Whole genome sequencing and de novo assembly identifies Sydney-like variant noroviruses and recombinants during the winter 2012/2013 outbreak in England
- T H Nicholas Wong1, 2, 4,
- Bethany L Dearlove1,
- Jessica Hedge1,
- Adam P Giess1,
- Paolo Piazza3,
- Amy Trebes3,
- John Paul5,
- Erasmus Smit6,
- E Grace Smith6,
- Julian K Sutton7,
- Mark H Wilcox8,
- Kate E Dingle1, 2,
- Tim E A Peto1, 2, 4,
- Derrick W Crook1, 2, 4,
- Daniel J Wilson1, 3 and
- David H Wyllie1, 4Email author
© Wong et al.; licensee BioMed Central Ltd. 2013
Received: 9 September 2013
Accepted: 11 November 2013
Published: 13 November 2013
Norovirus is the commonest cause of epidemic gastroenteritis among people of all ages. Outbreaks frequently occur in hospitals and the community, costing the UK an estimated £110 m per annum. An evolutionary explanation for periodic increases in norovirus cases, despite some host-specific post immunity is currently limited to the identification of obvious recombinants. Our understanding could be significantly enhanced by full length genome sequences for large numbers of intensively sampled viruses, which would also assist control and vaccine design. Our objective is to develop rapid, high-throughput, end-to-end methods yielding complete norovirus genome sequences. We apply these methods to recent English outbreaks, placing them in the wider context of the international norovirus epidemic of winter 2012.
Norovirus sequences were generated from 28 unique clinical samples by Illumina RNA sequencing (RNA-Seq) of total faecal RNA. A range of de novo sequence assemblers were attempted. The best assembler was identified by validation against three replicate samples and two norovirus qPCR negative samples, together with an additional 20 sequences determined by PCR and fractional capillary sequencing. Phylogenetic methods were used to reconstruct evolutionary relationships from the whole genome sequences.
Full length norovirus genomes were generated from 23/28 samples. 5/28 partial norovirus genomes were associated with low viral copy numbers. The de novo assembled sequences differed from sequences determined by capillary sequencing by <0.003%. Intra-host nucleotide sequence diversity was rare, but detectable by mapping short sequence reads onto its de novo assembled consensus. Genomes similar to the Sydney 2012 strain caused 78% (18/23) of cases, consistent with its previously documented association with the winter 2012 global outbreak. Interestingly, phylogenetic analysis and recombination detection analysis of the consensus sequences identified two related viruses as recombinants, containing sequences in prior circulation to Sydney 2012 in open reading frame (ORF) 2.
Our approach facilitates the rapid determination of complete norovirus genomes. This method provides high resolution of full norovirus genomes which, when coupled with detailed epidemiology, may improve the understanding of evolution and control of this important healthcare-associated pathogen.
Norovirus is a leading cause of diarrhoea worldwide and the most common aetiological agent of epidemic gastroenteritis in all age groups , being recognised in semi-closed institutional settings, particularly hospitals and care centres for the elderly, child care centres, military settings and cruise ships [2, 3]. The cost and burden of norovirus outbreaks on the use of health resources is substantial , hence rapid and effective interventions to reduce norovirus transmission are needed. However, successful development of these interventions relies, in part, on improving our understanding of norovirus transmission dynamics and global epidemiology.
Multiple norovirus genogroups and genotypes exist. Although co-circulation of different genotypes occurs every winter season, one genotype (GII.4) has dominated over all the others since the early 1990s worldwide, and has been responsible for the majority of outbreaks in the last 20 years [5, 6]. Since 2002, norovirus epidemiology has been characterized by ‘winter peaks’ of infection. However, autumn 2012 saw a marked departure from this pattern, with a large and unusually early outbreak affecting Western Europe [7–9]. Molecular typing of reported outbreaks indicated that this was due to a new strain designated Sydney 2012, which largely displaced the previously widespread New Orleans 2009 strain. The Sydney 2012 strain was described first in Australia in March 2012, and later worldwide including in the UK [7, 9].
Full length genome sequencing is improving our understanding of both host pathogen relationships and transmission within outbreaks of bacterial [10, 11] and viral  disease. To address this need for RNA viruses, we recently reported a flexible method using a modified RNA-Seq approach for sequencing direct extracts of faeces , yielding full length norovirus genomes by mapping to a reference norovirus sequence. This technique is simpler and likely to be less vulnerable to primer-induced biases than the re-sequencing of single long PCR products, or of multiple smaller PCR products . However, limitations arise from sole reliance on a mapping based approach. In particular, assembling recombinant chimeric viruses, which have recently been reported for Norovirus [15, 16], is likely to be incomplete or ineffective, and a de novo assembly approach might be more robust. To date, however, using de novo assembly of sequences derived from faecal extracts consisting of highly heterogeneous short reads from diverse organisms has not been reported.
Here we describe an end-to-end method for efficient sequencing and de novo assembly of full length norovirus genomes building on our RNA-Seq approach, including a comparison of de novo assembler performance. We demonstrate the power and future potential of this approach by characterizing the whole genome sequences of multiple GII.4 noroviruses representing October 2012 - January 2013 outbreaks from 10 sites in England and the island of Jersey. We discuss the general applicability of our approach to other viruses, and reflect on the implications of our results for the recent evolution and biological behaviour of the globally transmitted Sydney-like noroviruses.
Comparison with known norovirus genomes
Using blastn, we determined the number of reads similar to known human and animal norovirus sequences for each sample studied. We also examined the positions along the genome at which these reads mapped. We observed similar patterns for all sample and known norovirus sequence combinations, with more reads mapping towards the 3′ end of the virus and marked variation in read density across the genome. Counting numbers of reads similar to known norovirus sequences suggested many samples in our study contained sequences most similar to the Sydney norovirus Hu/GII.4/Sydney/NSW0514/2012/AU (Genbank accession JX459908.1); up to 22% of the norovirus reads in some samples matched this genome. One interesting aspect was that while some were similar to the Sydney 2012 strain throughout their length (e.g. samples C00014384 and C00014389), in others (e.g. samples C00014386, C00014390) the 5′ end appeared more similar to other known GII.4 strains.
De novo assembly of norovirus sequences
Determinants of non-assembly
Some samples did not assemble fully. Read numbers did not differ between samples which could not be fully assembled and samples that could be assembled (mean 1.8 × 106 vs. 2.1 × 106 reads (p = 0.22, t-test)). In contrast, the total number of reads matching norovirus sequences differed markedly (0.17 × 106 vs. 1.04 × 106 reads, p = 0.009). Read depth appears, therefore, to be a determinant of the ability to assemble using the technique we outlined here. The two qPCR-negative samples did not yield full genomes, although partial assemblies were produced (<59% of the genome in one sample).
Reproducibility of the process and relationship to capillary sequencing
To assess the reproducibility of our sequencing and assembly process, one sample was processed and sequenced independently three times starting from the same total RNA extract using the Illumina MiSeq. De novo assembly using our method revealed no nucleotide differences between these replicates. We compared the sequences obtained with capillary sequenced isolates (n = 16). We also analysed four repeat samples from a previous Illumina HiSeq run, re-sequenced to confirm reproducibility of both the sequencing and the pipeline analyses. Out of a total of 151,180 bases obtained by capillary sequencing of 20 samples (consisting of 16 samples and 4 replicates), comparison against the de novo pipeline generated a total of 49 differences; however, 44 of these were within 13nt of contig termini, suggesting that the two techniques concur well apart from at the very ends of the de novo contigs (five variants were not at the contig ends, representing 0.003% discordance between the sequencing methods).
Relationship of the outbreak strain to previous viruses
We investigated the support for this potential recombination event using the suite of recombination detection methods employed in the software RDP3 (35). No recombination events were detected in any of the 3 New Orleans 2009 strains in the sample (C00014394, C00014416, C00014423). Of the six recombination detection methods used, five provided significant support for the two sequences identified in the maximum likelihood trees as being recombinants. The recombination breakpoint was estimated to be at position 4,971 in the alignment, close to the ORF1/2 overlap (3SEQ p-value = 3.61 × 10-6).
Visual inspection of the phylogenetic trees and breakpoint analysis in RDP3 suggests that two recombinant sequences are present in our dataset, most likely sharing the same ancestral recombination event. We suggest that this involved the ORF1 from a New Orleans strain and the ORF2/ORF3 from a close relative of Sydney 2012.
Our study shows that a recently described, primer-independent method of RNA sequencing, together with an optimised bioinformatic pipeline has been established by which complete norovirus genomes can be recovered by de novo assembly from ~80% of faecal samples (23/28 qPCR + ve samples). A key part of the bioinformatic pipeline is the use of the Vicuna assembler, which outperformed other assemblers tested.
Since the technique described here is high-throughput, automatable and yields full length norovirus genomes in a high proportion of cases, it has the potential to transform the identification of noroviruses, and to enhance understanding of norovirus transmission. For example, we detected inter-genotypic recombinants, in two out of twenty three samples (~9%), supporting an emerging view that recombination within GII.4 strains may be relatively common. Recombination has been recently recognized to play an important role in the evolution of the GII.4 pandemic lineage [8–12]. The recombination breakpoint identified in our sample (4,971nt) was similar to the recombination hotspot recently described . This further supports the utility of the approach we describe here.
We have shown, using capillary sequencing as a gold standard, that the bioinformatic strategy used (de-novo consensus followed by mapping of reads back to the local consensus) produces valid consensus sequences and allows intra-sample strain detection. In theory, there might be individuals with mixed infections in which the de novo assembly fails to pick out either consensus. In practice however, such a situation does not appear to have occurred in the samples studied in this paper, where intra-specimen diversity appear to be very limited.
Although the results presented here are encouraging, larger multi-national sample studies are required to fundamentally answer questions about its feasibility in widespread clinical use and infection control. In addition, a larger sampling set may provide the best opportunity to rationalise the depth of coverage required to answer specific questions without wasting potential redundant sequence information.
Our novel end-to-end laboratory and bioinformatic solution generates accurate, complete norovirus genomes in a large majority of clinical samples without any enrichment or sequence-specific PCR steps. As such, it may complement and extend the power of already established epidemiological tools such as Noronet (http://www.rivm.nl/en/Topics/N/NoroNet) which currently rely on low-throughput fractional sequencing small parts of the genome, allowing improved determination of transmission routes in healthcare and community settings, as well as studies of evolution and molecular determinants of pathogenicity.
We have established an end to end approach using de novo assembly for achieving whole genome sequences of norovirus. This method provides an alternative to current diagnostic tests of norovirus, with the added benefit of supplying detailed resolution of the viral genome and improving our understanding of its evolution and surveillance of this important healthcare associated pathogen.
Materials and methods
Samples and laboratory processing8
Samples used for de novo assembly analyses
We analysed 46 faeces samples from multiple locations within England and the island of Jersey. These included 28 samples collected from patients with symptoms of diarrhoea and/or vomiting during outbreaks believed, based on clinical criteria , to be due to norovirus, both in hospital wards (n = 24) as well as in the community (n = 4). Reproducibility was assessed by using a New Orleans 2009 sample. One ward outbreak sample containing the New Orleans 2009 strain was included in the first Illumina MiSeq run and two replicates on the second run. Two stool samples from symptomatic patients within ward outbreaks found to be qPCR negative for norovirus were also included on the MiSeq runs. For assembly comparison, sixteen samples collected from hospital ward outbreaks between 2009–2011 previously sequenced using Illumina HiSeq, together with four replicates (i.e. re-sequenced using the same total RNA) of these samples were included. These samples had been subjected to complete capillary sequencing, as described previously . Quantitative polymerase chain reaction (qPCR) assays were performed for all samples using primers and Taqman probes as described .
Preparation and Illumina sequencing of RNA from faeces
Total RNA was extracted from faecal samples collected and prepared for sequencing using a modified RNA-Seq approach published recently . Briefly, total RNA from faecal samples was isolated using the Fujifilm Quickgene DNA tissue kit SII (Fuji, Japan) under the manufacturer’s RNA extraction from stool protocol. Three hundred microlitres of supernatant from a 10% clarified emulsion was used as the lysate. One hundred nanograms of total RNA was extracted using a NEBNext mRNA sample preparation kit (NEB) and first strand synthesis performed using random primers as described, substituting Accuscript reverse transcriptase (Agilent), which displays higher fidelity than the enzyme used previously [23, 24]. RNA-Seq library preparation was otherwise as described previously . We multiplexed 16 samples per MiSeq run using custom index tags.
A total of 32 samples, including replicates were sequenced using two MiSeq runs, generating paired end reads of 150 nucleotide (nt) in length. The 20 samples (consisting of 16 samples and 4 replicates) previously sequenced using the Illumina HiSeq 2000, consisted of 100nt paired end reads.
Norovirus reference sequences
477 full length norovirus genomes were downloaded from NCBI on 11 January 2013 (Additional file 1). We identified 91 sequence clusters with < =2% divergence over an alignment of at least 90% of the genome using BLASTClust, which is part of the NCBI Blast tools package. One representative genome was chosen from each cluster.
Identification of norovirus-like sequences among illumina reads
Illumina paired-end reads in which either or both sequences matched any cluster representative with a blastn e-value of <1×10-8 were retained. We refer to these sequences as Norovirus-like sequences (NLS). For each sample, the most similar reference sequence (MSRS) was identified on the basis of the number of matching read pairs.
Reads were quality trimmed using the FastX Toolkit (version 0.0.13, Cold Spring Harbour Laboratory, New York, USA (http://hannonlab.cshl.edu/fastx_toolkit/)) with a Q-score cut-off of 15, adapters were removed using CutAdapt , and duplicate read-pairs were removed using custom Python scripts. We screened reads for library artefact sequences of the form 5′ ABA, where A and B are sequences from the same strand of a norovirus reference genome, A is a sequence of at least 18 nucleotides, and ABA is a short read of either 100 (for HiSeq runs) or 150nt (for MiSeq runs). The ABA pattern is not present in any of the canonical norovirus sequences and we found a low (<1/1000) frequency of such reads (Additional file 1). Singleton reads without matching partners following processing, were also removed.
De novo assembly
We compared four de-novo assembly algorithms, Velvet , Celera , Edena , and Vicuna , adapting their default settings as follows: in Velvet, k-mer and exp_cov were explored in a pairwise manner; for k-mer, values of 23 to 79 in steps of 4 were evaluated for the following values of exp_cov: auto, 1, 3, 10, 20, 30, 40, 50, 75, 100, 125, 150, 175, 200, 225, 250, 300, 400, 500, 600, 700, 800, 1000, 1200, 1500, 1800, 2000. Ins_length was specified at 250, based on known insert size distribution. For Edena, all read trimming lengths between 35 and 150 in steps of 5 were evaluated. In Vicuna, the following settings were used: minMSize = 9, maxOverhangSize = 2, Divergence = 15, Max read overhand = 4, Max contig overhang = 6, Seed kmer length = 9, Min contig overlap = 25, Min contig links =2, min identity = 90. In cases where multiple assembly parameters were compared, the setting(s) producing maximal N50 were selected. For all assemblers, contigs less than 300nt were removed from further analysis.
Assessing de novo assembly
To assess assembly quality and performance, we aligned each contig to its MSRS with blastn and a minimum e-value of 1×10-8. We computed the number of contigs, N50, percent of the MSRS which aligned to contigs, presence of gapped or multiple alignments to the MSRS.
Additionally, NLS reads were mapped to ether the Vicuna-derived contigs, or to contigs produced by capillary sequencing and contig assembly using the Staden package  and Geneious Pro software (version 6.1.6; Biomatters, New Zealand), using the built-in mapping algorithm using the ‘highest sensitivity’ setting. The results of the mapping, and the alignment of the contigs to the reference, were inspected manually.
Within-patient variant discovery
The NLS reads were mapped to the de-novo contig if a single contig was derived from the assembly. Mapping was performed with BOWTIE2 (version 2.1.0)  using the --very-sensitive flag. Samtools (version 0.1.19)  was used to covert alignments to pileup format. Pileup files were parsed to produce variant calls, excluding variants with base quality scores of less than 30, or mapping quality scores of less than 40. Additionally, we undertook a step designed to assess credibility of variants supported by low read numbers: we ignored variants for which, using an exact Binomial test (R 2.1.5, binom.test function), the proportion of reads supporting a variant relative to the reference was not significantly different (p > 0.01) than an expectation of 1×10-4. Finally, we only considered variants present at 1% or more of the reads.
Mis-assembly at the termini of contigs
In three samples, we observed that, although >99.5% coverage was obtained, two contigs were produced that differed at their termini. In each case, one contig had high (>500 reads) read support and represented part of a canonical norovirus genome, while the other was a rearrangement of a noroviral genome, with low (2 – 4 reads) support. These rearrangements disrupt open reading frames and are therefore unlikely to originate from a replication-competent virus (data not shown). In view of this, and the low read support for them, we manually removed the re-arranged, low-read terminus from these three samples and formed a single contig by manual editing.
Phylogenetic analyses and recombination detection
All unique genome sequences assembled from one or two contigs (n = 23) were aligned in Muscle v3.8 . Only one of the three replicates has been included in our analyses. Maximum likelihood trees were constructed separately for ORF1 and ORF2/3 using PhyML 3.0 . One hundred bootstrap replicates were performed for each tree.
We examined our dataset for the presence of recombinant sequences using the recombination detection software RDP3 . We employed all 6 of the recombination detection methods available in RDP3’s automated scan, which provide the corresponding statistical significance of each event detected [31–36]. To identify as many potential breakpoints as possible, we included a genetically diverse set of 16 historical GII.4 reference sequences for which whole genome sequences were available from GenBank (accession numbers: FJ537134, X86557, AF145896, AY741811, EU310927, AB294779, AY502023, DQ369797, DQ078814, EF187497, EF684915, AB541319, GQ845368, HQ009513, GQ845367, JX459908).
The study was approved by Berkshire Research Ethics Committee on the 1st October 2010 (10/H0505/83) and information governance approval for processing of patient identifiable information was the UK National Information Governance Board (8-05(e)/2010).
The reads reported in this paper have been deposited in the European Nucleotide Archive Sequence Read Archive under study accession number PRJEB4318. The sequences produced by capillary sequencing used for validation have been similarly submitted under accession numbers HF952120-HF952135.
This study was supported by the National Institute for Health Research (NIHR) Oxford Biomedical Research Centre and the UKCRC Modernising Medical Microbiology Consortium, the latter funded under the UKCRC Translational Infection Research Initiative supported by Medical Research Council, Biotechnology and Biological Sciences Research Council and the NIHR on behalf of the Department of Health (grant G0800778) and the Wellcome Trust (grant 087646/Z/08/Z). We acknowledge the support of Wellcome Trust core funding (grant 090532/Z/09/Z) and MRC Hub (grant G0900747 91070). TEAP and DWC are NIHR Senior Investigators. THNW is an NIHR Oxford BRC Doctoral Research Fellow. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
We thank Dr David Hernandez, and Dr Xiao Yang, authors of the Edena and Vicuna assemblers, for helpful discussions. We wish to acknowledge Carlos del Ojo Elias for uploading the reads to the Sequence Read Archive, Dr Karen Knox and Peter Webber from Surrey and Sussex Healthcare NHS Trust, Dina Ashridge and Richard Winetrobe from Leeds University Hospitals Department of Microbiology and Virology, Dr Mohammed Osman Hassan-Ibrahim, Angeline Boorer, Kevin Cole from Brighton University Hospital, Dave Browning and Will Rivenburg from Public Health Laboratory Southampton for providing epidemiological data and faecal samples for extraction and analyses.
- Phillips G, Tam CC, Rodrigues LC, Lopman B: Prevalence and characteristics of asymptomatic norovirus infection in the community in England. Epidemiol Infect 2010, 138: 1454-1458. 10.1017/S0950268810000439PubMedView ArticleGoogle Scholar
- Blanton LH, Adams SM, Beard RS, Wei G, Bulens SN, Widdowson MA, Glass RI, Monroe SS: Molecular and epidemiologic trends of caliciviruses associated with outbreaks of acute gastroenteritis in the United States, 2000–2004. J Infect Dis 2006, 193: 413-421. 10.1086/499315PubMedView ArticleGoogle Scholar
- Bernard H, Hohne M, Niendorf S, Altmann D, Stark K: Epidemiology of norovirus gastroenteritis in Germany 2001–2009: eight seasons of routine surveillance. Epidemiol Infect 2013, 1-12. doi 10.1017/S0950268813000435Google Scholar
- Lopman BA, Reacher MH, Vipond IB, Hill D, Perry C, Halladay T, Brown DW, Edmunds WJ, Sarangi J: Epidemiology and cost of nosocomial gastroenteritis, Avon, England, 2002–2003. Emerg Infect Dis 2004, 10: 1827-1834. 10.3201/eid1010.030941PubMedPubMed CentralView ArticleGoogle Scholar
- Siebenga JJ, Lemey P, Pond SLK, Rambaut A, Vennema H, Koopmans M: Phylodynamic reconstruction reveals norovirus GII. 4 Epidemic expansions and their molecular determinants. PLoS Pathog 2010, 6: e1000884. 10.1371/journal.ppat.1000884PubMedPubMed CentralView ArticleGoogle Scholar
- Donaldson EF, Lindesmith LC, Lobue AD, Baric RS: Norovirus pathogenesis: mechanisms of persistence and immune evasion in human populations. Immunol Rev 2008, 225: 190-211. 10.1111/j.1600-065X.2008.00680.xPubMedView ArticleGoogle Scholar
- van Beek J, Ambert-Balay K, Botteldoorn N, Eden JS, Fonager J, Hewitt J, Iritani N, Kroneman A, Vennema H, Vinje J, et al.: Indications for worldwide increased norovirus activity associated with emergence of a new variant of genotype II.4, late 2012. Euro Surveill 2013, 18: 8-9.PubMedGoogle Scholar
- Fonager J, Hindbaek LS, Fischer TK: Rapid emergence and antigenic diversification of the norovirus 2012 Sydney variant in Denmark, October to December, 2012. Euro Surveill 2013, 18: 2-5.View ArticleGoogle Scholar
- Bennett S, MacLean A, Miller RS, Aitken C, Gunson RN: Increased norovirus activity in Scotland in 2012 is associated with the emergence of a new norovirus GII. 4 variant. Euro Surveill 2013, 18: 22-23.Google Scholar
- Eyre DW, Golubchik T, Gordon NC, Bowden R, Piazza P, Batty EM, Ip CLC, Wilson DJ, Didelot X, O’Connor L, et al.: A pilot study of rapid benchtop sequencing of staphylococcus aureus and clostridium difficile for outbreak detection and surveillance. BMJ Open 2012,2(3):e001124.PubMedPubMed CentralView ArticleGoogle Scholar
- Walker TM, Clp CL, Harrell RH, Evans JT, Kapatai G, Dedicoat MJ, Eyre DW, Wilson DJ, Hawkey PM, Crook DW, et al.: Whole-genome sequencing to delineate mycobacterium tuberculosis outbreaks: a retrospective observational study. Lancet Infect Dis 2013, 13: 137-146. 10.1016/S1473-3099(12)70277-3PubMedPubMed CentralView ArticleGoogle Scholar
- Malboeuf CM, Yang X, Charlebois P, Qu J, Berlin AM, Casali M, Pesko KN, Boutwell CL, DeVincenzo JP, Ebel GD, et al.: Complete viral RNA genome sequencing of ultra-low copy samples by sequence-independent amplification. Nucleic Acids Res 2013,41(1):e13. 10.1093/nar/gks794PubMedPubMed CentralView ArticleGoogle Scholar
- Batty EM, Wong TH, Trebes A, Argoud K, Attar M, Buck D, Ip CL, Golubchik T, Cule M, Bowden R, et al.: A modified RNA-Seq approach for whole genome sequencing of RNA viruses from faecal and blood samples. PLoS One 2013, 8: e66129. 10.1371/journal.pone.0066129PubMedPubMed CentralView ArticleGoogle Scholar
- Kundu S, Lockwood J, Depledge DP, Chaudhry Y, Aston A, Rao K, Hartley JC, Goodfellow I, Breuer J: Next generation whole genome sequencing identifies the direction of norovirus transmission in linked patients. Clin Infect Dis 2013,57(3):407-414. 10.1093/cid/cit287PubMedPubMed CentralView ArticleGoogle Scholar
- Bull RA, Tanaka MM, White PA: Norovirus recombination. J Gen Virol 2007, 88: 3347-3359. 10.1099/vir.0.83321-0PubMedView ArticleGoogle Scholar
- Eden JS, Tanaka MM, Boni MF, Rawlinson WD, White PA: Recombination within the pandemic norovirus GII.4 lineage. J Virol 2013, 87: 6270-6282. 10.1128/JVI.03464-12PubMedPubMed CentralView ArticleGoogle Scholar
- Kageyama T, Kojima S, Shinohara M, Uchida K, Fukushi S, Hoshino FB, Takeda N, Katayama K: Broadly reactive and highly sensitive assay for Norwalk-like viruses based on real-time quantitative reverse transcription-PCR. J Clin Microbiol 2003, 41: 1548-1557. 10.1128/JCM.41.4.1548-1557.2003PubMedPubMed CentralView ArticleGoogle Scholar
- Zerbino DR, Birney E: Velvet: algorithms for de novo short read assembly using de bruijn graphs. Genome Res 2008, 18: 821-829. 10.1101/gr.074492.107PubMedPubMed CentralView ArticleGoogle Scholar
- Myers EW, Sutton GG, Delcher AL, Dew IM, Fasulo DP, Flanigan MJ, Kravitz SA, Mobarry CM, Reinert KHJ, Remington KA, et al.: A whole-genome assembly of drosophila. Science 2000, 287: 2196-2204. 10.1126/science.287.5461.2196PubMedView ArticleGoogle Scholar
- Hernandez D, Francois P, Farinelli L, Osteras M, Schrenzel J: De novo bacterial genome sequencing: millions of very short reads assembled on a desktop computer. Genome Res 2008, 18: 802-809. 10.1101/gr.072033.107PubMedPubMed CentralView ArticleGoogle Scholar
- Yang X, Charlebois P, Gnerre S, Coole MG, Lennon NJ, Levin JZ, Qu J, Ryan EM, Zody MC, Henn MR: De novo assembly of highly diverse viral populations. BMC Genomics 2012, 13: 475. 10.1186/1471-2164-13-475PubMedPubMed CentralView ArticleGoogle Scholar
- Kaplan JE, Gary GW, Baron RC, Singh N, Schonberger LB, Feldman R, Greenberg HB: Epidemiology of Norwalk gastroenteritis and the role of Norwalk virus in outbreaks of acute nonbacterial gastroenteritis. Ann Intern Med 1982, 96: 756-761. 10.7326/0003-4819-96-6-756PubMedView ArticleGoogle Scholar
- Malet I, Belnard M, Agut H, Cahour A: From RNA to quasispecies: a DNA polymerase with proofreading activity is highly recommended for accurate assessment of viral diversity. J Virol Methods 2003, 109: 161-170. 10.1016/S0166-0934(03)00067-3PubMedView ArticleGoogle Scholar
- Arezi B, Hogrefe HH: Escherichia coli DNA polymerase III epsilon subunit increases moloney murine leukemia virus reverse transcriptase fidelity and accuracy of RT-PCR procedures. Anal Biochem 2007, 360: 84-91. 10.1016/j.ab.2006.10.009PubMedView ArticleGoogle Scholar
- Martin M: Cut adapt removes adapter sequences from high-throughput sequencing reads. EMBnet J 2011,17(1):10-12.View ArticleGoogle Scholar
- Bonfield JK, Smith K, Staden R: A new DNA sequence assembly program. Nucleic Acids Res 1995, 23: 4992-4999. 10.1093/nar/23.24.4992PubMedPubMed CentralView ArticleGoogle Scholar
- Langmead B, Salzberg SL: Fast gapped-read alignment with Bowtie 2. Nat Methods 2012, 9: 357-359. 10.1038/nmeth.1923PubMedPubMed CentralView ArticleGoogle Scholar
- Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, Marth G, Abecasis G, Durbin R, Genome Project Data Processing S: The sequence alignment/Map format and SAMtools. Bioinformatics 2009, 25: 2078-2079. 10.1093/bioinformatics/btp352PubMedPubMed CentralView ArticleGoogle Scholar
- Edgar RC: MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res 2004, 32: 1792-1797. 10.1093/nar/gkh340PubMedPubMed CentralView ArticleGoogle Scholar
- Guindon S, Dufayard JF, Lefort V, Anisimova M, Hordijk W, Gascuel O: New algorithms and methods to estimate maximum-likelihood phylogenies: assessing the performance of PhyML 3.0. Syst Biol 2010, 59: 307-321. 10.1093/sysbio/syq010PubMedView ArticleGoogle Scholar
- Martin D, Rybicki E: RDP: detection of recombination amongst aligned sequences. Bioinformatics 2000, 16: 562-563. 10.1093/bioinformatics/16.6.562PubMedView ArticleGoogle Scholar
- Martin DP, Posada D, Crandall KA, Williamson C: A modified bootscan algorithm for automated identification of recombinant sequences and recombination breakpoints. AIDS Res Hum Retroviruses 2005, 21: 98-102. 10.1089/aid.2005.21.98PubMedView ArticleGoogle Scholar
- Smith JM: Analyzing the mosaic structure of genes. J Mol Evol 1992, 34: 126-129.PubMedGoogle Scholar
- Posada D, Crandall KA: Evaluation of methods for detecting recombination from DNA sequences: computer simulations. Proc Natl Acad Sci USA 2001, 98: 13757-13762. 10.1073/pnas.241370698PubMedPubMed CentralView ArticleGoogle Scholar
- Gibbs MJ, Armstrong JS, Gibbs AJ: Sister-scanning: a Monte Carlo procedure for assessing signals in recombinant sequences. Bioinformatics 2000, 16: 573-582. 10.1093/bioinformatics/16.7.573PubMedView ArticleGoogle Scholar
- Boni MF, Posada D, Feldman MW: An exact nonparametric method for inferring mosaic structure in sequence triplets. Genetics 2007, 176: 1035-1047.PubMedPubMed CentralView ArticleGoogle Scholar
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