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      An amplicon-based sequencing framework for accurately measuring intrahost virus diversity using PrimalSeq and iVar

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          Abstract

          How viruses evolve within hosts can dictate infection outcomes; however, reconstructing this process is challenging. We evaluate our multiplexed amplicon approach, PrimalSeq, to demonstrate how virus concentration, sequencing coverage, primer mismatches, and replicates influence the accuracy of measuring intrahost virus diversity. We develop an experimental protocol and computational tool, iVar, for using PrimalSeq to measure virus diversity using Illumina and compare the results to Oxford Nanopore sequencing. We demonstrate the utility of PrimalSeq by measuring Zika and West Nile virus diversity from varied sample types and show that the accumulation of genetic diversity is influenced by experimental and biological systems.

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          The online version of this article (10.1186/s13059-018-1618-7) contains supplementary material, which is available to authorized users.

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          Most cited references 33

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          Detection and quantification of rare mutations with massively parallel sequencing.

          The identification of mutations that are present in a small fraction of DNA templates is essential for progress in several areas of biomedical research. Although massively parallel sequencing instruments are in principle well suited to this task, the error rates in such instruments are generally too high to allow confident identification of rare variants. We here describe an approach that can substantially increase the sensitivity of massively parallel sequencing instruments for this purpose. The keys to this approach, called the Safe-Sequencing System ("Safe-SeqS"), are (i) assignment of a unique identifier (UID) to each template molecule, (ii) amplification of each uniquely tagged template molecule to create UID families, and (iii) redundant sequencing of the amplification products. PCR fragments with the same UID are considered mutant ("supermutants") only if ≥95% of them contain the identical mutation. We illustrate the utility of this approach for determining the fidelity of a polymerase, the accuracy of oligonucleotides synthesized in vitro, and the prevalence of mutations in the nuclear and mitochondrial genomes of normal cells.
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            Insight into biases and sequencing errors for amplicon sequencing with the Illumina MiSeq platform

            With read lengths of currently up to 2 × 300 bp, high throughput and low sequencing costs Illumina's MiSeq is becoming one of the most utilized sequencing platforms worldwide. The platform is manageable and affordable even for smaller labs. This enables quick turnaround on a broad range of applications such as targeted gene sequencing, metagenomics, small genome sequencing and clinical molecular diagnostics. However, Illumina error profiles are still poorly understood and programs are therefore not designed for the idiosyncrasies of Illumina data. A better knowledge of the error patterns is essential for sequence analysis and vital if we are to draw valid conclusions. Studying true genetic variation in a population sample is fundamental for understanding diseases, evolution and origin. We conducted a large study on the error patterns for the MiSeq based on 16S rRNA amplicon sequencing data. We tested state-of-the-art library preparation methods for amplicon sequencing and showed that the library preparation method and the choice of primers are the most significant sources of bias and cause distinct error patterns. Furthermore we tested the efficiency of various error correction strategies and identified quality trimming (Sickle) combined with error correction (BayesHammer) followed by read overlapping (PANDAseq) as the most successful approach, reducing substitution error rates on average by 93%.
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              • Record: found
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              Rapid evolution of RNA genomes.

              RNA viruses show high mutation frequencies partly because of a lack of the proofreading enzymes that assure fidelity of DNA replication. This high mutation frequency is coupled with high rates of replication reflected in rates of RNA genome evolution which can be more than a millionfold greater than the rates of the DNA chromosome evolution of their hosts. There are some disease implications for the DNA-based biosphere of this rapidly evolving RNA biosphere.
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                Author and article information

                Contributors
                nathan.grubaugh@yale.edu
                gkarthik@scripps.edu
                Journal
                Genome Biol
                Genome Biol
                Genome Biology
                BioMed Central (London )
                1474-7596
                1474-760X
                8 January 2019
                8 January 2019
                2019
                : 20
                Affiliations
                [1 ]ISNI 0000000122199231, GRID grid.214007.0, Department of Immunology and Microbiology, , The Scripps Research Institute, ; La Jolla, CA 92037 USA
                [2 ]ISNI 0000000419368710, GRID grid.47100.32, Department of Epidemiology of Microbial Diseases, , Yale School of Public Health, ; New Haven, CT 06510 USA
                [3 ]ISNI 0000 0004 1936 7486, GRID grid.6572.6, Institute of Microbiology and Infection, , University of Birmingham, ; Birmingham, B15 2TT UK
                [4 ]ISNI 0000 0001 0723 0931, GRID grid.418068.3, Laboratory of Experimental Pathology, Gonçalo Moniz Institute, , Oswaldo Cruz Foundation, ; Salvador, Bahia Brazil
                [5 ]ISNI 0000 0004 1936 9684, GRID grid.27860.3b, Department of Pathology, Microbiology and Immunology, , University of California, ; Davis, CA 95616 USA
                [6 ]ISNI 0000 0001 0647 2963, GRID grid.255962.f, Department of Biological Sciences, College of Arts and Sciences, , Florida Gulf Coast University, ; Fort Myers, FL 33965 USA
                [7 ]ISNI 0000 0000 8788 3977, GRID grid.421470.4, Department of Environmental Sciences, , The Connecticut Agricultural Experiment Station, ; New Haven, CT 06504 USA
                [8 ]Department of Environmental Health, San Diego County Vector Control Program, San Diego, CA 92123 USA
                [9 ]ISNI 0000 0004 1936 9684, GRID grid.27860.3b, California National Primate Research Center and Department of Pathology, Microbiology and Immunology, , University of California, ; Davis, CA 95616 USA
                [10 ]Scripps Research Translational Institute, La Jolla, CA 92037 USA
                Article
                1618
                10.1186/s13059-018-1618-7
                6325816
                30621750
                © The Author(s). 2019

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100000060, National Institute of Allergy and Infectious Diseases;
                Award ID: U19AI135995
                Award ID: R21AI137690
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100006108, National Center for Advancing Translational Sciences;
                Award ID: UL1TR002550
                Award Recipient :
                Categories
                Method
                Custom metadata
                © The Author(s) 2019

                Genetics

                viral sequencing, west nile, zika, intrahost evolution, amplicon sequencing, snp calling

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