This is a PDF file of a peer-reviewed paper that has been accepted for publication. Although unedited, the content has been subjected to preliminary formatting. Nature is providing this early version of the typeset paper as a service to our authors and readers. The text and figures will undergo copyediting and a proof review before the paper is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers apply.

BackgroundDeep sequencing makes it possible to observe low-frequency viral variants and sub-populations with greater accuracy and sensitivity than ever before. Existing platforms can be used to multiplex a large number of samples; however, analysis of the resulting data is complex and involves separating barcoded samples and various read manipulation processes ending in final assembly. Many assembly tools were designed with larger genomes and higher fidelity polymerases in mind and do not perform well with reads derived from highly variable viral genomes. Reference-based assemblers may leave gaps in viral assemblies while de novo assemblers may struggle to assemble unique genomes.ResultsThe IRMA (iterative refinement meta-assembler) pipeline solves the problem of viral variation by the iterative optimization of read gathering and assembly. As with all reference-based assembly, reads are included in assembly when they match consensus template sets; however, IRMA provides for on-the-fly reference editing, correction, and optional elongation without the need for additional reference selection. This increases both read depth and breadth. IRMA also focuses on quality control, error correction, indel reporting, variant calling and variant phasing. In fact, IRMA’s ability to detect and phase minor variants is one of its most distinguishing features. We have built modules for influenza and ebolavirus. We demonstrate usage and provide calibration data from mixture experiments. Methods for variant calling, phasing, and error estimation/correction have been redesigned to meet the needs of viral genomic sequencing.ConclusionIRMA provides a robust next-generation sequencing assembly solution that is adapted to the needs and characteristics of viral genomes. The software solves issues related to the genetic diversity of viruses while providing customized variant calling, phasing, and quality control. IRMA is freely available for non-commercial use on Linux and Mac OS X and has been parallelized for high-throughput computing.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-3030-6) contains supplementary material, which is available to authorized users.

For the first time, a coding complete genome of an RNA virus has been sequenced in its original form. Previously, RNA was sequenced by the chemical degradation of radiolabeled RNA, a difficult method that produced only short sequences. Instead, RNA has usually been sequenced indirectly by copying it into cDNA, which is often amplified to dsDNA by PCR and subsequently analyzed using a variety of DNA sequencing methods. We designed an adapter to short highly conserved termini of the influenza A virus genome to target the (-) sense RNA into a protein nanopore on the Oxford Nanopore MinION sequencing platform. Utilizing this method with total RNA extracted from the allantoic fluid of influenza rA/Puerto Rico/8/1934 (H1N1) virus infected chicken eggs (EID50 6.8 × 109), we demonstrate successful sequencing of the coding complete influenza A virus genome with 100% nucleotide coverage, 99% consensus identity, and 99% of reads mapped to influenza A virus. By utilizing the same methodology one can redesign the adapter in order to expand the targets to include viral mRNA and (+) sense cRNA, which are essential to the viral life cycle, or other pathogens. This approach also has the potential to identify and quantify splice variants and base modifications, which are not practically measurable with current methods.

This is a PDF file of a peer-reviewed paper that has been accepted for publication. Although unedited, the content has been subjected to preliminary formatting. Nature Medicine is providing this early version of the typeset paper as a service to our authors and readers. The text and figures will undergo copyediting and a proof review before the paper is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers apply.

During the evolution of SARS-CoV-2 in humans a D614G substitution in the spike (S) protein emerged and became the predominant circulating variant (S-614G) of the COVID-19 pandemic. However, whether the increasing prevalence of the S-614G variant represents a fitness advantage that improves replication and/or transmission in humans or is merely due to founder effects remains elusive. Here, we generated isogenic SARS-CoV-2 variants and demonstrate that the S-614G variant has (i) enhanced binding to human ACE2, (ii) increased replication in primary human bronchial and nasal airway epithelial cultures as well as in a novel human ACE2 knock-in mouse model, and (iii) markedly increased replication and transmissibility in hamster and ferret models of SARS-CoV-2 infection. Collectively, our data show that while the S-614G substitution results in subtle increases in binding and replication in vitro, it provides a real competitive advantage in vivo, particularly during the transmission bottle neck, providing an explanation for the global predominance of S-614G variant among the SARS-CoV-2 viruses currently circulating.

We tested and clinically validated a targeted next-generation sequencing (NGS) mutation panel using 80 formalin-fixed, paraffin-embedded (FFPE) tumor samples. Forty non-small cell lung carcinoma (NSCLC), 30 melanoma, and 30 gastrointestinal (12 colonic, 10 gastric, and 8 pancreatic adenocarcinoma) FFPE samples were selected from laboratory archives. After appropriate specimen and nucleic acid quality control, 80 NGS libraries were prepared using the Illumina TruSight tumor (TST) kit and sequenced on the Illumina MiSeq. Sequence alignment, variant calling, and sequencing quality control were performed using vendor software and laboratory-developed analysis workflows. TST generated !500Â coverage for 98.4% of the 13,952 targeted bases. Reproducible and accurate variant calling was achieved at !5% variant allele frequency with 8 to 12 multiplexed samples per MiSeq flow cell. TST detected 112 variants overall, and confirmed all known single-nucleotide variants (n Z 27), deletions (n Z 5), insertions (n Z 3), and multinucleotide variants (n Z 3). TST detected at least one variant in 85.0% (68/80), and two or more variants in 36.2% (29/80), of samples. TP53 was the most frequently mutated gene in NSCLC (13 variants; 13/32 samples), gastrointestinal malignancies (15 variants; 13/25 samples), and overall (30 variants; 28/ 80 samples). BRAF mutations were most common in melanoma (nine variants; 9/23 samples). Clinically relevant NGS data can be obtained from routine clinical FFPE solid tumor specimens using TST, benchtop instruments, and vendor-supplied bioinformatics pipelines. (J Mol Diagn 2016, 18: 299e315; http:// dx

PURPOSE Common polymorphisms in the N-acetyltransferase-2 (NAT2) metabolic enzyme determine slow or rapid acetylator phenotypes. We investigated the effects of alcohol, smoking, and caffeine on fecundability, and determined whether the effects were modified by NAT2. METHODS Three NAT2 polymorphisms were genotyped in 319 women office workers participating in a prospective pregnancy study (1990–1994). Women were ages 20–41 and at risk for pregnancy. Discrete-time survival analysis was used to determine the effects of alcohol, smoking, and caffeine on fecundability and evaluate effect modification by NAT2. RESULTS 319 women (161 slow acetylators, 158 rapid) were followed for an average of 8 menstrual cycles, resulting in 124 pregnancies. There was no effect of caffeine on fecundability. Drinking 1+ alcoholic drink/day and current smoking were significantly associated with reduced fecundability, but only among slow acetylators (adjusted fecundability odds ratio (FOR) for smoking= 0.34: 95% CI, 0.22, 0.90; adjusted FOR for 1+ drink/day = 0.20: 0.05, 0.92). There was no effect among rapid acetylators. CONCLUSIONS NAT2 status significantly modified the effects of alcohol and smoking on fecundability, emphasizing the importance of incorporating genetic and metabolic information in studies of reproductive health. Replication of this study is warranted.

While working overnight at a swine exhibition, we identified an influenza A virus (IAV) outbreak in swine, Nanopore sequenced 13 IAV genomes from samples we collected, and predicted in real time that these viruses posed a novel risk to humans due to genetic mismatches between the viruses and current prepandemic candidate vaccine viruses (CVVs). We developed and used a portable IAV sequencing and analysis platform called Mia (Mobile Influenza Analysis) to complete and characterize full-length consensus genomes approximately 18 h after unpacking the mobile lab. Exhibition swine are a known source for zoonotic transmission of IAV to humans and pose a potential pandemic risk. Genomic analyses of IAV in swine are critical to understanding this risk, the types of viruses circulating in swine, and whether current vaccines developed for use in humans would be predicted to provide immune protection. Nanopore sequencing technology has enabled genome sequencing in the field at the source of viral outbreaks or at the bedside or pen-side of infected humans and animals. The acquired data, however, have not yet demonstrated real-time, actionable public health responses. The Mia system rapidly identified three genetically distinct swine IAV lineages from three subtypes, A(H1N1), A(H3N2), and A(H1N2). Analysis of the hemagglutinin (HA) sequences of the A(H1N2) viruses identified >30 amino acid differences between the HA1 of these viruses and the most closely related CVV. As an exercise in pandemic preparedness, all sequences were emailed to CDC collaborators who initiated the development of a synthetically derived CVV. IMPORTANCE Swine are influenza virus reservoirs that have caused outbreaks and pandemics. Genomic characterization of these viruses enables pandemic risk assessment and vaccine comparisons, though this typically occurs after a novel swine virus jumps into humans. The greatest risk occurs where large groups of swine and humans comingle. At a large swine exhibition, we used Nanopore sequencing and on-site analytics to interpret 13 swine influenza virus genomes and identified an influenza virus cluster that was genetically highly varied to currently available vaccines. As part of the National Strategy for Pandemic Preparedness exercises, the sequences were emailed to colleagues at the CDC who initiated the development of a synthetically derived vaccine designed to match the viruses at the exhibition. Subsequently, this virus caused 14 infections in humans and was the dominant U.S. variant virus in 2018.