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Massively parallel reporter assays and variant scoring identified functional variants and target genes for melanoma loci and highlighted cell-type specificity.
Long, Erping; Yin, Jinhu; Funderburk, Karen M; Xu, Mai; Feng, James; Kane, Alexander; Zhang, Tongwu; Myers, Timothy; Golden, Alyxandra; Thakur, Rohit; Kong, Hyunkyung; Jessop, Lea; Kim, Eun Young; Jones, Kristine; Chari, Raj; Machiela, Mitchell J; Yu, Kai; Iles, Mark M; Landi, Maria Teresa; Law, Matthew H; Chanock, Stephen J; Brown, Kevin M; Choi, Jiyeon.
  • Long E; Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA.
  • Yin J; Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA.
  • Funderburk KM; Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA.
  • Xu M; Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA.
  • Feng J; Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA.
  • Kane A; Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA.
  • Zhang T; Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA.
  • Myers T; Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA.
  • Golden A; Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA.
  • Thakur R; Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA.
  • Kong H; Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA.
  • Jessop L; Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA.
  • Kim EY; Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea.
  • Jones K; Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA.
  • Chari R; Genome Modification Core, Frederick National Lab for Cancer Research, National Cancer Institute, Frederick, MD, USA.
  • Machiela MJ; Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA.
  • Yu K; Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA.
  • Iles MM; Leeds Institute for Data Analytics, School of Medicine, University of Leeds, Leeds LS2 9NL, UK.
  • Landi MT; Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA.
  • Law MH; Statistical Genetics, QIMR Berghofer Medical Research Institute, Brisbane, QLD 4006, Australia; Faculty of Health, Queensland University of Technology, Brisbane, QLD, Australia; School of Biomedical Sciences, University of Queensland, Brisbane, QLD, Australia.
  • Chanock SJ; Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA.
  • Brown KM; Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA.
  • Choi J; Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA. Electronic address: jiyeon.choi2@nih.gov.
Am J Hum Genet ; 109(12): 2210-2229, 2022 12 01.
Article en En | MEDLINE | ID: mdl-36423637
ABSTRACT
The most recent genome-wide association study (GWAS) of cutaneous melanoma identified 54 risk-associated loci, but functional variants and their target genes for most have not been established. Here, we performed massively parallel reporter assays (MPRAs) by using malignant melanoma and normal melanocyte cells and further integrated multi-layer annotation to systematically prioritize functional variants and susceptibility genes from these GWAS loci. Of 1,992 risk-associated variants tested in MPRAs, we identified 285 from 42 loci (78% of the known loci) displaying significant allelic transcriptional activities in either cell type (FDR < 1%). We further characterized MPRA-significant variants by motif prediction, epigenomic annotation, and statistical/functional fine-mapping to create integrative variant scores, which prioritized one to six plausible candidate variants per locus for the 42 loci and nominated a single variant for 43% of these loci. Overlaying the MPRA-significant variants with genome-wide significant expression or methylation quantitative trait loci (eQTLs or meQTLs, respectively) from melanocytes or melanomas identified candidate susceptibility genes for 60% of variants (172 of 285 variants). CRISPRi of top-scoring variants validated their cis-regulatory effect on the eQTL target genes, MAFF (22q13.1) and GPRC5A (12p13.1). Finally, we identified 36 melanoma-specific and 45 melanocyte-specific MPRA-significant variants, a subset of which are linked to cell-type-specific target genes. Analyses of transcription factor availability in MPRA datasets and variant-transcription-factor interaction in eQTL datasets highlighted the roles of transcription factors in cell-type-specific variant functionality. In conclusion, MPRAs along with variant scoring effectively prioritized plausible candidates for most melanoma GWAS loci and highlighted cellular contexts where the susceptibility variants are functional.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Neoplasias Cutáneas / Melanoma Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Año: 2022 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Neoplasias Cutáneas / Melanoma Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Año: 2022 Tipo del documento: Article