Cellular deconvolution of GTEx tissues powers discovery of disease and cell-type associated regulatory variants
Cellular deconvolution of GTEx tissues powers discovery of disease and cell-type associated regulatory variants
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DOI：
10.1038/s41467-020-14561-0
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发表时间：
2020-02-19
影响因子：
16.6
通讯作者：
Frazer, Kelly A.
中科院分区：
文献类型：
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作者：
Donovan, Margaret K. R.;D'Antonio-Chronowska, Agnieszka;Frazer, Kelly A.
基因型组织表达 (GTEx) 资源提供了有关遗传变异对人体组织基因表达的调控影响的见解；然而，迄今为止尚未考虑变异如何在不同细胞类型的分辨率上发挥作用。在这里，我们使用从小鼠细胞类型获得的基因表达特征，对来自 28 个 GTEx 组织的大量 RNA-seq 样本进行解卷积，以量化细胞组成，这揭示了这些样本之间惊人的异质性。使用细胞组成估计值作为交互项对 GTEx 肝脏和皮肤样本进行 eQTL 分析，我们确定了数千个与细胞类型相关的遗传关联。皮肤细胞类型相关的 eQTL 与皮肤疾病共存，表明影响不同皮肤细胞类型基因表达的变异在性状和疾病中发挥着重要作用。我们的研究提供了一个框架来估计 GTEx 组织的细胞组成，从而能够对以细胞类型特异性方式影响基因表达的人类遗传变异进行功能表征。细胞异质性可能会混淆大量组织的功能基因组学分析。在这里，多诺万等人。利用 Tabula Muris 项目的 scRNA-seq 数据对批量 GTEx RNA-seq 数据进行解卷积，并展示在 eQTL 分析中使用细胞群来识别疾病和细胞类型相关调控变异的能力。
The Genotype-Tissue Expression (GTEx) resource has provided insights into the regulatory impact of genetic variation on gene expression across human tissues; however, thus far has not considered how variation acts at the resolution of the different cell types. Here, using gene expression signatures obtained from mouse cell types, we deconvolute bulk RNA-seq samples from 28 GTEx tissues to quantify cellular composition, which reveals striking heterogeneity across these samples. Conducting eQTL analyses for GTEx liver and skin samples using cell composition estimates as interaction terms, we identify thousands of genetic associations that are cell-type-associated. The skin cell-type associated eQTLs colocalize with skin diseases, indicating that variants which influence gene expression in distinct skin cell types play important roles in traits and disease. Our study provides a framework to estimate the cellular composition of GTEx tissues enabling the functional characterization of human genetic variation that impacts gene expression in cell-type-specific manners. Cellular heterogeneity can confound functional genomics analyses of bulk tissues. Here, Donovan et al. deconvolute bulk GTEx RNA-seq data utilizing scRNA-seq data from the Tabula Muris project and show the power of using cell populations in eQTL analyses to identify disease and cell-type-associated regulatory variants.