De novo mutations revealed by whole-exome sequencing are strongly associated with autism.

Enrichment of non-synonymous de novo variants in probands compared with sibling controlsa) The rate of de novo variants is shown for 200 probands (red) and matched unaffected siblings (blue). ‘All’ refers to all RefSeq genes in hg18, ‘Brain’ refers to the subset of genes that are brain-expressed23 and ‘Non-syn’ to non-synonymous SNVs (including missense, nonsense and splice site SNVs). Error bars represent the 95% CI and p-values are calculated with a two-tailed binomial exact test. b) The proportion of transmitted variants in brain-expressed genes is equal between 200 probands (red) and matched unaffected siblings (blue) for all mutation types and allele frequencies, including common (≥1%); rare (<1%), and novel (single allele in one of the 400 parents); in contrast both non-synonymous and nonsense de novo variants show significant enrichment in probands compared to unaffected siblings (73.7% vs. 66.7%, p=0.01, asymptotic test and 9.5% vs. 3.1%, p=0.01 respectively). c) The frequency distribution of brain-expressed non-synonymous de novo SNVs is shown per sample for probands (red) and siblings (blue). Neither distribution differs from the Poisson distribution (black line) suggesting that multiple de novo SNVs within a single individual do not confirm ASD risk.† ‘Nonsense’ represents the combination of nonsense and splice site SNVs.

Identification of multiple de novo mutations in the same gene reliably distinguishes risk-associated mutationsa) This plot shows the results of a simulation experiment modeling the likelihood, measured in −log(P) values, of observing two independent nonsense/splice site de novo mutations in the same brain-expressed gene among unrelated probands. We modeled the observed rate of de novo brain-expressed mutations in probands and siblings and evaluated models of locus heterogeneity, including 100, 333, 667, or 1,000 contributing genes, as well as using the top 1% of genes derived from a model of exponential distribution of risk. A total of 150,000 iterations were run. The identification of two or more independent nonsense/splice site de novo variants in a brain-expressed gene provides significant evidence for ASD association (p<0.05) for all models irrespective of increasing sample size. This observation remained statistically significant when the simulation was repeated using the lower bound of the 95% confidence interval for the estimate of de novo mutation rate (Fig. S7). b) The simulation described in ‘a’ was used to predict the number of genes that will be found to carry two or more nonsense/splice site de novo mutations for a sample of a given size (specified on the x-axis). c) The simulation was repeated for non-synonymous de novo mutations. The identification of three or more independent non-synonymous de novo mutations in a brain-expressed gene provides significant evidence for ASD association (p<0.05) in the sample reported here, however this threshold is sensitive both to sample size and heterogeneity models.