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高海拔低氧适应的染色质可及性图谱和调控网络。

Chromatin accessibility landscape and regulatory network of high-altitude hypoxia adaptation.

机构信息

State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, 650223, Kunming, China.

CEMS, NCMIS, MDIS, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, 100190, Beijing, China.

出版信息

Nat Commun. 2020 Oct 1;11(1):4928. doi: 10.1038/s41467-020-18638-8.

Abstract

High-altitude adaptation of Tibetans represents a remarkable case of natural selection during recent human evolution. Previous genome-wide scans found many non-coding variants under selection, suggesting a pressing need to understand the functional role of non-coding regulatory elements (REs). Here, we generate time courses of paired ATAC-seq and RNA-seq data on cultured HUVECs under hypoxic and normoxic conditions. We further develop a variant interpretation methodology (vPECA) to identify active selected REs (ASREs) and associated regulatory network. We discover three causal SNPs of EPAS1, the key adaptive gene for Tibetans. These SNPs decrease the accessibility of ASREs with weakened binding strength of relevant TFs, and cooperatively down-regulate EPAS1 expression. We further construct the downstream network of EPAS1, elucidating its roles in hypoxic response and angiogenesis. Collectively, we provide a systematic approach to interpret phenotype-associated noncoding variants in proper cell types and relevant dynamic conditions, to model their impact on gene regulation.

摘要

藏人对高海拔环境的适应代表了人类进化过程中自然选择的一个显著案例。先前的全基因组扫描发现了许多受选择的非编码变异,这表明迫切需要了解非编码调控元件 (REs) 的功能作用。在这里,我们生成了在缺氧和常氧条件下培养的 HUVECs 的 ATAC-seq 和 RNA-seq 数据的时间过程。我们进一步开发了一种变体解释方法 (vPECA) 来识别活性选择的 REs (ASREs) 和相关的调控网络。我们发现了三个与藏族人关键适应基因 EPAS1 相关的因果 SNP。这些 SNP 降低了 ASREs 的可及性,同时削弱了相关 TF 的结合强度,并协同下调 EPAS1 的表达。我们进一步构建了 EPAS1 的下游网络,阐明了它在缺氧反应和血管生成中的作用。总的来说,我们提供了一种系统的方法,可以在适当的细胞类型和相关的动态条件下解释与表型相关的非编码变异,从而模拟它们对基因调控的影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a398/7529806/1f106817fa73/41467_2020_18638_Fig1_HTML.jpg

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