Genomic Patterns of De Novo Mutation in Simplex Autism

Abstract

To further our understanding of the genetic etiology of autism, we generated and analyzed genome sequence data from 516 idiopathic autism families (2,064 individuals). This resource includes >59 million single-nucleotide variants (SNVs) and 9,212 private copy number variants (CNVs), of which 133,992 and 88 are de novo mutations (DNMs), respectively. We estimate a mutation rate of ∼1.5 × 10^-8 SNVs per site per generation with a significantly higher mutation rate in repetitive DNA. Comparing probands and unaffected siblings, we observe several DNM trends. Probands carry more gene-disruptive CNVs and SNVs, resulting in severe missense mutations and mapping to predicted fetal brain promoters and embryonic stem cell enhancers. These differences become more pronounced for autism genes (p = 1.8 × 10^-3, OR = 2.2). Patients are more likely to carry multiple coding and noncoding DNMs in different genes, which are enriched for expression in striatal neurons (p = 3 × 10^-3), suggesting a path forward for genetically characterizing more complex cases of autism.

Keywords: attributable fraction; autism; de novo mutation; genome sequencing; mechanisms of disease; multifactorial genetics; noncoding; oligogenic; regulatory.

Figure 1. Patterns of DNM

(A) There was a strong correlation between the number of de novo SNVs and paternal age (SNV Pearson’s r=0.50, p=1.17×10⁻⁶⁴) with an estimated increase of 1.49 [1.32, 1.65] SNVs for each additional year of father’s age. (B) There was a strong correlation between the number of de novo indels and paternal age (indel Pearson’s r=0.27, p=1.75×10⁻¹⁷) with an increase of 0.16 [0.12, 0.19] indels for each additional year of father’s age. (C) Histogram of de novo SNVs per individual (red=proband, blue=sibling). (D) Histogram of de novo indels per individual (red=proband, blue=sibling). (E) Mutation rate estimates comparing unique and ancient repeat portions of the genome. The overall mutation rate based on experimental validation was 1.7×10⁻⁸ substitutions per site per generation with a mutation rate of 1.3×10⁻⁸ in unique regions (blue arrow) and 1.5×10⁻⁸ in ancient repetitive DNA (red arrow). VRs were comparable between unique regions (97.6%, n=1,640) and ancient repetitive DNA (95.8%, n=216). The average paternal age was 33.4 ± 5.9 years for the 1,032 genomes analyzed here.

Figure 2. Proband–sibling DNM differences by functional annotation

Number of autosomal de novo variants by functional category by (A) coding variants (LGD=likely gene-disrupting, MIS30=missense with CADD score >30, DEL=exonic deletion); (B) putative noncoding regulatory variants (UTR=untranslated region, 3' UTR=3' untranslated region, TFBS=putative noncoding regulatory with a transcription factor binding site); and (C) ENCODE/ChromHMM putative regulatory variants (fetal promoters=within a TFBS in a fetal brain transcription start site and embryonic enhancers=within a TFBS in a human embryonic stem cell strong enhancer). * Indicates nominal significance (p<0.05) by FET. (D) One of the three de novo sequence variants identified in autism probands that was tested for in vivo enhancer activity in the CNS (reference allele from enhancer.lbl.gov) (Visel et al., 2007). We extended the previous assessment for the reference allele in our current study by also testing the variant allele. For the locus, we show, from top to bottom, the human genome reference allele, the patient variant (red text), the location of a conserved TFBS near the variant, the VISTA enhancer with hs number (blue bar), and representative transgenic embryonic day 11.5 mouse embryos for the reference and variant alleles, respectively, displaying the enhancer activity pattern (blue staining). Whole embryos are shown on left, with enlarged images of the forebrain on the right. FB: forebrain, MB: midbrain, HB: hindbrain. (E) Results of the enhancer assay identified a novel forebrain enhancer activity pattern being driven by the allele containing the de novo patient variant. The expression in both the midbrain and hindbrain were unaffected. P-values by FET.

Figure 3. Oligogenic mutation burden

(A) The number of individuals carrying 0 or more de novo variants of interest (see Methods). (B) TSEA of genes in probands with 3 or more DNMs shows enrichment in the brain. (C) TSEA of genes in siblings with 3 or more DNMs shows no enrichment for any tissue. (D) CSEA) analysis of genes in probands with 3 or more DNMs shows an enrichment for striatal D2 + spiny neurons as well as striatal D1 + spiny neurons. (E) CSEA of genes in siblings with three or more DNMs shows no enrichments. For each plot in B-E, hierarchical clustering is shown for tissues (TSEA) or for cell types (CSEA). For each bullseye image, different stringency thresholds are shown by each hexagon and the darker the color the more significant the p-value.

Figure 4. Autism gene enrichment analysis

(A) Number of DNMs in functional elements compared for two autism gene sets (Turner57 and SFARI845). (Turner57 nominal p=1.76×10⁻³, OR=2.2; SFARI845 nominal p=1.36×10⁻³, OR=1.3). (B) Waterfall plots compare DNMs in various classes of “functional elements” for genes implicated for DNM Turner57 (OR=2.2, p=1.8×10⁻³). Significance estimates are calculated using the FET and although nominal p-values are shown these are multiple test correction significant (n=2 tests). (C) Counts of individuals with two or more variants within SFARI845 genes.