiling deletion screening in human induced pluripotent stem cell (iPSC)-induced excitatory neurons. We found that enhancer annotation provides potential pathological insights into disease-associated copy number variants. More importantly, we discovered that allelic enhancer deletions at SIN3A could be compensated by increased transcriptional activities from the other intact allele. Such allelic compensation effects (ACE) on transcription is stably maintained during differentiation and, once established, cannot be reversed by ectopic SIN3A expression. Further, ACE at SIN3A occurs through dosage sensing by the promoter. Together, our findings unravel a regulatory compensation mechanism that ensures stable and precise transcriptional output for SIN3A, and potentially other dosage-sensitive genes.

genetics↗

bioRxiv2023

Cell-Specific Transposable Element Gene Expression Analysis Identifies Associations with Systemic Lupus Erythematosus Phenotypes

There is an established yet unexplained link between interferon (IFN) and systemic lupus erythematosus (SLE). The expression of sequences derived from transposable elements (TEs) may contribute to production of type I IFNs and generation of autoantibodies. We profiled cell-sorted RNA-seq data (CD4+ T cells, CD14+ monocytes, CD19+ B cells, and NK cells) from PBMCs of 120 SLE patients and quantified TE expression identifying 27,135 TEs. We tested for differential TE expression across 10 SLE phenotypes including autoantibody production and disease activity and discovered 731 differentially expressed (DE) TEs whose effects were mostly cell-specific and phenotype-specific. DE TEs were enriched for specific families and viral genes encoded in TE sequences. Increased expression of DE TEs was associated with genes involved in antiviral activity such as LY6E, ISG15, TRIM22 and pathways such as interferon signaling. These findings suggest that expression of TEs contributes to activation of SLE-related mechanisms in a cell-specific manner, which can impact disease diagnostics and therapeutics.

molecular biology↗

bioRxiv2021

Parallel Characterization of cis-Regulatory Elements for Multiple Genes UsingCRISPRpath

Current pooled CRISPR screens for cis-regulatory elements (CREs) can only accommodate one gene based on its expression level. Here, we describe CRISPRpath, a scalable screening strategy for parallelly characterizing CREs of genes linked to the same biological pathway and converging phenotypes. We demonstrate the ability of CRISPRpath for simultaneously identifying functional enhancers of six genes in the 6-thioguanine-induced DNA mismatch repair pathway using both CRISPR interference (CRISPRi) and CRISPR nuclease (CRISPRn) approaches. 60% of the identified enhancers are known promoters with distinct epigenomic features compared to other active promoters, including increased chromatin accessibility and interactivity. Furthermore, by imposing different levels of selection pressure, CRISPRpath can distinguish enhancers exerting strong impact on gene expression from those exerting weak impact. Our results offer a nuanced view of cis-regulation and demonstrate that CRISPRpath can be leveraged for understanding the complex gene regulatory program beyond transcriptional output at scale.

genomics↗

bioRxiv2020

Ethnicity-specific transcriptomic variation in immune cells and correlation with disease activity in systemic lupus erythematosus

Systemic lupus erythematosus (SLE) is a heterogeneous autoimmune disease in which outcomes vary among different racial groups. The aim of this study is to leverage large-scale transcriptomic data from diverse populations to better sub-classify SLE patients into more clinically actionable groups. We leverage cell sorted RNA-seq data (CD14+ monocytes, B cells, CD4+T cells, and NK cells) from 120 SLE patients (63 Asian and 57 White individuals) and apply a four tier analytical approach to identify SLE subgroups within this multiethnic cohort: unsupervised clustering, differential expression analyses, gene co-expression analyses, and machine learning. K-means clustering on the individual cell type data resulted in three clusters for CD4 and CD14, and two clusters for B cells and NK cells. Correlation analysis revealed significant positive associations between the transcriptomic clusters of each immune cell and clinical parameters including disease activity and ethnicity. We then explored differentially expressed genes between Asian and White groups for each cell-type. The shared differentially expressed genes across the four cell types were involved in SLE or other autoimmune related pathways. Co-expression analysis identified similarly regulated genes across samples and grouped these genes into modules. Samples were grouped into White-high, Asians-high (high disease activity defined by SLEDAI score >=6) and White-low, Asians-low (SLEDAI < 6). Random forest classification of disease activity in the White and Asian cohorts showed the best classification in CD4+ T cells in White. The results from these analyses will help stratify patients based on their gene expression signatures to enable precision medicine for SLE.

bioinformatics↗

bioRxiv2020

3D Epigenomic Characterization Reveals Insights Into Gene Regulation and Lineage Specification During Corticogenesis

Lineage-specific epigenomic changes during human corticogenesis have previously remained elusive due to challenges with tissue heterogeneity and sample availability. Here, we analyze cis-regulatory chromatin interactions, open chromatin regions, and transcriptomes for radial glia, intermediate progenitor cells, excitatory neurons, and interneurons isolated from mid-gestational human brain samples. We show that chromatin looping underlies transcriptional regulation for lineage-specific genes, with transcription factor motifs, families of transposable elements, and disease-associated variants enriched at distal interacting regions in a cell type-specific manner. A subset of promoters exhibit unusually high degrees of chromatin interactivity, which we term super interactive promoters. Super interactive promoters are enriched for critical lineage-specific genes, suggesting that interactions at these loci contribute to the fine-tuning of cell type-specific transcription. Finally, we present CRISPRview, a novel approach for validating distal interacting regions in primary cells. Our study presents the first characterization of cell type-specific 3D epigenomic landscapes during human corticogenesis, advancing our understanding of gene regulation and lineage specification during human brain development.

genomics↗

bioRxiv2018

cis-Regulatory Chromatin Contacts in Neural Cells Reveal Contributions of Genetic Variants to Complex Neurological Disorders

Mutations in gene regulatory elements have been associated with a wide range of complex neurological disorders. However, due to their inherent cell type-specificity and difficulties in characterizing their regulatory targets, our ability to identify causal genetic variants has remained limited. To address these constraints, we perform integrative analysis of chromatin interactions using promoter capture Hi-C (pcHi-C), open chromatin regions using ATAC-seq, and transcriptomes using RNA-seq in four functionally distinct neural cell types: iPSC-induced excitatory neurons and lower motor neurons, iPSC-derived hippocampal dentate gyrus (DG)-like neurons, and primary astrocytes. We identify hundreds of thousands of long-range cis interactions between promoters and distal promoter-interacting regions (PIRs), enabling us to link regulatory elements to their target genes and reveal putative pathways that are dysregulated in disease. We validate several novel PIRs using CRISPR techniques in human excitatory neurons, demonstrating that CDK5RAP3, STRAP, and DRD2 are transcriptionally regulated by physically linked enhancers. Finally, we show that physical chromatin interactions mediate genetic interactions in autism spectrum disorder (ASD). Our study illustrates how characterizing the 3D epigenome elucidates novel regulatory relationships in the central nervous system (CNS), shedding light on previously unknown functions for noncoding variants in complex neurological disorders.

genomics↗

bioRxiv2017

Promoter Or Enhancer Activation By CRISPRa Rescues Haploinsufficiency Caused Obesity

Haploinsufficiency, having only one functional copy of a gene, leads to a wide range of human disease and has been associated with over 300 genes. Here, we tested whether CRISPR activation (CRISPRa) could rescue a haploinsufficient disease in vivo. Haploinsufficiency of Sim1, a transcription factor involved in the leptin pathway, results in severe obesity in humans and mice. CRISPRa targeting of either the Sim1 promoter or its ~270kb distant hypothalamic enhancer using transgenic mice, rescued the obesity phenotype in Sim1 heterozygous mice. Interestingly, despite using a ubiquitous promoter for CRISPRa, Sim1 was upregulated only in tissues where the promoter or enhancer are active, suggesting that cis-regulatory elements can determine CRISPRa tissue-specificity. To further relate this to therapy, we injected CRISPRa adeno associated virus into the hypothalamus, leading to reversal of the obesity phenotype. This therapeutic strategy could be used to rescue numerous diseases resulting from altered gene dosage.

genetics↗

bioRxiv2017

Multiplexing droplet-based single cell RNA-sequencing using natural genetic barcodes

Droplet-based single-cell RNA-sequencing (dscRNA-seq) has enabled rapid, massively parallel profiling of transcriptomes from tens of thousands of cells. Multiplexing samples for single cell capture and library preparation in dscRNA-seq would enable cost-effective designs of differential expression and genetic studies while avoiding technical batch effects, but its implementation remains challenging. Here, we introduce an in-silico algorithm demuxlet that harnesses natural genetic variation to discover the sample identity of each cell and identify droplets containing two cells. These capabilities enable multiplexed dscRNA-seq experiments where cells from unrelated individuals are pooled and captured at higher throughput than standard workflows. To demonstrate the performance of demuxlet, we sequenced 3 pools of peripheral blood mononuclear cells (PBMCs) from 8 lupus patients. Given genotyping data for each individual, demuxlet correctly recovered the sample identity of > 99% of singlets, and identified doublets at rates consistent with previous estimates. In PBMCs, we demonstrate the utility of multiplexed dscRNA-seq in two applications: characterizing cell type specificity and inter-individual variability of cytokine response from 8 lupus patients and mapping genetic variants associated with cell type specific gene expression from 23 donors. Demuxlet is fast, accurate, scalable and could be extended to other single cell datasets that incorporate natural or synthetic DNA barcodes.

bioinformatics↗