Measuring intolerance to mutation in human genetics

Cytochrome P450 monooxygenase systems: Diversity and plasticity for adaptive stress response

Superfamily of cytochromes P450 (CYPs) is composed of heme-thiolate-containing monooxygenase enzymes, which play crucial roles in the biosynthesis, bioactivation, and detoxification of a variety of organic compounds, both endogenic and exogenic. Majority of CYP monooxygenase systems are multi-component and contain various redox partners, cofactors and auxiliary proteins, which contribute to their diversity in both prokaryotes and eukaryotes. Recent progress in bioinformatics and computational biology approaches make it possible to undertake whole-genome and phylogenetic analyses of CYPomes of a variety of organisms. Considerable variations in sequences within and between CYP families and high similarity in secondary and tertiary structures between all CYPs along with dramatic conformational changes in secondary structure elements of a substrate binding site during catalysis have been reported. This provides structural plasticity and substrate promiscuity, which underlie functional diversity of CYPs. Gene duplication and mutation events underlie CYP evolutionary diversity and emergence of novel selectable functions, which provide the involvement of CYPs in high adaptability to changing environmental conditions and dietary restrictions. In our review, we discuss the recent advancements and challenges in the elucidating the evolutionary origin and mechanisms underlying the CYP monooxygenase system diversity and plasticity. Our review is in the view of hypothesis that diversity of CYP monooxygenase systems is translated into the broad metabolic profiles, and this has been acquired during the long evolutionary time to provide structural plasticity leading to high adaptative capabilities to environmental stress conditions.

Context-adjusted proportion of singletons (CAPS): a novel metric for assessing negative selection in the human genome

Interpretation of genetic variants remains challenging, partly due to the lack of well-established ways of determining the potential pathogenicity of genetic variation, especially for understudied classes of variants. Addressing this, population genetics methods offer a practical solution by evaluating variant effects through human population distributions. Negative selection influences the ratio of singleton variants and can serve as a proxy for deleteriousness, as exemplified by the Mutability-Adjusted Proportion of Singletons (MAPS) metric. However, MAPS is sensitive to the calibration of the singletons-by-mutability linear model, which results in biased estimates for certain variant classes. Building up on the methodology used in MAPS, we introduce the Context-Adjusted Proportion of Singletons (CAPS) metric for assessing negative selection in the human genome. CAPS produces corrected estimates with more accurate confidence intervals by eliminating the mutability layer in the model. Retaining the advantageous features of MAPS, CAPS emerges as a robust and reliable tool. We believe that CAPS has the potential to enhance the identification of new disease-variant associations in clinical and research settings, offering improved accuracy in assessing negative selection for diverse SNV classes.

ccdc141 is required for left-right axis development by regulating cilia formation in the Kupffer's vesicle of zebrafish

Laterality is a crucial physiological process intricately linked to the cilium-centrosome complex during embryo development. Defects in the process can result in severe organ mispositioning. Coiled-coil domain containing 141 (CCDC141) has been previously known as a centrosome-related gene, but its role in left-right (LR) asymmetry has not been characterized. In this study, we utilize the zebrafish model and human exome analysis to elucidate the function of ccdc141 in laterality defects. The knockdown of ccdc141 in zebrafish disrupts early LR signaling pathways, cilia function, and Kupffer's vesicle formation. Unlike ccdc141-knockdown embryos exhibiting aberrant LR patterns, ccdc141-null mutants show no apparent abnormality, suggesting a genetic compensation response effect. In parallel, we observe a marked reduction in α-tubulin acetylation levels in the ccdc141 crispants. The treatment with histone deacetylase (HDAC) inhibitors, particularly the HDAC6 inhibitor, rescues the ccdc141 crispant phenotypes. Furthermore, exome analysis of 70 patients with laterality defects reveals an increased burden of CCDC141 mutations, with in-vivo studies verifying the pathogenicity of the patient mutation CCDC141-R123G. Our findings highlight the critical role of ccdc141 in ciliogenesis and demonstrate that CCDC141 mutations lead to abnormal LR patterns, identifying it as a candidate gene for laterality defects.

Bayesian estimation of gene constraint from an evolutionary model with gene features

Measures of selective constraint on genes have been used for many applications, including clinical interpretation of rare coding variants, disease gene discovery and studies of genome evolution. However, widely used metrics are severely underpowered at detecting constraints for the shortest ~25% of genes, potentially causing important pathogenic mutations to be overlooked. Here we developed a framework combining a population genetics model with machine learning on gene features to enable accurate inference of an interpretable constraint metric, shet. Our estimates outperform existing metrics for prioritizing genes important for cell essentiality, human disease and other phenotypes, especially for short genes. Our estimates of selective constraint should have wide utility for characterizing genes relevant to human disease. Finally, our inference framework, GeneBayes, provides a flexible platform that can improve the estimation of many gene-level properties, such as rare variant burden or gene expression differences.

Prevalence of comorbidities in individuals with neurodevelopmental disorders from the aggregated phenomics data of 51,227 pediatric individuals

The prevalence of comorbidities in individuals with neurodevelopmental disorders (NDDs) is not well understood, yet these are important for accurate diagnosis and prognosis in routine care and for characterizing the clinical spectrum of NDD syndromes. We thus developed PhenomAD-NDD, an aggregated database containing the comorbid phenotypic data of 51,227 individuals with NDD, all harmonized into Human Phenotype Ontology (HPO), with in total 3,054 unique HPO terms. We demonstrate that almost all congenital anomalies are more prevalent in the NDD population than in the general population, and the NDD baseline prevalence allows for an approximation of the enrichment of symptoms. For example, such analyses of 33 genetic NDDs show that 32% of enriched phenotypes are currently not reported in the clinical synopsis in the Online Mendelian Inheritance in Man (OMIM). PhenomAD-NDD is open to all via a visualization online tool and allows us to determine the enrichment of symptoms in NDD.

A deep catalogue of protein-coding variation in 983,578 individuals

Rare coding variants that substantially affect function provide insights into the biology of a gene1-3. However, ascertaining the frequency of such variants requires large sample sizes4-8. Here we present a catalogue of human protein-coding variation, derived from exome sequencing of 983,578 individuals across diverse populations. In total, 23% of the Regeneron Genetics Center Million Exome (RGC-ME) data come from individuals of African, East Asian, Indigenous American, Middle Eastern and South Asian ancestry. The catalogue includes more than 10.4 million missense and 1.1 million predicted loss-of-function (pLOF) variants. We identify individuals with rare biallelic pLOF variants in 4,848 genes, 1,751 of which have not been previously reported. From precise quantitative estimates of selection against heterozygous loss of function (LOF), we identify 3,988 LOF-intolerant genes, including 86 that were previously assessed as tolerant and 1,153 that lack established disease annotation. We also define regions of missense depletion at high resolution. Notably, 1,482 genes have regions that are depleted of missense variants despite being tolerant of pLOF variants. Finally, we estimate that 3% of individuals have a clinically actionable genetic variant, and that 11,773 variants reported in ClinVar with unknown significance are likely to be deleterious cryptic splice sites. To facilitate variant interpretation and genetics-informed precision medicine, we make this resource of coding variation from the RGC-ME dataset publicly accessible through a variant allele frequency browser.

The landscape of regional missense mutational intolerance quantified from 125,748 exomes

Missense variants can have a range of functional impacts depending on factors such as the specific amino acid substitution and location within the gene. To interpret their deleteriousness, studies have sought to identify regions within genes that are specifically intolerant of missense variation 1-12 . Here, we leverage the patterns of rare missense variation in 125,748 individuals in the Genome Aggregation Database (gnomAD) 13 against a null mutational model to identify transcripts that display regional differences in missense constraint. Missense-depleted regions are enriched for ClinVar 14 pathogenic variants, de novo missense variants from individuals with neurodevelopmental disorders (NDDs) 15,16 , and complex trait heritability. Following ClinGen calibration recommendations for the ACMG/AMP guidelines, we establish that regions with less than 20% of their expected missense variation achieve moderate support for pathogenicity. We create a missense deleteriousness metric (MPC) that incorporates regional constraint and outperforms other deleteriousness scores at stratifying case and control de novo missense variation, with a strong enrichment in NDDs. These results provide additional tools to aid in missense variant interpretation.

Heterozygous loss-of-function SMC3 variants are associated with variable growth and developmental features

Heterozygous missense variants and in-frame indels in SMC3 are a cause of Cornelia de Lange syndrome (CdLS), marked by intellectual disability, growth deficiency, and dysmorphism, via an apparent dominant-negative mechanism. However, the spectrum of manifestations associated with SMC3 loss-of-function variants has not been reported, leading to hypotheses of alternative phenotypes or even developmental lethality. We used matchmaking servers, patient registries, and other resources to identify individuals with heterozygous, predicted loss-of-function (pLoF) variants in SMC3, and analyzed population databases to characterize mutational intolerance in this gene. Here, we show that SMC3 behaves as an archetypal haploinsufficient gene: it is highly constrained against pLoF variants, strongly depleted for missense variants, and pLoF variants are associated with a range of developmental phenotypes. Among 14 individuals with SMC3 pLoF variants, phenotypes were variable but coalesced on low growth parameters, developmental delay/intellectual disability, and dysmorphism, reminiscent of atypical CdLS. Comparisons to individuals with SMC3 missense/in-frame indel variants demonstrated an overall milder presentation in pLoF carriers. Furthermore, several individuals harboring pLoF variants in SMC3 were nonpenetrant for growth, developmental, and/or dysmorphic features, and some had alternative symptomatologies with rational biological links to SMC3. Analyses of tumor and model system transcriptomic data and epigenetic data in a subset of cases suggest that SMC3 pLoF variants reduce SMC3 expression but do not strongly support clustering with functional genomic signatures of typical CdLS. Our finding of substantial population-scale LoF intolerance in concert with variable growth and developmental features in subjects with SMC3 pLoF variants expands the scope of cohesinopathies, informs on their allelic architecture, and suggests the existence of additional clearly LoF-constrained genes whose disease links will be confirmed only by multilayered genomic data paired with careful phenotyping.

Bayesian estimation of gene constraint from an evolutionary model with gene features

Measures of selective constraint on genes have been used for many applications including clinical interpretation of rare coding variants, disease gene discovery, and studies of genome evolution. However, widely-used metrics are severely underpowered at detecting constraint for the shortest ∼25% of genes, potentially causing important pathogenic mutations to be overlooked. We developed a framework combining a population genetics model with machine learning on gene features to enable accurate inference of an interpretable constraint metric, shet. Our estimates outperform existing metrics for prioritizing genes important for cell essentiality, human disease, and other phenotypes, especially for short genes. Our new estimates of selective constraint should have wide utility for characterizing genes relevant to human disease. Finally, our inference framework, GeneBayes, provides a flexible platform that can improve estimation of many gene-level properties, such as rare variant burden or gene expression differences.

Constraining models of dominance for nonsynonymous mutations in the human genome

Dominance is a fundamental parameter in genetics, determining the dynamics of natural selection on deleterious and beneficial mutations, the patterns of genetic variation in natural populations, and the severity of inbreeding depression in a population. Despite this importance, dominance parameters remain poorly known, particularly in humans or other non-model organisms. A key reason for this lack of information about dominance is that it is extremely challenging to disentangle the selection coefficient (s) of a mutation from its dominance coefficient (h). Here, we explore dominance and selection parameters in humans by fitting models to the site frequency spectrum (SFS) for nonsynonymous mutations. When assuming a single dominance coefficient for all nonsynonymous mutations, we find that numerous h values can fit the data, so long as h is greater than ~0.15. Moreover, we also observe that theoretically-predicted models with a negative relationship between h and s can also fit the data well, including models with h=0.05 for strongly deleterious mutations. Finally, we use our estimated dominance and selection parameters to inform simulations revisiting the question of whether the out-of-Africa bottleneck has led to differences in genetic load between African and non-African human populations. These simulations suggest that the relative burden of genetic load in non-African populations depends on the dominance model assumed, with slight increases for more weakly recessive models and slight decreases shown for more strongly recessive models. Moreover, these results also demonstrate that models of partially recessive nonsynonymous mutations can explain the observed severity of inbreeding depression in humans, bridging the gap between molecular population genetics and direct measures of fitness in humans. Our work represents a comprehensive assessment of dominance and deleterious variation in humans, with implications for parameterizing models of deleterious variation in humans and other mammalian species.

Genetic analysis of ocular tumour-associated genes using large genomic datasets: insights into selection constraints and variant representation in the population

BACKGROUND

Large genomic databases enable genetic evaluation in terms of haploinsufficiency and prevalence of missense and synonymous variants. We explored these parameters in ocular tumour-associated genes.

METHODS

A curated list of ocular tumour-associated genes was assessed using the genomic databases Genome Aggregation Database (gnomAD) and DatabasE of genomiC varIation and Phenotype in Humans using Ensembl Resources (DECIPHER) and compared with breast and lung cancer-associated gene lists. Haploinsufficiency was determined based on specific criteria: probability of loss of function index ≥0.9 in gnomAD, upper CI O/E limit <0.35 for loss of function variants in gnomAD and/or a DECIPHER pHaplo ≥0.86. UniProt was used for further gene characterisation, and gene ontology Protein Analysis THrough Evolutionary Relationships was explored for common biological pathways. In addition, we identified genes with under-representation/over-representation of missense/synonymous variants.

RESULTS

Fifty-seven genes were identified in association with ocular and extraocular tumours.Regarding haploinsufficiency, 41% of genes met the criteria for negative selection, with 57% categorised as tumour-suppressing and 39% as oncogenic. Most genes were involved in regulatory processes. Regarding triplosensitivity, 33% of genes reached significance and 83% of these were haploinsufficient. Analysis of variants revealed under-representation of missense variants in 23% of genes and over-representation of synonymous variants in 5% of genes. Ocular tumour-associated genes exhibited higher scores for haploinsufficiency and triplosensitivity compared with breast and lung cancer-associated genes. Pathway analysis revealed significant enrichment in cellular proliferation, differentiation and division. Encoded proteins of ocular tumour-associated genes were generally longer than the median of the UniProt database.

CONCLUSION

Our findings highlight the importance of negative selection in ocular tumour genes, supporting cranial gene conservation. This study provides insights into ocular tumourigenesis and future research avenues.

A probabilistic graphical model for estimating selection coefficient of missense variants from human population sequence data

Accurately predicting the effect of missense variants is a central problem in interpretation of genomic variation. Commonly used computational methods does not capture the quantitative impact on fitness in populations. We developed MisFit to estimate missense fitness effect using biobank-scale human population genome data. MisFit jointly models the effect at molecular level ( d ) and population level (selection coefficient, s ), assuming that in the same gene, missense variants with similar d have similar s . MisFit is a probabilistic graphical model that integrates deep neural network components and population genetics models efficiently with inductive bias based on biological causality of variant effect. We trained it by maximizing probability of observed allele counts in 236,017 European individuals. We show that s is informative in predicting frequency across ancestries and consistent with the fraction of de novo mutations given s . Finally, MisFit outperforms previous methods in prioritizing missense variants in individuals with neurodevelopmental disorders.

A deep catalog of protein-coding variation in 985,830 individuals

Coding variants that have significant impact on function can provide insights into the biology of a gene but are typically rare in the population. Identifying and ascertaining the frequency of such rare variants requires very large sample sizes. Here, we present the largest catalog of human protein-coding variation to date, derived from exome sequencing of 985,830 individuals of diverse ancestry to serve as a rich resource for studying rare coding variants. Individuals of African, Admixed American, East Asian, Middle Eastern, and South Asian ancestry account for 20% of this Exome dataset. Our catalog of variants includes approximately 10.5 million missense (54% novel) and 1.1 million predicted loss-of-function (pLOF) variants (65% novel, 53% observed only once). We identified individuals with rare homozygous pLOF variants in 4,874 genes, and for 1,838 of these this work is the first to document at least one pLOF homozygote. Additional insights from the RGC-ME dataset include 1) improved estimates of selection against heterozygous loss-of-function and identification of 3,459 genes intolerant to loss-of-function, 83 of which were previously assessed as tolerant to loss-of-function and 1,241 that lack disease annotations; 2) identification of regions depleted of missense variation in 457 genes that are tolerant to loss-of-function; 3) functional interpretation for 10,708 variants of unknown or conflicting significance reported in ClinVar as cryptic splice sites using splicing score thresholds based on empirical variant deleteriousness scores derived from RGC-ME; and 4) an observation that approximately 3% of sequenced individuals carry a clinically actionable genetic variant in the ACMG SF 3.1 list of genes. We make this important resource of coding variation available to the public through a variant allele frequency browser. We anticipate that this report and the RGC-ME dataset will serve as a valuable reference for understanding rare coding variation and help advance precision medicine efforts.

Systematic differences in discovery of genetic effects on gene expression and complex traits

Most signals in genome-wide association studies (GWAS) of complex traits implicate noncoding genetic variants with putative gene regulatory effects. However, currently identified regulatory variants, notably expression quantitative trait loci (eQTLs), explain only a small fraction of GWAS signals. Here, we show that GWAS and cis-eQTL hits are systematically different: eQTLs cluster strongly near transcription start sites, whereas GWAS hits do not. Genes near GWAS hits are enriched in key functional annotations, are under strong selective constraint and have complex regulatory landscapes across different tissue/cell types, whereas genes near eQTLs are depleted of most functional annotations, show relaxed constraint, and have simpler regulatory landscapes. We describe a model to understand these observations, including how natural selection on complex traits hinders discovery of functionally relevant eQTLs. Our results imply that GWAS and eQTL studies are systematically biased toward different types of variant, and support the use of complementary functional approaches alongside the next generation of eQTL studies.

Heterozygous nonsense variants in laminin subunit 3α resulting in Ebstein's anomaly

Ebstein's anomaly is a rare congenital heart disease characterized by tricuspid valve downward displacement and is associated with additional cardiac phenotypes such as left ventricle non-compaction. The genetic basis of Ebstein's anomaly has yet to be fully elucidated, although several genes (e.g., NKX2-5, MYH7, TPM1, and FLNA) may contribute to Ebstein's anomaly. Here, in two Ebstein's anomaly families (a three-generation family and a trio), we identified independent heterozygous nonsense variants in laminin subunit 3 α (LAMA3), cosegregated with phenotypes in families with reduced penetrance. Furthermore, knocking out Lama3 in mice revealed that haploinsufficiency of Lama3 led to Ebstein's malformation of the tricuspid valve and an abnormal basement membrane structure. In conclusion, we identified a novel gene-disease association of LAMA3 implicated in Ebstein's anomaly, and the findings extended our understanding of the role of the extracellular matrix in Ebstein's anomaly etiology.

Deep multiple-instance learning accurately predicts gene haploinsufficiency and deletion pathogenicity

Copy number losses (deletions) are a major contributor to the etiology of severe genetic disorders. Although haploinsufficient genes play a critical role in deletion pathogenicity, current methods for deletion pathogenicity prediction fail to integrate multiple lines of evidence for haploinsufficiency at the gene level, limiting their power to pinpoint deleterious deletions associated with genetic disorders. Here we introduce DosaCNV, a deep multiple-instance learning framework that, for the first time, models deletion pathogenicity jointly with gene haploinsufficiency. By integrating over 30 gene-level features potentially predictive of haploinsufficiency, DosaCNV shows unmatched performance in prioritizing pathogenic deletions associated with a broad spectrum of genetic disorders. Furthermore, DosaCNV outperforms existing methods in predicting gene haploinsufficiency even though it is not trained on known haploinsufficient genes. Finally, DosaCNV leverages a state-of-the-art technique to quantify the contributions of individual gene-level features to haploinsufficiency, allowing for human-understandable explanations of model predictions. Altogether, DosaCNV is a powerful computational tool for both fundamental and translational research.

Heterozygous loss-of-function SMC3 variants are associated with variable and incompletely penetrant growth and developmental features

Heterozygous missense variants and in-frame indels in SMC3 are a cause of Cornelia de Lange syndrome (CdLS), marked by intellectual disability, growth deficiency, and dysmorphism, via an apparent dominant-negative mechanism. However, the spectrum of manifestations associated with SMC3 loss-of-function variants has not been reported, leading to hypotheses of alternative phenotypes or even developmental lethality. We used matchmaking servers, patient registries, and other resources to identify individuals with heterozygous, predicted loss-of-function (pLoF) variants in SMC3, and analyzed population databases to characterize mutational intolerance in this gene. Here, we show that SMC3 behaves as an archetypal haploinsufficient gene: it is highly constrained against pLoF variants, strongly depleted for missense variants, and pLoF variants are associated with a range of developmental phenotypes. Among 13 individuals with SMC3 pLoF variants, phenotypes were variable but coalesced on low growth parameters, developmental delay/intellectual disability, and dysmorphism reminiscent of atypical CdLS. Comparisons to individuals with SMC3 missense/in-frame indel variants demonstrated a milder presentation in pLoF carriers. Furthermore, several individuals harboring pLoF variants in SMC3 were nonpenetrant for growth, developmental, and/or dysmorphic features, some instead having intriguing symptomatologies with rational biological links to SMC3 including bone marrow failure, acute myeloid leukemia, and Coats retinal vasculopathy. Analyses of transcriptomic and epigenetic data suggest that SMC3 pLoF variants reduce SMC3 expression but do not result in a blood DNA methylation signature clustering with that of CdLS, and that the global transcriptional signature of SMC3 loss is model-dependent. Our finding of substantial population-scale LoF intolerance in concert with variable penetrance in subjects with SMC3 pLoF variants expands the scope of cohesinopathies, informs on their allelic architecture, and suggests the existence of additional clearly LoF-constrained genes whose disease links will be confirmed only by multi-layered genomic data paired with careful phenotyping.

An unsupervised deep learning framework for predicting human essential genes from population and functional genomic data

BACKGROUND

The ability to accurately predict essential genes intolerant to loss-of-function (LOF) mutations can dramatically improve the identification of disease-associated genes. Recently, there have been numerous computational methods developed to predict human essential genes from population genomic data. While the existing methods are highly predictive of essential genes of long length, they have limited power in pinpointing short essential genes due to the sparsity of polymorphisms in the human genome.

RESULTS

Motivated by the premise that population and functional genomic data may provide complementary evidence for gene essentiality, here we present an evolution-based deep learning model, DeepLOF, to predict essential genes in an unsupervised manner. Unlike previous population genetic methods, DeepLOF utilizes a novel deep learning framework to integrate both population and functional genomic data, allowing us to pinpoint short essential genes that can hardly be predicted from population genomic data alone. Compared with previous methods, DeepLOF shows unmatched performance in predicting ClinGen haploinsufficient genes, mouse essential genes, and essential genes in human cell lines. Notably, at a false positive rate of 5%, DeepLOF detects 50% more ClinGen haploinsufficient genes than previous methods. Furthermore, DeepLOF discovers 109 novel essential genes that are too short to be identified by previous methods.

CONCLUSION

The predictive power of DeepLOF shows that it is a compelling computational method to aid in the discovery of essential genes.

Advances for pediatricians in 2022: allergy, anesthesiology, cardiology, dermatology, endocrinology, gastroenterology, genetics, global health, infectious diseases, metabolism, neonatology, neurology, oncology, pulmonology

The last year saw intensive efforts to advance knowledge in pediatric medicine. This review highlights important publications that have been issued in the Italian Journal of Pediatrics in 2022. We have chosen papers in the fields of allergy, anesthesiology, cardiology, dermatology, endocrinology, gastroenterology, genetics, global health, infectious diseases, metabolism, neonatology, neurology, oncology, pulmonology. Novel valuable developments in epidemiology, pathophysiology, prevention, diagnosis and treatment that can rapidly change the approach to diseases in childhood have been included and discussed.

An RNA-informed dosage sensitivity map reflects the intrinsic functional nature of genes

Understanding dosage sensitivity or why Mendelian diseases have dominant vs. recessive modes of inheritance is crucial for uncovering the etiology of human disease. Previous knowledge of dosage sensitivity is mainly based on observations of rare loss-of-function mutations or copy number changes, which are underpowered due to ultra rareness of such variants. Thus, the functional underpinnings of dosage constraint remain elusive. In this study, we aim to systematically quantify dosage perturbations from cis-regulatory variants in the general population to yield a tissue-specific dosage constraint map of genes and further explore their underlying functional logic. We reveal an inherent divergence of dosage constraints in genes by functional categories with signaling genes (transcription factors, protein kinases, ion channels, and cellular machinery) being dosage sensitive, while effector genes (transporters, metabolic enzymes, cytokines, and receptors) are generally dosage resilient. Instead of being a metric of functional dispensability, we show that dosage constraint reflects underlying homeostatic constraints arising from negative feedback. Finally, we employ machine learning to integrate DNA and RNA metrics to generate a comprehensive, tissue-specific map of dosage sensitivity (MoDs) for autosomal genes.

The Warburg micro syndrome protein RAB3GAP1 modulates neuronal morphogenesis and interacts with axon elongation end ER-Golgi trafficking factors

RAB3GAP1 is GTPase activating protein localized to the ER and Golgi compartments. In humans, mutations in RAB3GAP1 are the most common cause of Warburg Micro syndrome, a neurodevelopmental disorder associated with intellectual disability, microcephaly, and agenesis of the corpus callosum. We found that downregulation of RAB3GAP1 leads to a reduction in neurite outgrowth and complexity in human stem cell derived neurons. To further define the cellular function of RAB3GAP1, we sought to identify novel interacting proteins. We used a combination of mass spectrometry, co-immunoprecipitation and colocalization analysis and identified two novel interactors of RAB3GAP1: the axon elongation factor Dedicator of cytokinesis 7 (DOCK7) and the TATA modulatory factor 1 (TMF1) a modulator of Endoplasmic Reticulum (ER) to Golgi trafficking. To define the relationship between RAB3GAP1 and its two novel interactors, we analyzed their localization to different subcellular compartments in neuronal and non-neuronal cells with loss of RAB3GAP1. We find that RAB3GAP1 is important for the sub-cellular localization of TMF1 and DOCK7 across different compartments of the Golgi and endoplasmic reticulum. In addition, we find that loss of function mutations in RAB3GAP1 lead to dysregulation of pathways that are activated in response to the cellular stress like ATF6, MAPK, and PI3-AKT signaling. In summary, our findings suggest a novel role for RAB3GAP1 in neurite outgrowth that could encompass the regulation of proteins that control axon elongation, ER-Golgi trafficking, as well as pathways implicated in response to cellular stress.

Quantifying the fraction of new mutations that are recessive lethal

The presence and impact of recessive lethal mutations have been widely documented in diploid outcrossing species. However, precise estimates of the proportion of new mutations that are recessive lethal remain limited. Here, we evaluate the performance of Fit∂a∂i, a commonly used method for inferring the distribution of fitness effects (DFE), in the presence of lethal mutations. Using simulations, we demonstrate that in both additive and recessive cases, inference of the deleterious nonlethal portion of the DFE is minimally affected by a small proportion (<10%) of lethal mutations. Additionally, we demonstrate that while Fit∂a∂i cannot estimate the fraction of recessive lethal mutations, Fit∂a∂i can accurately infer the fraction of additive lethal mutations. Finally, as an alternative approach to estimate the proportion of mutations that are recessive lethal, we employ models of mutation-selection-drift balance using existing genomic parameters and estimates of segregating recessive lethals for humans and Drosophila melanogaster. In both species, the segregating recessive lethal load can be explained by a very small fraction (<1%) of new nonsynonymous mutations being recessive lethal. Our results refute recent assertions of a much higher proportion of mutations being recessive lethal (4%-5%), while highlighting the need for additional information on the joint distribution of selection and dominance coefficients.

Heterozygous loss-of-function DHX9 variants are associated with neurodevelopmental disorders: Human genetic and experimental evidences

DExH-box helicases are involved in unwinding of RNA and DNA. Among the 16 DExH-box genes, monoallelic variants of DHX16, DHX30, DHX34, and DHX37 are known to be associated with neurodevelopmental disorders. In particular, DHX30 is well established as a causative gene for neurodevelopmental disorders. Germline variants of DHX9, the closest homolog of DHX30, have not been reported until now as being associated with congenital disorders in humans, except that one de novo heterozygous variant, p.(Arg1052Gln) of the gene was identified during comprehensive screening in a patient with autism; unfortunately, the phenotypic details of this individual are unknown. Herein, we report a patient with a heterozygous de novo missense variant, p.(Gly414Arg) of DHX9 who presented with a short stature, intellectual disability, and ventricular non-compaction cardiomyopathy. The variant was located in the glycine codon of the ATP-binding site, G-C-G-K-T. To assess the pathogenicity of this variants, we generated transgenic Drosophila lines expressing human wild-type and mutant DHX9 proteins: 1) the mutant proteins showed aberrant localization both in the nucleus and the cytoplasm; 2) ectopic expression of wild-type protein in the visual system led to the rough eye phenotype, whereas expression of the mutant proteins had minimal effect; 3) overexpression of the wild-type protein in the retina led to a reduction in axonal numbers, whereas expression of the mutant proteins had a less pronounced effect. Furthermore, in a gene-editing experiment of Dhx9 G416 to R416, corresponding to p.(Gly414Arg) in humans, heterozygous mice showed a reduced body size, reduced emotionality, and cardiac conduction abnormality. In conclusion, we established that heterozygosity for a loss-of-function variant of DHX9 can lead to a new neurodevelopmental disorder.

A non-coding variant in the Kozak sequence of RARS2 strongly decreases protein levels and causes pontocerebellar hypoplasia

Bi-allelic variants in the mitochondrial arginyl-transfer RNA synthetase (RARS2) gene have been involved in early-onset encephalopathies classified as pontocerebellar hypoplasia (PCH) type 6 and in epileptic encephalopathy. A variant (NM_020320.3:c.-2A > G) in the promoter and 5'UTR of the RARS2 gene has been previously identified in a family with PCH. Only a mild impact of this variant on the mRNA level has been detected. As RARS2 is non-dosage-sensitive, this observation is not conclusive in regard of the pathogenicity of the variant.We report and describe here a new patient with the same variant in the RARS2 gene, at the homozygous state. This patient presents with a clinical phenotype consistent with PCH6 although in the absence of lactic acidosis. In agreement with the previous study, we measured RARS2 mRNA levels in patient's fibroblasts and detected a partially preserved gene expression compared to control. Importantly, this variant is located in the Kozak sequence that controls translation initiation. Therefore, we investigated the impact on protein translation using a bioinformatic approach and western blotting. We show here that this variant, additionally to its effect on the transcription, also disrupts the consensus Kozak sequence, and has a major impact on RARS2 protein translation. Through the identification of this additional case and the characterization of the molecular consequences, we clarified the involvement of this Kozak variant in PCH and on protein synthesis. This work also points to the current limitation in the pathogenicity prediction of variants located in the translation initiation region.

The impact of rare protein coding genetic variation on adult cognitive function

Compelling evidence suggests that human cognitive function is strongly influenced by genetics. Here, we conduct a large-scale exome study to examine whether rare protein-coding variants impact cognitive function in the adult population (n = 485,930). We identify eight genes (ADGRB2, KDM5B, GIGYF1, ANKRD12, SLC8A1, RC3H2, CACNA1A and BCAS3) that are associated with adult cognitive function through rare coding variants with large effects. Rare genetic architecture for cognitive function partially overlaps with that of neurodevelopmental disorders. In the case of KDM5B we show how the genetic dosage of one of these genes may determine the variability of cognitive, behavioral and molecular traits in mice and humans. We further provide evidence that rare and common variants overlap in association signals and contribute additively to cognitive function. Our study introduces the relevance of rare coding variants for cognitive function and unveils high-impact monogenic contributions to how cognitive function is distributed in the normal adult population.

Genetics of mirror movements identifies a multifunctional complex required for Netrin-1 guidance and lateralization of motor control

Mirror movements (MM) disorder is characterized by involuntary movements on one side of the body that mirror intentional movements on the opposite side. We performed genetic characterization of a family with autosomal dominant MM and identified ARHGEF7, a RhoGEF, as a candidate MM gene. We found that Arhgef7 and its partner Git1 bind directly to Dcc. Dcc is the receptor for Netrin-1, an axon guidance cue that attracts commissural axons to the midline, promoting the midline crossing of axon tracts. We show that Arhgef7 and Git1 are required for Netrin-1-mediated axon guidance and act as a multifunctional effector complex. Arhgef7/Git1 activates Rac1 and Cdc42 and inhibits Arf1 downstream of Netrin-1. Furthermore, Arhgef7/Git1, via Arf1, mediates the Netrin-1-induced increase in cell surface Dcc. Mice heterozygous for Arhgef7 have defects in commissural axon trajectories and increased symmetrical paw placements during skilled walking, a MM-like phenotype. Thus, we have delineated how ARHGEF7 mutation causes MM.

De novo variants implicate chromatin modification, transcriptional regulation, and retinoic acid signaling in syndromic craniosynostosis

Craniosynostosis (CS) is the most common congenital cranial anomaly. Several Mendelian forms of syndromic CS are well described, but a genetic etiology remains elusive in a substantial fraction of probands. Analysis of exome sequence data from 526 proband-parent trios with syndromic CS identified a marked excess (observed 98, expected 33, p = 4.83 × 10-20) of damaging de novo variants (DNVs) in genes highly intolerant to loss-of-function variation (probability of LoF intolerance > 0.9). 30 probands harbored damaging DNVs in 21 genes that were not previously implicated in CS but are involved in chromatin modification and remodeling (4.7-fold enrichment, p = 1.1 × 10-11). 17 genes had multiple damaging DNVs, and 13 genes (CDK13, NFIX, ADNP, KMT5B, SON, ARID1B, CASK, CHD7, MED13L, PSMD12, POLR2A, CHD3, and SETBP1) surpassed thresholds for genome-wide significance. A recurrent gain-of-function DNV in the retinoic acid receptor alpha (RARA; c.865G>A [p.Gly289Arg]) was identified in two probands with similar CS phenotypes. CS risk genes overlap with those identified for autism and other neurodevelopmental disorders, are highly expressed in cranial neural crest cells, and converge in networks that regulate chromatin modification, gene transcription, and osteoblast differentiation. Our results identify several CS loci and have major implications for genetic testing and counseling.

Heterozygous Variants in FREM2 Are Associated with Mesiodens, Supernumerary Teeth, Oral Exostoses, and Odontomas

BACKGROUND

Supernumerary teeth refer to extra teeth that exceed the usual number of dentitions. A mesiodens is a particular form of supernumerary tooth, which is located in the premaxilla region. The objective of the study was to investigate the genetic etiology of extra tooth phenotypes, including mesiodens and isolated supernumerary teeth.

METHODS

Oral and radiographic examinations and whole-exome sequencing were performed on every patient in our cohort of 122 patients, including 27 patients with isolated supernumerary teeth and 94 patients with mesiodens. A patient who had multiple supernumerary teeth also had odontomas.

RESULTS

We identified a novel (c.8498A>G; p.Asn2833Ser) and six recurrent (c.1603C>T; p.Arg535Cys, c.5852G>A; p.Arg1951His, c.6949A>T; p.Thr2317Ser; c.1549G>A; p.Val517Met, c.1921A>G; p.Thr641Ala, and c.850G>C; p.Val284Leu) heterozygous missense variants in FREM2 in eight patients with extra tooth phenotypes.

CONCLUSIONS

Biallelic variants in FREM2 are implicated in autosomal recessive Fraser syndrome with or without dental anomalies. Here, we report for the first time that heterozygous carriers of FREM2 variants have phenotypes including oral exostoses, mesiodens, and isolated supernumerary teeth.

Mendelian inheritance revisited: dominance and recessiveness in medical genetics

Understanding the consequences of genotype for phenotype (which ranges from molecule-level effects to whole-organism traits) is at the core of genetic diagnostics in medicine. Many measures of the deleteriousness of individual alleles exist, but these have limitations for predicting the clinical consequences. Various mechanisms can protect the organism from the adverse effects of functional variants, especially when the variant is paired with a wild type allele. Understanding why some alleles are harmful in the heterozygous state - representing dominant inheritance - but others only with the biallelic presence of pathogenic variants - representing recessive inheritance - is particularly important when faced with the deluge of rare genetic alterations identified by high throughput DNA sequencing. Both awareness of the specific quantitative and/or qualitative effects of individual variants and the elucidation of allelic and non-allelic interactions are essential to optimize genetic diagnosis and counselling.

Genomic Underpinnings of Population Persistence in Isle Royale Moose

Island ecosystems provide natural laboratories to assess the impacts of isolation on population persistence. However, most studies of persistence have focused on a single species, without comparisons to other organisms they interact with in the ecosystem. The case study of moose and gray wolves on Isle Royale allows for a direct contrast of genetic variation in isolated populations that have experienced dramatically differing population trajectories over the past decade. Whereas the Isle Royale wolf population recently declined nearly to extinction due to severe inbreeding depression, the moose population has thrived and continues to persist, despite having low genetic diversity and being isolated for ∼120 years. Here, we examine the patterns of genomic variation underlying the continued persistence of the Isle Royale moose population. We document high levels of inbreeding in the population, roughly as high as the wolf population at the time of its decline. However, inbreeding in the moose population manifests in the form of intermediate-length runs of homozygosity suggestive of historical inbreeding and purging, contrasting with the long runs of homozygosity observed in the smaller wolf population. Using simulations, we confirm that substantial purging has likely occurred in the moose population. However, we also document notable increases in genetic load, which could eventually threaten population viability over the long term. Overall, our results demonstrate a complex relationship between inbreeding, genetic diversity, and population viability that highlights the use of genomic datasets and computational simulation tools for understanding the factors enabling persistence in isolated populations.

Relating pathogenic loss-of-function mutations in humans to their evolutionary fitness costs

Causal loss-of-function (LOF) variants for Mendelian and severe complex diseases are enriched in 'mutation intolerant' genes. We show how such observations can be interpreted in light of a model of mutation-selection balance and use the model to relate the pathogenic consequences of LOF mutations at present to their evolutionary fitness effects. To this end, we first infer posterior distributions for the fitness costs of LOF mutations in 17,318 autosomal and 679 X-linked genes from exome sequences in 56,855 individuals. Estimated fitness costs for the loss of a gene copy are typically above 1%; they tend to be largest for X-linked genes, whether or not they have a Y homolog, followed by autosomal genes and genes in the pseudoautosomal region. We compare inferred fitness effects for all possible de novo LOF mutations to those of de novo mutations identified in individuals diagnosed with one of six severe, complex diseases or developmental disorders. Probands carry an excess of mutations with estimated fitness effects above 10%; as we show by simulation, when sampled in the population, such highly deleterious mutations are typically only a couple of generations old. Moreover, the proportion of highly deleterious mutations carried by probands reflects the typical age of onset of the disease. The study design also has a discernible influence: a greater proportion of highly deleterious mutations is detected in pedigree than case-control studies, and for autism, in simplex than multiplex families and in female versus male probands. Thus, anchoring observations in human genetics to a population genetic model allows us to learn about the fitness effects of mutations identified by different mapping strategies and for different traits.

Biallelic loss of LDB3 leads to a lethal pediatric dilated cardiomyopathy

Autosomal dominant variants in LDB3 (also known as ZASP), encoding the PDZ-LIM domain-binding factor, have been linked to a late onset phenotype of cardiomyopathy and myofibrillar myopathy in humans. However, despite knockout mice displaying a much more severe phenotype with premature death, bi-allelic variants in LDB3 have not yet been reported. Here we identify biallelic loss-of-function variants in five unrelated cardiomyopathy families by next-generation sequencing. In the first family, we identified compound heterozygous LOF variants in LDB3 in a fetus with bilateral talipes and mild left cardiac ventricular enlargement. Ultra-structural examination revealed highly irregular Z-disc formation, and RNA analysis demonstrated little/no expression of LDB3 protein with a functional C-terminal LIM domain in muscle tissue from the affected fetus. In a second family, a homozygous LDB3 nonsense variant was identified in a young girl with severe early-onset dilated cardiomyopathy with left ventricular non-compaction; the same homozygous nonsense variant was identified in a third unrelated female infant with dilated cardiomyopathy. We further identified homozygous LDB3 frameshift variants in two unrelated probands diagnosed with cardiomegaly and severely reduced left ventricular ejection fraction. Our findings demonstrate that recessive LDB3 variants can lead to an early-onset severe human phenotype of cardiomyopathy and myopathy, reminiscent of the knockout mouse phenotype, and supporting a loss of function mechanism.

Whole exome sequencing in dense families suggests genetic pleiotropy amongst Mendelian and complex neuropsychiatric syndromes

Whole Exome Sequencing (WES) studies provide important insights into the genetic architecture of serious mental illness (SMI). Genes that are central to the shared biology of SMIs may be identified by WES in families with multiple affected individuals with diverse SMI (F-SMI). We performed WES in 220 individuals from 75 F-SMI families and 60 unrelated controls. Within pedigree prioritization employed criteria of rarity, functional consequence, and sharing by ≥ 3 affected members. Across the sample, gene and gene-set-wide case-control association analysis was performed with Sequence Kernel Association Test (SKAT). In 14/16 families with ≥ 3 sequenced affected individuals, we identified a total of 78 rare predicted deleterious variants in 78 unique genes shared by ≥ 3 members with SMI. Twenty (25%) genes were implicated in monogenic CNS syndromes in OMIM (OMIM-CNS), a fraction that is a significant overrepresentation (Fisher's Exact test OR = 2.47, p = 0.001). In gene-set SKAT, statistically significant association was noted for OMIM-CNS gene-set (SKAT-p = 0.005) but not the synaptic gene-set (SKAT-p = 0.17). In this WES study in F-SMI, we identify private, rare, protein altering variants in genes previously implicated in Mendelian neuropsychiatric syndromes; suggesting pleiotropic influences in neurodevelopment between complex and Mendelian syndromes.

LOF variants identifying candidate genes of laterality defects patients with congenital heart disease

Defects in laterality pattern can result in abnormal positioning of the internal organs during the early stages of embryogenesis, as manifested in heterotaxy syndrome and situs inversus, while laterality defects account for 3~7% of all congenital heart defects (CHDs). However, the pathogenic mechanism underlying most laterality defects remains unknown. In this study, we recruited 70 laterality defect patients with CHDs to identify candidate disease genes by exome sequencing. We then evaluated rare, loss-of-function (LOF) variants, identifying candidates by referring to previous literature. We chose TRIP11, DNHD1, CFAP74, and EGR4 as candidates from 776 LOF variants that met the initial screening criteria. After the variants-to-gene mapping, we performed function research on these candidate genes. The expression patterns and functions of these four candidate genes were studied by whole-mount in situ hybridization, gene knockdown, and gene rescue methods in zebrafish models. Among the four genes, trip11, dnhd1, and cfap74 morphant zebrafish displayed abnormalities in both cardiac looping and expression patterns of early signaling molecules, suggesting that these genes play important roles in the establishment of laterality patterns. Furthermore, we performed immunostaining and high-speed cilia video microscopy to investigate Kupffer's vesicle organogenesis and ciliogenesis of morphant zebrafish. Impairments of Kupffer's vesicle organogenesis or ciliogenesis were found in trip11, dnhd1, and cfap74 morphant zebrafish, which revealed the possible pathogenic mechanism of their LOF variants in laterality defects. These results highlight the importance of rare, LOF variants in identifying disease-related genes and identifying new roles for TRIP11, DNHD1, and CFAP74 in left-right patterning. Additionally, these findings are consistent with the complex genetics of laterality defects.

Genomic profiling for clinical decision making in myeloid neoplasms and acute leukemia

Myeloid neoplasms and acute leukemias derive from the clonal expansion of hematopoietic cells driven by somatic gene mutations. Although assessment of morphology plays a crucial role in the diagnostic evaluation of patients with these malignancies, genomic characterization has become increasingly important for accurate diagnosis, risk assessment, and therapeutic decision making. Conventional cytogenetics, a comprehensive and unbiased method for assessing chromosomal abnormalities, has been the mainstay of genomic testing over the past several decades and remains relevant today. However, more recent advances in sequencing technology have increased our ability to detect somatic mutations through the use of targeted gene panels, whole-exome sequencing, whole-genome sequencing, and whole-transcriptome sequencing or RNA sequencing. In patients with myeloid neoplasms, whole-genome sequencing represents a potential replacement for both conventional cytogenetic and sequencing approaches, providing rapid and accurate comprehensive genomic profiling. DNA sequencing methods are used not only for detecting somatically acquired gene mutations but also for identifying germline gene mutations associated with inherited predisposition to hematologic neoplasms. The 2022 International Consensus Classification of myeloid neoplasms and acute leukemias makes extensive use of genomic data. The aim of this report is to help physicians and laboratorians implement genomic testing for diagnosis, risk stratification, and clinical decision making and illustrates the potential of genomic profiling for enabling personalized medicine in patients with hematologic neoplasms.

Integrating de novo and inherited variants in 42,607 autism cases identifies mutations in new moderate-risk genes

To capture the full spectrum of genetic risk for autism, we performed a two-stage analysis of rare de novo and inherited coding variants in 42,607 autism cases, including 35,130 new cases recruited online by SPARK. We identified 60 genes with exome-wide significance (P < 2.5 × 10^-6), including five new risk genes (NAV3, ITSN1, MARK2, SCAF1 and HNRNPUL2). The association of NAV3 with autism risk is primarily driven by rare inherited loss-of-function (LoF) variants, with an estimated relative risk of 4, consistent with moderate effect. Autistic individuals with LoF variants in the four moderate-risk genes (NAV3, ITSN1, SCAF1 and HNRNPUL2; n = 95) have less cognitive impairment than 129 autistic individuals with LoF variants in highly penetrant genes (CHD8, SCN2A, ADNP, FOXP1 and SHANK3) (59% vs 88%, P = 1.9 × 10^-6). Power calculations suggest that much larger numbers of autism cases are needed to identify additional moderate-risk genes.

When LUCA met gnomAD: genetic constraints on universal genes in humans

LUCA, the last universal common ancestor, is the hypothetical most recent common ancestor of the three domains of life which share the universal genes (UG). It seems interesting to evaluate whether the UG phylogeny has had an impact on current Human gene constraints. A list of human homologs of UG was retrieved from the eggNOG database. We analyzed this LUCA gene (LG) group, and a random sample of 500 genes from the gnomAD database (RG group). Gene constraint metrics were retrieved from gnomAD and associations with Mendelian diseases and modes of inheritance were retrieved from OMIM. The LG group consisted of 277 genes and the RG group, 492 (8 genes were in LG group). 38.6% of the genes in the LG group and 25.2% of the genes in the RG group were associated with a Mendelian disease (p < 0.0001). The mode of inheritance was more often autosomal recessive (69.0 vs. 50.5%), and less often autosomal dominant (19.0 vs. 31.3%), or mixed (6.0 vs. 12.1%) for those associated with the LG group (p = 0.048). The LG group was significantly more constrained for missense variants (MOEUF, 0.919 vs. 0.997, p < 0.0001) and was borderline significantly more constrained for loss-of-function variants (LOEUF, 0.872 vs. 0.947, p = 0.051). These results suggest that the UG in humans differs from the rest of the genome in terms of constraints and associated Mendelian diseases. It suggests that phylogenic data can explain some of the characteristics of human genes and could help in interpreting variants.

A Simple Evolutionary Model of Genetic Robustness After Gene Duplication

When a dispensable gene is duplicated (referred to the ancestral dispensability denoted by O⁺), genetic buffering and duplicate compensation together maintain the duplicate redundancy, whereas duplicate compensation is the only mechanism when an essential gene is duplicated (referred to the ancestral essentiality denoted by O^-). To investigate these evolutionary scenarios of genetic robustness, I formulated a simple mixture model for analyzing duplicate pairs with one of the following states: double dispensable (DD), semi-dispensable (one dispensable one essential, DE), or double essential (EE). This model was applied to the yeast duplicate pairs from a whole-genome duplication (WGD) occurred about 100 million years ago (mya), and the mouse duplicate pairs from a WGD occurred about more than 500 mya. Both case studies revealed that the proportion of essentiality for those duplicates with ancestral essentiality [P_E(O^-)] was much higher than that for those with ancestral dispensability [P_E(O⁺)]. While it was negligible in the yeast duplicate pairs, P_E(O⁺) (about 20%) was shown statistically significant in the mouse duplicate pairs. These findings, together, support the hypothesis that both sub-functionalization and neo-functionalization may play some roles after gene duplication, though the former may be much faster than the later.

Exploring the mutational landscape of genes associated with inherited retinal disease using large genomic datasets: identifying loss of function intolerance and outlying propensities for missense changes

Background

Large databases permit quantitative description of genes in terms of intolerance to loss of function (‘haploinsufficiency’) and prevalence of missense variants. We explored these parameters in inherited retinal disease (IRD) genes.

Methods

IRD genes (from the ‘RetNet’ resource) were classified by probability of loss of function intolerance (pLI) using online Genome Aggregation Database (gnomAD) and DatabasE of genomiC varIation and Phenotype in Humans using Ensembl Resources (DECIPHER) databases. Genes were identified having pLI ≥0.9 together with one or both of the following: upper bound of CI <0.35 for observed to expected (o/e) ratio of loss of function variants in the gnomAD resource; haploinsufficiency score <10 in the DECIPHER resource. IRD genes in which missense variants appeared under-represented or over-represented (Z score for o/e ratio of <−2.99 or >2.99, respectively) were also identified. The genes were evaluated in the gene ontology Protein Analysis THrough Evolutionary Relationships (PANTHER) resource.

Results

Of 280 analysed genes, 39 (13.9%) were predicted loss of function intolerant. A greater proportion of X-linked than autosomal IRD genes fulfilled these criteria, as expected. Most autosomal genes were associated with dominant disease. PANTHER analysis showed >100 fold enrichment of spliceosome tri-snRNP complex assembly. Most encoded proteins were longer than the median length in the UniProt database. Fourteen genes (11 of which were in the ‘haploinsufficient’ group) showed under-representation of missense variants. Six genes (SAMD11, ALMS1, WFS1, RP1L1, KCNV2, ADAMTS18) showed over-representation of missense variants.

Conclusion

A minority of IRD-associated genes appear to be ‘haploinsufficient’. Over-representation of spliceosome pathways was observed. When interpreting genetic tests, variants found in genes with over-representation of missense variants should be interpreted with caution.

Extreme purifying selection against point mutations in the human genome

Large-scale genome sequencing has enabled the measurement of strong purifying selection in protein-coding genes. Here we describe a new method, called ExtRaINSIGHT, for measuring such selection in noncoding as well as coding regions of the human genome. ExtRaINSIGHT estimates the prevalence of "ultraselection" by the fractional depletion of rare single-nucleotide variants, after controlling for variation in mutation rates. Applying ExtRaINSIGHT to 71,702 whole genome sequences from gnomAD v3, we find abundant ultraselection in evolutionarily ancient miRNAs and neuronal protein-coding genes, as well as at splice sites. By contrast, we find much less ultraselection in other noncoding RNAs and transcription factor binding sites, and only modest levels in ultraconserved elements. We estimate that ~0.4-0.7% of the human genome is ultraselected, implying ~ 0.26-0.51 strongly deleterious mutations per generation. Overall, our study sheds new light on the genome-wide distribution of fitness effects by combining deep sequencing data and classical theory from population genetics.

PARD3 gene variation as candidate cause of nonsyndromic cleft palate only

Nonsyndromic cleft palate only (NSCP) is a common congenital malformation worldwide. In this study, we report a three‐generation pedigree with NSCP following the autosomal‐dominant pattern. Whole‐exome sequencing and Sanger sequencing revealed that only the frameshift variant c.1012dupG [p. E338Gfs*26] in PARD3 cosegregated with the disease. In zebrafish embryos, ethmoid plate patterning defects were observed with PARD3 ortholog disruption or expression of patient‐derived N‐terminal truncating PARD3 (c.1012dupG), which implicated PARD3 in ethmoid plate morphogenesis. PARD3 plays vital roles in determining cellular polarity. Compared with the apical distribution of wild‐type PARD3, PARD3‐p. E338Gfs*26 mainly localized to the basal membrane in 3D‐cultured MCF‐10A epithelial cells. The interaction between PARD3‐p. E338Gfs*26 and endogenous PARD3 was identified by LC–MS/MS and validated by co‐IP. Immunofluorescence analysis showed that PARD3‐p. E338Gfs*26 substantially altered the localization of endogenous PARD3 to the basement membrane in 3D‐cultured MCF‐10A cells. Furthermore, seven variants, including one nonsense variant and six missense variants, were identified in the coding region of PARD3 in sporadic cases with NSCP. Subsequent analysis showed that PARD3‐p. R133*, like the insertion variant of c.1012dupG, also changed the localization of endogenous full‐length PARD3 and that its expression induced abnormal ethmoid plate morphogenesis in zebrafish. Based on these data, we reveal PARD3 gene variation as a novel candidate cause of nonsyndromic cleft palate only.

Copy Number Variant Risk Scores Associated With Cognition, Psychopathology, and Brain Structure in Youths in the Philadelphia Neurodevelopmental Cohort

Importance

Psychiatric and cognitive phenotypes have been associated with a range of specific, rare copy number variants (CNVs). Moreover, IQ is strongly associated with CNV risk scores that model the predicted risk of CNVs across the genome. But the utility of CNV risk scores for psychiatric phenotypes has been sparsely examined.

Objective

To determine how CNV risk scores, common genetic variation indexed by polygenic scores (PGSs), and environmental factors combine to associate with cognition and psychopathology in a community sample.

Design, Setting, and Participants

The Philadelphia Neurodevelopmental Cohort is a community-based study examining genetics, psychopathology, neurocognition, and neuroimaging. Participants were recruited through the Children's Hospital of Philadelphia pediatric network. Participants with stable health and fluency in English underwent genotypic and phenotypic characterization from November 5, 2009, through December 30, 2011. Data were analyzed from January 1 through July 30, 2021.

Exposures

The study examined (1) CNV risk scores derived from models of burden, predicted intolerance, and gene dosage sensitivity; (2) PGSs from genomewide association studies related to developmental outcomes; and (3) environmental factors, including trauma exposure and neighborhood socioeconomic status.

Main Outcomes and Measures

The study examined (1) neurocognition, with the Penn Computerized Neurocognitive Battery; (2) psychopathology, with structured interviews based on the Schedule for Affective Disorders and Schizophrenia for School-Age Children; and (3) brain volume, with magnetic resonance imaging.

Results

Participants included 9498 youths aged 8 to 21 years; 4906 (51.7%) were female, and the mean (SD) age was 14.2 (3.7) years. After quality control, 18 185 total CNVs greater than 50 kilobases (10 517 deletions and 7668 duplications) were identified in 7101 unrelated participants genotyped on Illumina arrays. In these participants, elevated CNV risk scores were associated with lower overall accuracy on cognitive tests (standardized β = 0.12; 95% CI, 0.10-0.14; P = 7.41 × 10-26); lower accuracy across a range of cognitive subdomains; increased overall psychopathology; increased psychosis-spectrum symptoms; and higher deviation from a normative developmental model of brain volume. Statistical models of developmental outcomes were significantly improved when CNV risk scores were combined with PGSs and environmental factors.

Conclusions and Relevance

In this study, elevated CNV risk scores were associated with lower cognitive ability, higher psychopathology including psychosis-spectrum symptoms, and greater deviations from normative magnetic resonance imaging models of brain development. Together, these results represent a step toward synthesizing rare genetic, common genetic, and environmental factors to understand clinically relevant outcomes in youth.

Structural variant-based pangenome construction has low sensitivity to variability of haplotype-resolved bovine assemblies

Advantages of pangenomes over linear reference assemblies for genome research have recently been established. However, potential effects of sequence platform and assembly approach, or of combining assemblies created by different approaches, on pangenome construction have not been investigated. Here we generate haplotype-resolved assemblies from the offspring of three bovine trios representing increasing levels of heterozygosity that each demonstrate a substantial improvement in contiguity, completeness, and accuracy over the current Bos taurus reference genome. Diploid coverage as low as 20x for HiFi or 60x for ONT is sufficient to produce two haplotype-resolved assemblies meeting standards set by the Vertebrate Genomes Project. Structural variant-based pangenomes created from the haplotype-resolved assemblies demonstrate significant consensus regardless of sequence platform, assembler algorithm, or coverage. Inspecting pangenome topologies identifies 90 thousand structural variants including 931 overlapping with coding sequences; this approach reveals variants affecting QRICH2, PRDM9, HSPA1A, TAS2R46, and GC that have potential to affect phenotype.

Large-scale discovery of novel neurodevelopmental disorder-related genes through a unified analysis of single-nucleotide and copy number variants

Background

Previous large-scale studies of de novo variants identified a number of genes associated with neurodevelopmental disorders (NDDs); however, it was also predicted that many NDD-associated genes await discovery. Such genes can be discovered by integrating copy number variants (CNVs), which have not been fully considered in previous studies, and increasing the sample size.

Methods

We first constructed a model estimating the rates of de novo CNVs per gene from several factors such as gene length and number of exons. Second, we compiled a comprehensive list of de novo single-nucleotide variants (SNVs) in 41,165 individuals and de novo CNVs in 3675 individuals with NDDs by aggregating our own and publicly available datasets, including denovo-db and the Deciphering Developmental Disorders study data. Third, summing up the de novo CNV rates that we estimated and SNV rates previously established, gene-based enrichment of de novo deleterious SNVs and CNVs were assessed in the 41,165 cases. Significantly enriched genes were further prioritized according to their similarity to known NDD genes using a deep learning model that considers functional characteristics (e.g., gene ontology and expression patterns).

Results

We identified a total of 380 genes achieving statistical significance (5% false discovery rate), including 31 genes affected by de novo CNVs. Of the 380 genes, 52 have not previously been reported as NDD genes, and the data of de novo CNVs contributed to the significance of three genes (GLTSCR1, MARK2, and UBR3). Among the 52 genes, we reasonably excluded 18 genes [a number almost identical to the theoretically expected false positives (i.e., 380 × 0.05 = 19)] given their constraints against deleterious variants and extracted 34 “plausible” candidate genes. Their validity as NDD genes was consistently supported by their similarity in function and gene expression patterns to known NDD genes. Quantifying the overall similarity using deep learning, we identified 11 high-confidence (> 90% true-positive probabilities) candidate genes: HDAC2, SUPT16H, HECTD4, CHD5, XPO1, GSK3B, NLGN2, ADGRB1, CTR9, BRD3, and MARK2.

Conclusions

We identified dozens of new candidates for NDD genes. Both the methods and the resources developed here will contribute to the further identification of novel NDD-associated genes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13073-022-01042-w.

Transcription factor protein interactomes reveal genetic determinants in heart disease

Congenital heart disease (CHD) is present in 1% of live births, yet identification of causal mutations remains challenging. We hypothesized that genetic determinants for CHDs may lie in the protein interactomes of transcription factors whose mutations cause CHDs. Defining the interactomes of two transcription factors haplo-insufficient in CHD, GATA4 and TBX5, within human cardiac progenitors, and integrating the results with nearly 9,000 exomes from proband-parent trios revealed an enrichment of de novo missense variants associated with CHD within the interactomes. Scoring variants of interactome members based on residue, gene, and proband features identified likely CHD-causing genes, including the epigenetic reader GLYR1. GLYR1 and GATA4 widely co-occupied and co-activated cardiac developmental genes, and the identified GLYR1 missense variant disrupted interaction with GATA4, impairing in vitro and in vivo function in mice. This integrative proteomic and genetic approach provides a framework for prioritizing and interrogating genetic variants in heart disease.

The Medaka Inbred Kiyosu-Karlsruhe (MIKK) panel

BACKGROUND

Unraveling the relationship between genetic variation and phenotypic traits remains a fundamental challenge in biology. Mapping variants underlying complex traits while controlling for confounding environmental factors is often problematic. To address this, we establish a vertebrate genetic resource specifically to allow for robust genotype-to-phenotype investigations. The teleost medaka (Oryzias latipes) is an established genetic model system with a long history of genetic research and a high tolerance to inbreeding from the wild.

RESULTS

Here we present the Medaka Inbred Kiyosu-Karlsruhe (MIKK) panel: the first near-isogenic panel of 80 inbred lines in a vertebrate model derived from a wild founder population. Inbred lines provide fixed genomes that are a prerequisite for the replication of studies, studies which vary both the genetics and environment in a controlled manner, and functional testing. The MIKK panel will therefore enable phenotype-to-genotype association studies of complex genetic traits while allowing for careful control of interacting factors, with numerous applications in genetic research, human health, drug development, and fundamental biology.

CONCLUSIONS

Here we present a detailed characterization of the genetic variation across the MIKK panel, which provides a rich and unique genetic resource to the community by enabling large-scale experiments for mapping complex traits.

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.

Rap_GAP Domain of TSC2 Contributes to Tumor Suppression Through mTOR Signaling in Human Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is an aggressive disease with a high degree of tumor heterogeneity. Genetic lesions of mTOR-related genes, including TSC2 and hyperactivation of mTOR signaling, are common in HCC. However, the association of genetic alterations with hepatocarcinogenesis remains unclear. In this study, continuous truncating mutations occurred within or upstream of the TSC2 Rap_GAP domain in clinical HCC samples. To elucidate whether hyperactivation of mTOR signaling in HCC is caused by TSC2 truncating mutations, HCC cell models carrying the TSC2 deletion (CRISPR/Cas9) or the TSC2 truncating mutation (mutagenesis) were established. Our findings showed that either TSC2 deletion or TSC2 mutant could lead to TSC2 loss-of-function and hyperactivation of mTOR signaling. Furthermore, hyperactivation of mTOR signaling was relieved by rapamycin. Immunohistochemistry of clinical samples confirmed frequent TSC2 loss in HCC. Thus, our study revealed that genetic alterations cause TSC2 loss of function and result in the hyperactivation of mTOR, and high frequency of TSC2 truncating mutations around RAP_GAP domain may be one of the reasons for the hyperactivation of mTOR in HCC patients.