Clohisey, S. | Search bioRxiv

bioRxiv2019

Comprehensive characterisation of molecular host-pathogen interactions in influenza A virus-infected human macrophages

Macrophages in the lung detect and respond to influenza A virus (IAV), determining the nature of the immune response. Using terminal depth 5-RNA sequencing (CAGE) we quantify transcriptional activity of both host and pathogen over a 24-hour timecourse of IAV infection in primary human monocyte-derived macrophages (MDM). We use a systems approach to describe the transcriptional landscape of the host response to IAV contrasted with bacterial lipopolysaccharide treated MDMs, observing a failure of IAV-treated MDMs to induce feedback inhibitors of inflammation. Systematic comparison of host RNA sequences incorporated into viral mRNA (\"snatched\") against a complete survey of background RNA in the host cell enables an unbiased quantification of over-represented features of snatched host RNAs. We detect preferential snatching of RNAs associated with snRNA transcription and demonstrate that cap-snatching avoids transcripts encoding host ribosomal proteins, which are required by IAV for replication.\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=177 SRC=\"FIGDIR/small/670919v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (34K):\norg.highwire.dtl.DTLVardef@b05478org.highwire.dtl.DTLVardef@79a519org.highwire.dtl.DTLVardef@462739org.highwire.dtl.DTLVardef@1b91eb6_HPS_FORMAT_FIGEXP M_FIG C_FIG Graphical Abstract(A) Overview of bioinformatics pipeline. (B) Host gene expression reveals that human macrophages exposed to IAV exhibit sustained production of key inflammatory mediators and failure to induce expression of feedback inhibitors of inflammation. (C) Unbiased comparison with total background RNA expression demonstrates that IAV cap-snatching has a strong preference for, and aversion to, different groups of host transcripts.

immunology↗

bioRxiv2016

Shared activity patterns arising at genetic susceptibility loci reveal underlying genomic and cellular architecture of human disease.

Genetic variants underlying complex traits, including disease susceptibility, are enriched within the transcriptional regulatory elements, promoters and enhancers. There is emerging evidence that regulatory elements associated with particular traits or diseases share patterns of transcriptional regulation. Accordingly, shared transcriptional regulation (coexpression) may help prioritise loci associated with a given trait, and help to identify the biological processes underlying it. Using cap analysis of gene expression (CAGE) profiles of promoter and enhancer-derived RNAs across 1824 human samples, we have quantified coexpression of RNAs originating from trait-associated regulatory regions using a novel analytical method (network density analysis; NDA). For most traits studied, sequence variants in regulatory regions were linked to tightly coexpressed networks that are likely to share important functional characteristics. These networks implicate particular cell types and tissues in disease pathogenesis; for example, variants associated with ulcerative colitis are linked to expression in gut tissue, whereas Crohns disease variants are restricted to immune cells. We show that this coexpression signal provides additional independent information for fine mapping likely causative variants. This approach identifies additional genetic variants associated with specific traits, including an association between the regulation of the OCT1 cation transporter and genetic variants underlying circulating cholesterol levels. This approach enables a deeper biological understanding of the causal basis of complex traits.\n\nONE SENTENCE SUMMARYWe discover that variants associated with a specific disease share expression profiles across tissues and cell types, enabling fine mapping and identification of new disease-associated variants, illuminating key cell types involved in disease pathogenesis.

genomics↗