De novo mutations (DNMs) in protein-coding genes are a well-established cause of developmental disorders (DD). However, known DD-associated genes only account for a minority of the observed excess of such DNMs. To identify novel DD-associated genes, we integrated healthcare and research exome sequences on 31,058 DD parent-offspring trios, and developed a simulation-based statistical test to identify gene-specific enrichments of DNMs. We identified 285 significantly DD-associated genes, including 28 not previously robustly associated with DDs. Despite detecting more DD-associated genes than in any previous study, much of the excess of DNMs of protein-coding genes remains unaccounted for. Modelling suggests that over 1,000 novel DD-associated genes await discovery, many of which are likely to be less penetrant than the currently known genes. Research access to clinical diagnostic datasets will be critical for completing the map of dominant DDs.

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CNOT1 is a member of the CCR4-NOT complex, which is a master regulator, orchestrating gene expression, RNA deadenylation, and protein ubiquitination. We report on 39 individuals with heterozygous de novo CNOT1 variants, including missense, splice site, and nonsense variants, who present with a clinical spectrum of intellectual disability, motor delay, speech delay, seizures, hypotonia, and behavioral problems. To link CNOT1 dysfunction to the neurodevelopmental phenotype observed, we generated variant-specific Drosophila models, which showed learning and memory defects upon CNOT1 knockdown. Introduction of human wild-type CNOT1 was able to rescue this phenotype, whereas mutants could not or only partially, supporting our hypothesis that CNOT1 impairment results in neurodevelopmental delay. Furthermore, the genetic interaction with autism-spectrum genes, such as ASH1L, DYRK1A, MED13, and SHANK3, was impaired in our Drosophila models. Molecular characterization of CNOT1 variants revealed normal CNOT1 expression levels, with both mutant and wild-type alleles expressed at similar levels. Analysis of protein-protein interactions with other members indicated that the CCR4-NOT complex remained intact. An integrated omics approach of patient-derived genomics and transcriptomics data suggested only minimal effects on endonucleolytic nonsense-mediated mRNA decay components, suggesting that de novo CNOT1 variants are likely haploinsufficient hypomorph or neomorph, rather than dominant negative. In summary, we provide strong evidence that de novo CNOT1 variants cause neurodevelopmental delay with a wide range of additional co-morbidities. Whereas the underlying pathophysiological mechanism warrants further analysis, our data demonstrate an essential and central role of the CCR4-NOT complex in human brain development.Master regulators controlling development include, but are not limited to, paired box (PAX) proteins, 1 SRY-related HMG-box (SOX) proteins, 2 and the relatively unknown CCR4-NOT protein complex. 3 Although the full spectrum of functional diversity for the CCR4-NOT complex has not yet been established, it has already become apparent that it is active on all levels of gene expression, from accessibility of the DNA to translation and degradation of mRNA. 4

Deletion 1p36 (del1p36) syndrome is the most common human disorder resulting from a terminal autosomal deletion. This condition is molecularly and clinically heterogeneous. Deletions involving two non-overlapping regions, known as the distal (telomeric) and proximal (centromeric) critical regions, are sufficient to cause the majority of the recurrent clinical features, although with different facial features and dysmorphisms. SPEN encodes a transcriptional repressor commonly deleted in proximal del1p36 syndrome and is located centromeric to the proximal 1p36 critical region. Here, we used clinical data from 34 individuals with truncating variants in SPEN to define a neurodevelopmental disorder presenting with features that overlap considerably with those of proximal del1p36 syndrome. The clinical profile of this disease includes developmental delay/intellectual disability, autism spectrum disorder, anxiety, aggressive behavior, attention deficit disorder, hypotonia, brain and spine anomalies, congenital heart defects, high/narrow palate, facial dysmorphisms, and obesity/increased BMI, especially in females. SPEN also emerges as a relevant gene for del1p36 syndrome by co-expression analyses. Finally, we show that haploinsufficiency of SPEN is associated with a distinctive DNA methylation episignature of the X chromosome in affected females, providing further evidence of a specific contribution of the protein to the epigenetic control of this chromosome, and a paradigm of an X chromosome-specific episignature that classifies syndromic traits. We conclude that SPEN is required for multiple developmental processes and SPEN haploinsufficiency is a major contributor to a disorder associated with deletions centromeric to the previously established 1p36 critical regions.Neurodevelopmental disorders (NDDs) and intellectual disability (ID) affect approximately 1%-3% of the general population. 1-3 NDDs/ID are largely genetically determined, but identification of the underlying molecular causes has been hampered by clinical and genetic heterogeneity. During the last decades, the use of high-resolution array-based copy number variant (CNV) analysis and second-generation sequencing techniques has improved our knowledge of the genetic basis of both syndromic and non-syndromic NDDs/ID. [2][3][4] Notwithstanding these achievements, the genetic basis of NDDs/ID is still unsolved in a large proportion of affected individuals.Deletion 1p36 (del1p36) syndrome, first described by Shapira and colleagues in 1997, 5 is the most common autosomal terminal deletion syndrome in humans, occurring in about 1 in 5,000 births. [6][7][8] This disorder is characterized by developmental delay (DD)/ID, behavioral abnormalities, hypotonia, seizures, brain anomalies, vision problems, hearing loss, orofacial clefting, congenital heart defects (CHDs), cardiomyopathy, renal anomalies, short

Whereas large-scale statistical analyses can robustly identify disease-gene relationships, they do not accurately capture genotype-phenotype correlations or disease mechanisms. We use multiple lines of independent evidence to show that different variant types in a single gene, SATB1, cause clinically overlapping but distinct neurodevelopmental disorders. Clinical evaluation of 42 individuals carrying SATB1 variants identified overt genotype-phenotype relationships, associated with different pathophysiological mechanisms, established by functional assays. Missense variants in the CUT1 and CUT2 DNA-binding domains result in stronger chromatin binding, increased transcriptional repression and a severe phenotype. Contrastingly, variants predicted to result in haploinsufficiency are associated with a milder clinical presentation. A similarly mild phenotype is observed for individuals with premature protein truncating variants that escape nonsense-mediated decay and encode truncated proteins, which are transcriptionally active but mislocalized in the cell. Our results suggest that in-depth mutation-specific genotype-phenotype studies are essential to capture full disease complexity and to explain phenotypic variability. 3. CC-BY 4.0 International license perpetuity. It is made available under a preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in

For the first time in Europe hundreds of rare disease (RD) experts team up to actively share and jointly analyse existing patient’s data. Solve-RD is a Horizon 2020-supported EU flagship project bringing together >300 clinicians, scientists, and patient representatives of 51 sites from 15 countries. Solve-RD is built upon a core group of four European Reference Networks (ERNs; ERN-ITHACA, ERN-RND, ERN-Euro NMD, ERN-GENTURIS) which annually see more than 270,000 RD patients with respective pathologies. The main ambition is to solve unsolved rare diseases for which a molecular cause is not yet known. This is achieved through an innovative clinical research environment that introduces novel ways to organise expertise and data. Two major approaches are being pursued (i) massive data re-analysis of >19,000 unsolved rare disease patients and (ii) novel combined -omics approaches. The minimum requirement to be eligible for the analysis activities is an inconclusive exome that can be shared with controlled access. The first preliminary data re-analysis has already diagnosed 255 cases form 8393 exomes/genome datasets. This unprecedented degree of collaboration focused on sharing of data and expertise shall identify many new disease genes and enable diagnosis of many so far undiagnosed patients from all over Europe.

Reanalysis of inconclusive exome/genome sequencing data increases the diagnosis yield of patients with rare diseases. However, the cost and efforts required for reanalysis prevent its routine implementation in research and clinical environments. The Solve-RD project aims to reveal the molecular causes underlying undiagnosed rare diseases. One of the goals is to implement innovative approaches to reanalyse the exomes and genomes from thousands of well-studied undiagnosed cases. The raw genomic data is submitted to Solve-RD through the RD-Connect Genome-Phenome Analysis Platform (GPAP) together with standardised phenotypic and pedigree data. We have developed a programmatic workflow to reanalyse genome-phenome data. It uses the RD-Connect GPAP’s Application Programming Interface (API) and relies on the big-data technologies upon which the system is built. We have applied the workflow to prioritise rare known pathogenic variants from 4411 undiagnosed cases. The queries returned an average of 1.45 variants per case, which first were evaluated in bulk by a panel of disease experts and afterwards specifically by the submitter of each case. A total of 120 index cases (21.2% of prioritised cases, 2.7% of all exome/genome-negative samples) have already been solved, with others being under investigation. The implementation of solutions as the one described here provide the technical framework to enable periodic case-level data re-evaluation in clinical settings, as recommended by the American College of Medical Genetics.

SummaryDe novo mutations (DNMs) in protein-coding genes are a well-established cause of developmental disorders (DD). However, known DD-associated genes only account for a minority of the observed excess of such DNMs. To identify novel DD-associated genes, we integrated healthcare and research exome sequences on 31,058 DD parent-offspring trios, and developed a simulation-based statistical test to identify gene-specific enrichments of DNMs. We identified 299 significantly DD-associated genes, including 49 not previously robustly associated with DDs. Despite detecting more DD-associated genes than in any previous study, much of the excess of DNMs of protein-coding genes remains unaccounted for. Modelling suggests that over 500 novel DD-associated genes await discovery, many of which are likely to be less penetrant than the currently known genes. Research access to clinical diagnostic datasets will be critical for completing the map of dominant DDs.