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Recent work has revealed an important role for rare, incompletely penetrant inherited coding variants in neurodevelopmental disorders (NDDs). Additionally, we have previously shown that common variants contribute to risk for rare NDDs. Here, we investigate whether common variants exert their effects by modifying gene expression, using multi-cis-expression quantitative trait loci (cis-eQTL) prediction models. We first performed a transcriptome-wide association study for NDDs using 6,987 probands from the Deciphering Developmental Disorders (DDD) study and 9,720 controls, and found one gene,RAB2A, that passed multiple testing correction (p = 6.7×10−7). We then investigated whethercis-eQTLs modify the penetrance of putatively damaging, rare coding variants inherited by NDD probands from their unaffected parents in a set of 1,700 trios. We found no evidence that unaffected parents transmitting putatively damaging coding variants had higher genetically-predicted expression of the variant-harboring gene than their child. In probands carrying putatively damaging variants in constrained genes, the genetically-predicted expression of these genes in blood was lower than in controls (p = 2.7×10−3). However, results for proband-control comparisons were inconsistent across different sets of genes, variant filters and tissues. We find limited evidence that commoncis-eQTLs modify penetrance of rare coding variants in a large cohort of NDD probands.

Sleep apnea is a common disorder that represents a global public health burden. KCNK3 encodes TASK-1, a K+ channel implicated in the control of breathing, but its link with sleep apnea remains poorly understood. Here we describe a new developmental disorder with associated sleep apnea (developmental delay with sleep apnea, or DDSA) caused by rare de novo gain-of-function mutations in KCNK3. The mutations cluster around the ‘X-gate’, a gating motif that controls channel opening, and produce overactive channels that no longer respond to inhibition by G-protein-coupled receptor pathways. However, despite their defective X-gating, these mutant channels can still be inhibited by a range of known TASK channel inhibitors. These results not only highlight an important new role for TASK-1 K+ channels and their link with sleep apnea but also identify possible therapeutic strategies.

OBJECTIVE To determine the incremental yield of exome sequencing (ES) over chromosomal microarray analysis (CMA) or karyotyping in prenatally diagnosed non-immune hydrops fetalis (NIHF). METHODS A prospective cohort study (comprising an extended group of the Prenatal Assessment of Genomes and Exomes (PAGE) study) was performed which included 28 cases of prenatally diagnosed NIHF undergoing trio ES following negative CMA or karyotyping. These cases were combined with data from a systematic review of the literature. MEDLINE, EMBASE, CINAHL and ClinicalTrials.gov databases were searched electronically (January 2000 to October 2020) for studies reporting on the incremental yield of ES over CMA or karyotyping in fetuses with prenatally detected NIHF. Inclusion criteria for the systematic review were: (i) at least two cases of NIHF undergoing sequencing; (ii) testing initiated based on prenatal ultrasound-based phenotype; and (iii) negative CMA or karyotyping result. The incremental diagnostic yield of ES was assessed in: (i) all cases of NIHF; (ii) isolated NIHF; (iii) NIHF associated with an additional fetal structural anomaly; and (iv) NIHF according to severity (i.e. two vs three or more cavities affected). RESULTS In the extended PAGE study cohort, the additional diagnostic yield of ES over CMA or karyotyping was 25.0% (7/28) in all NIHF cases, 21.4% (3/14) in those with isolated NIHF and 28.6% (4/14) in those with non-isolated NIHF. In the meta-analysis, the pooled incremental yield based on 21 studies (306 cases) was 29% (95% CI, 24-34%; P

OBJECTIVE To evaluate the utility of prenatal exome sequencing (ES) for isolated increased nuchal translucency (NT) and to investigate factors that increase diagnostic yield. DESIGN Retrospective analysis of data from two prospective cohort studies. SETTING Fetal medicine centres in the UK and USA. POPULATION Fetuses with increased NT ≥3.5 mm at 11-14 weeks of gestation recruited to the Prenatal Assessment of Genomes and Exomes (PAGE) and Columbia fetal whole exome sequencing studies (n = 213). METHODS We grouped cases based on (1) the presence of additional structural abnormalities at presentation in the first trimester or later in pregnancy, and (2) NT measurement at presentation. We compared diagnostic rates between groups using Fisher exact test. MAIN OUTCOME MEASURES Detection of diagnostic genetic variants considered to have caused the observed fetal structural anomaly. RESULTS Diagnostic variants were detected in 12 (22.2%) of 54 fetuses presenting with non-isolated increased NT, 12 (32.4%) of 37 fetuses with isolated increased NT in the first trimester and additional abnormalities later in pregnancy, and 2 (1.8%) of 111 fetuses with isolated increased NT in the first trimester and no other abnormalities on subsequent scans. Diagnostic rate also increased with increasing size of NT. CONCLUSIONS The diagnostic yield of prenatal ES is low for fetuses with isolated increased NT but significantly higher where there are additional structural anomalies. Prenatal ES may not be appropriate for truly isolated increased NT but timely, careful ultrasound scanning to identify other anomalies emerging later can direct testing to focus where there is a higher likelihood of diagnosis.

Efficient and effective methods for converting human induced pluripotent stem cells (iPSC) into differentiated derivatives are critical for performing robust, large-scale studies of development and disease modelling, and for providing a source of cells for regenerative medicine. Here, we describe a 14-day neural differentiation protocol which allows for the scalable, simultaneous differentiation of multiple iPSC lines into cortical neural stem cells (NSCs). We currently employ this protocol to differentiate and compare sets of engineered iPSC lines carrying loss of function alleles in developmental disorder associated genes, alongside isogenic wildtype controls. Using RNA sequencing (RNA-Seq), we can examine the changes in gene expression brought about by each disease gene knockout, to determine its impact on neural development and explore mechanisms of disease. The 10-day Neural Induction period uses the well established dual-SMAD inhibition approach combined with Wnt/β-Catenin inhibition to selectively induce formation of cortical NSCs. This is followed by a 4-day Neural Maintenance period facilitating NSC expansion and rosette formation, and NSC cryopreservation. We also describe methods for thawing and passaging the cryopreserved NSCs, which are useful in confirming their viability for further culture. Routine implementation of ICC Quality Control confirms the presence of PAX6-positive and/or FOXG1-positive NSCs and the absence of OCT4-positive iPSCs after differentiation. RNA-Seq, flow cytometry, immunocytochemistry (ICC) and RT-qPCR provide additional confirmation of robust presence of NSC markers in the differentiated cells. The broader utility and application of our protocol is demonstrated by the successful differentiation of wildtype iPSC lines from five additional independent donors. This paper thereby describes an efficient method for the production of large numbers of high purity cortical NSCs, which are widely applicable for downstream research into developmental mechanisms, further differentiation into postmitotic cortical neurons, or other applications such as large-scale drug screening experiments.

BackgroundPediatric disorders include a range of highly genetically heterogeneous conditions that are amenable to genome-wide diagnostic approaches. Finding a molecular diagnosis is challenging but can have profound lifelong benefits.MethodsThe Deciphering Developmental Disorders (DDD) study recruited >33,500 individuals from families with severe, likely monogenic developmental disorders from 24 regional genetics services around the UK and Ireland. We collected detailed standardised phenotype data and performed whole-exome sequencing and microarray analysis to investigate novel genetic causes. We developed an augmented variant analysis and re-analysis pipeline to maximise sensitivity and specificity, and communicated candidate variants to clinical teams for validation and diagnostic interpretation. We performed multiple regression analyses to evaluate factors affecting the probability of being diagnosed.ResultsWe reported approximately one candidate variant per parent-offspring trio and 2.5 variants per singleton proband, including both sequence and structural variants. Using clinical and computational approaches to variant classification, we have achieved a diagnosis in at least 34% (4507 probands), of whom 67% have a pathogenicde novomutation. Being recruited as a parent-offspring trio had the largest impact on the chance of being diagnosed (OR=4.70). Probands who were extremely premature (OR=0.39), hadin uteroexposure to antiepileptic medications (OR=0.44), or whose mothers had diabetes (OR=0.52) were less likely to be diagnosed, as were those of African ancestry (OR=0.51).ConclusionsOptimising diagnosis and discovery in highly penetrant genomic disease depends upon ongoing and novel scientific analyses, ethical recruitment and feedback policies, and collaborative clinical-research partnerships.

KPTN-related disorder (KRD) is an autosomal recessive disorder associated with germline variants in KPTN (kaptin), a component of the mTOR regulatory complex KICSTOR. To gain further insights into the pathogenesis of KRD, we analysed mouse knockout and human stem cell KPTN loss-of-function models. Kptn−/− mice display many of the key KRD phenotypes, including brain overgrowth, behavioural abnormalities, and cognitive deficits. Assessment of affected individuals has identified concordant selectivity of cognitive deficits, postnatal onset of brain overgrowth, and a previously unrecognised KPTN dosage-sensitivity, resulting in increased head circumference in their heterozygous parents. Molecular and structural analysis of Kptn−/− mice revealed pathological changes, including differences in brain size, shape, and cell numbers primarily due to abnormal postnatal brain development. Both the mouse and differentiated iPSC models of the disorder display transcriptional and biochemical evidence for altered mTOR pathway signalling, supporting the role of KPTN in regulating mTORC1. Increased mTOR signalling downstream of KPTN is rapamycin sensitive, highlighting possible therapeutic avenues with currently available mTOR inhibitors. These findings place KRD in the broader group of mTORC1 related disorders affecting brain structure, cognitive function, and network integrity.

SummarySynonymous mutations change the DNA sequence of a gene without affecting the amino acid sequence of the encoded protein. Although emerging evidence suggests that synonymous mutations can impact RNA splicing, translational efficiency, and mRNA stability1, studies in human genetics, mutagenesis screens, and other experiments and evolutionary analyses have repeatedly shown that most synonymous variants are neutral or only weakly deleterious, with some notable exceptions. In their recent article, Shen et al. claim to have disproved these well-established findings. They perform mutagenesis experiments in yeast and conclude that synonymous mutations frequently reduce fitness to the same extent as nonsynonymous mutations2. Based on their findings, the authors state that their results “imply that synonymous mutations are nearly as important as nonsynonymous mutations in causing disease.” An accompanying News and Views argues that “revising our expectations about synonymous mutations should expand our view of the genetic underpinnings of human health”3. Considering potential technical concerns with these experiments4 and a large, coherent body of knowledge establishing the predominant neutrality of synonymous variants, we caution against interpreting this study in the context of human disease.

Introduction: The objective was to evaluate: (i) the proportion of prenatally diagnosed congenital heart disease (CHD) associated with an abnormal quantitative fluorescence-PCR (QF-PCR), chromosome microarray (CMA), and exome sequencing (ES) result; and (ii) the diagnostic yield of these technologies based on CHD category and presence of extra-cardiac anomalies (ECAs). Methods: This prospective cohort study was set across 12 UK foetal medicine centres. All cases underwent QF-PCR, CMA, and ES, and the diagnostic yield in n = 147 cases of prenatally diagnosed CHD was assessed. Results: In 34.7% (n = 51/147), a genetic diagnosis was obtained. Using a stepwise testing strategy, the diagnostic yield for QF-PCR, CMA, and ES was 15.6% (n = 23/147), 13.7% (n = 17/124), and 10.2% (n = 11/107), respectively. Abnormal QF-PCR/shunt (septal) defects 31.4% (n = 11/35), p = 0.046, and abnormal CMA/conotruncal anomalies 22.7% (n = 10/44), p = 0.04, had significant associations. Monogenic variants were commonest in complex CHD 36.4% (n = 4/11). Multisystem CHD had a greater diagnostic yield overall compared to isolated OR 2.41 (95% CI, 1.1–5.1), particularly in association with brain and gastrointestinal tract anomalies. The proportion of variants of uncertain significance was 4.7% (n = 5/107) with ES, with none in the CMA group. Conclusion: In the era of prenatal ES, there remains an important role for QF-PCR and CMA. Identification of monogenic pathologic variants further allows delineation of prognosis in CHD.

OBJECTIVE To determine the incremental yield of antenatal exome sequencing (ES) over chromosomal microarray analysis (CMA) or conventional karyotyping in prenatally diagnosed congenital heart disease (CHD). METHODS A prospective cohort study of 197 trios undergoing ES following CMA or karyotyping owing to CHD identified prenatally and a systematic review of the literature were performed. MEDLINE, EMBASE, CINAHL and ClinicalTrials.gov (January 2000 to October 2019) databases were searched electronically for studies reporting on the diagnostic yield of ES in prenatally diagnosed CHD. Selected studies included those with more than three cases, with initiation of testing based upon prenatal phenotype only and that included cases in which CMA or karyotyping was negative. The incremental diagnostic yield of ES was assessed in: (1) all cases of CHD; (2) isolated CHD; (3) CHD associated with extracardiac anomaly (ECA); and (4) CHD according to phenotypic subgroup. RESULTS In our cohort, ES had an additional diagnostic yield in all CHD, isolated CHD and CHD associated with ECA of 12.7% (25/197), 11.5% (14/122) and 14.7% (11/75), respectively (P = 0.81). The corresponding pooled incremental yields from 18 studies (encompassing 636 CHD cases) included in the systematic review were 21% (95% CI, 15-27%), 11% (95% CI, 7-15%) and 37% (95% CI, 18-56%), respectively. The results did not differ significantly when subanalysis was limited to studies including more than 20 cases, except for CHD associated with ECA, in which the incremental yield was greater (49% (95% CI, 17-80%)). In cases of CHD associated with ECA in the primary analysis, the most common extracardiac anomalies associated with a pathogenic variant were those affecting the genitourinary system (23/52 (44.2%)). The greatest incremental yield was in cardiac shunt lesions (41% (95% CI, 19-63%)), followed by right-sided lesions (26% (95% CI, 9-43%)). In the majority (68/96 (70.8%)) of instances, pathogenic variants occurred de novo and in autosomal dominant (monoallelic) disease genes. The most common (19/96 (19.8%)) monogenic syndrome identified was Kabuki syndrome. CONCLUSIONS There is an apparent incremental yield of prenatal ES in CHD. While the greatest yield is in CHD associated with ECA, consideration could also be given to performing ES in the presence of an isolated cardiac abnormality. A policy of routine application of ES would require the adoption of robust bioinformatic, clinical and ethical pathways. Copyright © 2020 ISUOG. Published by John Wiley & Sons Ltd.

SummaryDiagnosing rare developmental disorders using genome-wide sequencing data commonly necessitates review of multiple plausible candidate variants, often using ontologies of categorical clinical terms. We show that Integrating Multiple Phenotype Resources Optimises Variant Evaluation in Developmental Disorders (IMPROVE-DD) by incorporating additional classes of data commonly available to clinicians and recorded in health records. In doing so, we quantify the distinct contributions of gender, growth, and development in addition to Human Phenotype Ontology (HPO) terms, and demonstrate added value from these readily-available information sources. We use likelihood ratios for nominal and quantitative data and propose a novel classifier for HPO terms in this framework. This Bayesian framework results in more robust diagnoses. Using data systematically collected in the DDD study, we considered 77 genes with pathogenic/likely pathogenic variants in >10 probands. All genes showed at least a satisfactory prediction by ROC when testing on training data (AUC≥0.6), and HPO terms were the best individual predictor for the majority of genes, though a minority (13/77) of genes were better predicted by other phenotypic data types. Overall, classifiers based upon multiple integrated phenotypic data sources performed better than those based upon any individual source, and importantly, integrated models produced notably fewer false positives. Finally, we show that IMPROVE-DD models with good predictive performance on cross-validation can be constructed from relatively few cases. This suggests new strategies for candidate gene prioritisation, and highlights the value of systematic clinical data collection to support diagnostic programmes.

PurposeStructural mosaicism has been previously implicated in developmental disorders. We aim to identify rare mosaic chromosomal alterations (MCAs) in probands with severe undiagnosed developmental disorders.MethodsWe identified MCAs in SNP array data from 12,530 probands in the Deciphering Developmental Disorders (DDD) study using MoChA.ResultsWe found 61 MCAs in 57 probands, many of these were tissue specific. In 23/26 (88.5%) cases for which the MCA was detected in saliva where blood was also available for analysis, the MCA could not be detected in blood. The MCAs included 20 polysomies, comprising either one arm of a chromosome or a whole chromosome, for which we were able to show the timing of the error (25% mitosis, 40% meiosis I, 35% meiosis II). Only 2/57 (3.5%) of the probands in whom we found MCAs had another likely genetic diagnosis identified by whole exome sequencing, despite an overall diagnostic yield of ∼40% across the cohort.ConclusionOur results show that identification of MCAs provides candidate diagnoses for previously undiagnosed patients with developmental disorders, potentially explaining ∼0.45% of cases in the DDD study. Nearly 90% of these MCAs would have remained undetected by analysing DNA from blood and no other tissue.

Purpose Automated variant filtering is an essential part of diagnostic genome-wide sequencing but may generate false negative results. We sought to investigate whether some previously identified pathogenic variants may be being routinely excluded by standard variant filtering pipelines. Methods We evaluated variants that were previously classified as pathogenic or likely pathogenic in ClinVar in known developmental disorder genes using exome sequence data from the Deciphering Developmental Disorders (DDD) study. Results Of these ClinVar pathogenic variants, 3.6% were identified among 13,462 DDD probands, and 1134/1352 (83.9%) had already been independently communicated to clinicians using DDD variant filtering pipelines as plausibly pathogenic. The remaining 218 variants failed consequence, inheritance, or other automated variant filters. Following clinical review of these additional variants, we were able to identify 112 variants in 107 (0.8%) DDD probands as potential diagnoses. Conclusion Lower minor allele frequency (1 star) are good predictors of a previously identified variant being plausibly diagnostic for developmental disorders. However, around half of previously identified pathogenic variants excluded by automated variant filtering did not appear to be disease-causing, underlining the continued need for clinical evaluation of candidate variants as part of the diagnostic process.

Funder: European Molecular Biology Laboratory; Id: http://dx.doi.org/10.13039/100013060, DECIPHER (https://www.deciphergenomics.org) is a free web platform for sharing anonymized phenotype-linked variant data from rare disease patients. Its dynamic interpretation interfaces contextualize genomic and phenotypic data to enable more informed variant interpretation, incorporating international standards for variant classification. DECIPHER supports almost all types of germline and mosaic variation in the nuclear and mitochondrial genome: sequence variants, short tandem repeats, copy-number variants, and large structural variants. Patient phenotypes are deposited using Human Phenotype Ontology (HPO) terms, supplemented by quantitative data, which is aggregated to derive gene-specific phenotypic summaries. It hosts data from >250 projects from ~40 countries, openly sharing >40,000 patient records containing >51,000 variants and >172,000 phenotype terms. The rich phenotype-linked variant data in DECIPHER drives rare disease research and diagnosis by enabling patient matching within DECIPHER and with other resources, and has been cited in >2,600 publications. In this study, we describe the types of data deposited to DECIPHER, the variant interpretation tools, and patient matching interfaces which make DECIPHER an invaluable rare disease resource.

Structural variation (SV) describes a broad class of genetic variation greater than 50 bp in size. SVs can cause a wide range of genetic diseases and are prevalent in rare developmental disorders (DDs). Individuals presenting with DDs are often referred for diagnostic testing with chromosomal microarrays (CMAs) to identify large copy-number variants (CNVs) and/or with single-gene, gene-panel, or exome sequencing (ES) to identify single-nucleotide variants, small insertions/deletions, and CNVs. However, individuals with pathogenic SVs undetectable by conventional analysis often remain undiagnosed. Consequently, we have developed the tool InDelible, which interrogates short-read sequencing data for split-read clusters characteristic of SV breakpoints. We applied InDelible to 13,438 probands with severe DDs recruited as part of the Deciphering Developmental Disorders (DDD) study and discovered 63 rare, damaging variants in genes previously associated with DDs missed by standard SNV, indel, or CNV discovery approaches. Clinical review of these 63 variants determined that about half (30/63) were plausibly pathogenic. InDelible was particularly effective at ascertaining variants between 21 and 500 bp in size and increased the total number of potentially pathogenic variants identified by DDD in this size range by 42.9%. Of particular interest were seven confirmed de novo variants in MECP2, which represent 35.0% of all de novo protein-truncating variants in MECP2 among DDD study participants. InDelible provides a framework for the discovery of pathogenic SVs that are most likely missed by standard analytical workflows and has the potential to improve the diagnostic yield of ES across a broad range of genetic diseases. ispartof: AMERICAN JOURNAL OF HUMAN GENETICS vol:108 issue:11 pages:2186-2194 ispartof: location:United States status: published

Genome-wide sequencing of human populations has revealed substantial variation among genes in the intensity of purifying selection acting on damaging genetic variants1. Although genes under the strongest selective constraint are highly enriched for associations with Mendelian disorders, most of these genes are not associated with disease and therefore the nature of the selection acting on them is not known2. Here we show that genetic variants that damage these genes are associated with markedly reduced reproductive success, primarily owing to increased childlessness, with a stronger effect in males than in females. We present evidence that increased childlessness is probably mediated by genetically associated cognitive and behavioural traits, which may mean that male carriers are less likely to find reproductive partners. This reduction in reproductive success may account for 20% of purifying selection against heterozygous variants that ablate protein-coding genes. Although this genetic association may only account for a very minor fraction of the overall likelihood of being childless (less than 1%), especially when compared to more influential sociodemographic factors, it may influence how genes evolve over time.

Sleep apnea is a common disorder that represents a global public health burden.KCNK3encodes TASK-1, a K+channel implicated in the control of breathing, but its link with sleep apnea remains poorly understood. Here we describe a novel developmental disorder with sleep apnea caused by rarede novogain-of-function mutations inKCNK3. The mutations cluster around the ‘X-gate’, a gating motif which controls channel opening, and produce overactive channels that no longer respond to inhibition by G-protein coupled receptor pathways, but which can be inhibited by several clinically relevant drugs. These findings demonstrate a clear role for TASK-1 in sleep apnea and identify possible therapeutic strategies.

SummaryMutation in the germline is the source of all evolutionary genetic variation and a cause of genetic disease. Previous studies have shown parental age to be the primary determinant of the number of new germline mutations seen in an individual’s genome. Here we analysed the genome-wide sequences of 21,879 families with rare genetic diseases and identified 12 hypermutated individuals with between two and seven times more de novo single nucleotide variants (dnSNVs) than expected. In most of these families (8/12) the excess mutations could be attributed to the father. We determined that two of these families had genetic drivers of germline hypermutation, with the fathers carrying damaging genetic variation in known DNA repair genes, causing distinctive mutational signatures. For five families, by analysing clinical records and mutational signatures, we determined that paternal exposure to chemotherapeutic agents prior to conception was a key driver of hypermutation. Our results suggest that the germline is well protected from mutagenic effects, hypermutation is rare and relatively modest in degree and that most hypermutated individuals will not have a genetic disease.

Trio-based whole-exome sequence (WES) data have established confident genetic diagnoses in ∼40% of previously undiagnosed individuals recruited to the Deciphering Developmental Disorders (DDD) study. Here we aim to use the breadth of phenotypic information recorded in DDD to augment diagnosis and disease variant discovery in probands. Median Euclidean distances (mEuD) were employed as a simple measure of similarity of quantitative phenotypic data within sets of ≥10 individuals with plausibly causative de novo mutations (DNM) in 28 different developmental disorder genes. 13/28 (46.4%) showed significant similarity for growth or developmental milestone metrics, 10/28 (35.7%) showed similarity in HPO term usage, and 12/28 (43%) showed no phenotypic similarity. Pairwise comparisons of individuals with high-impact inherited variants to the 32 individuals with causative DNM in ANKRD11 using only growth z-scores highlighted 5 likely causative inherited variants and two unrecognized DNM resulting in an 18% diagnostic uplift for this gene. Using an independent approach, naive Bayes classification of growth and developmental data produced reasonably discriminative models for the 24 DNM genes with sufficiently complete data. An unsupervised naive Bayes classification of 6,993 probands with WES data and sufficient phenotypic information defined 23 in silico syndromes (ISSs) and was used to test a “phenotype first” approach to the discovery of causative genotypes using WES variants strictly filtered on allele frequency, mutation consequence, and evidence of constraint in humans. This highlighted heterozygous de novo nonsynonymous variants in SPTBN2 as causative in three DDD probands.

Whole genome sequencing (WGS) studies have estimated the human germline mutation rate per basepair per generation (~1.2 × 10−8) to be higher than in mice (3.5–5.4 × 10−9). In humans, most germline mutations are paternal in origin and numbers of mutations per offspring increase with paternal and maternal age. Here we estimate germline mutation rates and spectra in six multi-sibling mouse pedigrees and compare to three multi-sibling human pedigrees. In both species we observe a paternal mutation bias, a parental age effect, and a highly mutagenic first cell division contributing to the embryo. We also observe differences between species in mutation spectra, in mutation rates per cell division, and in the parental bias of mutations in early embryogenesis. These differences between species likely result from both species-specific differences in cellular genealogies of the germline, as well as biological differences within the same stage of embryogenesis or gametogenesis., Estimates of mutation rates differ between species. Here, Lindsay et al. perform side-by-side analyses of germline mutation rates using multi-sibling mouse and human pedigrees and find different mutation rates between species, also stratified by sex and temporal stage of mutation acquisition.

Mosaic genetic variants can have major clinical impact. We systematically analyse trio exome sequence data from 4,293 probands from the DDD Study with severe developmental disorders for pathogenic postzygotic mosaicism (PZM) in the child or a clinically-unaffected parent, and use ultrahigh-depth sequencing to validate candidate mosaic variants. We observe that levels of mosaicism for small genetic variants are usually equivalent in both saliva and blood and ~3% of causative de novo mutations exhibit PZM; this is an important observation, as the sibling recurrence risk is extremely low. We identify parental PZM in 21 trios (0.5% of trios), resulting in a substantially increased sibling recurrence risk in future pregnancies. Together, these forms of mosaicism account for 40 (1%) diagnoses in our cohort. Likely child-PZM mutations occur equally on both parental haplotypes, and the penetrance of detectable mosaic pathogenic variants overall is likely to be less than half that of constitutive variants., Systematic analysis of postzygotic mosaicism (PZM) is difficult due to challenges in detecting such events. Here, Wright et al. analyse trio exome sequencing data from blood and saliva of 4,293 probands with developmental disorders from the DDD Study and estimate that >3% of causative de novo mutations result from PZM.

Genetic architecture of developmental disorders The genetics of developmental disorders (DDs) is complex. Martin et al. wanted to determine the degree of recessive inheritance of DDs in protein-coding genes. They examined the exomes of more than 6000 families in populations with high and low proportions of consanguineous marriages. They found that 3.6% of DDs in individuals of European ancestry involved recessive coding disorders, less than a tenth of the levels previously estimated. Furthermore, among South Asians with high parental relatedness, rather than most of the disorders arising from inherited variants, fewer than half had a recessive coding diagnosis. Science , this issue p. 1161

Over 130 X-linked genes have been robustly associated with developmental disorders, and X-linked causes have been hypothesised to underlie the higher developmental disorder rates in males. Here, we evaluate the burden of X-linked coding variation in 11,044 developmental disorder patients, and find a similar rate of X-linked causes in males and females (6.0% and 6.9%, respectively), indicating that such variants do not account for the 1.4-fold male bias. We develop an improved strategy to detect X-linked developmental disorders and identify 23 significant genes, all of which were previously known, consistent with our inference that the vast majority of the X-linked burden is in known developmental disorder-associated genes. Importantly, we estimate that, in male probands, only 13% of inherited rare missense variants in known developmental disorder-associated genes are likely to be pathogenic. Our results demonstrate that statistical analysis of large datasets can refine our understanding of modes of inheritance for individual X-linked disorders., Developmental disorders (DDs) are more prevalent in males, thought to be due to X-linked genetic variation. Here, the authors investigate the burden of X-linked coding variants in 11,044 DD patients, showing that this contributes to ~6% of both male and female cases and therefore does not solely explain male bias in DDs.

MotivationRecent advances in CRISPR/Cas9 technology allow for the functional analysis of genetic variants at single nucleotide resolution whilst maintaining genomic context (Findlay et al., 2018). This approach, known as saturation genome editing (SGE), is a distinct type of deep mutational scanning (DMS) that systematically alters each position in a target region to explore its function. SGE experiments require the design and synthesis of oligonucleotide variant libraries which are introduced into the genome by homology-directed repair (HDR). This technology is broadly applicable to diverse research fields such as disease variant identification, drug development, structure-function studies, synthetic biology, evolutionary genetics and the study of host-pathogen interactions. Here we present the Variant Library Annotation Tool (VaLiAnT) which can be used to generate saturation mutagenesis oligonucleotide libraries from user-defined genomic coordinates and standardised input files. This software package is intentionally versatile to accommodate diverse operability, with species, genomic reference sequences and transcriptomic annotations specified by the user. Genomic ranges, directionality and frame information are considered to allow perturbations at both the nucleotide and amino acid level.ResultsCoordinates for a genomic range, that may include exonic and/or intronic sequence, are provided by the user in order to retrieve a corresponding oligonucleotide reference sequence. A user-specified range within this sequence is then subject to systematic, nucleotide and/or amino acid saturating mutator functions, with each discrete mutation returned to the user as a separate sequence, building up the final oligo library. If desired, variant accessions from genetic information repositories, such as ClinVar and gnomAD, that fall within the user-specified ranges, will also be incorporated into the library.For SGE library generation, base reference sequences can be modified to include PAM (Protospacer Adjacent Motif) and protospacer ‘protection edits’ that prevent Cas9 from cutting incorporated oligonucleotide tracts. Mutator functions modify this protected reference sequence to generate variant sequences. Constant regions are designated for non-editing to allow specific adapter annealing for downstream cloning and amplification from the library pool.A metadata file is generated, delineating annotation information for each variant sequence to aid computational analysis. In addition, a library file is generated, which contains unique sequences (any exact duplicate sequences are removed) ready for submission to commercial synthesis platforms. A VCF file listing all variants is also generated for analysis and quality control processes.The VaLiAnT software package provides a novel means to systemically retrieve, mutate and annotate genomic sequences for oligonucleotide library generation. Specific features for SGE library generation can be employed, with other diverse applications possible.Availability and ImplementationVaLiAnT is a command line tool written in Python. Source code, testing data, example library input and output files, and executables are available at https://github.com/cancerit/VaLiAnT. A user manual details step by step instructions for software use, available at https://github.com/cancerit/VaLiAnT/wiki. The software is freely available for non-commercial use (see Licence for more details, https://github.com/cancerit/VaLiAnT/blob/develop/LICENSE).

Rare copy-number variants (rCNVs) include deletions and duplications that occur infrequently in the global human population and can confer substantial risk for disease. In this study, we aimed to quantify the properties of haploinsufficiency (i.e., deletion intolerance) and triplosensitivity (i.e., duplication intolerance) throughout the human genome. We harmonized and meta-analyzed rCNVs from nearly one million individuals to construct a genome-wide catalog of dosage sensitivity across 54 disorders, which defined 163 dosage sensitive segments associated with at least one disorder. These segments were typically gene dense and often harbored dominant dosage sensitive driver genes, which we were able to prioritize using statistical fine-mapping. Finally, we designed an ensemble machine-learning model to predict probabilities of dosage sensitivity (pHaplopTriplo) for all autosomal genes, which identified 2,987 haploinsufficient and 1,559 triplosensitive genes, including 648 that were uniquely triplosensitive. This dosage sensitivity resource will provide broad utility for human disease research and clinical genetics.

Purpose: In this study we aimed to establish the genetic cause of a myriad of cardiovascular defects prevalent in individuals from a genetically isolated population, who were found to share a common ancestor in 1728. Methods: Trio genome sequencing was carried out in an index patient with critical congenital heart disease (CHD); family members had either exome or Sanger sequencing. To confirm enrichment, we performed a gene-based association test and meta-analysis in two independent validation cohorts: one with 2685 CHD cases versus 4370. These controls were also ancestry-matched (same as FTAA controls), and the other with 326 cases with familial thoracic aortic aneurysms (FTAA) and dissections versus 570 ancestry-matched controls. Functional consequences of identified variants were evaluated using expression studies. Results: We identified a loss-of-function variant in the Notch target transcription factor-encoding gene HEY2. The homozygous state (n = 3) causes life-threatening congenital heart defects, while 80% of heterozygous carriers (n = 20) had cardiovascular defects, mainly CHD and FTAA of the ascending aorta. We confirm enrichment of rare risk variants in HEY2 functional domains after meta-analysis (MetaSKAT p = 0.018). Furthermore, we show that several identified variants lead to dysregulation of repression by HEY2. Conclusion: A homozygous germline loss-of-function variant in HEY2 leads to critical CHD. The majority of heterozygotes show a myriad of cardiovascular defects.

SummaryStructural Variation (SV) describes a broad class of genetic variation greater than 50bps in size. SVs can cause a wide range of genetic diseases and are prevalent in rare developmental disorders (DD). Patients presenting with DD are often referred for diagnostic testing with chromosomal microarrays (CMA) to identify large copy-number variants (CNVs) and/or with single gene, gene-panel, or exome sequencing (ES) to identify single nucleotide variants, small insertions/deletions, and CNVs. However, patients with pathogenic SVs undetectable by conventional analysis often remain undiagnosed. Consequently, we have developed the novel tool ‘InDelible’, which interrogates short-read sequencing data for split-read clusters characteristic of SV breakpoints. We applied InDelible to 13,438 probands with severe DD recruited as part of the Deciphering Developmental Disorders (DDD) study and discovered 64 rare, damaging variants in genes previously associated with DD missed by standard SNV, InDel or CNV discovery approaches. Clinical review of these 64 variants determined that about half (30/64) were plausibly pathogenic. InDelible was particularly effective at ascertaining variants between 21-500 bps in size, and increased the total number of potentially pathogenic variants identified by DDD in this size range by 42.3%. Of particular interest were seven confirmed de novo variants in MECP2 which represent 35.0% of all de novo protein truncating variants in MECP2 among DDD patients. InDelible provides a framework for the discovery of pathogenic SVs that are likely missed by standard analytical workflows and has the potential to improve the diagnostic yield of ES across a broad range of genetic diseases.

A primary goal of human genetics is to identify DNA sequence variants that influence biomedical traits, particularly those related to the onset and progression of human disease. Over the past 25 years, progress in realizing this objective has been transformed by advances in technology, foundational genomic resources and analytical tools, and by access to vast amounts of genotype and phenotype data. Genetic discoveries have substantially improved our understanding of the mechanisms responsible for many rare and common diseases and driven development of novel preventative and therapeutic strategies. Medical innovation will increasingly focus on delivering care tailored to individual patterns of genetic predisposition.

Congenital Heart Disease (CHD) affects approximately 7-9 children per 1000 live births. Numerous genetic studies have established a role for rare genomic variants at the copy number variation (CNV) and single nucleotide variant level. In particular, the role of de novo mutations (DNM) has been highlighted in syndromic and non-syndromic CHD. To identify novel haploinsufficient CHD disease genes we performed an integrative analysis of CNVs and DNMs identified in probands with CHD including cases with sporadic thoracic aortic aneurysm (TAA). We assembled CNV data from 7,958 cases and 14,082 controls and performed a gene-wise analysis of the burden of rare genomic deletions in cases versus controls. In addition, we performed mutation rate testing for DNMs identified in 2,489 parent-offspring trios. Our combined analysis revealed 21 genes which were significantly affected by rare genomic deletions and/or constrained non-synonymous de novo mutations in probands. Fourteen of these genes have previously been associated with CHD while the remaining genes (FEZ1, MYO16, ARID1B, NALCN, WAC, KDM5B and WHSC1) have only been associated in singletons and small cases series, or show new associations with CHD. In addition, a systems level analysis revealed shared contribution of CNV deletions and DNMs in CHD probands, affecting protein-protein interaction networks involved in Notch signaling pathway, heart morphogenesis, DNA repair and cilia/centrosome function. Taken together, this approach highlights the importance of re-analyzing existing datasets to strengthen disease association and identify novel disease genes.

SummaryGenome-wide sequencing of human populations has revealed substantial variation among genes in the intensity of purifying selection acting on damaging genetic variants1. While genes under the strongest selective constraint are highly enriched for associations with Mendelian disorders, most of these genes are not associated with disease and therefore the nature of the selection acting on them is not known2. Here we show that genetic variants that damage these genes are associated with markedly reduced reproductive success, primarily due to increased childlessness, with a stronger effect in males than in females. We present evidence that increased childlessness is likely mediated by genetically associated cognitive and behavioural traits, which may mean male carriers are less likely to find reproductive partners. This reduction in reproductive success may account for 20% of purifying selection against heterozygous variants that ablate protein-coding genes. While this genetic association could only account for a very minor fraction of the overall likelihood of being childless (less than 1%), especially when compared to more influential sociodemographic factors, it may influence how genes evolve over time.

Genome-wide sequencing of human populations has revealed substantial variation among genes in the intensity of purifying selection acting on damaging genetic variants

Ataxia Telangiectasia and Rad3 related (ATR) is one of the main regulators of the DNA damage response. It coordinates cell cycle checkpoint activation, replication fork stability, restart and origin firing to maintain genome integrity. Mutations of the ATR gene have been reported in Seckel patients, who suffer from a rare genetic disease characterized by severe microcephaly and growth retardation. Here, we report the case of a Seckel patient with compound heterozygous mutations in ATR. One allele has an intronic mutation affecting splicing of neighboring exons, the other an exonic missense mutation, producing the variant p.Lys1665Asn, of unknown pathogenicity. We have modeled this novel missense mutation, as well as a previously described missense mutation p.Met1159Ile, and assessed their effect on ATR function. Interestingly, our data indicate that both missense mutations have no direct effect on protein function, but rather result in defective ATR splicing. These results emphasize the importance of splicing mutations in Seckel Syndrome.

Motivation Understanding the protein structural context and patterning on proteins of genomic variants can help to separate benign from pathogenic variants and reveal molecular consequences. However, mapping genomic coordinates to protein structures is non-trivial, complicated by alternative splicing and transcript evidence. Results Here we present VarMap, a web tool for mapping a list of chromosome coordinates to canonical UniProt sequences and associated protein 3D structures, including validation checks, and annotating them with structural information. Availability and implementation https://www.ebi.ac.uk/thornton-srv/databases/VarMap. Supplementary information Supplementary data are available at Bioinformatics online.