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A framework for the interpretation of de novo mutation in human disease
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Journal Article
A framework for the interpretation of de novo mutation in human disease
2014
Overview
Mark Daly and colleagues present a statistical framework to evaluate the role of
de novo
mutations in human disease by calibrating a model of
de novo
mutation rates at the individual gene level. The mutation probabilities defined by their model and list of constrained genes can be used to help identify genetic variants that have a significant role in disease.
Spontaneously arising (
de novo
) mutations have an important role in medical genetics. For diseases with extensive locus heterogeneity, such as autism spectrum disorders (ASDs), the signal from
de novo
mutations is distributed across many genes, making it difficult to distinguish disease-relevant mutations from background variation. Here we provide a statistical framework for the analysis of excesses in
de novo
mutation per gene and gene set by calibrating a model of
de novo
mutation. We applied this framework to
de novo
mutations collected from 1,078 ASD family trios, and, whereas we affirmed a significant role for loss-of-function mutations, we found no excess of
de novo
loss-of-function mutations in cases with IQ above 100, suggesting that the role of
de novo
mutations in ASDs might reside in fundamental neurodevelopmental processes. We also used our model to identify ∼1,000 genes that are significantly lacking in functional coding variation in non-ASD samples and are enriched for
de novo
loss-of-function mutations identified in ASD cases.
Publisher
Nature Publishing Group UK,Nature Publishing Group
Subject
/ 45/23
/ Animal Genetics and Genomics
/ Child Development Disorders, Pervasive - genetics
/ Disease
/ Exome
/ Female
/ Genes
/ Genetic Predisposition to Disease
/ Genetics
/ Genomes
/ Genomics
/ Grants
/ Humans
/ Identification and classification
/ Male
/ Mutation
