Loss-of-function, gain-of-function and dominant-negative mutations have profoundly different effects on protein structure

A monoallelic UXS1 variant associated with short-limbed short stature

BACKGROUND

Serine residues in the protein backbone of heavily glycosylated proteoglycans are bound to glycosaminoglycans through a tetrasaccharide linker. UXS1 encodes UDP-glucuronate decarboxylase 1, which catalyzes synthesis of UDP-xylose, the donor of the first building block in the linker. Defects in other enzymes involved in formation of the tetrasaccharide linker cause so-called linkeropathies, characterized by short stature, radio-ulnar synostosis, decreased bone density, congenital contractures, dislocations, and more.

METHODS

Whole exome sequencing was performed in a father and son who presented with a mild skeletal dysplasia, as well as the father's unaffected parents. Wild-type and mutant UXS1 were recombinantly expressed in Escherichia coli and purified. Enzyme activity was evaluated by LC-MS/MS. In vivo effects were studied using HeparinRed assay and metabolomics.

RESULTS

The son had short long bones, normal epiphysis, and subtle metaphyseal changes especially in his legs. The likely pathogenic heterozygous variant NM_001253875.1(UXS1):c.557T>A p.(Ile186Asn) detected in the son was de novo in the father. Purified Ile186Asn-UXS1, in contrast to the wild-type, was not able to convert UDP-glucuronic acid to UDP-xylose. Plasma glycosaminoglycan levels were decreased in both son and father.

CONCLUSION

This is the first report linking UXS1 to short-limbed short stature in humans.

The full spectrum of SLC22 OCT1 mutations illuminates the bridge between drug transporter biophysics and pharmacogenomics

Mutations in transporters can impact an individual's response to drugs and cause many diseases. Few variants in transporters have been evaluated for their functional impact. Here, we combine saturation mutagenesis and multi-phenotypic screening to dissect the impact of 11,213 missense single-amino-acid deletions, and synonymous variants across the 554 residues of OCT1, a key liver xenobiotic transporter. By quantifying in parallel expression and substrate uptake, we find that most variants exert their primary effect on protein abundance, a phenotype not commonly measured alongside function. Using our mutagenesis results combined with structure prediction and molecular dynamic simulations, we develop accurate structure-function models of the entire transport cycle, providing biophysical characterization of all known and possible human OCT1 polymorphisms. This work provides a complete functional map of OCT1 variants along with a framework for integrating functional genomics, biophysical modeling, and human genetics to predict variant effects on disease and drug efficacy.

PreMode predicts mode-of-action of missense variants by deep graph representation learning of protein sequence and structural context

Accurate prediction of the functional impact of missense variants is important for disease gene discovery, clinical genetic diagnostics, therapeutic strategies, and protein engineering. Previous efforts have focused on predicting a binary pathogenicity classification, but the functional impact of missense variants is multi-dimensional. Pathogenic missense variants in the same gene may act through different modes of action (i.e., gain/loss-of-function) by affecting different aspects of protein function. They may result in distinct clinical conditions that require different treatments. We developed a new method, PreMode, to perform gene-specific mode-of-action predictions. PreMode models effects of coding sequence variants using SE(3)-equivariant graph neural networks on protein sequences and structures. Using the largest-to-date set of missense variants with known modes of action, we showed that PreMode reached state-of-the-art performance in multiple types of mode-of-action predictions by efficient transfer-learning. Additionally, PreMode's prediction of G/LoF variants in a kinase is consistent with inactive-active conformation transition energy changes. Finally, we show that PreMode enables efficient study design of deep mutational scans and optimization in protein engineering.

Heterozygous CAPZA2 mutations cause global developmental delay, hypotonia with epilepsy: a case report and the literature review

CAPZA2 encodes the α2 subunit of CAPZA, which is vital for actin polymerization and depolymerization in humans. However, understanding of diseases associated with CAPZA2 remains limited. To date, only three cases have been documented with neurodevelopmental abnormalities such as delayed motor development, speech delay, intellectual disability, hypotonia, and a history of seizures. In this study, we document a patient who exhibited seizures, mild intellectual disability, and impaired motor development yet did not demonstrate speech delay or hypotonia. The patient also suffered from recurrent instances of respiratory infections, gastrointestinal and allergic diseases. A novel de novo splicing variant c.219+1 G > A was detected in the CAPZA2 gene through whole-exome sequencing. This variant led to exon 4 skipping in mRNA splicing, confirmed by RT-PCR and Sanger sequencing. To our knowledge, this is the third study on human CAPZA2 defects, documenting the fourth unambiguously diagnosed case. Furthermore, this splicing mutation type is reported here for the first time. Our research offers additional support for the existence of a CAPZA2-related non-syndromic neurodevelopmental disorder. Our findings augment our understanding of the phenotypic range associated with CAPZA2 deficiency and enrich the knowledge of the mutational spectrum of the CAPZA2 gene.

An update on clinical presentation and responses to therapy of patients with hereditary hypophosphatemic rickets with hypercalciuria (HHRH)

Pathogenic variants in solute carrier family 34, member 3 (SLC34A3), the gene encoding the sodium-dependent phosphate cotransporter 2c (NPT2c), cause hereditary hypophosphatemic rickets with hypercalciuria (HHRH). Here, we report a pooled analysis of clinical and laboratory records of 304 individuals from 145 kindreds, including 20 previously unreported HHRH kindreds, in which two novel SLC34A3 pathogenic variants were identified. Compound heterozygous/homozygous carriers show above 90% penetrance for kidney and bone phenotypes. The biochemical phenotype for heterozygous carriers is intermediate with decreased serum phosphate, tubular reabsorption of phosphate (TRP (%)), fibroblast growth factor 23, and intact parathyroid hormone, but increased serum 1,25-dihydroxy vitamin D, and urine calcium excretion causing idiopathic hypercalciuria in 38%, with bone phenotypes still observed in 23% of patients. Oral phosphate supplementation is the current standard of care, which typically normalizes serum phosphate. However, although in more than half of individuals this therapy achieves correction of hypophosphatemia it fails to resolve the other outcomes. The American College of Medical Genetics and Genomics score correlated with functional analysis of frequent SLC34A3 pathogenic variants in vitro and baseline disease severity. The number of mutant alleles and baseline TRP (%) were identified as predictors for kidney and bone phenotypes, baseline TRP (%) furthermore predicted response to therapy. Certain SLC34A3/NPT2c pathogenic variants can be identified with partial responses to therapy, whereas with some overlap, others present only with kidney phenotypes and a third group present only with bone phenotypes. Thus, our report highlights important novel clinical aspects of HHRH and heterozygous carriers, raises awareness to this rare group of disorders and can be a foundation for future studies urgently needed to guide therapy of HHRH.

Molecular Dynamics Simulation of Kir6.2 Variants Reveals Potential Association with Diabetes Mellitus

Diabetes mellitus (DM) represents a problem for the healthcare system worldwide. DM has very serious complications such as blindness, kidney failure, and cardiovascular disease. In addition to the very bad socioeconomic impacts, it influences patients and their families and communities. The global costs of DM and its complications are huge and expected to rise by the year 2030. DM is caused by genetic and environmental risk factors. Genetic testing will aid in early diagnosis and identification of susceptible individuals or populations using ATP-sensitive potassium (KATP) channels present in different tissues such as the pancreas, myocardium, myocytes, and nervous tissues. The channels respond to different concentrations of blood sugar, stimulation by hormones, or ischemic conditions. In pancreatic cells, they regulate the secretion of insulin and glucagon. Mutations in the KCNJ11 gene that encodes the Kir6.2 protein (a major constituent of KATP channels) were reported to be associated with Type 2 DM, neonatal diabetes mellitus (NDM), and maturity-onset diabetes of the young (MODY). Kir6.2 harbors binding sites for ATP and phosphatidylinositol 4,5-diphosphate (PIP2). The ATP inhibits the KATP channel, while the (PIP2) activates it. A Kir6.2 mutation at tyrosine330 (Y330) was demonstrated to reduce ATP inhibition and predisposes to NDM. In this study, we examined the effect of mutations on the Kir6.2 structure using bioinformatics tools and molecular dynamic simulations (SIFT, PolyPhen, SNAP2, PANTHER, PhD&SNP, SNP&Go, I-Mutant, MuPro, MutPred, ConSurf, HOPE, and GROMACS). Our results indicated that M199R, R201H, R206H, and Y330H mutations influence Kir6.2 structure and function and therefore may cause DM. We conclude that MD simulations are useful techniques to predict the effects of mutations on protein structure. In addition, the M199R, R201H, R206H, and Y330H variant in the Kir6.2 protein may be associated with DM. These results require further verification in protein-protein interactions, Kir6.2 function, and case-control studies.

A Structural Proteome Screen Identifies Protein Mimicry in Host-Microbe Systems

Host-microbe systems are evolutionary niches that produce coevolved biological interactions and are a key component of global health. However, these systems have historically been a difficult field of biological research due to their experimental intractability. Impactful advances in global health will be obtained by leveraging in silico screens to identify genes involved in mediating interspecific interactions. These predictions will progress our understanding of these systems and lay the groundwork for future in vitro and in vivo experiments and bioengineering projects. A driver of host-manipulation and intracellular survival utilized by host-associated microbes is molecular mimicry, a critical mechanism that can occur at any level from DNA to protein structures. We applied protein structure prediction and alignment tools to explore host-associated bacterial structural proteomes for examples of protein structure mimicry. By leveraging the Legionella pneumophila proteome and its many known structural mimics, we developed and validated a screen that can be applied to virtually any host-microbe system to uncover signals of protein mimicry. These mimics represent candidate proteins that mediate host interactions in microbial proteomes. We successfully applied this screen to other microbes with demonstrated effects on global health, Helicobacter pylori and Wolbachia , identifying protein mimic candidates in each proteome. We discuss the roles these candidates may play in important Wolbachia -induced phenotypes and show that Wobachia infection can partially rescue the loss of one of these factors. This work demonstrates how a genome-wide screen for candidates of host-manipulation and intracellular survival offers an opportunity to identify functionally important genes in host-microbe systems.

DNA binding analysis of rare variants in homeodomains reveals homeodomain specificity-determining residues

Homeodomains (HDs) are the second largest class of DNA binding domains (DBDs) among eukaryotic sequence-specific transcription factors (TFs) and are the TF structural class with the largest number of disease-associated mutations in the Human Gene Mutation Database (HGMD). Despite numerous structural studies and large-scale analyses of HD DNA binding specificity, HD-DNA recognition is still not fully understood. Here, we analyze 92 human HD mutants, including disease-associated variants and variants of uncertain significance (VUS), for their effects on DNA binding activity. Many of the variants alter DNA binding affinity and/or specificity. Detailed biochemical analysis and structural modeling identifies 14 previously unknown specificity-determining positions, 5 of which do not contact DNA. The same missense substitution at analogous positions within different HDs often exhibits different effects on DNA binding activity. Variant effect prediction tools perform moderately well in distinguishing variants with altered DNA binding affinity, but poorly in identifying those with altered binding specificity. Our results highlight the need for biochemical assays of TF coding variants and prioritize dozens of variants for further investigations into their pathogenicity and the development of clinical diagnostics and precision therapies.

Prioritizing genomic variants pathogenicity via DNA, RNA, and protein-level features based on extreme gradient boosting

Genetic diseases are mostly implicated with genetic variants, including missense, synonymous, non-sense, and copy number variants. These different kinds of variants are indicated to affect phenotypes in various ways from previous studies. It remains essential but challenging to understand the functional consequences of these genetic variants, especially the noncoding ones, due to the lack of corresponding annotations. While many computational methods have been proposed to identify the risk variants. Most of them have only curated DNA-level and protein-level annotations to predict the pathogenicity of the variants, and others have been restricted to missense variants exclusively. In this study, we have curated DNA-, RNA-, and protein-level features to discriminate disease-causing variants in both coding and noncoding regions, where the features of protein sequences and protein structures have been shown essential for analyzing missense variants in coding regions while the features related to RNA-splicing and RBP binding are significant for variants in noncoding regions and synonymous variants in coding regions. Through the integration of these features, we have formulated the Multi-level feature Genomic Variants Predictor (ML-GVP) using the gradient boosting tree. The method has been trained on more than 400,000 variants in the Sherloc-training set from the 6th critical assessment of genome interpretation with superior performance. The method is one of the two best-performing predictors on the blind test in the Sherloc assessment, and is further confirmed by another independent test dataset of de novo variants.

Understanding large scale sequencing datasets through changes to protein folding

The expansion of high-quality, low-cost sequencing has created an enormous opportunity to understand how genetic variants alter cellular behaviour in disease. The high diversity of mutations observed has however drawn a spotlight onto the need for predictive modelling of mutational effects on phenotype from variants of uncertain significance. This is particularly important in the clinic due to the potential value in guiding clinical diagnosis and patient treatment. Recent computational modelling has highlighted the importance of mutation induced protein misfolding as a common mechanism for loss of protein or domain function, aided by developments in methods that make large computational screens tractable. Here we review recent applications of this approach to different genes, and how they have enabled and supported subsequent studies. We further discuss developments in the approach and the role for the approach in light of increasingly high throughput experimental approaches.

Spectral Fluorescence Pathology of Protein Misfolding Disorders

Protein misfolding has been extensively studied in the context of neurodegenerative disorders and systemic amyloidoses. Due to misfolding and aggregation of proteins being highly heterogeneous and generating a variety of structures, a growing body of evidence illustrates numerous ways how the aggregates contribute to progression of diseases such as Alzheimer's disease, Parkinson's disease, and prion disorders. Different misfolded species of the same protein, commonly referred to as strains, appear to play a significant role in shaping the disease clinical phenotype and clinical progression. The distinct toxicity profiles of various misfolded proteins underscore their importance. Current diagnostics struggle to differentiate among these strains early in the disease course. This review explores the potential of spectral fluorescence approaches to illuminate the complexities of protein misfolding pathology and discusses the applications of advanced spectral methods in the detection and characterization of protein misfolding disorders. By examining spectrally variable probes, current data analysis approaches, and important considerations for the use of these techniques, this review aims to provide an overview of the progress made in this field and highlights directions for future research.

Epigenetic editing for autosomal dominant neurological disorders

Epigenetics refers to the molecules and mechanisms that modify gene expression states without changing the nucleotide context. These modifications are what encode the cell state during differentiation or epigenetic memory in mitosis. Epigenetic modifications can alter gene expression by changing the chromatin architecture by altering the affinity for DNA to wrap around histone octamers, forming nucleosomes. The higher affinity the DNA has for the histones, the tighter it will wrap and therefore induce a heterochromatin state, silencing gene expression. Several groups have shown the ability to harness the cell's natural epigenetic modification pathways to engineer proteins that can induce changes in epigenetics and consequently regulate gene expression. Therefore, epigenetic modification can be used to target and treat disorders through the modification of endogenous gene expression. The use of epigenetic modifications may prove an effective path towards regulating gene expression to potentially correct or cure genetic disorders.

Walking with giants: The challenges of variant impact assessment in the giant sarcomeric protein titin

Titin, the so-called "third filament" of the sarcomere, represents a difficult challenge for the determination of damaging genetic variants. A single titin molecule extends across half the length of a sarcomere in striated muscle, fulfilling a variety of vital structural and signaling roles, and has been linked to an equally varied range of myopathies, resulting in a significant burden on individuals and healthcare systems alike. While the consequences of truncating variants of titin are well-documented, the ramifications of the missense variants prevalent in the general population are less so. We here present a compendium of titin missense variants-those that result in a single amino-acid substitution in coding regions-reported to be pathogenic and discuss these in light of the nature of titin and the variant position within the sarcomere and their domain, the structural, pathological, and biophysical characteristics that define them, and the methods used for characterization. Finally, we discuss the current knowledge and integration of the multiple fields that have contributed to our understanding of titin-related pathology and offer suggestions as to how these concurrent methodologies may aid the further development in our understanding of titin and hopefully extend to other, less well-studied giant proteins. This article is categorized under: Cardiovascular Diseases > Genetics/Genomics/Epigenetics Congenital Diseases > Genetics/Genomics/Epigenetics Congenital Diseases > Molecular and Cellular Physiology.

Genetic variant interpretation for the neurologist - A pragmatic approach in the next-generation sequencing era in childhood epilepsy

Genetic advances over the past decade have enhanced our understanding of the genetic landscape of childhood epilepsy. However a major challenge for clinicians ha been understanding the rationale and systematic approach towards interpretation of the clinical significance of variant(s) detected in their patients. As the clinical paradigm evolves from gene panels to whole exome or whole genome testing including rapid genome sequencing, the number of patients tested and variants identified per patient will only increase. Each step in the process of variant interpretation has limitations and there is no single criterion which enables the clinician to draw reliable conclusions on a causal relationship between the variant and disease without robust clinical phenotyping. Although many automated online analysis software tools are available, these carry a risk of misinterpretation. This guideline provides a pragmatic, real-world approach to variant interpretation for the child neurologist. The focus will be on ascertaining aspects such as variant frequency, subtype, inheritance pattern, structural and functional consequence with regard to genotype-phenotype correlations, while refraining from mere interpretation of the classification provided in a genetic test report. It will not replace the expert advice of colleagues in clinical genetics, however as genomic investigations become a first-line test for epilepsy, it is vital that neurologists and epileptologists are equipped to navigate this landscape.

Considerations for reporting variants in novel candidate genes identified during clinical genomic testing

Since the first novel gene discovery for a Mendelian condition was made via exome sequencing (ES), the rapid increase in the number of genes known to underlie Mendelian conditions coupled with the adoption of exome (and more recently, genome) sequencing by diagnostic testing labs has changed the landscape of genomic testing for rare disease. Specifically, many individuals suspected to have a Mendelian condition are now routinely offered clinical ES. This commonly results in a precise genetic diagnosis but frequently overlooks the identification of novel candidate genes. Such candidates are also less likely to be identified in the absence of large-scale gene discovery research programs. Accordingly, clinical laboratories have both the opportunity, and some might argue a responsibility, to contribute to novel gene discovery which should in turn increase the diagnostic yield for many conditions. However, clinical diagnostic laboratories must necessarily balance priorities for throughput, turnaround time, cost efficiency, clinician preferences, and regulatory constraints, and often do not have the infrastructure or resources to effectively participate in either clinical translational or basic genome science research efforts. For these and other reasons, many laboratories have historically refrained from broadly sharing potentially pathogenic variants in novel genes via networks like Matchmaker Exchange, much less reporting such results to ordering providers. Efforts to report such results are further complicated by a lack of guidelines for clinical reporting and interpretation of variants in novel candidate genes. Nevertheless, there are myriad benefits for many stakeholders, including patients/families, clinicians, researchers, if clinical laboratories systematically and routinely identify, share, and report novel candidate genes. To facilitate this change in practice, we developed criteria for triaging, sharing, and reporting novel candidate genes that are most likely to be promptly validated as underlying a Mendelian condition and translated to use in clinical settings.

Differential functional consequences of GRIN2A mutations associated with schizophrenia and neurodevelopmental disorders

Human genetic studies have revealed rare missense and protein-truncating variants in GRIN2A, encoding for the GluN2A subunit of the NMDA receptors, that confer significant risk for schizophrenia (SCZ). Mutations in GRIN2A are also associated with epilepsy and developmental delay/intellectual disability (DD/ID). However, it remains enigmatic how alterations to the same protein can result in diverse clinical phenotypes. Here, we performed functional characterization of human GluN1/GluN2A heteromeric NMDA receptors that contain SCZ-linked GluN2A variants, and compared them to NMDA receptors with GluN2A variants associated with epilepsy or DD/ID. Our findings demonstrate that SCZ-associated GRIN2A variants were predominantly loss-of-function (LoF), whereas epilepsy and DD/ID-associated variants resulted in both gain- and loss-of-function phenotypes. We additionally show that M653I and S809R, LoF GRIN2A variants associated with DD/ID, exert a dominant-negative effect when co-expressed with a wild-type GluN2A, whereas E58Ter and Y698C, SCZ-linked LoF variants, and A727T, an epilepsy-linked LoF variant, do not. These data offer a potential mechanism by which SCZ/epilepsy and DD/ID-linked variants can cause different effects on receptor function and therefore result in divergent pathological outcomes.

Interpreting the effect of mutations to protein binding sites from large-scale genomic screens

Predicting the functionality of missense mutations is extremely difficult. Large-scale genomic screens are commonly performed to identify mutational correlates or drivers of disease and treatment resistance, but interpretation of how these mutations impact protein function is limited. One such consequence of mutations to a protein is to impact its ability to bind and interact with partners or small molecules such as ATP, thereby modulating its function. Multiple methods exist for predicting the impact of a single mutation on protein-protein binding energy, but it is difficult in the context of a genomic screen to understand if these mutations with large impacts on binding are more common than statistically expected. We present a methodology for taking mutational data from large-scale genomic screens and generating functional and statistical insights into their role in the binding of proteins both with each other and their small molecule ligands. This allows a quantitative and statistical analysis to determine whether mutations impacting protein binding or ligand interactions are occurring more or less frequently than expected by chance. We achieve this by calculating the potential impact of any possible mutation and comparing an expected distribution to the observed mutations. This method is applied to examples demonstrating its ability to interpret mutations involved in protein-protein binding, protein-DNA interactions, and the evolution of therapeutic resistance.

Applications of Gene Therapy in Cardiomyopathies

Gene therapy is defined by the introduction of new genes or the genetic modification of existing genes and/or their regulatory portions via gene replacement and gene editing strategies, respectively. The genetic material is usually delivered though cardiotropic vectors such as adeno-associated virus 9 or engineered capsids. The enthusiasm for gene therapy has been hampered somewhat by adverse events observed in clinical trials, including dose-dependent immunologic reactions such as hepatotoxicity, acquired hemolytic uremic syndrome and myocarditis. Notably, gene therapy for Duchenne muscular dystrophy has recently been approved and pivotal clinical trials are testing gene therapy approaches in rare myocardial conditions such as Danon disease and Fabry disease. Furthermore, promising results have been shown in animal models of gene therapy in hypertrophic cardiomyopathy and arrhythmogenic cardiomyopathy. This review summarizes the gene therapy techniques, the toxicity risk associated with adeno-associated virus delivery, the ongoing clinical trials, and future targets.

Ensemble-based design of tau to inhibit aggregation while preserving biological activity

The microtubule-associated protein tau is implicated in neurodegenerative diseases characterized by amyloid formation. Mutations associated with frontotemporal dementia increase tau aggregation propensity and disrupt its endogenous microtubule-binding activity. The structural relationship between aggregation propensity and biological activity remains unclear. We employed a multi-disciplinary approach, including computational modeling, NMR, cross-linking mass spectrometry, and cell models to design tau sequences that stabilize its structural ensemble. Our findings reveal that substitutions near the conserved 'PGGG' beta-turn motif can modulate local conformation, more stably engaging in interactions with the 306VQIVYK311 amyloid motif to decrease aggregation in vitro and in cells. Designed tau sequences maintain microtubule binding and explain why 3R isoforms of tau exhibit reduced pathogenesis over 4R isoforms. We propose a simple mechanism to reduce the formation of pathogenic species while preserving biological function, offering insights for therapeutic strategies aimed at reducing protein misfolding in neurodegenerative diseases.

Transcriptome analysis in a humanized mouse model of familial dysautonomia reveals tissue-specific gene expression disruption in the peripheral nervous system

Familial dysautonomia (FD) is a rare recessive neurodevelopmental disease caused by a splice mutation in the Elongator acetyltransferase complex subunit 1 (ELP1) gene. This mutation results in a tissue-specific reduction of ELP1 protein, with the lowest levels in the central and peripheral nervous systems (CNS and PNS, respectively). FD patients exhibit complex neurological phenotypes due to the loss of sensory and autonomic neurons. Disease symptoms include decreased pain and temperature perception, impaired or absent myotatic reflexes, proprioceptive ataxia, and progressive retinal degeneration. While the involvement of the PNS in FD pathogenesis has been clearly recognized, the underlying mechanisms responsible for the preferential neuronal loss remain unknown. In this study, we aimed to elucidate the molecular mechanisms underlying FD by conducting a comprehensive transcriptome analysis of neuronal tissues from the phenotypic mouse model TgFD9; Elp1Δ20/flox. This mouse recapitulates the same tissue-specific ELP1 mis-splicing observed in patients while modeling many of the disease manifestations. Comparison of FD and control transcriptomes from dorsal root ganglion (DRG), trigeminal ganglion (TG), medulla (MED), cortex, and spinal cord (SC) showed significantly more differentially expressed genes (DEGs) in the PNS than the CNS. We then identified genes that were tightly co-expressed and functionally dependent on the level of full-length ELP1 transcript. These genes, defined as ELP1 dose-responsive genes, were combined with the DEGs to generate tissue-specific dysregulated FD signature genes and networks. Within the PNS networks, we observed direct connections between Elp1 and genes involved in tRNA synthesis and genes related to amine metabolism and synaptic signaling. Importantly, transcriptomic dysregulation in PNS tissues exhibited enrichment for neuronal subtype markers associated with peptidergic nociceptors and myelinated sensory neurons, which are known to be affected in FD. In summary, this study has identified critical tissue-specific gene networks underlying the etiology of FD and provides new insights into the molecular basis of the disease.

Genomics 2 Proteins portal: A resource and discovery tool for linking genetic screening outputs to protein sequences and structures

Recent advances in AI-based methods have revolutionized the field of structural biology. Concomitantly, high-throughput sequencing and functional genomics technologies have enabled the detection and generation of variants at an unprecedented scale. However, efficient tools and resources are needed to link these two disparate data types - to "map" variants onto protein structures, to better understand how the variation causes disease and thereby design therapeutics. Here we present the Genomics 2 Proteins Portal (G2P; g2p.broadinstitute.org/): a human proteome-wide resource that maps 19,996,443 genetic variants onto 42,413 protein sequences and 77,923 structures, with a comprehensive set of structural and functional features. Additionally, the G2P portal generalizes the capability of linking genomics to proteins beyond databases by allowing users to interactively upload protein residue-wise annotations (variants, scores, etc.) as well as the protein structure to establish the connection. The portal serves as an easy-to-use discovery tool for researchers and scientists to hypothesize the structure-function relationship between natural or synthetic variations and their molecular phenotype.

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.

Ensemble-based design of tau to inhibit aggregation while preserving biological activity

The microtubule-associated protein tau is implicated in neurodegenerative diseases characterized by amyloid formation. Mutations associated with frontotemporal dementia increase tau aggregation propensity and disrupt its endogenous microtubule-binding activity. The structural relationship between aggregation propensity and biological activity remains unclear. We employed a multi-disciplinary approach, including computational modeling, NMR, cross-linking mass spectrometry, and cell models to design tau sequences that stabilize its structural ensemble. Our findings reveal that substitutions near the conserved 'PGGG' beta-turn motif can modulate local conformation, more stably engaging in interactions with the 306 VQIVYK 311 amyloid motif to decrease aggregation in vitro and in cells. Designed tau sequences maintain microtubule binding and explain why 3R isoforms of tau exhibit reduced pathogenesis over 4R isoforms. We propose a simple mechanism to reduce the formation of pathogenic species while preserving biological function, offering insights for therapeutic strategies aimed at reducing protein misfolding in neurodegenerative diseases.

Epileptic Encephalopathy GABRB Structural Variants Share Common Gating and Trafficking Defects

Variants in the GABRB gene, which encodes the β subunit of the GABAA receptor, have been implicated in various epileptic encephalopathies and related neurodevelopmental disorders such as Dravet syndrome and Angelman syndrome. These conditions are often associated with early-onset seizures, developmental regression, and cognitive impairments. The severity and specific features of these encephalopathies can differ based on the nature of the genetic variant and its impact on GABAA receptor function. These variants can lead to dysfunction in GABAA receptor-mediated inhibition, resulting in an imbalance between neuronal excitation and inhibition that contributes to the development of seizures. Here, 13 de novo EE-associated GABRB variants, occurring as missense mutations, were analyzed to determine their impact on protein stability and flexibility, channel function, and receptor biogenesis. Our results showed that all mutations studied significantly impact the protein structure, altering protein stability, flexibility, and function to varying degrees. Variants mapped to the GABA-binding domain, coupling zone, and pore domain significantly impact the protein structure, modifying the β+/α- interface of the receptor and altering channel activation and receptor trafficking. Our study proposes that the extent of loss or gain of GABAA receptor function can be elucidated by identifying the specific structural domain impacted by mutation and assessing the variability in receptor structural dynamics. This paves the way for future studies to explore and uncover links between the incidence of a variant in the receptor topology and the severity of the related disease.

Rendering protein mutation movies with MutAmore

BACKGROUND

The success of AlphaFold2 in reliable protein three-dimensional (3D) structure prediction, assists the move of structural biology toward studies of protein dynamics and mutational impact on structure and function. This transition needs tools that qualitatively assess alternative 3D conformations.

RESULTS

We introduce MutAmore, a bioinformatics tool that renders individual images of protein 3D structures for, e.g., sequence mutations into a visually intuitive movie format. MutAmore streamlines a pipeline casting single amino-acid variations (SAVs) into a dynamic 3D mutation movie providing a qualitative perspective on the mutational landscape of a protein. By default, the tool first generates all possible variants of the sequence reachable through SAVs (L*19 for proteins with L residues). Next, it predicts the structural conformation for all L*19 variants using state-of-the-art models. Finally, it visualizes the mutation matrix and produces a color-coded 3D animation. Alternatively, users can input other types of variants, e.g., from experimental structures.

CONCLUSION

MutAmore samples alternative protein configurations to study the dynamical space accessible from SAVs in the post-AlphaFold2 era of structural biology. As the field shifts towards the exploration of alternative conformations of proteins, MutAmore aids in the understanding of the structural impact of mutations by providing a flexible pipeline for the generation of protein mutation movies using current and future structure prediction models.

Genome-wide prediction of pathogenic gain- and loss-of-function variants from ensemble learning of a diverse feature set

Gain-of-function (GOF) variants give rise to increased/novel protein functions whereas loss-of-function (LOF) variants lead to diminished protein function. Experimental approaches for identifying GOF and LOF are generally slow and costly, whilst available computational methods have not been optimized to discriminate between GOF and LOF variants. We have developed LoGoFunc, a machine learning method for predicting pathogenic GOF, pathogenic LOF, and neutral genetic variants, trained on a broad range of gene-, protein-, and variant-level features describing diverse biological characteristics. LoGoFunc outperforms other tools trained solely to predict pathogenicity for identifying pathogenic GOF and LOF variants and is available at https://itanlab.shinyapps.io/goflof/ .

ALS-Associated KIF5A Mutation Causes Locomotor Deficits Associated with Cytoplasmic Inclusions, Alterations of Neuromuscular Junctions, and Motor Neuron Loss

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease affecting motor neurons. Recently, genome-wide association studies identified KIF5A as a new ALS-causing gene. KIF5A encodes a protein of the kinesin-1 family, allowing the anterograde transport of cargos along the microtubule rails in neurons. In ALS patients, mutations in the KIF5A gene induce exon 27 skipping, resulting in a mutated protein with a new C-terminal region (KIF5A Δ27). To understand how KIF5A Δ27 underpins the disease, we developed an ALS-associated KIF5A Drosophila model. When selectively expressed in motor neurons, KIF5A Δ27 alters larval locomotion as well as morphology and synaptic transmission at neuromuscular junctions in both males and females. We show that the distribution of mitochondria and synaptic vesicles is profoundly disturbed by KIF5A Δ27 expression. That is consistent with the numerous KIF5A Δ27-containing inclusions observed in motor neuron soma and axons. Moreover, KIF5A Δ27 expression leads to motor neuron death and reduces life expectancy. Our in vivo model reveals that a toxic gain of function underlies the pathogenicity of ALS-linked KIF5A mutant.SIGNIFICANCE STATEMENT Understanding how a mutation identified in patients with amyotrophic lateral sclerosis (ALS) causes the disease and the loss of motor neurons is crucial to fight against this disease. To this end, we have created a Drosophila model based on the motor neuron expression of the KIF5A mutant gene, recently identified in ALS patients. KIF5A encodes a kinesin that allows the anterograde transport of cargos. This model recapitulates the main features of ALS, including alterations of locomotion, synaptic neurotransmission, and morphology at neuromuscular junctions, as well as motor neuron death. KIF5A mutant is found in cytoplasmic inclusions, and its pathogenicity is because of a toxic gain of function.

Mining cancer genomes for change-of-metabolic-function mutations

Enzymes with novel functions are needed to enable new organic synthesis techniques. Drawing inspiration from gain-of-function cancer mutations that functionally alter proteins and affect cellular metabolism, we developed METIS (Mutated Enzymes from Tumors In silico Screen). METIS identifies metabolism-altering cancer mutations using mutation recurrence rates and protein structure. We used METIS to screen 298,517 cancer mutations and identify 48 candidate mutations, including those previously identified to alter enzymatic function. Unbiased metabolomic profiling of cells exogenously expressing a candidate mutant (OGDHLp.A400T) supports an altered phenotype that boosts in vitro production of xanthosine, a pharmacologically useful chemical that is currently produced using unsustainable, water-intensive methods. We then applied METIS to 49 million cancer mutations, yielding a refined set of candidates that may impart novel enzymatic functions or contribute to tumor progression. Thus, METIS can be used to identify and catalog potentially-useful cancer mutations for green chemistry and therapeutic applications.

Speos: an ensemble graph representation learning framework to predict core gene candidates for complex diseases

Understanding phenotype-to-genotype relationships is a grand challenge of 21st century biology with translational implications. The recently proposed "omnigenic" model postulates that effects of genetic variation on traits are mediated by core-genes and -proteins whose activities mechanistically influence the phenotype, whereas peripheral genes encode a regulatory network that indirectly affects phenotypes via core gene products. Here, we develop a positive-unlabeled graph representation-learning ensemble-approach based on a nested cross-validation to predict core-like genes for diverse diseases using Mendelian disorder genes for training. Employing mouse knockout phenotypes for external validations, we demonstrate that core-like genes display several key properties of core genes: Mouse knockouts of genes corresponding to our most confident predictions give rise to relevant mouse phenotypes at rates on par with the Mendelian disorder genes, and all candidates exhibit core gene properties like transcriptional deregulation in disease and loss-of-function intolerance. Moreover, as predicted for core genes, our candidates are enriched for drug targets and druggable proteins. In contrast to Mendelian disorder genes the new core-like genes are enriched for druggable yet untargeted gene products, which are therefore attractive targets for drug development. Interpretation of the underlying deep learning model suggests plausible explanations for our core gene predictions in form of molecular mechanisms and physical interactions. Our results demonstrate the potential of graph representation learning for the interpretation of biological complexity and pave the way for studying core gene properties and future drug development.

A FEN 1-driven DNA walker-like reaction coupling with magnetic bead-based separation for specific SNP detection

Single-nucleotide polymorphism (SNP) plays a key role in the carcinogenesis of the human genome, and understanding the intrinsic relationship between individual genetic variations and carcinogenesis lies heavily in the establishment of a precise and sensitive SNP detection platform. Given this, a powerful and reliable SNP detection platform is proposed by a flap endonuclease 1 (FEN 1)-driven DNA walker-like reaction coupling with a magnetic bead (MB)-based separation. A carboxyfluorescein (FAM)-labeled downstream probe (DP) was decorated on a streptavidin magnetic bead (SMB). The target DNA, as a walker strand, was captured by hybridization with DP and an upstream probe (UP) to form a three-base overlapping structure and execute the walking function on the surface of SMB. FEN 1 was employed to specifically recognize the three-base overlapping structure and cut the 5'flap at the SNP site to report the walking event and signal amplification. Considering the fact that the fluorescence was labeled on the cleavage and uncleavage sequences of DP and the target DNA-triggered walking event was undistinguishable from the mixtures, magnetic separation came in handy for cleavage probe (CP) isolation and discrimination of the amplified signal from the background signal. In comparison with the conventional DNA walker reaction, this strategy was coupling with SMB-based separation, thus promising a powerful and reliable method for SNP detection and signal amplification.

Heterogeneous splicing patterns resulting from KIF5A variants associated with amyotrophic lateral sclerosis

Single-nucleotide variants (SNVs) in the gene encoding Kinesin Family Member 5A (KIF5A), a neuronal motor protein involved in anterograde transport along microtubules, have been associated with amyotrophic lateral sclerosis (ALS). ALS is a rapidly progressive and fatal neurodegenerative disease that primarily affects the motor neurons. Numerous ALS-associated KIF5A SNVs are clustered near the splice-site junctions of the penultimate exon 27 and are predicted to alter the carboxy-terminal (C-term) cargo-binding domain of KIF5A. Mis-splicing of exon 27, resulting in exon exclusion, is proposed to be the mechanism by which these SNVs cause ALS. Whether all SNVs proximal to exon 27 result in exon exclusion is unclear. To address this question, we designed an in vitro minigene splicing assay in human embryonic kidney 293 cells, which revealed heterogeneous site-specific effects on splicing: only 5' splice-site (5'ss) SNVs resulted in exon skipping. We also quantified splicing in select clustered, regularly interspaced, short palindromic repeats-edited human stem cells, differentiated to motor neurons, and in neuronal tissues from a 5'ss SNV knock-in mouse, which showed the same result. Moreover, the survival of representative 3' splice site, 5'ss, and truncated C-term variant KIF5A (v-KIF5A) motor neurons was severely reduced compared with wild-type motor neurons, and overt morphological changes were apparent. While the total KIF5A mRNA levels were comparable across the cell lines, the total KIF5A protein levels were decreased for v-KIF5A lines, suggesting an impairment of protein synthesis or stability. Thus, despite the heterogeneous effect on ribonucleic acid splicing, KIF5A SNVs similarly reduce the availability of the KIF5A protein, leading to axonal transport defects and motor neuron pathology.

Rare de novo gain-of-function missense variants in DOT1L are associated with developmental delay and congenital anomalies

Misregulation of histone lysine methylation is associated with several human cancers and with human developmental disorders. DOT1L is an evolutionarily conserved gene encoding a lysine methyltransferase (KMT) that methylates histone 3 lysine-79 (H3K79) and was not previously associated with a Mendelian disease in OMIM. We have identified nine unrelated individuals with seven different de novo heterozygous missense variants in DOT1L through the Undiagnosed Disease Network (UDN), the SickKids Complex Care genomics project, and GeneMatcher. All probands had some degree of global developmental delay/intellectual disability, and most had one or more major congenital anomalies. To assess the pathogenicity of the DOT1L variants, functional studies were performed in Drosophila and human cells. The fruit fly DOT1L ortholog, grappa, is expressed in most cells including neurons in the central nervous system. The identified DOT1L variants behave as gain-of-function alleles in flies and lead to increased H3K79 methylation levels in flies and human cells. Our results show that human DOT1L and fly grappa are required for proper development and that de novo heterozygous variants in DOT1L are associated with a Mendelian disease.

CUX1-related neurodevelopmental disorder: deep insights into phenotype-genotype spectrum and underlying pathology

Heterozygous, pathogenic CUX1 variants are associated with global developmental delay or intellectual disability. This study delineates the clinical presentation in an extended cohort and investigates the molecular mechanism underlying the disorder in a Cux1+/- mouse model. Through international collaboration, we assembled the phenotypic and molecular information for 34 individuals (23 unpublished individuals). We analyze brain CUX1 expression and susceptibility to epilepsy in Cux1+/- mice. We describe 34 individuals, from which 30 were unrelated, with 26 different null and four missense variants. The leading symptoms were mild to moderate delayed speech and motor development and borderline to moderate intellectual disability. Additional symptoms were muscular hypotonia, seizures, joint laxity, and abnormalities of the forehead. In Cux1+/- mice, we found delayed growth, histologically normal brains, and increased susceptibility to seizures. In Cux1+/- brains, the expression of Cux1 transcripts was half of WT animals. Expression of CUX1 proteins was reduced, although in early postnatal animals significantly more than in adults. In summary, disease-causing CUX1 variants result in a non-syndromic phenotype of developmental delay and intellectual disability. In some individuals, this phenotype ameliorates with age, resulting in a clinical catch-up and normal IQ in adulthood. The post-transcriptional balance of CUX1 expression in the heterozygous brain at late developmental stages appears important for this favorable clinical course.

Lipid nanoparticles with PEG-variant surface modifications mediate genome editing in the mouse retina

Ocular delivery of lipid nanoparticle (LNPs) packaged mRNA can enable efficient gene delivery and editing. We generated LNP variants through the inclusion of positively charged-amine-modified polyethylene glycol (PEG)-lipids (LNPa), negatively charged-carboxyl-(LNPz) and carboxy-ester (LNPx) modified PEG-lipids, and neutral unmodified PEG-lipids (LNP). Subretinal injections of LNPa containing Cre mRNA in the mouse show tdTomato signal in the retinal pigmented epithelium (RPE) like conventional LNPs. Unexpectedly, LNPx and LNPz show 27% and 16% photoreceptor transfection, respectively, with striking localization extending from the photoreceptor synaptic pedicle to the outer segments, displaying pan-retinal distribution in the photoreceptors and RPE. LNPx containing Cas9 mRNA and sgAi9 leads to the formation of an oval elongated structure with a neutral charge resulting in 16.4% editing restricted to RPE. Surface modifications of LNPs with PEG variants can alter cellular tropism of mRNA. LNPs enable genome editing in the retina and in the future can be used to correct genetic mutations that lead to blindness.

The fitness cost of spurious phosphorylation

The fidelity of signal transduction requires the binding of regulatory molecules to their cognate targets. However, the crowded cell interior risks off-target interactions between proteins that are functionally unrelated. How such off-target interactions impact fitness is not generally known, but quantifying this is required to understand the constraints faced by cell systems as they evolve. Here, we use the model organism S. cerevisiae to inducibly express tyrosine kinases. Because yeast lacks bona fide tyrosine kinases, most of the resulting tyrosine phosphorylation is spurious. This provides a suitable system to measure the impact of artificial protein interactions on fitness. We engineered 44 yeast strains each expressing a tyrosine kinase, and quantitatively analysed their phosphoproteomes. This analysis resulted in ~30,000 phosphosites mapping to ~3,500 proteins. Examination of the fitness costs in each strain revealed a strong correlation between the number of spurious pY sites and decreased growth. Moreover, the analysis of pY effects on protein structure and on protein function revealed over 1000 pY events that we predict to be deleterious. However, we also find that a large number of the spurious pY sites have a negligible effect on fitness, possibly because of their low stoichiometry. This result is consistent with our evolutionary analyses demonstrating a lack of phosphotyrosine counter-selection in species with bona fide tyrosine kinases. Taken together, our results suggest that, alongside the risk for toxicity, the cell can tolerate a large degree of non-functional crosstalk as interaction networks evolve.

Losing, preserving, and restoring vision from neurodegeneration in the eye

The retina is a part of the brain that sits at the back of the eye, looking out onto the world. The first neurons of the retina are the rod and cone photoreceptors, which convert changes in photon flux into electrical signals that are the basis of vision. Rods and cones are frequent targets of heritable neurodegenerative diseases that cause visual impairment, including blindness, in millions of people worldwide. This review summarizes the diverse genetic causes of inherited retinal degenerations (IRDs) and their convergence onto common pathogenic mechanisms of vision loss. Currently, there are few effective treatments for IRDs, but recent advances in disparate areas of biology and technology (e.g., genome editing, viral engineering, 3D organoids, optogenetics, semiconductor arrays) discussed here enable promising efforts to preserve and restore vision in IRD patients with implications for neurodegeneration in less approachable brain areas.

Analysis of the Arabidopsis venosa4-0 mutant supports the role of VENOSA4 in dNTP metabolism

Human Sterile alpha motif and histidine-aspartate domain containing protein 1 (SAMHD1) functions as a dNTPase to maintain dNTP pool balance. In eukaryotes, the limiting step in de novo dNTP biosynthesis is catalyzed by RIBONUCLEOTIDE REDUCTASE (RNR). In Arabidopsis, the RNR1 subunit of RNR is encoded by CRINKLED LEAVES 8 (CLS8), and RNR2 by three paralogous genes, including TSO MEANING 'UGLY' IN CHINESE 2 (TSO2). In plants, DIFFERENTIAL DEVELOPMENT OF VASCULAR ASSOCIATED CELLS 1 (DOV1) catalyzes the first step of the de novo biosynthesis of purines. Here, to explore the role of VENOSA4 (VEN4), the most likely Arabidopsis ortholog of human SAMHD1, we studied the ven4-0 point mutation, whose leaf phenotype was stronger than those of its insertional alleles. Structural predictions suggested that the E249L substitution in the mutated VEN4-0 protein rigidifies its 3D structure. The morphological phenotypes of the ven4, cls8, and dov1 single mutants were similar, and those of the ven4 tso2 and ven4 dov1 double mutants were synergistic. The ven4-0 mutant had reduced levels of four amino acids related to dNTP biosynthesis, including glutamine and glycine, which are precursors in the de novo purine biosynthesis. Our results reveal high functional conservation between VEN4 and SAMHD1 in dNTP metabolism.

Predicting pathogenic protein variants

Machine-learning algorithm uses structure prediction to spot disease-causing mutations.

Evolutionary dynamics of genome size and content during the adaptive radiation of Heliconiini butterflies

Heliconius butterflies, a speciose genus of Müllerian mimics, represent a classic example of an adaptive radiation that includes a range of derived dietary, life history, physiological and neural traits. However, key lineages within the genus, and across the broader Heliconiini tribe, lack genomic resources, limiting our understanding of how adaptive and neutral processes shaped genome evolution during their radiation. Here, we generate highly contiguous genome assemblies for nine Heliconiini, 29 additional reference-assembled genomes, and improve 10 existing assemblies. Altogether, we provide a dataset of annotated genomes for a total of 63 species, including 58 species within the Heliconiini tribe. We use this extensive dataset to generate a robust and dated heliconiine phylogeny, describe major patterns of introgression, explore the evolution of genome architecture, and the genomic basis of key innovations in this enigmatic group, including an assessment of the evolution of putative regulatory regions at the Heliconius stem. Our work illustrates how the increased resolution provided by such dense genomic sampling improves our power to generate and test gene-phenotype hypotheses, and precisely characterize how genomes evolve.

In Silico Evaluation of the Potential Association of the Pathogenic Mutations of Alpha Synuclein Protein with Induction of Synucleinopathies

Alpha synuclein (α-Syn) is a neuronal protein encoded by the SNCA gene and is involved in the development of Parkinson's disease (PD). The objective of this study was to examine in silico the functional implications of non-synonymous single nucleotide polymorphisms (nsSNPs) in the SNCA gene. We used a range of computational algorithms such as sequence conservation, structural analysis, physicochemical properties, and machine learning. The sequence of the SNCA gene was analyzed, resulting in the mapping of 42,272 SNPs that are classified into different functional categories. A total of 177 nsSNPs were identified within the coding region; there were 20 variants that may influence the α-Syn protein structure and function. This identification was made by employing different analytical tools including SIFT, PolyPhen2, Mut-pred, SNAP2, PANTHER, PhD-SNP, SNP&Go, MUpro, Cosurf, I-Mut, and HOPE. Three mutations, V82A, K80E, and E46K, were selected for further examinations due to their spatial positioning within the α-Syn as determined by PyMol. Results indicated that these mutations may affect the stability and function of α-Syn. Then, a molecular dynamics simulation was conducted for the SNCA wildtype and the four mutant variants (p.A18G, p.V82A, p.K80E, and p.E46K). The simulation examined temperature, pressure, density, root-mean-square deviation (RMSD), root-mean-square fluctuation (RMSF), solvent-accessible surface area (SASA), and radius of gyration (Rg). The data indicate that the mutations p.V82A, p.K80E, and p.E46K reduce the stability and functionality of α-Syn. These findings highlight the importance of understanding the impact of nsSNPs on α-syn structure and function. Our results required verifications in further protein functional and case-control studies. After being verified these findings can be used in genetic testing for the early diagnosis of PD, the evaluation of the risk factors, and therapeutic approaches.

aenmd: annotating escape from nonsense-mediated decay for transcripts with protein-truncating variants

SUMMARY

DNA changes that cause premature termination codons (PTCs) represent a large fraction of clinically relevant pathogenic genomic variation. Typically, PTCs induce transcript degradation by nonsense-mediated mRNA decay (NMD) and render such changes loss-of-function alleles. However, certain PTC-containing transcripts escape NMD and can exert dominant-negative or gain-of-function (DN/GOF) effects. Therefore, systematic identification of human PTC-causing variants and their susceptibility to NMD contributes to the investigation of the role of DN/GOF alleles in human disease. Here we present aenmd, a software for annotating PTC-containing transcript-variant pairs for predicted escape from NMD. aenmd is user-friendly and self-contained. It offers functionality not currently available in other methods and is based on established and experimentally validated rules for NMD escape; the software is designed to work at scale, and to integrate seamlessly with existing analysis workflows. We applied aenmd to variants in the gnomAD, Clinvar, and GWAS catalog databases and report the prevalence of human PTC-causing variants in these databases, and the subset of these variants that could exert DN/GOF effects via NMD escape.

AVAILABILITY AND IMPLEMENTATION

aenmd is implemented in the R programming language. Code is available on GitHub as an R-package (github.com/kostkalab/aenmd.git), and as a containerized command-line interface (github.com/kostkalab/aenmd_cli.git).

A Stop-gain Variant c.220C>T (p.(Gln74*)) in FLNB Segregates with Spondylocarpotarsal Synostosis Syndrome in a Consanguineous Family

Spondylocarpotarsal synostosis (SCT) syndrome is a very rare and severe form of skeletal dysplasia. The hallmark features of SCT are disproportionate short stature, scoliosis, fusion of carpal and tarsal bones, and clubfoot. Other common manifestations are cleft palate, conductive and sensorineural hearing loss, joint stiffness, and dental enamel hypoplasia. Homozygous variants in FLNB are known to cause SCT. This study was aimed to investigate the phenotypic and genetic basis of unique presentation of SCT syndrome segregating in a consanguineous Pakistani family. Three of the four affected siblings evaluated had severe short stature, short trunk, short neck, kyphoscoliosis, pectus carinatum, and winged scapula. The subjects had difficulty in walking and gait problems and complained of knee pain and backache. Roentgenographic examination of the eldest patient revealed gross anomalies in the axial skeleton including thoracolumbar and cervical fusion of ribs, severe kyphoscoliosis, thoracic and lumbar lordosis, coxa valga, fusion of certain carpals and tarsals, and clinodactyly. The patients had normal faces and lacked other typical features of SCT like cleft palate, conductive and sensorineural hearing loss, joint stiffness, and dental enamel hypoplasia. Whole exome sequencing (WES) of two affected siblings led to the discovery of a rare stop-gain variant c.220C>T (p.(Gln74*)) in exon 1 of the FLNB gene. The variant was homozygous and segregated with the malformation in this family. This study reports extensive phenotypic variability in SCT and expands the mutation spectrum of FLNB.

Meiotic Chromosome Structure, the Synaptonemal Complex, and Infertility

In meiosis, homologous chromosome synapsis is mediated by a supramolecular protein structure, the synaptonemal complex (SC), that assembles between homologous chromosome axes. The mammalian SC comprises at least eight largely coiled-coil proteins that interact and self-assemble to generate a long, zipper-like structure that holds homologous chromosomes in close proximity and promotes the formation of genetic crossovers and accurate meiotic chromosome segregation. In recent years, numerous mutations in human SC genes have been associated with different types of male and female infertility. Here, we integrate structural information on the human SC with mouse and human genetics to describe the molecular mechanisms by which SC mutations can result in human infertility. We outline certain themes in which different SC proteins are susceptible to different types of disease mutation and how genetic variants with seemingly minor effects on SC proteins may act as dominant-negative mutations in which the heterozygous state is pathogenic.

Updated benchmarking of variant effect predictors using deep mutational scanning

The assessment of variant effect predictor (VEP) performance is fraught with biases introduced by benchmarking against clinical observations. In this study, building on our previous work, we use independently generated measurements of protein function from deep mutational scanning (DMS) experiments for 26 human proteins to benchmark 55 different VEPs, while introducing minimal data circularity. Many top-performing VEPs are unsupervised methods including EVE, DeepSequence and ESM-1v, a protein language model that ranked first overall. However, the strong performance of recent supervised VEPs, in particular VARITY, shows that developers are taking data circularity and bias issues seriously. We also assess the performance of DMS and unsupervised VEPs for discriminating between known pathogenic and putatively benign missense variants. Our findings are mixed, demonstrating that some DMS datasets perform exceptionally at variant classification, while others are poor. Notably, we observe a striking correlation between VEP agreement with DMS data and performance in identifying clinically relevant variants, strongly supporting the validity of our rankings and the utility of DMS for independent benchmarking.

De novo missense variants in phosphatidylinositol kinase PIP5KIγ underlie a neurodevelopmental syndrome associated with altered phosphoinositide signaling

Phosphoinositides (PIs) are membrane phospholipids produced through the local activity of PI kinases and phosphatases that selectively add or remove phosphate groups from the inositol head group. PIs control membrane composition and play key roles in many cellular processes including actin dynamics, endosomal trafficking, autophagy, and nuclear functions. Mutations in phosphatidylinositol 4,5 bisphosphate [PI(4,5)P2] phosphatases cause a broad spectrum of neurodevelopmental disorders such as Lowe and Joubert syndromes and congenital muscular dystrophy with cataracts and intellectual disability, which are thus associated with increased levels of PI(4,5)P2. Here, we describe a neurodevelopmental disorder associated with an increase in the production of PI(4,5)P2 and with PI-signaling dysfunction. We identified three de novo heterozygous missense variants in PIP5K1C, which encodes an isoform of the phosphatidylinositol 4-phosphate 5-kinase (PIP5KIγ), in nine unrelated children exhibiting intellectual disability, developmental delay, acquired microcephaly, seizures, visual abnormalities, and dysmorphic features. We provide evidence that the PIP5K1C variants result in an increase of the endosomal PI(4,5)P2 pool, giving rise to ectopic recruitment of filamentous actin at early endosomes (EEs) that in turn causes dysfunction in EE trafficking. In addition, we generated an in vivo zebrafish model that recapitulates the disorder we describe with developmental defects affecting the forebrain, including the eyes, as well as craniofacial abnormalities, further demonstrating the pathogenic effect of the PIP5K1C variants.

Sarcomeric gene variants among Indians with hypertrophic cardiomyopathy: A scoping review

Hypertrophic cardiomyopathy (HCM) is a genetic heart muscle disease that frequently causes sudden cardiac death (SCD) among young adults. Several pathogenic mutations in genes encoding the cardiac sarcomere have been identified as diagnostic factors for HCM and proposed as prognostic markers for SCD. The objective of this review was to determine the scope of available literature on the variants encoding sarcomere proteins associated with SCD reported among Indian patients with HCM. The eligibility criteria for the scoping review included full text articles that reported the results of genetic screening for sarcomeric gene mutations in HCM patients of Indian south Asian ancestry. We systematically reviewed studies from the databases of Medline, Scopus, Web of Science core collection and Google Scholar. The electronic search strategy included a combination of generic terms related to genetics, disease and population. The protocol of the study was registered with Open Science Framework (https://osf.io/53gde/). A total of 19 articles were identified that reported pathogenic or likely pathogenic (P/LP) variants within MYH7, MYBPC3, TNNT2, TNNI3 and TPM1 genes, that included 16 singletons, one de novo and one digenic mutation (MYH7/ TPM1) associated with SCD among Indian patients. Evidence from functional studies and familial segregation implied a plausible mechanistic role of these P/LP variants in HCM pathology. This scoping review has compiled all the P/LP variants reported to-date among Indian patients and summarized their association with SCD. Single homozygous, de novo and digenic mutations were observed to be associated with severe phenotypes compared to single heterozygous mutations. The abstracted genetic information was updated with reference sequence ID (rsIDs) and compiled into freely accessible HCMvar database, available at https://hcmvar.heartfailure.org.in/. This can be used as a population specific genetic database for reference by clinicians and researchers involved in the identification of diagnostic and prognostic markers for HCM.

Classification of PRSS1 variants responsible for chronic pancreatitis: An expert perspective from the Franco-Chinese GREPAN study group

BACKGROUND

PRSS1 was the first reported chronic pancreatitis (CP) gene. The existence of both gain-of-function (GoF) and gain-of-proteotoxicity (GoP) pathological PRSS1 variants, together with the fact that PRSS1 variants have been identified in CP subtypes spanning the range from monogenic to multifactorial, has made the classification of PRSS1 variants very challenging.

METHODS

All currently reported PRSS1 variants (derived primarily from two databases) were manually reviewed with respect to their clinical genetics, functional analysis and population allele frequency. They were classified by variant type and pathological mechanism within the framework of our recently proposed ACMG/AMP guidelines-based seven-category system.

RESULTS

The total number of distinct germline PRSS1 variants included for analysis was 100, comprising 3 copy number variants (CNVs), 12 5' and 3' variants, 19 intronic variants, 5 nonsense variants, 1 frameshift deletion variant, 6 synonymous variants, 1 in-frame duplication, 3 gene conversions and 50 missense variants. Based upon a combination of clinical genetic and functional analysis, population data and in silico analysis, we classified 26 variants (all 3 CNVs, the in-frame duplication, all 3 gene conversions and 19 missense) as "pathogenic", 3 variants (missense) as "likely pathogenic", 5 variants (four missense and one promoter) as "predisposing", 13 variants (all missense) as "unknown significance", 2 variants (missense) as "likely benign", and all remaining 51 variants as "benign".

CONCLUSIONS

We describe an expert classification of the 100 PRSS1 variants reported to date. The results have immediate implications for reclassifying many ClinVar-registered PRSS1 variants as well as providing optimal guidelines/standards for reporting PRSS1 variants.

The Spectrum of the Heterozygous Effect in Biallelic Mendelian Diseases-The Symptomatic Heterozygote Issue

Heterozygous carriers of pathogenic/likely pathogenic variants in autosomal recessive disorders seem to be asymptomatic. However, in recent years, an increasing number of case reports have suggested that mild and unspecific symptoms can occur in some heterozygotes, as symptomatic heterozygotes have been identified across different disease types, including neurological, neuromuscular, hematological, and pulmonary diseases. The symptoms are usually milder in heterozygotes than in biallelic variants and occur "later in life". The status of symptomatic heterozygotes as separate entities is often disputed, and alternative diagnoses are considered. Indeed, often only a thin line exists between dual, dominant, and recessive modes of inheritance and symptomatic heterozygosity. Interestingly, recent population studies have found global disease effects in heterozygous carriers of some genetic variants. What makes the few heterozygotes symptomatic, while the majority show no symptoms? The molecular basis of this phenomenon is still unknown. Possible explanations include undiscovered deep-splicing variants, genetic and environmental modifiers, digenic/oligogenic inheritance, skewed methylation patterns, and mutational burden. Symptomatic heterozygotes are rarely reported in the literature, mainly because most did not undergo the complete diagnostic procedure, so alternative diagnoses could not be conclusively excluded. However, despite the increasing accessibility to high-throughput technologies, there still seems to be a small group of patients with mild symptoms and just one variant of autosomes in biallelic diseases. Here, we present some examples, the current state of knowledge, and possible explanations for this phenomenon, and thus argue against the existing dominant/recessive classification.

An in vivo functional assay to characterize human STAT5B genetic variants during zebrafish development

Growth hormone (GH) binding to GH receptor activates janus kinase 2 (JAK2)-signal transducer and activator of transcription 5b (STAT5b) pathway, which stimulates transcription of insulin-like growth factor-1 (IGF1), insulin-like growth factor binding protein 3 (IGFBP3) and insulin-like growth factor acid-labile subunit (IGFALS). Although STAT5B deficiency was established as an autosomal recessive disorder, heterozygous dominant-negative STAT5B variants have been reported in patients with less severe growth deficit and milder immune dysfunction. We developed an in vivo functional assay in zebrafish to characterize the pathogenicity of three human STAT5B variants (p.Ala630Pro, p.Gln474Arg and p.Lys632Asn). Overexpression of human wild-type (WT) STAT5B mRNA and its variants led to a significant reduction of body length together with developmental malformations in zebrafish embryos. Overexpression of p.Ala630Pro, p.Gln474Arg or p.Lys632Asn led to an increased number of embryos with pericardial edema, cyclopia and bent spine compared with WT STAT5B. Although co-injection of WT and p.Gln474Arg and WT and p.Lys632Asn STAT5B mRNA in zebrafish embryos partially or fully rescues the length and the developmental malformations in zebrafish embryos, co-injection of WT and p.Ala630Pro STAT5B mRNA leads to a greater number of embryos with developmental malformations and a reduction in body length of these embryos. These results suggest that these variants could interfere with endogenous stat5.1 signaling through different mechanisms. In situ hybridization of zebrafish embryos overexpressing p.Gln474Arg and p.Lys632Asn STAT5B mRNA shows a reduction in igf1 expression. In conclusion, our study reveals the pathogenicity of the STAT5B variants studied.