表达数量性状基因座
数量性状位点
生物
遗传建筑学
遗传学
全基因组关联研究
遗传力
特质
计算生物学
基因组学
基因
基因组
基因型
单核苷酸多态性
计算机科学
程序设计语言
作者
Farhad Hormozdiari,Steven Gazal,Bryce van de Geijn,Hilary Finucane,Chelsea J.‐T. Ju,Po−Ru Loh,Armin Schoech,Yakir Reshef,Xuanyao Liu,Luke O’Connor,Alexander Gusev,Eleazar Eskin,Alkes L. Price
出处
期刊:Nature Genetics
[Springer Nature]
日期:2018-06-25
卷期号:50 (7): 1041-1047
被引量:155
标识
DOI:10.1038/s41588-018-0148-2
摘要
There is increasing evidence that many risk loci found using genome-wide association studies are molecular quantitative trait loci (QTLs). Here we introduce a new set of functional annotations based on causal posterior probabilities of fine-mapped molecular cis-QTLs, using data from the Genotype-Tissue Expression (GTEx) and BLUEPRINT consortia. We show that these annotations are more strongly enriched for heritability (5.84× for eQTLs; P = 1.19 × 10-31) across 41 diseases and complex traits than annotations containing all significant molecular QTLs (1.80× for expression (e)QTLs). eQTL annotations obtained by meta-analyzing all GTEx tissues generally performed best, whereas tissue-specific eQTL annotations produced stronger enrichments for blood- and brain-related diseases and traits. eQTL annotations restricted to loss-of-function intolerant genes were even more enriched for heritability (17.06×; P = 1.20 × 10-35). All molecular QTLs except splicing QTLs remained significantly enriched in joint analysis, indicating that each of these annotations is uniquely informative for disease and complex trait architectures.
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