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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
DC Field | Value | Language |
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dc.contributor.author | 김은영 | - |
dc.date.accessioned | 2023-03-10T01:35:15Z | - |
dc.date.available | 2023-03-10T01:35:15Z | - |
dc.date.issued | 2022-12 | - |
dc.identifier.issn | 0002-9297 | - |
dc.identifier.uri | https://ir.ymlib.yonsei.ac.kr/handle/22282913/193247 | - |
dc.description.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. | - |
dc.description.statementOfResponsibility | restriction | - |
dc.language | English | - |
dc.publisher | University of Chicago Press | - |
dc.relation.isPartOf | AMERICAN JOURNAL OF HUMAN GENETICS | - |
dc.rights | CC BY-NC-ND 2.0 KR | - |
dc.subject.MESH | Biological Assay | - |
dc.subject.MESH | Genome-Wide Association Study | - |
dc.subject.MESH | Humans | - |
dc.subject.MESH | Melanoma* / genetics | - |
dc.subject.MESH | Receptors, G-Protein-Coupled | - |
dc.subject.MESH | Skin Neoplasms* / genetics | - |
dc.subject.MESH | Transcription Factors | - |
dc.title | Massively parallel reporter assays and variant scoring identified functional variants and target genes for melanoma loci and highlighted cell-type specificity | - |
dc.type | Article | - |
dc.contributor.college | College of Medicine (의과대학) | - |
dc.contributor.department | Dept. of Internal Medicine (내과학교실) | - |
dc.contributor.googleauthor | Erping Long | - |
dc.contributor.googleauthor | Jinhu Yin | - |
dc.contributor.googleauthor | Karen M Funderburk | - |
dc.contributor.googleauthor | Mai Xu | - |
dc.contributor.googleauthor | James Feng | - |
dc.contributor.googleauthor | Alexander Kane | - |
dc.contributor.googleauthor | Tongwu Zhang | - |
dc.contributor.googleauthor | Timothy Myers | - |
dc.contributor.googleauthor | Alyxandra Golden | - |
dc.contributor.googleauthor | Rohit Thakur | - |
dc.contributor.googleauthor | Hyunkyung Kong | - |
dc.contributor.googleauthor | Lea Jessop | - |
dc.contributor.googleauthor | Eun Young Kim | - |
dc.contributor.googleauthor | Kristine Jones | - |
dc.contributor.googleauthor | Raj Chari | - |
dc.contributor.googleauthor | Mitchell J Machiela | - |
dc.contributor.googleauthor | Kai Yu | - |
dc.contributor.googleauthor | Melanoma Meta-Analysis Consortium | - |
dc.contributor.googleauthor | Mark M Iles | - |
dc.contributor.googleauthor | Maria Teresa Landi | - |
dc.contributor.googleauthor | Matthew H Law | - |
dc.contributor.googleauthor | Stephen J Chanock | - |
dc.contributor.googleauthor | Kevin M Brown | - |
dc.contributor.googleauthor | Jiyeon Choi | - |
dc.identifier.doi | 10.1016/j.ajhg.2022.11.006 | - |
dc.contributor.localId | A00811 | - |
dc.relation.journalcode | J00086 | - |
dc.identifier.eissn | 1537-6605 | - |
dc.identifier.pmid | 36423637 | - |
dc.identifier.url | https://www.sciencedirect.com/science/article/pii/S0002929722004979 | - |
dc.subject.keyword | CRISPRi | - |
dc.subject.keyword | GWAS | - |
dc.subject.keyword | GWAS follow-up | - |
dc.subject.keyword | MPRA | - |
dc.subject.keyword | cell of tumor origin | - |
dc.subject.keyword | cell-type specificity | - |
dc.subject.keyword | eQTL | - |
dc.subject.keyword | melanoma | - |
dc.subject.keyword | transcription factors | - |
dc.subject.keyword | variant scoring | - |
dc.contributor.alternativeName | Kim, Eun Young | - |
dc.contributor.affiliatedAuthor | 김은영 | - |
dc.citation.volume | 109 | - |
dc.citation.number | 12 | - |
dc.citation.startPage | 2210 | - |
dc.citation.endPage | 2229 | - |
dc.identifier.bibliographicCitation | AMERICAN JOURNAL OF HUMAN GENETICS, Vol.109(12) : 2210-2229, 2022-12 | - |
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