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Servaas, N.

Publications and source records attributed to Servaas, N..

2 recordsLinked to original sources

GRaNIE and GRaNPA: Inference and evaluation of enhancer-mediated gene regulatory networks applied to study macrophages

Among the biggest challenges in the post-GWAS (genome-wide association studies) era is the interpretation of disease-associated genetic variants in non-coding genomic regions. Enhancers have emerged as key players in mediating the effect of genetic variants on complex traits and diseases. Their activity is regulated by a combination of transcription factors (TFs), epigenetic changes and genetic variants. Several approaches exist to link enhancers to their target genes, and others that infer TF-gene connections. However, we currently lack a framework that systematically integrates enhancers into TF-gene regulatory networks. Furthermore, we lack an unbiased way of assessing whether inferred regulatory interactions are biologically meaningful. Here we present two methods, implemented as user-friendly R packages: GRaNIE (Gene Regulatory Network Inference including Enhancers) for building enhancer-based gene regulatory networks (eGRNs) and GRaNPA (Gene Regulatory Network Performance Analysis) for evaluating GRNs. GRaNIE jointly infers TF-enhancer, enhancer-gene and TF-gene interactions by integrating open chromatin data such as ATAC-Seq or H3K27ac with RNA-seq across a set of samples (e.g. individuals), and optionally also Hi-C data. GRaNPA is a general framework for evaluating the biological relevance of TF-gene GRNs by assessing their performance for predicting cell-type specific differential expression. We demonstrate the power of our tool-suite by investigating gene regulatory mechanisms in macrophages that underlie their response to infection and cancer, their involvement in common genetic diseases including autoimmune diseases, and identify the TF PURA as putative regulator of pro-inflammatory macrophage polarisation. Availability- GRaNIE: https://bioconductor.org/packages/release/bioc/html/GRaNIE.html - GRaNPA: https://git.embl.de/grp-zaugg/GRaNPA Graphical abstract O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY

genomics↗

Whole transcriptome-sequencing and network analysis of CD1c+ human dendritic cells identifies cytokine-secreting subsets linked to type I IFN-negative autoimmunity to the eye

BackgroundType I interferons (IFNs) promote the expansion of subsets of CD1c+ conventional dendritic cells (CD1c+ DCs), but the molecular basis of CD1c+ DCs involvement in conditions not associated without elevated type I IFNs remains unclear. MethodsWe analyzed CD1c+ DCs from two cohorts of non-infectious uveitis patients and healthy donors using RNA-sequencing followed by high-dimensional flow cytometry to characterize the CD1c+ DC populations. ResultsWe report that the CD1c+ DCs pool from patients with non-infectious uveitis is skewed towards a gene module with the chemokine receptor CX3CR1 as the key hub gene. We confirmed these results in an independent case-control cohort and show that the disease-associated gene module is not mediated by type I IFNs. An analysis of peripheral blood using flow cytometry revealed that CX3CR1+ DC3s were diminished, whereas CX3CR1-DC3s were not. Stimulated CX3CR1+ DC3s secrete high levels of inflammatory cytokines, including TNF-alpha, and CX3CR1+ DC3-like cells can be detected in inflamed eyes of patients. ConclusionsThese results show that CX3CR1+ DC3s are implicated in non-infectious uveitis and can secrete proinflammatory mediators implicated in its pathophysiology. FundingThe presented work is supported by UitZicht (project number #2014-4, #2019-10, an #2021-4). The funders had no role in the design, execution, interpretation, or writing of the study.

immunology↗