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Genetic analyses support the contribution of mRNA N6-methyladenosine (m6A) modification to human disease heritability.
Nature Genetics ( IF 31.7 ) Pub Date : 2020-06-29 , DOI: 10.1038/s41588-020-0644-z
Zijie Zhang 1, 2 , Kaixuan Luo 3 , Zhongyu Zou 1, 2 , Maguanyun Qiu 1, 2 , Jiakun Tian 1, 2 , Laura Sieh 1, 2 , Hailing Shi 1, 2 , Yuxin Zou 4 , Gao Wang 3 , Jean Morrison 3 , Allen C Zhu 1, 2, 5 , Min Qiao 6 , Zhongshan Li 3, 7 , Matthew Stephens 3, 4 , Xin He 3 , Chuan He 1, 2, 5, 8
Affiliation  

N6-methyladenosine (m6A) plays important roles in regulating messenger RNA processing. Despite rapid progress in this field, little is known about the genetic determinants of m6A modification and their role in common diseases. In this study, we mapped the quantitative trait loci (QTLs) of m6A peaks in 60 Yoruba (YRI) lymphoblastoid cell lines. We found that m6A QTLs are largely independent of expression and splicing QTLs and are enriched with binding sites of RNA-binding proteins, RNA structure-changing variants and transcriptional features. Joint analysis of the QTLs of m6A and related molecular traits suggests that the downstream effects of m6A are heterogeneous and context dependent. We identified proteins that mediate m6A effects on translation. Through integration with data from genome-wide association studies, we show that m6A QTLs contribute to the heritability of various immune and blood-related traits at levels comparable to splicing QTLs and roughly half of expression QTLs. By leveraging m6A QTLs in a transcriptome-wide association study framework, we identified putative risk genes of these traits.



中文翻译:


遗传分析支持 mRNA N6-甲基腺苷 (m6A) 修饰对人类疾病遗传性的贡献。



N 6 -甲基腺苷 (m 6 A) 在调节信使 RNA 加工中发挥重要作用。尽管该领域取得了快速进展,但人们对 m 6 A 修饰的遗传决定因素及其在常见疾病中的作用知之甚少。在本研究中,我们绘制了 60 个约鲁巴 (YRI) 类淋巴母细胞系中 m 6 A 峰的数量性状位点 (QTL)。我们发现 m 6 A QTL 在很大程度上独立于表达和剪接 QTL,并且富含 RNA 结合蛋白的结合位点、RNA 结构改变变体和转录特征。 m 6 A 的 QTL 和相关分子性状的联合分析表明,m 6 A 的下游效应是异质的且依赖于环境。我们鉴定了介导 m 6 A 对翻译的影响的蛋白质。通过与全基因组关联研究的数据整合,我们发现 m 6 A QTL 对各种免疫和血液相关性状的遗传性有贡献,其水平与剪接 QTL 和大约一半的表达 QTL 相当。通过在全转录组关联研究框架中利用 m 6 A QTL,我们确定了这些性状的假定风险基因。

更新日期:2020-06-29
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