The Genetic Architecture of Gene Expression in Peripheral Blood

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• 作者：Luke R. Lloyd-Jones¹ ; ² ; ⁷ ; ^{l.lloydjones@uq.edu.au} ; Alexander Holloway² ; ⁷ ; Allan McRae¹ ; Jian Yang¹ ; ² ; Kerrin Small³ ; Jing Zhao⁴ ; Biao Zeng⁴ ; Andrew Bakshi² ; Andres Metspalu⁵ ; Manolis Dermitzakis⁶ ; Greg Gibson⁴ ; Tim Spector³ ; Grant Montgomery¹ ; Tonu Esko⁵ ; Peter M. Visscher¹ ; ² ; ⁷ ; Joseph E. Powell¹ ; ² ; ⁷ ; ^{joseph.powell@uq.edu.au}
• 关键词：gene expression ; genetic architecture ; genetic association study ; heritability ; linear mixed models
• 刊名：The American Journal of Human Genetics
• 出版年：2017
• 出版时间：2 February 2017
• 年：2017
• 卷：100
• 期：2
• 页码：228-237
• 全文大小：838 K
• 卷排序：100

文摘

We analyzed the mRNA levels for 36,778 transcript expression traits (probes) from 2,765 individuals to comprehensively investigate the genetic architecture and degree of missing heritability for gene expression in peripheral blood. We identified 11,204 cis and 3,791 trans independent expression quantitative trait loci (eQTL) by using linear mixed models to perform genome-wide association analyses. Furthermore, using information on both closely and distantly related individuals, heritability was estimated for all expression traits. Of the set of expressed probes (15,966), 10,580 (66%) had an estimated narrow-sense heritability (h2) greater than zero with a mean (median) value of 0.192 (0.142). Across these probes, on average the proportion of genetic variance explained by all eQTL (hCOJO2) was 31% (0.060/0.192), meaning that 69% is missing, with the sentinel SNP of the largest eQTL explaining 87% (0.052/0.060) of the variance attributed to all identified cis- and trans  -eQTL. For the same set of probes, the genetic variance attributed to genome-wide common (MAF > 0.01) HapMap 3 SNPs (hg2) accounted for on average 48% (0.093/0.192) of h2. Taken together, the evidence suggests that approximately half the genetic variance for gene expression is not tagged by common SNPs, and of the variance that is tagged by common SNPs, a large proportion can be attributed to identifiable eQTL of large effect, typically in cis. Finally, we present evidence that, compared with a meta-analysis, using individual-level data results in an increase of approximately 50% in power to detect eQTL.