In the past several years, single-molecule sequencing platforms, such as those by Pacific Biosciences and Oxford Nanopore Technologies, have become available to researchers and are currently being tested for clinical applications. They offer exceptionally long reads that permit direct sequencing through regions of the genome inaccessible or difficult to analyze by short-read platforms. This includes disease-causing long repetitive elements, extreme GC content regions, and complex gene loci. Similarly, these platforms enable structural variation characterization at previously unparalleled resolution and direct detection of epigenetic marks in native DNA. Here, we review how these technologies are opening up new clinical avenues that are being applied to pathogenic microorganisms and viruses, constitutional disorders, pharmacogenomics, cancer, and more.Copyright © 2018 Elsevier Ltd. All rights reserved.
Despite recent breakthroughs in treatment of hepatitis C virus (HCV) infection, we have limited understanding of how virus diversity generated within individuals impacts the evolution and spread of HCV variants at the population scale. Addressing this gap is important for identifying the main sources of disease transmission and evaluating the risk of drug-resistance mutations emerging and disseminating in a population.We have undertaken a high-resolution analysis of HCV within-host evolution from 4 individuals coinfected with human immunodeficiency virus 1 (HIV-1). We used long-read, deep-sequenced data of full-length HCV envelope glycoprotein, longitudinally sampled from acute to chronic HCV infection to investigate the underlying viral population and evolutionary dynamics.We found statistical support for population structure maintaining the within-host HCV genetic diversity in 3 out of 4 individuals. We also report the first population genetic estimate of the within-host recombination rate for HCV (0.28 × 10-7 recombination/site/year), which is considerably lower than that estimated for HIV-1 and the overall nucleotide substitution rate estimated during HCV infection.Our findings indicate that population structure and strong genetic linkage shapes within-host HCV evolutionary dynamics. These results will guide the future investigation of potential HCV drug resistance adaptation during infection, and at the population scale. © The Author(s) 2019. Published by Oxford University Press for the Infectious Diseases Society of America.
Detection of pretreatment minority HIV-1 reverse transcriptase inhibitor-resistant variants by ultra-deep sequencing has a limited impact on virological outcomes.
Ultra-deep sequencing (UDS) is a powerful tool for exploring the impact on virological outcome of minority variants with low frequencies, some even <1% of the virus population. Here, we compared HIV-1 minority variants at baseline, through plasma RNA and PBMC DNA analyses, and the dominant variants at the virological failure (VF) point, to evaluate the impact of minority drug-resistant variants (MDRVs) on virological outcomes.Single-molecule real-time sequencing (SMRTS) was performed on baseline RNA and DNA. The Stanford HIV-1 drug resistance database was used for the identification and evaluation of drug resistance-associated mutations (DRAMs).We classified 50 patients into virological success (VS) and VF groups. We found that the rates of reverse transcriptase inhibitor (RTI) DRAMs determined by SMRTS did not differ significantly within or between groups, whether based on RNA or DNA analyses. There was no significant difference in the level of resistance to specific drugs between groups, in either DNA or RNA analyses, except for the DNA-based analysis of lamivudine, for which there was a trend towards a higher prevalence of intermediate/high-level resistance in the VF group. The RNA MDRVs corresponded to DNA MDRVs, except for M100I and Y188H. Sequencing from DNA appeared to be more sensitive than from RNA to detect MDRVs.Detection of pretreatment minority HIV-1 RTI-resistant variants by UDS showed that MDRVs at baseline were not significantly associated with virological outcome. However, HIV-1 DNA sequencing by UDS was useful for detecting pretreatment drug resistance mutations in patients, potentially affecting virological responses, suggesting a potential clinical relevance for ultra-deep DNA sequencing. © The Author(s) 2019. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy. All rights reserved. For permissions, please email: email@example.com.
The DNA base modification N6-methyladenine (m6A) is involved in many pathways related to the survival of bacteria and their interactions with hosts. Nanopore sequencing offers a new, portable method to detect base modifications. Here, we show that a neural network can improve m6A detection at trained sequence contexts compared to previously published methods using deviations between measured and expected current values as each adenine travels through a pore. The model, implemented as the mCaller software package, can be extended to detect known or confirm suspected methyltransferase target motifs based on predictions of methylation at untrained contexts. We use PacBio, Oxford Nanopore, methylated DNA immunoprecipitation sequencing (MeDIP-seq), and whole-genome bisulfite sequencing data to generate and orthogonally validate methylomes for eight microbial reference species. These well-characterized microbial references can serve as controls in the development and evaluation of future methods for the identification of base modifications from single-molecule sequencing data.