From the Department of Physiology, Center of Systems Molecular Medicine (M.K.M., E.Y.L., A.M.G., P.L., A.S.G., M.L., Y.L.), Medical College of Wisconsin, Milwaukee.
Joseph J. Zilber School of Public Health, University of Wisconsin-Milwaukee (P.W.L.A.).
Hypertension. 2020 Mar;75(3):859-868. doi: 10.1161/HYPERTENSIONAHA.119.14109. Epub 2020 Jan 6.
The objective of the current study is to use comparative and functional genomic analysis to help to understand the biological mechanism mediating the effect of single nucleotide polymorphisms (SNPs) on blood pressure. We mapped 26 585 SNPs that are in linkage disequilibrium with 1071 human blood pressure-associated sentinel SNPs to 9447 syntenic regions in the mouse genome. Approximately 21.8% of the 1071 linkage disequilibrium regions are located at least 10 kb from any protein-coding gene. Approximately 300 blood pressure-associated SNPs are expression quantitative trait loci for a few dozen known blood pressure physiology genes in tissues including specific kidney regions. Blood pressure-associated sentinel SNPs are significantly enriched for expression quantitative trait loci for blood pressure physiology genes compared with randomly selected SNPs (<0.00023, Fisher exact test). Using a newly developed deep learning method and other methods, we identified SNPs that were predicted to influence the conservation of CTCF (CCCTC-binding factor) binding across cell types, transcription factor binding, mRNA splicing, or secondary structures of RNA including long noncoding RNA. The SNPs were more likely to be located in CTCF-binding regions than what would be expected from the whole genome (=4.90×10, Pearson χ test). One example synonymous SNP rs9337951 was predicted to influence the secondary structure of its host mRNA JCAD (junctional cadherin 5 associated) and was experimentally validated to influence JCAD protein expression. These findings provide an extensive comparative and functional genomic resource for developing experiments to test the functional significance of human blood pressure-associated SNPs in human cells and animal models.
本研究的目的是利用比较和功能基因组分析来帮助理解介导单核苷酸多态性(SNP)对血压影响的生物学机制。我们将 26585 个与 1071 个人类血压相关的哨点 SNP 连锁不平衡的 SNP 映射到小鼠基因组的 9447 个同线区域。大约 1071 个连锁不平衡区域中,有 21.8%至少位于 10kb 以外的任何蛋白编码基因。大约 300 个与血压相关的 SNP 是包括特定肾脏区域在内的几种已知血压生理学基因的表达数量性状基因座。与随机选择的 SNP 相比,与血压相关的哨点 SNP 明显富集了血压生理学基因的表达数量性状基因座(<0.00023,Fisher 精确检验)。使用一种新开发的深度学习方法和其他方法,我们鉴定了预测影响 CTCF(CCCTC 结合因子)在细胞类型之间结合、转录因子结合、mRNA 剪接或包括长非编码 RNA 在内的 RNA 二级结构的 SNP。这些 SNP 更有可能位于 CTCF 结合区域,而不是整个基因组的 SNP (=4.90×10,Pearson χ 检验)。一个同义 SNP rs9337951 被预测会影响其宿主 mRNA JCAD(连接钙粘蛋白 5 相关)的二级结构,并且实验验证了它会影响 JCAD 蛋白的表达。这些发现为在人类细胞和动物模型中测试人类血压相关 SNP 的功能意义提供了广泛的比较和功能基因组资源。