Using whole-exome sequencing and protein interaction networks to prioritize candidate genes for germline cutaneous melanoma susceptibility
| Autor: | Sally Yepes, Bin Zhu, Alisa M. Goldstein, Aurelie Vogt, Yanzi Xiao, Amy Hutchinson, Wen Luo, Neal D. Freedman, Meredith Yeager, Laurie Burdette, Hela Koka, Belynda Hicks, Margaret A. Tucker, Xiaohong R. Yang, Kristine Jones, Stephen J. Chanock |
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| Rok vydání: | 2020 |
| Předmět: |
Male
Candidate gene Skin Neoplasms lcsh:Medicine Context (language use) Computational biology Biology Germline Article Genetic Heterogeneity Exome Sequencing Genetics Humans Exome Gene Regulatory Networks Genetic Predisposition to Disease Protein Interaction Maps NGLY1 lcsh:Science Gene Melanoma Exome sequencing Cancer Multidisciplinary Genetic heterogeneity lcsh:R High-Throughput Nucleotide Sequencing Germ Cells Cutaneous melanoma lcsh:Q Female Systems biology |
| Zdroj: | Scientific Reports Scientific Reports, Vol 10, Iss 1, Pp 1-13 (2020) |
| ISSN: | 2045-2322 |
| Popis: | Although next-generation sequencing has demonstrated great potential for novel gene discovery, confirming disease-causing genes after initial discovery remains challenging. Here, we applied a network analysis approach to prioritize candidate genes identified from whole-exome sequencing analysis of 98 cutaneous melanoma patients from 27 families. Using a network propagation method, we ranked candidate genes by their similarity to known disease genes in protein–protein interaction networks and identified gene clusters with functional connectivity. Using this approach, we identified several new candidate susceptibility genes that warrant future investigations such as NGLY1, IL1RN, FABP2, PRKDC, and PROSER2. The propagated network analysis also allowed us to link families that did not have common underlying genes but that carried variants in genes that interact on protein–protein interaction networks. In conclusion, our study provided an analysis perspective for gene prioritization in the context of genetic heterogeneity across families and prioritized top potential candidate susceptibility genes in our dataset. |
| Databáze: | OpenAIRE |
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