48 research outputs found

    Prioritisation of Candidate Genes Underpinning COVID-19 Host Genetic Traits Based on High-Resolution 3D Chromosomal Topology

    Get PDF
    Genetic variants showing associations with specific biological traits and diseases detected by genome-wide association studies (GWAS) commonly map to non-coding DNA regulatory regions. Many of these regions are located considerable distances away from the genes they regulate and come into their proximity through 3D chromosomal interactions. We previously developed COGS, a statistical pipeline for linking GWAS variants with their putative target genes based on 3D chromosomal interaction data arising from high-resolution assays such as Promoter Capture Hi-C (PCHi-C). Here, we applied COGS to COVID-19 Host Genetic Consortium (HGI) GWAS meta-analysis data on COVID-19 susceptibility and severity using our previously generated PCHi-C results in 17 human primary cell types and SARS-CoV-2-infected lung carcinoma cells. We prioritise 251 genes putatively associated with these traits, including 16 out of 47 genes highlighted by the GWAS meta-analysis authors. The prioritised genes are expressed in a broad array of tissues, including, but not limited to, blood and brain cells, and are enriched for genes involved in the inflammatory response to viral infection. Our prioritised genes and pathways, in conjunction with results from other prioritisation approaches and targeted validation experiments, will aid in the understanding of COVID-19 pathology, paving the way for novel treatments

    The impact of chromatin modifiers on the timing of locus replication in mouse embryonic stem cells

    Get PDF
    A panel of mutant embryonic stem (ES) cell lines lacking important chromatin modifiers was used to dissect the relationship between chromatin structure and replication timing, revealing the importance of several chromatin modifiers for maintaining correct replication of satellite sequences in pluripotent ES cells

    Disease-relevant transcriptional signatures identified in individual smooth muscle cells from healthy mouse vessels.

    Get PDF
    Vascular smooth muscle cells (VSMCs) show pronounced heterogeneity across and within vascular beds, with direct implications for their function in injury response and atherosclerosis. Here we combine single-cell transcriptomics with lineage tracing to examine VSMC heterogeneity in healthy mouse vessels. The transcriptional profiles of single VSMCs consistently reflect their region-specific developmental history and show heterogeneous expression of vascular disease-associated genes involved in inflammation, adhesion and migration. We detect a rare population of VSMC-lineage cells that express the multipotent progenitor marker Sca1, progressively downregulate contractile VSMC genes and upregulate genes associated with VSMC response to inflammation and growth factors. We find that Sca1 upregulation is a hallmark of VSMCs undergoing phenotypic switching in vitro and in vivo, and reveal an equivalent population of Sca1-positive VSMC-lineage cells in atherosclerotic plaques. Together, our analyses identify disease-relevant transcriptional signatures in VSMC-lineage cells in healthy blood vessels, with implications for disease susceptibility, diagnosis and prevention.BH

    CHiCAGO: robust detection of DNA looping interactions in Capture Hi-C data.

    Get PDF
    Capture Hi-C (CHi-C) is a method for profiling chromosomal interactions involving targeted regions of interest, such as gene promoters, globally and at high resolution. Signal detection in CHi-C data involves a number of statistical challenges that are not observed when using other Hi-C-like techniques. We present a background model and algorithms for normalisation and multiple testing that are specifically adapted to CHi-C experiments. We implement these procedures in CHiCAGO ( http://regulatorygenomicsgroup.org/chicago ), an open-source package for robust interaction detection in CHi-C. We validate CHiCAGO by showing that promoter-interacting regions detected with this method are enriched for regulatory features and disease-associated SNPs

    Analysis of variation at transcription factor binding sites in Drosophila and humans

    Get PDF
    Background: Advances in sequencing technology have boosted population genomics and made it possible to map the positions of transcription factor binding sites (TFBSs) with high precision. Here we investigate TFBS variability by combining transcription factor binding maps generated by ENCODE, modENCODE, our previously published data and other sources with genomic variation data for human individuals and Drosophila isogenic lines. Results: We introduce a metric of TFBS variability that takes into account changes in motif match associated with mutation and makes it possible to investigate TFBS functional constraints instance-by-instance as well as in sets that share common biological properties. We also take advantage of the emerging per-individual transcription factor binding data to show evidence that TFBS mutations, particularly at evolutionarily conserved sites, can be efficiently buffered to ensure coherent levels of transcription factor binding. Conclusions: Our analyses provide insights into the relationship between individual and interspecies variation and show evidence for the functional buffering of TFBS mutations in both humans and flies. In a broad perspective, these results demonstrate the potential of combining functional genomics and population genetics approaches for understanding gene regulation.European Molecular Biology Laboratory (interdisciplinary fellowship (EIPOD))Deutsche Forschungsgemeinschaft (DFG FU 750/1-1

    Genetic perturbation of PU.1 binding and chromatin looping at neutrophil enhancers associates with autoimmune disease.

    Get PDF
    Neutrophils play fundamental roles in innate immune response, shape adaptive immunity, and are a potentially causal cell type underpinning genetic associations with immune system traits and diseases. Here, we profile the binding of myeloid master regulator PU.1 in primary neutrophils across nearly a hundred volunteers. We show that variants associated with differential PU.1 binding underlie genetically-driven differences in cell count and susceptibility to autoimmune and inflammatory diseases. We integrate these results with other multi-individual genomic readouts, revealing coordinated effects of PU.1 binding variants on the local chromatin state, enhancer-promoter contacts and downstream gene expression, and providing a functional interpretation for 27 genes underlying immune traits. Collectively, these results demonstrate the functional role of PU.1 and its target enhancers in neutrophil transcriptional control and immune disease susceptibility

    Lineage-specific dynamic and pre-established enhancer–promoter contacts cooperate in terminal differentiation

    Get PDF
    Chromosome conformation is an important feature of metazoan gene regulation; however, enhancer–promoter contact remodeling during cellular differentiation remains poorly understood. To address this, genome-wide promoter capture Hi-C (CHi-C) was performed during epidermal differentiation. Two classes of enhancer–promoter contacts associated with differentiation-induced genes were identified. The first class ('gained') increased in contact strength during differentiation in concert with enhancer acquisition of the H3K27ac activation mark. The second class ('stable') were pre-established in undifferentiated cells, with enhancers constitutively marked by H3K27ac. The stable class was associated with the canonical conformation regulator cohesin, whereas the gained class was not, implying distinct mechanisms of contact formation and regulation. Analysis of stable enhancers identified a new, essential role for a constitutively expressed, lineage-restricted ETS-family transcription factor, EHF, in epidermal differentiation. Furthermore, neither class of contacts was observed in pluripotent cells, suggesting that lineage-specific chromatin structure is established in tissue progenitor cells and is further remodeled in terminal differentiation
    corecore