Deconvolution of bulk blood eQTL effects into immune cell subpopulations
Deconvolution of bulk blood eQTL effects into immune cell subpopulations
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DOI：
10.1186/s12859-020-03576-5
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发表时间：
2020-06-12
影响因子：
3
通讯作者：
Li, Yang
中科院分区：
文献类型：
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作者：
Aguirre-Gamboa, Raul;de Klein, Niek;Li, Yang
背景 表达数量性状位点 (eQTL) 研究用于解释疾病相关遗传风险因素的功能。迄今为止，大多数 eQTL 分析都是在大量组织中进行的，例如全血和组织活检，这可能掩盖了 eQTL 调节效应的细胞类型背景。尽管可以通过从纯化的细胞亚群生成转录谱来研究这种情况，但目前的方法是劳动密集型且昂贵的。我们引入了一种新方法 Decon2，作为使用大量血液样本 (Decon-cell) 的表达谱，然后对细胞类型 eQTL (Decon-eQTL) 进行解卷积来估计细胞比例的框架。结果 Decon-cell 估计的细胞比例与各队列的实验测量结果一致 (R >= 0.77)。使用 Decon-cell，我们可以预测基于人群的队列中 3194 个样本的 34 种循环细胞类型的比例。接下来，我们使用 Decon-cell 预测的细胞比例鉴定了 16,362 个全血 eQTL 和解卷积细胞类型相互作用 (CTi) eQTL。 CTi eQTL 与使用纯化细胞亚群或单细胞 RNA-seq 的 eQTL (>= 96-100%) 和染色质标记 QTL (>= 87-92%) 研究显示出极好的等位基因方向一致性，优于传统的相互作用效应。结论 Decon2 提供了一种从大量血液 eQTL 中检测细胞类型相互作用效应的方法，可用于确定给定复杂疾病最相关的细胞类型。 Decon2 可作为 R 包和 Java 应用程序 (https://github.com/molgenis/systems Genetics/tree/master/Decon2) 以及 Web 工具 (www.molgenis.org/devolving) 提供。
Background Expression quantitative trait loci (eQTL) studies are used to interpret the function of disease-associated genetic risk factors. To date, most eQTL analyses have been conducted in bulk tissues, such as whole blood and tissue biopsies, which are likely to mask the cell type-context of the eQTL regulatory effects. Although this context can be investigated by generating transcriptional profiles from purified cell subpopulations, current methods to do this are labor-intensive and expensive. We introduce a new method,Decon2,as a framework for estimating cell proportions using expression profiles from bulk blood samples (Decon-cell) followed by deconvolution of cell type eQTLs (Decon-eQTL). Results The estimated cell proportions from Decon-cell agree with experimental measurements across cohorts (R >= 0.77). Using Decon-cell, we could predict the proportions of 34 circulating cell types for 3194 samples from a population-based cohort. Next, we identified 16,362 whole-blood eQTLs and deconvoluted cell type interaction (CTi) eQTLs using the predicted cell proportions from Decon-cell. CTi eQTLs show excellent allelic directional concordance with eQTL (>= 96-100%) and chromatin mark QTL (>= 87-92%) studies that used either purified cell subpopulations or single-cell RNA-seq, outperforming the conventional interaction effect. Conclusions Decon2 provides a method to detect cell type interaction effects from bulk blood eQTLs that is useful for pinpointing the most relevant cell type for a given complex disease. Decon2 is available as an R package and Java application (https://github.com/molgenis/systemsgenetics/tree/master/Decon2) and as a web tool (www.molgenis.org/deconvolution).