The gene dose makes the disease.

A long-standing challenge in genomics has been to identify causal genes within rare copy-number variant regions that are intolerant to altered dosage. In this issue, Collins et al. perform a meta-analysis of almost a million individuals to identify dosage-sensitive segments and genes conferring risk for a range of disease phenotypes.

Strategies for dissecting the complexity of neurodevelopmental disorders.

Neurodevelopmental disorders (NDDs) are associated with a wide range of clinical features, affecting multiple pathways involved in brain development and function. Recent advances in high-throughput sequencing have unveiled numerous genetic variants associated with NDDs, which further contribute to disease complexity and make it challenging to infer disease causation and underlying mechanisms. Herein, we review current strategies for dissecting the complexity of NDDs using model organisms, induced pluripotent stem cells, single-cell sequencing technologies, and massively parallel reporter assays. We further highlight single-cell CRISPR-based screening techniques that allow genomic investigation of cellular transcriptomes with high efficiency, accuracy, and throughput. Overall, we provide an integrated review of experimental approaches that can be applicable for investigating a broad range of complex disorders.

Genome-wide analysis of copy-number variation in humans with cleft lip and/or cleft palate identifies COBLL1, RIC1, and ARHGEF38 as clefting genes.

Cleft lip with or without cleft palate (CL/P) is a common birth defect with a complex, heterogeneous etiology. It is well established that common and rare sequence variants contribute to the formation of CL/P, but the contribution of copy-number variants (CNVs) to cleft formation remains relatively understudied. To fill this knowledge gap, we conducted a large-scale comparative analysis of genome-wide CNV profiles of 869 individuals from the Philippines and 233 individuals of European ancestry with CL/P with three primary goals: first, to evaluate whether differences in CNV number, amount of genomic content, or amount of coding genomic content existed within clefting subtypes; second, to assess whether CNVs in our cohort overlapped with known Mendelian clefting loci; and third, to identify unestablished Mendelian clefting genes. Significant differences in CNVs across cleft types or in individuals with non-syndromic versus syndromic clefts were not observed; however, several CNVs in our cohort overlapped with known syndromic and non-syndromic Mendelian clefting loci. Moreover, employing a filtering strategy relying on population genetics data that rare variants are on the whole more deleterious than common variants, we identify several CNV-associated gene losses likely driving non-syndromic clefting phenotypes. By prioritizing genes deleted at a rare frequency across multiple individuals with clefts yet enriched in our cohort of individuals with clefts compared to control subjects, we identify COBLL1, RIC1, and ARHGEF38 as clefting genes. CRISPR-Cas9 mutagenesis of these genes in Xenopus laevis and Danio rerio yielded craniofacial dysmorphologies, including clefts analogous to those seen in human clefting disorders.

Assortative mating and parental genetic relatedness contribute to the pathogenicity of variably expressive variants.

We examined more than 97,000 families from four neurodevelopmental disease cohorts and the UK Biobank to identify phenotypic and genetic patterns in parents contributing to neurodevelopmental disease risk in children. We identified within- and cross-disorder correlations between six phenotypes in parents and children, such as obsessive-compulsive disorder (R = 0.32-0.38, p < 10-126). We also found that measures of sub-clinical autism features in parents are associated with several autism severity measures in children, including biparental mean Social Responsiveness Scale scores and proband Repetitive Behaviors Scale scores (regression coefficient = 0.14, p = 3.38 × 10-4). We further describe patterns of phenotypic similarity between spouses, where spouses show correlations for six neurological and psychiatric phenotypes, including a within-disorder correlation for depression (R = 0.24-0.68, p < 0.001) and a cross-disorder correlation between anxiety and bipolar disorder (R = 0.09-0.22, p < 10-92). Using a simulated population, we also found that assortative mating can lead to increases in disease liability over generations and the appearance of "genetic anticipation" in families carrying rare variants. We identified several families in a neurodevelopmental disease cohort where the proband inherited multiple rare variants in disease-associated genes from each of their affected parents. We further identified parental relatedness as a risk factor for neurodevelopmental disorders through its inverse relationship with variant pathogenicity and propose that parental relatedness modulates disease risk by increasing genome-wide homozygosity in children (R = 0.05-0.26, p < 0.05). Our results highlight the utility of assessing parent phenotypes and genotypes toward predicting features in children who carry rare variably expressive variants and implicate assortative mating as a risk factor for increased disease severity in these families.

Challenges and considerations for reproducibility of STARR-seq assays.

High-throughput methods such as RNA-seq, ChIP-seq, and ATAC-seq have well-established guidelines, commercial kits, and analysis pipelines that enable consistency and wider adoption for understanding genome function and regulation. STARR-seq, a popular assay for directly quantifying the activities of thousands of enhancer sequences simultaneously, has seen limited standardization across studies. The assay is long, with more than 250 steps, and frequent customization of the protocol and variations in bioinformatics methods raise concerns for reproducibility of STARR-seq studies. Here, we assess each step of the protocol and analysis pipelines from published sources and in-house assays, and identify critical steps and quality control (QC) checkpoints necessary for reproducibility of the assay. We also provide guidelines for experimental design, protocol scaling, customization, and analysis pipelines for better adoption of the assay. These resources will allow better optimization of STARR-seq for specific research needs, enable comparisons and integration across studies, and improve the reproducibility of results.

A general framework for identifying oligogenic combinations of rare variants in complex disorders.

Genetic studies of complex disorders such as autism and intellectual disability (ID) are often based on enrichment of individual rare variants or their aggregate burden in affected individuals compared to controls. However, these studies overlook the influence of combinations of rare variants that may not be deleterious on their own due to statistical challenges resulting from rarity and combinatorial explosion when enumerating variant combinations, limiting our ability to study oligogenic basis for these disorders. Here, we present RareComb, a framework that combines the Apriori algorithm and statistical inference to identify specific combinations of mutated genes associated with complex phenotypes. RareComb overcomes computational barriers and exhaustively evaluates variant combinations to identify nonadditive relationships between simultaneously mutated genes. Using RareComb, we analyzed 6189 individuals with autism and identified 718 combinations significantly associated with ID, and carriers of these combinations showed lower IQ than expected in an independent cohort of 1878 individuals. These combinations were enriched for nervous system genes such as NIN and NGF, showed complex inheritance patterns, and were depleted in unaffected siblings. We found that an affected individual can carry many oligogenic combinations, each contributing to the same phenotype or distinct phenotypes at varying effect sizes. We also used this framework to identify combinations associated with multiple comorbid phenotypes, including mutations of COL28A1 and MFSD2B for ID and schizophrenia and ABCA4, DNAH10 and MC1R for ID and anxiety/depression. Our framework identifies a key component of missing heritability and provides a novel paradigm to untangle the genetic architecture of complex disorders.

Functional assessment of the "two-hit" model for neurodevelopmental defects in Drosophila and X. laevis.

We previously identified a deletion on chromosome 16p12.1 that is mostly inherited and associated with multiple neurodevelopmental outcomes, where severely affected probands carried an excess of rare pathogenic variants compared to mildly affected carrier parents. We hypothesized that the 16p12.1 deletion sensitizes the genome for disease, while "second-hits" in the genetic background modulate the phenotypic trajectory. To test this model, we examined how neurodevelopmental defects conferred by knockdown of individual 16p12.1 homologs are modulated by simultaneous knockdown of homologs of "second-hit" genes in Drosophila melanogaster and Xenopus laevis. We observed that knockdown of 16p12.1 homologs affect multiple phenotypic domains, leading to delayed developmental timing, seizure susceptibility, brain alterations, abnormal dendrite and axonal morphology, and cellular proliferation defects. Compared to genes within the 16p11.2 deletion, which has higher de novo occurrence, 16p12.1 homologs were less likely to interact with each other in Drosophila models or a human brain-specific interaction network, suggesting that interactions with "second-hit" genes may confer higher impact towards neurodevelopmental phenotypes. Assessment of 212 pairwise interactions in Drosophila between 16p12.1 homologs and 76 homologs of patient-specific "second-hit" genes (such as ARID1B and CACNA1A), genes within neurodevelopmental pathways (such as PTEN and UBE3A), and transcriptomic targets (such as DSCAM and TRRAP) identified genetic interactions in 63% of the tested pairs. In 11 out of 15 families, patient-specific "second-hits" enhanced or suppressed the phenotypic effects of one or many 16p12.1 homologs in 32/96 pairwise combinations tested. In fact, homologs of SETD5 synergistically interacted with homologs of MOSMO in both Drosophila and X. laevis, leading to modified cellular and brain phenotypes, as well as axon outgrowth defects that were not observed with knockdown of either individual homolog. Our results suggest that several 16p12.1 genes sensitize the genome towards neurodevelopmental defects, and complex interactions with "second-hit" genes determine the ultimate phenotypic manifestation.

Drosophila models of pathogenic copy-number variant genes show global and non-neuronal defects during development.

While rare pathogenic copy-number variants (CNVs) are associated with both neuronal and non-neuronal phenotypes, functional studies evaluating these regions have focused on the molecular basis of neuronal defects. We report a systematic functional analysis of non-neuronal defects for homologs of 59 genes within ten pathogenic CNVs and 20 neurodevelopmental genes in Drosophila melanogaster. Using wing-specific knockdown of 136 RNA interference lines, we identified qualitative and quantitative phenotypes in 72/79 homologs, including 21 lines with severe wing defects and six lines with lethality. In fact, we found that 10/31 homologs of CNV genes also showed complete or partial lethality at larval or pupal stages with ubiquitous knockdown. Comparisons between eye and wing-specific knockdown of 37/45 homologs showed both neuronal and non-neuronal defects, but with no correlation in the severity of defects. We further observed disruptions in cell proliferation and apoptosis in larval wing discs for 23/27 homologs, and altered Wnt, Hedgehog and Notch signaling for 9/14 homologs, including AATF/Aatf, PPP4C/Pp4-19C, and KIF11/Klp61F. These findings were further supported by tissue-specific differences in expression patterns of human CNV genes, as well as connectivity of CNV genes to signaling pathway genes in brain, heart and kidney-specific networks. Our findings suggest that multiple genes within each CNV differentially affect both global and tissue-specific developmental processes within conserved pathways, and that their roles are not restricted to neuronal functions.

NCBP2 modulates neurodevelopmental defects of the 3q29 deletion in Drosophila and Xenopus laevis models.

The 1.6 Mbp deletion on chromosome 3q29 is associated with a range of neurodevelopmental disorders, including schizophrenia, autism, microcephaly, and intellectual disability. Despite its importance towards neurodevelopment, the role of individual genes, genetic interactions, and disrupted biological mechanisms underlying the deletion have not been thoroughly characterized. Here, we used quantitative methods to assay Drosophila melanogaster and Xenopus laevis models with tissue-specific individual and pairwise knockdown of 14 homologs of genes within the 3q29 region. We identified developmental, cellular, and neuronal phenotypes for multiple homologs of 3q29 genes, potentially due to altered apoptosis and cell cycle mechanisms during development. Using the fly eye, we screened for 314 pairwise knockdowns of homologs of 3q29 genes and identified 44 interactions between pairs of homologs and 34 interactions with other neurodevelopmental genes. Interestingly, NCBP2 homologs in Drosophila (Cbp20) and X. laevis (ncbp2) enhanced the phenotypes of homologs of the other 3q29 genes, leading to significant increases in apoptosis that disrupted cellular organization and brain morphology. These cellular and neuronal defects were rescued with overexpression of the apoptosis inhibitors Diap1 and xiap in both models, suggesting that apoptosis is one of several potential biological mechanisms disrupted by the deletion. NCBP2 was also highly connected to other 3q29 genes in a human brain-specific interaction network, providing support for the relevance of our results towards the human deletion. Overall, our study suggests that NCBP2-mediated genetic interactions within the 3q29 region disrupt apoptosis and cell cycle mechanisms during development.

A machine-learning approach for accurate detection of copy number variants from exome sequencing.

Copy number variants (CNVs) are a major cause of several genetic disorders, making their detection an essential component of genetic analysis pipelines. Current methods for detecting CNVs from exome-sequencing data are limited by high false-positive rates and low concordance because of inherent biases of individual algorithms. To overcome these issues, calls generated by two or more algorithms are often intersected using Venn diagram approaches to identify "high-confidence" CNVs. However, this approach is inadequate, because it misses potentially true calls that do not have consensus from multiple callers. Here, we present CN-Learn, a machine-learning framework that integrates calls from multiple CNV detection algorithms and learns to accurately identify true CNVs using caller-specific and genomic features from a small subset of validated CNVs. Using CNVs predicted by four exome-based CNV callers (CANOES, CODEX, XHMM, and CLAMMS) from 503 samples, we demonstrate that CN-Learn identifies true CNVs at higher precision (∼90%) and recall (∼85%) rates while maintaining robust performance even when trained with minimal data (∼30 samples). CN-Learn recovers twice as many CNVs compared to individual callers or Venn diagram-based approaches, with features such as exome capture probe count, caller concordance, and GC content providing the most discriminatory power. In fact, ∼58% of all true CNVs recovered by CN-Learn were either singletons or calls that lacked support from at least one caller. Our study underscores the limitations of current approaches for CNV identification and provides an effective method that yields high-quality CNVs for application in clinical diagnostics.

An interaction-based model for neuropsychiatric features of copy-number variants.

Variably expressive copy-number variants (CNVs) are characterized by extensive phenotypic heterogeneity of neuropsychiatric phenotypes. Approaches to identify single causative genes for these phenotypes within each CNV have not been successful. Here, we posit using multiple lines of evidence, including pathogenicity metrics, functional assays of model organisms, and gene expression data, that multiple genes within each CNV region are likely responsible for the observed phenotypes. We propose that candidate genes within each region likely interact with each other through shared pathways to modulate the individual gene phenotypes, emphasizing the genetic complexity of CNV-associated neuropsychiatric features.

Gene discoveries in autism are biased towards comorbidity with intellectual disability.

BACKGROUND: Autism typically presents with highly heterogeneous features, including frequent comorbidity with intellectual disability (ID). The overlap between these phenotypes has confounded the diagnosis and discovery of genetic factors associated with autism. We analysed pathogenic de novo genetic variants in individuals with autism who had either ID or normal cognitive function to determine whether genes associated with autism also contribute towards ID comorbidity. METHODS: We analysed 2290 individuals from the Simons Simplex Collection for de novo likely gene-disruptive (LGD) variants and copy-number variants (CNVs), and determined their relevance towards IQ and Social Responsiveness Scale (SRS) measures. RESULTS: Individuals who carried de novo variants in a set of 173 autism-associated genes showed an average 12.8-point decrease in IQ scores (p=5.49×10-6) and 2.8-point increase in SRS scores (p=0.013) compared with individuals without such variants. Furthermore, individuals with high-functioning autism (IQ >100) had lower frequencies of de novo LGD variants (42 of 397 vs 86 of 562, p=0.021) and CNVs (9 of 397 vs 24 of 562, p=0.065) compared with individuals who manifested both autism and ID (IQ <70). Pathogenic variants disrupting autism-associated genes conferred a 4.85-fold increased risk (p=0.011) for comorbid ID, while de novo variants observed in individuals with high-functioning autism disrupted genes with little functional relevance towards neurodevelopment. CONCLUSIONS: Pathogenic de novo variants disrupting autism-associated genes contribute towards autism and ID comorbidity, while other genetic factors are likely to be causal for high-functioning autism.

Human copy number variation and complex genetic disease.

Copy number variants (CNVs) play an important role in human disease and population diversity. Advancements in technology have allowed for the analysis of CNVs in thousands of individuals with disease in addition to thousands of controls. These studies have identified rare CNVs associated with neuropsychiatric diseases such as autism, schizophrenia, and intellectual disability. In addition, copy number polymorphisms (CNPs) are present at higher frequencies in the population, show high diversity in copy number, sequence, and structure, and have been associated with multiple phenotypes, primarily related to immune or environmental response. However, the landscape of copy number variation still remains largely unexplored, especially for smaller CNVs and those embedded within complex regions of the human genome. An integrated approach including characterization of single nucleotide variants and CNVs in a large number of individuals with disease and normal genomes holds the promise of thoroughly elucidating the genetic basis of human disease and diversity.

De Novo and Rare Variants at Multiple Loci Support the Oligogenic Origins of Atrioventricular Septal Heart Defects.

Congenital heart disease (CHD) has a complex genetic etiology, and recent studies suggest that high penetrance de novo mutations may account for only a small fraction of disease. In a multi-institutional cohort surveyed by exome sequencing, combining analysis of 987 individuals (discovery cohort of 59 affected trios and 59 control trios, and a replication cohort of 100 affected singletons and 533 unaffected singletons) we observe variation at novel and known loci related to a specific cardiac malformation the atrioventricular septal defect (AVSD). In a primary analysis, by combining developmental coexpression networks with inheritance modeling, we identify a de novo mutation in the DNA binding domain of NR1D2 (p.R175W). We show that p.R175W changes the transcriptional activity of Nr1d2 using an in vitro transactivation model in HUVEC cells. Finally, we demonstrate previously unrecognized cardiovascular malformations in the Nr1d2tm1-Dgen knockout mouse. In secondary analyses we map genetic variation to protein-interaction networks suggesting a role for two collagen genes in AVSD, which we corroborate by burden testing in a second replication cohort of 100 AVSDs and 533 controls (p = 8.37e-08). Finally, we apply a rare-disease inheritance model to identify variation in genes previously associated with CHD (ZFPM2, NSD1, NOTCH1, VCAN, and MYH6), cardiac malformations in mouse models (ADAM17, CHRD, IFT140, PTPRJ, RYR1 and ATE1), and hypomorphic alleles of genes causing syndromic CHD (EHMT1, SRCAP, BBS2, NOTCH2, and KMT2D) in 14 of 59 trios, greatly exceeding variation in control trios without CHD (p = 9.60e-06). In total, 32% of trios carried at least one putatively disease-associated variant across 19 loci,suggesting that inherited and de novo variation across a heterogeneous group of loci may contribute to disease risk.

Parental Origin of Interstitial Duplications at 15q11.2-q13.3 in Schizophrenia and Neurodevelopmental Disorders.

Duplications at 15q11.2-q13.3 overlapping the Prader-Willi/Angelman syndrome (PWS/AS) region have been associated with developmental delay (DD), autism spectrum disorder (ASD) and schizophrenia (SZ). Due to presence of imprinted genes within the region, the parental origin of these duplications may be key to the pathogenicity. Duplications of maternal origin are associated with disease, whereas the pathogenicity of paternal ones is unclear. To clarify the role of maternal and paternal duplications, we conducted the largest and most detailed study to date of parental origin of 15q11.2-q13.3 interstitial duplications in DD, ASD and SZ cohorts. We show, for the first time, that paternal duplications lead to an increased risk of developing DD/ASD/multiple congenital anomalies (MCA), but do not appear to increase risk for SZ. The importance of the epigenetic status of 15q11.2-q13.3 duplications was further underlined by analysis of a number of families, in which the duplication was paternally derived in the mother, who was unaffected, whereas her offspring, who inherited a maternally derived duplication, suffered from psychotic illness. Interestingly, the most consistent clinical characteristics of SZ patients with 15q11.2-q13.3 duplications were learning or developmental problems, found in 76% of carriers. Despite their lower pathogenicity, paternal duplications are less frequent in the general population with a general population prevalence of 0.0033% compared to 0.0069% for maternal duplications. This may be due to lower fecundity of male carriers and differential survival of embryos, something echoed in the findings that both types of duplications are de novo in just over 50% of cases. Isodicentric chromosome 15 (idic15) or interstitial triplications were not observed in SZ patients or in controls. Overall, this study refines the distinct roles of maternal and paternal interstitial duplications at 15q11.2-q13.3, underlining the critical importance of maternally expressed imprinted genes in the contribution of Copy Number Variants (CNVs) at this interval to the incidence of psychotic illness. This work will have tangible benefits for patients with 15q11.2-q13.3 duplications by aiding genetic counseling.

Sporadic autism exomes reveal a highly interconnected protein network of de novo mutations.

It is well established that autism spectrum disorders (ASD) have a strong genetic component; however, for at least 70% of cases, the underlying genetic cause is unknown. Under the hypothesis that de novo mutations underlie a substantial fraction of the risk for developing ASD in families with no previous history of ASD or related phenotypes--so-called sporadic or simplex families--we sequenced all coding regions of the genome (the exome) for parent-child trios exhibiting sporadic ASD, including 189 new trios and 20 that were previously reported. Additionally, we also sequenced the exomes of 50 unaffected siblings corresponding to these new (n = 31) and previously reported trios (n = 19), for a total of 677 individual exomes from 209 families. Here we show that de novo point mutations are overwhelmingly paternal in origin (4:1 bias) and positively correlated with paternal age, consistent with the modest increased risk for children of older fathers to develop ASD. Moreover, 39% (49 of 126) of the most severe or disruptive de novo mutations map to a highly interconnected ß-catenin/chromatin remodelling protein network ranked significantly for autism candidate genes. In proband exomes, recurrent protein-altering mutations were observed in two genes: CHD8 and NTNG1. Mutation screening of six candidate genes in 1,703 ASD probands identified additional de novo, protein-altering mutations in GRIN2B, LAMC3 and SCN1A. Combined with copy number variant (CNV) data, these results indicate extreme locus heterogeneity but also provide a target for future discovery, diagnostics and therapeutics.

A novel copy number variants kernel association test with application to autism spectrum disorders studies.

MOTIVATION: Copy number variants (CNVs) have been implicated in a variety of neurodevelopmental disorders, including autism spectrum disorders, intellectual disability and schizophrenia. Recent advances in high-throughput genomic technologies have enabled rapid discovery of many genetic variants including CNVs. As a result, there is increasing interest in studying the role of CNVs in the etiology of many complex diseases. Despite the availability of an unprecedented wealth of CNV data, methods for testing association between CNVs and disease-related traits are still under-developed due to the low prevalence and complicated multi-scale features of CNVs. RESULTS: We propose a novel CNV kernel association test (CKAT) in this paper. To address the low prevalence, CNVs are first grouped into CNV regions (CNVR). Then, taking into account the multi-scale features of CNVs, we first design a single-CNV kernel which summarizes the similarity between two CNVs, and next aggregate the single-CNV kernel to a CNVR kernel which summarizes the similarity between two CNVRs. Finally, association between CNVR and disease-related traits is assessed by comparing the kernel-based similarity with the similarity in the trait using a score test for variance components in a random effect model. We illustrate the proposed CKAT using simulations and show that CKAT is more powerful than existing methods, while always being able to control the type I error. We also apply CKAT to a real dataset examining the association between CNV and autism spectrum disorders, which demonstrates the potential usefulness of the proposed method. AVAILABILITY AND IMPLEMENTATION: A R package to implement the proposed CKAT method is available at http://works.bepress.com/debashis_ghosh/ CONTACTS: xzhan@fhcrc.org or debashis.ghosh@ucdenver.eduSupplementary information: Supplementary data are available at Bioinformatics online.

Implication of LRRC4C and DPP6 in neurodevelopmental disorders.

We performed whole-genome sequencing on an individual from a family with variable psychiatric phenotypes that had a sensory processing disorder, apraxia, and autism. The proband harbored a maternally inherited balanced translocation (46,XY,t(11;14)(p12;p12)mat) that disrupted LRRC4C, a member of the highly specialized netrin G family of axon guidance molecules. The proband also inherited a paternally derived chromosomal inversion that disrupted DPP6, a potassium channel interacting protein. Copy Number (CN) analysis in 14,077 cases with neurodevelopmental disorders and 8,960 control subjects revealed that 60% of cases with exonic deletions in LRRC4C had a second clinically recognizable syndrome associated with variable clinical phenotypes, including 16p11.2, 1q44, and 2q33.1 CN syndromes, suggesting LRRC4C deletion variants may be modifiers of neurodevelopmental disorders. In vitro, functional assessments modeling patient deletions in LRRC4C suggest a negative regulatory role of these exons found in the untranslated region of LRRC4C, which has a single, terminal coding exon. These data suggest that the proband's autism may be due to the inheritance of disruptions in both DPP6 and LRRC4C, and may highlight the importance of the netrin G family and potassium channel interacting molecules in neurodevelopmental disorders. © 2016 Wiley Periodicals, Inc.

Refinement and discovery of new hotspots of copy-number variation associated with autism spectrum disorder.

Rare copy-number variants (CNVs) have been implicated in autism and intellectual disability. These variants are large and affect many genes but lack clear specificity toward autism as opposed to developmental-delay phenotypes. We exploited the repeat architecture of the genome to target segmental duplication-mediated rearrangement hotspots (n = 120, median size 1.78 Mbp, range 240 kbp to 13 Mbp) and smaller hotspots flanked by repetitive sequence (n = 1,247, median size 79 kbp, range 3-96 kbp) in 2,588 autistic individuals from simplex and multiplex families and in 580 controls. Our analysis identified several recurrent large hotspot events, including association with 1q21 duplications, which are more likely to be identified in individuals with autism than in those with developmental delay (p = 0.01; OR = 2.7). Within larger hotspots, we also identified smaller atypical CNVs that implicated CHD1L and ACACA for the 1q21 and 17q12 deletions, respectively. Our analysis, however, suggested no overall increase in the burden of smaller hotspots in autistic individuals as compared to controls. By focusing on gene-disruptive events, we identified recurrent CNVs, including DPP10, PLCB1, TRPM1, NRXN1, FHIT, and HYDIN, that are enriched in autism. We found that as the size of deletions increases, nonverbal IQ significantly decreases, but there is no impact on autism severity; and as the size of duplications increases, autism severity significantly increases but nonverbal IQ is not affected. The absence of an increased burden of smaller CNVs in individuals with autism and the failure of most large hotspots to refine to single genes is consistent with a model where imbalance of multiple genes contributes to a disease state.