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Wingett, S. W.

Publications and source records attributed to Wingett, S. W..

2 recordsLinked to original sources

Spatial RNA proximities reveal a bipartite nuclear transcriptome and territories of differential density and transcription elongation rates

Spatial transcriptomics aims to understand how the ensemble of RNA molecules in tissues and cells is organized in 3D space. Here we introduce Proximity RNA-seq, which enriches for nascent transcripts, and identifies contact preferences for individual RNAs in cell nuclei. Proximity RNA-seq is based on massive-throughput RNA-barcoding of sub-nuclear particles in water-in-oil emulsion droplets, followed by sequencing. We show a bipartite organization of the nuclear transcriptome in which compartments of different RNA density correlate with transcript families, tissue specificity and extent of alternative splicing. Integration of proximity measurements at the DNA and NA level identify transcriptionally active genomic regions with increased nucleic acid density and faster RNA polymerase II elongation located close to compact chromatin.

molecular biology

Chromosome contacts in activated T cells identify autoimmune disease-candidate genes

BackgroundAutoimmune disease-associated variants are preferentially found in regulatory regions in immune cells, particularly CD4+ T cells. Linking such regulatory regions to gene promoters in disease-relevant cell contexts facilitates identification of candidate disease genes.\n\nResultsWithin four hours, activation of CD4+ T cells invokes changes in histone modifications and enhancer RNA transcription that correspond to altered expression of the interacting genes identified by promoter capture Hi-C. By integrating promoter capture Hi-C data with genetic associations for five autoimmune diseases we prioritised 245 candidate genes with a median distance from peak signal to prioritised gene of 153 kb. Just under half (108/245) prioritised genes related to activation-sensitive interactions. This included IL2RA, where allele-specific expression analyses were consistent with its interaction-mediated regulation, illustrating the utility of the approach.\n\nConclusionsOur systematic experimental framework offers an alternative approach to candidate causal gene identification for variants with cell state-specific functional effects, with achievable sample sizes.

genomics