RNA splicing. The human splicing code reveals new insights into the genetic determinants of disease.
Science
; 347(6218): 1254806, 2015 Jan 09.
Article
em En
| MEDLINE
| ID: mdl-25525159
ABSTRACT
To facilitate precision medicine and whole-genome annotation, we developed a machine-learning technique that scores how strongly genetic variants affect RNA splicing, whose alteration contributes to many diseases. Analysis of more than 650,000 intronic and exonic variants revealed widespread patterns of mutation-driven aberrant splicing. Intronic disease mutations that are more than 30 nucleotides from any splice site alter splicing nine times as often as common variants, and missense exonic disease mutations that have the least impact on protein function are five times as likely as others to alter splicing. We detected tens of thousands of disease-causing mutations, including those involved in cancers and spinal muscular atrophy. Examination of intronic and exonic variants found using whole-genome sequencing of individuals with autism revealed misspliced genes with neurodevelopmental phenotypes. Our approach provides evidence for causal variants and should enable new discoveries in precision medicine.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Inteligência Artificial
/
Atrofia Muscular Espinal
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Neoplasias Colorretais Hereditárias sem Polipose
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Transtornos Globais do Desenvolvimento Infantil
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Splicing de RNA
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Estudo de Associação Genômica Ampla
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Anotação de Sequência Molecular
Tipo de estudo:
Prognostic_studies
Limite:
Humans
Idioma:
En
Revista:
Science
Ano de publicação:
2015
Tipo de documento:
Article