Genetic susceptibility to intellectual disability (ID), autism spectrum disorder (ASD), and schizophrenia (SCZ) often arises from mutations in the same genes, suggesting that they share common mechanisms. We studied genes with de novo mutations in the three disorders and genes implicated in SCZ by genome-wide association study (GWAS). Using biological annotations and brain gene expression, we show that mutation class explains enrichment patterns more than specific disorder. Genes with loss-of-function mutations and genes with missense mutations were associated with different pathways across disorders. Conversely, gene expression patterns were specific for each disorder. ID genes were preferentially expressed in the cortex; ASD genes were expressed in the fetal cortex, cerebellum, and striatum; and genes associated with SCZ were expressed in the adolescent cortex. Our study suggests that convergence across neuropsychiatric disorders stems from common pathways that are consistently vulnerable to genetic variations but that spatiotemporal activity of genes contributes to specific phenotypes.

Monoallelic expression, including genomic imprinting, X-chromosome inactivation and random monoallelic expression of autosomal genes are epigenetic phenomena. Genes that are expressed in a monoallelic way may be more vulnerable to genetic or epigenetic mutations. Thus, comprehensive exploration of monoallelic expression in human brains may shed light on complex brain disorders. Autism-related disorders are known to be associated with imprinted genes on chromosome 15. However, it is not clear whether other imprinted regions or other types of monoallelic expression are associated with autism spectrum disorder (ASD). Here, we performed a genome-wide survey of allele expression imbalance (AEI) in the human brain using single-nucleotide polymorphisms (SNPs), in 18 individuals with ASD and 15 controls. Individuals with ASD had the most extreme number of monoallelic expressed SNPs in both the autosomes and the X chromosome. In two cases that were studied in detail, the monoallelic expression was confined to specific brain region or cell type. Using these data, we were also able to define the allelic expression status of known imprinted genes in the human brain and to identify abnormal imprinting in an individual with ASD. Lastly, we developed an analysis of individual-level expression, focusing on the difference of each individual from the mean. We found that individuals with ASD had more genes that were up- or down-regulated in an individual-specific manner. We also identified pathways perturbed in specific individuals. These results underline the heterogeneity in gene regulation in ASD, at the level of both allelic and total expression.

Mouse embryonic stem cells (mESCs) are key components in generating mouse models for human diseases and performing basic research on pluripotency, yet the number of genes essential for mESCs is still unknown. We performed a genome-wide screen for essential genes in mESCs and compared it to screens in human cells. We found that essential genes are enriched for basic cellular functions, are highly expressed in mESCs, and tend to lack paralog genes. We discovered that genes that are essential specifically in mESCs play a role in pathways associated with their pluripotent state. We show that 29.5% of human genes intolerant to loss-of-function mutations are essential in mouse or human ESCs, and that the human phenotypes most significantly associated with genes essential for ESCs are neurodevelopmental. Our results provide insights into essential genes in the mouse, the pathways which govern pluripotency, and suggest that many genes associated with neurodevelopmental disorders are essential at very early embryonic stages.

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Autism spectrum disorder (ASD) presents a wide, and often varied, behavioral phenotype. Improper assessment of risks has been reported among individuals diagnosed with ASD. Improper assessment of risks may lead to increased accidents and self-injury, also reported among individuals diagnosed with ASD. However, there is little knowledge of the molecular underpinnings of the impaired risk-assessment phenotype. In this study, we have identified impaired risk-assessment activity in multiple male ASD mouse models. By performing network-based analysis of striatal whole transcriptome data from each of these ASD models, we have identified a cluster of glutamate receptor-associated genes that correlate with the risk-assessment phenotype. Furthermore, pharmacological inhibition of striatal glutamatergic receptors was able to mimic the dysregulation in risk-assessment. Therefore, this study has identified a molecular mechanism that may underlie risk-assessment dysregulation in ASD.

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