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Modern sequencing technology enables the detection of complex structural variation (SV) across genomes. However, extensive DNA rearrangements arising through series of mutations, a phenomenon we term serial SV (sSV), remain understudied since their complexity poses a challenge for SV discovery. Here, we present NAHRwhals (https://github.com/WHops/NAHRwhals), a method to infer repeat-mediated series of SVs in long-read genomic assemblies. Applying NAHRwhals to 58 haplotype-resolved human genomes reveals 37 sSV loci of various length and complexity. These sSVs explain otherwise cryptic variation in medically relevant regions such as theTPSAB1gene, 8p23.1 and the DiGeorge and Sotos syndrome regions. Comparisons with great ape assemblies indicate that most human sSVs formed recently and involved non-repeat-mediated processes. NAHRwhals reliably discovers and characterizes sSVs at scale and independent of species, uncovering their genomic abundance and revealing broader implications for disease than prior studies suggested.

PURPOSE: Mendelian disease genomic research has undergone a massive transformation over the past decade. With increasing availability of exome and genome sequencing, the role of Mendelian research has expanded beyond data collection, sequencing, and analysis to worldwide data sharing and collaboration. METHODS: Over the past 10 years, the National Institutes of Health–supported Centers for Mendelian Genomics (CMGs) have played a major role in this research and clinical evolution. RESULTS: We highlight the cumulative gene discoveries facilitated by the program, biomedical research leveraged by the approach, and the larger impact on the research community. Beyond generating a list of gene-phenotype relationships and participating in widespread data sharing, the CMGs have created resources, tools, and training for the larger community to foster understanding of genes and genome variation. The CMGs have participated in a wide range of data sharing activities, including deposition of all eligible CMG data into the Analysis, Visualization, and Informatics Lab-space (AnVIL), sharing candidate genes through the Matchmaker Exchange and the CMG website, and sharing variants in Genotypes to Mendelian Phenotypes (Geno2MP) and VariantMatcher. CONCLUSION: The work is far from complete; strengthening communication between research and clinical realms, continued development and sharing of knowledge and tools, and improving access to richly characterized data sets are all required to diagnose the remaining molecularly undiagnosed patients.

Ever larger Structural Variant (SV) catalogs highlighting the diversity within and between populations help researchers better understand the links between SVs and disease. The identification of SVs from DNA sequence data is non-trivial and requires a balance between comprehensiveness and precision. Here we present a catalog of 355,667 SVs (59.34% novel) across autosomes and the X chromosome (50bp+) from 138,134 individuals in the diverse TOPMed consortium. We describe our methodologies for SV inference resulting in high variant quality and >90% allele concordance compared to long-read de-novo assemblies of well-characterized control samples. We demonstrate utility through significant associations between SVs and important various cardio-metabolic and hematologic traits. We have identified 690 SV hotspots and deserts and those that potentially impact the regulation of medically relevant genes. This catalog characterizes SVs across multiple populations and will serve as a valuable tool to understand the impact of SV on disease development and progression.

The COVID-19 pandemic has sparked an urgent need to uncover the underlying biology of this devastating disease. Though RNA viruses mutate more rapidly than DNA viruses, there are a relatively small number of single nucleotide polymorphisms (SNPs) that differentiate the main SARS-CoV-2 lineages that have spread throughout the world. In this study, we investigated 129 RNA-seq data sets and 6928 consensus genomes to contrast the intra-host and inter-host diversity of SARS-CoV-2. Our analyses yielded three major observations. First, the mutational profile of SARS-CoV-2 highlights intra-host single nucleotide variant (iSNV) and SNP similarity, albeit with differences in CU changes. Second, iSNV and SNP patterns in SARS-CoV-2 are more similar to MERS-CoV than SARS-CoV-1. Third, a significant fraction of insertions and deletions contribute to the genetic diversity of SARS-CoV-2. Altogether, our findings provide insight into SARS-CoV-2 genomic diversity, inform the design of detection tests, and highlight the potential of iSNVs for tracking the transmission of SARS-CoV-2.

Advancements in DNA sequencing technologies are occurring at a rapid rate. Various platforms have proven useful in all aspects of health and science research, from molecular diagnostics in cancer research to spore identification in bioterrorism. In the field of forensics, one particular single-molecule sequencing platform shows promise for becoming a viable solution for small to midsize forensic laboratories. Oxford Nanopore Technologies (ONT) has developed a portable, nanopore-based sequencing instrument that has already been utilized for on-site identification of Zika and Ebola viruses, full genome sequencing, evaluation of DNA and RNA base modifications, and enrichment-free mitochondrial DNA analysis. The rapid development of this technology creates possibilities relevant to standard DNA sequencing, direct analysis of forensic samples, including blood, semen, and buccal swabs, mitochondrial DNA analysis, SNP and STR analysis, familial identification, and microbial identification for bioterrorism and geolocation. The small size of the platform, its low cost, and its requirement of only basic laboratory equipment makes this platform well suited for small laboratories wishing to begin developing expertise in sequence-based forensic analyses. Herein, we outline recent developments and applications of nanopore sequencing technologies and their potential application in forensic analysis. We address current and potential techniques in mitochondrial DNA analysis, SNP and STR typing, and microbial identification. Additionally, we discuss recent developments in library preparation and data analysis tool further streamlining the sequencing process that integrate workflows in laboratories or in remote field scenarios.