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Abstract

Genome sequencing has been widely deployed to study the evolution of SARS-CoV-2 with more than 90,000 genome sequences uploaded to the GISAID database. We published a method for SARS-CoV-2 genome sequencing (https://www.protocols.io/view/ncov-2019-sequencing-protocol-bbmuik6w) online on January 22, 2020. This approach has rapidly become the most popular method for sequencing SARS-CoV-2 due to its simplicity and cost-effectiveness. Here we present improvements to the original protocol: i) an updated primer scheme with 22 additional primers to improve genome coverage, ii) a streamlined library preparation workflow which improves demultiplexing rate for up to 96 samples and reduces hands-on time by several hours and iii) cost savings which bring the reagent cost down to {pound}10 per sample making it practical for individual labs to sequence thousands of SARS-CoV-2 genomes to support national and international genomic epidemiology efforts.

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Claude Opus 5.5 · xhigh effort · 17 Oct 2026 · from the full text of version 1 (4 Sept 2020) · CC BY 4.0

V3 primer pools with 22 extra alternates improve coverage; revised library preps raise double-barcode demultiplexing from 42.15% to 74.5%, cut misassignment 35x and bring reagent cost near £10 per sample.

Amplicon sequencing is the dominant way to generate SARS-CoV-2 genomes for surveillance, but early adopters of the ARTIC protocol hit reproducible amplicon dropouts, poor barcode ligation that wasted over half the reads, and a laborious normalisation step that capped throughput. The authors quantify fixes for all three (extra alternate primers in V3 and two revised library-prep variants, GunIt and LoCost) and add a cost model over barcode counts, flowcell washing and sequencing platform.

Key results

  1. ShownThe revised library preparations substantially increase the fraction of reads that can be demultiplexed with double-ended barcoding while making barcode misassignment rarer.

    With porechop on libraries of 24 individually barcoded amplicons: demultiplexing rate 42.15% (Baseline), 67.1% (GunIt), 74.5% (LoCost); incorrect assignment 0.070%, 0.010% and 0.002%, a 35x reduction for LoCost over Baseline alongside a 32.4% higher demultiplexing rate. Single-end barcoding stayed worse (0.219% for LoCost). Runs produced about 5M reads in 12 hours. · Protocol improvements; Discussion

  2. ShownSubstituting reagents and shrinking reaction volumes lowers material cost per sample, 96-barcode runs lower it sharply, and a first flowcell wash saves more than any later wash.

    MinION with 24 barcodes: £33.42 (GunIt), £24.91 (LoCost), £16.85 (LoCost with one wash); with 96 barcodes: £18.19, £10.49 and £8.47. PromethION with 96 barcodes, LoCost and two washes gives £10.08. Reagent prices were those listed on Science Warehouse for the University of Birmingham on 1st April 2020. · Run configurations and reagent costs; Discussion; Cost model

  3. ShownOf the primer schemes compared on a cDNA dilution series, V3 gave the most complete coverage over the widest input range and the least uneven coverage, so fewer reads are needed per sample.

    All schemes (V1, V2, V3, Itokawa) reached full coverage at 1e-02 input with 131,072 reads; V3 alone held maximum coverage from 1e-01 to 1e-04 and led at 1e-05, while Itokawa led at 1e-06. V3 had the lowest coefficient of variation from 1e-01 to 1e-05; the discussion puts the V3 requirement at around 100k reads per sample. · Primer schemes; Discussion

  4. ShownWashing and reloading a flowcell with the same barcode set carries over very little of the previous library, making reuse viable for cost saving.

    Three eight-barcode libraries of E. coli amplicons loaded in turn on one FLO-MIN106 flowcell gave 0.01% carry-over after both the first and the second wash. The cost model caps washes at three per flowcell because it ignores pore loss from washing. · Run configurations and reagent costs; Amplicon generation; Library preparation and sequencing

  5. ShownReplacing the post-PCR bead clean-up and the normalisation step with a fixed dilution removes hours of hands-on work without hurting barcode assignment.

    A 1:10 dilution in place of the clean-up left barcode assignment unaffected and saved 1-2 hours; the authors attribute this to PCR product concentration plateauing near 100 ng/ul by cycle 35, which self-normalises input. GunIt held a mean 71.9% demultiplexing rate across 8 clinical runs. · Protocol improvements; Discussion; Library preparation and sequencing

Methods, data and reproducibility

Four multiplex primer schemes were run on a serial dilution of cDNA from cultured SARS-CoV-2 and scored for genome coverage after subsampling reads; three library-prep variants were compared by barcoding 24 known amplicons individually so each read's true origin could be recovered from its mapping position; reagent cost was modelled per platform, barcode count and number of flowcell washes.

  • cDNA dilution series from cultured SARS-CoV-2 clinical isolate England/2/2020 grown on Vero E6 cells · SARS-CoV-2 (Vero E6 cells) · n = dilutions 1e-01 to 1e-07, Ct 18 to undetected; stock 1.75×10^5 PFU/mL
  • Reference genome used for scheme design and read alignment · SARS-CoV-2 · MN908947.3
  • Singleplex amplicons 1-24 of the ARTIC V3 scheme, each with its own barcode, for the demultiplexing experiment · SARS-CoV-2 · n = 24 amplicons per protocol, 3 protocols
  • Genomic DNA amplicons used for the flowcell wash carry-over test · Escherichia coli DH5α · n = 21 amplicons, 3 libraries of 8 barcodes
  • Clinical sequencing runs using the GunIt protocol · n = 8 runs
Methods & tools
field bioinformatics pipeline (guppyplex, minion), primalscheme, porechop, Guppy (3.2.10 and 4.0.14), MinKNOW (19.12.6), minimap2, samtools, bedtools, seqtk, scipy, Oxford Nanopore MinION/GridION/PromethION/Flongle
Software & environment
Software versions are given for the sequencing and basecalling stack (MinKNOW 19.12.6, Guppy 3.2.10 and 4.0.14) and exact command lines for guppyplex, the minion command, guppy_barcoder and porechop; no container or dependency file.
Assay conditions & compute
12-hour nanopore runs for the primer-scheme and library-prep comparisons; the wash test ran a FLO-MIN106 9.4.1 flowcell until every amplicon had 100,000 reads. Reads were subsampled in batches doubling from 128 to 131072. No CPU/GPU or runtime figures for analysis.
Reproducibility gaps
The two links are protocols.io DOIs for the Baseline and GunIt protocols, not software repositories; no link is given for LoCost. The data availability statement says raw reads can be downloaded but the location is missing from this text.
Limitations (6)
  • Only one dataset per library-prep variant was generated; consistency is supported only for GunIt, across 8 clinical runs. · stated by the authors
  • Results depend on thermocycler calibration, which the authors invoke to explain why another group reports better coverage with their scheme than with V3; annealing temperature has to be tuned per instrument. · stated by the authors
  • The cost model ignores loss of active pores caused by washing, so washes were capped at three per flowcell. · stated by the authors
  • PCR enrichment still loses coverage wherever a region fails to amplify, and using amplicons diagnostically raises contamination risk because plates must be unsealed. · stated by the authors
  • Primer-scheme comparisons rest on a dilution series of one cultured isolate, so performance on diverse circulating lineages or degraded clinical RNA is not measured here. · noted in this summary
  • Several authors declare support from or employment by the manufacturer of the sequencing platform being evaluated. · noted in this summary

Who should read:Read this if you run or plan amplicon-based viral genome sequencing on nanopore and need concrete numbers on primer scheme coverage, barcode demultiplexing accuracy and per-sample reagent cost.

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