A transcription-centric model of SNP-age interaction

以转录为中心的SNP-年龄相互作用模型

阅读:2

Abstract

Complex age-associated phenotypes are caused, in part, by an interaction between an individual's genotype and age. The mechanisms governing such interactions are however not entirely understood. Here, we provide a novel transcriptional mechanism-based framework-SNiPage, to investigate such interactions, whereby a transcription factor (TF) whose expression changes with age (age-associated TF), binds to a polymorphic regulatory element in an allele-dependent fashion, rendering the target gene's expression dependent on both, the age and the genotype. Applying SNiPage to GTEx, we detected ~637 significant TF-SNP-Gene triplets on average across 25 tissues, where the TF binds to a regulatory SNP in the gene's promoter or putative enhancer and potentially regulates its expression in an age- and allele-dependent fashion. The detected SNPs are enriched for epigenomic marks indicative of regulatory activity, exhibit allele-specific chromatin accessibility, and spatial proximity to their putative gene targets. Furthermore, the TF-SNP interaction-dependent target genes have established links to aging and to age-associated diseases. In six hypertension-implicated tissues, detected interactions significantly inform hypertension state of an individual. Lastly, the age-interacting SNPs exhibit a greater proximity to the reported phenotype/diseases-associated SNPs than eSNPs identified in an interaction-independent fashion. Overall, we present a novel mechanism-based model, and a novel framework SNiPage, to identify functionally relevant SNP-age interactions in transcriptional control and illustrate their potential utility in understanding complex age-associated phenotypes.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。