Megabase Length Hypermutation Accompanies Human Structural Variation at 17p11.2.

DNA rearrangements resulting in human genome structural variants (SVs) are caused by diverse mutational mechanisms. We used long- and short-read sequencing technologies to investigate end products of de novo chromosome 17p11.2 rearrangements and query the molecular mechanisms underlying both recurrent and non-recurrent events. Evidence for an increased rate of clustered single-nucleotide variant (SNV) mutation in cis with non-recurrent rearrangements was found. Indel and SNV formation are associated with both copy-number gains and losses of 17p11.2, occur up to ∼1 Mb away from the breakpoint junctions, and favor C > G transversion substitutions; results suggest that single-stranded DNA is formed during the genesis of the SV and provide compelling support for a microhomology-mediated break-induced replication (MMBIR) mechanism for SV formation. Our data show an additional mutational burden of MMBIR consisting of hypermutation confined to the locus and manifesting as SNVs and indels predominantly within genes.

An Organismal CNV Mutator Phenotype Restricted to Early Human Development.

De novo copy number variants (dnCNVs) arising at multiple loci in a personal genome have usually been considered to reflect cancer somatic genomic instabilities. We describe a multiple dnCNV (MdnCNV) phenomenon in which individuals with genomic disorders carry five to ten constitutional dnCNVs. These CNVs originate from independent formation incidences, are predominantly tandem duplications or complex gains, exhibit breakpoint junction features reminiscent of replicative repair, and show increased de novo point mutations flanking the rearrangement junctions. The active CNV mutation shower appears to be restricted to a transient perizygotic period. We propose that a defect in the CNV formation process is responsible for the "CNV-mutator state," and this state is dampened after early embryogenesis. The constitutional MdnCNV phenomenon resembles chromosomal instability in various cancers. Investigations of this phenomenon may provide unique access to understanding genomic disorders, structural variant mutagenesis, human evolution, and cancer biology.

The impact of clinical genome sequencing in a global population with suspected rare genetic disease.

There is mounting evidence of the value of clinical genome sequencing (cGS) in individuals with suspected rare genetic disease (RGD), but cGS performance and impact on clinical care in a diverse population drawn from both high-income countries (HICs) and low- and middle-income countries (LMICs) has not been investigated. The iHope program, a philanthropic cGS initiative, established a network of 24 clinical sites in eight countries through which it provided cGS to individuals with signs or symptoms of an RGD and constrained access to molecular testing. A total of 1,004 individuals (median age, 6.5 years; 53.5% male) with diverse ancestral backgrounds (51.8% non-majority European) were assessed from June 2016 to September 2021. The diagnostic yield of cGS was 41.4% (416/1,004), with individuals from LMIC sites 1.7 times more likely to receive a positive test result compared to HIC sites (LMIC 56.5% [195/345] vs. HIC 33.5% [221/659], OR 2.6, 95% CI 1.9-3.4, p < 0.0001). A change in diagnostic evaluation occurred in 76.9% (514/668) of individuals. Change of management, inclusive of specialty referrals, imaging and testing, therapeutic interventions, and palliative care, was reported in 41.4% (285/694) of individuals, which increased to 69.2% (480/694) when genetic counseling and avoidance of additional testing were also included. Individuals from LMIC sites were as likely as their HIC counterparts to experience a change in diagnostic evaluation (OR 6.1, 95% CI 1.1-∞, p = 0.05) and change of management (OR 0.9, 95% CI 0.5-1.3, p = 0.49). Increased access to genomic testing may support diagnostic equity and the reduction of global health care disparities.

Activation of multiple proto-oncogenic tyrosine kinases in breast cancer via loss of the PTPN12 phosphatase.

Among breast cancers, triple-negative breast cancer (TNBC) is the most poorly understood and is refractory to current targeted therapies. Using a genetic screen, we identify the PTPN12 tyrosine phosphatase as a tumor suppressor in TNBC. PTPN12 potently suppresses mammary epithelial cell proliferation and transformation. PTPN12 is frequently compromised in human TNBCs, and we identify an upstream tumor-suppressor network that posttranscriptionally controls PTPN12. PTPN12 suppresses transformation by interacting with and inhibiting multiple oncogenic tyrosine kinases, including HER2 and EGFR. The tumorigenic and metastatic potential of PTPN12-deficient TNBC cells is severely impaired upon restoration of PTPN12 function or combined inhibition of PTPN12-regulated tyrosine kinases, suggesting that TNBCs are dependent on the proto-oncogenic tyrosine kinases constrained by PTPN12. Collectively, these data identify PTPN12 as a commonly inactivated tumor suppressor and provide a rationale for combinatorially targeting proto-oncogenic tyrosine kinases in TNBC and other cancers based on their profile of tyrosine-phosphatase activity.

Sox7-positive endothelial progenitors establish coronary arteries and govern ventricular compaction.

The cardiac endothelium influences ventricular chamber development by coordinating trabeculation and compaction. However, the endothelial-specific molecular mechanisms mediating this coordination are not fully understood. Here, we identify the Sox7 transcription factor as a critical cue instructing cardiac endothelium identity during ventricular chamber development. Endothelial-specific loss of Sox7 function in mice results in cardiac ventricular defects similar to non-compaction cardiomyopathy, with a change in the proportions of trabecular and compact cardiomyocytes in the mutant hearts. This phenotype is paralleled by abnormal coronary artery formation. Loss of Sox7 function disrupts the transcriptional regulation of the Notch pathway and connexins 37 and 40, which govern coronary arterial specification. Upon Sox7 endothelial-specific deletion, single-nuclei transcriptomics analysis identifies the depletion of a subset of Sox9/Gpc3-positive endocardial progenitor cells and an increase in erythro-myeloid cell lineages. Fate mapping analysis reveals that a subset of Sox7-null endothelial cells transdifferentiate into hematopoietic but not cardiomyocyte lineages. Our findings determine that Sox7 maintains cardiac endothelial cell identity, which is crucial to the cellular cross-talk that drives ventricular compaction and coronary artery development.

Clinical genome sequencing: Three years' experience at a tertiary children's hospital.

PURPOSE: Genome sequencing (GS) may shorten the diagnostic odyssey for patients, but clinical experience with this assay in nonresearch settings remains limited. Texas Children's Hospital began offering GS as a clinical test to admitted patients in 2020, providing an opportunity to study GS utilization, possibilities for test optimization, and testing outcomes. METHODS: We retrospectively reviewed GS orders for admitted patients for a nearly 3-year period from March 2020 through December 2022. We gathered anonymized clinical data from the electronic health record to answer the study questions. RESULTS: The diagnostic yield over 97 admitted patients was 35%. The majority of GS clinical indications were neurologic or metabolic (61%) and most patients were in intensive care (58%). Tests were often characterized as candidates for intervention/improvement (56%), frequently because of redundancy with prior testing. Patients receiving GS without prior exome sequencing (ES) had higher diagnostic rates (45%) than the cohort as a whole. In 2 cases, GS revealed a molecular diagnosis that is unlikely to be detected by ES. CONCLUSION: The performance of GS in clinical settings likely justifies its use as a first-line diagnostic test, but the incremental benefit for patients with prior ES may be limited.

Clinical exome sequencing data reveal high diagnostic yields for congenital diaphragmatic hernia plus (CDH+) and new phenotypic expansions involving CDH.

BACKGROUND: Congenital diaphragmatic hernia (CDH) is a life-threatening birth defect that often co-occurs with non-hernia-related anomalies (CDH+). While copy number variant (CNV) analysis is often employed as a diagnostic test for CDH+, clinical exome sequencing (ES) has not been universally adopted. METHODS: We analysed a clinical database of ~12 000 test results to determine the diagnostic yields of ES in CDH+ and to identify new phenotypic expansions. RESULTS: Among the 76 cases with an indication of CDH+, a molecular diagnosis was made in 28 cases for a diagnostic yield of 37% (28/76). A provisional diagnosis was made in seven other cases (9%; 7/76). Four individuals had a diagnosis of Kabuki syndrome caused by frameshift variants in KMT2D. Putatively deleterious variants in ALG12 and EP300 were each found in two individuals, supporting their role in CDH development. We also identified individuals with de novo pathogenic variants in FOXP1 and SMARCA4, and compound heterozygous pathogenic variants in BRCA2. The role of these genes in CDH development is supported by the expression of their mouse homologs in the developing diaphragm, their high CDH-specific pathogenicity scores generated using a previously validated algorithm for genome-scale knowledge synthesis and previously published case reports. CONCLUSION: We conclude that ES should be ordered in cases of CDH+ when a specific diagnosis is not suspected and CNV analyses are negative. Our results also provide evidence in favour of phenotypic expansions involving CDH for genes associated with ALG12-congenital disorder of glycosylation, Rubinstein-Taybi syndrome, Fanconi anaemia, Coffin-Siris syndrome and FOXP1-related disorders.

Validation Studies for Single Circulating Trophoblast Genetic Testing as a Form of Noninvasive Prenatal Diagnosis.

It has long been appreciated that genetic analysis of fetal or trophoblast cells in maternal blood could revolutionize prenatal diagnosis. We implemented a protocol for single circulating trophoblast (SCT) testing using positive selection by magnetic-activated cell sorting and single-cell low-coverage whole-genome sequencing to detect fetal aneuploidies and copy-number variants (CNVs) at ∼1 Mb resolution. In 95 validation cases, we identified on average 0.20 putative trophoblasts/mL, of which 55% were of high quality and scorable for both aneuploidy and CNVs. We emphasize the importance of analyzing individual cells because some cells are apoptotic, in S-phase, or otherwise of poor quality. When two or more high-quality trophoblast cells were available for singleton pregnancies, there was complete concordance between all trophoblasts unless there was evidence of confined placental mosaicism. SCT results were highly concordant with available clinical data from chorionic villus sampling (CVS) or amniocentesis procedures. Although determining the exact sensitivity and specificity will require more data, this study further supports the potential for SCT testing to become a diagnostic prenatal test.

Identifying phenotypic expansions for congenital diaphragmatic hernia plus (CDH+) using DECIPHER data.

Congenital diaphragmatic hernia (CDH) can occur in isolation or in conjunction with other birth defects (CDH+). A molecular etiology can only be identified in a subset of CDH cases. This is due, in part, to an incomplete understanding of the genes that contribute to diaphragm development. Here, we used clinical and molecular data from 36 individuals with CDH+ who are cataloged in the DECIPHER database to identify genes that may play a role in diaphragm development and to discover new phenotypic expansions. Among this group, we identified individuals who carried putatively deleterious sequence or copy number variants affecting CREBBP, SMARCA4, UBA2, and USP9X. The role of these genes in diaphragm development was supported by their expression in the developing mouse diaphragm, their similarity to known CDH genes using data from a previously published and validated machine learning algorithm, and/or the presence of CDH in other individuals with their associated genetic disorders. Our results demonstrate how data from DECIPHER, and other public databases, can be used to identify new phenotypic expansions and suggest that CREBBP, SMARCA4, UBA2, and USP9X play a role in diaphragm development.

Functionalization of CD36 cardiovascular disease and expression associated variants by interdisciplinary high throughput analysis.

CD36 is a platelet membrane glycoprotein whose engagement with oxidized low-density lipoprotein (oxLDL) results in platelet activation. The CD36 gene has been associated with platelet count, platelet volume, as well as lipid levels and CVD risk by genome-wide association studies. Platelet CD36 expression levels have been shown to be associated with both the platelet oxLDL response and an elevated risk of thrombo-embolism. Several genomic variants have been identified as associated with platelet CD36 levels, however none have been conclusively demonstrated to be causative. We screened 81 expression quantitative trait loci (eQTL) single nucleotide polymorphisms (SNPs) associated with platelet CD36 expression by a Massively Parallel Reporter Assay (MPRA) and analyzed the results with a novel Bayesian statistical method. Ten eQTLs located 13kb to 55kb upstream of the CD36 transcriptional start site of transcript ENST00000309881 and 49kb to 92kb upstream of transcript ENST00000447544, demonstrated significant transcription shifts between their minor and major allele in the MPRA assay. Of these, rs2366739 and rs1194196, separated by only 20bp, were confirmed by luciferase assay to alter transcriptional regulation. In addition, electromobility shift assays demonstrated differential DNA:protein complex formation between the two alleles of this locus. Furthermore, deletion of the genomic locus by CRISPR/Cas9 in K562 and Meg-01 cells results in upregulation of CD36 transcription. These data indicate that we have identified a variant that regulates expression of CD36, which in turn affects platelet function. To assess the clinical relevance of our findings we used the PhenoScanner tool, which aggregates large scale GWAS findings; the results reinforce the clinical relevance of our variants and the utility of the MPRA assay. The study demonstrates a generalizable paradigm for functional testing of genetic variants to inform mechanistic studies, support patient management and develop precision therapies.

Identifying Genes Whose Mutant Transcripts Cause Dominant Disease Traits by Potential Gain-of-Function Alleles.

Premature termination codon (PTC)-bearing transcripts are often degraded by nonsense-mediated decay (NMD) resulting in loss-of-function (LoF) alleles. However, not all PTCs result in LoF mutations, i.e., some such transcripts escape NMD and are translated to truncated peptide products that result in disease due to gain-of-function (GoF) effects. Since the location of the PTC is a major factor determining transcript fate, we hypothesized that depletion of protein-truncating variants (PTVs) within the gene region predicted to escape NMD in control databases could provide a rank for genic susceptibility for disease through GoF versus LoF. We developed an NMD escape intolerance score to rank genes based on the depletion of PTVs that would render them able to escape NMD using the Atherosclerosis Risk in Communities Study (ARIC) and the Exome Aggregation Consortium (ExAC) control databases, which was further used to screen the Baylor-Center for Mendelian Genomics disease database. This analysis revealed 1,996 genes significantly depleted for PTVs that are predicted to escape from NMD, i.e., PTVesc; further studies provided evidence that revealed a subset as candidate genes underlying Mendelian phenotypes. Importantly, these genes have characteristically low pLI scores, which can cause them to be overlooked as candidates for dominant diseases. Collectively, we demonstrate that this NMD escape intolerance score is an effective and efficient tool for gene discovery in Mendelian diseases due to production of truncated or altered proteins. More importantly, we provide a complementary analytical tool to aid identification of genes associated with dominant traits through a mechanism distinct from LoF.

Predicting human genes susceptible to genomic instability associated with Alu/Alu-mediated rearrangements.

Alu elements, the short interspersed element numbering more than 1 million copies per human genome, can mediate the formation of copy number variants (CNVs) between substrate pairs. These Alu/Alu-mediated rearrangements (AAMRs) can result in pathogenic variants that cause diseases. To investigate the impact of AAMR on gene variation and human health, we first characterized Alus that are involved in mediating CNVs (CNV-Alus) and observed that these Alus tend to be evolutionarily younger. We then computationally generated, with the assistance of a supercomputer, a test data set consisting of 78 million Alu pairs and predicted ∼18% of them are potentially susceptible to AAMR. We further determined the relative risk of AAMR in 12,074 OMIM genes using the count of predicted CNV-Alu pairs and experimentally validated the predictions with 89 samples selected by correlating predicted hotspots with a database of CNVs identified by clinical chromosomal microarrays (CMAs) on the genomes of approximately 54,000 subjects. We fine-mapped 47 duplications, 40 deletions, and two complex rearrangements and examined a total of 52 breakpoint junctions of simple CNVs. Overall, 94% of the candidate breakpoints were at least partially Alu mediated. We successfully predicted all (100%) of Alu pairs that mediated deletions (n = 21) and achieved an 87% positive predictive value overall when including AAMR-generated deletions and duplications. We provided a tool, AluAluCNVpredictor, for assessing AAMR hotspots and their role in human disease. These results demonstrate the utility of our predictive model and provide insights into the genomic features and molecular mechanisms underlying AAMR.

A joint modeling approach for longitudinal microbiome data improves ability to detect microbiome associations with disease.

Changes in the composition of the microbiome over time are associated with myriad human illnesses. Unfortunately, the lack of analytic techniques has hindered researchers' ability to quantify the association between longitudinal microbial composition and time-to-event outcomes. Prior methodological work developed the joint model for longitudinal and time-to-event data to incorporate time-dependent biomarker covariates into the hazard regression approach to disease outcomes. The original implementation of this joint modeling approach employed a linear mixed effects model to represent the time-dependent covariates. However, when the distribution of the time-dependent covariate is non-Gaussian, as is the case with microbial abundances, researchers require different statistical methodology. We present a joint modeling framework that uses a negative binomial mixed effects model to determine longitudinal taxon abundances. We incorporate these modeled microbial abundances into a hazard function with a parameterization that not only accounts for the proportional nature of microbiome data, but also generates biologically interpretable results. Herein we demonstrate the performance improvements of our approach over existing alternatives via simulation as well as a previously published longitudinal dataset studying the microbiome during pregnancy. The results demonstrate that our joint modeling framework for longitudinal microbiome count data provides a powerful methodology to uncover associations between changes in microbial abundances over time and the onset of disease. This method offers the potential to equip researchers with a deeper understanding of the associations between longitudinal microbial composition changes and disease outcomes. This new approach could potentially lead to new diagnostic biomarkers or inform clinical interventions to help prevent or treat disease.

Bayesian modelling of high-throughput sequencing assays with malacoda.

NGS studies have uncovered an ever-growing catalog of human variation while leaving an enormous gap between observed variation and experimental characterization of variant function. High-throughput screens powered by NGS have greatly increased the rate of variant functionalization, but the development of comprehensive statistical methods to analyze screen data has lagged. In the massively parallel reporter assay (MPRA), short barcodes are counted by sequencing DNA libraries transfected into cells and the cell's output RNA in order to simultaneously measure the shifts in transcription induced by thousands of genetic variants. These counts present many statistical challenges, including overdispersion, depth dependence, and uncertain DNA concentrations. So far, the statistical methods used have been rudimentary, employing transformations on count level data and disregarding experimental and technical structure while failing to quantify uncertainty in the statistical model. We have developed an extensive framework for the analysis of NGS functionalization screens available as an R package called malacoda (available from github.com/andrewGhazi/malacoda). Our software implements a probabilistic, fully Bayesian model of screen data. The model uses the negative binomial distribution with gamma priors to model sequencing counts while accounting for effects from input library preparation and sequencing depth. The method leverages the high-throughput nature of the assay to estimate the priors empirically. External annotations such as ENCODE data or DeepSea predictions can also be incorporated to obtain more informative priors-a transformative capability for data integration. The package also includes quality control and utility functions, including automated barcode counting and visualization methods. To validate our method, we analyzed several datasets using malacoda and alternative MPRA analysis methods. These data include experiments from the literature, simulated assays, and primary MPRA data. We also used luciferase assays to experimentally validate several hits from our primary data, as well as variants for which the various methods disagree and variants detectable only with the aid of external annotations.

The spliceosome is a therapeutic vulnerability in MYC-driven cancer.

MYC (also known as c-MYC) overexpression or hyperactivation is one of the most common drivers of human cancer. Despite intensive study, the MYC oncogene remains recalcitrant to therapeutic inhibition. MYC is a transcription factor, and many of its pro-tumorigenic functions have been attributed to its ability to regulate gene expression programs. Notably, oncogenic MYC activation has also been shown to increase total RNA and protein production in many tissue and disease contexts. While such increases in RNA and protein production may endow cancer cells with pro-tumour hallmarks, this increase in synthesis may also generate new or heightened burden on MYC-driven cancer cells to process these macromolecules properly. Here we discover that the spliceosome is a new target of oncogenic stress in MYC-driven cancers. We identify BUD31 as a MYC-synthetic lethal gene in human mammary epithelial cells, and demonstrate that BUD31 is a component of the core spliceosome required for its assembly and catalytic activity. Core spliceosomal factors (such as SF3B1 and U2AF1) associated with BUD31 are also required to tolerate oncogenic MYC. Notably, MYC hyperactivation induces an increase in total precursor messenger RNA synthesis, suggesting an increased burden on the core spliceosome to process pre-mRNA. In contrast to normal cells, partial inhibition of the spliceosome in MYC-hyperactivated cells leads to global intron retention, widespread defects in pre-mRNA maturation, and deregulation of many essential cell processes. Notably, genetic or pharmacological inhibition of the spliceosome in vivo impairs survival, tumorigenicity and metastatic proclivity of MYC-dependent breast cancers. Collectively, these data suggest that oncogenic MYC confers a collateral stress on splicing, and that components of the spliceosome may be therapeutic entry points for aggressive MYC-driven cancers.

Increased Moraxella and Streptococcus species abundance after severe bronchiolitis is associated with recurrent wheezing.

BACKGROUND: The role of the airway microbiome in the development of recurrent wheezing and asthma remains uncertain, particularly in the high-risk group of infants hospitalized for bronchiolitis. OBJECTIVE: We sought to examine the relation of the nasal microbiota at bronchiolitis-related hospitalization and 3 later points to the risk of recurrent wheezing by age 3 years. METHODS: In 17 US centers researchers collected clinical data and nasal swabs from infants hospitalized for bronchiolitis. Trained parents collected nasal swabs 3 weeks after hospitalization and, when healthy, during the summer and 1 year after hospitalization. We applied 16S rRNA gene sequencing to all nasal swabs. We used joint modeling to examine the relation of longitudinal nasal microbiota abundances to the risk of recurrent wheezing. RESULTS: Among 842 infants hospitalized for bronchiolitis, there was 88% follow-up at 3 years, and 31% had recurrent wheezing. The median age at enrollment was 3.2 months (interquartile range, 1.7-5.8 months). In joint modeling analyses adjusting for 16 covariates, including viral cause, a 10% increase in relative abundance of Moraxella or Streptococcus species 3 weeks after day 1 of hospitalization was associated with an increased risk of recurrent wheezing (hazard ratio [HR] of 1.38 and 95% high-density interval [HDI] of 1.11-1.85 and HR of 1.76 and 95% HDI of 1.13-3.19, respectively). Increased Streptococcus species abundance the summer after hospitalization was also associated with a greater risk of recurrent wheezing (HR, 1.76; 95% HDI, 1.15-3.27). CONCLUSIONS: Enrichment of Moraxella or Streptococcus species after bronchiolitis hospitalization was associated with recurrent wheezing by age 3 years, possibly providing new avenues to ameliorate the long-term respiratory outcomes of infants with severe bronchiolitis.

De Novo Disruption of the Proteasome Regulatory Subunit PSMD12 Causes a Syndromic Neurodevelopmental Disorder.

Degradation of proteins by the ubiquitin-proteasome system (UPS) is an essential biological process in the development of eukaryotic organisms. Dysregulation of this mechanism leads to numerous human neurodegenerative or neurodevelopmental disorders. Through a multi-center collaboration, we identified six de novo genomic deletions and four de novo point mutations involving PSMD12, encoding the non-ATPase subunit PSMD12 (aka RPN5) of the 19S regulator of 26S proteasome complex, in unrelated individuals with intellectual disability, congenital malformations, ophthalmologic anomalies, feeding difficulties, deafness, and subtle dysmorphic facial features. We observed reduced PSMD12 levels and an accumulation of ubiquitinated proteins without any impairment of proteasome catalytic activity. Our PSMD12 loss-of-function zebrafish CRISPR/Cas9 model exhibited microcephaly, decreased convolution of the renal tubules, and abnormal craniofacial morphology. Our data support the biological importance of PSMD12 as a scaffolding subunit in proteasome function during development and neurogenesis in particular; they enable the definition of a neurodevelopmental disorder due to PSMD12 variants, expanding the phenotypic spectrum of UPS-dependent disorders.

Resolution of Disease Phenotypes Resulting from Multilocus Genomic Variation.

BACKGROUND: Whole-exome sequencing can provide insight into the relationship between observed clinical phenotypes and underlying genotypes. METHODS: We conducted a retrospective analysis of data from a series of 7374 consecutive unrelated patients who had been referred to a clinical diagnostic laboratory for whole-exome sequencing; our goal was to determine the frequency and clinical characteristics of patients for whom more than one molecular diagnosis was reported. The phenotypic similarity between molecularly diagnosed pairs of diseases was calculated with the use of terms from the Human Phenotype Ontology. RESULTS: A molecular diagnosis was rendered for 2076 of 7374 patients (28.2%); among these patients, 101 (4.9%) had diagnoses that involved two or more disease loci. We also analyzed parental samples, when available, and found that de novo variants accounted for 67.8% (61 of 90) of pathogenic variants in autosomal dominant disease genes and 51.7% (15 of 29) of pathogenic variants in X-linked disease genes; both variants were de novo in 44.7% (17 of 38) of patients with two monoallelic variants. Causal copy-number variants were found in 12 patients (11.9%) with multiple diagnoses. Phenotypic similarity scores were significantly lower among patients in whom the phenotype resulted from two distinct mendelian disorders that affected different organ systems (50 patients) than among patients with disorders that had overlapping phenotypic features (30 patients) (median score, 0.21 vs. 0.36; P=1.77×10-7). CONCLUSIONS: In our study, we found multiple molecular diagnoses in 4.9% of cases in which whole-exome sequencing was informative. Our results show that structured clinical ontologies can be used to determine the degree of overlap between two mendelian diseases in the same patient; the diseases can be distinct or overlapping. Distinct disease phenotypes affect different organ systems, whereas overlapping disease phenotypes are more likely to be caused by two genes encoding proteins that interact within the same pathway. (Funded by the National Institutes of Health and the Ting Tsung and Wei Fong Chao Foundation.).

Low-level parental somatic mosaic SNVs in exomes from a large cohort of trios with diverse suspected Mendelian conditions.

PURPOSE: The goal of this study was to assess the scale of low-level parental mosaicism in exome sequencing (ES) databases. METHODS: We analyzed approximately 2000 family trio ES data sets from the Baylor-Hopkins Center for Mendelian Genomics (BHCMG) and Baylor Genetics (BG). Among apparent de novo single-nucleotide variants identified in the affected probands, we selected rare unique variants with variant allele fraction (VAF) between 30% and 70% in the probands and lower than 10% in one of the parents. RESULTS: Of 102 candidate mosaic variants validated using amplicon-based next-generation sequencing, droplet digital polymerase chain reaction, or blocker displacement amplification, 27 (26.4%) were confirmed to be low- (VAF between 1% and 10%) or very low (VAF <1%) level mosaic. Detection precision in parental samples with two or more alternate reads was 63.6% (BHCMG) and 43.6% (BG). In nine investigated individuals, we observed variability of mosaic ratios among blood, saliva, fibroblast, buccal, hair, and urine samples. CONCLUSION: Our computational pipeline enables robust discrimination between true and false positive candidate mosaic variants and efficient detection of low-level mosaicism in ES samples. We confirm that the presence of two or more alternate reads in the parental sample is a reliable predictor of low-level parental somatic mosaicism.

CNVs cause autosomal recessive genetic diseases with or without involvement of SNV/indels.

PURPOSE: Improved resolution of molecular diagnostic technologies enabled detection of smaller sized exonic level copy-number variants (CNVs). The contribution of CNVs to autosomal recessive (AR) conditions may be better recognized using a large clinical cohort. METHODS: We retrospectively investigated the CNVs' contribution to AR conditions in cases subjected to chromosomal microarray analysis (CMA, N = ~70,000) and/or clinical exome sequencing (ES, N = ~12,000) at Baylor Genetics; most had pediatric onset neurodevelopmental disorders. RESULTS: CNVs contributed to biallelic variations in 87 cases, including 81 singletons and three affected sibling pairs. Seventy cases had CNVs affecting both alleles, and 17 had a CNV and a single-nucleotide variant (SNV)/indel in trans. In total, 94.3% of AR-CNVs affected one gene; among these 41.4% were single-exon and 35.0% were multiexon partial-gene events. Sixty-nine percent of homozygous AR-CNVs were embedded in homozygous genomic intervals. Five cases had large deletions unmasking an SNV/indel on the intact allele for a recessive condition, resulting in multiple molecular diagnoses. CONCLUSIONS: AR-CNVs are often smaller in size, transmitted through generations, and underrecognized due to limitations in clinical CNV detection methods. Our findings from a large clinical cohort emphasized integrated CNV and SNV/indel analyses for precise clinical and molecular diagnosis especially in the context of genomic disorders.