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Cell-type-specific meQTLs extend melanoma GWAS annotation beyond eQTLs and inform melanocyte gene-regulatory mechanisms.
Zhang, Tongwu; Choi, Jiyeon; Dilshat, Ramile; Einarsdóttir, Berglind Ósk; Kovacs, Michael A; Xu, Mai; Malasky, Michael; Chowdhury, Salma; Jones, Kristine; Bishop, D Timothy; Goldstein, Alisa M; Iles, Mark M; Landi, Maria Teresa; Law, Matthew H; Shi, Jianxin; Steingrímsson, Eiríkur; Brown, Kevin M.
  • Zhang T; Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD 20892, USA.
  • Choi J; Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD 20892, USA.
  • Dilshat R; Department of Biochemistry and Molecular Biology, BioMedical Center, Faculty of Medicine, University of Iceland, Sturlugata 8, 101 Reykjavik, Iceland.
  • Einarsdóttir BÓ; Department of Biochemistry and Molecular Biology, BioMedical Center, Faculty of Medicine, University of Iceland, Sturlugata 8, 101 Reykjavik, Iceland.
  • Kovacs MA; Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD 20892, USA.
  • Xu M; Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD 20892, USA.
  • Malasky M; Cancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD 20892, USA.
  • Chowdhury S; Cancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD 20892, USA.
  • Jones K; Cancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD 20892, USA.
  • Bishop DT; Leeds Institute for Data Analytics, School of Medicine, University of Leeds, Leeds LS9 7TF, UK.
  • Goldstein AM; Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD 20892, USA.
  • Iles MM; Leeds Institute for Data Analytics, School of Medicine, University of Leeds, Leeds LS9 7TF, UK.
  • Landi MT; Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD 20892, USA.
  • Law MH; Statistical Genetics, QIMR Berghofer Medical Research Institute, Brisbane, QLD 4006, Australia; School of Biomedical Sciences, Faculty of Health, and Institute of Health and Biomedical Innovation, Queensland University of Technology, Kelvin Grove, QLD 4059, Australia.
  • Shi J; Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD 20892, USA.
  • Steingrímsson E; Department of Biochemistry and Molecular Biology, BioMedical Center, Faculty of Medicine, University of Iceland, Sturlugata 8, 101 Reykjavik, Iceland.
  • Brown KM; Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD 20892, USA. Electronic address: kevin.brown3@nih.gov.
Am J Hum Genet ; 108(9): 1631-1646, 2021 09 02.
Article en En | MEDLINE | ID: mdl-34293285
ABSTRACT
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.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Neoplasias Cutáneas / Sitios de Carácter Cuantitativo / Factores Reguladores del Interferón / Redes Reguladoras de Genes / Melanocitos / Melanoma Tipo de estudio: Prognostic_studies Límite: Humans / Male / Newborn Idioma: En Año: 2021 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Neoplasias Cutáneas / Sitios de Carácter Cuantitativo / Factores Reguladores del Interferón / Redes Reguladoras de Genes / Melanocitos / Melanoma Tipo de estudio: Prognostic_studies Límite: Humans / Male / Newborn Idioma: En Año: 2021 Tipo del documento: Article