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Multi-omics analysis in primary T cells elucidates mechanisms behind disease-associated genetic loci

生物 人类遗传学 基因组生物学 遗传学 计算生物学 进化生物学 疾病 组学 基因组学 基因组 基因 医学 病理
作者
Chenfu Shi,Danyun Zhao,J. Scott Butler,Antonios Frantzeskos,Stefano Rossi,James Ding,Carlo Ferrazzano,Charlotte Wynn,Ryan Malcolm Hum,Ellie Richards,Muskan Gupta,Khadijah Patel,Chuan Fu Yap,Darren Plant,Richard K. Grencis,Paul J. Martin,Antony Adamson,Stephen Eyre,John Bowes,Anne Barton
出处
期刊:Genome Biology [BioMed Central]
卷期号:26 (1) 被引量:2
标识
DOI:10.1186/s13059-025-03492-y
摘要

Genome-wide association studies (GWAS) have uncovered the genetic basis behind many diseases and conditions. However, most of these genetic loci affect regulatory regions, making the interpretation challenging. Chromatin conformation has a fundamental role in gene regulation and is frequently used to associate potential target genes to regulatory regions. However, previous studies mostly used small sample sizes and immortalized cell lines instead of primary cells. Here we present the most extensive dataset of chromatin conformation with matching gene expression and chromatin accessibility from primary CD4+ and CD8+ T cells to date, isolated from psoriatic arthritis patients and healthy controls. We generated 108 Hi-C libraries (49 billion reads), 128 RNA-seq libraries and 126 ATAC-seq libraries. These data enhance our understanding of the mechanisms by which GWAS variants impact gene regulation, revealing how genetic variation alters chromatin accessibility and structure in primary cells at an unprecedented scale. We refine the mapping of GWAS loci to implicated regulatory elements, such as CTCF binding sites and other enhancer elements, aiding gene assignment. We uncover BCL2L11 as the probable causal gene within the rheumatoid arthritis (RA) locus rs13396472, despite the GWAS variants' intronic positioning relative to ACOXL, and we identify mechanisms involving SESN3 dysregulation in the RA locus rs4409785. Given these genes' significant role in T cell development and maturation, our work deepens our comprehension of autoimmune disease pathogenesis, suggesting potential treatment targets. In addition, our dataset provides a valuable resource for the investigation of immune-mediated diseases and gene regulatory mechanisms.
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