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免疫和 B 细胞相关疾病的等位基因特异性染色质信号、3D 相互作用和基序预测。

Allele specific chromatin signals, 3D interactions, and motif predictions for immune and B cell related diseases.

机构信息

Science for Life Laboratory, Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.

Department of Cell and Molecular Biology, Computational Biology and Bioinformatics, Uppsala University, Uppsala, Sweden.

出版信息

Sci Rep. 2019 Feb 25;9(1):2695. doi: 10.1038/s41598-019-39633-0.

Abstract

Several Genome Wide Association Studies (GWAS) have reported variants associated to immune diseases. However, the identified variants are rarely the drivers of the associations and the molecular mechanisms behind the genetic contributions remain poorly understood. ChIP-seq data for TFs and histone modifications provide snapshots of protein-DNA interactions allowing the identification of heterozygous SNPs showing significant allele specific signals (AS-SNPs). AS-SNPs can change a TF binding site resulting in altered gene regulation and are primary candidates to explain associations observed in GWAS and expression studies. We identified 17,293 unique AS-SNPs across 7 lymphoblastoid cell lines. In this set of cell lines we interrogated 85% of common genetic variants in the population for potential regulatory effect and we identified 237 AS-SNPs associated to immune GWAS traits and 714 to gene expression in B cells. To elucidate possible regulatory mechanisms we integrated long-range 3D interactions data to identify putative target genes and motif predictions to identify TFs whose binding may be affected by AS-SNPs yielding a collection of 173 AS-SNPs associated to gene expression and 60 to B cell related traits. We present a systems strategy to find functional gene regulatory variants, the TFs that bind differentially between alleles and novel strategies to detect the regulated genes.

摘要

几项全基因组关联研究(GWAS)已经报道了与免疫疾病相关的变异。然而,鉴定出的变异很少是关联的驱动因素,遗传贡献的分子机制仍知之甚少。TF 和组蛋白修饰的 ChIP-seq 数据提供了蛋白质-DNA 相互作用的快照,允许识别显示显著等位基因特异性信号(AS-SNPs)的杂合 SNPs。AS-SNPs 可以改变 TF 结合位点,导致基因调控改变,是解释 GWAS 和表达研究中观察到的关联的主要候选者。我们在 7 个淋巴母细胞系中鉴定了 17,293 个独特的 AS-SNPs。在这组细胞系中,我们检测了人群中 85%的常见遗传变异是否具有潜在的调节作用,我们鉴定了 237 个与免疫 GWAS 特征相关的 AS-SNPs 和 714 个与 B 细胞基因表达相关的 AS-SNPs。为了阐明可能的调节机制,我们整合了长程 3D 相互作用数据,以识别可能的靶基因,并进行基序预测,以识别可能受到 AS-SNPs 影响的 TF,从而产生了 173 个与基因表达相关和 60 个与 B 细胞相关的性状相关的 AS-SNPs 集合。我们提出了一种系统策略来寻找功能基因调节变异、等位基因之间结合不同的 TF 以及检测调节基因的新策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f21/6389883/5beb6860a1dc/41598_2019_39633_Fig1_HTML.jpg

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