Impact of admixture and ancestry on eQTL analysis and GWAS colocalization in GTEx
Impact of admixture and ancestry on eQTL analysis and GWAS colocalization in GTEx
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DOI：
10.1186/s13059-020-02113-0
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发表时间：
2020-09-11
期刊：
影响因子：
12.3
通讯作者：
Montgomery, Stephen B.
中科院分区：
文献类型：
--
作者：
Gay, Nicole R.;Gloudemans, Michael;Montgomery, Stephen B.
研究背景研究对象的群体结构可能混淆遗传关联研究，缺乏适当的校正可能导致虚假的结果。基因型-组织表达（GTEx）项目主要包含欧洲血统的个体，但v8版本也包括多达15%的非欧洲血统的个体。评估祖先为基础的调整GTEx提高了这项研究的可移植性在人群中，并进一步表征人口结构对GWAS colocalization.ResultsHere的影响，我们确定了一个子集的117个人在GTEx（V8）具有高度的人口混合和估计全基因组的地方血统。我们进行全基因组cis-eQTL定位使用混合样品在7个组织，调整全球或当地的祖先。与以前的工作一致，我们观察到改善的权力与当地祖先的调整。在两个调整产生不同前导变异的位点，我们观察到31个位点（0.02%），其中一个显着的共定位仅被称为一个eQTL祖先调整方法。值得注意的是，这两种调整在两种不同的共定位方法中的每一种中产生相似数量的显著共定位，CONOM和FINEMAP。最后，我们确定了一个小的子集的eQTL相关的变体高度相关的地方祖先，提供了一个资源，以提高功能follow-up.ConclusionsWe提供了一个本地的祖先地图混合个人在GTEx v8版本，并描述了祖先和混合物对基因表达，eQTL，和GWAS共定位的影响。虽然大多数的结果是一致的本地和全球的祖先为基础的调整，我们确定了不同的优点和缺点，每种方法。
BackgroundPopulation structure among study subjects may confound genetic association studies, and lack of proper correction can lead to spurious findings. The Genotype-Tissue Expression (GTEx) project largely contains individuals of European ancestry, but the v8 release also includes up to 15% of individuals of non-European ancestry. Assessing ancestry-based adjustments in GTEx improves portability of this research across populations and further characterizes the impact of population structure on GWAS colocalization.ResultsHere, we identify a subset of 117 individuals in GTEx (v8) with a high degree of population admixture and estimate genome-wide local ancestry. We perform genome-wide cis-eQTL mapping using admixed samples in seven tissues, adjusted by either global or local ancestry. Consistent with previous work, we observe improved power with local ancestry adjustment. At loci where the two adjustments produce different lead variants, we observe 31 loci (0.02%) where a significant colocalization is called only with one eQTL ancestry adjustment method. Notably, both adjustments produce similar numbers of significant colocalizations within each of two different colocalization methods, COLOC and FINEMAP. Finally, we identify a small subset of eQTL-associated variants highly correlated with local ancestry, providing a resource to enhance functional follow-up.ConclusionsWe provide a local ancestry map for admixed individuals in the GTEx v8 release and describe the impact of ancestry and admixture on gene expression, eQTLs, and GWAS colocalization. While the majority of the results are concordant between local and global ancestry-based adjustments, we identify distinct advantages and disadvantages to each approach.