ArticlePLoS genetics2022
Super interactive promoters provide insight into cell type-specific regulatory networks in blood lineage cell types.
Article in PLoS genetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed, 4 citations in OpenAlex.
- Discovery of target genes and pathways at GWAS loci by pooled single-cell CRISPR screens.Science (New York, N.Y.) · 2023Article
- Whole genome sequencing identifies structural variants contributing to hematologic traits in the NHLBI TOPMed program.Nature communications · 2022Article
- Understanding the function of regulatory DNA interactions in the interpretation of non-coding GWAS variants.Frontiers in cell and developmental biology · 2022Review
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Authors and funding
11 authors at 4 institutions in 2 countries.
Funding
Abstract
Existing studies of chromatin conformation have primarily focused on potential enhancers interacting with gene promoters. By contrast, the interactivity of promoters per se, while equally critical to understanding transcriptional control, has been largely unexplored, particularly in a cell type-specific manner for blood lineage cell types. In this study, we leverage promoter capture Hi-C data across a compendium of blood lineage cell types to identify and characterize cell type-specific super-interactive promoters (SIPs). Notably, promoter-interacting regions (PIRs) of SIPs are more likely to overlap with cell type-specific ATAC-seq peaks and GWAS variants for relevant blood cell traits than PIRs of non-SIPs. Moreover, PIRs of cell-type-specific SIPs show enriched heritability of relevant blood cell trait (s), and are more enriched with GWAS variants associated with blood cell traits compared to PIRs of non-SIPs. Further, SIP genes tend to express at a higher level in the corresponding cell type. Importantly, SIP subnetworks incorporating cell-type-specific SIPs and ATAC-seq peaks help interpret GWAS variants. Examples include GWAS variants associated with platelet count near the megakaryocyte SIP gene EPHB3 and variants associated lymphocyte count near the native CD4 T-Cell SIP gene ETS1. Interestingly, around 25.7% ~ 39.6% blood cell traits GWAS variants residing in SIP PIR regions disrupt transcription factor binding motifs. Importantly, our analysis shows the potential of using promoter-centric analyses of chromatin spatial organization data to identify biologically important genes and their regulatory regions.
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