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.

A phenotypic spectrum of autism is attributable to the combined effects of rare variants, polygenic risk and sex.

The genetic etiology of autism spectrum disorder (ASD) is multifactorial, but how combinations of genetic factors determine risk is unclear. In a large family sample, we show that genetic loads of rare and polygenic risk are inversely correlated in cases and greater in females than in males, consistent with a liability threshold that differs by sex. De novo mutations (DNMs), rare inherited variants and polygenic scores were associated with various dimensions of symptom severity in children and parents. Parental age effects on risk for ASD in offspring were attributable to a combination of genetic mechanisms, including DNMs that accumulate in the paternal germline and inherited risk that influences behavior in parents. Genes implicated by rare variants were enriched in excitatory and inhibitory neurons compared with genes implicated by common variants. Our results suggest that a phenotypic spectrum of ASD is attributable to a spectrum of genetic factors that impact different neurodevelopmental processes.

SNPs, short tandem repeats, and structural variants are responsible for differential gene expression across C57BL/6 and C57BL/10 substrains.

Mouse substrains are an invaluable model for understanding disease. We compared C57BL/6J, which is the most commonly used inbred mouse strain, with eight C57BL/6 and five C57BL/10 closely related inbred substrains. Whole-genome sequencing and RNA-sequencing analysis yielded 352,631 SNPs, 109,096 indels, 150,344 short tandem repeats (STRs), 3,425 structural variants (SVs), and 2,826 differentially expressed genes (DE genes) among these 14 strains; 312,981 SNPs (89%) distinguished the B6 and B10 lineages. These SNPs were clustered into 28 short segments that are likely due to introgressed haplotypes rather than new mutations. Outside of these introgressed regions, we identified 53 SVs, protein-truncating SNPs, and frameshifting indels that were associated with DE genes. Our results can be used for both forward and reverse genetic approaches and illustrate how introgression and mutational processes give rise to differences among these widely used inbred substrains.

Somatic mosaicism reveals clonal distributions of neocortical development.

The structure of the human neocortex underlies species-specific traits and reflects intricate developmental programs. Here we sought to reconstruct processes that occur during early development by sampling adult human tissues. We analysed neocortical clones in a post-mortem human brain through a comprehensive assessment of brain somatic mosaicism, acting as neutral lineage recorders1,2. We combined the sampling of 25 distinct anatomic locations with deep whole-genome sequencing in a neurotypical deceased individual and confirmed results with 5 samples collected from each of three additional donors. We identified 259 bona fide mosaic variants from the index case, then deconvolved distinct geographical, cell-type and clade organizations across the brain and other organs. We found that clones derived after the accumulation of 90-200 progenitors in the cerebral cortex tended to respect the midline axis, well before the anterior-posterior or ventral-dorsal axes, representing a secondary hierarchy following the overall patterning of forebrain and hindbrain domains. Clones across neocortically derived cells were consistent with a dual origin from both dorsal and ventral cellular populations, similar to rodents, whereas the microglia lineage appeared distinct from other resident brain cells. Our data provide a comprehensive analysis of brain somatic mosaicism across the neocortex and demonstrate cellular origins and progenitor distribution patterns within the human brain.

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.

Cortical organoids model early brain development disrupted by 16p11.2 copy number variants in autism.

Reciprocal deletion and duplication of the 16p11.2 region is the most common copy number variation (CNV) associated with autism spectrum disorders. We generated cortical organoids from skin fibroblasts of patients with 16p11.2 CNV to investigate impacted neurodevelopmental processes. We show that organoid size recapitulates macrocephaly and microcephaly phenotypes observed in the patients with 16p11.2 deletions and duplications. The CNV dosage affects neuronal maturation, proliferation, and synapse number, in addition to its effect on organoid size. We demonstrate that 16p11.2 CNV alters the ratio of neurons to neural progenitors in organoids during early neurogenesis, with a significant excess of neurons and depletion of neural progenitors observed in deletions. Transcriptomic and proteomic profiling revealed multiple pathways dysregulated by the 16p11.2 CNV, including neuron migration, actin cytoskeleton, ion channel activity, synaptic-related functions, and Wnt signaling. The level of the active form of small GTPase RhoA was increased in both, deletions and duplications. Inhibition of RhoA activity rescued migration deficits, but not neurite outgrowth. This study provides insights into potential neurobiological mechanisms behind the 16p11.2 CNV during neocortical development.

Mutations in Spliceosomal Genes PPIL1 and PRP17 Cause Neurodegenerative Pontocerebellar Hypoplasia with Microcephaly.

Autosomal-recessive cerebellar hypoplasia and ataxia constitute a group of heterogeneous brain disorders caused by disruption of several fundamental cellular processes. Here, we identified 10 families showing a neurodegenerative condition involving pontocerebellar hypoplasia with microcephaly (PCHM). Patients harbored biallelic mutations in genes encoding the spliceosome components Peptidyl-Prolyl Isomerase Like-1 (PPIL1) or Pre-RNA Processing-17 (PRP17). Mouse knockouts of either gene were lethal in early embryogenesis, whereas PPIL1 patient mutation knockin mice showed neuron-specific apoptosis. Loss of either protein affected splicing integrity, predominantly affecting short and high GC-content introns and genes involved in brain disorders. PPIL1 and PRP17 form an active isomerase-substrate interaction, but we found that isomerase activity is not critical for function. Thus, we establish disrupted splicing integrity and "major spliceosome-opathies" as a new mechanism underlying PCHM and neurodegeneration and uncover a non-enzymatic function of a spliceosomal proline isomerase.

Alternative genomic diagnoses for individuals with a clinical diagnosis of Dubowitz syndrome.

Dubowitz syndrome (DubS) is considered a recognizable syndrome characterized by a distinctive facial appearance and deficits in growth and development. There have been over 200 individuals reported with Dubowitz or a "Dubowitz-like" condition, although no single gene has been implicated as responsible for its cause. We have performed exome (ES) or genome sequencing (GS) for 31 individuals clinically diagnosed with DubS. After genome-wide sequencing, rare variant filtering and computational and Mendelian genomic analyses, a presumptive molecular diagnosis was made in 13/27 (48%) families. The molecular diagnoses included biallelic variants in SKIV2L, SLC35C1, BRCA1, NSUN2; de novo variants in ARID1B, ARID1A, CREBBP, POGZ, TAF1, HDAC8, and copy-number variation at1p36.11(ARID1A), 8q22.2(VPS13B), Xp22, and Xq13(HDAC8). Variants of unknown significance in known disease genes, and also in genes of uncertain significance, were observed in 7/27 (26%) additional families. Only one gene, HDAC8, could explain the phenotype in more than one family (N = 2). All but two of the genomic diagnoses were for genes discovered, or for conditions recognized, since the introduction of next-generation sequencing. Overall, the DubS-like clinical phenotype is associated with extensive locus heterogeneity and the molecular diagnoses made are for emerging clinical conditions sharing characteristic features that overlap the DubS phenotype.

Autism risk in offspring can be assessed through quantification of male sperm mosaicism.

De novo mutations arising on the paternal chromosome make the largest known contribution to autism risk, and correlate with paternal age at the time of conception. The recurrence risk for autism spectrum disorders is substantial, leading many families to decline future pregnancies, but the potential impact of assessing parental gonadal mosaicism has not been considered. We measured sperm mosaicism using deep-whole-genome sequencing, for variants both present in an offspring and evident only in father's sperm, and identified single-nucleotide, structural and short tandem-repeat variants. We found that mosaicism quantification can stratify autism spectrum disorders recurrence risk due to de novo mutations into a vast majority with near 0% recurrence and a small fraction with a substantially higher and quantifiable risk, and we identify novel mosaic variants at risk for transmission to a future offspring. This suggests, therefore, that genetic counseling would benefit from the addition of sperm mosaicism assessment.

Pathogenicity and functional impact of non-frameshifting insertion/deletion variation in the human genome.

Differentiation between phenotypically neutral and disease-causing genetic variation remains an open and relevant problem. Among different types of variation, non-frameshifting insertions and deletions (indels) represent an understudied group with widespread phenotypic consequences. To address this challenge, we present a machine learning method, MutPred-Indel, that predicts pathogenicity and identifies types of functional residues impacted by non-frameshifting insertion/deletion variation. The model shows good predictive performance as well as the ability to identify impacted structural and functional residues including secondary structure, intrinsic disorder, metal and macromolecular binding, post-translational modifications, allosteric sites, and catalytic residues. We identify structural and functional mechanisms impacted preferentially by germline variation from the Human Gene Mutation Database, recurrent somatic variation from COSMIC in the context of different cancers, as well as de novo variants from families with autism spectrum disorder. Further, the distributions of pathogenicity prediction scores generated by MutPred-Indel are shown to differentiate highly recurrent from non-recurrent somatic variation. Collectively, we present a framework to facilitate the interrogation of both pathogenicity and the functional effects of non-frameshifting insertion/deletion variants. The MutPred-Indel webserver is available at http://mutpred.mutdb.org/.

Multi-platform discovery of haplotype-resolved structural variation in human genomes.

The incomplete identification of structural variants (SVs) from whole-genome sequencing data limits studies of human genetic diversity and disease association. Here, we apply a suite of long-read, short-read, strand-specific sequencing technologies, optical mapping, and variant discovery algorithms to comprehensively analyze three trios to define the full spectrum of human genetic variation in a haplotype-resolved manner. We identify 818,054 indel variants (<50 bp) and 27,622 SVs (≥50 bp) per genome. We also discover 156 inversions per genome and 58 of the inversions intersect with the critical regions of recurrent microdeletion and microduplication syndromes. Taken together, our SV callsets represent a three to sevenfold increase in SV detection compared to most standard high-throughput sequencing studies, including those from the 1000 Genomes Project. The methods and the dataset presented serve as a gold standard for the scientific community allowing us to make recommendations for maximizing structural variation sensitivity for future genome sequencing studies.

Paternally inherited cis-regulatory structural variants are associated with autism.

The genetic basis of autism spectrum disorder (ASD) is known to consist of contributions from de novo mutations in variant-intolerant genes. We hypothesize that rare inherited structural variants in cis-regulatory elements (CRE-SVs) of these genes also contribute to ASD. We investigated this by assessing the evidence for natural selection and transmission distortion of CRE-SVs in whole genomes of 9274 subjects from 2600 families affected by ASD. In a discovery cohort of 829 families, structural variants were depleted within promoters and untranslated regions, and paternally inherited CRE-SVs were preferentially transmitted to affected offspring and not to their unaffected siblings. The association of paternal CRE-SVs was replicated in an independent sample of 1771 families. Our results suggest that rare inherited noncoding variants predispose children to ASD, with differing contributions from each parent.

SV2: accurate structural variation genotyping and de novo mutation detection from whole genomes.

Motivation: Structural variation (SV) detection from short-read whole genome sequencing is error prone, presenting significant challenges for population or family-based studies of disease. Results: Here, we describe SV2, a machine-learning algorithm for genotyping deletions and duplications from paired-end sequencing data. SV2 can rapidly integrate variant calls from multiple structural variant discovery algorithms into a unified call set with high genotyping accuracy and capability to detect de novo mutations. Availability and implementation: SV2 is freely available on GitHub (https://github.com/dantaki/SV2). Contact: jsebat@ucsd.edu. Supplementary information: Supplementary data are available at Bioinformatics online.

Contribution of copy number variants to schizophrenia from a genome-wide study of 41,321 subjects.

Copy number variants (CNVs) have been strongly implicated in the genetic etiology of schizophrenia (SCZ). However, genome-wide investigation of the contribution of CNV to risk has been hampered by limited sample sizes. We sought to address this obstacle by applying a centralized analysis pipeline to a SCZ cohort of 21,094 cases and 20,227 controls. A global enrichment of CNV burden was observed in cases (odds ratio (OR) = 1.11, P = 5.7 × 10-15), which persisted after excluding loci implicated in previous studies (OR = 1.07, P = 1.7 × 10-6). CNV burden was enriched for genes associated with synaptic function (OR = 1.68, P = 2.8 × 10-11) and neurobehavioral phenotypes in mouse (OR = 1.18, P = 7.3 × 10-5). Genome-wide significant evidence was obtained for eight loci, including 1q21.1, 2p16.3 (NRXN1), 3q29, 7q11.2, 15q13.3, distal 16p11.2, proximal 16p11.2 and 22q11.2. Suggestive support was found for eight additional candidate susceptibility and protective loci, which consisted predominantly of CNVs mediated by nonallelic homologous recombination.

Frequency and Complexity of De Novo Structural Mutation in Autism.

Genetic studies of autism spectrum disorder (ASD) have established that de novo duplications and deletions contribute to risk. However, ascertainment of structural variants (SVs) has been restricted by the coarse resolution of current approaches. By applying a custom pipeline for SV discovery, genotyping, and de novo assembly to genome sequencing of 235 subjects (71 affected individuals, 26 healthy siblings, and their parents), we compiled an atlas of 29,719 SV loci (5,213/genome), comprising 11 different classes. We found a high diversity of de novo mutations, the majority of which were undetectable by previous methods. In addition, we observed complex mutation clusters where combinations of de novo SVs, nucleotide substitutions, and indels occurred as a single event. We estimate a high rate of structural mutation in humans (20%) and propose that genetic risk for ASD is attributable to an elevated frequency of gene-disrupting de novo SVs, but not an elevated rate of genome rearrangement.

An integrated map of structural variation in 2,504 human genomes.

Structural variants are implicated in numerous diseases and make up the majority of varying nucleotides among human genomes. Here we describe an integrated set of eight structural variant classes comprising both balanced and unbalanced variants, which we constructed using short-read DNA sequencing data and statistically phased onto haplotype blocks in 26 human populations. Analysing this set, we identify numerous gene-intersecting structural variants exhibiting population stratification and describe naturally occurring homozygous gene knockouts that suggest the dispensability of a variety of human genes. We demonstrate that structural variants are enriched on haplotypes identified by genome-wide association studies and exhibit enrichment for expression quantitative trait loci. Additionally, we uncover appreciable levels of structural variant complexity at different scales, including genic loci subject to clusters of repeated rearrangement and complex structural variants with multiple breakpoints likely to have formed through individual mutational events. Our catalogue will enhance future studies into structural variant demography, functional impact and disease association.

Nucleocapsid Protein: A Desirable Target for Future Therapies Against HIV-1.

The currently available anti-HIV-1 therapeutics is highly beneficial to infected patients. However, clinical failures occur as a result of the ability of HIV-1 to rapidly mutate. One approach to overcome drug resistance is to target HIV-1 proteins that are highly conserved among phylogenetically distant viral strains and currently not targeted by available therapies. In this respect, the nucleocapsid (NC) protein, a zinc finger protein, is particularly attractive, as it is highly conserved and plays a central role in virus replication, mainly by interacting with nucleic acids. The compelling rationale for considering NC as a viable drug target is illustrated by the fact that point mutants of this protein lead to noninfectious viruses and by the inability to select viruses resistant to a first generation of anti-NC drugs. In our review, we discuss the most relevant properties and functions of NC, as well as recent developments of small molecules targeting NC. Zinc ejectors show strong antiviral activity, but are endowed with a low therapeutic index due to their lack of specificity, which has resulted in toxicity. Currently, they are mainly being investigated for use as topical microbicides. Greater specificity may be achieved by using non-covalent NC inhibitors (NCIs) targeting the hydrophobic platform at the top of the zinc fingers or key nucleic acid partners of NC. Within the last few years, innovative methodologies have been developed to identify NCIs. Though the antiviral activity of the identified NCIs needs still to be improved, these compounds strongly support the druggability of NC and pave the way for future structure-based design and optimization of efficient NCIs.