OBJECTIVE: Occurring once in every 2000 live births, craniosynostosis (CS) is the most frequent cranial birth defect. Although the genetic etiologies of syndromic CS cases are well defined, the genetic cause of most nonsyndromic cases remains unknown.
METHODS: The authors analyzed exome or RNA sequencing data from 876 children with nonsyndromic CS, including 291 case-parent trios and 585 additional probands. The authors also utilized the GeneMatcher platform and the Gabriella Miller Kids First genome sequencing project to identify additional CS patients with AXIN1 mutations.
RESULTS: The authors describe 11 patients with nonsyndromic CS harboring rare, damaging mutations in AXIN1, an inhibitor of Wnt signaling. AXIN1 regulates signaling upstream of key mediators of osteoblast differentiation. Three of the 6 mutations identified in trios occurred de novo in the proband, while 3 were transmitted from unaffected parents. Patients with nonsyndromic CS were highly enriched for mutations in AXIN1 compared to both expectation (p = 0.0008) and exome sequencing data from > 76,000 healthy controls (p = 2.3 × 10-6), surpassing the thresholds for genome-wide significance.
CONCLUSIONS: These findings describe the first phenotype associated with mutations in AXIN1, with mutations identified in approximately 1% of nonsyndromic CS cases. The results strengthen the existing link between Wnt signaling and maintenance of cranial suture patency and have implications for genetic testing in families with CS.

Neurodevelopmental disorders (NDDs) are a class of pathologies arising from perturbations in brain circuit formation and maturation with complex etiological triggers often classified as environmental and genetic. Neuropsychiatric conditions such as autism spectrum disorders (ASD), intellectual disability (ID), and attention deficit hyperactivity disorders (ADHD) are common NDDs characterized by their hereditary underpinnings and inherent heterogeneity. Genetic risk factors for NDDs are increasingly being identified in non-coding regions and proteins bound to them, including transcriptional regulators and chromatin remodelers. Importantly, de novo mutations are emerging as important contributors to NDDs and neuropsychiatric disorders. Recently, de novo mutations in transcriptional co-factor Zmiz1 or its regulatory regions have been identified in unrelated patients with syndromic ID and ASD. However, the role of Zmiz1 in brain development is unknown. Here, using publicly available databases and a Zmiz1 mutant mouse model, we reveal that Zmiz1 is highly expressed during embryonic brain development in mice and humans, and though broadly expressed across the brain, Zmiz1 is enriched in areas prominently impacted in ID and ASD such as cortex, hippocampus, and cerebellum. We investigated the relationship between Zmiz1 structure and pathogenicity of protein variants, the epigenetic marks associated with Zmiz1 regulation, and protein interactions and signaling pathways regulated by Zmiz1. Our analysis reveals that Zmiz1 regulates multiple developmental processes, including neurogenesis, neuron connectivity, and synaptic signaling. This work paves the way for future studies on the functions of Zmiz1 and highlights the importance of combining analysis of mouse models and human data.

Despite a relatively low mutation rate, the large number of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections has allowed for substantial genetic change, leading to a multitude of emerging variants. Using a recently determined mutation rate (per site replication), as well as within-host parameter estimates for symptomatic SARS-CoV-2 infection, we apply a stochastic transmission-bottleneck model to describe the survival probability of de novo SARS-CoV-2 mutations as a function of bottleneck size and selection coefficient. For narrow bottlenecks, we find that mutations affecting per-target-cell attachment rate (with phenotypes associated with fusogenicity and ACE2 binding) have similar transmission probabilities to mutations affecting viral load clearance (with phenotypes associated with humoral evasion). We further find that mutations affecting the eclipse rate (with phenotypes associated with reorganization of cellular metabolic processes and synthesis of viral budding precursor material) are highly favoured relative to all other traits examined. We find that mutations leading to reduced removal rates of infected cells (with phenotypes associated with innate immune evasion) have limited transmission advantage relative to mutations leading to humoral evasion. Predicted transmission probabilities, however, for mutations affecting innate immune evasion are more consistent with the range of clinically estimated household transmission probabilities for de novo mutations. This result suggests that although mutations affecting humoral evasion are more easily transmitted when they occur, mutations affecting innate immune evasion may occur more readily. We examine our predictions in the context of a number of previously characterized mutations in circulating strains of SARS-CoV-2. Our work offers both a null model for SARS-CoV-2 mutation rates and predicts which aspects of viral life history are most likely to successfully evolve, despite low mutation rates and repeated transmission bottlenecks.

Delayed fatherhood results in a higher risk of inheriting a new germline mutation that might result in a congenital disorder in the offspring. In particular, some FGFR3 mutations increase in frequency with age, but there are still a large number of uncharacterized FGFR3 mutations that could be expanding in the male germline with potentially early- or late-onset effects in the offspring. Here, we used digital polymerase chain reaction to assess the frequency and spatial distribution of 10 different FGFR3 missense substitutions in the sexually mature male germline. Our functional assessment of the receptor signaling of the variants with biophysical methods showed that 9 of these variants resulted in a higher activation of the receptor´s downstream signaling, resulting in 2 different expansion behaviors. Variants that form larger subclonal expansions in a dissected postmortem testis also showed a positive correlation of the substitution frequency with the sperm donor\'s age, and a high and ligand-independent FGFR3 activation. In contrast, variants that measured high FGFR3 signaling and elevated substitution frequencies independent of the donor\'s age did not result in measurable subclonal expansions in the testis. This suggests that promiscuous signal activation might also result in an accumulation of mutations before the sexual maturation of the male gonad with clones staying relatively constant in size throughout time. Collectively, these results provide novel insights into our understanding of the mutagenesis of driver mutations and their resulting mosaicism in the male germline with important consequences for the transmission and recurrence of associated disorders.

The use of next-generation sequencing has provided new insights into the causes and mechanisms of congenital heart disease (CHD). Examinations of the whole exome sequence have detected detrimental gene variations modifying single or contiguous nucleotides, which are characterised as pathogenic based on statistical assessments of families and correlations with congenital heart disease, elevated expression during heart development, and reductions in harmful protein-coding mutations in the general population. Patients with CHD and extracardiac abnormalities are enriched for gene classes meeting these criteria, supporting a common set of pathways in the organogenesis of CHDs. Single-cell transcriptomics data have revealed the expression of genes associated with CHD in specific cell types, and emerging evidence suggests that genetic mutations disrupt multicellular genes essential for cardiogenesis. Metrics and units are being tracked in whole-genome sequencing studies.

Long-read sequencing (LRS) techniques have been very successful in identifying structural variants (SVs). However, the high error rate of LRS made the detection of small variants (substitutions and short indels < 20 bp) more challenging. The introduction of PacBio HiFi sequencing makes LRS also suited for detecting small variation. Here we evaluate the ability of HiFi reads to detect de novo mutations (DNMs) of all types, which are technically challenging variant types and a major cause of sporadic, severe, early-onset disease.
We sequenced the genomes of eight parent-child trios using high coverage PacBio HiFi LRS (~ 30-fold coverage) and Illumina short-read sequencing (SRS) (~ 50-fold coverage). De novo substitutions, small indels, short tandem repeats (STRs) and SVs were called in both datasets and compared to each other to assess the accuracy of HiFi LRS. In addition, we determined the parent-of-origin of the small DNMs using phasing.
We identified a total of 672 and 859 de novo substitutions/indels, 28 and 126 de novo STRs, and 24 and 1 de novo SVs in LRS and SRS respectively. For the small variants, there was a 92 and 85% concordance between the platforms. For the STRs and SVs, the concordance was 3.6 and 0.8%, and 4 and 100% respectively. We successfully validated 27/54 LRS-unique small variants, of which 11 (41%) were confirmed as true de novo events. For the SRS-unique small variants, we validated 42/133 DNMs and 8 (19%) were confirmed as true de novo event. Validation of 18 LRS-unique de novo STR calls confirmed none of the repeat expansions as true DNM. Confirmation of the 23 LRS-unique SVs was possible for 19 candidate SVs of which 10 (52.6%) were true de novo events. Furthermore, we were able to assign 96% of DNMs to their parental allele with LRS data, as opposed to just 20% with SRS data.
HiFi LRS can now produce the most comprehensive variant dataset obtainable by a single technology in a single laboratory, allowing accurate calling of substitutions, indels, STRs and SVs. The accuracy even allows sensitive calling of DNMs on all variant levels, and also allows for phasing, which helps to distinguish true positive from false positive DNMs.

Molecular screening tools have significantly eased the assessment of potential germline susceptibility factors that may underlie the development of pediatric malignancies. Most of the hitherto published studies utilize the comparative analyses of the respective patients\' germline and tumor tissues for this purpose. Since this approach is not able to discriminate between de novo and inherited sequence variants, we performed whole exome trio analyses in a consecutive series of 131 children with various forms of hematologic malignancies and their parents. In total, we identified 458 de novo variants with a range from zero to 28 (median value = 3) per patient, although most of them (58%) had only up to three per exome. Overall, we identified bona fide cancer predisposing alterations in five of the investigated 131 (3.8%) patients. Three of them had de novo pathogenic lesions in the SOS1, PTPN11 and TP53 genes and two of them parentally inherited ones in the STK11 and PMS2 genes that are specific for a Peutz-Jeghers and a constitutional mismatch repair deficiency (CMMRD) syndrome, respectively. Notwithstanding that we did not identify a disease-specific alteration in the two cases with the highest number of de novo variants, one of them developed two almost synchronous malignancies: a myelodysplastic syndrome and successively within two months a cerebral astrocytoma. Moreover, we also found that the rate of de novo sequence variants in the offspring increased especially with the age of the father, but less so with that of the mother. We therefore conclude that trio analyses deliver an immediate overview about the inheritance pattern of the entire spectrum of sequence variants, which not only helps to securely identify the de novo or inherited nature of genuinely disease-related lesions, but also of all other less obvious variants that in one or the other way may eventually advance our understanding of the disease process.

Variant interpretation remains a major challenge in medical genetics. We developed Meta-Domain HotSpot (MDHS) to identify mutational hotspots across homologous protein domains. We applied MDHS to a dataset of 45,221 de novo mutations (DNMs) from 31,058 individuals with neurodevelopmental disorders (NDDs) and identified three significantly enriched missense DNM hotspots in the ion transport protein domain family (PF00520). The 37 unique missense DNMs that drive enrichment affect 25 genes, 19 of which were previously associated with NDDs. 3D protein structure modeling supports the hypothesis of function-altering effects of these mutations. Hotspot genes have a unique expression pattern in tissue, and we used this pattern alongside in silico predictors and population constraint information to identify candidate NDD-associated genes. We also propose a lenient version of our method, which identifies 32 hotspot positions across 16 different protein domains. These positions are enriched for likely pathogenic variation in clinical databases and DNMs in other genetic disorders.

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder with heterogeneous clinical presentation, variable severity, and multiple comorbidities. A complex underlying genetic architecture matches the clinical heterogeneity, and evidence indicates that several co-occurring brain disorders share a genetic component with ASD. In this study, we established a genetic similarity disease network approach to explore the shared genetics between ASD and frequent comorbid brain diseases (and subtypes), namely Intellectual Disability, Attention-Deficit/Hyperactivity Disorder, and Epilepsy, as well as other rarely co-occurring neuropsychiatric conditions in the Schizophrenia and Bipolar Disease spectrum. Using sets of disease-associated genes curated by the DisGeNET database, disease genetic similarity was estimated from the Jaccard coefficient between disease pairs, and the Leiden detection algorithm was used to identify network disease communities and define shared biological pathways. We identified a heterogeneous brain disease community that is genetically more similar to ASD, and that includes Epilepsy, Bipolar Disorder, Attention-Deficit/Hyperactivity Disorder combined type, and some disorders in the Schizophrenia Spectrum. To identify loss-of-function rare de novo variants within shared genes underlying the disease communities, we analyzed a large ASD whole-genome sequencing dataset, showing that ASD shares genes with multiple brain disorders from other, less genetically similar, communities. Some genes (e.g., SHANK3, ASH1L, SCN2A, CHD2, and MECP2) were previously implicated in ASD and these disorders. This approach enabled further clarification of genetic sharing between ASD and brain disorders, with a finer granularity in disease classification and multi-level evidence from DisGeNET. Understanding genetic sharing across disorders has important implications for disease nosology, pathophysiology, and personalized treatment.

Over the past two years, scientists throughout the world have completed more than 6 million SARS-CoV-2 genome sequences. Today, the number of SARS-CoV-2 genomes exceeds the total number of all other viral genomes. These genomes are a record of the evolution of SARS-CoV-2 in the human host, and provide information on the emergence of mutations. In this study, analysis of these sequenced genomes identified 296,728 de novo mutations (DNMs), and found that six types of base substitutions reached saturation in the sequenced genome population. Based on this analysis, a \"mutation blacklist\" of SARS-CoV-2 was compiled. The loci on the \"mutation blacklist\" are highly conserved, and these mutations likely have detrimental effects on virus survival, replication, and transmission. This information is valuable for SARS-CoV-2 research on gene function, vaccine design, and drug development. Through association analysis of DNMs and viral transmission rates, we identified 185 DNMs that positively correlated with the SARS-CoV-2 transmission rate, and these DNMs where classified as the \"mutation whitelist\" of SARS-CoV-2. The mutations on the \"mutation whitelist\" are beneficial for SARS-CoV-2 transmission and could therefore be used to evaluate the transmissibility of new variants. The occurrence of mutations and the evolution of viruses are dynamic processes. To more effectively monitor the mutations and variants of SARS-CoV-2, we built a SARS-CoV-2 mutation and variant monitoring and pre-warning system (MVMPS), which can monitor the occurrence and development of mutations and variants of SARS-CoV-2, as well as provide pre-warning for the prevention and control of SARS-CoV-2 (https://www.omicx.cn/). Additionally, this system could be used in real-time to update the \"mutation whitelist\" and \"mutation blacklist\" of SARS-CoV-2.