Comprehensive Gene Panel Testing for Hearing Loss in Children: Understanding Factors Influencing Diagnostic Yield.

OBJECTIVE: To evaluate factors influencing the diagnostic yield of comprehensive gene panel testing (CGPT) for hearing loss (HL) in children and to understand the characteristics of undiagnosed probands. STUDY DESIGN: This was a retrospective cohort study of 474 probands with childhood-onset HL who underwent CGPT between 2016 and 2020 at a single center. Main outcomes and measures included the association between clinical variables and diagnostic yield and the genetic and clinical characteristics of undiagnosed probands. RESULTS: The overall diagnostic yield was 44% (209/474) with causative variants involving 41 genes. While the diagnostic yield was high in the probands with congenital, bilateral, and severe HL, it was low in those with unilateral, noncongenital, or mild HL; cochlear nerve deficiency; preterm birth; neonatal intensive care unit admittance; certain ancestry; and developmental delay. Follow-up studies on 49 probands with initially inconclusive CGPT results changed the diagnostic status to likely positive or negative outcomes in 39 of them (80%). Reflex to exome sequencing on 128 undiagnosed probands by CGPT revealed diagnostic findings in 8 individuals, 5 of whom had developmental delays. The remaining 255 probands were undiagnosed, with 173 (173/255) having only a single variant in the gene(s) associated with autosomal recessive HL and 28% (48/173) having a matched phenotype. CONCLUSION: CGPT efficiently identifies the genetic etiologies of HL in children. CGPT-undiagnosed probands may benefit from follow-up studies or expanded testing.

Genomic analyses in Cornelia de Lange Syndrome and related diagnoses: Novel candidate genes, genotype-phenotype correlations and common mechanisms.

Cornelia de Lange Syndrome (CdLS) is a rare, dominantly inherited multisystem developmental disorder characterized by highly variable manifestations of growth and developmental delays, upper limb involvement, hypertrichosis, cardiac, gastrointestinal, craniofacial, and other systemic features. Pathogenic variants in genes encoding cohesin complex structural subunits and regulatory proteins (NIPBL, SMC1A, SMC3, HDAC8, and RAD21) are the major pathogenic contributors to CdLS. Heterozygous or hemizygous variants in the genes encoding these five proteins have been found to be contributory to CdLS, with variants in NIPBL accounting for the majority (>60%) of cases, and the only gene identified to date that results in the severe or classic form of CdLS when mutated. Pathogenic variants in cohesin genes other than NIPBL tend to result in a less severe phenotype. Causative variants in additional genes, such as ANKRD11, EP300, AFF4, TAF1, and BRD4, can cause a CdLS-like phenotype. The common role that these genes, and others, play as critical regulators of developmental transcriptional control has led to the conditions they cause being referred to as disorders of transcriptional regulation (or "DTRs"). Here, we report the results of a comprehensive molecular analysis in a cohort of 716 probands with typical and atypical CdLS in order to delineate the genetic contribution of causative variants in cohesin complex genes as well as novel candidate genes, genotype-phenotype correlations, and the utility of genome sequencing in understanding the mutational landscape in this population.

Genome-first approach to rare EYA4 variants and cardio-auditory phenotypes in adults.

While newborns and children with hearing loss are routinely offered genetic testing, adults are rarely clinically tested for a genetic etiology. One clinically actionable result from genetic testing in children is the discovery of variants in syndromic hearing loss genes. EYA4 is a known hearing loss gene which is also involved in important pathways in cardiac tissue. The pleiotropic effects of rare EYA4 variants are poorly understood and their prevalence in a large cohort has not been previously reported. We investigated cardio-auditory phenotypes in 11,451 individuals in a large biobank using a rare variant, genome-first approach to EYA4. We filtered 256 EYA4 variants carried by 6737 participants to 26 rare and predicted deleterious variants carried by 42 heterozygotes. We aggregated predicted deleterious EYA4 gene variants into a combined variable (i.e. "gene burden") and performed association studies across phenotypes compared to wildtype controls. We validated findings with replication in three independent cohorts and human tissue expression data. EYA4 gene burden was significantly associated with audiometric-proven HL (p = [Formula: see text], Mobitz Type II AV block (p = [Formula: see text]) and the syndromic presentation of HL and primary cardiomyopathy (p = 0.0194). Analyses on audiogram, echocardiogram, and electrocardiogram data validated these associations. Prior reports have focused on identifying variants in families with severe or syndromic phenotypes. In contrast, we found, using a genotype-first approach, that gene burden in EYA4 is associated with more subtle cardio-auditory phenotypes in an adult medical biobank population, including cardiac conduction disorders which have not been previously reported. We show the value of using a focused approach to uncover human disease related to pleiotropic gene variants and suggest a role for genetic testing in adults presenting with hearing loss.

Correction: The Genomics Research and Innovation Network: creating an interoperable, federated, genomics learning system.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

The Genomics Research and Innovation Network: creating an interoperable, federated, genomics learning system.

PURPOSE: Clinicians and researchers must contextualize a patient's genetic variants against population-based references with detailed phenotyping. We sought to establish globally scalable technology, policy, and procedures for sharing biosamples and associated genomic and phenotypic data on broadly consented cohorts, across sites of care. METHODS: Three of the nation's leading children's hospitals launched the Genomic Research and Innovation Network (GRIN), with federated information technology infrastructure, harmonized biobanking protocols, and material transfer agreements. Pilot studies in epilepsy and short stature were completed to design and test the collaboration model. RESULTS: Harmonized, broadly consented institutional review board (IRB) protocols were approved and used for biobank enrollment, creating ever-expanding, compatible biobanks. An open source federated query infrastructure was established over genotype-phenotype databases at the three hospitals. Investigators securely access the GRIN platform for prep to research queries, receiving aggregate counts of patients with particular phenotypes or genotypes in each biobank. With proper approvals, de-identified data is exported to a shared analytic workspace. Investigators at all sites enthusiastically collaborated on the pilot studies, resulting in multiple publications. Investigators have also begun to successfully utilize the infrastructure for grant applications. CONCLUSIONS: The GRIN collaboration establishes the technology, policy, and procedures for a scalable genomic research network.

Utility and limitations of exome sequencing as a genetic diagnostic tool for children with hearing loss.

PURPOSE: Hearing loss (HL) is the most common sensory disorder in children. Prompt molecular diagnosis may guide screening and management, especially in syndromic cases when HL is the single presenting feature. Exome sequencing (ES) is an appealing diagnostic tool for HL as the genetic causes are highly heterogeneous. METHODS: ES was performed on a prospective cohort of 43 probands with HL. Sequence data were analyzed for primary and secondary findings. Capture and coverage analysis was performed for genes and variants associated with HL. RESULTS: The diagnostic rate using ES was 37.2%, compared with 15.8% for the clinical HL panel. Secondary findings were discovered in three patients. For 247 genes associated with HL, 94.7% of the exons were targeted for capture and 81.7% of these exons were covered at 20× or greater. Further analysis of 454 randomly selected HL-associated variants showed that 89% were targeted for capture and 75% were covered at a read depth of at least 20×. CONCLUSION: ES has an improved yield compared with clinical testing and may capture diagnoses not initially considered due to subtle clinical phenotypes. Technical challenges were identified, including inadequate capture and coverage of HL genes. Additional considerations of ES include secondary findings, cost, and turnaround time.

Utility and limitations of exome sequencing in the molecular diagnosis of pediatric inherited platelet disorders.

Inherited platelet disorders (IPD) are a heterogeneous group of rare disorders that affect platelet number and function and often predispose to other significant medical complications. In spite of the identification of over 50 IPD disease-associated genes, a molecular diagnosis is only identified in a minority (10%) of affected patients without a clinically suspected etiology. We studied a cohort of 21 pediatric patients with suspected IPDs by exome sequencing (ES) to: (1) examine the performance of the exome test for IPD genes, (2) determine if this exome-wide diagnostic test provided a higher diagnostic yield than has been previously reported, (3) to evaluate the frequency of variants of uncertain significance identified, and (4) to identify candidate variants for functional evaluation in patients with an uncertain or negative diagnosis. We established a high priority gene list of 53 genes, evaluated exome capture kit performance, and determined the coverage for these genes and disease-related variants. We identified likely disease causing variants in 5 of the 21 probands (23.8%) and variants of uncertain significance in 52% of patients studied. In conclusion, ES has the potential to molecularly diagnose causes of IPD, and to identify candidate genes for functional evaluation. Robust exome sequencing also requires that coverage of genes known to be associated with clinical findings of interest need to be carefully examined and supplemented if necessary. Clinicians who undertake ES should understand the limitations of the test and the full significance of results that may be returned.

Lack of association of KATNAL1 gene sequence variants and azoospermia in humans.

PURPOSE: A recent experiment indicated that a loss of function mutation in the murine Katnal1 gene resulted in male factor infertility due to premature exfoliation of spermatids. This study investigated the relevance of this gene to infertility in humans. METHODS: Multiple methods of genetic analysis were employed to investigate whether mutations in human KATNAL1 have a causative role in male infertility. This was a genetic association study, which included DNA samples from 105 men with non-obstructive azoospermia (NOA) and 242 anonymous sperm donor controls. 28 commercially available TaqMan SNP assays were used to haplotype samples from both groups and genetically tag regions of interest across the entire gene. AmpliSeq primers were then designed for identified regions so that targeted next-generation sequencing (NGS) could be used to identify causative variants. RESULTS: Four SNPs in the 3'UTR demonstrated a putative association with NOA. The AmpliSeq primers designed for the 3'UTR provided 83 % coverage of the 7,202 basepairs within the regions of interest. Variant sites were analyzed against genetic models to identify sequence polymorphisms which associated with NOA. No variants met standard criteria for significance when tested between the groups. CONCLUSIONS: This study suggests a lack of association of KATNAL1 gene sequence variants and azoospermia in humans.

EMDataBank.org: unified data resource for CryoEM.

Cryo-electron microscopy reconstruction methods are uniquely able to reveal structures of many important macromolecules and macromolecular complexes. EMDataBank.org, a joint effort of the Protein Data Bank in Europe (PDBe), the Research Collaboratory for Structural Bioinformatics (RCSB) and the National Center for Macromolecular Imaging (NCMI), is a global 'one-stop shop' resource for deposition and retrieval of cryoEM maps, models and associated metadata. The resource unifies public access to the two major archives containing EM-based structural data: EM Data Bank (EMDB) and Protein Data Bank (PDB), and facilitates use of EM structural data of macromolecules and macromolecular complexes by the wider scientific community.

Motion of transfer RNA from the A/T state into the A-site using docking and simulations.

The ribosome catalyzes peptidyl transfer reactions at the growing nascent polypeptide chain. Here, we present a structural mechanism for selecting cognate over near-cognate A/T transfer RNA (tRNA). In part, the structural basis for the fidelity of translation relies on accommodation to filter cognate from near-cognate tRNAs. To examine the assembly of tRNAs within the ribonucleic-riboprotein complex, we conducted a series of all-atom molecular dynamics (MD) simulations of the entire solvated 70S Escherichia coli ribosome, along with its associated cofactors, proteins, and messenger RNA (mRNA). We measured the motion of the A/T state of tRNA between initial binding and full accommodation. The mechanism of rejection was investigated. Using novel in-house algorithms, we determined trajectory pathways. Despite the large intersubunit cavity, the available space is limited by the presence of the tRNA, which is equally large. This article describes a "structural gate," formed between helices 71 and 92 on the ribosomal large subunit, which restricts tRNA motion. The gate and the interacting protein, L14, of the 50S ribosome act as steric filters in two consecutive substeps during accommodation, each requiring: (1) sufficient energy contained in the hybrid tRNA kink and (2) sufficient energy in the Watson-Crick base pairing of the codon-anticodon. We show that these barriers act to filter out near-cognate tRNA and promote proofreading of the codon-anticodon. Since proofreading is essential for understanding the fidelity of translation, our model for the dynamics of this process has substantial biomedical implications.

Hospitalizations Associated With Mental Health Conditions Among Adolescents in the US and France During the COVID-19 Pandemic.

Importance: The COVID-19 pandemic has been associated with an increase in mental health diagnoses among adolescents, though the extent of the increase, particularly for severe cases requiring hospitalization, has not been well characterized. Large-scale federated informatics approaches provide the ability to efficiently and securely query health care data sets to assess and monitor hospitalization patterns for mental health conditions among adolescents. Objective: To estimate changes in the proportion of hospitalizations associated with mental health conditions among adolescents following onset of the COVID-19 pandemic. Design, Setting, and Participants: This retrospective, multisite cohort study of adolescents 11 to 17 years of age who were hospitalized with at least 1 mental health condition diagnosis between February 1, 2019, and April 30, 2021, used patient-level data from electronic health records of 8 children's hospitals in the US and France. Main Outcomes and Measures: Change in the monthly proportion of mental health condition-associated hospitalizations between the prepandemic (February 1, 2019, to March 31, 2020) and pandemic (April 1, 2020, to April 30, 2021) periods using interrupted time series analysis. Results: There were 9696 adolescents hospitalized with a mental health condition during the prepandemic period (5966 [61.5%] female) and 11 101 during the pandemic period (7603 [68.5%] female). The mean (SD) age in the prepandemic cohort was 14.6 (1.9) years and in the pandemic cohort, 14.7 (1.8) years. The most prevalent diagnoses during the pandemic were anxiety (6066 [57.4%]), depression (5065 [48.0%]), and suicidality or self-injury (4673 [44.2%]). There was an increase in the proportions of monthly hospitalizations during the pandemic for anxiety (0.55%; 95% CI, 0.26%-0.84%), depression (0.50%; 95% CI, 0.19%-0.79%), and suicidality or self-injury (0.38%; 95% CI, 0.08%-0.68%). There was an estimated 0.60% increase (95% CI, 0.31%-0.89%) overall in the monthly proportion of mental health-associated hospitalizations following onset of the pandemic compared with the prepandemic period. Conclusions and Relevance: In this cohort study, onset of the COVID-19 pandemic was associated with increased hospitalizations with mental health diagnoses among adolescents. These findings support the need for greater resources within children's hospitals to care for adolescents with mental health conditions during the pandemic and beyond.

International Analysis of Electronic Health Records of Children and Youth Hospitalized With COVID-19 Infection in 6 Countries.

Importance: Additional sources of pediatric epidemiological and clinical data are needed to efficiently study COVID-19 in children and youth and inform infection prevention and clinical treatment of pediatric patients. Objective: To describe international hospitalization trends and key epidemiological and clinical features of children and youth with COVID-19. Design, Setting, and Participants: This retrospective cohort study included pediatric patients hospitalized between February 2 and October 10, 2020. Patient-level electronic health record (EHR) data were collected across 27 hospitals in France, Germany, Spain, Singapore, the UK, and the US. Patients younger than 21 years who tested positive for COVID-19 and were hospitalized at an institution participating in the Consortium for Clinical Characterization of COVID-19 by EHR were included in the study. Main Outcomes and Measures: Patient characteristics, clinical features, and medication use. Results: There were 347 males (52%; 95% CI, 48.5-55.3) and 324 females (48%; 95% CI, 44.4-51.3) in this study's cohort. There was a bimodal age distribution, with the greatest proportion of patients in the 0- to 2-year (199 patients [30%]) and 12- to 17-year (170 patients [25%]) age range. Trends in hospitalizations for 671 children and youth found discrete surges with variable timing across 6 countries. Data from this cohort mirrored national-level pediatric hospitalization trends for most countries with available data, with peaks in hospitalizations during the initial spring surge occurring within 23 days in the national-level and 4CE data. A total of 27 364 laboratory values for 16 laboratory tests were analyzed, with mean values indicating elevations in markers of inflammation (C-reactive protein, 83 mg/L; 95% CI, 53-112 mg/L; ferritin, 417 ng/mL; 95% CI, 228-607 ng/mL; and procalcitonin, 1.45 ng/mL; 95% CI, 0.13-2.77 ng/mL). Abnormalities in coagulation were also evident (D-dimer, 0.78 ug/mL; 95% CI, 0.35-1.21 ug/mL; and fibrinogen, 477 mg/dL; 95% CI, 385-569 mg/dL). Cardiac troponin, when checked (n = 59), was elevated (0.032 ng/mL; 95% CI, 0.000-0.080 ng/mL). Common complications included cardiac arrhythmias (15.0%; 95% CI, 8.1%-21.7%), viral pneumonia (13.3%; 95% CI, 6.5%-20.1%), and respiratory failure (10.5%; 95% CI, 5.8%-15.3%). Few children were treated with COVID-19-directed medications. Conclusions and Relevance: This study of EHRs of children and youth hospitalized for COVID-19 in 6 countries demonstrated variability in hospitalization trends across countries and identified common complications and laboratory abnormalities in children and youth with COVID-19 infection. Large-scale informatics-based approaches to integrate and analyze data across health care systems complement methods of disease surveillance and advance understanding of epidemiological and clinical features associated with COVID-19 in children and youth.

Effect of Whole-Genome Sequencing on the Clinical Management of Acutely Ill Infants With Suspected Genetic Disease: A Randomized Clinical Trial.

Importance: Whole-genome sequencing (WGS) shows promise as a first-line genetic test for acutely ill infants, but widespread adoption and implementation requires evidence of an effect on clinical management. Objective: To determine the effect of WGS on clinical management in a racially and ethnically diverse and geographically distributed population of acutely ill infants in the US. Design, Setting, and Participants: This randomized, time-delayed clinical trial enrolled participants from September 11, 2017, to April 30, 2019, with an observation period extending to July 2, 2019. The study was conducted at 5 US academic medical centers and affiliated children's hospitals. Participants included infants aged between 0 and 120 days who were admitted to an intensive care unit with a suspected genetic disease. Data were analyzed from January 14 to August 20, 2020. Interventions: Patients were randomized to receive clinical WGS results 15 days (early) or 60 days (delayed) after enrollment, with the observation period extending to 90 days. Usual care was continued throughout the study. Main Outcomes and Measures: The main outcome was the difference in the proportion of infants in the early and delayed groups who received a change of management (COM) 60 days after enrollment. Additional outcome measures included WGS diagnostic efficacy, within-group COM at 90 days, length of hospital stay, and mortality. Results: A total of 354 infants were randomized to the early (n = 176) or delayed (n = 178) arms. The mean participant age was 15 days (IQR, 7-32 days); 201 participants (56.8%) were boys; 19 (5.4%) were Asian; 47 (13.3%) were Black; 250 (70.6%) were White; and 38 (10.7%) were of other race. At 60 days, twice as many infants in the early group vs the delayed group received a COM (34 of 161 [21.1%; 95% CI, 15.1%-28.2%] vs 17 of 165 [10.3%; 95% CI, 6.1%-16.0%]; P = .009; odds ratio, 2.3; 95% CI, 1.22-4.32) and a molecular diagnosis (55 of 176 [31.0%; 95% CI, 24.5%-38.7%] vs 27 of 178 [15.0%; 95% CI, 10.2%-21.3%]; P < .001). At 90 days, the delayed group showed a doubling of COM (to 45 of 161 [28.0%; 95% CI, 21.2%-35.6%]) and diagnostic efficacy (to 56 of 178 [31.0%; 95% CI, 24.7%-38.8%]). The most frequent COMs across the observation window were subspecialty referrals (39 of 354; 11%), surgery or other invasive procedures (17 of 354; 4%), condition-specific medications (9 of 354; 2%), or other supportive alterations in medication (12 of 354; 3%). No differences in length of stay or survival were observed. Conclusions and Relevance: In this randomized clinical trial, for acutely ill infants in an intensive care unit, introduction of WGS was associated with a significant increase in focused clinical management compared with usual care. Access to first-line WGS may reduce health care disparities by enabling diagnostic equity. These data support WGS adoption and implementation in this population. Trail Registration: ClinicalTrials.gov Identifier: NCT03290469.

International Comparisons of Harmonized Laboratory Value Trajectories to Predict Severe COVID-19: Leveraging the 4CE Collaborative Across 342 Hospitals and 6 Countries: A Retrospective Cohort Study.

Objectives: To perform an international comparison of the trajectory of laboratory values among hospitalized patients with COVID-19 who develop severe disease and identify optimal timing of laboratory value collection to predict severity across hospitals and regions. Design: Retrospective cohort study. Setting: The Consortium for Clinical Characterization of COVID-19 by EHR (4CE), an international multi-site data-sharing collaborative of 342 hospitals in the US and in Europe. Participants: Patients hospitalized with COVID-19, admitted before or after PCR-confirmed result for SARS-CoV-2. Primary and secondary outcome measures: Patients were categorized as "ever-severe" or "never-severe" using the validated 4CE severity criteria. Eighteen laboratory tests associated with poor COVID-19-related outcomes were evaluated for predictive accuracy by area under the curve (AUC), compared between the severity categories. Subgroup analysis was performed to validate a subset of laboratory values as predictive of severity against a published algorithm. A subset of laboratory values (CRP, albumin, LDH, neutrophil count, D-dimer, and procalcitonin) was compared between North American and European sites for severity prediction. Results: Of 36,447 patients with COVID-19, 19,953 (43.7%) were categorized as ever-severe. Most patients (78.7%) were 50 years of age or older and male (60.5%). Longitudinal trajectories of CRP, albumin, LDH, neutrophil count, D-dimer, and procalcitonin showed association with disease severity. Significant differences of laboratory values at admission were found between the two groups. With the exception of D-dimer, predictive discrimination of laboratory values did not improve after admission. Sub-group analysis using age, D-dimer, CRP, and lymphocyte count as predictive of severity at admission showed similar discrimination to a published algorithm (AUC=0.88 and 0.91, respectively). Both models deteriorated in predictive accuracy as the disease progressed. On average, no difference in severity prediction was found between North American and European sites. Conclusions: Laboratory test values at admission can be used to predict severity in patients with COVID-19. Prediction models show consistency across international sites highlighting the potential generalizability of these models.

A Centralized Approach for Practicing Genomic Medicine.

Next-generation sequencing has revolutionized the diagnostic process, making broadscale testing affordable and applicable to almost all specialties; however, there remain several challenges in its widespread implementation. Barriers such as lack of infrastructure or expertise within local health systems and complex result interpretation or counseling make it harder for frontline clinicians to incorporate genomic testing in their existing workflow. The general population is more informed and interested in pursuing genetic testing, and this has been coupled with the increasing accessibility of direct-to-consumer testing. As a result of these changes, primary care physicians and nongenetics specialty providers find themselves seeing patients for whom genetic testing would be beneficial but managing genetic test results that are out of their scope of practice. In this report, we present a practical and centralized approach to providing genomic services through an independent, enterprise-wide clinical service model. We present 4 years of clinical experience, with >3400 referrals, toward designing and implementing the clinical service, maximizing resources, identifying barriers, and improving patient care. We provide a framework that can be implemented at other institutions to support and integrate genomic services across the enterprise.

International electronic health record-derived COVID-19 clinical course profiles: the 4CE consortium.

We leveraged the largely untapped resource of electronic health record data to address critical clinical and epidemiological questions about Coronavirus Disease 2019 (COVID-19). To do this, we formed an international consortium (4CE) of 96 hospitals across five countries (www.covidclinical.net). Contributors utilized the Informatics for Integrating Biology and the Bedside (i2b2) or Observational Medical Outcomes Partnership (OMOP) platforms to map to a common data model. The group focused on temporal changes in key laboratory test values. Harmonized data were analyzed locally and converted to a shared aggregate form for rapid analysis and visualization of regional differences and global commonalities. Data covered 27,584 COVID-19 cases with 187,802 laboratory tests. Case counts and laboratory trajectories were concordant with existing literature. Laboratory tests at the time of diagnosis showed hospital-level differences equivalent to country-level variation across the consortium partners. Despite the limitations of decentralized data generation, we established a framework to capture the trajectory of COVID-19 disease in patients and their response to interventions.

Viral assembly: a molecular modeling perspective.

Icosahedral viruses are among the smallest and simplest of biological systems. The investigation of their structures represented the first step toward the establishment of molecular biophysics, over half a century ago. Many research groups are now pursuing investigations of viral assembly, a process that could offer new opportunities for the design of antiviral drugs and novel nanoparticles. A variety of experimental, theoretical and computational methods have been brought to bear on the study of virus structure and assembly. In this Perspective we review the contributions of theoretical and computational approaches to our understanding of the structure, energetics, thermodynamics and assembly of DNA bacteriophage and single-stranded icosahedral RNA viruses.

Rapid and accurate interpretation of clinical exomes using Phenoxome: a computational phenotype-driven approach.

Clinical exome sequencing (CES) has become the preferred diagnostic platform for complex pediatric disorders with suspected monogenic etiologies. Despite rapid advancements, the major challenge still resides in identifying the casual variants among the thousands of variants detected during CES testing, and thus establishing a molecular diagnosis. To improve the clinical exome diagnostic efficiency, we developed Phenoxome, a robust phenotype-driven model that adopts a network-based approach to facilitate automated variant prioritization. Phenoxome dissects the phenotypic manifestation of a patient in concert with their genomic profile to filter and then prioritize variants that are likely to affect the function of the gene (potentially pathogenic variants). To validate our method, we have compiled a clinical cohort of 105 positive patient samples that represent a wide range of genetic heterogeneity. Phenoxome identifies the causative variants within the top 5, 10, or 25 candidates in more than 50%, 71%, or 88% of these exomes, respectively. Furthermore, we show that our method is optimized for clinical testing by outperforming the current state-of-art method. We have demonstrated the performance of Phenoxome using a clinical cohort and showed that it enables rapid and accurate interpretation of clinical exomes. Phenoxome is available at https://phenoxome.chop.edu/ .

YUP.SCX: coaxing atomic models into medium resolution electron density maps.

The structures of large macromolecular complexes in different functional states can be determined by cryo-electron microscopy, which yields electron density maps of low to intermediate resolutions. The maps can be combined with high-resolution atomic structures of components of the complex, to produce a model for the complex that is more accurate than the formal resolution of the map. To this end, methods have been developed to dock atomic models into density maps rigidly or flexibly, and to refine a docked model so as to optimize the fit of the atomic model into the map. We have developed a new refinement method called YUP.SCX. The electron density map is converted into a component of the potential energy function to which terms for stereochemical restraints and volume exclusion are added. The potential energy function is then minimized (using simulated annealing) to yield a stereochemically-restrained atomic structure that fits into the electron density map optimally. We used this procedure to construct an atomic model of the 70S ribosome in the pre-accommodation state. Although some atoms are displaced by as much as 33A, they divide themselves into nearly rigid fragments along natural boundaries with smooth transitions between the fragments.