Paternally inherited cis-regulatory structural variants are associated with autism

Systematic assessment of structural variant annotation tools for genomic interpretation

Structural variants (SVs) over 50 base pairs play a significant role in phenotypic diversity and are associated with various diseases, but their analysis is complex and resource-intensive. Numerous computational tools have been developed for SV prioritization, yet their effectiveness in biomedicine remains unclear. Here we benchmarked eight widely used SV prioritization tools, categorized into knowledge-driven (AnnotSV, ClassifyCNV) and data-driven (CADD-SV, dbCNV, StrVCTVRE, SVScore, TADA, XCNV) groups in accordance with the ACMG guidelines. We assessed their accuracy, robustness, and usability across diverse genomic contexts, biological mechanisms and computational efficiency using seven carefully curated independent datasets. Our results revealed that both groups of methods exhibit comparable effectiveness in predicting SV pathogenicity, although performance varies among tools, emphasizing the importance of selecting the appropriate tool based on specific research purposes. Furthermore, we pinpointed the potential improvement of expanding these tools for future applications. Our benchmarking framework provides a crucial evaluation method for SV analysis tools, offering practical guidance for biomedical research and facilitating the advancement of better genomic research tools.

Diversity and consequences of structural variation in the human genome

The biomedical community is increasingly invested in capturing all genetic variants across human genomes, interpreting their functional consequences and translating these findings to the clinic. A crucial component of this endeavour is the discovery and characterization of structural variants (SVs), which are ubiquitous in the human population, heterogeneous in their mutational processes, key substrates for evolution and adaptation, and profound drivers of human disease. The recent emergence of new technologies and the remarkable scale of sequence-based population studies have begun to crystalize our understanding of SVs as a mutational class and their widespread influence across phenotypes. In this Review, we summarize recent discoveries and new insights into SVs in the human genome in terms of their mutational patterns, population genetics, functional consequences, and impact on human traits and disease. We conclude by outlining three frontiers to be explored by the field over the next decade.

Generation and Characterization of a Knockout Mouse of an Enhancer of EBF3

Genomic studies of autism and other neurodevelopmental disorders have identified several relevant protein-coding and noncoding variants. One gene with an excess of protein-coding de novo variants is EBF3 that also is the gene underlying the Hypotonia, Ataxia, and Delayed Development Syndrome (HADDS). In previous work, we have identified noncoding de novo variants in an enhancer of EBF3 called hs737 and further showed that there was an enrichment of deletions of this enhancer in individuals with neurodevelopmental disorders. In this present study, we generated a novel mouse line that deletes the highly conserved, orthologous mouse region of hs737 within the Rr169617 regulatory region, and characterized the molecular and phenotypic aspects of this mouse model. This line contains a 1,160 bp deletion within Rr169617 and through heterozygous crosses we found a deviation from Mendelian expectation (p = 0.02) with a significant depletion of the deletion allele (p = 5.8 × 10-4). Rr169617 +/- mice had a reduction of Ebf3 expression by 10% and Rr169617 -/- mice had a reduction of Ebf3 expression by 20%. Differential expression analyses in E12.5 forebrain, midbrain, and hindbrain in Rr169617 +/+ versus Rr169617 -/- mice identified dysregulated genes including histone genes (i.e., Hist1h1e, Hist1h2bk, Hist1h3i, Hist1h2ao) and other brain development related genes (e.g., Chd5, Ntng1). A priori phenotyping analysis (open field, hole board and light/dark transition) identified sex-specific differences in behavioral traits when comparing Rr169617 -/- males versus females; whereby, males were observed to be less mobile, move slower, and spend more time in the dark. Furthermore, both sexes when homozygous for the enhancer deletion displayed body composition differences when compared to wild-type mice. Overall, we show that deletion within Rr169617 reduces the expression of Ebf3 and results in phenotypic outcomes consistent with potential sex specific behavioral differences. This enhancer deletion line provides a valuable resource for others interested in noncoding regions in neurodevelopmental disorders and/or those interested in the gene regulatory network downstream of Ebf3.

Shared rare genetic variants in multiplex autism families suggest a social memory gene under selection

Autism spectrum disorder (ASD) affects up to 1 in 59 children, and is one of the most common neurodevelopmental disorders. Recent genomic studies have highlighted the role of rare variants in ASD. This study aimed to identify genes affected by rare variants shared by siblings with ASD and validate the function of a candidate gene FRRS1L. By integrating the whole genome sequencing data of 866 multiplex families from the Hartwell Foundation's Autism Research and Technology Initiative and Autism Speaks MSSNG project, we identified rare variants shared by two or more siblings with ASD. Using shared rare variants (SRVs), we selected candidate genes for ASD. Gene prioritization by evolutionary features and expression alterations on autism identified FRRS1L in two families, including one with impaired social behaviors. One variant in this family was 6 bp away from human-specific trinucleotide fixation. Additionally, CRISPR/Cas9 experiments demonstrated downregulation by a family variant and upregulation by a fixed site. Population genetics further demonstrated that upregulation of this gene has been favored during human evolution. Various mouse behavioral tests showed that Frrs1l knockout specifically impairs social novelty recognition without altering other behavioral phenotypes. Furthermore, we constructed humanized mice by introducing human sequences into a mouse genome. These knockin mice showed improved abilities to retain social memory over time. The results of our population genetic and evolutionary analyses, behavior experiments, and genome editing propose a molecular mechanism that may confer a selective advantage through social memory enhancement and may cause autism-related social impairment when disrupted in humans. These findings highlight the role of FRRS1L, the AMPA receptor subunit, in social behavior and evolution.

Integrative genetic analysis: cornerstone of precision psychiatry

The role of genetic testing in the domain of neurodevelopmental and psychiatric disorders (NPDs) is gradually changing from providing etiological explanation for the presence of NPD phenotypes to also identifying young individuals at high risk of developing NPDs before their clinical manifestation. In clinical practice, the latter implies a shift towards the availability of individual genetic information predicting a certain liability to develop an NPD (e.g., autism, intellectual disability, psychosis etc.). The shift from mostly a posteriori explanation to increasingly a priori risk prediction is the by-product of the systematic implementation of whole exome or genome sequencing as part of routine diagnostic work-ups during the neonatal and prenatal periods. This rapid uptake of genetic testing early in development has far-reaching consequences for psychiatry: Whereas until recently individuals would come to medical attention because of signs of abnormal developmental and/or behavioral symptoms, increasingly, individuals are presented based on genetic liability for NPD outcomes before NPD symptoms emerge. This novel clinical scenario, while challenging, also creates opportunities for research on prevention interventions and precision medicine approaches. Here, we review why optimization of individual risk prediction is a key prerequisite for precision medicine in the sphere of NPDs, as well as the technological and statistical methods required to achieve this ambition.

Genetic Variant Analyses Identify Novel Candidate Autism Risk Genes from a Highly Consanguineous Cohort of 104 Families from Oman

Deficits in social communication, restricted interests, and repetitive behaviours are hallmarks of autism spectrum disorder (ASD). Despite high genetic heritability, the majority of clinically diagnosed ASD cases have unknown genetic origins. We performed genome sequencing on mothers, fathers, and affected individuals from 104 families with ASD in Oman, a Middle Eastern country underrepresented in international genetic studies. This approach identified 48 novel candidate genes significantly associated with ASD in Oman. In particular, 35 of these genes have been previously implicated in neurodevelopmental disorders (NDDs) in other populations, underscoring the conserved genetic basis of ASD across ethnicities. Genetic variants within these candidate genes that would impact the encoded protein included 1 insertion, 4 frameshift, 6 splicing, 12 nonsense, and 67 missense changes. Notably, 61% of the SNVs were homozygous, suggesting a prominent recessive genetic architecture for ASD in this unique population. The scarcity of genetic studies on ASD in the Arabian Peninsula has impeded the understanding of the unique genetic landscape of ASD in this region. These findings help bridge this knowledge gap and provide valuable insights into the complex genetic basis of ASD in Oman.

Observational methods for human studies of transgenerational effects

There are substantial challenges in studying human transgenerational epigenetic outcomes resulting from environmental conditions. The task requires specialized methods and tools that incorporate specific knowledge of multigenerational relationship combinations of probands and their ancestors, phenotype data for individuals, environmental information of ancestors and their descendants, which can span historical to present datasets, and informative environmental data that chronologically aligns with ancestors and descendants over space and time. As a result, there are few epidemiologic studies of potential transgenerational effects in human populations, thus limiting the knowledge of ancestral environmental conditions and the potential impacts we face with modern human health outcomes. In an effort to overcome some of the challenges in studying human transgenerational effects, we present two transgenerational study designs: transgenerational space-time cluster detection and transgenerational case-control study design. Like other epidemiological methods, these methods determine whether there are statistical associations between phenotypic outcomes (e.g., adverse health outcomes) among probands and the shared environments and environmental factors facing their ancestors. When the ancestor is a paternal grandparent, a statistically significant association provides some evidence that a transgenerational inheritable factor may be involved. Such results may generate useful hypotheses that can be explored using epigenomic data to establish conclusive evidence of transgenerational heritable effects. Both methods are proband-centric: They are designed around the phenotype of interest in the proband generation for case selection and family pedigree creation. In the examples provided, we incorporate at least three generations of paternal lineage in both methods to observe a potential transgenerational effect.

Burden re-analysis of neurodevelopmental disorder cohorts for prioritization of candidate genes

This study aimed to uncover novel genes associated with neurodevelopmental disorders (NDD) by leveraging recent large-scale de novo burden analysis studies to enhance a virtual gene panel used in a diagnostic setting. We re-analyzed historical trio-exome sequencing data from 745 individuals with NDD according to the most recent diagnostic standards, resulting in a cohort of 567 unsolved individuals. Next, we designed a virtual gene panel containing candidate genes from three large de novo burden analysis studies in NDD and prioritized candidate genes by stringent filtering for ultra-rare de novo variants with high pathogenicity scores. Our analysis revealed an increased burden of de novo variants in our selected candidate genes within the unsolved NDD cohort and identified qualifying de novo variants in seven candidate genes: RIF1, CAMK2D, RAB11FIP4, AGO3, PCBP2, LEO1, and VCP. Clinical data were collected from six new individuals with de novo or inherited LEO1 variants and three new individuals with de novo PCBP2 variants. Our findings add additional evidence for LEO1 as a risk gene for autism and intellectual disability. Furthermore, we prioritize PCBP2 as a candidate gene for NDD associated with motor and language delay. In summary, by leveraging de novo burden analysis studies, employing a stringent variant filtering pipeline, and engaging in targeted patient recruitment, our study contributes to the identification of novel genes implicated in NDDs.

Whole-genome sequencing identifies novel genes for autism in Chinese trios

Autism spectrum disorder (ASD) is a neurodevelopmental disorder with high genetic heritability but heterogeneity. Fully understanding its genetics requires whole-genome sequencing (WGS), but the ASD studies utilizing WGS data in Chinese population are limited. In this study, we present a WGS study for 334 individuals, including 112 ASD patients and their non-ASD parents. We identified 146 de novo variants in coding regions in 85 cases and 60 inherited variants in coding regions. By integrating these variants with an association model, we identified 33 potential risk genes (P<0.001) enriched in neuron and regulation related biological process. Besides the well-known ASD genes (SCN2A, NF1, SHANK3, CHD8 etc.), several high confidence genes were highlighted by a series of functional analyses, including CTNND1, DGKZ, LRP1, DDN, ZNF483, NR4A2, SMAD6, INTS1, and MRPL12, with more supported evidence from GO enrichment, expression and network analysis. We also integrated RNA-seq data to analyze the effect of the variants on the gene expression and found 12 genes in the individuals with the related variants had relatively biased expression. We further presented the clinical phenotypes of the proband carrying the risk genes in both our samples and Caucasian samples to show the effect of the risk genes on phenotype. Regarding variants in non-coding regions, a total of 74 de novo variants and 30 inherited variants were predicted as pathogenic with high confidence, which were mapped to specific genes or regulatory features. The number of de novo variants found in patient was significantly associated with the parents' ages at the birth of the child, and gender with trend. We also identified small de novo structural variants in ASD trios. The results in this study provided important evidence for understanding the genetic mechanism of ASD.

A Genetic Bridge Between Medicine and Neurodiversity for Autism

Autism represents a large spectrum of diverse individuals with varying underlying genetic architectures and needs. For some individuals, a single de novo or ultrarare genetic variant has a large effect on the intensity of specific dimensions of the phenotype, while, for others, a combination of thousands of variants commonly found in the general population are involved. The variants with large impact are found in up to 30% of autistic individuals presenting with intellectual disability, significant speech delay, motor delay, and/or seizures. The common variants are shared with those found in individuals with attention-deficit/hyperactivity disorder, major depressive disorders, greater educational attainment, and higher cognitive performance, suggesting overlapping genetic architectures. The genetic variants modulate the function of chromatin remodeling and synaptic proteins that influence the connectivity of neuronal circuits and, in interaction with the environment of each individual, the subsequent cognitive and personal trajectory of the child. Overall, this genetic heterogeneity mirrors the phenotypic diversity of autistic individuals and provides a helpful bridge between biomedical and neurodiversity perspectives. We propose that participative and multidisciplinary research should use this information to understand better the assessment, treatments, and accommodations that individuals with autism and families need.

Genetic modifiers and ascertainment drive variable expressivity of complex disorders

Variable expressivity of disease-associated variants implies a role for secondary variants that modify clinical features. We assessed the effects of modifier variants towards clinical outcomes of 2,252 individuals with primary variants. Among 132 families with the 16p12.1 deletion, distinct rare and common variant classes conferred risk for specific developmental features, including short tandem repeats for neurological defects and SNVs for microcephaly, while additional disease-associated variants conferred multiple genetic diagnoses. Within disease and population cohorts of 773 individuals with the 16p12.1 deletion, we found opposing effects of secondary variants towards clinical features across ascertainments. Additional analysis of 1,479 probands with other primary variants, such as 16p11.2 deletion and CHD8 variants, and 1,084 without primary variants, showed that phenotypic associations differed by primary variant context and were influenced by synergistic interactions between primary and secondary variants. Our study provides a paradigm to dissect the genomic architecture of complex disorders towards personalized treatment.

Potential clinical applications of advanced genomic analysis in cerebral palsy

Cerebral palsy (CP) has historically been attributed to acquired insults, but emerging research suggests that genetic variations are also important causes of CP. While microarray and whole-exome sequencing based studies have been the primary methods for establishing new CP-gene relationships and providing a genetic etiology for individual patients, the cause of their condition remains unknown for many patients with CP. Recent advancements in genomic technologies offer additional opportunities to uncover variations in human genomes, transcriptomes, and epigenomes that have previously escaped detection. In this review, we outline the use of these state-of-the-art technologies to address the molecular diagnostic challenges experienced by individuals with CP. We also explore the importance of identifying a molecular etiology whenever possible, given the potential for genomic medicine to provide opportunities to treat patients with CP in new and more precise ways.

The Importance of Large-Scale Genomic Studies to Unravel Genetic Risk Factors for Autism

Autism spectrum disorder (ASD) is a common and highly heritable neurodevelopmental disorder. During the last 15 years, advances in genomic technologies and the availability of increasingly large patient cohorts have greatly expanded our knowledge of the genetic architecture of ASD and its neurobiological mechanisms. Over two hundred risk regions and genes carrying rare de novo and transmitted high-impact variants have been identified. Additionally, common variants with small individual effect size are also important, and a number of loci are now being uncovered. At the same time, these new insights have highlighted ongoing challenges. In this perspective article, we summarize developments in ASD genetic research and address the enormous impact of large-scale genomic initiatives on ASD gene discovery.

Long-read sequencing and structural variant characterization in 1,019 samples from the 1000 Genomes Project

Structural variants (SVs) contribute significantly to human genetic diversity and disease 1-4 . Previously, SVs have remained incompletely resolved by population genomics, with short-read sequencing facing limitations in capturing the whole spectrum of SVs at nucleotide resolution 5-7 . Here we leveraged nanopore sequencing 8 to construct an intermediate coverage resource of 1,019 long-read genomes sampled within 26 human populations from the 1000 Genomes Project. By integrating linear and graph-based approaches for SV analysis via pangenome graph-augmentation, we uncover 167,291 sequence-resolved SVs in these samples, considerably advancing SV characterization compared to population-wide short-read sequencing studies 3,4 . Our analysis details diverse SV classes-deletions, duplications, insertions, and inversions-at population-scale. LINE-1 and SVA retrotransposition activities frequently mediate transductions 9,10 of unique sequences, with both mobile element classes transducing sequences at either the 3'- or 5'-end, depending on the source element locus. Furthermore, analyses of SV breakpoint junctions suggest a continuum of homology-mediated rearrangement processes are integral to SV formation, and highlight evidence for SV recurrence involving repeat sequences. Our open-access dataset underscores the transformative impact of long-read sequencing in advancing the characterisation of polymorphic genomic architectures, and provides a resource for guiding variant prioritisation in future long-read sequencing-based disease studies.

Contribution of de novo retroelements to birth defects and childhood cancers

Insertion of active retroelements-L1s, Alus, and SVAs-can disrupt proper genome function and lead to various disorders including cancer. However, the role of de novo retroelements (DNRTs) in birth defects and childhood cancers has not been well characterized due to the lack of adequate data and efficient computational tools. Here, we examine whole-genome sequencing data of 3,244 trios from 12 birth defect and childhood cancer cohorts in the Gabriella Miller Kids First Pediatric Research Program. Using an improved version of our tool xTea (x-Transposable element analyzer) that incorporates a deep-learning module, we identified 162 DNRTs, as well as 2 pseudogene insertions. Several variants are likely to be causal, such as a de novo Alu insertion that led to the ablation of a whole exon in the NF1 gene in a proband with brain tumor. We observe a high de novo SVA insertion burden in both high-intolerance loss-of-function genes and exons as well as more frequent de novo Alu insertions of paternal origin. We also identify potential mosaic DNRTs from embryonic stages. Our study reveals the important roles of DNRTs in causing birth defects and predisposition to childhood cancers.

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.

PhenoSV: interpretable phenotype-aware model for the prioritization of genes affected by structural variants

Structural variants (SVs) represent a major source of genetic variation associated with phenotypic diversity and disease susceptibility. While long-read sequencing can discover over 20,000 SVs per human genome, interpreting their functional consequences remains challenging. Existing methods for identifying disease-related SVs focus on deletion/duplication only and cannot prioritize individual genes affected by SVs, especially for noncoding SVs. Here, we introduce PhenoSV, a phenotype-aware machine-learning model that interprets all major types of SVs and genes affected. PhenoSV segments and annotates SVs with diverse genomic features and employs a transformer-based architecture to predict their impacts under a multiple-instance learning framework. With phenotype information, PhenoSV further utilizes gene-phenotype associations to prioritize phenotype-related SVs. Evaluation on extensive human SV datasets covering all SV types demonstrates PhenoSV's superior performance over competing methods. Applications in diseases suggest that PhenoSV can determine disease-related genes from SVs. A web server and a command-line tool for PhenoSV are available at https://phenosv.wglab.org .

[Autism spectrum disorder in adulthood]

Autism is a neurodevelopmental disorder that starts in early childhood and persists over the lifespan. A combination of genetic factors and environmental factors around birth contribute to its etiology. Autistic individuals show differences and difficulties in social interaction and communication as well as repetitive, stereotypical behavior and interests. The diagnostic procedure is complex and should be carried out in a specialized assessment unit. Diagnostic assessment is based on behavioral observation and a careful evaluation of developmental history. A wide range of potential differential diagnoses should be considered. Autistic adults have a higher risk of developing psychiatric disorders such as anxiety and depression. Psychotherapeutic treatment that is adapted to autism-related difficulties can be helpful. Co-occurring conditions should be treated in accordance with disorder-specific guidelines. Psychopharmacological treatment of co-occurring conditions is, in most cases, only recommended as an addition to behavioral interventions. Autistic people often experience difficulties in social participation, which can be targeted with sociotherapeutic interventions.

Three generation families: Analysis of de novo variants in autism

De novo variants (DNVs) analysis has proven to be a powerful approach to gene discovery in Autism Spectrum Disorder (ASD), which has not yet been shown in a Brazilian ASD cohort. The relevance of inherited rare variants has also been suggested, particularly in oligogenic models. We hypothesized that three-generation analyses of DNVs could provide new insights into the relevance of de novo and inherited variants across generations. To accomplish this goal, we performed whole-exome sequencing of 33 septet families composed of probands, parents, and grandparents (n = 231 individuals) and compared DNV rates (DNVr) between generations and those from two control cohorts. The DNVr in the probands (DNVr = 1.16) was marginally higher than in parents (DNVr = 0.60; p = 0.054), and in controls (DNVr = 0.68; p = 0.035, congenital heart disorder and DNVr = 0.70; p = 0.047, unaffected ASD siblings from Simons Simplex Collection). Moreover, most of the DNVs were found to have paternal origin in both generations (84.6%). Finally, we observed that 40% (6/15) of the DNVs in parents transmitted for probands are in ASD or ASD candidate genes, representing recently emerged risk variants to ASD in their families and suggest ZNF536, MSL2 and HDAC9 as ASD candidate genes. We did not observe an enrichment of risk variants nor sex bias of transmitted variants in the three generations, that can be due to sample size. These results further reinforce the relevance of de novo variants in ASD.

The rate of de novo structural variation is increased in in vitro-produced offspring and preferentially affects the paternal genome

Assisted reproductive technologies (ARTs), including in vitro maturation and fertilization (IVF), are increasingly used in human and animal reproduction. Whether these technologies directly affect the rate of de novo mutation (DNM), and to what extent, has been a matter of debate. Here we take advantage of domestic cattle, characterized by complex pedigrees that are ideally suited to detect DNMs and by the systematic use of ART, to study the rate of de novo structural variation (dnSV) in this species and how it is impacted by IVF. By exploiting features of associated de novo point mutations (dnPMs) and dnSVs in clustered DNMs, we provide strong evidence that (1) IVF increases the rate of dnSV approximately fivefold, and (2) the corresponding mutations occur during the very early stages of embryonic development (one- and two-cell stage), yet primarily affect the paternal genome.

Structural Variations Contribute to the Genetic Etiology of Autism Spectrum Disorder and Language Impairments

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by restrictive interests and/or repetitive behaviors and deficits in social interaction and communication. ASD is a multifactorial disease with a complex polygenic genetic architecture. Its genetic contributing factors are not yet fully understood, especially large structural variations (SVs). In this study, we aimed to assess the contribution of SVs, including copy number variants (CNVs), insertions, deletions, duplications, and mobile element insertions, to ASD and related language impairments in the New Jersey Language and Autism Genetics Study (NJLAGS) cohort. Within the cohort, ~77% of the families contain SVs that followed expected segregation or de novo patterns and passed our filtering criteria. These SVs affected 344 brain-expressed genes and can potentially contribute to the genetic etiology of the disorders. Gene Ontology and protein-protein interaction network analysis suggested several clusters of genes in different functional categories, such as neuronal development and histone modification machinery. Genes and biological processes identified in this study contribute to the understanding of ASD and related neurodevelopment disorders.

NeuroCNVscore: a tissue-specific framework to prioritise the pathogenicity of CNVs in neurodevelopmental disorders

BACKGROUND

Neurodevelopmental disorders (NDDs) are associated with altered development of the brain especially in childhood. Copy number variants (CNVs) play a crucial role in the genetic aetiology of NDDs by disturbing gene expression directly at linear sequence or remotely at three-dimensional genome level in a tissue-specific manner. Despite the substantial increase in NDD studies employing whole-genome sequencing, there is no specific tool for prioritising the pathogenicity of CNVs in the context of NDDs.

METHODS

Using an XGBoost classifier, we integrated 189 features that represent genomic sequences, gene information and functional/genomic segments for evaluating genome-wide CNVs in a neuro/brain-specific manner, to develop a new tool, neuroCNVscore. We used Human Phenotype Ontology to construct an independent NDD-related set.

RESULTS

Our neuroCNVscore framework (https://github.com/lxsbch/neuroCNVscore) achieved high predictive performance (precision recall=0.82; area under curve=0.85) and outperformed an existing reference method SVScore. Notably, the predicted pathogenic CNVs showed enrichment in known genes associated with autism.

CONCLUSIONS

NeuroCNVscore prioritises functional, deleterious and pathogenic CNVs in NDDs at whole genome-wide level, which is important for genetic studies and clinical genomic screening of NDDs as well as for providing novel biological insights into NDDs.

A systematic review of non-coding RNA genes with differential expression profiles associated with autism spectrum disorders

AIMS

To identify differential expression of shorter non-coding RNA (ncRNA) genes associated with autism spectrum disorders (ASD).

BACKGROUND

ncRNA are functional molecules that derive from non-translated DNA sequence. The HUGO Gene Nomenclature Committee (HGNC) have approved ncRNA gene classes with alignment to the reference human genome. One subset is microRNA (miRNA), which are highly conserved, short RNA molecules that regulate gene expression by direct post-transcriptional repression of messenger RNA. Several miRNA genes are implicated in the development and regulation of the nervous system. Expression of miRNA genes in ASD cohorts have been examined by multiple research groups. Other shorter classes of ncRNA have been examined less. A comprehensive systematic review examining expression of shorter ncRNA gene classes in ASD is timely to inform the direction of research.

METHODS

We extracted data from studies examining ncRNA gene expression in ASD compared with non-ASD controls. We included studies on miRNA, piwi-interacting RNA (piRNA), small NF90 (ILF3) associated RNA (snaR), small nuclear RNA (snRNA), small nucleolar RNA (snoRNA), transfer RNA (tRNA), vault RNA (vtRNA) and Y RNA. The following electronic databases were searched: Cochrane Library, EMBASE, PubMed, Web of Science, PsycINFO, ERIC, AMED and CINAHL for papers published from January 2000 to May 2022. Studies were screened by two independent investigators with a third resolving discrepancies. Data was extracted from eligible papers.

RESULTS

Forty-eight eligible studies were included in our systematic review with the majority examining miRNA gene expression alone. Sixty-four miRNA genes had differential expression in ASD compared to controls as reported in two or more studies, but often in opposing directions. Four miRNA genes had differential expression in the same direction in the same tissue type in at least 3 separate studies. Increased expression was reported in miR-106b-5p, miR-155-5p and miR-146a-5p in blood, post-mortem brain, and across several tissue types, respectively. Decreased expression was reported in miR-328-3p in bloods samples. Seven studies examined differential expression from other classes of ncRNA, including piRNA, snRNA, snoRNA and Y RNA. No individual ncRNA genes were reported in more than one study. Six studies reported differentially expressed snoRNA genes in ASD. A meta-analysis was not possible because of inconsistent methodologies, disparate tissue types examined, and varying forms of data presented.

CONCLUSION

There is limited but promising evidence associating the expression of certain miRNA genes and ASD, although the studies are of variable methodological quality and the results are largely inconsistent. There is emerging evidence associating differential expression of snoRNA genes in ASD. It is not currently possible to say whether the reports of differential expression in ncRNA may relate to ASD aetiology, a response to shared environmental factors linked to ASD such as sleep and nutrition, other molecular functions, human diversity, or chance findings. To improve our understanding of any potential association, we recommend improved and standardised methodologies and reporting of raw data. Further high-quality research is required to shine a light on possible associations, which may yet yield important information.

Novel correlative analysis identifies multiple genomic variations impacting ASD with macrocephaly

Autism spectrum disorders (ASD) display both phenotypic and genetic heterogeneity, impeding the understanding of ASD and development of effective means of diagnosis and potential treatments. Genes affected by genomic variations for ASD converge in dozens of gene ontologies (GOs), but the relationship between the variations at the GO level have not been well elucidated. In the current study, multiple types of genomic variations were mapped to GOs and correlations among GOs were measured in ASD and control samples. Several ASD-unique GO correlations were found, suggesting the importance of co-occurrence of genomic variations in genes from different functional categories in ASD etiology. Combined with experimental data, several variations related to WNT signaling, neuron development, synapse morphology/function and organ morphogenesis were found to be important for ASD with macrocephaly, and novel co-occurrence patterns of them in ASD patients were found. Furthermore, we applied this gene ontology correlation analysis method to find genomic variations that contribute to ASD etiology in combination with changes in gene expression and transcription factor binding, providing novel insights into ASD with macrocephaly and a new methodology for the analysis of genomic variation.

Genome-Wide Analysis of Structural Variants in Parkinson Disease

OBJECTIVE

Identification of genetic risk factors for Parkinson disease (PD) has to date been primarily limited to the study of single nucleotide variants, which only represent a small fraction of the genetic variation in the human genome. Consequently, causal variants for most PD risk are not known. Here we focused on structural variants (SVs), which represent a major source of genetic variation in the human genome. We aimed to discover SVs associated with PD risk by performing the first large-scale characterization of SVs in PD.

METHODS

We leveraged a recently developed computational pipeline to detect and genotype SVs from 7,772 Illumina short-read whole genome sequencing samples. Using this set of SV variants, we performed a genome-wide association study using 2,585 cases and 2,779 controls and identified SVs associated with PD risk. Furthermore, to validate the presence of these variants, we generated a subset of matched whole-genome long-read sequencing data.

RESULTS

We genotyped and tested 3,154 common SVs, representing over 412 million nucleotides of previously uncatalogued genetic variation. Using long-read sequencing data, we validated the presence of three novel deletion SVs that are associated with risk of PD from our initial association analysis, including a 2 kb intronic deletion within the gene LRRN4.

INTERPRETATION

We identified three SVs associated with genetic risk of PD. This study represents the most comprehensive assessment of the contribution of SVs to the genetic risk of PD to date. ANN NEUROL 2023;93:1012-1022.

Chromosomal Instability in Genome Evolution: From Cancer to Macroevolution

The integrity of the genome is crucial for the survival of all living organisms. However, genomes need to adapt to survive certain pressures, and for this purpose use several mechanisms to diversify. Chromosomal instability (CIN) is one of the main mechanisms leading to the creation of genomic heterogeneity by altering the number of chromosomes and changing their structures. In this review, we will discuss the different chromosomal patterns and changes observed in speciation, in evolutional biology as well as during tumor progression. By nature, the human genome shows an induction of diversity during gametogenesis but as well during tumorigenesis that can conclude in drastic changes such as the whole genome doubling to more discrete changes as the complex chromosomal rearrangement chromothripsis. More importantly, changes observed during speciation are strikingly similar to the genomic evolution observed during tumor progression and resistance to therapy. The different origins of CIN will be treated as the importance of double-strand breaks (DSBs) or the consequences of micronuclei. We will also explain the mechanisms behind the controlled DSBs, and recombination of homologous chromosomes observed during meiosis, to explain how errors lead to similar patterns observed during tumorigenesis. Then, we will also list several diseases associated with CIN, resulting in fertility issues, miscarriage, rare genetic diseases, and cancer. Understanding better chromosomal instability as a whole is primordial for the understanding of mechanisms leading to tumor progression.

The non-coding genome in Autism Spectrum Disorders

Autism Spectrum Disorders (ASD) are a group of neurodevelopmental disorders (NDDs) characterized by difficulties in social interaction and communication, repetitive behavior, and restricted interests. While ASD have been proven to have a strong genetic component, current research largely focuses on coding regions of the genome. However, non-coding DNA, which makes up for ∼99% of the human genome, has recently been recognized as an important contributor to the high heritability of ASD, and novel sequencing technologies have been a milestone in opening up new directions for the study of the gene regulatory networks embedded within the non-coding regions. Here, we summarize current progress on the contribution of non-coding alterations to the pathogenesis of ASD and provide an overview of existing methods allowing for the study of their functional relevance, discussing potential ways of unraveling ASD's "missing heritability".

Whole Genome Analysis of Dizygotic Twins With Autism Reveals Prevalent Transposon Insertion Within Neuronal Regulatory Elements: Potential Implications for Disease Etiology and Clinical Assessment

Transposable elements (TEs) have been implicated in autism spectrum disorder (ASD). However, our understanding of their roles is far from complete. Herein, we explored de novo TE insertions (dnTEIs) and de novo variants (DNVs) across the genomes of dizygotic twins with ASD and their parents. The neuronal regulatory elements had a tendency to harbor dnTEIs that were shared between twins, but ASD-risk genes had dnTEIs that were unique to each twin. The dnTEIs were 4.6-fold enriched in enhancers that are active in embryonic stem cell (ESC)-neurons (p < 0.001), but DNVs were 1.5-fold enriched in active enhancers of astrocytes (p = 0.0051). Our findings suggest that dnTEIs and DNVs play a role in ASD etiology by disrupting enhancers of neurons and astrocytes.

Jasmine and Iris: population-scale structural variant comparison and analysis

The availability of long reads is revolutionizing studies of structural variants (SVs). However, because SVs vary across individuals and are discovered through imprecise read technologies and methods, they can be difficult to compare. Addressing this, we present Jasmine and Iris ( https://github.com/mkirsche/Jasmine/ ), for fast and accurate SV refinement, comparison and population analysis. Using an SV proximity graph, Jasmine outperforms six widely used comparison methods, including reducing the rate of Mendelian discordance in trio datasets by more than fivefold, and reveals a set of high-confidence de novo SVs confirmed by multiple technologies. We also present a unified callset of 122,813 SVs and 82,379 indels from 31 samples of diverse ancestry sequenced with long reads. We genotype these variants in 1,317 samples from the 1000 Genomes Project and the Genotype-Tissue Expression project with DNA and RNA-sequencing data and assess their widespread impact on gene expression, including within medically relevant genes.

Amniotes co-opt intrinsic genetic instability to protect germ-line genome integrity

Unlike PIWI-interacting RNA (piRNA) in other species that mostly target transposable elements (TEs), >80% of piRNAs in adult mammalian testes lack obvious targets. However, mammalian piRNA sequences and piRNA-producing loci evolve more rapidly than the rest of the genome for unknown reasons. Here, through comparative studies of chickens, ducks, mice, and humans, as well as long-read nanopore sequencing on diverse chicken breeds, we find that piRNA loci across amniotes experience: (1) a high local mutation rate of structural variations (SVs, mutations ≥ 50 bp in size); (2) positive selection to suppress young and actively mobilizing TEs commencing at the pachytene stage of meiosis during germ cell development; and (3) negative selection to purge deleterious SV hotspots. Our results indicate that genetic instability at pachytene piRNA loci, while producing certain pathogenic SVs, also protects genome integrity against TE mobilization by driving the formation of rapid-evolving piRNA sequences.

Role of the Paf1 complex in the maintenance of stem cell pluripotency and development

Cell identity is determined by the transcriptional regulation of a cell-type-specific gene group. The Paf1 complex (Paf1C), an RNA polymerase II-associating factor, is an important transcriptional regulator that not only participates in transcription elongation and termination but also affects transcription-coupled histone modifications and chromatin organisation. Recent studies have shown that Paf1C is involved in the expression of genes required for self-renewal and pluripotency in stem cells and tumorigenesis. In this review, we focused on the role of Paf1C as a critical transcriptional regulator in cell fate decisions. Paf1C affects the pluripotency of stem cells by regulating the expression of core transcription factors such as Oct4 and Nanog. In addition, Paf1C directly binds to the promoters or distant elements of target genes, thereby maintaining the pluripotency in embryonic stem cells derived from an early stage of the mammalian embryo. Paf1C is upregulated in cancer stem cells, as compared with that in cancer cells, suggesting that Paf1C may be a target for cancer therapy. Interestingly, Paf1C is involved in multiple developmental stages in Drosophila, zebrafish, mice and even humans, thereby displaying a trend for the correlation between Paf1C and cell fate. Thus, we propose that Paf1C is a critical contributor to cell differentiation, cell specification and its characteristics and could be employed as a therapeutic target in developmental diseases.

Combining multi-omics approaches to prioritize the variant-regulated functional long non-coding RNAs in autism spectrum disorder

OBJECTIVE

Rising evidence has indicated that long non-coding RNA (lncRNA) may play an essential role in the development of autism spectrum disorder (ASD). However, identifying the lncRNAs associated with ASD and the risk loci on them remains a major challenge. This study aims to identify potential causative variants and explore the related mechanisms.

METHODS

By leveraging differential expression analysis, WGCNA analysis and cis-expression quantitative analysis, our study mined functional SNPs with the regulated long non-coding RNA genes in brain tissues. We recruited 611 ASD children and 645 healthy children in the case-control study.

RESULTS

Total 68 different expressed lncRNAs were validated by calculating the brain tissue-specific expression using RNA-seq data. By the WGCNA method, 9 functional lncRNAs classified as e-lncRNA were found to interact with 976 ASD risk genes. Furthermore, we mined functional SNPs regulated long non-coding RNAs in brain tissues. We analyzed the association between candidate SNPs and ASD risks in Chinese children, which showed BDNF-AS rs1565228 allele G to C reduced the risk of ASD (OR = 0.81, 95%CI: 0.66-0.98). Further bioinformatics analysis showed that the variant rs1565228 C>G with the low binding affinity of transcription factor SRF caused the decreased expression of lncRNA BDNF-AS. Our study revealed that rs2295412 in the non-coding sequence of the lncRNA gene region was significantly associated with the risk of ASD.

DISCUSSION

These findings suggested that the SNPs in the non-coding region of lncRNA may play important roles in the genetic susceptibility of ASD, which may facilitate the early screening of ASD.

Evidence for parent-of-origin effects in autism spectrum disorder: a narrative review

Autism spectrum disorder (ASD) is a heterogeneous group of early-onset neurodevelopmental disorders known to be highly heritable with a complex genetic architecture. Abnormal brain developmental trajectories that impact synaptic functioning, excitation-inhibition balance and brain connectivity are now understood to play a central role in ASD. Ongoing efforts to identify the genetic underpinnings still prove challenging, in part due to phenotypic and genetic heterogeneity.This review focuses on parent-of-origin effects (POEs), where the phenotypic effect of an allele depends on its parental origin. POEs include genomic imprinting, transgenerational effects, mitochondrial DNA, sex chromosomes and mutational transmission bias. The motivation for investigating these mechanisms in ASD has been driven by their known impacts on early brain development and brain functioning, in particular for the most well-documented POE, genomic imprinting. Moreover, imprinting is implicated in syndromes such as Angelman and Prader-Willi, which frequently share comorbid symptoms with ASD. In addition to other regions in the genome, this comprehensive review highlights the 15q11-q13 and 7q chromosomal regions as well as the mitochondrial DNA as harbouring the majority of currently identified POEs in ASD.

Gut Microbiota Analysis and In Silico Biomarker Detection of Children with Autism Spectrum Disorder across Cohorts

The study of human gut microbiota has attracted increasing interest in the fields of life science and healthcare. However, the complicated and interconnected associations between gut microbiota and human diseases are still difficult to determine in a predictive fashion. Artificial intelligence such as machine learning (ML) and deep learning can assist in processing and interpreting biological datasets. In this study, we aggregated data from different studies based on the species composition and relative abundance of gut microbiota in children with autism spectrum disorder (ASD) and typically developed (TD) individuals and analyzed the commonalities and differences of ASD-associated microbiota across cohorts. We established a predictive model using an ML algorithm to explore the diagnostic value of the gut microbiome for the children with ASD and identify potential biomarkers for ASD diagnosis. The results indicated that the Shenzhen cohort achieved a higher area under the receiver operating characteristic curve (AUROC) value of 0.984 with 97% accuracy, while the Moscow cohort achieved an AUROC value of 0.81 with 67% accuracy. For the combination of the two cohorts, the average prediction results had an AUROC of 0.86 and 80% accuracy. The results of our cross-cohort analysis suggested that a variety of influencing factors, such as population characteristics, geographical region, and dietary habits, should be taken into consideration in microbial transplantation or dietary therapy. Collectively, our prediction strategy based on gut microbiota can serve as an enhanced strategy for the clinical diagnosis of ASD and assist in providing a more complete method to assess the risk of the disorder.

Inference of putative cell-type-specific imprinted regulatory elements and genes during human neuronal differentiation

Genomic imprinting results in gene expression bias caused by parental chromosome of origin and occurs in genes with important roles during human brain development. However, the cell-type and temporal specificity of imprinting during human neurogenesis is generally unknown. By detecting within-donor allelic biases in chromatin accessibility and gene expression that are unrelated to cross-donor genotype, we inferred imprinting in both primary human neural progenitor cells and their differentiated neuronal progeny from up to 85 donors. We identified 43/20 putatively imprinted regulatory elements (IREs) in neurons/progenitors, and 133/79 putatively imprinted genes in neurons/progenitors. Although 10 IREs and 42 genes were shared between neurons and progenitors, most putative imprinting was only detected within specific cell types. In addition to well-known imprinted genes and their promoters, we inferred novel putative IREs and imprinted genes. Consistent with both DNA methylation-based and H3K27me3-based regulation of imprinted expression, some putative IREs also overlapped with differentially methylated or histone-marked regions. Finally, we identified a progenitor-specific putatively imprinted gene overlapping with copy number variation that is associated with uniparental disomy-like phenotypes. Our results can therefore be useful in interpreting the function of variants identified in future parent-of-origin association studies.

Using coding and non-coding rare variants to target candidate genes in patients with severe tinnitus

Tinnitus is the phantom percept of an internal non-verbal set of noises and tones. It is reported by 15% of the population and it is usually associated with hearing and/or brain disorders. The role of structural variants (SVs) in coding and non-coding regions has not been investigated in patients with severe tinnitus. In this study, we performed whole-genome sequencing in 97 unrelated Swedish individuals with chronic tinnitus (TIGER cohort). Rare single nucleotide variants (SNV), large structural variants (LSV), and copy number variations (CNV) were retrieved to perform a gene enrichment analysis in TIGER and in a subgroup of patients with severe tinnitus (SEVTIN, n = 34), according to the tinnitus handicap inventory (THI) scores. An independent exome sequencing dataset of 147 Swedish tinnitus patients was used as a replication cohort (JAGUAR cohort) and population-specific datasets from Sweden (SweGen) and Non-Finish Europeans (NFE) from gnomAD were used as control groups. SEVTIN patients showed a higher prevalence of hyperacusis, hearing loss, and anxiety when they were compared to individuals in the TIGER cohort. We found an enrichment of rare missense variants in 6 and 8 high-constraint genes in SEVTIN and TIGER cohorts, respectively. Of note, an enrichment of missense variants was found in the CACNA1E gene in both SEVTIN and TIGER. We replicated the burden of missense variants in 9 high-constrained genes in the JAGUAR cohort, including the gene NAV2, when data were compared with NFE. Moreover, LSVs in constrained regions overlapping CACNA1E, NAV2, and TMEM132D genes were observed in TIGER and SEVTIN.

Genome-wide rare variant score associates with morphological subtypes of autism spectrum disorder

Defining different genetic subtypes of autism spectrum disorder (ASD) can enable the prediction of developmental outcomes. Based on minor physical and major congenital anomalies, we categorize 325 Canadian children with ASD into dysmorphic and nondysmorphic subgroups. We develop a method for calculating a patient-level, genome-wide rare variant score (GRVS) from whole-genome sequencing (WGS) data. GRVS is a sum of the number of variants in morphology-associated coding and non-coding regions, weighted by their effect sizes. Probands with dysmorphic ASD have a significantly higher GRVS compared to those with nondysmorphic ASD (P = 0.03). Using the polygenic transmission disequilibrium test, we observe an over-transmission of ASD-associated common variants in nondysmorphic ASD probands (P = 2.9 × 10^-3). These findings replicate using WGS data from 442 ASD probands with accompanying morphology data from the Simons Simplex Collection. Our results provide support for an alternative genomic classification of ASD subgroups using morphology data, which may inform intervention protocols.

Analyses of rare predisposing variants of lung cancer in 6,004 whole genomes in Chinese

We present the largest whole-genome sequencing (WGS) study of non-small cell lung cancer (NSCLC) to date among 6,004 individuals of Chinese ancestry, coupled with 23,049 individuals genotyped by SNP array. We construct a high-quality haplotype reference panel for imputation and identify 20 common and low-frequency loci (minor allele frequency [MAF] ≥ 0.5%), including five loci that have never been reported before. For rare loss-of-function (LoF) variants (MAF < 0.5%), we identify BRCA2 and 18 other cancer predisposition genes that affect 5.29% of individuals with NSCLC, and 98.91% (181 of 183) of LoF variants have not been linked previously to NSCLC risk. Promoter variants of BRCA2 also have a substantial effect on NSCLC risk, and their prevalence is comparable with BRCA2 LoF variants. The associations are validated in an independent case-control study including 4,410 individuals and a prospective cohort study including 23,826 individuals. Our findings not only provide a high-quality reference panel for future array-based association studies but depict the whole picture of rare pathogenic variants for NSCLC.

Evidence of transgenerational effects on autism spectrum disorder using multigenerational space-time cluster detection

Background

Transgenerational epigenetic risks associated with complex health outcomes, such as autism spectrum disorder (ASD), have attracted increasing attention. Transgenerational environmental risk exposures with potential for epigenetic effects can be effectively identified using space-time clustering. Specifically applied to ancestors of individuals with disease outcomes, space-time clustering characterized for vulnerable developmental stages of growth can provide a measure of relative risk for disease outcomes in descendants.

Objectives

(1) Identify space-time clusters of ancestors with a descendent with a clinical ASD diagnosis and matched controls. (2) Identify developmental windows of ancestors with the highest relative risk for ASD in descendants. (3) Identify how the relative risk may vary through the maternal or paternal line.

Methods

Family pedigrees linked to residential locations of ASD cases in Utah have been used to identify space-time clusters of ancestors. Control family pedigrees of none-cases based on age and sex have been matched to cases 2:1. The data have been categorized by maternal or paternal lineage at birth, childhood, and adolescence. A total of 3957 children, both parents, and maternal and paternal grandparents were identified. Bernoulli space-time binomial relative risk (RR) scan statistic was used to identify clusters. Monte Carlo simulation was used for statistical significance testing.

Results

Twenty statistically significant clusters were identified. Thirteen increased RR (> 1.0) space-time clusters were identified from the maternal and paternal lines at a p-value < 0.05. The paternal grandparents carry the greatest RR (2.86–2.96) during birth and childhood in the 1950’s–1960, which represent the smallest size clusters, and occur in urban areas. Additionally, seven statistically significant clusters with RR < 1 were relatively large in area, covering more rural areas of the state.

Conclusion

This study has identified statistically significant space-time clusters during critical developmental windows that are associated with ASD risk in descendants. The geographic space and time clusters family pedigrees with over 3 + generations, which we refer to as a person’s geographic legacy, is a powerful tool for studying transgenerational effects that may be epigenetic in nature. Our novel use of space-time clustering can be applied to any disease where family pedigree data is available.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12942-022-00313-4.

A phenotypic spectrum of autism is attributable to the combined effects of rare variants, polygenic risk and sex

The genetic etiology of autism spectrum disorder (ASD) is multifactorial, but how combinations of genetic factors determine risk is unclear. In a large family sample, we show that genetic loads of rare and polygenic risk are inversely correlated in cases and greater in females than in males, consistent with a liability threshold that differs by sex. De novo mutations (DNMs), rare inherited variants and polygenic scores were associated with various dimensions of symptom severity in children and parents. Parental age effects on risk for ASD in offspring were attributable to a combination of genetic mechanisms, including DNMs that accumulate in the paternal germline and inherited risk that influences behavior in parents. Genes implicated by rare variants were enriched in excitatory and inhibitory neurons compared with genes implicated by common variants. Our results suggest that a phenotypic spectrum of ASD is attributable to a spectrum of genetic factors that impact different neurodevelopmental processes.

Rare coding variation provides insight into the genetic architecture and phenotypic context of autism

Some individuals with autism spectrum disorder (ASD) carry functional mutations rarely observed in the general population. We explored the genes disrupted by these variants from joint analysis of protein-truncating variants (PTVs), missense variants and copy number variants (CNVs) in a cohort of 63,237 individuals. We discovered 72 genes associated with ASD at false discovery rate (FDR) ≤ 0.001 (185 at FDR ≤ 0.05). De novo PTVs, damaging missense variants and CNVs represented 57.5%, 21.1% and 8.44% of association evidence, while CNVs conferred greatest relative risk. Meta-analysis with cohorts ascertained for developmental delay (DD) (n = 91,605) yielded 373 genes associated with ASD/DD at FDR ≤ 0.001 (664 at FDR ≤ 0.05), some of which differed in relative frequency of mutation between ASD and DD cohorts. The DD-associated genes were enriched in transcriptomes of progenitor and immature neuronal cells, whereas genes showing stronger evidence in ASD were more enriched in maturing neurons and overlapped with schizophrenia-associated genes, emphasizing that these neuropsychiatric disorders may share common pathways to risk.

Rare variants and the oligogenic architecture of autism

Most large-scale genetic studies of autism have focused on the discovery of genes by proving an enrichment of de novo mutations (DNMs) in autism probands or characterizing polygenic risk based on the association of common variants. We present evidence in support of an oligogenic model where two or more ultrarare mutations of more modest effect are preferentially transmitted to children with autism. Such private gene-disruptive mutations are enriched in families where there are multiple affected individuals, emerged two or three generations ago, and map to genes not previously associated with autism. Although no single gene has reached statistical significance, this class of variation should be considered along with genetic and nongenetic factors to better explain the etiology of this complex trait.

Unbiased mosaic variant assessment in sperm: a cohort study to test predictability of transmission

Background:

De novo mutations underlie individually rare but collectively common pediatric congenital disorders. Some of these mutations can also be detected in tissues and from cells in a parent, where their abundance and tissue distribution can be measured. We previously reported that a subset of these mutations is detectable in sperm from the father, predicted to impact the health of offspring.

Methods:

As a cohort study, in three independent couples undergoing in vitro fertilization, we first identified male gonadal mosaicism through deep whole genome sequencing. We then confirmed variants and assessed their transmission to preimplantation blastocysts (32 total) through targeted ultra-deep genotyping.

Results:

Across 55 gonadal mosaic variants, 15 were transmitted to blastocysts for a total of 19 transmission events. This represented an overall predictable but slight undertransmission based upon the measured mutational abundance in sperm. We replicated this conclusion in an independent, previously published family-based cohort.

Conclusions:

Unbiased preimplantation genetic testing for gonadal mosaicism may represent a feasible approach to reduce the transmission of potentially harmful de novo mutations. This—in turn—could help to reduce their impact on miscarriages and pediatric disease.

Funding:

No external funding was received for this work.

Transcription Pause and Escape in Neurodevelopmental Disorders

Transcription pause-release is an important, highly regulated step in the control of gene expression. Modulated by various factors, it enables signal integration and fine-tuning of transcriptional responses. Mutations in regulators of pause-release have been identified in a range of neurodevelopmental disorders that have several common features affecting multiple organ systems. This review summarizes current knowledge on this novel subclass of disorders, including an overview of clinical features, mechanistic details, and insight into the relevant neurodevelopmental processes.

Massively parallel identification of functionally consequential noncoding genetic variants in undiagnosed rare disease patients

Clinical whole genome sequencing has enabled the discovery of potentially pathogenic noncoding variants in the genomes of rare disease patients with a prior history of negative genetic testing. However, interpreting the functional consequences of noncoding variants and distinguishing those that contribute to disease etiology remains a challenge. Here we address this challenge by experimentally profiling the functional consequences of rare noncoding variants detected in a cohort of undiagnosed rare disease patients at scale using a massively parallel reporter assay. We demonstrate that this approach successfully identifies rare noncoding variants that alter the regulatory capacity of genomic sequences. In addition, we describe an integrative analysis that utilizes genomic features alongside patient clinical data to further prioritize candidate variants with an increased likelihood of pathogenicity. This work represents an important step towards establishing a framework for the functional interpretation of clinically detected noncoding variants.

Heritability of social behavioral phenotypes and preliminary associations with autism spectrum disorder risk genes in rhesus macaques: A whole exome sequencing study

Nonhuman primates and especially rhesus macaques (Macaca mulatta) have been indispensable animal models for studies of various aspects of neurobiology, developmental psychology, and other aspects of neuroscience. While remarkable progress has been made in our understanding of influences on atypical human social behavior, such as that observed in autism spectrum disorders (ASD), many significant questions remain. Improved understanding of the relationships among variation in specific genes and variation in expressed social behavior in a nonhuman primate would benefit efforts to investigate risk factors, developmental mechanisms, and potential therapies for behavioral disorders including ASD. To study genetic influences on key aspects of social behavior and interactions-individual competence and/or motivation for specific aspects of social behavior-we quantified individual variation in social interactions among juvenile rhesus macaques using both a standard macaque ethogram and a macaque-relevant modification of the human Social Responsiveness Scale. Our analyses demonstrate that various aspects of juvenile social behavior exhibit significant genetic heritability, with estimated quantitative genetic effects similar to that described for ASD in human children. We also performed exome sequencing and analyzed variants in 143 genes previously suggested to influence risk for human ASD. We find preliminary evidence for genetic association between specific variants and both individual behaviors and multi-behavioral factor scores. To our knowledge, this is the first demonstration that spontaneous social behaviors performed by free-ranging juvenile rhesus macaques display significant genetic heritability and then to use exome sequencing data to examine potential macaque genetic associations in genes associated with human ASD.

GCAT|Panel, a comprehensive structural variant haplotype map of the Iberian population from high-coverage whole-genome sequencing

The combined analysis of haplotype panels with phenotype clinical cohorts is a common approach to explore the genetic architecture of human diseases. However, genetic studies are mainly based on single nucleotide variants (SNVs) and small insertions and deletions (indels). Here, we contribute to fill this gap by generating a dense haplotype map focused on the identification, characterization, and phasing of structural variants (SVs). By integrating multiple variant identification methods and Logistic Regression Models (LRMs), we present a catalogue of 35 431 441 variants, including 89 178 SVs (≥50 bp), 30 325 064 SNVs and 5 017 199 indels, across 785 Illumina high coverage (30x) whole-genomes from the Iberian GCAT Cohort, containing a median of 3.52M SNVs, 606 336 indels and 6393 SVs per individual. The haplotype panel is able to impute up to 14 360 728 SNVs/indels and 23 179 SVs, showing a 2.7-fold increase for SVs compared with available genetic variation panels. The value of this panel for SVs analysis is shown through an imputed rare Alu element located in a new locus associated with Mononeuritis of lower limb, a rare neuromuscular disease. This study represents the first deep characterization of genetic variation within the Iberian population and the first operational haplotype panel to systematically include the SVs into genome-wide genetic studies.

Mutations in trpγ, the homologue of TRPC6 autism candidate gene, causes autism-like behavioral deficits in Drosophila

Autism Spectrum Disorder (ASD) is characterized by impaired social communication, restricted interests, and repetitive and stereotyped behaviors. The TRPC6 (transient receptor potential channel 6) represents an ASD candidate gene under an oligogenic/multifactorial model based on the initial description and cellular characterization of an individual with ASD bearing a de novo heterozygous mutation disrupting TRPC6, together with the enrichment of disruptive TRPC6 variants in ASD cases as compared to controls. Here, we perform a clinical re-evaluation of the initial non-verbal patient, and also present eight newly reported individuals ascertained for ASD and bearing predicted loss-of-function mutations in TRPC6. In order to understand the consequences of mutations in TRPC6 on nervous system function, we used the fruit fly, Drosophila melanogaster, to show that null mutations in transient receptor gamma (trpγ; the fly gene most similar to TRPC6), cause a number of behavioral defects that mirror features seen in ASD patients, including deficits in social interactions (based on courtship behavior), impaired sleep homeostasis (without affecting the circadian control of sleep), hyperactivity in both young and old flies, and defects in learning and memory. Some defects, most notably in sleep, differed in severity between males and females and became normal with age. Interestingly, hyperforin, a TRPC6 agonist and the primary active component of the St. John's wort antidepressant, attenuated many of the deficits expressed by trpγ mutant flies. In summary, our results provide further evidence that the TRPC6 gene is a risk factor for ASD. In addition, they show that the behavioral defects caused by mutations in TRPC6 can be modeled in Drosophila, thereby establishing a paradigm to examine the impact of mutations in other candidate genes.