Genetic diversity among pandemic 2009 influenza viruses isolated from a transmission chain
© Fordyce et al.; licensee BioMed Central Ltd. 2013
Received: 13 November 2012
Accepted: 9 April 2013
Published: 12 April 2013
Influenza viruses such as swine-origin influenza A(H1N1) virus (A(H1N1)pdm09) generate genetic diversity due to the high error rate of their RNA polymerase, often resulting in mixed genotype populations (intra-host variants) within a single infection. This variation helps influenza to rapidly respond to selection pressures, such as those imposed by the immunological host response and antiviral therapy. We have applied deep sequencing to characterize influenza intra-host variation in a transmission chain consisting of three cases due to oseltamivir-sensitive viruses, and one derived oseltamivir-resistant case.
Following detection of the A(H1N1)pdm09 infections, we deep-sequenced the complete NA gene from two of the oseltamivir-sensitive virus-infected cases, and all eight gene segments of the viruses causing the remaining two cases.
No evidence for the resistance-causing mutation (resulting in NA H275Y substitution) was observed in the oseltamivir-sensitive cases. Furthermore, deep sequencing revealed a subpopulation of oseltamivir-sensitive viruses in the case carrying resistant viruses. We detected higher levels of intra-host variation in the case carrying oseltamivir-resistant viruses than in those infected with oseltamivir-sensitive viruses.
Oseltamivir-resistance was only detected after prophylaxis with oseltamivir, suggesting that the mutation was selected for as a result of antiviral intervention. The persisting oseltamivir-sensitive virus population in the case carrying resistant viruses suggests either that a small proportion survive the treatment, or that the oseltamivir-sensitive virus rapidly re-establishes itself in the virus population after the bottleneck. Moreover, the increased intra-host variation in the oseltamivir-resistant case is consistent with the hypothesis that the population diversity of a RNA virus can increase rapidly following a population bottleneck.
Influenza A (family Orthomyxoviridae) is a negative sense, single-stranded RNA virus that infects a large variety of hosts, including aquatic birds, humans and swine. The influenza genome consists of eight segments, ranging from 890–2341 nucleotides (nt) in length, encoding up to 13 proteins. Reassortment of the eight segments between coinfecting strains results in genetic diversity of influenza virus. Such multiple-reassortment events occurring between numerous hosts were the cause of at least two pandemics in the 20th century and the 2009 pandemic due to the triple-reassortant swine-origin A(H1N1)pdm09 virus .
In addition to reassortment, influenza viruses generate genetic diversity due to the high error rate of their RNA polymerase during transcription. This results in mixed populations of virus genotypes within a single infection (intra-host variants), that often exhibit varying levels of fitness . Furthermore, the high mutation rate enables the virus to rapidly adapt to selective pressures, whether due to the host’s immune system or antiviral intervention. Genetic change can result in a virus subtype acquiring advantageous mutations such as those conferring antiviral-resistance. As the progeny of the successfully adapting viruses replace the other viruses in the population, population bottlenecks occur . These profoundly affect the dynamics of virus evolution, and an improved understanding of these intra-host processes may assist in the development of more effective antiviral treatments.
Until recently, the genetic diversity of a virus population could only be assessed by reverse-transcriptase PCR (RT-PCR) , RT-PCR/electroscopy ionization mass spectrometry (ESI-MS) , or by isolating and cloning individual viruses and applying Sanger sequencing . However, these approaches are time-consuming and laborious, hence only a few studies have analyzed influenza populations in great detail [7–11]. Deep sequencing techniques, including the Roche Genome Sequencer (GS) FLX and Illumina Genome Analyzer (GA) platforms, can detect low-frequency mutations and can provide considerable information on intra-host virus populations and the relative frequencies of virus variants. For instance, Ramakrishnan et al.  performed the first full influenza genome de novo Roche GS FLX sequencing for the purpose of identifying mixed infections and intra-host variation. Other studies have applied deep sequencing to patient samples from A(H1N1)pdm09-infected individuals to reveal intra-host diversity of the virus in relation to the presence of oseltamivir-resistance conferring mutations [7, 9].
Here we present a case-study where the mode of A(H1N1)pdm09 influenza transmission between four infected individuals is known, with the emergence of oseltamivir-resistant A(H1N1)pdm09 viruses in the last of the cases (http://who.int/csr/disease/swineflu/notes/h1n1_antiviral_resistance_20090708/en/index.html).
Using a novel real-time RT-PCR assay to initially detect A(H1N1)pdm09, we subsequently applied deep sequencing techniques to investigate the intra-host diversity in the cases infected with oseltamivir-sensitive viruses compared to the case carrying oseltamivir-resistant viruses.
Specimen collection and oseltamivir treatment information
Date of specimen collection
A(H1N1)pdm + or -
2 June 2009
60 twice daily
2 June 2009
60 twice daily
2 June 2009
75 twice daily
2 June 2009
75 once daily
7 June 2009
Neuraminidase inhibition assay
Oseltamivir IC50 (nM)
Zanamivir IC50 (nM)
Fold difference compared to sensitive control* for Oseltamivir IC50
A/Norway/1758/07 (seasonal H1N1 sensitive control)
A/Norway/1735/07 (seasonal H1N1 resistant control)
Roche GS FLX sequencing of NA gene
Intra-host variant sites and frequencies in GS FLX sequences from the NA gene in patient D compared to GAIIx sequences
Freq GS FLX
Freq GS FLX
Total Coverage GS FLX
Total Coverage GAIIx
Variation (%) GS FLX
Variation (%) GAIIx
Illumina GAIIx sequencing of full genomes
Locations and details of genome nucleotide positions containing variation
Dom base (freq)
Alt base (freq)
Log LH (AA)
Log LH (AB)
Log LH (BB)
S or NS.
Analysis for intra-host variants present in >2% of the sequences across all 8 segments of the influenza genome in cases C and D indicated variation at one, and seven nucleotide positions respectively, including variation at the oseltamivir-resistance conferring mutation in the NA gene (Table 4). This variation consisted of five transitions and three transversions and the eight single nucleotide positions were in the PA, HA, PBI and NA genes (Table 4). No intra-host variants were seen in the NS, M, NP and PB2 genes. All variant positions were sequenced with high coverage (a minimum of 123) and high quality (scoring 99 for genotype quality), indicating that they were unlikely to be the result of sequencing errors. Moreover, positions showing variation only contained two possible bases corresponding to either the dominant or the variant sequence, further reducing the possibility of sequencing error. The log-scaled likelihood values supporting intra-host variation (AB) were higher than the support for no variation (AA or BB in Table 4) for all the variant sites, excluding variation at nucleotide position 823 (conferring H275Y substitution) on the NA gene. However, given that the 275H genotype was represented in only 3% of the sequences from case D, the log-likelihood value was expected to be low.
Seven of the eight nucleotide positions showing evidence of intra-host variation caused non-synonymous amino acid substitutions, with the synonymous substitution being associated with nucleotide 1800 in the PA gene (Table 4). This high level of non-synonymous versus synonymous substitutions is consistent with a previous study , where Ghedin et al. deep sequenced intra-host variants of an A(H1N1)pdm09 virus and determined that there were 10 variant nucleotide positions causing 10 non-synonymous substitutions.
Top BLASTn and reference hits for intra-host variantsCase
Variant nt Location
A/green wing teal/Ohio/175/1986(H2N1)
A/northern pintail/Interior Alaska/8BM3582/2008(H3N8)
Chakrabarti et al. (2009)29
Baz et al. (2010)28
In this study, case C, who was treated with oseltamivir, most likely infected case D, who was receiving prophylactic doses of oseltamivir. Case C was sampled prior to receiving oseltamivir, while case D was sampled five days after oseltamivir prophylaxis commenced. It has been suggested that resistant viruses carrying the NA H275Y substitution suffer no fitness losses compared with those with NA 275H wild-type in the absence of drug intervention , and since samples were taken from cases A-C prior to oseltamivir-treatment, it is not possible to conclude whether resistance was acquired during their treatment and resistant virus transmitted to case D, or whether resistance emerged during prophylaxis in case D.
However, several pieces of evidence support case C infecting case D (although it cannot be ruled out that the infection originated from case A or B). Firstly, cases A-C tested positive for A(H1N1)pdm09 influenza on June 2nd and they were subsequently isolated. At this time case D remained negative for A(H1N1)pdm09 influenza. Case C and D were in a close, personal relationship and case D had only been in contact with case C (rather than cases A or B) when case D developed symptoms. Secondly, looking to the consensus sequences from patients C and D lends strong support to their epidemiological linkage. For all 8 segments it holds true that the consensus sequences of the virus populations are identical, with the exception of the H275Y conferring mutation in the NA gene from case D. Additionally, performing a BLASTn search against the GenBank nucleotide database (online version as of 14/3 2012, http://www.ncbi.nlm.nih.gov/blast) revealed that the HA, NP and NS genes were uniquely identical, meaning that they matched no other sequences in GenBank. The PB1 sequence matched only a single entry completely, and PB2 matched only 3 other entries (none of which share a patient origin with the PB1 hit), leaving only the PA and M genes matching multiple, globally distributed, entries in the database. For NA the sequences derived from patient C also matched multiple hits whereas those encoding resistance in patient D had a single perfect match.
To date, few studies have reported on the intra-host evolutionary dynamics of influenza viruses. One major reason for this has been the limited capacity to detect low frequency virus variants using conventional methods. However, new deep sequencing technologies offer an efficient and economic way to obtain a snapshot of the entire virus population. During this study we demonstrated the diversity between intra-host variants in cases of oseltamivir–sensitive and oseltamavir–resistant A(H1N1)pdm09 infections. While the master sequences of these cases remained identical, but for the mutation encoding the NA H275Y substitution, the subpopulations of the virus quasispecies varied significantly. Interestingly, case D contained a mixed population at nucleotide 823 on the NA gene, resulting in 3-14% (depending on the sequencing platform used) of the viruses remaining sensitive to oseltamivir. This result is similar to other reports of mixed populations occurring in H275Y variant A(H1N1)pdm09 viruses , and together they suggest either that a small proportion of the sensitive viruses survive the treatment, or that the mutation conferring oseltamivir sensitivity rapidly re-establishes itself in the virus population after the bottleneck. These data also suggest that the NA 275Y containing virus may be less fit than the sensitive NA 275H virus, a hypothesis that is supported by experiments in a ferret model , although contradictory to the 275Y variant outgrowing the 275H wild-type in MDCK cells. However, other authors did not find the resistant 275Y virus to be attenuated in other animal models . In order for the oseltamivir-resistant virus to be stable and more fit than the non-resistant counterpart, other changes in the NA or HA genes may have to be present as has been shown for the former seasonal A(H1N1) virus during 2008 .
In addition to harboring a subpopulation of oseltamivir-sensitive viruses, case D was noteworthy for the occurrence of seven additional intra-host variants. Only four of the seven mutations have been reported in previous influenza studies, three of which have been associated with A(H1N1)pdm09 virus (including that conferring H275Y substitution). Firstly, Baz et al.  reported that a NA S153N substitution occurred concomitantly with the H275Y substitution in an oseltamivir-resistant virus. Secondly, the mutation at residue 600 of the PA gene appears in numerous consensus sequences submitted to the NCBI database. Thirdly, the mutation conferring HA I282V substitution in A(H5N1) influenza virus, was reported by Chakrabarti et al. , but it was not seen in combination with NA H275Y substitution so is unlikely to be linked to oseltamivir-resistance. The occurrence of these intra-host variants in case D may be related to maintenance of virus fitness. However, these mutations occur in non-conserved regions of the influenza A virus genome [18–21], suggesting that they may have arisen as deleterious mutations during a population expansion, with no direct correlation to the NA H275Y conferring mutation.
Given one nucleotide change per 10,000 nucleotides during replication and that most infections are caused by 10–1,000 virions which likely possess varying numbers of nucleotide differences in their genomes, one can expect that each influenza A virion is a possible intra-host variant. However, we identify relatively few variant sites, probably because currently available sequence analysis software do not allow robust intra-host variant analyses and manual curation is necessary. Hence, we believe that with improved bioinformatic tools we would detect more subpopulation variation in our sample set. However, while our levels of intra-host variation seem low, they are consistent with other second-generation sequencing studies. Ghedin et al.  used a 10% cut-off for including a variant. This conservatively high cut-off ensured that variants were not determined by substitution errors (0.03% per nucleotide on the Roche GS FLX). Using this cut-off, the authors detected only 10 sites containing variation throughout the genome. Similarly Ramakrishnan et al.  detected between 0 and 10 sites with variation, depending on the sample.
The aim of our study was to characterize the intra-host variation occurring in the virus populations in a transmission chain. There are, however, some limitations to the methodology and processes that can influence the accurate quantification of subpopulation variants: i) cell culturing processes; ii) RT-PCR amplification; iii) emulsion PCR (emPCR) and bridge PCR (in GS FLX and GAIIx sequencing, respectively); and iv) the sequencing process.
Firstly, second-generation sequences for cases C and D were determined from viral culture isolates rather than from clinical specimens directly. It is possible that some of the substitutions observed may have occurred during passage of virus in cells, although reports of genetic variation occurring during MDCK cell passage are predominantly linked to changes in the NA and HA genes . MDCK cell cultures have been reported to select for new variants, particularly for mutations leading to enhanced growth of virus in these cells . However, given that both cases C and D were cultured in much the same manner, with only one passage more required for case D, they allow direct comparison, with the H275Y conferring mutation being the primary difference between the samples. Additionally, reports of oseltamivir-resistant viruses outgrowing sensitive viruses in MDCK and rhesus monkey kidney cells might suggest that the 3-14% (GAIIx and GS FLX results, respectively) of oseltamivir-sensitive virus that we detected may be an under-estimate of persisting oseltamivir-sensitive viruses in the case D patient [9, 16]. Thus, a direct analysis of clinical specimens for the polymorphisms at the sites listed in Table 3 would be required to confirm these observations. However, due to the low virus concentration in the case C and D clinical samples, we were unable to convert the uncultured samples into libraries. Future generations of sequencing platforms, such as the PacBio RS, requiring lower starting amounts of template and the ability to sequence single influenza segments may resolve these issues.
Secondly, PCR-induced errors were minimized in the preparation of the One-Step RT-PCRs and library amplification steps by using Platinum and Phusion (respectively), both high fidelity polymerases. Further, for the PCR replication step (5 separate reactions for the Illumina GAIIx library template), a small number of amplification cycles (18 cycles total) were used in the preparation of the amplified Illumina GAIIx library.
However, despite the aforementioned precautions, evidence of amplification biases were still evident in the variant sites detected in the NA gene of case D. The H275Y conferring mutation was present in 86% and 97% of sequences using the GS FLX and GAIIx platforms, respectively. This difference is likely to represent biases introduced during RT-PCR or emPCR/bridge PCR, rather than during cell culturing given that these libraries were constructed based on the same cell culture products. Repeating/duplicating the sequencing process could resolve this discrepancy. It should be noted that the GAIIx library was built using 5 replicate RT-PCR reactions; hence this could represent a more reliable variant frequency measurement. The differences could also represent biases introduced due to the differences in GS FLX and GAIIx library amplification and sequencing methods.
Moreover, we detected the NA S153N conferring mutation in 7% of the sequences obtained on the GAIIx platform but not those from the GS FLX platform. This could be explained by: i) a nearly 3-fold decrease in coverage of this site using the GS FLX platform (51-fold coverage compared to 138-fold coverage on the GAIIx platform); ii) the S153N conferring mutation arose as a sequencing error on the GAIIx sequencer; or iii) preferential PCR or sequencing bias in the GS FLX library for the dominant 153S encoding sequences. Given that the S153N encoding variant was present in 10/138 sequences, post-filtering, this anomaly is most likely explained by hypotheses i) or iii).
Given that oseltamivir treatment would cause a virus bottleneck, one might expect to see a reduction in the genetic diversity of the virus population . However, this is not what was observed in case D, as was seen in another A(H1N1)pdm09 study . Specifically, Ghedin et al.  compared virus sequences in specimens taken from an individual prior to and after the emergence of oseltamivir-resistance and detected no variation in the oseltamivir-sensitive sample, compared to 10 nucleotide positions showing variation in the resistant sample. There were no common positions of nucleotide variation, excluding the H275Y conferring mutation, between the resistant virus specimens analyzed in the two studies.
How might one explain these observations? Previously it was shown that RNA viruses can undergo rapid evolution following bottleneck events, leading to the accumulation of neutral and deleterious mutations and, rarely, the emergence of biologically fit variants [23, 24]. Therefore, in the present study, it would appear that the introduction of oseltamivir either as treatment to case C or as prophylaxis to case D created selective pressure that caused the drug-resistant viruses to rapidly accumulate in case D. However, as we had only one collection date for each case in this study, we could not determine whether or not the levels of virus variants remained constant throughout the infections. For future studies of intra-host variation it will be interesting to investigate samples taken over time-series, both within single infections to monitor the variation within an individual, and within longer transmission chains. The latter will enable characterization of whether the unexpected diversity post-bottleneck is maintained, or lost.
In conclusion, we used deep sequencing to characterize the diversity of influenza viruses within a transmission chain that involved the development of oseltamivir resistance. As in previous studies, we detected the presence of low levels of oseltamivir-sensitive virus in the case harboring oseltamivir-resistant viruses, suggesting either survival through the treatment bottleneck, or rapid re-evolution of the sensitivity-conferring mutation post bottleneck. In addition, we paradoxically detected higher levels of intra-host variation in the case harboring oseltamivir-resistant virus, compared to the case carrying oseltamivir-sensitive virus. This contributes evidence to support the hypothesis that post-bottleneck, virus population expansions result in the generation of greater levels of genetic diversity than are otherwise found in the population.
Materials and methods
Research carried out on humans was in compliance with the Helsinki Declaration. Following the guidelines of the National Board of Health (Denmark), informed consent for use of the sequences in this paper was not required from the sample sources, as the influenza viruses were analyzed for clinical diagnosis under Danish Data Protection Agency (Datatilsynet) permit number 2007-54-0364 provided to Dr Lars P. Nielsen, State Serums Institute. As required by this agreement, the identity of the patients remains anonymous.
Written informed consent was obtained from the patient for publication of this report and any accompanying images.
Virus isolation and extraction
Throat swabs collected from cases A-D and contacts were suspended in 1 ml of virus transport medium, 200 μl of which was used for extraction of viral RNA by a MagNA Pure LC Instrument applying the MagNa Pure LC Total Nucleic Acid Isolation Kit (Roche diagnostics, Basel, Switzerland).
Initial A(H1N1)pdm09 diagnosis was performed by real-time RT-PCR. Extracted RNA (5 μl) was added to 20 μl of master mix consisting of 10 μM of each primer and 2 μM of the Taqman probe together with reagents from the OneStep® RT-PCR Kit (QIAGEN, Hilden, Germany) according to the manufacturer’s instructions. Primer sequences are available upon request. Target sequences were amplified on the MX3005 Thermocycler system (Stratagene, CA, USA) with the following thermal cycling parameters: 20 minutes at 50°C, 15 minutes at 95°C followed by 45 cycles of 15 seconds at 95°C and 60 seconds at 55°C.
The NA genes from patient samples for cases C and D, prior to cell culturing, were amplified by traditional one-step RT-PCR and Sanger sequenced as previously described . We were unable to amplify all other gene segments from cases C and D prior to cell culturing.
Inoculation and neuraminidase inhibition assay
Patient samples from cases C and D were inoculated onto primary swine kidney cells (due to slow growth in MDCK cells) and were further propagated on MDCK cells and in 10-days-old fertilized chicken eggs. Specifically, sample C was passaged three times in swine kidney cells (titre 4 × 105 TCID50/ml), while sample D was passage four times in the same manner. The viruses were harvested and examined by neuraminidase inhibition assay to determine the NI drug sensitivity phenotype, at the WHO Collaborating Centre for Reference and Research on Influenza, London, UK. Inhibition of neuraminidase activity was measured using the fluorescent substrate, 2’-(4-methylumbelliferyl)-α-D-N-acetylneuraminic acid (MUNANA; Sigma). Briefly, 20 μl of virus was incubated with 30 μl of 100 μM MUNANA in 32.5 mM MES buffer pH 6.5 containing 4 mM CaCl2 for 1 hr at 37°C. The reaction was stopped by addition of 150 μl 0.1 M glycine containing 25% ethanol and 2% SuperQ pH 10.7 and fluorescence of the released 4-methylumbelliferone was measured at excitation and emission wavelengths of 360 nm and 460 nm, respectively. The activity of each virus sample was titrated, by assaying serial twofold dilutions, and the amount of virus adjusted to equivalent NA activities, which fell in the linear portion of the activity curve. Each virus was preincubated for 30 minutes at 37°C with oseltamivir or zanamivir at final concentrations of 4 μM-15.3pM, in serial 4-fold dilutions, NA activity measured and the drug concentration that inhibited 50% of the neuraminidase activity (IC50) was determined .
Roche Genome Sequencer FLX
The level of influenza RNA in the samples from cases A and B was of insufficient quantity/quality to enable complete influenza genome sequencing using universal influenza primers that co-amplify all 8 segments in a single RT-PCR reaction . Hence, Center for Disease Control (CDC) primers were used to RT-PCR amplify the NA genes from cases A, B (both patient samples), C and D (both cultured samples) . Although it would have been preferable to obtain sequence from the uncultured patient samples for cases C and D, to allow assessment of potential selection of sequence variants during the culture process, we were unable to construct libraries on these samples, hence the libraries were based on the cultured samples. PCR products were converted into Roche GS FLX libraries and were sequenced on 1/8th of a PicoTitre Plate (PTP), using LR70 chemistry, following the manufacturer’s protocol (Roche, Basel, Switzerland).
An Illumina GAIIx was used for full influenza genome sequencing (all 8 gene segments) for cell-cultured virus from cases C and D. In comparison to the Roche platform, the Illumina GAIIx yields several orders of magnitude more sequences in a single sequencing run, thereby allowing the generation of deeper sequencing coverage of the influenza genomes. Library building and sequencing of samples were performed using a previously described method . Briefly, full influenza genomes sampled from cases C and D were converted into cDNA and amplified, in five separate SuperScript III One-Step RT-PCR reactions (with Platinum Taq High Fidelity: Invitrogen, Carlsbad, CA) reactions, using a previously published method . The temperature cycle parameters were 94°C for 30 sec, 45°C for 30 sec, and 68°C for 3 min, followed by 31 cycles at 94°C for 30 sec, 57°C for 30 sec, and 68°C for 3 min. There were two reasons for amplifying the samples in five separate RT-PCR reactions: firstly, to create a large volume of sample that could then be concentrated; and secondly, to reduce the effects of biases caused by RT-PCR amplification. The five RT-PCR reactions were then pooled and built into indexed Illumina GAIIx libraries using the NEBNext Quick DNA Sample Prep Master Mix Set 2 (New England Biolabs, Ipswich, MA, USA) and sequenced on 1 lane of an Illumina GAIIx following the manufacturer’s protocol (Illumina, San Diego, CA, USA) as part of a larger pool of other libraries not relevant to this study.
Roche Genome Sequencer FLX
Sequence and quality files produced after sequencing were manipulated using R scripts in order to obtain fastq files suitable for subsequent processes. Roche GS FLX reads were mapped to the Influenza A(H1N1)pdm09 prototype, A/California/07/2009, NA gene (GI:229396468) using the bwasw algorithm  included in the bwa v.0.5.9-r16 package: bwasw was preferred over the regular bwa due to the length of sequence reads. Resulting bam files were filtered for reads with two or more different mapping locations and chimeric reads (defined as having two or more different mapping locations for different sections in the read) for the following analyses, using Perl scripts. After filtering, samtools v.0.1.14  rmdup was used in order to collapse PCR duplicates. PCR duplicates are defined as reads with the same 5’ mapping position and orientation; only the read with the highest mapping quality is kept. Samtools ’mpileup’, with its default parameters, was used on the sorted and collapsed alignments in order to produce a base pileup. Using the output from ’mpileup’, genotypes for each position were called using bcftools which implements a Bayesian diploid SNP calling model, based on base and mapping qualities. This model is useful when attempting to characterize the intra-host diversity due to its ‘calling of sites with variation’ capability.
Post Illumina GAIIx sequencing, data was sorted using the method detailed in Kampmann et al.. Briefly, reads were aligned to the reference A/California/07/2009 sequences using bwa v.0.5.9-r16 . The bam files were manipulated using Perl scripts, along with samtools v.0.1.14 , and GATK v.1.0.4641 M . Coverage and depth of coverage was calculated with GATK’s DepthOfCoverage analysis. Variants were called using GATK’s UnifiedGenotyper walker . The resulting vcf files were manually sorted to remove variants that occurred only once (i.e. singletons) or at a frequency of less than 2% of bases at the specific location.
Following the guidelines of the National Board of Health (Denmark), informed consent for use of the sequences in this paper was not required from the sample sources, as the influenza viruses were analyzed for clinical diagnosis under Danish Data Protection Agency (Datatilsynet) permit number 2007-54-0364 provided to Dr Lars P. Nielsen, State Serums Institute. As required by this agreement, the identity of the patients remains anonymous.
The authors thank Kim Magnussen and Morten Rasmussen for technical assistance with deep sequencing, and Maanasa Raghavan for her feedback on the manuscript draft.
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