Detection of structural variation using target captured next-generation sequencing data for genetic diagnostic testing.

PURPOSE: Structural variation (SV) is associated with inherited diseases. Next-generation sequencing (NGS) is an efficient method for SV detection because of its high-throughput, low cost, and base-pair resolution. However, due to lack of standard NGS protocols and a limited number of clinical samples with pathogenic SVs, comprehensive standards for SV detection, interpretation, and reporting are to be established. METHODS: We performed SV assessment on 60,000 clinical samples tested with hereditary cancer NGS panels spanning 48 genes. To evaluate NGS results, NGS and orthogonal methods were used separately in a blinded fashion for SV detection in all samples. RESULTS: A total of 1,037 SVs in coding sequence (CDS) or untranslated regions (UTRs) and 30,847 SVs in introns were detected and validated. Across all variant types, NGS shows 100% sensitivity and 99.9% specificity. Overall, 64% of CDS/UTR SVs were classified as pathogenic/likely pathogenic, and five deletions/duplications were reclassified as pathogenic using breakpoint information from NGS. CONCLUSION: The SVs presented here can be used as a valuable resource for clinical research and diagnostics. The data illustrate NGS as a powerful tool for SV detection. Application of NGS and confirmation technologies in genetic testing ensures delivering accurate and reliable results for diagnosis and patient care.

Comparative genomics reveals mobile pathogenicity chromosomes in Fusarium.

Fusarium species are among the most important phytopathogenic and toxigenic fungi. To understand the molecular underpinnings of pathogenicity in the genus Fusarium, we compared the genomes of three phenotypically diverse species: Fusarium graminearum, Fusarium verticillioides and Fusarium oxysporum f. sp. lycopersici. Our analysis revealed lineage-specific (LS) genomic regions in F. oxysporum that include four entire chromosomes and account for more than one-quarter of the genome. LS regions are rich in transposons and genes with distinct evolutionary profiles but related to pathogenicity, indicative of horizontal acquisition. Experimentally, we demonstrate the transfer of two LS chromosomes between strains of F. oxysporum, converting a non-pathogenic strain into a pathogen. Transfer of LS chromosomes between otherwise genetically isolated strains explains the polyphyletic origin of host specificity and the emergence of new pathogenic lineages in F. oxysporum. These findings put the evolution of fungal pathogenicity into a new perspective.

Deciphering the uniqueness of Mucoromycotina cell walls by combining biochemical and phylogenomic approaches.

Most fungi from the Mucoromycotina lineage occur in ecosystems as saprobes, although some species are phytopathogens or may induce human mycosis. Mucoromycotina represent early diverging models that are most valuable for understanding fungal evolution. Here we reveal the uniqueness of the cell wall structure of the Mucoromycotina Rhizopus oryzae and Phycomyces blakesleeanus compared with the better characterized cell wall of the ascomycete Neurospora crassa. We have analysed the corresponding polysaccharide biosynthetic and modifying pathways, and highlight their evolutionary features and higher complexity in terms of gene copy numbers compared with species from other lineages. This work uncovers the presence in Mucoromycotina of abundant fucose-based polysaccharides similar to algal fucoidans. These unexpected polymers are associated with unusually low amounts of glucans and a higher proportion of chitin compared with N. crassa. The specific structural features are supported by the identification of genes potentially involved in the corresponding metabolic pathways. Phylogenomic analyses of genes encoding carbohydrate synthases, polysaccharide modifying enzymes and enzymes involved in nucleotide-sugar formation provide evidence for duplication events during evolution of cell wall metabolism in fungi. Altogether, the data highlight the specificity of Mucoromycotina cell walls and pave the way for a finer understanding of their metabolism.

Pancreatic Cancer Action Network's SPARK: A Cloud-Based Patient Health Data and Analytics Platform for Pancreatic Cancer.

PURPOSE: Pancreatic cancer currently holds the position of third deadliest cancer in the United States and the 5-year survival rate is among the lowest for major cancers at just 12%. Thus, continued research efforts to better understand the clinical and molecular underpinnings of pancreatic cancer are critical to developing both early detection methodologies as well as improved therapeutic options. This study introduces Pancreatic Cancer Action Network's (PanCAN's) SPARK, a cloud-based data and analytics platform that integrates patient health data from the PanCAN's research initiatives and aims to accelerate pancreatic cancer research by making real-world patient health data and analysis tools easier to access and use. MATERIALS AND METHODS: The SPARK platform integrates clinical, molecular, multiomic, imaging, and patient-reported data generated from PanCAN's research initiatives. The platform is built on a cloud-based infrastructure powered by Velsera. Cohort exploration and browser capabilities are built using Velsera ARIA, a specialized product for leveraging clinicogenomic data to build cohorts, query variant information, and drive downstream association analyses. Data science and analytic capabilities are also built into the platform allowing researchers to perform simple to complex analysis. RESULTS: Version 1 of the SPARK platform was released to pilot users, who represented diverse end users, including molecular biologists, clinicians, and bioinformaticians. Included in the pilot release of SPARK are deidentified clinical (including treatment and outcomes data), molecular, multiomic, and whole-slide pathology images for over 600 patients enrolled in PanCAN's Know Your Tumor molecular profiling service. CONCLUSION: The pilot release of the SPARK platform introduces qualified researchers to PanCAN real-world patient health data and analytical resources in a centralized location.

Comparative genomic analysis of the 'pseudofungus' Hyphochytrium catenoides.

Eukaryotic microbes have three primary mechanisms for obtaining nutrients and energy: phagotrophy, photosynthesis and osmotrophy. Traits associated with the latter two functions arose independently multiple times in the eukaryotes. The Fungi successfully coupled osmotrophy with filamentous growth, and similar traits are also manifested in the Pseudofungi (oomycetes and hyphochytriomycetes). Both the Fungi and the Pseudofungi encompass a diversity of plant and animal parasites. Genome-sequencing efforts have focused on host-associated microbes (mutualistic symbionts or parasites), providing limited comparisons with free-living relatives. Here we report the first draft genome sequence of a hyphochytriomycete 'pseudofungus'; Hyphochytrium catenoides Using phylogenomic approaches, we identify genes of recent viral ancestry, with related viral derived genes also present on the genomes of oomycetes, suggesting a complex history of viral coevolution and integration across the Pseudofungi. H. catenoides has a complex life cycle involving diverse filamentous structures and a flagellated zoospore with a single anterior tinselate flagellum. We use genome comparisons, drug sensitivity analysis and high-throughput culture arrays to investigate the ancestry of oomycete/pseudofungal characteristics, demonstrating that many of the genetic features associated with parasitic traits evolved specifically within the oomycete radiation. Comparative genomics also identified differences in the repertoire of genes associated with filamentous growth between the Fungi and the Pseudofungi, including differences in vesicle trafficking systems, cell-wall synthesis pathways and motor protein repertoire, demonstrating that unique cellular systems underpinned the convergent evolution of filamentous osmotrophic growth in these two eukaryotic groups.

Shared signatures of parasitism and phylogenomics unite Cryptomycota and microsporidia.

Fungi grow within their food, externally digesting it and absorbing nutrients across a semirigid chitinous cell wall. Members of the new phylum Cryptomycota were proposed to represent intermediate fungal forms, lacking a chitinous cell wall during feeding and known almost exclusively from ubiquitous environmental ribosomal RNA sequences that cluster at the base of the fungal tree [1, 2]. Here, we sequence the first Cryptomycotan genome (the water mold endoparasite Rozella allomycis) and unite the Cryptomycota with another group of endoparasites, the microsporidia, based on phylogenomics and shared genomic traits. We propose that Cryptomycota and microsporidia share a common endoparasitic ancestor, with the clade unified by a chitinous cell wall used to develop turgor pressure in the infection process [3, 4]. Shared genomic elements include a nucleotide transporter that is used by microsporidia for stealing energy in the form of ATP from their hosts [5]. Rozella harbors a mitochondrion that contains a very rapidly evolving genome and lacks complex I of the respiratory chain. These degenerate features are offset by the presence of nuclear genes for alternative respiratory pathways. The Rozella proteome has not undergone major contraction like microsporidia; instead, several classes have undergone expansion, such as host-effector, signal-transduction, and folding proteins.