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基因组图谱可检测流感感染期间处于活跃表观基因组状态的人类多态性。

Genome graphs detect human polymorphisms in active epigenomic state during influenza infection.

作者信息

Groza Cristian, Chen Xun, Pacis Alain, Simon Marie-Michelle, Pramatarova Albena, Aracena Katherine A, Pastinen Tomi, Barreiro Luis B, Bourque Guillaume

机构信息

Quantitative Life Sciences, McGill University, Montréal, QC, Canada.

Institute for the Advanced Study of Human Biology (WPI-ASHBi), Kyoto University, Kyoto, Japan.

出版信息

Cell Genom. 2023 Apr 7;3(5):100294. doi: 10.1016/j.xgen.2023.100294. eCollection 2023 May 10.

Abstract

Genetic variants, including mobile element insertions (MEIs), are known to impact the epigenome. We hypothesized that genome graphs, which encapsulate genetic diversity, could reveal missing epigenomic signals. To test this, we sequenced the epigenome of monocyte-derived macrophages from 35 ancestrally diverse individuals before and after influenza infection, allowing us to investigate the role of MEIs in immunity. We characterized genetic variants and MEIs using linked reads and built a genome graph. Mapping epigenetic data revealed 2.3%-3% novel peaks for H3K4me1, H3K27ac chromatin immunoprecipitation sequencing (ChIP-seq), and ATAC-seq. Additionally, the use of a genome graph modified some quantitative trait loci estimates and revealed 375 polymorphic MEIs in an active epigenomic state. Among these is an AluYh3 polymorphism whose chromatin state changed after infection and was associated with the expression of , a gene that restricts influenza RNA synthesis. Our results demonstrate that graph genomes can reveal regulatory regions that would have been overlooked by other approaches.

摘要

已知包括移动元件插入(MEIs)在内的基因变异会影响表观基因组。我们推测,封装遗传多样性的基因组图谱可能会揭示缺失的表观基因组信号。为了验证这一点,我们对35名来自不同祖先的个体在流感感染前后的单核细胞衍生巨噬细胞的表观基因组进行了测序,从而能够研究MEIs在免疫中的作用。我们使用连接读数对基因变异和MEIs进行了表征,并构建了一个基因组图谱。对表观遗传数据的映射揭示了H3K4me1、H3K27ac染色质免疫沉淀测序(ChIP-seq)和ATAC-seq的2.3%-3%的新峰。此外,使用基因组图谱修改了一些数量性状位点估计,并揭示了375个处于活跃表观基因组状态的多态性MEIs。其中有一个AluYh3多态性,其染色质状态在感染后发生了变化,并与一个限制流感RNA合成的基因的表达相关。我们的结果表明,图谱基因组可以揭示其他方法可能会忽略的调控区域。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d992/10203048/01cfce367571/fx1.jpg

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