A resource of variant effect predictions of single nucleotide variants in model organisms.
Mol Syst Biol
; 14(12): e8430, 2018 12 20.
Article
em En
| MEDLINE
| ID: mdl-30573687
ABSTRACT
The effect of single nucleotide variants (SNVs) in coding and noncoding regions is of great interest in genetics. Although many computational methods aim to elucidate the effects of SNVs on cellular mechanisms, it is not straightforward to comprehensively cover different molecular effects. To address this, we compiled and benchmarked sequence and structure-based variant effect predictors and we computed the impact of nearly all possible amino acid and nucleotide variants in the reference genomes of Homo sapiens, Saccharomyces cerevisiae and Escherichia coli Studied mechanisms include protein stability, interaction interfaces, post-translational modifications and transcription factor binding sites. We apply this resource to the study of natural and disease coding variants. We also show how variant effects can be aggregated to generate protein complex burden scores that uncover protein complex to phenotype associations based on a set of newly generated growth profiles of 93 sequenced S. cerevisiae strains in 43 conditions. This resource is available through mutfunc (www.mutfunc.com), a tool by which users can query precomputed predictions by providing amino acid or nucleotide-level variants.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Software
/
Biologia Computacional
/
Polimorfismo de Nucleotídeo Único
Tipo de estudo:
Prognostic_studies
/
Risk_factors_studies
Limite:
Humans
Idioma:
En
Revista:
Mol Syst Biol
Assunto da revista:
BIOLOGIA MOLECULAR
/
BIOTECNOLOGIA
Ano de publicação:
2018
Tipo de documento:
Article
País de afiliação:
Reino Unido