A combination of favipiravir and zanamivir successfully cleared influenza B infection in a child who had undergone bone marrow transplant for X-linked severe combined immunodeficiency, with no recovery of T lymphocytes. Deep sequencing of viral samples illuminated the within-host dynamics of infection, demonstrating the effectiveness of favipiravir in this case.

Strains of the influenza virus form coherent global populations, yet exist at the level of single infections in individual hosts. The relationship between these scales is a critical topic for understanding viral evolution. Here we investigate the within-host relationship between selection and the stochastic effects of genetic drift, estimating an effective population size of infection Ne for influenza infection. Examining whole-genome sequence data describing a chronic case of influenza B in a severely immunocompromised child we infer an Ne of 2.5 x 107 (95% confidence range 1.0 x 107 to 9.0 x 107) suggesting that genetic drift is of minimal importance during an established influenza infection. Our result, supported by data from influenza A infection, suggests that positive selection during within-host infection is primarily limited by the typically short period of infection. Atypically long infections may have a disproportionate influence upon global patterns of viral evolution.

DNA comprises molecular information stored in genetic and epigenetic bases, both of which are vital to our understanding of biology. Most DNA sequencing approaches address either genetics or epigenetics and thus capture incomplete information. Methods widely used to detect epigenetic DNA bases fail to capture common C-to-T mutations or distinguish 5-methylcytosine from 5-hydroxymethylcytosine. We present a single base-resolution sequencing methodology that sequences complete genetics and the two most common cytosine modifications in a single workflow. DNA is copied and bases are enzymatically converted. Coupled decoding of bases across the original and copy strand provides a phased digital readout. Methods are demonstrated on human genomic DNA and cell-free DNA from a blood sample of a patient with cancer. The approach is accurate, requires low DNA input and has a simple workflow and analysis pipeline. Simultaneous, phased reading of genetic and epigenetic bases provides a more complete picture of the information stored in genomes and has applications throughout biomedicine.

Transmission between hosts is a critical part of the viral lifecycle. Recent studies of viral transmission have 9 used genome sequence data to evaluate the number of particles transmitted between hosts, and the role 10 of selection as it operates during the transmission process. However, the interpretation of sequence data 11 describing transmission events is a challenging task. We here present a novel and comprehensive frame-12 work for using short-read sequence data to understand viral transmission events. Our model describes 13 transmission as an event involving whole viruses, rather than independent alleles. We demonstrate how 14 selection and noisy sequence data may each affect inferences of the population bottleneck, and identify

20The transmission bottleneck is defined as the number of viral particles that transmit from one 21 host to establish an infection in another. Genome sequence data has been used to evaluate the 22 size of the transmission bottleneck between humans infected with the influenza virus, however, 23 the methods used to make these estimates have some limitations. Specifically, viral allele 24 frequencies, which form the basis of many calculations, may not fully capture a process which 25 involves the transmission of entire viral genomes. Here we set out a novel approach for 26 inferring viral transmission bottlenecks; our method combines an algorithm for haplotype 27 reconstruction with maximum likelihood methods for bottleneck inference. This approach allows 28 for rapid calculation, and performs well when applied to data from simulated transmission 29 events; errors in the haplotype reconstruction step did not adversely affect inferences of the 30 population bottleneck. Applied to data from a previous household transmission study of 31 influenza A infection we confirm the result that the majority of transmission events involve a 32 small number of viruses, albeit with slightly looser bottlenecks being inferred, with between 1 33 and 13 particles transmitted in the majority of cases. While influenza A transmission involves a 34 JVI Accepted Manuscript Posted Online 15 April 2020 J. Virol.