Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, Cambridge, MA, USA.
The Broad Institute of Harvard and MIT, Cambridge, MA, USA.
Nat Genet. 2023 Oct;55(10):1665-1676. doi: 10.1038/s41588-023-01509-5. Epub 2023 Sep 28.
Genetic variants associated with complex traits are primarily noncoding, and their effects on gene-regulatory activity remain largely uncharacterized. To address this, we profile epigenomic variation of histone mark H3K27ac across 387 brain, heart, muscle and lung samples from Genotype-Tissue Expression (GTEx). We annotate 282 k active regulatory elements (AREs) with tissue-specific activity patterns. We identify 2,436 sex-biased AREs and 5,397 genetically influenced AREs associated with 130 k genetic variants (haQTLs) across tissues. We integrate genetic and epigenomic variation to provide mechanistic insights for disease-associated loci from 55 genome-wide association studies (GWAS), by revealing candidate tissues of action, driver SNPs and impacted AREs. Lastly, we build ARE-gene linking scores based on genetics (gLink scores) and demonstrate their unique ability to prioritize SNP-ARE-gene circuits. Overall, our epigenomic datasets, computational integration and mechanistic predictions provide valuable resources and important insights for understanding the molecular basis of human diseases/traits such as schizophrenia.
与复杂性状相关的遗传变异主要是非编码的，它们对基因调控活性的影响在很大程度上仍未得到阐明。为了解决这个问题，我们对来自基因型组织表达 (GTEx) 的 387 个大脑、心脏、肌肉和肺样本中的组蛋白标记 H3K27ac 的表观基因组变异进行了分析。我们对具有组织特异性活性模式的 282000 个活跃调控元件 (ARE) 进行了注释。我们在跨组织的 130000 个遗传变异 (haQTL) 中鉴定了 2436 个性别偏向的 ARE 和 5397 个受遗传影响的 ARE。我们整合遗传和表观基因组变异，通过揭示候选作用组织、驱动 SNP 和受影响的 ARE，为来自 55 个全基因组关联研究 (GWAS) 的与疾病相关的基因座提供机制见解。最后，我们基于遗传学构建了 ARE-基因连接评分 (gLink 评分)，并证明了它们在优先考虑 SNP-ARE-基因回路方面的独特能力。总的来说，我们的表观基因组数据集、计算整合和机制预测为理解人类疾病/性状(如精神分裂症)的分子基础提供了有价值的资源和重要的见解。
