The Genetic Architecture of Gene Expression in Peripheral Blood
The Genetic Architecture of Gene Expression in Peripheral Blood
复制标题
DOI：
10.1016/j.ajhg.2016.12.008
复制
发表时间：
2017-02-02
影响因子：
9.8
通讯作者：
Powell, Joseph E.
中科院分区：
文献类型：
--
作者：
Lloyd-Jones, Luke R.;Holloway, Alexander;Powell, Joseph E.
我们分析了来自2,765个个体的36,778个转录表达特征(探针)的mRNA水平，以全面调查外周血中基因表达的遗传结构和缺失遗传度。我们使用线性混合模型进行全基因组关联分析，确定了11,204个顺式和3,791个反式独立表达的数量性状基因座(EQTL)。此外，利用近亲和远亲个体的信息，对所有表达性状的遗传力进行了估计。在15,966个表达探针中，10,580个(66%)的估计狭义遗传度(h(2))大于零，平均(中位数)为0.192(0.142)。在这些探针中，所有eQTL(h(Colo)(2))解释的遗传变异的比例平均为31%(0.060/0.192)，这意味着69%的eQTL缺失，其中最大的eQTL的前哨SNP解释了87A，(0.052/0.060)所有已识别的顺式和反式eQTL解释了遗传变异。对于同一套探针，全基因组共同(MAF>；0.01)HapMap3SNPs(h(Q)(2))的遗传变异平均占h(2)的48%(0.093/0.192)。综上所述，证据表明，大约一半的基因表达的遗传变异不是由普通SNPs标记的，而在由普通SNPs标记的变异中，很大一部分可以归因于可识别的大效应eQTL，通常在顺基因中。最后，我们提出了证据，与荟萃分析相比，使用个体水平的数据导致检测eQTL的能力增加了约50%。
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 (h(2)) 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 (h(COlO)(2)) was 31% (0.060/0.192), meaning that 69% is missing, with the sentinel SNP of the largest eQTL explaining 87 A, (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 (h(q)(2)) accounted for on average 48% (0.093/0.192) of h(2). 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.