The Sturge–Weber syndrome is a sporadic congenital neurocutaneous disorder characterized by a port-wine stain affecting the skin in the distribution of the ophthalmic branch of the trigeminal nerve, abnormal capillary venous vessels in the leptomeninges of the brain and choroid, glaucoma, seizures, stroke, and intellectual disability. It has been hypothesized that somatic mosaic mutations disrupting vascular development cause both the Sturge–Weber syndrome and port-wine stains, and the severity and extent of presentation are determined by the developmental time point at which the mutations occurred. To date, no such mutation has been identified. We performed whole-genome sequencing of DNA from paired samples of visibly affected and normal tissue from 3 persons with the Sturge–Weber syndrome. We tested for the presence of a somatic mosaic mutation in 97 samples from 50 persons with the Sturge–Weber syndrome, a port-wine stain, or neither (controls), using amplicon sequencing and SNaPshot assays, and investigated the effects of the mutation on downstream signaling, using phosphorylation-specific antibodies for relevant effectors and a luciferase reporter assay. We identified a nonsynonymous single-nucleotide variant (c.548G→A, p.Arg183Gln) in GNAQ in samples of affected tissue from 88% of the participants (23 of 26) with the Sturge–Weber syndrome and from 92% of the participants (12 of 13) with apparently nonsyndromic port-wine stains, but not in any of the samples of affected tissue from 4 participants with an unrelated cerebrovascular malformation or in any of the samples from the 6 controls. The prevalence of the mutant allele in affected tissues ranged from 1.0 to 18.1%. Extracellular signal-regulated kinase activity was modestly increased during transgenic expression of mutant Gα_q. The Sturge–Weber syndrome and port-wine stains are caused by a somatic activating mutation in GNAQ. This finding confirms a long-standing hypothesis. (Funded by the National Institutes of Health and Hunter's Dream for a Cure Foundation.)

Neuropsychiatric disorders have a complex genetic architecture. Human genetic population-based studies have identified numerous heritable sequence and structural genomic variants associated with susceptibility to neuropsychiatric disease. However, these germline variants do not fully account for disease risk. During brain development, progenitor cells undergo billions of cell divisions to generate the ~80 billion neurons in the brain. The failure to accurately repair DNA damage arising during replication, transcription, and cellular metabolism amid this dramatic cellular expansion can lead to somatic mutations. Somatic mutations that alter subsets of neuronal transcriptomes and proteomes can, in turn, affect cell proliferation and survival and lead to neurodevelopmental disorders. The long life span of individual neurons and the direct relationship between neural circuits and behavior suggest that somatic mutations in small populations of neurons can significantly affect individual neurodevelopment. The Brain Somatic Mosaicism Network has been founded to study somatic mosaicism both in neurotypical human brains and in the context of complex neuropsychiatric disorders.

Somatic mosaicism refers to the occurrence of two genetically distinct populations of cells within an individual, derived from a postzygotic mutation. In contrast to inherited mutations, somatic mosaic mutations may affect only a portion of the body and are not transmitted to progeny. These mutations affect varying genomic sizes ranging from single nucleotides to entire chromosomes and have been implicated in disease, most prominently cancer. The phenotypic consequences of somatic mosaicism are dependent upon many factors including the developmental time at which the mutation occurs, the areas of the body that are affected, and the pathophysiological effect(s) of the mutation. The advent of second-generation sequencing technologies has augmented existing array-based and cytogenetic approaches for the identification of somatic mutations. We outline the strengths and weaknesses of these techniques and highlight recent insights into the role of somatic mosaicism in causing cancer, neurodegenerative, monogenic, and complex disease.

Background: Down syndrome, caused by trisomic chromosome 21, is the leading genetic cause of mental retardation. Recent studies demonstrated that dosage-dependent increases in chromosome 21 gene expression occur in trisomy 21. However, it is unclear whether the entire transcriptome is disrupted, or whether there is a more restricted increase in the expression of those genes assigned to chromosome 21. Also, the statistical significance of differentially expressed genes in human Down syndrome tissues has not been reported. Results: We measured levels of transcripts in human fetal cerebellum and heart tissues using DNA microarrays and demonstrated a dosage-dependent increase in transcription across different tissue/cell types as a result of trisomy 21. Moreover, by having a larger sample size, combining the data from four different tissue and cell types, and using an ANOVA approach, we identified individual genes with significantly altered expression in trisomy 21, some of which showed this dysregulation in a tissue-specific manner. We validated our microarray data by over 5,600 quantitative real-time PCRs on 28 genes assigned to chromosome 21 and other chromosomes. Gene expression values from chromosome 21, but not from other chromosomes, accurately classified trisomy 21 from euploid samples. Our data also indicated functional groups that might be perturbed in trisomy 21. Conclusions: In Down syndrome, there is a primary transcriptional effect of disruption of chromosome 21 gene expression, without a pervasive secondary effect on the remaining transcriptome. The identification of dysregulated genes and pathways suggests molecular changes that may underlie the Down syndrome phenotypes.

It is an assumption of large, population-based datasets that samples are annotated accurately whether they correspond to known relationships or unrelated individuals. These annotations are key for a broad range of genetics applications. While many methods are available to assess relatedness that involve estimates of identity-by-descent (IBD) and/or identity-by-state (IBS) allele-sharing proportions, we developed a novel approach that estimates IBD0, 1, and 2 based on observed IBS within windows. When combined with genome-wide IBS information, it provides an intuitive and practical graphical approach with the capacity to analyze datasets with thousands of samples without prior information about relatedness between individuals or haplotypes. We applied the method to a commonly used Human Variation Panel consisting of 400 nominally unrelated individuals. Surprisingly, we identified identical, parent-child, and full-sibling relationships and reconstructed pedigrees. In two instances non-sibling pairs of individuals in these pedigrees had unexpected IBD2 levels, as well as multiple regions of homozygosity, implying inbreeding. This combined method allowed us to distinguish related individuals from those having atypical heterozygosity rates and determine which individuals were outliers with respect to their designated population. Additionally, it becomes increasingly difficult to identify distant relatedness using genome-wide IBS methods alone. However, our IBD method further identified distant relatedness between individuals within populations, supported by the presence of megabase-scale regions lacking IBS0 across individual chromosomes. We benchmarked our approach against the hidden Markov model of a leading software package (PLINK), showing improved calling of distantly related individuals, and we validated it using a known pedigree from a clinical study. The application of this approach could improve genome-wide association, linkage, heterozygosity, and other population genomics studies that rely on SNP genotype data. High-density microarrays measuring single nucleotide polymorphisms (SNPs) provide information about the genotypes across many loci. SNP genotypes observed for any two individuals can be compared in terms of identity-by-state (IBS), in which two individuals are observed to have 0, 1, or 2 alleles in common at a given locus, across a chromosomal region, or throughout the genome. These alleles may be shared identical-by-descent (IBD) in which 0, 1, or 2 alleles are inherited from a recent common ancestor, or they may be identical by chance because the allele is frequent in the population. The expected proportion of genome sharing between two individuals varies as a function of their genetic relatedness. We introduce a method to estimate IBD that can be used to analyze relatedness in pedigrees or in large-scale population studies with thousands of individuals. This can be combined with observed IBS to distinguish a variety of types of relatedness, providing theoretically justified results that are graphed in a manner that is straightforward to interpret. The methods we introduce are relevant to a variety of SNP applications including linkage and association studies and population genomics studies.

De novo mutation is highly implicated in autism spectrum disorder (ASD). However, the contribution of post-zygotic mutation to ASD is poorly characterized. We performed both exome sequencing of paired samples and analysis of de novo variants from whole-exome sequencing of 2,388 families. While we find little evidence for tissue-specific mosaic mutation, multi-tissue post-zygotic mutation (i.e. mosaicism) is frequent, with detectable mosaic variation comprising 5.4% of all de novo mutations. We identify three mosaic missense and likely-gene disrupting mutations in genes previously implicated in ASD (KMT2C, NCKAP1, and MYH10) in probands but none in siblings. We find a strong ascertainment bias for mosaic mutations in probands relative to their unaffected siblings (p = 0.003). We build a model of de novo variation incorporating mosaic variants and errors in classification of mosaic status and from this model we estimate that 33% of mosaic mutations in probands contribute to 5.1% of simplex ASD diagnoses (95% credible interval 1.3% to 8.9%). Our results indicate a contributory role for multi-tissue mosaic mutation in some individuals with an ASD diagnosis. Recent sequencing experiments have shown that genetic mutations present in children but not their parents contribute to autism diagnoses in a large fraction of affected families. Here we address the question of whether mutations occurring uniquely in the children arise in the parents’ sperm or egg, or as mosaics in the child after conception. Using a dataset of 2,388 families, we find that while these mutations are primarily inherited from parental germ cells, 5.4% of these mutations appear to arise after conception. Mosaic mutations occur more frequently in probands relative to their unaffected siblings and from this enrichment we estimate that mosaic mutations contribute to 5.1% of autism diagnoses. In addition, we show that brain-specific mutations are not frequently detectable in individuals with an autism diagnosis. Our results indicate that some fraction of identical twins is expected to be discordant for an autism diagnosis due to genetic factors (post-zygotic mutation).