Whole-genome sequencing in autism identifies hot spots for de novo germline mutation

Rare damaging variants in the sex differences of congenital heart disease: an exome sequencing study

BACKGROUND

Congenital heart disease (CHD) exhibits a marked male predominance in birth prevalence, yet the genetic mechanisms underlying this sex disparity remain poorly understood. This study investigates the contribution of rare damaging variants on autosomes and the X chromosome to sex differences in foetal CHD.

METHODS

Parents of foetuses with CHD were recruited for the study. Rare damaging variants were identified by analysing whole-exome sequencing data from foetus-parental trios, and their contributions to sex differences were estimated through case-control studies. Functional enrichment analysis was conducted to assess functional differences in genetic variants between sexes.

FINDINGS

820 foetal probands with CHD were recruited, including 487 males and 333 females. We identified a significant enrichment of X-linked rare damaging variants, primarily driven by maternally inherited hemizygous variants (MIHVs) in male probands (OR = 1·84, P < 0·05), which accounted for 7·2% of male cases in our cohort. These variants were not found to be enriched in female probands. Additionally, X-linked rare damaging de novo variants (DNVs) were not enriched in either male or female probands (female probands: 1·8% versus female controls: 0·7%, P = 0·6789; no DNVs observed in males). Gene-level variant burden analysis revealed three X-linked CHD candidate genes: DCX, CACNA1F, and MAP3K15. Autosomal rare variants did not show significant differences in variant burdens between sexes. Notably, male probands showed specific functional enrichments in cilia-related pathways for autosomal recessive variants, as well as in chromatin remodelling and nervous system development pathways for autosomal DNVs.

INTERPRETATION

Male and female foetal CHD have significantly different genetic landscapes. The enrichment of X-linked rare damaging MIHVs in males provides a genetic explanation for the higher prevalence of CHD in males. This finding highlights the importance of incorporating sex-stratified approaches in clinical diagnostics and research.

FUNDING

Natural Science Foundation of China and Key research and development project of Hebei Province.

Duplex sequencing identifies unique characteristics of ENU-induced mutations in male mouse germ cells†

Germ cell mutagenicity testing is increasingly required for chemical risk assessment. Duplex sequencing is rapidly gaining acceptance as a method to assess in vivo mutagenesis, and as a valid alternative to transgenic rodent mutation models such as the MutaMouse. We used a duplex sequencing panel of 20 genomic targets and the transgenic rodent assay to measure mutations in the germ cells of MutaMouse males exposed to 0, 1, 2, or 5 mg/kg N-ethyl-N-nitrosourea for 28 days. Germ cells from the seminiferous tubules were collected 28 days post-exposure. The transgenic rodent assay showed a significant increase in mutant frequencies at the high (P < 0.001) and medium (P = 0.01) N-ethyl-N-nitrosourea doses relative to controls, while duplex sequencing revealed a significant increase (P < 0.001) in N-ethyl-N-nitrosourea-induced mutations only at the high dose. Duplex sequencing mutation frequencies were lower in genic than in intergenic targets, suggesting a protective role for transcription-coupled repair. Interestingly, we observed several unique germ cell characteristics with respect to duplex sequencing data from rodent somatic tissues: 1) larger inter-animal variability in clonally expanded mutations that affects the ability to detect significant increases in mutation frequency; 2) a target on chromosome 2 showing much higher susceptibility to spontaneous and chemical-induced mutagenesis than other targets; and 3) a mutation spectrum consistent with that observed in the offspring of N-ethyl-N-nitrosourea-treated males but not with the spectrum in bone marrow of directly-exposed males. These results suggest that duplex sequencing is a promising approach for characterizing germ cell mutagenesis and that mutagenic mechanisms operating in germ cells differ from those in somatic tissues.

Quantifying the effects of computational filter criteria on the accurate identification of de novo mutations at varying levels of sequencing coverage

The rate of spontaneous (de novo) germline mutation is a key parameter in evolutionary biology, impacting genetic diversity and contributing to the evolution of populations and species. Mutation rates themselves evolve over time but the mechanisms underlying the mutation rate variation observed across the Tree of Life remain largely to be elucidated. In recent years, whole genome sequencing has enabled the estimation of mutation rates for several organisms. However, due to a lack of community standards, many previous studies differ both empirically - most notably, in the depth of sequencing used to reliably identify de novo mutations - and computationally - utilizing different computational pipelines to detect germline mutations as well as different analysis strategies to mitigate technical artifacts - rendering comparisons between studies challenging. Using a pedigree of Western chimpanzees as an illustrative example, we here quantify the effects of commonly utilized quality metrics to reliably identify de novo mutations at different levels of sequencing coverage. We demonstrate that datasets with a mean depth of ≤ 30X are ill-suited for the detection of de novo mutations due to high false positive rates that can only be partially mitigated by computational filter criteria. In contrast, higher coverage datasets enable a comprehensive identification of de novo mutations at low false positive rates, with minimal benefits beyond a sequencing coverage of 60X, suggesting that future work should favor breadth (by sequencing additional individuals) over depth. Importantly, the simulation and analysis framework described here provides conceptual guidelines that will allow researchers to take study design and species-specific resources into account when determining computational filtering strategies for their organism of interest.

Estimating mutation rate and characterising single nucleotide de novo mutations in pigs

BACKGROUND

Direct estimates of mutation rates in humans have changed our understanding of evolutionary timing and de novo mutations (DNM) have been associated with several developmental disorders in humans. Livestock species, including pigs, can contribute to the study of DNM because of their ideal population structure and routine phenotype collection. In principle, there is the potential for livestock populations to quickly accumulate new genetic variants because of short generation intervals and high selection intensity. However, the impact of DNM on the fitness of individuals is not known and with current genomic selection programs they cannot contribute to estimated breeding values. The aims of our project were to detect and validate single nucleotide DNM in two commercial pig breeding lines, estimate the single nucleotide mutation rate, and characterise DNM.

RESULTS

We sequenced (150 bp paired end reads, 30X coverage) 46 pig trios from two commercial lines. Single nucleotide DNM were detected using a trio-aware method. We defined candidate DNM as single nucleotide variants (SNVs) found in heterozygous state in trio-offspring with both trio-parents homozygous for the reference allele. In this study, we estimate a lower threshold of the DNM rate in pigs of 6.3 × 10-9 per site per gamete. Our findings are consistent with those from other mammals and those published for a small number of livestock species. Most DNM we detected were in introns (47%) and intergenic regions (49%). The mutational spectrum in pigs differs from that in humans and we found several DNM predicted to have an effect on animal's fitness based on the base pair change and their location in the genome.

CONCLUSIONS

With this study, we have generated fundamental knowledge on mutation rate in a non-primate species and identified DNM that could have an impact on the fitness of individuals.

A structured coalescent model reveals deep ancestral structure shared by all modern humans

Understanding the history of admixture events and population size changes leading to modern humans is central to human evolutionary genetics. Here we introduce a coalescence-based hidden Markov model, cobraa, that explicitly represents an ancestral population split and rejoin, and demonstrate its application on simulated and real data across multiple species. Using cobraa, we present evidence for an extended period of structure in the history of all modern humans, in which two ancestral populations that diverged ~1.5 million years ago came together in an admixture event ~300 thousand years ago, in a ratio of ~80:20%. Immediately after their divergence, we detect a strong bottleneck in the major ancestral population. We inferred regions of the present-day genome derived from each ancestral population, finding that material from the minority correlates strongly with distance to coding sequence, suggesting it was deleterious against the majority background. Moreover, we found a strong correlation between regions of majority ancestry and human-Neanderthal or human-Denisovan divergence, suggesting the majority population was also ancestral to those archaic humans.

Comparing the predictors of mutability among healthy human tissues inferred from mutations in single-cell genome data

Studying mutation in healthy somatic tissues is the key for understanding the genesis of cancer and other genetic diseases. Mutation rate varies from site to site in the human genome by up to 100-fold and is influenced by numerous epigenetic and genetic factors including GC content, trinucleotide sequence context, and DNAse accessibility. These factors influence mutation at both local and regional scales and are often interrelated with one another, meaning that predicting mutability or uncovering its drivers requires modelling multiple factors and scales simultaneously. Historically, most investigations have focused either on analyzing the local sequence scale through triplet signatures or on examining the impact of epigenetic processes at larger scales, but not both concurrently. Additionally, sequencing technology limitations have restricted analyses of healthy mutations to coding regions (RNA-seq) or to those that have been influenced by selection (e.g. bulk samples from cancer tissue). Here, we leverage single-cell mutations and present a comprehensive analysis of epigenetic and genetic factors at multiple scales in the germline and 3 healthy somatic tissues. We create models that predict mutability with on average 2% error and find up to 63-fold variation among sites within the same tissue. We observe varying degrees of similarity between tissues: the mutability of genomic positions was 93.4% similar between liver and germline tissues, but sites in germline and skin were only 85.9% similar. We observe both universal and tissue-specific mutagenic processes in healthy tissues, with implications for understanding the maintenance of germline vs soma and the mechanisms underlying early tumorigenesis.

Characterizing the Rates and Patterns of De Novo Germline Mutations in the Aye-Aye (Daubentonia madagascariensis)

Given the many levels of biological variation in mutation rates observed to date in primates-spanning from species to individuals to genomic regions-future steps in our understanding of mutation rate evolution will not only be aided by a greater breadth of species coverage across the primate clade but also by a greater depth as afforded by an evaluation of multiple trios within individual species. In order to help bridge these gaps, we here present an analysis of a species representing one of the most basal splits on the primate tree (aye-ayes), combining whole-genome sequencing of seven parent-offspring trios from a three-generation pedigree with a novel computational pipeline that takes advantage of recently developed pan-genome graphs, thereby circumventing the application of (highly subjective) quality metrics that has previously been shown to result in notable differences in the detection of de novo mutations and ultimately estimates of mutation rates. This deep sampling has enabled both a detailed picture of parental age effects and sex dependency in mutation rates, which we here compare with previously studied primates, but has also provided unique insights into the nature of genetic variation in one of the most endangered primates on the planet.

Aging and tumors: a dynamic interaction

Aging is an inevitable physiological process in organisms, and the development of tumors is closely associated with cellular senescence. This article initially examines the role of cellular senescence in tumorigenesis, emphasizing the correlation between telomere length-a marker of cellular senescence-and tumor risk. Concurrently, the study explores the expression levels of senescence-associated markers, such as p16, p53, and mTOR, in the context of tumor development. Additionally, the study investigates the impact of tumors on cellular and organismal senescence, including the effects on immune system function and metabolic processes. Ultimately, the discussion explores the potential application of anti-aging strategies in tumor therapy and considers the possibility of utilizing senescence mechanisms as a novel therapeutic approach for tumors. This research provides novel insights into the complex interplay between senescence and tumor development, suggesting potential strategies for future preventative measures and therapeutic interventions.

Transgenerational effects of paternal exposures: the role of germline de novo mutations

Germline de novo mutations (DNMs) refer to spontaneous mutations arising during gametogenesis, resulting in genetic changes within germ cells that are subsequently transmitted to the next generation. While the impact of maternal exposures on germline DNMs has been extensively studied, more recent studies have begun to highlight the increasing importance of the effects of paternal factors. In this review, we have summarized the existing literature on how various exposures experienced by fathers affect the germline DNM burden in their spermatozoa, as well as their consequences for semen analysis parameters, pregnancy outcomes, and offspring health. A growing body of literature supports the conclusion that advanced paternal age (APA) correlates with a higher germline DNM rate in offspring. Furthermore, lifestyle choices, environmental toxins, assisted reproductive techniques (ART), and chemotherapy are associated with the accumulation of paternal DNMs in spermatozoa, with deleterious consequences for pregnancy outcomes and offspring health. Ultimately, our review highlights the clear importance of the germline DNM mode of inheritance, and the current understanding of how this is affected by various paternal factors. In addition, we explore conflicting reports or gaps of knowledge that should be addressed in future research.

Short tandem repeats delineate gene bodies across eukaryotes

Short tandem repeats (STRs) have emerged as important and hypermutable sites where genetic variation correlates with gene expression in plant and animal systems. Recently, it has been shown that a broad range of transcription factors (TFs) are affected by STRs near or in the DNA target binding site. Despite this, the distribution of STR motif repetitiveness in eukaryote genomes is still largely unknown. Here, we identify monomer and dimer STR motif repetitiveness in 5.1 billion 10-bp windows upstream of translation starts and downstream of translation stops in 25 million genes spanning 1270 species across the eukaryotic Tree of Life. We report that all surveyed genomes have gene-proximal shifts in motif repetitiveness. Within genomes, variation in gene-proximal repetitiveness landscapes correlated to the function of genes; genes with housekeeping functions were depleted in upstream and downstream repetitiveness. Furthermore, the repetitiveness landscapes correlated with TF binding sites, indicating that gene function has evolved in conjunction with cis-regulatory STRs and TFs that recognize repetitive sites. These results suggest that the hypermutability inherent to STRs is canalized along the genome sequence and contributes to regulatory and eco-evolutionary dynamics in all eukaryotes.

Resolving complex duplication variants in autism spectrum disorder using long-read genome sequencing

Rare or de novo structural variation, primarily in the form of copy number variants, is detected in 5%-10% of autism spectrum disorder (ASD) families. While complex structural variants involving duplications can generally be detected using microarray or short-read genome sequencing (GS), these methods frequently fail to characterize breakpoints at nucleotide resolution, requiring additional molecular methods for validation and fine-mapping. Here, we use Oxford Nanopore Technologies PromethION long-read GS to characterize complex genomic rearrangements (CGRs) involving large duplications that segregate with ASD in five families. In total, we investigated 13 CGR carriers and were able to resolve all breakpoint junctions at nucleotide resolution. While all breakpoints were identified, the precise genomic architecture of one rearrangement remained unresolved with three different potential structures. The findings in two families include potential fusion genes formed through duplication rearrangements, involving IL1RAPL1-DMD and SUPT16H-CHD8 In two of the families originating from the same geographical region, an identical rearrangement involving ANK2 was identified, which likely represents a founder variant. In addition, we analyze methylation status directly from the long-read data, allowing us to assess the activity of rearranged genes and regulatory regions. Investigation of methylation across the CGRs reveals aberrant methylation status in carriers across a rearrangement affecting the CREBBP locus. In aggregate, our results demonstrate the utility of nanopore sequencing to pinpoint CGRs associated with ASD in five unrelated families, and highlight the importance of a gene-centric description of disease-associated complex chromosomal rearrangements.

Characterizing the rates and patterns of de novo germline mutations in the aye-aye (Daubentonia madagascariensis)

Given the many levels of biological variation in mutation rates observed to date in primates - spanning from species to individuals to genomic regions - future steps in our understanding of mutation rate evolution will be aided by both a greater breadth of species coverage across the primate clade, but also by a greater depth as afforded by an evaluation of multiple trios within individual species. In order to help bridge these gaps, we here present an analysis of a species representing one of the most basal splits on the primate tree (aye-ayes), combining whole-genome sequencing of seven parent-offspring trios from a three-generation pedigree with a novel computational pipeline that takes advantage of recently developed pan-genome graphs, thereby circumventing the application of (highly subjective) quality metrics that has previously been shown to result in notable differences in the detection of de novo mutations, and ultimately estimates of mutation rates. This deep sampling has enabled both a detailed picture of parental age effects as well as sex dependency in mutation rates which we here compare with previously studied primates, but has also provided unique insights into the nature of genetic variation in one of the most endangered primates on the planet.

Mutational signature analyses in multi-child families reveal sources of age-related increases in human germline mutations

Whole-genome sequencing studies of parent-offspring trios have provided valuable insights into the potential impact of de novo mutations (DNMs) on human health and disease. However, the molecular mechanisms that drive DNMs are unclear. Studies with multi-child families can provide important insight into the causes of inter-family variability in DNM rates but they are highly limited. We characterized 2479 de novo single nucleotide variants (SNVs) in 13 multi-child families of Mexican-American ethnicity. We observed a strong paternal age effect on validated de novo SNVs with extensive inter-family variability in the yearly rate of increase. Children of older fathers showed more C > T transitions at CpG sites than children from younger fathers. Validated SNVs were examined against one cancer (COSMIC) and two non-cancer (human germline and CRISPR-Cas 9 knockout of human DNA repair genes) mutational signature databases. These analyses suggest that inaccurate DNA mismatch repair during repair initiation and excision processes, along with DNA damage and replication errors, are major sources of human germline de novo SNVs. Our findings provide important information for understanding the potential sources of human germline de novo SNVs and the critical role of DNA mismatch repair in their genesis.

A modeling of complex trait phenotypic variance determinants

Studies have now shown that the heritability of some complex traits, such as human height, can be virtually fully captured via potential use of sufficiently powered approaches that can characterize the associated collective common- and rare-variant additive genetic architecture. However, for other traits, including complex disease traits, full recovery of such narrow sense heritability would still likely fall far short of respective heritability estimates yielded from pedigree-based analyses such as twin studies. Here, it is proposed that such traits could also involve additional types of relevant architecture and underlying genetic mechanism, such that interaction of somatic variants with heritable variants may represent an underappreciated component. The theoretical model suggested predicts that some relevant heritability estimates are systematically inflated by twin studies, and that instead a significant proportion of the phenotypic variances may be explained by specialized types of heritable genotype-by-environment interaction.

Mechanisms of Germline Stem Cell Competition across Species

In this review, we introduce the concept of cell competition, which occurs between heterogeneous neighboring cell populations. Cells with higher relative fitness become "winners" that outcompete cells of lower relative fitness ("losers"). We discuss the idea of super-competitors, mutant cells that expand at the expense of wild-type cells. Work on adult stem cells (ASCs) has revealed principles of neutral competition, wherein ASCs can be stochastically lost and replaced, and of biased competition, in which a winning ASC with a competitive advantage replaces its neighbors. Germline stem cells (GSCs) are ASCs that are uniquely endowed with the ability to produce gametes and, therefore, impact the next generation. Mechanisms of GSC competition have been elucidated by studies in Drosophila gonads, tunicates, and the mammalian testis. Competition between ASCs is thought to underlie various forms of cancer, including spermatocytic tumors in the human testis. Paternal age effect (PAE) disorders are caused by de novo mutations in human GSCs that increase their competitive ability and make them more likely to be inherited, leading to skeletal and craniofacial abnormalities in offspring. Given its widespread effects on human health, it is important to study GSC competition to elucidate how cells can become winners or losers.

Association between rare, genetic variants linked to autism and ultrasonography fetal anomalies in children with autism spectrum disorder

BACKGROUND

Recent evidence suggests that certain fetal anomalies detected upon prenatal ultrasound screenings are associated with autism spectrum disorder (ASD). In this cross-sectional study, we aimed to identify genetic variants associated with fetal ultrasound anomalies (UFAs) in children with ASD.

METHODS

The study included all children with ASD who are registered in the database of the Azrieli National Center of Autism and Neurodevelopment and for whom both prenatal ultrasound and whole exome sequencing (WES) data were available. We applied our in-house integrative bioinformatics pipeline, AutScore, to these WES data to prioritize rare, gene-disrupting variants (GDVs) probably contributing to ASD susceptibily. Univariate statistics and multivariable regression were used to assess the associations between UFAs and GDVs identified in these children.

RESULTS

The study sample comprised 126 children, of whom 43 (34.1%) had at least one UFA detected in the prenatal ultrasound scan. A total of 87 candidate ASD genetic variants were detected in 60 children, with 24 (40%) children carrying multiple variants. Children with UFAs were more likely to have loss-of-function (LoF) mutations (aOR = 2.55, 95%CI: 1.13-5.80). This association was particularly noticeable when children with structural anomalies or children with UFAs in their head and brain scans were compared to children without UFAs (any mutation: aOR = 8.28, 95%CI: 2.29-30.01; LoF: aOR = 5.72, 95%CI: 2.08-15.71 and any mutation: aOR = 6.39, 95%CI: 1.34-30.47; LoF: aOR = 4.50, 95%CI: 1.32-15.35, respectively). GDVs associated with UFAs were enriched in genes highly expressed across all tissues (aOR = 2.76, 95%CI: 1.14-6.68). There was a weak, but significant, correlation between the number of mutations and the number of abnormalities detected in the same children (r = 0.21, P = 0.016).

CONCLUSIONS

The results provide valuable insights into the potential genetic basis of prenatal organogenesis abnormalities associated with ASD and shed light on the complex interplay between genetic factors and fetal development.

Genetic etiology of autism spectrum disorder in the African population: a scoping review

Background

Autism spectrum disorder (ASD) is a neurodevelopmental disorder (NDD) characterized by significant impairments in social, communicative, and behavioral abilities. However, only a limited number of studies address the genetic basis of ASD in the African population. This study aims to document the genes associated with ASD in Africa and the techniques used to identify them. Additionally, genes identified elsewhere but not yet in Africa are also noted.

Methods

Online databases such as Wiley Online Library, PubMed, and Africa Journal Online were used. The review was conducted using the keyword related to genetic and genomic ASD study in the African population.

Result

In this scoping review, 40 genetic studies on ASD in Africa were reviewed. The Egyptian and South African populations were the most studied, with 25 and 5 studies, respectively. Countries with fewer studies included Tunisia (4), East African countries (3), Libya (1), Nigeria (1), and Morocco (1). Some 61 genes responsible for ASD were identified in the African population: 26 were identified using a polymerase chain reaction (PCR)-based method, 22 were identified using sequencing technologies, and 12 genes and one de novo chromosomal aberration were identified through other techniques. No African study identified any ASD gene with genome-wide association studies (GWAS). Notably, at least 20 ASD risk genes reported in non-African countries were yet to be confirmed in Africa's population.

Conclusion

There are insufficient genetic studies on ASD in the African population, with sample size being a major limitation in most genetic association studies, leading to inconclusive results. Thus, there is a need to conduct more studies with large sample sizes to identify other genes associated with ASD in Africa's population using high-throughput sequencing technology.

Rare Pathogenic Variants Identified in Whole Exome Sequencing of Monozygotic Twins With Autism Spectrum Disorder

BACKGROUND

Autism spectrum disorder (ASD) is a childhood-onset complex neurodevelopmental disorder characterized by problems with communication and social interaction and restricted, repetitive, stereotyped behavior. The prevalence of ASD is one in 36 children. The genetic architecture of ASD is complex in spite of its high heritability. To identify the potential candidate genes of ASD, we carried out a comprehensive genetic study of monozygotic (MZ) twins concordant or discordant for ASD.

METHODS

Five MZ twins and their parents were recruited for the study. Four of the twins were concordant, whereas one was discordant for ASD. Whole exome sequencing was conducted for the twins and their parents. The exome DNA was enriched using Twist Human Customized Core Exome Kit, and paired-end sequencing was performed on HiSeq system.

RESULTS

We identified several rare and pathogenic variants (homozygous recessive, compound heterozygous, de novo) in ASD-affected individuals.

CONCLUSION

We report novel variants in individuals diagnosed with ASD. Several of these genes are involved in brain-related functions and not previously reported in ASD. Intriguingly, some of the variants were observed in the genes involved in sensory perception (auditory [MYO15A, PLEC, CDH23, UBR3, GPSM2], olfactory [OR9K2], gustatory [TAS2R31], and visual [CDH23, UBR3]). This is the first comprehensive genetic study of MZ twins in an Indian population. Further validation is required to determine whether these variants are associated with ASD.

Inhibitory neurons marked by a connectivity molecule regulate memory precision

The CA3 region is central to hippocampal function during learning and memory and has a unique connectivity. CA3 pyramidal neurons are the targets of huge, excitatory mossy fiber synapses from DG axons and have a high degree of excitatory recurrent connectivity. Thus, inhibition likely plays an outsized importance in constraining excitation and shaping CA3 ensembles during learning and memory. Here, we investigate the function of a never-before studied set of dendrite-targeting, GABAergic neurons defined by expression of the synaptic adhesion molecule, Kirrel3. We discovered that activating Kirrel3-expressing GABAergic neurons specifically impairs memory discrimination and inhibits CA3 pyramidal neurons in novel contexts. Kirrel3 is required for DG-to-GABA synapse formation and variants in Kirrel3 are strong risk factors for neurodevelopmental disorders. Thus, our work suggests that Kirrel3-GABA neurons are a critical source of feed-forward inhibition from DG to CA3 during the encoding and retrieval of contextual memories, a function which may be specifically disrupted in some brain disorders.

Mutation accumulation in H. sapiens F508del CFTR countermands dN/dS type genomic analysis

Understanding the mechanisms that underlie de novo mutations (DNMs) can be essential for interpreting human evolution, including aspects such as rapidly diverging genes, conservation of non-coding regulatory elements, and somatic DNA adaptation, among others. DNM accumulation in Homo sapiens is often limited to evaluation of human trios or quads across a single generation. Moreover, human SNPs in exons, pseudogenes, or other non-coding elements can be ancient and difficult to date, including polymorphisms attributable to founder effects and identity by descent. In this report, we describe multigenerational evolution of a human coding locus devoid of natural selection, and delineate patterns and principles by which DNMs have accumulated over the past few thousand years. We apply a data set comprising cystic fibrosis transmembrane conductance regulator (CFTR) alleles from 2,393 individuals homozygous for the F508del defect. Additional polymorphism on the F508del background diversified subsequent to a single mutational event during recent human history. Because F508del CFTR is without function, SNPs observed on this haplotype are effectively attributable to factors that govern accumulating de novo mutations. We show profound enhancement of transition, synonymous, and positionally repetitive polymorphisms, indicating appearance of DNMs in a manner evolutionarily designed to protect protein coding DNA against mutational attrition while promoting diversity.

Improving population scale statistical phasing with whole-genome sequencing data

Haplotype estimation, or phasing, has gained significant traction in large-scale projects due to its valuable contributions to population genetics, variant analysis, and the creation of reference panels for imputation and phasing of new samples. To scale with the growing number of samples, haplotype estimation methods designed for population scale rely on highly optimized statistical models to phase genotype data, and usually ignore read-level information. Statistical methods excel in resolving common variants, however, they still struggle at rare variants due to the lack of statistical information. In this study we introduce SAPPHIRE, a new method that leverages whole-genome sequencing data to enhance the precision of haplotype calls produced by statistical phasing. SAPPHIRE achieves this by refining haplotype estimates through the realignment of sequencing reads, particularly targeting low-confidence phase calls. Our findings demonstrate that SAPPHIRE significantly enhances the accuracy of haplotypes obtained from state of the art methods and also provides the subset of phase calls that are validated by sequencing reads. Finally, we show that our method scales to large data sets by its successful application to the extensive 3.6 Petabytes of sequencing data of the last UK Biobank 200,031 sample release.

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.

Relationships between genomic dissipation and de novo SNP evolution

Patterns of single nucleotide polymorphisms (SNPs) in eukaryotic DNA are traditionally attributed to selective pressure, drift, identity descent, or related factors-without accounting for ways in which bias during de novo SNP formation, itself, might contribute. A functional and phenotypic analysis based on evolutionary resilience of DNA points to decreased numbers of non-synonymous SNPs in human and other genomes, with a predominant component of SNP depletion in the human gene pool caused by robust preferences during de novo SNP formation (rather than selective constraint). Ramifications of these findings are broad, belie a number of concepts regarding human evolution, and point to a novel interpretation of evolving DNA across diverse species.

Noncoding de novo mutations in SCN2A are associated with autism spectrum disorders

Coding de novo mutations (DNMs) contribute to the risk for autism spectrum disorders (ASD), but the contribution of noncoding DNMs remains relatively unexplored. Here we use whole genome sequencing (WGS) data of 12,411 individuals (including 3,508 probands and 2,218 unaffected siblings) from 3,357 families collected in Simons Foundation Powering Autism Research for Knowledge (SPARK) to detect DNMs associated with ASD, while examining Simons Simplex Collection (SSC) with 6383 individuals from 2274 families to replicate the results. For coding DNMs, SCN2A reached exome-wide significance (p=2.06×10-11) in SPARK. The 618 known dominant ASD genes as a group are strongly enriched for coding DNMs in cases than sibling controls (fold change=1.51, p =1.13×10-5 for SPARK; fold change=1.86, p =2.06×10-9 for SSC). For noncoding DNMs, we used two methods to assess statistical significance: a point-based test that analyzes sites with a Combined Annotation Dependent Depletion (CADD) score ≥15, and a segment-based test that analyzes 1kb genomic segments with segment-specific background mutation rates (inferred from expected rare mutations in Gnocchi genome constraint scores). The point-based test identified SCN2A as marginally significant (p=6.12×10-4) in SPARK, yet segment-based test identified CSMD1, RBFOX1 and CHD13 as exome-wide significant. We did not identify significant enrichment of noncoding DNMs (in all 1kb segments or those with Gnocchi>4) in the 618 known ASD genes as a group in cases than sibling controls. When combining evidence from both coding and noncoding DNMs, we found that SCN2A with 11 coding and 5 noncoding DNMs exhibited the strongest significance (p=4.15×10-13). In summary, we identified both coding and noncoding DNMs in SCN2A associated with ASD, while nominating additional candidates for further examination in future studies.

Prognostic analysis of mutated genes and insight into effects of DNA damage and repair on mutational strand asymmetries in gastric cancer

Gastric cancer (GACA) is a complex and multifaceted disease influenced by a variety of environmental and genetic factors. Somatic mutations play a major role in its development, and their characteristics, including the asymmetry between two DNA strands, are of great interest and appear as a signal of information and guidance, revealing mechanisms of DNA damage and repair. Here, we analyzed the impact of High-frequency mutated genes on patient prognosis and found that the effect of expression levels of tumor protein p53 (TP53) and lysine methyltransferase 2C (KMT2C) genes remained high throughout the development of GACA, with similar expression patterns. After investigating mutation asymmetry across mutagenic processes, we found that transcriptional asymmetry was dominated by T > G mutations under the influence of transcription couples repair and damage. The apolipoprotein B mRNA editing enzyme catalytic polypeptide like (APOBEC) enzyme that induces mutations during DNA replication has been identified here and we identified a replicative asymmetry, which was dominated by C > A mutations in left-replicating. Strand bias in different mutation classes at transcription factor binding sites and enhancer regions were also confirmed, which implies the important role of non-coding regulatory elements in the occurrence of mutations. This work systematically describes mutational strand asymmetries in specific genomic regions, shedding light on the DNA damage and repair mechanisms underlying somatic mutations in cohorts of GACA patients with gastric cancer.

Germline cell de novo mutations and potential effects of inflammation on germline cell genome stability

Uncontrolled pathogenic genome mutations in germline cells might impair adult fertility, lead to birth defects or even affect the adaptability of a species. Understanding the sources of DNA damage, as well as the features of damage response in germline cells are the overarching tasks to reduce the mutations in germline cells. With the accumulation of human genome data and genetic reports, genome variants formed in germline cells are being extensively explored. However, the sources of DNA damage, the damage repair mechanisms, and the effects of DNA damage or mutations on the development of germline cells are still unclear. Besides exogenous triggers of DNA damage such as irradiation and genotoxic chemicals, endogenous exposure to inflammation may also contribute to the genome instability of germline cells. In this review, we summarized the features of de novo mutations and the specific DNA damage responses in germline cells and explored the possible roles of inflammation on the genome stability of germline cells.

Proteome-Wide Assessment of Clustering of Missense Variants in Neurodevelopmental Disorders Versus Cancer

Missense de novo variants (DNVs) and missense somatic variants contribute to neurodevelopmental disorders (NDDs) and cancer, respectively. Proteins with statistical enrichment based on analyses of these variants exhibit convergence in the differing NDD and cancer phenotypes. Herein, the question of why some of the same proteins are identified in both phenotypes is examined through investigation of clustering of missense variation at the protein level. Our hypothesis is that missense variation is present in different protein locations in the two phenotypes leading to the distinct phenotypic outcomes. We tested this hypothesis in 1D protein space using our software CLUMP. Furthermore, we newly developed 3D-CLUMP that uses 3D protein structures to spatially test clustering of missense variation for proteome-wide significance. We examined missense DNVs in 39,883 parent-child sequenced trios with NDDs and missense somatic variants from 10,543 sequenced tumors covering five TCGA cancer types and two COSMIC pan-cancer aggregates of tissue types. There were 57 proteins with proteome-wide significant missense variation clustering in NDDs when compared to cancers and 79 proteins with proteome-wide significant missense clustering in cancers compared to NDDs. While our main objective was to identify differences in patterns of missense variation, we also identified a novel NDD protein BLTP2. Overall, our study is innovative, provides new insights into differential missense variation in NDDs and cancer at the protein-level, and contributes necessary information toward building a framework for thinking about prognostic and therapeutic aspects of these proteins.

Reanalysis of Trio Whole-Genome Sequencing Data Doubles the Yield in Autism Spectrum Disorder: De Novo Variants Present in Half

Autism spectrum disorder (ASD) is a common condition with lifelong implications. The last decade has seen dramatic improvements in DNA sequencing and related bioinformatics and databases. We analyzed the raw DNA sequencing files on the Variantyx® bioinformatics platform for the last 50 ASD patients evaluated with trio whole-genome sequencing (trio-WGS). "Qualified" variants were defined as coding, rare, and evolutionarily conserved. Primary Diagnostic Variants (PDV), additionally, were present in genes directly linked to ASD and matched clinical correlation. A PDV was identified in 34/50 (68%) of cases, including 25 (50%) cases with heterozygous de novo and 10 (20%) with inherited variants. De novo variants in genes directly associated with ASD were far more likely to be Qualifying than non-Qualifying versus a control group of genes (p = 0.0002), validating that most are indeed disease related. Sequence reanalysis increased diagnostic yield from 28% to 68%, mostly through inclusion of de novo PDVs in genes not yet reported as ASD associated. Thirty-three subjects (66%) had treatment recommendation(s) based on DNA analyses. Our results demonstrate a high yield of trio-WGS for revealing molecular diagnoses in ASD, which is greatly enhanced by reanalyzing DNA sequencing files. In contrast to previous reports, de novo variants dominate the findings, mostly representing novel conditions. This has implications to the cause and rising prevalence of autism.

HAT: de novo variant calling for highly accurate short-read and long-read sequencing data

MOTIVATION

de novo variants (DNVs) are variants that are present in offspring but not in their parents. DNVs are both important for examining mutation rates as well as in the identification of disease-related variation. While efforts have been made to call DNVs, calling of DNVs is still challenging from parent-child sequenced trio data. We developed Hare And Tortoise (HAT) as an automated DNV detection workflow for highly accurate short-read and long-read sequencing data. Reliable detection of DNVs is important for human genomics and HAT addresses this need.

RESULTS

HAT is a computational workflow that begins with aligned read data (i.e. CRAM or BAM) from a parent-child sequenced trio and outputs DNVs. HAT detects high-quality DNVs from Illumina short-read whole-exome sequencing, Illumina short-read whole-genome sequencing, and highly accurate PacBio HiFi long-read whole-genome sequencing data. The quality of these DNVs is high based on a series of quality metrics including number of DNVs per individual, percent of DNVs at CpG sites, and percent of DNVs phased to the paternal chromosome of origin.

AVAILABILITY AND IMPLEMENTATION

https://github.com/TNTurnerLab/HAT.

[Splicing mutations of GSDME cause late-onset non-syndromic hearing loss]

Objective:To dentify the genetic and audiological characteristics of families affected by late-onset hearing loss due to GSDMEgene mutations, aiming to explore clinical characteristics and pathogenic mechanisms for providing genetic counseling and intervention guidance. Methods:Six families with late-onset hearing loss from the Chinese Deafness Genome Project were included. Audiological tests, including pure-tone audiometry, acoustic immittance, speech recognition scores, auditory brainstem response, and distortion product otoacoustic emission, were applied to evaluate the hearing levels of patients. Combining with medical history and physical examination to analyze the phenotypic differences between the probands and their family members. Next-generation sequencing was used to identify pathogenic genes in probands, and validations were performed on their relatives by Sanger sequencing. Pathogenicity analysis was performed according to the American College of Medical Genetics and Genomics Guidelines. Meanwhile, the pathogenic mechanisms of GSDME-related hearing loss were explored combining with domestic and international research progress. Results:Among the six families with late-onset hearing loss, a total of 30 individuals performed hearing loss. The onset of hearing loss in these families ranged from 10 to 50 years（mean age: 27.88±9.74 years）. In the study, four splicing mutations of the GSDME were identified, including two novel variants: c. 991－7C>G and c. 1183+1G>T. Significantly, the c. 991－7C>G was a de novo variant. The others were previously reported variants: c. 991-1G>C and c. 991-15_991-13del, the latter was identified in three families. Genotype-phenotype correlation analysis revealed that probands with the c. 991－7C>G and c. 1183+1G>T performed a predominantly high-frequency hearing loss. The three families carrying the same mutation exhibited varying degrees of hearing loss, with an annual rate of hearing deterioration exceeding 0.94 dB HL/year. Furthermore, follow-up of interventions showed that four of six probands received intervention（66.67%）, but the results of intervention varied. Conclusion:The study analyzed six families with late-onset non-syndromic hearing loss linked to GSDME mutations, identifying four splicing variants. Notably, c. 991－7C>G is the first reported de novo variant of GSDME globally. Audiological analysis revealed that the age of onset generally exceeded 10 years,with variable effectiveness of interventions.

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.

Rare X-linked variants carry predominantly male risk in autism, Tourette syndrome, and ADHD

Autism spectrum disorder (ASD), Tourette syndrome (TS), and attention-deficit/hyperactivity disorder (ADHD) display strong male sex bias, due to a combination of genetic and biological factors, as well as selective ascertainment. While the hemizygous nature of chromosome X (Chr X) in males has long been postulated as a key point of "male vulnerability", rare genetic variation on this chromosome has not been systematically characterized in large-scale whole exome sequencing studies of "idiopathic" ASD, TS, and ADHD. Here, we take advantage of informative recombinations in simplex ASD families to pinpoint risk-enriched regions on Chr X, within which rare maternally-inherited damaging variants carry substantial risk in males with ASD. We then apply a modified transmission disequilibrium test to 13,052 ASD probands and identify a novel high confidence ASD risk gene at exome-wide significance (MAGEC3). Finally, we observe that rare damaging variants within these risk regions carry similar effect sizes in males with TS or ADHD, further clarifying genetic mechanisms underlying male vulnerability in multiple neurodevelopmental disorders that can be exploited for systematic gene discovery.

Acorn: an R package for de novo variant analysis

BACKGROUND

The study of de novo variation is important for assessing biological characteristics of new variation and for studies related to human phenotypes. Software programs exist to call de novo variants and programs also exist to test the burden of these variants in genomic regions; however, I am unaware of a program that fits in between these two aspects of de novo variant assessment. This intermediate space is important for assessing the quality of de novo variants and to understand the characteristics of the callsets. For this reason, I developed an R package called acorn.

RESULTS

Acorn is an R package that examines various features of de novo variants including subsetting the data by individual(s), variant type, or genomic region; calculating features including variant change counts, variant lengths, and presence/absence at CpG sites; and characteristics of parental age in relation to de novo variant counts.

CONCLUSIONS

Acorn is an R package that fills a critical gap in assessing de novo variants and will be of benefit to many investigators studying de novo variation.

The rate of de novo structural variation is increased in in vitro-produced offspring and preferentially affects the paternal genome

Assisted reproductive technologies (ARTs), including in vitro maturation and fertilization (IVF), are increasingly used in human and animal reproduction. Whether these technologies directly affect the rate of de novo mutation (DNM), and to what extent, has been a matter of debate. Here we take advantage of domestic cattle, characterized by complex pedigrees that are ideally suited to detect DNMs and by the systematic use of ART, to study the rate of de novo structural variation (dnSV) in this species and how it is impacted by IVF. By exploiting features of associated de novo point mutations (dnPMs) and dnSVs in clustered DNMs, we provide strong evidence that (1) IVF increases the rate of dnSV approximately fivefold, and (2) the corresponding mutations occur during the very early stages of embryonic development (one- and two-cell stage), yet primarily affect the paternal genome.

KIRREL3-related disorders: a case report confirming the radiological features and expanding the clinical spectrum to a less severe phenotype

BACKGROUND

Neurodevelopmental disorders have a multifactorial etiology, since biological, genetic, psychosocial and environmental risk factors are involved. Recent studies have been linking neurodevelopmental disorders and intellectual disability with a variety of genes, some of which encoding neuronal cell-adhesion molecules. Among these, KIRREL3 is known to play a role in CNS development, and his variants have recently been related to intellectual disability, autism spectrum disorder, childhood apraxia of speech, cerebellar hypoplasia and mild dysmorphic features.

CASE PRESENTATION

In this study, we describe a young Caucasian boy with mild intellectual disability, cerebellar anomalies (cerebellar hypoplasia and mega cisterna magna) and minor dysmorphic features associated to a novel KIRREL3 variant.

CONCLUSIONS

Aim of the present case report is to expand the clinical spectrum of KIRREL3-related diseases towards a milder phenotype than what is already described in the literature. We speculate that the interaction between KIRREL3 and CASK might play a major role in promoting cognitive and cerebellar development, contributing to a variety of clinical manifestations.

Structural underpinnings of mutation rate variations in the human genome

Single nucleotide mutation rates have critical implications for human evolution and genetic diseases. Importantly, the rates vary substantially across the genome and the principles underlying such variations remain poorly understood. A recent model explained much of this variation by considering higher-order nucleotide interactions in the 7-mer sequence context around mutated nucleotides. This model's success implicates a connection between DNA shape and mutation rates. DNA shape, i.e. structural properties like helical twist and tilt, is known to capture interactions between nucleotides within a local context. Thus, we hypothesized that changes in DNA shape features at and around mutated positions can explain mutation rate variations in the human genome. Indeed, DNA shape-based models of mutation rates showed similar or improved performance over current nucleotide sequence-based models. These models accurately characterized mutation hotspots in the human genome and revealed the shape features whose interactions underlie mutation rate variations. DNA shape also impacts mutation rates within putative functional regions like transcription factor binding sites where we find a strong association between DNA shape and position-specific mutation rates. This work demonstrates the structural underpinnings of nucleotide mutations in the human genome and lays the groundwork for future models of genetic variations to incorporate DNA shape.

Environmental carcinogens disproportionally mutate genes implicated in neurodevelopmental disorders

Introduction

De novo mutations contribute to a large proportion of sporadic psychiatric and developmental disorders, yet the potential role of environmental carcinogens as drivers of causal de novo mutations in neurodevelopmental disorders is poorly studied.

Methods

To explore environmental mutation vulnerability of disease-associated gene sets, we analyzed publicly available whole genome sequencing datasets of mutations in human induced pluripotent stem cell clonal lines exposed to 12 classes of environmental carcinogens, and human lung cancers from individuals living in highly polluted regions. We compared observed rates of exposure-induced mutations in disease-related gene sets with the expected rates of mutations based on control genes randomly sampled from the genome using exact binomial tests. To explore the role of sequence characteristics in mutation vulnerability, we modeled the effects of sequence length, gene expression, and percent GC content on mutation rates of entire genes and gene coding sequences using multivariate Quasi-Poisson regressions.

Results

We demonstrate that several mutagens, including radiation and polycyclic aromatic hydrocarbons, disproportionately mutate genes related to neurodevelopmental disorders including autism spectrum disorders, schizophrenia, and attention deficit hyperactivity disorder. Other disease genes including amyotrophic lateral sclerosis, Alzheimer's disease, congenital heart disease, orofacial clefts, and coronary artery disease were generally not mutated more than expected. Longer sequence length was more strongly associated with elevated mutations in entire genes compared with mutations in coding sequences. Increased expression was associated with decreased coding sequence mutation rate, but not with the mutability of entire genes. Increased GC content was associated with increased coding sequence mutation rates but decreased mutation rates in entire genes.

Discussion

Our findings support the possibility that neurodevelopmental disorder genetic etiology is partially driven by a contribution of environment-induced germ line and somatic mutations.

The contributions of rare inherited and polygenic risk to ASD in multiplex families

Autism spectrum disorder (ASD) has a complex genetic architecture involving contributions from both de novo and inherited variation. Few studies have been designed to address the role of rare inherited variation or its interaction with common polygenic risk in ASD. Here, we performed whole-genome sequencing of the largest cohort of multiplex families to date, consisting of 4,551 individuals in 1,004 families having two or more autistic children. Using this study design, we identify seven previously unrecognized ASD risk genes supported by a majority of rare inherited variants, finding support for a total of 74 genes in our cohort and a total of 152 genes after combined analysis with other studies. Autistic children from multiplex families demonstrate an increased burden of rare inherited protein-truncating variants in known ASD risk genes. We also find that ASD polygenic score (PGS) is overtransmitted from nonautistic parents to autistic children who also harbor rare inherited variants, consistent with combinatorial effects in the offspring, which may explain the reduced penetrance of these rare variants in parents. We also observe that in addition to social dysfunction, language delay is associated with ASD PGS overtransmission. These results are consistent with an additive complex genetic risk architecture of ASD involving rare and common variation and further suggest that language delay is a core biological feature of ASD.

Context and Mutation in Gymnosperm Chloroplast DNA

Mutations and subsequent repair processes are known to be strongly context-dependent in the flowering-plant chloroplast genome. At least six flanking bases, three on each side, can have an influence on the relative rates of different types of mutation at any given site. In this analysis, examine context and substitution at noncoding and fourfold degenerate coding sites in gymnosperm DNA. The sequences are analyzed in sets of three, allowing the inference of the substitution direction and the generation of context-dependent rate matrices. The size of the dataset limits the analysis to the tetranucleotide context of the sites, but the evidence shows that there are significant contextual effects, with patterns that are similar to those observed in angiosperms. These effects most likely represent an influence on the underlying mutation/repair dynamics. The data extend the plastome lineages that feature very complex patterns of mutation, which can have significant effects on the evolutionary dynamics of the chloroplast genome.

The landscape of somatic mutations in lymphoblastoid cell lines

Somatic mutations have important biological ramifications while exerting substantial rate, type, and genomic location heterogeneity. Yet, their sporadic occurrence makes them difficult to study at scale and across individuals. Lymphoblastoid cell lines (LCLs), a model system for human population and functional genomics, harbor large numbers of somatic mutations and have been extensively genotyped. By comparing 1,662 LCLs, we report that the mutational landscape of the genome varies across individuals in terms of the number of mutations, their genomic locations, and their spectra; this variation may itself be modulated by somatic trans-acting mutations. Mutations attributed to the translesion DNA polymerase η follow two different modes of formation, with one mode accounting for the hypermutability of the inactive X chromosome. Nonetheless, the distribution of mutations along the inactive X chromosome appears to follow an epigenetic memory of the active form.

Identification and characterisation of de novo germline structural variants in two commercial pig lines using trio-based whole genome sequencing

BACKGROUND

De novo mutations arising in the germline are a source of genetic variation and their discovery broadens our understanding of genetic disorders and evolutionary patterns. Although the number of de novo single nucleotide variants (dnSNVs) has been studied in a number of species, relatively little is known about the occurrence of de novo structural variants (dnSVs). In this study, we investigated 37 deeply sequenced pig trios from two commercial lines to identify dnSVs present in the offspring. The identified dnSVs were characterised by identifying their parent of origin, their functional annotations and characterizing sequence homology at the breakpoints.

RESULTS

We identified four swine germline dnSVs, all located in intronic regions of protein-coding genes. Our conservative, first estimate of the swine germline dnSV rate is 0.108 (95% CI 0.038-0.255) per generation (one dnSV per nine offspring), detected using short-read sequencing. Two detected dnSVs are clusters of mutations. Mutation cluster 1 contains a de novo duplication, a dnSNV and a de novo deletion. Mutation cluster 2 contains a de novo deletion and three de novo duplications, of which one is inverted. Mutation cluster 2 is 25 kb in size, whereas mutation cluster 1 (197 bp) and the other two individual dnSVs (64 and 573 bp) are smaller. Only mutation cluster 2 could be phased and is located on the paternal haplotype. Mutation cluster 2 originates from both micro-homology as well as non-homology mutation mechanisms, where mutation cluster 1 and the other two dnSVs are caused by mutation mechanisms lacking sequence homology. The 64 bp deletion and mutation cluster 1 were validated through PCR. Lastly, the 64 bp deletion and the 573 bp duplication were validated in sequenced offspring of probands with three generations of sequence data.

CONCLUSIONS

Our estimate of 0.108 dnSVs per generation in the swine germline is conservative, due to our small sample size and restricted possibilities of dnSV detection from short-read sequencing. The current study highlights the complexity of dnSVs and shows the potential of breeding programs for pigs and livestock species in general, to provide a suitable population structure for identification and characterisation of dnSVs.

The origins and functional effects of postzygotic mutations throughout the human life span

Postzygotic mutations (PZMs) begin to accrue in the human genome immediately after fertilization, but how and when PZMs affect development and lifetime health remain unclear. To study the origins and functional consequences of PZMs, we generated a multitissue atlas of PZMs spanning 54 tissue and cell types from 948 donors. Nearly half the variation in mutation burden among tissue samples can be explained by measured technical and biological effects, and 9% can be attributed to donor-specific effects. Through phylogenetic reconstruction of PZMs, we found that their type and predicted functional impact vary during prenatal development, across tissues, and through the germ cell life cycle. Thus, methods for interpreting effects across the body and the life span are needed to fully understand the consequences of genetic variants.

BIGKnock: fine-mapping gene-based associations via knockoff analysis of biobank-scale data

We propose BIGKnock (BIobank-scale Gene-based association test via Knockoffs), a computationally efficient gene-based testing approach for biobank-scale data, that leverages long-range chromatin interaction data, and performs conditional genome-wide testing via knockoffs. BIGKnock can prioritize causal genes over proxy associations at a locus. We apply BIGKnock to the UK Biobank data with 405,296 participants for multiple binary and quantitative traits, and show that relative to conventional gene-based tests, BIGKnock produces smaller sets of significant genes that contain the causal gene(s) with high probability. We further illustrate its ability to pinpoint potential causal genes at [Formula: see text] of the associated loci.

The frequency of somatic mutations in cancer predicts the phenotypic relevance of germline mutations

Genomic sequence mutations can be pathogenic in both germline and somatic cells. Several authors have observed that often the same genes are involved in cancer when mutated in somatic cells and in genetic diseases when mutated in the germline. Recent advances in high-throughput sequencing techniques have provided us with large databases of both types of mutations, allowing us to investigate this issue in a systematic way. Hence, we applied a machine learning based framework to this problem, comparing multiple models. The models achieved significant predictive power as shown by both cross-validation and their application to recently discovered gene/phenotype associations not used for training. We found that genes characterized by high frequency of somatic mutations in the most common cancers and ancient evolutionary age are most likely to be involved in abnormal phenotypes and diseases. These results suggest that the combination of tolerance for mutations at the cell viability level (measured by the frequency of somatic mutations in cancer) and functional relevance (demonstrated by evolutionary conservation) are the main predictors of disease genes. Our results thus confirm the deep relationship between pathogenic mutations in somatic and germline cells, provide new insight into the common origin of cancer and genetic diseases, and can be used to improve the identification of new disease genes.

Shared Cancer Dataset Analysis Identifies and Predicts the Quantitative Effects of Pan-Cancer Somatic Driver Variants

Driver mutations endow tumors with selective advantages and produce an array of pathogenic effects. Determining the function of somatic variants is important for understanding cancer biology and identifying optimal therapies. Here, we compiled a shared dataset from several cancer genomic databases. Two measures were applied to 535 cancer genes based on observed and expected frequencies of driver variants as derived from cancer-specific rates of somatic mutagenesis. The first measure comprised a binary classifier based on a binomial test; the second was tumor variant amplitude (TVA), a continuous measure representing the selective advantage of individual variants. TVA outperformed all other computational tools in terms of its correlation with experimentally derived functional scores of cancer mutations. TVA also highly correlated with drug response, overall survival, and other clinical implications in relevant cancer genes. This study demonstrates how a selective advantage measure based on a large cancer dataset significantly impacts our understanding of the spectral effect of driver variants in cancer. The impact of this information will increase as cancer treatment becomes more precise and personalized to tumor-specific mutations.

SIGNIFICANCE

A new selective advantage estimation assists in oncogenic driver identification and relative effect measurements, enabling better prognostication, therapy selection, and prioritization.

Depression-Associated Negr1 Gene-Deficiency Induces Alterations in the Monoaminergic Neurotransmission Enhancing Time-Dependent Sensitization to Amphetamine in Male Mice

In GWAS studies, the neural adhesion molecule encoding the neuronal growth regulator 1 (NEGR1) gene has been consistently linked with both depression and obesity. Although the linkage between NEGR1 and depression is the strongest, evidence also suggests the involvement of NEGR1 in a wide spectrum of psychiatric conditions. Here we show the expression of NEGR1 both in tyrosine- and tryptophan hydroxylase-positive cells. Negr1-/- mice show a time-dependent increase in behavioral sensitization to amphetamine associated with increased dopamine release in both the dorsal and ventral striatum. Upregulation of transcripts encoding dopamine and serotonin transporters and higher levels of several monoamines and their metabolites was evident in distinct brain areas of Negr1-/- mice. Chronic (23 days) escitalopram-induced reduction of serotonin and dopamine turnover is enhanced in Negr1-/- mice, and escitalopram rescued reduced weight of hippocampi in Negr1-/- mice. The current study is the first to show alterations in the brain monoaminergic systems in Negr1-deficient mice, suggesting that monoaminergic neural circuits contribute to both depressive and obesity-related phenotypes linked to the human NEGR1 gene.

Estimating the Prevalence of De Novo Monogenic Neurodevelopmental Disorders from Large Cohort Studies

Rare diseases impact up to 400 million individuals globally. Of the thousands of known rare diseases, many are rare neurodevelopmental disorders (RNDDs) impacting children. RNDDs have proven to be difficult to assess epidemiologically for several reasons. The rarity of them makes it difficult to observe them in the population, there is clinical overlap among many disorders, making it difficult to assess the prevalence without genetic testing, and data have yet to be available to have accurate counts of cases. Here, we utilized large sequencing cohorts of individuals with rare, de novo monogenic disorders to estimate the prevalence of variation in over 11,000 genes among cohorts with developmental delay, autism spectrum disorder, and/or epilepsy. We found that the prevalence of many RNDDs is positively correlated to the previously estimated incidence. We identified the most often mutated genes among neurodevelopmental disorders broadly, as well as developmental delay and autism spectrum disorder independently. Finally, we assessed if social media group member numbers may be a valuable way to estimate prevalence. These data are critical for individuals and families impacted by these RNDDs, clinicians and geneticists in their understanding of how common diseases are, and for researchers to potentially prioritize research into particular genes or gene sets.

Dissecting the multifaceted contribution of the mitochondrial genome to autism spectrum disorder

Autism spectrum disorder (ASD) is a clinically heterogeneous class of neurodevelopmental conditions with a strong, albeit complex, genetic basis. The genetic architecture of ASD includes different genetic models, from monogenic transmission at one end, to polygenic risk given by thousands of common variants with small effects at the other end. The mitochondrial DNA (mtDNA) was also proposed as a genetic modifier for ASD, mostly focusing on maternal mtDNA, since the paternal mitogenome is not transmitted to offspring. We extensively studied the potential contribution of mtDNA in ASD pathogenesis and risk through deep next generation sequencing and quantitative PCR in a cohort of 98 families. While the maternally-inherited mtDNA did not seem to predispose to ASD, neither for haplogroups nor for the presence of pathogenic mutations, an unexpected influence of paternal mtDNA, apparently centered on haplogroup U, came from the Italian families extrapolated from the test cohort (n = 74) when compared to the control population. However, this result was not replicated in an independent Italian cohort of 127 families and it is likely due to the elevated paternal age at time of conception. In addition, ASD probands showed a reduced mtDNA content when compared to their unaffected siblings. Multivariable regression analyses indicated that variants with 15%-5% heteroplasmy in probands are associated to a greater severity of ASD based on ADOS-2 criteria, whereas paternal super-haplogroups H and JT were associated with milder phenotypes. In conclusion, our results suggest that the mtDNA impacts on ASD, significantly modifying the phenotypic expression in the Italian population. The unexpected finding of protection induced by paternal mitogenome in term of severity may derive from a role of mtDNA in influencing the accumulation of nuclear de novo mutations or epigenetic alterations in fathers' germinal cells, affecting the neurodevelopment in the offspring. This result remains preliminary and needs further confirmation in independent cohorts of larger size. If confirmed, it potentially opens a different perspective on how paternal non-inherited mtDNA may predispose or modulate other complex diseases.

Predictive functional, statistical and structural analysis of CSNK2A1 and CSNK2B variants linked to neurodevelopmental diseases

Okur-Chung Neurodevelopmental Syndrome (OCNDS) and Poirier-Bienvenu Neurodevelopmental Syndrome (POBINDS) were recently identified as rare neurodevelopmental disorders. OCNDS and POBINDS are associated with heterozygous mutations in the CSNK2A1 and CSNK2B genes which encode CK2α, a serine/threonine protein kinase, and CK2β, a regulatory protein, respectively, which together can form a tetrameric enzyme called protein kinase CK2. A challenge in OCNDS and POBINDS is to understand the genetic basis of these diseases and the effect of the various CK2⍺ and CK2β mutations. In this study we have collected all variants available to date in CSNK2A1 and CSNK2B, and identified hotspots. We have investigated CK2⍺ and CK2β missense mutations through prediction programs which consider the evolutionary conservation, functionality and structure or these two proteins, compared these results with published experimental data on CK2α and CK2β mutants, and suggested prediction programs that could help predict changes in functionality of CK2α mutants. We also investigated the potential effect of CK2α and CK2β mutations on the 3D structure of the proteins and in their binding to each other. These results indicate that there are functional and structural consequences of mutation of CK2α and CK2β, and provide a rationale for further study of OCNDS and POBINDS-associated mutations. These data contribute to understanding the genetic and functional basis of these diseases, which is needed to identify their underlying mechanisms.

De novo mutations, genetic mosaicism and human disease

Mosaicism—the existence of genetically distinct populations of cells in a particular organism—is an important cause of genetic disease. Mosaicism can appear as de novo DNA mutations, epigenetic alterations of DNA, and chromosomal abnormalities. Neurodevelopmental or neuropsychiatric diseases, including autism—often arise by de novo mutations that usually not present in either of the parents. De novo mutations might occur as early as in the parental germline, during embryonic, fetal development, and/or post-natally, through ageing and life. Mutation timing could lead to mutation burden of less than heterozygosity to approaching homozygosity. Developmental timing of somatic mutation attainment will affect the mutation load and distribution throughout the body. In this review, we discuss the timing of de novo mutations, spanning from mutations in the germ lineage (all ages), to post-zygotic, embryonic, fetal, and post-natal events, through aging to death. These factors can determine the tissue specific distribution and load of de novo mutations, which can affect disease. The disease threshold burden of somatic de novo mutations of a particular gene in any tissue will be important to define.