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Systems Biology Approaches Reveal Potential Phenotype-Modifier Genes in Neurofibromatosis Type 1.
Woycinck Kowalski, Thayne; Brussa Reis, Larissa; Finger Andreis, Tiago; Ashton-Prolla, Patricia; Rosset, Clévia.
Afiliação
  • Woycinck Kowalski T; Laboratório de Medicina Genômica, Centro de Pesquisa Experimental, Hospital de Clínicas de Porto Alegre, Porto Alegre 90035-007, Rio Grande do Sul, Brazil.
  • Brussa Reis L; Programa de Pós-Graduação em Genética e Biologia Molecular, PPGBM, Departamento de Genética, Universidade Federal do Rio Grande do Sul, Porto Alegre 91501-970, Rio Grande do Sul, Brazil.
  • Finger Andreis T; CESUCA - Faculdade Inedi, Cachoeirinha 94935-630, Rio Grande do Sul, Brazil.
  • Ashton-Prolla P; Laboratório de Medicina Genômica, Centro de Pesquisa Experimental, Hospital de Clínicas de Porto Alegre, Porto Alegre 90035-007, Rio Grande do Sul, Brazil.
  • Rosset C; Programa de Pós-Graduação em Genética e Biologia Molecular, PPGBM, Departamento de Genética, Universidade Federal do Rio Grande do Sul, Porto Alegre 91501-970, Rio Grande do Sul, Brazil.
Cancers (Basel) ; 12(9)2020 Aug 26.
Article em En | MEDLINE | ID: mdl-32858845
Neurofibromatosis type (NF1) is a syndrome characterized by varied symptoms, ranging from mild to more aggressive phenotypes. The variation is not explained only by genetic and epigenetic changes in the NF1 gene and the concept of phenotype-modifier genes in extensively discussed in an attempt to explain this variability. Many datasets and tools are already available to explore the relationship between genetic variation and disease, including systems biology and expression data. To suggest potential NF1 modifier genes, we selected proteins related to NF1 phenotype and NF1 gene ontologies. Protein-protein interaction (PPI) networks were assembled, and network statistics were obtained by using forward and reverse genetics strategies. We also evaluated the heterogeneous networks comprising the phenotype ontologies selected, gene expression data, and the PPI network. Finally, the hypothesized phenotype-modifier genes were verified by a random-walk mathematical model. The network statistics analyses combined with the forward and reverse genetics strategies, and the assembly of heterogeneous networks, resulted in ten potential phenotype-modifier genes: AKT1, BRAF, EGFR, LIMK1, PAK1, PTEN, RAF1, SDC2, SMARCA4, and VCP. Mathematical models using the random-walk approach suggested SDC2 and VCP as the main candidate genes for phenotype-modifiers.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Cancers (Basel) Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Brasil País de publicação: Suíça
Texto completo
Adicionar na Minha BVS
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Cancers (Basel) Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Brasil País de publicação: Suíça