Using a new analytic approach for genotyping and phenotyping chromosome 9p deletion syndrome.

Using a new analytic method ("unique non-overlapping region" (UNOR) analysis), we characterized the genotypes and phenotypes of a large cohort of individuals diagnosed with chromosome 9p deletion syndrome (9PMS) and defined critical genomic regions. We extracted phenotypic information from 48 individuals with 9PMS from medical records and used a guided interview with caregivers to clarify ambiguities. Using high-resolution whole-genome sequencing for breakpoint definition, we aligned deletions and drew virtual breakpoints to obtain UNORs associated with phenotypic characteristics. We next extracted genotype and phenotype data for 57 individuals identified from a systematic review of the 9PMS literature and analyzed these as above. Common phenotypic features included developmental delay/intellectual disability, dysmorphic features, hypotonia, genital defects in XY individuals, psychiatric diagnoses, chronic constipation, atopic disease, vision problems, autism spectrum disorder, gastroesophageal reflux disease, trigonocephaly, congenital heart disease, and neonatal hypoglycemia. Our approach confirmed previous literature reports of an association of FREM1 with trigonocephaly and suggested a possible modifier element for this phenotype. In conclusion, the UNOR approach delineated phenotypic characteristics for 9PMS and confirmed the critical role of FREM1 and a possible long-distance regulatory element in pathogenesis of trigonocephaly that will need to be replicated in future studies.

Examining Sex Differences in Autism Heritability.

Importance: Autism spectrum disorder (ASD) is a neurodevelopmental disorder more prevalent in males than in females. The cause of ASD is largely genetic, but the association of genetics with the skewed sex ratio is not yet understood. To our knowledge, no large population-based study has provided estimates of heritability by sex. Objective: To estimate the sex-specific heritability of ASD. Design, Setting, and Participants: This was a population-based, retrospective analysis using national health registers of nontwin siblings and cousins from Sweden born between January 1, 1985, and December 31, 1998, with follow-up to 19 years of age. Data analysis occurred from August 2022 to November 2023. Main Outcomes and Measures: Models were fitted to estimate the relative variance in risk for ASD occurrence owing to sex-specific additive genetics, shared environmental effects, and a common residual term. The residual term conceptually captured other factors that promote individual behavioral variation (eg, maternal effects, de novo variants, rare genetic variants not additively inherited, or gene-environment interactions). Estimates were adjusted for differences in prevalence due to birth year and maternal and paternal age by sex. Results: The sample included 1 047 649 individuals in 456 832 families (538 283 males [51.38%]; 509 366 females [48.62%]). Within the entire sample, 12 226 (1.17%) received a diagnosis of ASD, comprising 8128 (1.51%) males and 4098 (0.80%) females. ASD heritability was estimated at 87.0% (95% CI, 81.4%-92.6%) for males and 75.7% (95% CI, 68.4%-83.1%) for females with a difference in heritability estimated at 11.3% (95% CI, 1.0%-21.6%). There was no support for shared environmental contributions. Conclusions and Relevance: These findings suggest that the degree of phenotypic variation attributable to genetic differences (heritability) differs between males and females, indicating that some of the underlying causes of the condition may differ between the 2 sexes. The skewed sex ratio in ASD may be partly explained by differences in genetic variance between the sexes.

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.

The Impact of Patterns in Linkage Disequilibrium and Sequencing Quality on the Imprint of Balancing Selection.

Regions under balancing selection are characterized by dense polymorphisms and multiple persistent haplotypes, along with other sequence complexities. Successful identification of these patterns depends on both the statistical approach and the quality of sequencing. To address this challenge, at first, a new statistical method called LD-ABF was developed, employing efficient Bayesian techniques to effectively test for balancing selection. LD-ABF demonstrated the most robust detection of selection in a variety of simulation scenarios, compared against a range of existing tests/tools (Tajima's D, HKA, Dng, BetaScan, and BalLerMix). Furthermore, the impact of the quality of sequencing on detection of balancing selection was explored, as well, using: (i) SNP genotyping and exome data, (ii) targeted high-resolution HLA genotyping (IHIW), and (iii) whole-genome long-read sequencing data (Pangenome). In the analysis of SNP genotyping and exome data, we identified known targets and 38 new selection signatures in genes not previously linked to balancing selection. To further investigate the impact of sequencing quality on detection of balancing selection, a detailed investigation of the MHC was performed with high-resolution HLA typing data. Higher quality sequencing revealed the HLA-DQ genes consistently demonstrated strong selection signatures otherwise not observed from the sparser SNP array and exome data. The HLA-DQ selection signature was also replicated in the Pangenome samples using considerably less samples but, with high-quality long-read sequence data. The improved statistical method, coupled with higher quality sequencing, leads to more consistent identification of selection and enhanced localization of variants under selection, particularly in complex regions.

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.

Unveiling the crucial neuronal role of the proteasomal ATPase subunit gene PSMC5 in neurodevelopmental proteasomopathies.

Neurodevelopmental proteasomopathies represent a distinctive category of neurodevelopmental disorders (NDD) characterized by genetic variations within the 26S proteasome, a protein complex governing eukaryotic cellular protein homeostasis. In our comprehensive study, we identified 23 unique variants in PSMC5 , which encodes the AAA-ATPase proteasome subunit PSMC5/Rpt6, causing syndromic NDD in 38 unrelated individuals. Overexpression of PSMC5 variants altered human hippocampal neuron morphology, while PSMC5 knockdown led to impaired reversal learning in flies and loss of excitatory synapses in rat hippocampal neurons. PSMC5 loss-of-function resulted in abnormal protein aggregation, profoundly impacting innate immune signaling, mitophagy rates, and lipid metabolism in affected individuals. Importantly, targeting key components of the integrated stress response, such as PKR and GCN2 kinases, ameliorated immune dysregulations in cells from affected individuals. These findings significantly advance our understanding of the molecular mechanisms underlying neurodevelopmental proteasomopathies, provide links to research in neurodegenerative diseases, and open up potential therapeutic avenues.

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.

A common single nucleotide variant in the cytokine receptor-like factor-3 (CRLF3) gene causes neuronal deficits in human and mouse cells.

Single nucleotide variants in the general population are common genomic alterations, where the majority are presumed to be silent polymorphisms without known clinical significance. Using human induced pluripotent stem cell (hiPSC) cerebral organoid modeling of the 1.4 megabase Neurofibromatosis type 1 (NF1) deletion syndrome, we previously discovered that the cytokine receptor-like factor-3 (CRLF3) gene, which is co-deleted with the NF1 gene, functions as a major regulator of neuronal maturation. Moreover, children with NF1 and the CRLF3L389P variant have greater autism burden, suggesting that this gene might be important for neurologic function. To explore the functional consequences of this variant, we generated CRLF3L389P-mutant hiPSC lines and Crlf3L389P-mutant genetically engineered mice. While this variant does not impair protein expression, brain structure, or mouse behavior, CRLF3L389P-mutant human cerebral organoids and mouse brains exhibit impaired neuronal maturation and dendrite formation. In addition, Crlf3L389P-mutant mouse neurons have reduced dendrite lengths and branching, without any axonal deficits. Moreover, Crlf3L389P-mutant mouse hippocampal neurons have decreased firing rates and synaptic current amplitudes relative to wild type controls. Taken together, these findings establish the CRLF3L389P variant as functionally deleterious and suggest that it may be a neurodevelopmental disease modifier.

High Coverage Highly Accurate Long-Read Sequencing of a Mouse Neuronal Cell Line Using the PacBio Revio Sequencer.

Recently, Pacific Biosciences released a new highly accurate long-read sequencer called the Revio System that is projected to generate 30× HiFi whole-genome sequencing for the human genome within one sequencing SMRT Cell. Mouse and human genomes are similar in size. In this study, we sought to test this new sequencer by characterizing the genome and epigenome of the mouse neuronal cell line Neuro-2a. We generated long-read HiFi whole-genome sequencing on three Revio SMRT Cells, achieving a total coverage of 98×, with 30×, 32×, and 36× coverage respectively for each of the three Revio SMRT Cells. We performed several tests on these data including single-nucleotide variant and small insertion detection using GPU-accelerated DeepVariant, structural variant detection with pbsv, methylation detection with pb-CpG-tools, and generating de novo assemblies with the HiCanu and hifiasm assemblers. Overall, we find consistency across SMRT Cells in coverage, detection of variation, methylation, and de novo assemblies for each of the three SMRT Cells.

Quantitative determination of SLC2A1 variant functional effects in GLUT1 deficiency syndrome.

OBJECTIVE: The goal of this study is to demonstrate the utility of a growth assay to quantify the functional impact of single nucleotide variants (SNVs) in SLC2A1, the gene responsible for Glut1DS. METHODS: The functional impact of 40 SNVs in SLC2A1 was quantitatively determined in HAP1 cells in which SLC2A1 is required for growth. Donor libraries were introduced into the endogenous SLC2A1 gene in HAP1-Lig4KO cells using CRISPR/Cas9. Cell populations were harvested and sequenced to quantify the effect of variants on growth and generate a functional score. Quantitative functional scores were compared to 3-OMG uptake, SLC2A1 cell surface expression, CADD score, and clinical data, including CSF/blood glucose ratio. RESULTS: Nonsense variants (N = 3) were reduced in cell culture over time resulting in negative scores (mean score: -1.15 ± 0.17), whereas synonymous variants (N = 10) were not depleted (mean score: 0.25 ± 0.12) (P < 2e-16). Missense variants (N = 27) yielded a range of functional scores including slightly negative scores, supporting a partial function and intermediate phenotype. Several variants with normal results on either cell surface expression (p.N34S and p.W65R) or 3-OMG uptake (p.W65R) had negative functional scores. There is a moderate but significant correlation between our functional scores and CADD scores. INTERPRETATION: Cell growth is useful to quantitatively determine the functional effects of SLC2A1 variants. Nonsense variants were reliably distinguished from benign variants in this in vitro functional assay. For facilitating early diagnosis and therapeutic intervention, future work is needed to determine the functional effect of every possible variant in SLC2A1.

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

Motivation: de novo variant (DNV) calling is challenging from parent-child sequenced trio data. We developed Hare And Tortoise (HAT) to work as an automated workflow to detect DNVs in highly accurate short-read and long-read sequencing data. Reliable detection of DNVs is important for human genetics studies (e.g., autism, epilepsy). Results: HAT is a workflow to detect DNVs from short-read and long read sequencing data. This workflow 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 short-read whole-exome sequencing, short-read whole-genome sequencing, and highly accurate long-read sequencing data.

A gap-free genome assembly of Chlamydomonas reinhardtii and detection of translocations induced by CRISPR-mediated mutagenesis.

Genomic assemblies of the unicellular green alga Chlamydomonas reinhardtii have provided important resources for researchers. However, assembly errors, large gaps, and unplaced scaffolds as well as strain-specific variants currently impede many types of analysis. By combining PacBio HiFi and Oxford Nanopore long-read technologies, we generated a de novo genome assembly for strain CC-5816, derived from crosses of strains CC-125 and CC-124. Multiple methods of evaluating genome completeness and base-pair error rate suggest that the final telomere-to-telomere assembly is highly accurate. The CC-5816 assembly enabled previously difficult analyses that include characterization of the 17 centromeres, rDNA arrays on three chromosomes, and 56 insertions of organellar DNA into the nuclear genome. Using Nanopore sequencing, we identified sites of cytosine (CpG) methylation, which are enriched at centromeres. We analyzed CRISPR-Cas9 insertional mutants in the PF23 gene. Two of the three alleles produced progeny that displayed patterns of meiotic inviability that suggested the presence of a chromosomal aberration. Mapping Nanopore reads from pf23-2 and pf23-3 onto the CC-5816 genome showed that these two strains each carry a translocation that was initiated at the PF23 gene locus on chromosome 11 and joined with chromosomes 5 or 3, respectively. The translocations were verified by demonstrating linkage between loci on the two translocated chromosomes in meiotic progeny. The three pf23 alleles display the expected short-cilia phenotype, and immunoblotting showed that pf23-2 lacks the PF23 protein. Our CC-5816 genome assembly will undoubtedly provide an important tool for the Chlamydomonas research community.

de novo variant calling identifies cancer mutation signatures in the 1000 Genomes Project.

Detection of de novo variants (DNVs) is critical for studies of disease-related variation and mutation rates. To accelerate DNV calling, we developed a graphics processing units-based workflow. We applied our workflow to whole-genome sequencing data from three parent-child sequenced cohorts including the Simons Simplex Collection (SSC), Simons Foundation Powering Autism Research (SPARK), and the 1000 Genomes Project (1000G) that were sequenced using DNA from blood, saliva, and lymphoblastoid cell lines (LCLs), respectively. The SSC and SPARK DNV callsets were within expectations for number of DNVs, percent at CpG sites, phasing to the paternal chromosome of origin, and average allele balance. However, the 1000G DNV callset was not within expectations and contained excessive DNVs that are likely cell line artifacts. Mutation signature analysis revealed 30% of 1000G DNV signatures matched B-cell lymphoma. Furthermore, we found variants in DNA repair genes and at Clinvar pathogenic or likely-pathogenic sites and significant excess of protein-coding DNVs in IGLL5; a gene known to be involved in B-cell lymphomas. Our study provides a new rapid DNV caller for the field and elucidates important implications of using sequencing data from LCLs for reference building and disease-related projects.

Integrating de novo and inherited variants in 42,607 autism cases identifies mutations in new moderate-risk genes.

To capture the full spectrum of genetic risk for autism, we performed a two-stage analysis of rare de novo and inherited coding variants in 42,607 autism cases, including 35,130 new cases recruited online by SPARK. We identified 60 genes with exome-wide significance (P < 2.5 × 10-6), including five new risk genes (NAV3, ITSN1, MARK2, SCAF1 and HNRNPUL2). The association of NAV3 with autism risk is primarily driven by rare inherited loss-of-function (LoF) variants, with an estimated relative risk of 4, consistent with moderate effect. Autistic individuals with LoF variants in the four moderate-risk genes (NAV3, ITSN1, SCAF1 and HNRNPUL2; n = 95) have less cognitive impairment than 129 autistic individuals with LoF variants in highly penetrant genes (CHD8, SCN2A, ADNP, FOXP1 and SHANK3) (59% vs 88%, P = 1.9 × 10-6). Power calculations suggest that much larger numbers of autism cases are needed to identify additional moderate-risk genes.

Can the "female protective effect" liability threshold model explain sex differences in autism spectrum disorder?

Male sex is a strong risk factor for autism spectrum disorder (ASD). The leading theory for a "female protective effect" (FPE) envisions males and females have "differing thresholds" under a "liability threshold model" (DT-LTM). Specifically, this model posits that females require either a greater number or larger magnitude of risk factors (i.e., greater liability) to manifest ASD, which is supported by the finding that a greater proportion of females with ASD have highly penetrant genetic mutations. Herein, we derive testable hypotheses from the DT-LTM for ASD, investigating heritability, familial recurrence, correlation between ASD penetrance and sex ratio, population traits, clinical features, the stability of the sex ratio across diagnostic changes, and highlight other key prerequisites. Our findings reveal that several key predictions of the DT-LTM are not supported by current data, requiring us to establish a different conceptual framework for evaluating alternate models that explain sex differences in ASD.

Germline mosaicism of a missense variant in KCNC2 in a multiplex family with autism and epilepsy characterized by long-read sequencing.

Currently, protein-coding de novo variants and large copy number variants have been identified as important for ~30% of individuals with autism. One approach to identify relevant variation in individuals who lack these types of events is by utilizing newer genomic technologies. In this study, highly accurate PacBio HiFi long-read sequencing was applied to a family with autism, epileptic encephalopathy, cognitive impairment, and mild dysmorphic features (two affected female siblings, unaffected parents, and one unaffected male sibling) with no known clinical variant. From our long-read sequencing data, a de novo missense variant in the KCNC2 gene (encodes Kv3.2) was identified in both affected children. This variant was phased to the paternal chromosome of origin and is likely a germline mosaic. In silico assessment revealed the variant was not in controls, highly conserved, and predicted damaging. This specific missense variant (Val473Ala) has been shown in both an ortholog and paralog of Kv3.2 to accelerate current decay, shift the voltage dependence of activation, and prevent the channel from entering a long-lasting open state. Seven additional missense variants have been identified in other individuals with neurodevelopmental disorders (p = 1.03 × 10-5 ). KCNC2 is most highly expressed in the brain; in particular, in the thalamus and is enriched in GABAergic neurons. Long-read sequencing was useful in discovering the relevant variant in this family with autism that had remained a mystery for several years and will potentially have great benefits in the clinic once it is widely available.

Ancestry adjustment improves genome-wide estimates of regional intolerance.

Genomic regions subject to purifying selection are more likely to carry disease-causing mutations than regions not under selection. Cross species conservation is often used to identify such regions but with limited resolution to detect selection on short evolutionary timescales such as that occurring in only one species. In contrast, genetic intolerance looks for depletion of variation relative to expectation within a species, allowing species-specific features to be identified. When estimating the intolerance of noncoding sequence, methods strongly leverage variant frequency distributions. As the expected distributions depend on ancestry, if not properly controlled for, ancestral population source may obfuscate signals of selection. We demonstrate that properly incorporating ancestry in intolerance estimation greatly improved variant classification. We provide a genome-wide intolerance map that is conditional on ancestry and likely to be particularly valuable for variant prioritization.

From karyotypes to precision genomics in 9p deletion and duplication syndromes.

While 9p deletion and duplication syndromes have been studied for several years, small sample sizes and minimal high-resolution data have limited a comprehensive delineation of genotypic and phenotypic characteristics. In this study, we examined genetic data from 719 individuals in the worldwide 9p Network Cohort: a cohort seven to nine times larger than any previous study of 9p. Most breakpoints occur in bands 9p22 and 9p24, accounting for 35% and 38% of all breakpoints, respectively. Bands 9p11 and 9p12 have the fewest breakpoints, with each accounting for 0.6% of all breakpoints. The most common phenotype in 9p deletion and duplication syndromes is developmental delay, and we identified eight known neurodevelopmental disorder genes in 9p22 and 9p24. Since it has been previously reported that some individuals have a secondary structural variant related to the 9p variant, we examined our cohort for these variants and found 97 events. The top secondary variant involved 9q in 14 individuals (1.9%), including ring chromosomes and inversions. We identified a gender bias with significant enrichment for females (p = 0.0006) that may arise from a sex reversal in some individuals with 9p deletions. Genes on 9p were characterized regarding function, constraint metrics, and protein-protein interactions, resulting in a prioritized set of genes for further study. Finally, we achieved precision genomics in one child with a complex 9p structural variation using modern genomic technologies, demonstrating that long-read sequencing will be integral for some cases. Our study is the largest ever on 9p-related syndromes and provides key insights into genetic factors involved in these syndromes.

The Mutationathon highlights the importance of reaching standardization in estimates of pedigree-based germline mutation rates.

In the past decade, several studies have estimated the human per-generation germline mutation rate using large pedigrees. More recently, estimates for various nonhuman species have been published. However, methodological differences among studies in detecting germline mutations and estimating mutation rates make direct comparisons difficult. Here, we describe the many different steps involved in estimating pedigree-based mutation rates, including sampling, sequencing, mapping, variant calling, filtering, and appropriately accounting for false-positive and false-negative rates. For each step, we review the different methods and parameter choices that have been used in the recent literature. Additionally, we present the results from a 'Mutationathon,' a competition organized among five research labs to compare germline mutation rate estimates for a single pedigree of rhesus macaques. We report almost a twofold variation in the final estimated rate among groups using different post-alignment processing, calling, and filtering criteria, and provide details into the sources of variation across studies. Though the difference among estimates is not statistically significant, this discrepancy emphasizes the need for standardized methods in mutation rate estimations and the difficulty in comparing rates from different studies. Finally, this work aims to provide guidelines for computational and statistical benchmarks for future studies interested in identifying germline mutations from pedigrees.

Neurofibromatosis-1 Gene Mutational Profiles Differ Between Syndromic Disease and Sporadic Cancers.

Objectives: Variants in the neurofibromatosis type 1 (NF1) gene are not only responsible for the NF1 cancer predisposition syndrome, but also frequently identified in cancers arising in the general population. While germline variants are pathogenic, it is not known whether those that arise in cancer (somatic variants) are passenger or driver variants. To address this question, we sought to define the landscape of NF1 variants in sporadic cancers. Methods: NF1 variants in sporadic cancers were compiled using data curated on the c-Bio database and compared with published germline variants and Genome Aggregation Database data. Pathogenicity was determined using Polyphen and Sorting Intolerant From Tolerant prediction tools. Results: The spectrum of NF1 variants in sporadic tumors differ from those most commonly seen in individuals with NF1. In addition, the type and location of the variants in sporadic cancer differ from germline variants, where a high proportion of missense variants were found. Finally, many of the sporadic cancer NF1 variants were not predicted to be pathogenic. Discussion: Taken together, these findings suggest that a significant proportion of NF1 variants in sporadic cancer may be passenger variants or hypomorphic alleles. Further mechanistic studies are warranted to define their unique roles in nonsyndromic cancer pathobiology.