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Background: Human Phenotype Ontology (HPO) has risen as a useful tool for precision medicine by providing a standardized vocabulary of phenotypic abnormalities to describe presentations of human pathologies; however, there have been relatively few reports combining whole genome sequencing (WGS) and HPO, especially in the context of structural variants. Methods: We illustrate an integrative analysis of WGS and HPO using an extended pedigree, which involves Prader-Willi Syndrome (PWS), hereditary hemochromatosis (HH), and dysautonomia-like symptoms. A comprehensive WGS pipeline was used to ensure reliable detection of genomic variants. Beyond variant filtering, we pursued phenotypic prioritization of candidate genes using Phenolyzer. Results: Regarding PWS, WGS confirmed a 5.5 Mb de novo deletion of the parental allele at 15q11.2 to 15q13.1. Phenolyzer successfully returned the diagnosis of PWS, and pinpointed clinically relevant genes in the deletion. Further, Phenolyzer revealed how each of the genes is linked with the phenotypes represented by HPO terms. For HH, WGS identified a known disease variant (p.C282Y) in HFE of an affected female. Analysis of HPO terms alone fails to provide a correct diagnosis, but Phenolyzer successfully revealed the phenotype-genotype relationship using a disease-centric approach. Finally, Phenolyzer also revealed the complexity behind dysautonomia-like symptoms, and seven variants that might be associated with the phenotypes were identified by manual filtering based on a dominant inheritance model. Conclusions: The integration of WGS and HPO can inform comprehensive molecular diagnosis for patients, eliminate false positives and reveal novel insights into undiagnosed diseases. Due to extreme heterogeneity and insufficient knowledge of human diseases, it is also important that phenotypic and genomic data are standardized and shared simultaneously. [ABSTRACT FROM AUTHOR]

Continued advances in variant effect prediction are necessary to demonstrate the ability of machine learning methods to accurately determine the clinical impact of variants of unknown significance (VUS). Towards this goal, the ARSA Critical Assessment of Genome Interpretation (CAGI) challenge was designed to characterize progress by utilizing 219 experimentally assayed missense VUS in the Arylsulfatase A ( ARSA ) gene to assess the performance of community-submitted predictions of variant functional effects. The challenge involved 15 teams, and evaluated additional predictions from established and recently released models. Notably, a model developed by participants of a genetics and coding bootcamp, trained with standard machine-learning tools in Python, demonstrated superior performance among submissions. Furthermore, the study observed that state-of-the-art deep learning methods provided small but statistically significant improvement in predictive performance compared to less elaborate techniques. These findings underscore the utility of variant effect prediction, and the potential for models trained with modest resources to accurately classify VUS in genetic and clinical research., Competing Interests: Declarations Conflict of interest/Competing interests Wyatt T. Clark, Marena Trinidad, Courtney Astore, Teague Sterling, and Sufyan Kazi are former employees and potential shareholders of BioMarin Pharmaceutical. Rocio Acuna-Hidalgo is a current employee and shareholder of Nostos Genomics GmbH. Andrea Grafmüller and Laura T. Jiménez Barrón are former employees of Nostos Genomics GmbH.

We describe an X-linked genetic syndrome associated with mutations in TAF1 and manifesting with global developmental delay, intellectual disability (ID), characteristic facial dysmorphology, generalized hypotonia, and variable neurologic features, all in male individuals. Simultaneous studies using diverse strategies led to the identification of nine families with overlapping clinical presentations and affected by de novo or maternally inherited single-nucleotide changes. Two additional families harboring large duplications involving TAF1 were also found to share phenotypic overlap with the probands harboring single-nucleotide changes, but they also demonstrated a severe neurodegeneration phenotype. Functional analysis with RNA-seq for one of the families suggested that the phenotype is associated with downregulation of a set of genes notably enriched with genes regulated by E-box proteins. In addition, knockdown and mutant studies of this gene in zebrafish have shown a quantifiable, albeit small, effect on a neuronal phenotype. Our results suggest that mutations in TAF1 play a critical role in the development of this X-linked ID syndrome., (Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.)

Autism spectrum disorders (ASDs) are a group of developmental disabilities that affect social interaction and communication and are characterized by repetitive behaviors. There is now a large body of evidence that suggests a complex role of genetics in ASDs, in which many different loci are involved. Although many current population-scale genomic studies have been demonstrably fruitful, these studies generally focus on analyzing a limited part of the genome or use a limited set of bioinformatics tools. These limitations preclude the analysis of genome-wide perturbations that may contribute to the development and severity of ASD-related phenotypes. To overcome these limitations, we have developed and utilized an integrative clinical and bioinformatics pipeline for generating a more complete and reliable set of genomic variants for downstream analyses. Our study focuses on the analysis of three simplex autism families consisting of one affected child, unaffected parents, and one unaffected sibling. All members were clinically evaluated and widely phenotyped. Genotyping arrays and whole-genome sequencing were performed on each member, and the resulting sequencing data were analyzed using a variety of available bioinformatics tools. We searched for rare variants of putative functional impact that were found to be segregating according to de novo, autosomal recessive, X-linked, mitochondrial, and compound heterozygote transmission models. The resulting candidate variants included three small heterozygous copy-number variations (CNVs), a rare heterozygous de novo nonsense mutation in MYBBP1A located within exon 1, and a novel de novo missense variant in LAMB3. Our work demonstrates how more comprehensive analyses that include rich clinical data and whole-genome sequencing data can generate reliable results for use in downstream investigations.