A sequencing and subtyping protocol for Influenza A and B viruses using Illumina® COVIDSeq™ Assay Kit v1
Authors: Lin Ying 
Published: March 2023

Summary Genomic surveillance of influenza is important to guide preparedness and response to seasonal, pandemic, and zoonotic influenza. The COVID-19 pandemic demonstrated the value of Next-Generation Sequencing (NGS)-based pathogen genomic surveillance for identification and tracking of emerging SARS-CoV-2 variants to guide the Public Health response. Amplicon-based assays, such as the Illumina COVIDSeq™ Assay (RUO), enable low-cost, scalable sequencing of the SARS-CoV-2 genome. To develop a similar, streamlined protocol to sequence the full genome of influenza A and B viruses, we leveraged the primers published by Zhou et al. [7,8] and modified the Illumina COVIDSeq™ Assay (RUO) protocol accordingly. Then the sequencing data was analyzed with the Explify RPIP Data Analysis and DRAGEN™ COVID Lineage software. This study demonstrated that this end-to-end workflow can efficiently and consistently sequence the full genomes of influenza A and B viruses, and provide accurate information for subtyping, lineage tracing, and antiviral resistance detection of influenza viruses. Background Seasonal flu is an acute respiratory disease caused by influenza viruses, which are global threats to human and animal health [1]. Out of the four types of influenza viruses, influenza A and B viruses cause seasonal disease in humans. In the past, influenza A virus triggered multiple pandemics (Spanish Flu in 1918, Asian Flu in 1957, and Swine flu in 2009) and had devastating impacts in animals, such as the highly pathogenic avian flu H5N1 outbreak in winter 2022 [1,2]. The genome of influenza viruses, which consists of 8 negative-sense, single-stranded RNA segments, evolves rapidly through antigenic drift and shift [3]. Of particular importance are the Neuraminidase (NA) and Hemagglutinin (HA) genes of influenza A viruses that vary between subtypes and impact host range [4]. The antigenic characterization of influenza virus can help to select seasonal flu vaccines and inform the effectiveness of antiviral drugs on the current influenza virus strains [1]. Therefore, genomic surveillance of influenza is important to guide vaccine strain selection, antiviral resistance monitoring, and characterization of emerging influenza virus subtypes. Amplicon-based influenza virus genome sequencing protocols have been reported, and enabled identification and rapid tracking of evolving variants [5, 6]. The design of “universal” primers took advantage of the highly conserved promoter regions at each end of the influenza virus genome segments to amplify the entire genomes [7, 8]. However, the current influenza virus sequencing workflows are not well streamlined and usually have limited reproducibility. The Illumina COVIDSeq™ Assay (RUO) kit was built for genomic surveillance of SARS-CoV-2, which is another virus that threatens human health, using the primer pools designed by the ARTIC community that amplify SARS-CoV-2 with the amplicon tiling approach [9]. The amplicon tiling approach is not suitable for influenza viruses due to the high variability in their genomes. The modularity of COVIDSeq™ Assay (RUO) kit and the flexibility in the workflow provides a great opportunity to adapt to sequencing different targeting viruses with target specific primers and minor modifications in the protocol. This kit includes reagents for reverse transcription of RNA, PCR amplification, as well as bead-linked transposomes for streamlined tagmentation and indexed adaptors to generate sequencing libraries from amplicons of variable length [10]. We developed a protocol using the reagents included in the COVIDSeq™ Assay (RUO) kit based on the published protocols to sequence the full genomes of both influenza A and B virus (detail steps listed below) [7,8]. In this study we describe a step-by-step protocol for influenza A and B virus genome sequencing that leverages the Illumina COVIDSeq™ Assay (RUO) as well as the Explify RPIP Data Analysis and DRAGEN COVID Lineage software. Illumina COVIDSeq™ Assay (RUO) reagents remain the same with a shorter, modified protocol that utilizes 16 well-tested universal primers [7,8]. We demonstrate whole genome amplification, extensive sequencing coverage for all influenza virus genome segments, and reporting consensus genome sequences and subtypes, expanding the use of the Illumina COVIDSeq™ Assay (RUO) from SARS-CoV-2 to influenza A and B viruses. Results In order to evaluate the performance of the protocol, both contrived and clinical research influenza virus samples were tested in this study. For contrived samples, four different influenza A viral strains representing H1N1 and H3N2 subtypes were tested in a serial dilution with 10 ng of Universal Human Reference RNA (UHR) as background. Samples tested had cycle threshold (Ct) values between 26.3 to 39.1, as determined by the CDC real-time RT-PCR assay (Table 1) [11]. Viral RNA concentration was calculated based on a standard curve (see methods) and ranged from 2 to 4,325 viral RNA copies/µl. In addition, two influenza B virus strains were also tested with 10 ng UHR as background. For clinical research samples, we obtained eight nasopharyngeal swabs collected in 2022, including two negative controls, and then extracted viral RNA (see Methods). The Ct values for clinical research samples ranged from 21.2 to 31.1 (between 243 and 96,475 viral RNA copies/µl). We combined two primer sets published in Zhou et al. 2012 and Zhou et al. 2014 in our protocol to report both influenza A and B viral genomes (detailed protocols in Methods). All samples were sequenced on Illumina Nextseq 550 at 2 x 149 bp. For all four strains of influenza A virus contrived samples and the different viral load tested in this study, the coverage of influenza A viral genome is >90% in the Ct range tested (26.3-39.1), with median depth between 6 and 42,879 that correlated with viral load (Figure 1). When samples have Ct values <35, more than 99% of the influenza A viral genome is covered. Genomic coverage decreased with reducing viral load, and the variability between replicates increased for low viral load samples. As shown in the color annotation of Figure 1, the influenza A viral subtypes identified by Explify RPIP data analysis software are consistent with the input virus subtypes even with low viral load (Ct 37.2-39.1). This data demonstrated the robustness and sensitivity of this assay in sequencing influenza A viral genomes. We also tested this protocol on clinical research samples. For all six influenza A virus positive clinical research samples (Ct value 21.2-31.1), more than 98% of the genomes were covered by sequencing reads, and the median depth ranged from 20 to 88,686 in the Ct range tested (21.2-31.1) (Figure 2). Two of the samples were categorized as H1N1 subtype and the other four samples were categorized as H3N2 subtype by Explify RPIP data analysis software (labeled in orange and green respectively). For the two negative controls, no influenza viral genome was detected. This data showed that this protocol also worked well on clinical research samples. To verify the coverage of all eight segments, we used the consensus genome generated from Explify RPIP data analysis software and selected its best matched reference genome using NCBI BLAST. Then we used the selected reference genome in DRAGEN COVID lineage software to analyze the coverage of each segment. The genomic coverage plots for two representative clinical samples are shown in Figure 3 (H1N1) and Figure 4 (H3N2). The genome of all eight segments is fully covered by sequencing reads. Although the median coverage depth varies across different segments, the coverage depth is still more than sufficient to call variants for all segments, including the ones encoding HA and NA genes. To assign a clade based on the most up to date database, we input the consensus genome sequences (HA segment) of the six influenza A positive samples into NextClade (https://clades.nextstrain.org). All clade assignments, mutations, gaps and insertions are listed in Table 2. To test the sequencing depth requirement for influenza virus genome, we down sampled the sequencing depth of each sample (2 x 149bp) to 0.1M, 0.25M, 0.5M, or 1M clusters (or 0.2M, 0.5M, 1M, or 2M paired-end reads) and then analyzed each down sampled data set using Explify RPIP data analysis software. As shown in Figure 5, for all samples with Ct value <30, even when the sequencing depth is as low as 0.1M clusters, there is still >99% of influenza A virus genomic coverage and >100 median coverage depth. The genomic coverage of clinical research sample 6 decreased with lower read depth, most likely because of its low viral load (Ct=31.1). To validate whether the same primer pool can be used to sequence influenza B virus genomic RNA, we performed the assay on two influenza B virus contrived samples. As shown in Figure 6, both influenza B virus strains had genomic coverage >94% with median coverage depth >104. This data demonstrated that the protocol can be used to report on both influenza A and influenza B viral genomes. Conclusions In this protocol we present modifications for using the popular Illumina COVIDSeq™ Assay (RUO) for whole genome sequencing and subtyping of influenza A and B viruses for research use. Due to the extreme variability within the influenza virus genomic RNA segments, the standard amplicon tiling approach (overlapping ~400 bp amplicons) used for SARS-CoV-2 whole genome sequencing was not suitable. To overcome this challenge, we leveraged the universal primers published by Zhou and Wentworth [7,8] which bind to the highly conserved promoter regions of each influenza virus genomic RNA to enable efficient reverse transcription and cDNA production of each RNA segment. These large cDNAs (≤2.5 kb) are then tagmented, indexed by PCR amplification and then ready to sequence. Data analysis is another critical step when analyzing influenza virus samples, and in this protocol, we have provided guidelines for leveraging both the Illumina Explify RPIP Data Analysis and DRAGEN COVID Lineage software available on Illumina BaseSpace™, as well as NextClade analysis to characterize the influenza viruses. The data shown here demonstrate that this protocol: 1.Works well across a wide range of starting sample viral loads 2.Provides genomic coverage of ≥94% of viral strains tested 3.Requires only 0.2M paired-end reads (149 bp) per sample to obtain nearly complete genomic coverage when sample Ct <30. (2M paired-end 149 bp reads are recommended for low viral low samples) 4.Identifies both influenza A and B virus strains enabling efficient subtyping of samples 5.Utilizes a complete, commercially available COVIDSeq Assay (RUO) kit to simplify reagent ordering It is important to note that this protocol is not recommended for highly degraded samples due to need to produce long cDNA products spanning the length of each influenza virus genomic RNA segment. It may be possible to use degraded samples, but performance will likely suffer. It may also be possible to reduce read counts for each sample depending on the experimental goals, but experimental parameters may need further optimization. Acknowledgements We would like to acknowledge Discovery Life Sciences for providing the influenza A virus clinical research samples. 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