Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD 20892, USA.
Department of Biochemistry and Molecular Biology, BioMedical Center, Faculty of Medicine, University of Iceland, Sturlugata 8, 101 Reykjavik, Iceland.
Am J Hum Genet. 2021 Sep 2;108(9):1631-1646. doi: 10.1016/j.ajhg.2021.06.018. Epub 2021 Jul 21.
Although expression quantitative trait loci (eQTLs) have been powerful in identifying susceptibility genes from genome-wide association study (GWAS) findings, most trait-associated loci are not explained by eQTLs alone. Alternative QTLs, including DNA methylation QTLs (meQTLs), are emerging, but cell-type-specific meQTLs using cells of disease origin have been lacking. Here, we established an meQTL dataset by using primary melanocytes from 106 individuals and identified 1,497,502 significant cis-meQTLs. Multi-QTL colocalization with meQTLs, eQTLs, and mRNA splice-junction QTLs from the same individuals together with imputed methylome-wide and transcriptome-wide association studies identified candidate susceptibility genes at 63% of melanoma GWAS loci. Among the three molecular QTLs, meQTLs were the single largest contributor. To compare melanocyte meQTLs with those from malignant melanomas, we performed meQTL analysis on skin cutaneous melanomas from The Cancer Genome Atlas (n = 444). A substantial proportion of meQTL probes (45.9%) in primary melanocytes is preserved in melanomas, while a smaller fraction of eQTL genes is preserved (12.7%). Integration of melanocyte multi-QTLs and melanoma meQTLs identified candidate susceptibility genes at 72% of melanoma GWAS loci. Beyond GWAS annotation, meQTL-eQTL colocalization in melanocytes suggested that 841 unique genes potentially share a causal variant with a nearby methylation probe in melanocytes. Finally, melanocyte trans-meQTLs identified a hotspot for rs12203592, a cis-eQTL of a transcription factor, IRF4, with 131 candidate target CpGs. Motif enrichment and IRF4 ChIP-seq analysis demonstrated that these target CpGs are enriched in IRF4 binding sites, suggesting an IRF4-mediated regulatory network. Our study highlights the utility of cell-type-specific meQTLs.
尽管表达数量性状基因座 (eQTLs) 在从全基因组关联研究 (GWAS) 发现中识别易感基因方面非常强大,但大多数与性状相关的基因座不能仅由 eQTLs 来解释。替代的 QTL 包括 DNA 甲基化 QTL(meQTLs),但缺乏使用疾病起源细胞的细胞特异性 meQTLs。在这里,我们使用来自 106 个人的原代黑素细胞建立了一个 meQTL 数据集,并鉴定了 1,497,502 个显著的 cis-meQTLs。来自同一个体的多-QTL 与 meQTLs、eQTLs 和 mRNA 剪接 QTL 的共定位以及对全基因组甲基化和转录组关联研究的推断,确定了 63%的黑色素瘤 GWAS 基因座的候选易感基因。在这三个分子 QTL 中,meQTLs 是最大的贡献者。为了将黑素细胞 meQTLs 与恶性黑色素瘤进行比较,我们对来自癌症基因组图谱的皮肤黑色素瘤 (n = 444) 进行了 meQTL 分析。原代黑素细胞中的相当一部分 meQTL 探针 (45.9%) 在黑色素瘤中得以保留,而较小比例的 eQTL 基因得以保留 (12.7%)。黑素细胞多-QTL 和黑色素瘤 meQTL 的整合确定了 72%的黑色素瘤 GWAS 基因座的候选易感基因。除了 GWAS 注释之外,黑素细胞中的 meQTL-eQTL 共定位表明,841 个独特的基因可能与黑素细胞中附近的甲基化探针共享一个因果变异体。最后,黑素细胞跨 meQTL 鉴定了 rs12203592 的热点,rs12203592 是转录因子 IRF4 的 cis-eQTL,有 131 个候选靶标 CpG。基序富集和 IRF4 ChIP-seq 分析表明,这些靶标 CpG 富含 IRF4 结合位点,表明存在一个由 IRF4 介导的调控网络。我们的研究强调了细胞特异性 meQTLs 的实用性。