La Jolla Institute for Allergy and Immunology, La Jolla, CA 92037, USA.
Salk Institute for Biological Studies, La Jolla, CA 92037, USA.
Cell. 2018 Nov 29;175(6):1701-1715.e16. doi: 10.1016/j.cell.2018.10.022. Epub 2018 Nov 15.
While many genetic variants have been associated with risk for human diseases, how these variants affect gene expression in various cell types remains largely unknown. To address this gap, the DICE (database of immune cell expression, expression quantitative trait loci [eQTLs], and epigenomics) project was established. Considering all human immune cell types and conditions studied, we identified cis-eQTLs for a total of 12,254 unique genes, which represent 61% of all protein-coding genes expressed in these cell types. Strikingly, a large fraction (41%) of these genes showed a strong cis-association with genotype only in a single cell type. We also found that biological sex is associated with major differences in immune cell gene expression in a highly cell-specific manner. These datasets will help reveal the effects of disease risk-associated genetic polymorphisms on specific immune cell types, providing mechanistic insights into how they might influence pathogenesis (https://dice-database.org).
虽然许多遗传变异与人类疾病的风险有关,但这些变异如何影响各种细胞类型中的基因表达在很大程度上仍是未知的。为了解决这一空白,DICE(免疫细胞表达数据库、表达数量性状基因座[eQTL]和表观基因组学)项目成立了。考虑到所有研究过的人类免疫细胞类型和条件,我们总共鉴定了 12254 个独特基因的顺式 eQTL,这些基因代表了这些细胞类型中表达的所有蛋白编码基因的 61%。令人惊讶的是,这些基因中有很大一部分(41%)仅在单个细胞类型中表现出与基因型的强烈顺式关联。我们还发现,生物性别以高度细胞特异性的方式与免疫细胞基因表达的主要差异相关。这些数据集将有助于揭示疾病风险相关遗传多态性对特定免疫细胞类型的影响,为它们如何影响发病机制提供机制见解(https://dice-database.org)。