Illumina MiSeq and iSeq are widely used short-read next-generation sequencing (NGS) platforms. The MiSeq instrument is specialized for mid-range throughput, while the iSeq instrument has lower throughput but is less expensive and simpler to operate. Several studies have compared Illumina platforms for sequencing of a variety of specimen types, but very few have quantified differences in sequencing quality, particularly for viruses. This study compared read quality, single nucleotide polymorphism (SNP) calling, and assembly metrics for SARS-CoV-2, norovirus, and poliovirus samples sequenced on both platforms. MiSeq and iSeq trimmed reads exhibited equivalent percentage of bases ≥ Q30 (% ≥ Q30) and equivalent reference mapping percentages. SNP concordance rates between the two platforms were 41 out of 43 (95.3%) for SARS-CoV-2, 1,628 out of 1,633 (99.7%) for norovirus, and 9 out of 11 (81.8%) for poliovirus. Within each of the three virus groups, MiSeq and iSeq assemblies had equivalent N50 and maximum contig lengths. Despite platform-specific differences in the sequencing chemistry and flow cell design, MiSeq and iSeq offered comparable data quality, indicating that using either platform should produce concordant results for viral genomic sequencing.

Trimming adapters and low-quality bases from next-generation sequencing (NGS) data is crucial for optimal analysis. We evaluated six trimming programs, implementing five different algorithms, for their effectiveness in trimming adapters and improving quality, contig assembly, and single-nucleotide polymorphism (SNP) quality and concordance for poliovirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and norovirus paired data sequenced on Illumina iSeq and MiSeq platforms. Trimmomatic and BBDuk effectively removed adapters from all datasets, unlike FastP, AdapterRemoval, SeqPurge, and Skewer. All trimmers improved read quality (Q ≥ 30, 87.8 - 96.1%) compared to raw reads (83.6 - 93.2%). Trimmers implementing traditional sequence-matching (Trimmomatic and AdapterRemoval) and overlapping algorithm (FastP) retained the highest-quality reads. While all trimmers improved the maximum contig length and genome coverage for iSeq and MiSeq viral assemblies, BBDuk-trimmed reads assembled the shortest contigs. SNP concordance was consistently high (> 97.7 - 100%) across trimmers. However, BBDuk-trimmed reads had the lowest quality SNPs. Overall, the two adapter trimmers that utilized the traditional sequence-matching algorithm performed consistently across the viral datasets analyzed. Our findings guide software selection and inform future versatile trimmer development for viral genome analysis.

The role of sub-Saharan Africa in the global spread of influenza viruses remains unclear due to insufficient spatiotemporal sequence data. Here, we analyzed 222 codon-complete sequences of influenza A viruses (IAVs) sampled between 2011 and 2013 from five countries across sub-Saharan Africa (Kenya, Zambia, Mali, Gambia, and South Africa); these genomes were compared with 1209 contemporaneous global genomes using phylogeographical approaches. The spread of influenza in sub-Saharan Africa was characterized by (i) multiple introductions of IAVs into the region over consecutive influenza seasons, with viral importations originating from multiple global geographical regions, some of which persisted in circulation as intra-subtype reassortants for multiple seasons, (ii) virus transfer between sub-Saharan African countries, and (iii) virus export from sub-Saharan Africa to other geographical regions. Despite sparse data from influenza surveillance in sub-Saharan Africa, our findings support the notion that influenza viruses persist as temporally structured migrating metapopulations in which new virus strains can emerge in any geographical region, including in sub-Saharan Africa; these lineages may have been capable of dissemination to other continents through a globally migrating virus population. Further knowledge of the viral lineages that circulate within understudied sub-Saharan Africa regions is required to inform vaccination strategies in those regions.

Genetic characterisation of circulating influenza viruses directs annual vaccine strain selection and mitigation of infection spread. We used next-generation sequencing to locally generate whole genomes from 116 A(H1N1)pdm09 and 118 A(H3N2) positive patient swabs collected across Uganda between 2010 and 2018. We recovered sequences from 92% (215/234) of the swabs, 90% (193/215) of which were whole genomes. The newly-generated sequences were genetically and phylogenetically compared to the WHO-recommended vaccines and other Africa strains sampled since 1994. Uganda strain hemagglutinin (n = 206), neuraminidase (n = 207), and matrix protein (MP, n = 213) sequences had 95.23-99.65%, 95.31-99.79%, and 95.46-100% amino acid similarity to the 2010-2020 season vaccines, respectively, with several mutated hemagglutinin antigenic, receptor binding, and N-linked glycosylation sites. Uganda influenza type-A virus strains sequenced before 2016 clustered uniquely while later strains mixed with other Africa and global strains. We are the first to report novel A(H1N1)pdm09 subclades 6B.1A.3, 6B.1A.5(a,b), and 6B.1A.6 (± T120A) that circulated in Eastern, Western, and Southern Africa in 2017-2019. Africa forms part of the global influenza ecology with high viral genetic diversity, progressive antigenic drift, and local transmissions. For a continent with inadequate health resources and where social distancing is unsustainable, vaccination is the best option. Hence, African stakeholders should prioritise routine genome sequencing and analysis to direct vaccine selection and virus control.