Postzygotic single-nucleotide mosaicisms contribute to the etiology of autism spectrum disorder and autistic traits and the origin of mutations

Rare nonsynonymous germline and mosaic de novo variants in Japanese patients with schizophrenia

AIM

Whole-exome sequencing (WES) studies have revealed that germline de novo variants (gDNVs) contribute to the genetic etiology of schizophrenia. However, the contribution of mosaic DNVs (mDNVs) to the risk of schizophrenia remains to be elucidated. In the present study, we systematically investigated the gDNVs and mDMVs that contribute to the genetic etiology of schizophrenia in a Japanese population.

METHODS

We performed deep WES (depth: 460×) of 73 affected offspring and WES (depth: 116×) of 134 parents from 67 families with schizophrenia. Prioritized rare nonsynonymous gDNV and mDNV candidates were validated using Sanger sequencing and ultra-deep targeted amplicon sequencing (depth: 71,375×), respectively. Subsequently, we performed a Gene Ontology analysis of the gDNVs and mDNVs to obtain biological insights. Lastly, we selected DNVs in known risk genes for psychiatric and neurodevelopmental disorders.

RESULTS

We identified 62 gDNVs and 98 mDNVs. The Gene Ontology analysis of mDNVs implicated actin filament and actin cytoskeleton as candidate biological pathways. There were eight DNVs in known risk genes: splice region gDNVs in AKAP11 and CUL1; a frameshift gDNV in SHANK1; a missense gDNV in SRCAP; missense mDNVs in CTNNB1, GRIN2A, and TSC2; and a nonsense mDNV in ZFHX4.

CONCLUSION

Our results suggest the potential contributions of rare nonsynonymous gDNVs and mDNVs to the genetic etiology of schizophrenia. This is the first report of the mDNVs in schizophrenia trios, demonstrating their potential relevance to schizophrenia pathology.

Autism Spectrum Disorder Pathogenesis-A Cross-Sectional Literature Review Emphasizing Molecular Aspects

The etiology of autism spectrum disorder (ASD) has not yet been completely elucidated. Through time, multiple attempts have been made to uncover the causes of ASD. Different theories have been proposed, such as being caused by alterations in the gut-brain axis with an emphasis on gut dysbiosis, post-vaccine complications, and genetic or even autoimmune causes. In this review, we present data covering the main streams that focus on ASD etiology. Data collection occurred in many countries covering ethnically diverse subjects. Moreover, we aimed to show how the progress in genetic techniques influences the explanation of medical White Papers in the ASD area. There is no single evidence-based pathway that results in symptoms of ASD. Patient management has constantly only been symptomatic, and there is no ASD screening apart from symptom-based diagnosis and parent-mediated interventions. Multigene sequencing or epigenetic alterations hold promise in solving the disjointed molecular puzzle. Further research is needed, especially in the field of biogenetics and metabolomic aspects, because young children constitute the patient group most affected by ASD. In summary, to date, molecular research has confirmed multigene dysfunction as the causative factor of ASD, the multigene model with metabolomic influence would explain the heterogeneity in ASD, and it is proposed that ion channel dysfunction could play a core role in ASD pathogenesis.

Somatic mosaicism in schizophrenia brains reveals prenatal mutational processes

Germline mutations modulate the risk of developing schizophrenia (SCZ). Much less is known about the role of mosaic somatic mutations in the context of SCZ. Deep (239×) whole-genome sequencing (WGS) of brain neurons from 61 SCZ cases and 25 controls postmortem identified mutations occurring during prenatal neurogenesis. SCZ cases showed increased somatic variants in open chromatin, with increased mosaic CpG transversions (CpG>GpG) and T>G mutations at transcription factor binding sites (TFBSs) overlapping open chromatin, a result not seen in controls. Some of these variants alter gene expression, including SCZ risk genes and genes involved in neurodevelopment. Although these mutational processes can reflect a difference in factors indirectly involved in disease, increased somatic mutations at developmental TFBSs could also potentially contribute to SCZ.

Application of multiple mosaic callers improves post-zygotic mutation detection from exome sequencing data

PURPOSE

The gold standard for identification of post-zygotic variants (PZVs) is droplet digital polymerase chain reaction or high-depth sequencing across multiple tissues types. These approaches are yet to be systematically implemented for monogenic disorders. We developed PZV detection pipelines for correct classification of de novo variants.

METHOD

Our pipelines detect PZV in parents (gonosomal mosaicism [pGoM]) and children (somatic mosaicism, "M3"). We applied them to research exome sequencing (ES) data from the Australian Cerebral Palsy Biobank (n = 145 trios) and Simons Simplex Collection (n = 405 families). Candidate mosaic variants were validated using deep amplicon sequencing or droplet digital polymerase chain reaction.

RESULTS

69.2% (M3trio), 63.9% (M3single), and 92.7% (pGoM) of detected variants were validated, with 48.6%, 56.7%, and 26.2% of variants, respectively, meeting strict criteria for mosaicism. In the Australian Cerebral Palsy Biobank, 16.6% of probands and 20.7% of parents had at least 1 true-positive somatic or pGoM variant, respectively. A large proportion of PZVs detected in Simons Simplex Collection parents (79.8%) and child (94.5%) were not previously reported. We reclassified 3.7% to 8.0% of germline de novo variants as mosaic.

CONCLUSION

Many PZVs were incorrectly classified as germline variants or missed by previous approaches. Systematic application of our pipelines could increase genetic diagnostic rate, improve estimates of recurrence risk in families, and benefit novel disease gene identification.

Mutation in the mitochondrial chaperone TRAP1 leads to autism with more severe symptoms in males

There is increasing evidence of mitochondrial dysfunction in autism spectrum disorders (ASD), but the causal relationships are unclear. In an ASD patient whose identical twin was unaffected, we identified a postzygotic mosaic mutation p.Q639* in the TRAP1 gene, which encodes a mitochondrial chaperone of the HSP90 family. Additional screening of 176 unrelated ASD probands revealed an identical TRAP1 variant in a male patient who had inherited it from a healthy mother. Notably, newly generated knock-in Trap1 p.Q641* mice display ASD-related behavioral abnormalities that are more pronounced in males than in females. Accordingly, Trap1 p.Q641* mutation also resulted in sex-specific changes in synaptic plasticity, the number of presynaptic mitochondria, and mitochondrial respiration. Thus, the TRAP1 p.Q639* mutation is the first example of a monogenic ASD caused by impaired mitochondrial protein homeostasis.

Genomic Mosaicism of the Brain: Origin, Impact, and Utility

Genomic mosaicism describes the phenomenon where some but not all cells within a tissue harbor unique genetic mutations. Traditionally, research focused on the impact of genomic mosaicism on clinical phenotype-motivated by its involvement in cancers and overgrowth syndromes. More recently, we increasingly shifted towards the plethora of neutral mosaic variants that can act as recorders of cellular lineage and environmental exposures. Here, we summarize the current state of the field of genomic mosaicism research with a special emphasis on our current understanding of this phenomenon in brain development and homeostasis. Although the field of genomic mosaicism has a rich history, technological advances in the last decade have changed our approaches and greatly improved our knowledge. We will provide current definitions and an overview of contemporary detection approaches for genomic mosaicism. Finally, we will discuss the impact and utility of genomic mosaicism.

Exploring key genes and pathways associated with sex differences in autism spectrum disorder: integrated bioinformatic analysis

Autism spectrum disorder (ASD) is a heterogenous neurodevelopmental disorder marked by functional abnormalities in brain that causes social and linguistic difficulties. The incidence of ASD is more prevalent in males compared to females, but the underlying mechanism, as well as molecular indications for identifying sex-specific differences in ASD symptoms remain unknown. Thus, impacting the development of personalized strategy towards pharmacotherapy of ASD. The current study employs an integrated bioinformatic approach to investigate the genes and pathways uniquely associated with sex specific differences in autistic individuals. Based on microarray dataset (GSE6575) extracted from the gene expression omnibus, the dysregulated genes between the autistic and the neurotypical individuals for both sexes were identified. Gene set enrichment analysis was performed to ascertain biological activities linked to the dysregulated genes. Protein-protein interaction network analysis was carried out to identify hub genes. The identified hub genes were examined to determine their functions and involvement in the associated pathways using Enrichr. Additionally, hub genes were validated from autism-associated databases and the potential small molecules targeting the hub genes were identified. The present study utilized whole blood transcriptomic gene expression analysis data and identified 2211 and 958 differentially expressed unique genes in males and females respectively. The functional enrichment analysis revealed that male hub genes were functionally associated with RNA polymerase II mediated transcriptional regulation whereas female hub genes were involved in intracellular signal transduction and cell migration. The top male hub genes exhibited functional enrichment in tyrosine kinase signalling pathway. The pathway enrichment analysis of male hub genes indicates the enrichment of papillomavirus infection. Female hub genes were enriched in androgen receptor signalling pathway and functionally enriched in focal adhesion specific excision repair. Identified drug like candidates targeting these genes may serve as a potential sex specific therapeutics. Wortmannin for males, 5-Fluorouracil for females had the highest scores. Targeted and sex-specific pharmacotherapies may be created for the management of ASD. The current investigation identifies sex-specific molecular signatures derived from whole blood which may serve as a potential peripheral sex-specific biomarkers for ASD. The study also uncovers the possible pharmacological interventions against the selected genes/pathway, providing support in development of therapeutic strategies to mitigate ASD. However, experimental proofs on biological systems are warranted.

The Importance of Large-Scale Genomic Studies to Unravel Genetic Risk Factors for Autism

Autism spectrum disorder (ASD) is a common and highly heritable neurodevelopmental disorder. During the last 15 years, advances in genomic technologies and the availability of increasingly large patient cohorts have greatly expanded our knowledge of the genetic architecture of ASD and its neurobiological mechanisms. Over two hundred risk regions and genes carrying rare de novo and transmitted high-impact variants have been identified. Additionally, common variants with small individual effect size are also important, and a number of loci are now being uncovered. At the same time, these new insights have highlighted ongoing challenges. In this perspective article, we summarize developments in ASD genetic research and address the enormous impact of large-scale genomic initiatives on ASD gene discovery.

In-Depth Genomic Analysis: The New Challenge in Congenital Heart Disease

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.

Genomic variation in neurons

Neurons born during the fetal period have extreme longevity and survive until the death of the individual because the human brain has highly limited tissue regeneration. The brain is comprised of an enormous variety of neurons each exhibiting different morphological and physiological characteristics and recent studies have further reported variations in their genome including chromosomal abnormalities, copy number variations, and single nucleotide mutations. During the early stages of brain development, the increasing number of neurons generated at high speeds has been proposed to lead to chromosomal instability. Additionally, mutations in the neuronal genome can occur in the mature brain. This observed genomic mosaicism in the brain can be produced by multiple endogenous and environmental factors and careful analyses of these observed variations in the neuronal genome remain central for our understanding of the genetic basis of neurological disorders.

Deep exome sequencing identifies enrichment of deleterious mosaic variants in neurodevelopmental disorder genes and mitochondrial tRNA regions in bipolar disorder

Bipolar disorder (BD) is a global medical issue, afflicting around 1% of the population with manic and depressive episodes. Despite various genetic studies, the genetic architecture and pathogenesis of BD have not been fully resolved. Besides germline variants, postzygotic mosaic variants are proposed as new candidate mechanisms contributing to BD. Here, we performed extensive deep exome sequencing (DES, ~300×) and validation experiments to investigate the roles of mosaic variants in BD with 235 BD cases (194 probands of trios and 41 single cases) and 39 controls. We found an enrichment of developmental disorder (DD) genes in the genes hit by deleterious mosaic variants in BD (P = 0.000552), including a ClinVar-registered pathogenic variant in ARID2. An enrichment of deleterious mosaic variants was also observed for autism spectrum disorder (ASD) genes (P = 0.000428). The proteins coded by the DD/ASD genes with non-synonymous mosaic variants in BD form more protein-protein interaction than expected, suggesting molecular mechanisms shared with DD/ASD but restricted to a subset of cells in BD. We also found significant enrichment of mitochondrial heteroplasmic variants, another class of mosaic variants, in mitochondrial tRNA genes in BD (P = 0.0102). Among them, recurrent m.3243 A > G variants known as causal for mitochondrial diseases were found in two unrelated BD probands with allele fractions of 5-12%, lower than in mitochondrial diseases. Despite the limitation of using peripheral tissues, our DES investigation supports the possible contribution of deleterious mosaic variants in the nuclear genome responsible for severer phenotypes, such as DD/ASD, to the risk of BD and further demonstrates that the same paradigm can be applied to the mitochondrial genome. These results, as well as the enrichment of heteroplasmic mitochondrial tRNA variants in BD, add a new piece to the understanding of the genetic architecture of BD and provide general insights into the pathological roles of mosaic variants in human diseases.

Organization of Purkinje cell development by neuronal MEGF11 in cerebellar granule cells

As cerebellar granule cells (GCs) coordinate the formation of regular cerebellar networks during postnatal development, molecules in GCs are expected to be involved. Here, we test the effects of the knockdown (KD) of multiple epidermal growth factor-like domains protein 11 (MEGF11), which is a homolog of proteins mediating astrocytic phagocytosis but is substantially increased at the later developmental stages of GCs on cerebellar development. MEGF11-KD in GCs of developing mice results in abnormal cerebellar structures, including extensively ectopic Purkinje cell (PC) somas, and in impaired motor functions. MEGF11-KD also causes abnormally asynchronous synaptic release from GC axons, parallel fibers, before the appearance of abnormal cerebellar structures. Interestingly, blockade of this abnormal synaptic release restores most of the cerebellar structures. Thus, apart from phagocytic functions of its related homologs in astrocytes, MEGF11 in GCs promotes proper PC development and cerebellar network formation by regulating immature synaptic transmission.

Parental mosaicism detection and preimplantation genetic testing in families with multiple transmissions of de novo mutations

BACKGROUND

De novo mutations (DNMs) are linked with many severe early-onset disorders ranging from rare congenital malformation to intellectual disability. Conventionally, DNMs are considered to have an estimated recurrence rate of 1%. Recently, studies have revealed a higher prevalence of parental mosaicism, leading to a greater recurrence risk, resulting in a second child harbouring the same DNM as a previous child.

METHODS

In this study, we included 10 families with DNMs leading to adverse pregnancy outcomes. DNA was extracted from tissue samples, including parental peripheral blood, parental saliva and paternal sperm. High-throughput sequencing was used to screen for parental mosaicism with a depth of more than 5000× on average and a variant allele fraction (VAF) detection limit of 0.5%.

RESULTS

The presence of mosaicism was detected in sperms in two families, with VAFs of 2.8% and 2.5%, respectively. Both families have a history of multiple adverse pregnancies and DNMs shared by siblings. Preimplantation genetic testing (PGT) and prenatal diagnosis were performed in one family, thereby preventing the reoccurrence of DNMs.

CONCLUSION

This study is the first to report the successful implementation of PGT for monogenic/single gene defects in the parental mosaicism family. Our study suggests that mosaic detection of paternal sperm is warranted in families with recurrent DNMs leading to adverse pregnancy outcomes, and PGT can effectively block the transmission of the pathogenic mutation.

Technological and computational approaches to detect somatic mosaicism in epilepsy

Lesional epilepsy is a common and severe disease commonly associated with malformations of cortical development, including focal cortical dysplasia and hemimegalencephaly. Recent advances in sequencing and variant calling technologies have identified several genetic causes, including both short/single nucleotide and structural somatic variation. In this review, we aim to provide a comprehensive overview of the methodological advancements in this field while highlighting the unresolved technological and computational challenges that persist, including ultra-low variant allele fractions in bulk tissue, low availability of paired control samples, spatial variability of mutational burden within the lesion, and the issue of false-positive calls and validation procedures. Information from genetic testing in focal epilepsy may be integrated into clinical care to inform histopathological diagnosis, postoperative prognosis, and candidate precision therapies.

Control-independent mosaic single nucleotide variant detection with DeepMosaic

Mosaic variants (MVs) reflect mutagenic processes during embryonic development and environmental exposure, accumulate with aging and underlie diseases such as cancer and autism. The detection of noncancer MVs has been computationally challenging due to the sparse representation of nonclonally expanded MVs. Here we present DeepMosaic, combining an image-based visualization module for single nucleotide MVs and a convolutional neural network-based classification module for control-independent MV detection. DeepMosaic was trained on 180,000 simulated or experimentally assessed MVs, and was benchmarked on 619,740 simulated MVs and 530 independent biologically tested MVs from 16 genomes and 181 exomes. DeepMosaic achieved higher accuracy compared with existing methods on biological data, with a sensitivity of 0.78, specificity of 0.83 and positive predictive value of 0.96 on noncancer whole-genome sequencing data, as well as doubling the validation rate over previous best-practice methods on noncancer whole-exome sequencing data (0.43 versus 0.18). DeepMosaic represents an accurate MV classifier for noncancer samples that can be implemented as an alternative or complement to existing methods.

The human brain through the lens of somatic mosaicism

Every cell in the human brain possesses a unique genome that is the product of the accumulation of somatic mutations starting from the first postzygotic cell division and continuing throughout life. Somatic mosaicism in the human brain has been the focus of several recent efforts that took advantage of key technological innovations to start elucidating brain development, aging and disease directly in human tissue. On one side, somatic mutation occurring in progenitor cells has been used as a natural barcoding system to address cell phylogenies of clone formation and cell segregation in the brain lineage. On the other side, analyses of mutation rates and patterns in the genome of brain cells have revealed mechanisms of brain aging and disorder predisposition. In addition to the study of somatic mosaicism in the normal human brain, the contribution of somatic mutation has been investigated in both developmental neuropsychiatric and neurodegenerative disorders. This review starts with a methodological perspective on the study of somatic mosaicism to then cover the most recent findings in brain development and aging, and ends with the role of somatic mutations in brain disease. Thus, this review underlies what we have learned and what is still possible to discover by looking at somatic mosaicism in the brain genome.

MECP2 germline mosaicism plays an important part in the inheritance of Rett syndrome: a study of MECP2 germline mosaicism in males

BACKGROUND

Germline mosaicisms could be inherited to offspring, which considered as "de novo" in most cases. Paternal germline MECP2 mosaicism has been reported in fathers of girls with Rett syndrome (RTT) previously. For further study, we focused on MECP2 germline mosaicism in males, not only RTT fathers.

METHODS

Thirty-two fathers of RTT girls with MECP2 pathogenic mutations and twenty-five healthy adult males without history and family history of RTT or other genetic disorders were recruited. Sperm samples were collected and ten MECP2 hotspot mutations were detected by micro-droplet digital PCR (mDDPCR). And routine semen test was performed at the same time if the sample was sufficient. Additionally, blood samples were also detected for those with sperm MECP2 mosaicisms.

RESULTS

Nine fathers with RTT daughters (28.1%, 9/32) were found to have MECP2 mosaicism in their sperm samples, with the mutant allele fractions (MAFs) ranging from 0.05% to 7.55%. Only one father with MECP2 c.806delG germline mosaicism (MAF 7.55%) was found to have mosaicism in the blood sample, with the MAF was 0.28%. In the group of healthy adult males, MECP2 mosaicism was found in 7 sperm samples (28.0%, 7/25), with the MAFs ranging from 0.05% to 0.18%. None of the healthy adult males with MECP2 germline mosaicisms were found with MECP2 mosaicism in blood samples. There were no statistical differences in age, or the incidence of asthenospermia between fathers with RTT daughters and healthy adult males with MECP2 germline mosaicisms. Additionally, there was no linear correlation between MAFs of MECP2 mosaicisms and the age of males with germline MECP2 mosaicisms.

CONCLUSIONS

Germline MECP2 mosaicism could be found not only in fathers with RTT daughters but also in healthy adult males without family history of RTT. As germline mosaic mutations may be passed on to offspring which commonly known as "de novo", more attention should be paid to germline mosaicism, especially in families with a proband diagnosed with genetic disorders.

The emergence of genotypic divergence and future precision medicine applications

Genotypic divergence is a term adapted from population genetics and intimately linked to evolution. We use divergence here to emphasize the differences that set individuals apart in any cohort. The history of genetics is filled with descriptions of genotypic differences, but causal inference of interindividual biological variation has been scarce. We suggest that the practice of precision medicine requires a divergent approach, an approach dependent on the causal interpretation of previous convergent (and preliminary) knowledge in the field. This knowledge has relied on convergent descriptive syndromology (lumping), which has overemphasized a reductionistic gene determinism on the quest of seeking associations without causal understanding. Regulatory variants with small effect and somatic mutations are some of the modifying factors that lead to incomplete penetrance and intrafamilial variable expressivity often observed in apparently monogenic clinical disorders. A truly divergent approach to precision medicine requires splitting, that is, the consideration of different layers of genetic phenomena that interact causally in a nonlinear fashion. This chapter reviews convergences and divergences in genetics and genomics, aiming to discuss what can be causally understood to approximate the as-yet utopian lands of Precision Medicine for patients with neurodegenerative disorders.

Detecting genomic mosaicism in "de novo" genetic epilepsy by amplicon-based deep sequencing

AIM

To investigate the occurrence of mosaicism in epilepsy probands and their parents using amplicon-based deep sequencing (ADS).

METHODS

Patients were recruited from the outpatient of Peking University First Hospital. Two hundred and sixty-four probands with pathogenic variants tested by next-generation sequencing (NGS) were enrolled.

RESULTS

Mosaic variants were detected in seventeen disease-associated genes from 20 probands, 5 paternal, and 6 maternal parents. The frequency of mosaicism was 11.74% (31/264). Mosaicism in 11 genes was identified from 20 probands with the mutant allelic fractions (MAFs) of 12.95-38.00% in autosomal dominant genes. Five paternal mosaicisms were identified in genes with a MAF of 6.30-20.99%, and six maternal mosaic individuals with a MAF of 2.07-21.90%. Only four mosaic parents had milder seizure history. The affected sibling had the same phenotype consistent with that of the proband, who inherited the variant of SLC1A2 or STXBP1 from their unaffected mosaic mothers, respectively.

INTERPRETATION

Mosaic phenomenon is not rare in families with epilepsy. Phenotypes of mosaic parents were milder or normal. Mosaicism detection is helpful to identify the mutation origin and it provides a theoretical basis for prenatal diagnosis of family reproduction. ADS is a reliable way of mosaicism detection for clinical application.

Concomitant selenoenzyme inhibitor exposures as etiologic contributors to disease: Implications for preventative medicine

The physiological activities of selenium (Se) occur through enzymes that incorporate selenocysteine (Sec), a rare but important amino acid. The human genome includes 25 genes coding for Sec that employ it to catalyze challenging reactions. Selenoenzymes control thyroid hormones, calcium activities, immune responses, and perform other vital roles, but most are devoted to preventing and reversing oxidative damage. As the most potent intracellular nucleophile (pKa 5.2), Sec is vulnerable to binding by metallic and organic soft electrophiles (E*). These electron poor reactants initially form covalent bonds with nucleophiles such as cysteine (Cys) whose thiol (pKa 8.3) forms adducts which function as suicide substrates for selenoenzymes. These adducts orient E* to interact with Sec and since Se has a higher affinity for E* than sulfur, the E* transfers to Sec and irreversibly inhibits the enzyme's activity. Organic electrophiles have lower Se-binding affinities than metallic E*, but exposure sources are more abundant. Individuals with poor Se status are more vulnerable to the toxic effects of high E* exposures. The relative E*:Se stoichiometries remain undefined, but the aggregate effects of multiple E* exposures are predicted to be additive and possibly synergistic under certain conditions. The potential for the combined Se-binding effects of common pharmaceutical, dietary, or environmental E* require study, but even temporary loss of selenoenzyme activities would accentuate oxidative damage to tissues. As various degenerative diseases are associated with accumulating DNA damage, defining the effects of complementary E* exposures on selenoenzyme activities may enhance the ability of preventative medicine to support healthy aging.

Identification of Somatic Mutations From Bulk and Single-Cell Sequencing Data

Somatic mutations are DNA variants that occur after the fertilization of zygotes and accumulate during the developmental and aging processes in the human lifespan. Somatic mutations have long been known to cause cancer, and more recently have been implicated in a variety of non-cancer diseases. The patterns of somatic mutations, or mutational signatures, also shed light on the underlying mechanisms of the mutational process. Advances in next-generation sequencing over the decades have enabled genome-wide profiling of DNA variants in a high-throughput manner; however, unlike germline mutations, somatic mutations are carried only by a subset of the cell population. Thus, sensitive bioinformatic methods are required to distinguish mutant alleles from sequencing and base calling errors in bulk tissue samples. An alternative way to study somatic mutations, especially those present in an extremely small number of cells or even in a single cell, is to sequence single-cell genomes after whole-genome amplification (WGA); however, it is critical and technically challenging to exclude numerous technical artifacts arising during error-prone and uneven genome amplification in current WGA methods. To address these challenges, multiple bioinformatic tools have been developed. In this review, we summarize the latest progress in methods for identification of somatic mutations and the challenges that remain to be addressed in the future.

Genomics, convergent neuroscience and progress in understanding autism spectrum disorder

More than a hundred genes have been identified that, when disrupted, impart large risk for autism spectrum disorder (ASD). Current knowledge about the encoded proteins - although incomplete - points to a very wide range of developmentally dynamic and diverse biological processes. Moreover, the core symptoms of ASD involve distinctly human characteristics, presenting challenges to interpreting evolutionarily distant model systems. Indeed, despite a decade of striking progress in gene discovery, an actionable understanding of pathobiology remains elusive. Increasingly, convergent neuroscience approaches have been recognized as an important complement to traditional uses of genetics to illuminate the biology of human disorders. These methods seek to identify intersection among molecular-level, cellular-level and circuit-level functions across multiple risk genes and have highlighted developing excitatory neurons in the human mid-gestational prefrontal cortex as an important pathobiological nexus in ASD. In addition, neurogenesis, chromatin modification and synaptic function have emerged as key potential mediators of genetic vulnerability. The continued expansion of foundational 'omics' data sets, the application of higher-throughput model systems and incorporating developmental trajectories and sex differences into future analyses will refine and extend these results. Ultimately, a systems-level understanding of ASD genetic risk holds promise for clarifying pathobiology and advancing therapeutics.

Somatic Mutations Detected in Parkinson Disease Could Affect Genes With a Role in Synaptic and Neuronal Processes

The role of somatic mutations in complex diseases, including neurodevelopmental and neurodegenerative disorders, is becoming increasingly clear. However, to date, no study has shown their relation to Parkinson disease’s phenotype. To explore the relevance of embryonic somatic mutations in sporadic Parkinson disease, we performed whole-exome sequencing in blood and four brain regions of ten patients. We identified 59 candidate somatic single nucleotide variants (sSNVs) through sensitive calling and a careful filtering strategy (COSMOS). We validated 27 of them with amplicon-based ultra-deep sequencing, with a 70% validation rate for the highest-confidence variants. The identified sSNVs are in genes with synaptic functions that are co-expressed with genes previously associated with Parkinson disease. Most of the sSNVs were only called in blood but were also found in the brain tissues with ultra-deep amplicon sequencing, demonstrating the strength of multi-tissue sampling designs.

Genetic mosaicism in the human brain: from lineage tracing to neuropsychiatric disorders

Genetic mosaicism is the result of the accumulation of somatic mutations in the human genome starting from the first postzygotic cell generation and continuing throughout the whole life of an individual. The rapid development of next-generation and single-cell sequencing technologies is now allowing the study of genetic mosaicism in normal tissues, revealing unprecedented insights into their clonal architecture and physiology. The somatic variant repertoire of an adult human neuron is the result of somatic mutations that accumulate in the brain by different mechanisms and at different rates during development and ageing. Non-pathogenic developmental mutations function as natural barcodes that once identified in deep bulk or single-cell sequencing can be used to retrospectively reconstruct human lineages. This approach has revealed novel insights into the clonal structure of the human brain, which is a mosaic of clones traceable to the early embryo that contribute differentially to the brain and distinct areas of the cortex. Some of the mutations happening during development, however, have a pathogenic effect and can contribute to some epileptic malformations of cortical development and autism spectrum disorder. In this Review, we discuss recent findings in the context of genetic mosaicism and their implications for brain development and disease.

The Current Progress of Psychiatric Genomics

Psychiatric disorders such as bipolar disorder and schizophrenia are highly heritable. While the genetic contribution to psychiatric disorders is quite sure, specific genetic factors contributing to particular conditions have long been a mystery. Empowered by the initial report of the Human Genome Project, the analysis of the comprehensive set of the human genome, called "genomics," became possible. Subsequent development of large-scale genomic technologies enabled us to elucidate various disease-related genetic information, accelerating our understanding of various diseases. Genomic research on psychiatric disorders is not an exception. In this Review, I introduce significant advancements in psychiatric genomics with a special focus on our investigation of bipolar disorder. International consortiums and advocacy groups accelerate psychiatric genomics, increasing the sample size and statistical power for robust findings. The genetic architecture of schizophrenia has been elucidated in both common and rare variant studies. The genetic architecture of autism spectrum disorder (ASD) has been elucidated mainly by rare variant analysis. As to bipolar disorder, common variant analysis precedes rare variant analysis, but we are struggling to elucidate relevant rare variants. While the genomic approach has explained specific genetic factors for particular disorders, overlapping risk genes or pleiotropy has been observed more than expected. The boundary in the current nosology of psychiatric disorders is more or less challenged. To understand the genotype-phenotype relation more deeply, an attempt to understand phenotypes based on genotypes, called the "genotype first" approach, has started. I discuss this new approach for better understanding and treatment of psychiatric disorders.

Methods to Improve Molecular Diagnosis in Genomic Cold Cases in Pediatric Neurology

During the last decade, genetic testing has emerged as an important etiological diagnostic tool for Mendelian diseases, including pediatric neurological conditions. A genetic diagnosis has a considerable impact on disease management and treatment; however, many cases remain undiagnosed after applying standard diagnostic sequencing techniques. This review discusses various methods to improve the molecular diagnostic rates in these genomic cold cases. We discuss extended analysis methods to consider, non-Mendelian inheritance models, mosaicism, dual/multiple diagnoses, periodic re-analysis, artificial intelligence tools, and deep phenotyping, in addition to integrating various omics methods to improve variant prioritization. Last, novel genomic technologies, including long-read sequencing, artificial long-read sequencing, and optical genome mapping are discussed. In conclusion, a more comprehensive molecular analysis and a timely re-analysis of unsolved cases are imperative to improve diagnostic rates. In addition, our current understanding of the human genome is still limited due to restrictions in technologies. Novel technologies are now available that improve upon some of these limitations and can capture all human genomic variation more accurately. Last, we recommend a more routine implementation of high molecular weight DNA extraction methods that is coherent with the ability to use and/or optimally benefit from these novel genomic methods.

Mutational Landscape of Autism Spectrum Disorder Brain Tissue

Rare post-zygotic mutations in the brain are now known to contribute to several neurodevelopmental disorders, including autism spectrum disorder (ASD). However, due to the limited availability of brain tissue, most studies rely on estimates of mosaicism from peripheral samples. In this study, we undertook whole exome sequencing on brain tissue from 26 ASD brain donors from the Harvard Brain Tissue Resource Center (HBTRC) and ascertained the presence of post-zygotic and germline mutations categorized as pathological, including those impacting known ASD-implicated genes. Although quantification did not reveal enrichment for post-zygotic mutations compared with the controls (n = 15), a small number of pathogenic, potentially ASD-implicated mutations were identified, notably in TRAK1 and CLSTN3. Furthermore, germline mutations were identified in the same tissue samples in several key ASD genes, including PTEN, SC1A, CDH13, and CACNA1C. The establishment of tissue resources that are available to the scientific community will facilitate the discovery of new mutations for ASD and other neurodevelopmental disorders.

Modeling Somatic Mutations Associated With Neurodevelopmental Disorders in Human Brain Organoids

Neurodevelopmental disorders (NDDs) are a collection of diseases with early life onset that often present with developmental delay, cognitive deficits, and behavioral conditions. In some cases, severe outcomes such as brain malformations and intractable epilepsy can occur. The mutations underlying NDDs may be inherited or de novo, can be gain- or loss-of-function, and can affect one or more genes. Recent evidence indicates that brain somatic mutations contribute to several NDDs, in particular malformations of cortical development. While advances in sequencing technologies have enabled the detection of these somatic mutations, the mechanisms by which they alter brain development and function are not well understood due to limited model systems that recapitulate these events. Human brain organoids have emerged as powerful models to study the early developmental events of the human brain. Brain organoids capture the developmental progression of the human brain and contain human-enriched progenitor cell types. Advances in human stem cell and genome engineering provide an opportunity to model NDD-associated somatic mutations in brain organoids. These organoids can be tracked throughout development to understand the impact of somatic mutations on early human brain development and function. In this review, we discuss recent evidence that somatic mutations occur in the developing human brain, that they can lead to NDDs, and discuss how they could be modeled using human brain organoids.

Somatic Mosaicism and Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a genetically heterogenous neurodevelopmental disorder. In the early years of next-generation sequencing, de novo germline variants were shown to contribute to ASD risk. These germline mutations are present in all of the cells of an affected individual and can be detected in any tissue, including clinically accessible DNA sources such as blood or saliva. In recent years, studies have also implicated de novo somatic variants in ASD risk. These somatic mutations arise postzygotically and are present in only a subset of the cells of an affected individual. Depending on the developmental time and progenitor cell in which a somatic mutation occurs, it may be detectable in some tissues and not in others. Somatic mutations detectable at relatively low sequencing coverage in clinically accessible tissues are suggested to contribute to 3-5% of simplex ASD diagnoses, and "brain limited" somatic mutations have been identified in postmortem ASD brain tissue. Somatic mutations likely represent the genetic diagnosis in a proportion of otherwise unexplained individuals with ASD, and brain limited somatic mutations can be used as markers to discover risk genes, cell types, brain regions, and cellular pathways important for ASD pathogenesis and to potentially target for therapeutics.

Developmental and temporal characteristics of clonal sperm mosaicism

Throughout development and aging, human cells accumulate mutations resulting in genomic mosaicism and genetic diversity at the cellular level. Mosaic mutations present in the gonads can affect both the individual and the offspring and subsequent generations. Here, we explore patterns and temporal stability of clonal mosaic mutations in male gonads by sequencing ejaculated sperm. Through 300× whole-genome sequencing of blood and sperm from healthy men, we find each ejaculate carries on average 33.3 ± 12.1 (mean ± SD) clonal mosaic variants, nearly all of which are detected in serial sampling, with the majority absent from sampled somal tissues. Their temporal stability and mutational signature suggest origins during embryonic development from a largely immutable stem cell niche. Clonal mosaicism likely contributes a transmissible, predicted pathogenic exonic variant for 1 in 15 men, representing a life-long threat of transmission for these individuals and a significant burden on human population health.

Somatic copy number variants in neuropsychiatric disorders

Copy number variants (CNVs) have been implicated in neuropsychiatric disorders, with rare-inherited and de novo CNVs (dnCNVs) having large effects on disease liability. Recent studies started exploring a class of dnCNVs that occur post-zygotically, and are therefore present in some but not all cells of the body. Analogous to conditional mutations in animal models, the presence of risk mutations in a fraction of cells has the potential to enlighten how damaging mutations affect cell-type/cell-circuit specific pathologies leading to neuropsychiatric manifestations. Although mosaic CNVs appear to contribute to a modest fraction of risk (0.3-0.5%), expanding our insights about them with more sensitive experimental and statistical methods, has the potential to help clarify mechanisms of neuropsychiatric disease.

The landscape of somatic mutation in cerebral cortex of autistic and neurotypical individuals revealed by ultra-deep whole-genome sequencing

We characterize the landscape of somatic mutations-mutations occurring after fertilization-in the human brain using ultra-deep (~250×) whole-genome sequencing of prefrontal cortex from 59 donors with autism spectrum disorder (ASD) and 15 control donors. We observe a mean of 26 somatic single-nucleotide variants per brain present in ≥4% of cells, with enrichment of mutations in coding and putative regulatory regions. Our analysis reveals that the first cell division after fertilization produces ~3.4 mutations, followed by 2-3 mutations in subsequent generations. This suggests that a typical individual possesses ~80 somatic single-nucleotide variants present in ≥2% of cells-comparable to the number of de novo germline mutations per generation-with about half of individuals having at least one potentially function-altering somatic mutation somewhere in the cortex. ASD brains show an excess of somatic mutations in neural enhancer sequences compared with controls, suggesting that mosaic enhancer mutations may contribute to ASD risk.

Exploring the biological role of postzygotic and germinal de novo mutations in ASD

De novo mutations (DNMs), including germinal and postzygotic mutations (PZMs), are a strong source of causality for Autism Spectrum Disorder (ASD). However, the biological processes involved behind them remain unexplored. Our aim was to detect DNMs (germinal and PZMs) in a Spanish ASD cohort (360 trios) and to explore their role across different biological hierarchies (gene, biological pathway, cell and brain areas) using bioinformatic approaches. For the majority of the analysis, a combined ASD cohort (N = 2171 trios) was created using previously published data by the Autism Sequencing Consortium (ASC). New plausible candidate genes for ASD such as FMR1 and NFIA were found. In addition, genes harboring PZMs were significantly enriched for miR-137 targets in comparison with germinal DNMs that were enriched in GO terms related to synaptic transmission. The expression pattern of genes with PZMs was restricted to early mid-fetal cortex. In contrast, the analysis of genes with germinal DNMs revealed a spatio-temporal window from early to mid-fetal development stages, with expression in the amygdala, cerebellum, cortex and striatum. These results provide evidence of the pathogenic role of PZMs and suggest the existence of distinct mechanisms between PZMs and germinal DNMs that are influencing ASD risk.

Modelling genetic mosaicism of neurodevelopmental disorders in vivo by a Cre-amplifying fluorescent reporter

Genetic mosaicism, a condition in which an organ includes cells with different genotypes, is frequently present in monogenic diseases of the central nervous system caused by the random inactivation of the X-chromosome, in the case of X-linked pathologies, or by somatic mutations affecting a subset of neurons. The comprehension of the mechanisms of these diseases and of the cell-autonomous effects of specific mutations requires the generation of sparse mosaic models, in which the genotype of each neuron is univocally identified by the expression of a fluorescent protein in vivo. Here, we show a dual-color reporter system that, when expressed in a floxed mouse line for a target gene, leads to the creation of mosaics with tunable degree. We demonstrate the generation of a knockout mosaic of the autism/epilepsy related gene PTEN in which the genotype of each neuron is reliably identified, and the neuronal phenotype is accurately characterized by two-photon microscopy.

Linking Autism Risk Genes to Disruption of Cortical Development

Autism spectrum disorder (ASD) is a prevalent neurodevelopmental disorder characterized by impairments in social communication and social interaction, and the presence of repetitive behaviors and/or restricted interests. In the past few years, large-scale whole-exome sequencing and genome-wide association studies have made enormous progress in our understanding of the genetic risk architecture of ASD. While showing a complex and heterogeneous landscape, these studies have led to the identification of genetic loci associated with ASD risk. The intersection of genetic and transcriptomic analyses have also begun to shed light on functional convergences between risk genes, with the mid-fetal development of the cerebral cortex emerging as a critical nexus for ASD. In this review, we provide a concise summary of the latest genetic discoveries on ASD. We then discuss the studies in postmortem tissues, stem cell models, and rodent models that implicate recently identified ASD risk genes in cortical development.

Mosaicism in Human Health and Disease

Mosaicism refers to the occurrence of two or more genomes in an individual derived from a single zygote. Germline mosaicism is a mutation that is limited to the gonads and can be transmitted to offspring. Somatic mosaicism is a postzygotic mutation that occurs in the soma, and it may occur at any developmental stage or in adult tissues. Mosaic variation may be classified in six ways: (a) germline or somatic origin, (b) class of DNA mutation (ranging in scale from single base pairs to multiple chromosomes), (c) developmental context, (d) body location(s), (e) functional consequence (including deleterious, neutral, or advantageous), and (f) additional sources of mosaicism, including mitochondrial heteroplasmy, exogenous DNA sources such as vectors, and epigenetic changes such as imprinting and X-chromosome inactivation. Technological advances, including single-cell and other next-generation sequencing, have facilitated improved sensitivity and specificity to detect mosaicism in a variety of biological contexts.

MosaicBase: A Knowledgebase of Postzygotic Mosaic Variants in Noncancer Disease-related and Healthy Human Individuals

Mosaic variants resulting from postzygotic mutations are prevalent in the human genome and play important roles in human diseases. However, except for cancer-related variants, there is no collection of postzygotic mosaic variants in noncancer disease-related and healthy individuals. Here, we present MosaicBase, a comprehensive database that includes 6698 mosaic variants related to 266 noncancer diseases and 27,991 mosaic variants identified in 422 healthy individuals. Genomic and phenotypic information of each variant was manually extracted and curated from 383 publications. MosaicBase supports the query of variants with Online Mendelian Inheritance in Man (OMIM) entries, genomic coordinates, gene symbols, or Entrez IDs. We also provide an integrated genome browser for users to easily access mosaic variants and their related annotations for any genomic region. By analyzing the variants collected in MosaicBase, we find that mosaic variants that directly contribute to disease phenotype show features distinct from those of variants in individuals with mild or no phenotypes, in terms of their genomic distribution, mutation signatures, and fraction of mutant cells. MosaicBase will not only assist clinicians in genetic counseling and diagnosis but also provide a useful resource to understand the genomic baseline of postzygotic mutations in the general human population. MosaicBase is publicly available at http://mosaicbase.com/ or http://49.4.21.8:8000.

The role of somatic mosaicism in brain disease

In this review we discuss the importance of genetic somatic mosaicism and its impact on brain diseases. We start from introducing the different types of somatic mutations, their frequencies and abundances across development and lifespan. We then describe how weakness in DNA repair mechanisms influences their prevalence. Finally, we address their functional consequences in the brain and review recent research showing their unsuspected importance in several neurodevelopmental, psychiatric, and neurodegenerative diseases.

Genome aging: somatic mutation in the brain links age-related decline with disease and nominates pathogenic mechanisms

Aging is a mysterious process, not only controlled genetically but also subject to random damage that can accumulate over time. While DNA damage and subsequent mutation in somatic cells were first proposed as drivers of aging more than 60 years ago, whether and to what degree these processes shape the neuronal genome in the human brain could not be tested until recent technological breakthroughs related to single-cell whole-genome sequencing. Indeed, somatic single-nucleotide variants (SNVs) increase with age in the human brain, in a somewhat stochastic process that may nonetheless be controlled by underlying genetic programs. Evidence from the literature suggests that in addition to demonstrated increases in somatic SNVs during aging in normal brains, somatic mutation may also play a role in late-onset, sporadic neurodegenerative diseases, such as Alzheimer's disease and Parkinson's disease. In this review, we will discuss somatic mutation in the human brain, mechanisms by which somatic mutations occur and can be controlled, and how this process can impact human health.

EM-mosaic detects mosaic point mutations that contribute to congenital heart disease

BACKGROUND

The contribution of somatic mosaicism, or genetic mutations arising after oocyte fertilization, to congenital heart disease (CHD) is not well understood. Further, the relationship between mosaicism in blood and cardiovascular tissue has not been determined.

METHODS

We developed a new computational method, EM-mosaic (Expectation-Maximization-based detection of mosaicism), to analyze mosaicism in exome sequences derived primarily from blood DNA of 2530 CHD proband-parent trios. To optimize this method, we measured mosaic detection power as a function of sequencing depth. In parallel, we analyzed our cohort using MosaicHunter, a Bayesian genotyping algorithm-based mosaic detection tool, and compared the two methods. The accuracy of these mosaic variant detection algorithms was assessed using an independent resequencing method. We then applied both methods to detect mosaicism in cardiac tissue-derived exome sequences of 66 participants for which matched blood and heart tissue was available.

RESULTS

EM-mosaic detected 326 mosaic mutations in blood and/or cardiac tissue DNA. Of the 309 detected in blood DNA, 85/97 (88%) tested were independently confirmed, while 7/17 (41%) candidates of 17 detected in cardiac tissue were confirmed. MosaicHunter detected an additional 64 mosaics, of which 23/46 (50%) among 58 candidates from blood and 4/6 (67%) of 6 candidates from cardiac tissue confirmed. Twenty-five mosaic variants altered CHD-risk genes, affecting 1% of our cohort. Of these 25, 22/22 candidates tested were confirmed. Variants predicted as damaging had higher variant allele fraction than benign variants, suggesting a role in CHD. The estimated true frequency of mosaic variants above 10% mosaicism was 0.14/person in blood and 0.21/person in cardiac tissue. Analysis of 66 individuals with matched cardiac tissue available revealed both tissue-specific and shared mosaicism, with shared mosaics generally having higher allele fraction.

CONCLUSIONS

We estimate that ~ 1% of CHD probands have a mosaic variant detectable in blood that could contribute to cardiac malformations, particularly those damaging variants with relatively higher allele fraction. Although blood is a readily available DNA source, cardiac tissues analyzed contributed ~ 5% of somatic mosaic variants identified, indicating the value of tissue mosaicism analyses.

Accurate detection of mosaic variants in sequencing data without matched controls

Detection of mosaic mutations that arise in normal development is challenging, as such mutations are typically present in only a minute fraction of cells and there is no clear matched control for removing germline variants and systematic artifacts. We present MosaicForecast, a machine-learning method that leverages read-based phasing and read-level features to accurately detect mosaic single-nucleotide variants (SNVs) and indels, achieving a multifold increase in specificity compared to existing algorithms. Using single-cell sequencing and targeted sequencing, we validated 80–90% of the mosaic SNVs and 60–80% indels detected in human brain whole-genome sequencing data. Our method should help elucidate the contribution of mosaic somatic mutations to the origin and development of disease.

Genetic Causes and Modifiers of Autism Spectrum Disorder

Autism Spectrum Disorder (ASD) is one of the most prevalent neurodevelopmental disorders, affecting an estimated 1 in 59 children. ASD is highly genetically heterogeneous and may be caused by both inheritable and de novo gene variations. In the past decade, hundreds of genes have been identified that contribute to the serious deficits in communication, social cognition, and behavior that patients often experience. However, these only account for 10-20% of ASD cases, and patients with similar pathogenic variants may be diagnosed on very different levels of the spectrum. In this review, we will describe the genetic landscape of ASD and discuss how genetic modifiers such as copy number variation, single nucleotide polymorphisms, and epigenetic alterations likely play a key role in modulating the phenotypic spectrum of ASD patients. We also consider how genetic modifiers can alter convergent signaling pathways and lead to impaired neural circuitry formation. Lastly, we review sex-linked modifiers and clinical implications. Further understanding of these mechanisms is crucial for both comprehending ASD and for developing novel therapies.

Next-Generation Sequencing in Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a common disorder that causes substantial distress. Heritability studies consistently show a strong genetic contribution, raising the hope that identifying ASD-associated genetic variants will offer insights into neurobiology and ultimately therapeutics. Next-generation sequencing (NGS) enabled the identification of disruptive variants throughout protein-coding regions of the genome. Alongside large cohorts and novel statistical methods, these NGS methods revolutionized ASD gene discovery. NGS methods have also contributed substantially to functional genetic data, such as gene expression, used to understand the neurobiological consequences of disrupting these ASD-associated genes. These functional data are also critical for annotating the noncoding genome as whole-genome sequencing (WGS) begins to provide initial insights outside of protein-coding regions. NGS methods still have a major role to play, as do similarly transformative advances in stem cell and gene-editing methods, in translating genetic discoveries into a first generation of ASD therapeutics.

Over-expressed LOC101927196 suppressed oxidative stress levels and neuron cell proliferation in a rat model of autism through disrupting the Wnt signaling pathway by targeting FZD3

Accumulating evidence indicates that long non-coding RNAs (lncRNAs) play an important role in autism. Herein, we delineated the functions of LOC101927196 and its potential mitigation effect on a rat model of autism. We retrieved various bioinformatics databases and websites to screen differentially expressed lncRNAs associated with autism. Next, a rat model of autism was established with the neuron cells extracted for transfection of different plasmids. The regulatory effect of LOC101927196 on neuron cell proliferation, apoptosis as well as oxidative stress was also investigated. Firstly, microarray dataset GSE18123 revealed that LOC101927196 was poorly expressed in a rat model of autism. Poor development and growth and oxidative stress disorder were also observed in a rat model of autism. In addition, LOC101927196 targeting FZD3 played a vital role in a rat model of autism through the Wnt signaling pathway. Furthermore, we further demonstrated that over-expressed LOC101927196 blocked neuron cell proliferation and reduced oxidative stress levels, while promoting apoptosis by suppressing the activation of the Wnt signaling pathway. Our findings illustrate that up-regulated LOC101927196 attenuated oxidative stress disorder in a rat model of autism through suppressing the activation of Wnt signaling pathway by targeting FZD3.

Ontogenetic and Pathogenetic Views on Somatic Chromosomal Mosaicism

Intercellular karyotypic variability has been a focus of genetic research for more than 50 years. It has been repeatedly shown that chromosome heterogeneity manifesting as chromosomal mosaicism is associated with a variety of human diseases. Due to the ability of changing dynamically throughout the ontogeny, chromosomal mosaicism may mediate genome/chromosome instability and intercellular diversity in health and disease in a bottleneck fashion. However, the ubiquity of negligibly small populations of cells with abnormal karyotypes results in difficulties of the interpretation and detection, which may be nonetheless solved by post-genomic cytogenomic technologies. In the post-genomic era, it has become possible to uncover molecular and cellular pathways to genome/chromosome instability (chromosomal mosaicism or heterogeneity) using advanced whole-genome scanning technologies and bioinformatic tools. Furthermore, the opportunities to determine the effect of chromosomal abnormalities on the cellular phenotype seem to be useful for uncovering the intrinsic consequences of chromosomal mosaicism. Accordingly, a post-genomic review of chromosomal mosaicism in the ontogenetic and pathogenetic contexts appears to be required. Here, we review chromosomal mosaicism in its widest sense and discuss further directions of cyto(post)genomic research dedicated to chromosomal heterogeneity.

ATP1A3 mosaicism in families with alternating hemiplegia of childhood

Alternating hemiplegia of childhood (AHC) is a rare and severe neurodevelopmental disorder characterized by recurrent hemiplegic episodes. Most AHC cases are sporadic and caused by de novo ATP1A3 pathogenic variants. In this study, the aim was to identify the origin of ATP1A3 pathogenic variants in a Chinese cohort. In 105 probands including 101 sporadic and 4 familial cases, 98 patients with ATP1A3 pathogenic variants were identified, and 96.8% were confirmed as de novo. Micro-droplet digital polymerase chain reaction was applied for detecting ATP1A3 mosaicism in 80 available families. In blood samples, four asymptomatic parents, including two paternal and two maternal, and one proband with a milder phenotype were identified as mosaicism. Six (7.5%) parental mosaicisms were identified in multiple tissues, including four previously identified in blood and two additional cases identified from paternal sperms. Mosaicism was identified in multiple tissues with varied mutant allele fractions (MAFs, 0.03%-33.03%). The results suggested that MAF of mosaicism may be related to phenotype severity. This is the first systematic report of ATP1A3 mosaicism in AHC and showed mosaicism as an unrecognized source of previously considered "de novo" AHC. Identifying ATP1A3 mosaicism provides more evidence for estimating recurrence risk and has implications in genetic counseling of AHC.

Somatic mutations in the human brain: implications for psychiatric research

Psychiatric disorders such as schizophrenia and bipolar disorder are caused by complex gene-environment interactions. While recent advances in genomic technologies have enabled the identification of several risk variants for psychiatric conditions, including single-nucleotide variants and copy-number variations, these factors can explain only a portion of the liability to these disorders. Although non-inherited factors had previously been attributed to environmental causes, recent genomic analyses have demonstrated that de novo mutations are among the main non-inherited risk factors for several psychiatric conditions. Somatic mutations in the brain may also explain how stochastic developmental events and environmental insults confer risk for a psychiatric disorder following fertilization. Here, we review evidence regarding somatic mutations in the brains of individuals with and without neuropsychiatric diseases. We further discuss the potential biological mechanisms underlying somatic mutations in the brain as well as the technical issues associated with the detection of somatic mutations in psychiatric research.

Somatic mosaicism and neurodevelopmental disease

Traditionally, we have considered genetic mutations that cause neurodevelopmental diseases to be inherited or de novo germline mutations. Recently, we have come to appreciate the importance of de novo somatic mutations, which occur postzygotically and are thus present in only a subset of the cells of an affected individual. The advent of next-generation sequencing and single-cell sequencing technologies has shown that somatic mutations contribute to normal and abnormal human brain development. Somatic mutations are one important cause of neuronal migration and brain overgrowth disorders, as suggested by visible focal lesions. In addition, somatic mutations contribute to neurodevelopmental diseases without visible lesions, including epileptic encephalopathies, intellectual disability, and autism spectrum disorder, and may contribute to a broad range of neuropsychiatric diseases. Studying somatic mutations provides insight into the mechanisms underlying human brain development and neurodevelopmental diseases and has important implications for diagnosis and treatment.

De novo Mutations (DNMs) in Autism Spectrum Disorder (ASD): Pathway and Network Analysis

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder (NDD) defined by impairments in social communication and social interactions, accompanied by repetitive behavior and restricted interests. ASD is characterized by its clinical and etiological heterogeneity, which makes it difficult to elucidate the neurobiological mechanisms underlying its pathogenesis. Recently, de novo mutations (DNMs) have been recognized as strong source of genetic causality. Here, we review different aspects of the DNMs associated with ASD, including their functional annotation and classification. In addition, we also focus on the most recent advances in this area, such as the detection of PZMs (post-zygotic mutations), and we outline the main bioinformatics tools commonly employed to study these. Some of these approaches available allow DNMs to be analyzed in the context of gene networks and pathways, helping to shed light on the biological processes underlying ASD. To end this review, a brief insight into the future perspectives for genetic studies into ASD will be provided.