Thakur Rohit, Xu Mai, Sowards Hayley, Yon Joshuah, Jessop Lea, Myers Timothy, Zhang Tongwu, Chari Raj, Long Erping, Rehling Thomas, Hennessey Rebecca, Funderburk Karen, Yin Jinhu, Machiela Mitchell J, Johnson Matthew E, Wells Andrew D, Chesi Alessandra, Grant Struan F A, Iles Mark M, Landi Maria Teresa, Law Matthew H, Choi Jiyeon, Brown Kevin M
Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA.
Laboratory of Genomic Susceptibility, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA.
medRxiv. 2024 Nov 15:2024.11.14.24317204. doi: 10.1101/2024.11.14.24317204.
Genome-wide association studies (GWAS) of melanoma risk have identified 68 independent signals at 54 loci. For most loci, specific functional variants and their respective target genes remain to be established. Capture-HiC is an assay that links fine-mapped risk variants to candidate target genes by comprehensively mapping cell-type specific chromatin interactions. We performed a melanoma GWAS region-focused capture-HiC assay in human primary melanocytes to identify physical interactions between fine-mapped risk variants and potential causal melanoma susceptibility genes. Overall, chromatin interaction data alone nominated potential causal genes for 61 of the 68 melanoma risk signals, identifying many candidates beyond those reported by previous studies. We further integrated these data with cell-type specific epigenomic (chromatin state, accessibility), gene expression (eQTL/TWAS), DNA methylation (meQTL/MWAS), and massively parallel reporter assay (MPRA) data to prioritize potentially -regulatory variants and their respective candidate gene targets. From the set of fine-mapped variants across these loci, we identified 140 prioritized candidate causal variants linked to 195 candidate genes at 42 risk signals. In addition, we developed an integrative scoring system to facilitate candidate gene prioritization, integrating melanocyte and melanoma datasets. Notably, at several GWAS risk signals we observed long-range chromatin connections (500 kb to >1 Mb) with distant candidate target genes. We validated several such -regulatory interactions using CRISPR inhibition, providing evidence for known cancer driver genes and , as well as the SRY-box transcription factor , as likely melanoma risk genes.
黑色素瘤风险的全基因组关联研究(GWAS)已在54个基因座上确定了68个独立信号。对于大多数基因座而言,特定的功能变异及其各自的靶基因仍有待确定。捕获Hi-C是一种通过全面绘制细胞类型特异性染色质相互作用,将精细定位的风险变异与候选靶基因联系起来的分析方法。我们在人类原代黑素细胞中进行了一项聚焦于黑色素瘤GWAS区域的捕获Hi-C分析,以确定精细定位的风险变异与潜在的因果性黑色素瘤易感基因之间的物理相互作用。总体而言,仅染色质相互作用数据就为68个黑色素瘤风险信号中的61个提名了潜在的因果基因,识别出了许多先前研究未报道的候选基因。我们进一步将这些数据与细胞类型特异性表观基因组(染色质状态、可及性)、基因表达(eQTL/TWAS)、DNA甲基化(meQTL/MWAS)和大规模平行报告基因分析(MPRA)数据相结合,以对潜在的调控变异及其各自的候选基因靶标进行优先级排序。从这些基因座上精细定位的变异集中,我们在42个风险信号中确定了140个优先级候选因果变异,这些变异与195个候选基因相关。此外,我们开发了一种综合评分系统,以促进候选基因的优先级排序,该系统整合了黑素细胞和黑色素瘤数据集。值得注意的是,在几个GWAS风险信号处,我们观察到与远处候选靶基因的长程染色质连接(500 kb至>1 Mb)。我们使用CRISPR抑制验证了几种此类调控相互作用,为已知的癌症驱动基因以及SRY盒转录因子作为可能的黑色素瘤风险基因提供了证据。