To enable the support for the rapidly expanding user requests, the team at Oxford Nanopore Technologies have put together an end-to-end workflow based on the ARTIC Network protocols and analysis methods.

While this protocol is available in the Nanopore Community, we kindly ask users to ensure they are citing the members of the ARTIC network who have been behind the development of these methods.

This protocol is based on the ARTIC amplicon sequencing protocol for MinION for nCOV-2019 by Josh Quick. The protocol generates 400 bp amplicons in a tiled fashion across the whole SARS-CoV-2 genome. Some example data is shown in the Downstream analysis and expected results section, this is generated using human coronavirus 229E to show what would be expected when running this protocol with SARS-CoV-2 samples.

Primers were designed by Josh Quick using Primal Scheme; the primer sequences can be found here.

Steps in the sequencing workflow:

Prepare for your experiment you will need to:

• Extract your RNA
• Ensure you have your sequencing kit, the correct equipment and third-party reagents
• Download the software for acquiring and analysing your data
• Check your flow cell to ensure it has enough pores for a good sequencing run

Prepare your library You will need to:

• Reverse transcribe your RNA samples with random hexamers
• Amplify the samples by tiled PCR using separate primer pools
• Combine the primer pools, purify and quantify the PCR products
• Prepare the DNA ends for adapter attachment
• Ligate native barcodes supplied in the kit to the DNA ends and pool the samples
• Ligate the sequencing adapters supplied in the kit to the DNA ends
• Prime the flow cell and load your DNA library into the flow cell

Sequencing and analysis You will need to:

• Start a sequencing run using the MinKNOW software, which will collect raw data from the device and convert it into basecalled reads
• Start the EPI2ME software and select the barcoding workflow

This protocol requires total RNA extracted from samples that have been screened by a suitable qPCR assay. Here we demonstrate the level of sensitivity and specificity by titrating total RNA extracted from cell culture infected with Human coronavirus 229E spiked into 100 ng human RNA extracted from GM12878 to give approximate figures.

Although not tested here, work performed by Josh Quick et al. on the Zika virus gives approximate dilution factors that may help reduction of inhibiting compounds that can be co-extracted from samples.

Note: this is a guideline and not currently tested for SARS-CoV-2.

qPCR ct	Dilution factor
18–35	none
15–18	1:10
12–15	1:100

When processing multiple samples at once, we recommend making master mixes with an additional 10% of the volume. We also recommend using pre- and post-PCR hoods when handling master mixes and samples. It is important to clean and/or UV irradiate these hoods between sample batches. Furthermore, to track and monitor cross-contamination events, it is important to run a negative control reaction at the reverse transcription stage using nuclease-free water instead of sample, and carrying this control through the rest of the prep.

To minimise the chance of pipetting errors when preparing primer mixes, we recommend ordering the tiling primers from IDT in a lab-ready format at 100 µM.

Where sample RNA is added to the below reaction, it is likely advantageous to follow the dilution guidelines proposed by Josh Quick:

qPCR Ct	Dilution factor
18–35	none
15–18	1:10
12–15	1:100

If the sample has a low copy number (ct 18–35) use up to 16 µl of sample. Use nuclease-free water to make up any remaining volume. Take note to be aware that co-extracted compounds may inhibit reverse transcription and PCR.

Name	Acronym	Cap colour	No. of vials	Fill volume per vial (µl)
DNA CS	DCS	Yellow	1	50
Adapter Mix	AMX	Green	1	40
Ligation Buffer	LNB	Clear	1	200
L Fragment Buffer	LFB	White cap, orange stripe on label	2	1,800
S Fragment Buffer	SFB	Grey	2	1,800
Sequencing Buffer	SQB	Red	2	300
Elution Buffer	EB	Black	1	200
Loading Beads	LB	Pink	1	360

Name	Acronym	Cap colour	No. of vials	Fill volume per vial (μl)
Flush Buffer	FB	Blue	6	1,170
Flush Tether	FLT	Purple	1	200

EXP-NBD104 kit contents

Name	Acronym	Cap colour	No. of vials	Fill volume per vial (μl)
Native Barcode 01-12	NB01-12	White	12	20
Adapter Mix II	AMII	Green	1	40

**EXP-NBD114 kit contents** 

Name	Acronym	Cap colour	No. of vials	Fill volume per vial (μl)
Native Barcode 13-24	NB13-24	White	12	20
Adapter Mix II	AMII	Green	1	40

Kits in batches NBD196.10.0007 onwards have barcodes ordered in columns on the plate:

Kits in batches prior to NBD196.10.0007 have barcodes ordered in rows:

Name	Acronym	Cap colour	No. of vials	Fill volume per vial (μl)
Native Barcode 01-96	NB01-96	-	1 plate	40 μl per well
Adapter Mix II	AMII	Green	1	70

Name	Acronym	Cap colour	No. of vials	Fill volume per vial (μl)
Short Fragment Buffer	SFB	Grey	4	1,800

Name	Acronym	Cap colour	No. of tubes	Fill volume per vial (μl)
Adapter Mix II	AMII	Green	2	40

Protocols that use the Native Barcoding Expansions require 5 μl of AMII per reaction. Native Barcoding Expansions EXP-NBD104/NBD114 and EXP-NBD196 contain sufficient AMII for 6 and 12 reactions, respectively (or 12 and 24 reactions when sequencing on Flongle). This assumes that all barcodes are used in one sequencing run.

The Adapter Mix II expansion provides additional AMII for customers who are running subsets of barcodes, and allows a further 12 reactions (24 on Flongle).

Below is the full list of our native barcode (NB01-96) sequences. The first 24 unique barcodes are available in the Native Barcoding Kit 24 V14 (SQK-NBD114.24). The Native Barcoding Kit 96 V14 (SQK-NBD114.96) include the first 24 native barcodes, with the additional 72 unique barcodes. The native barcodes are shipped at 640 nM.

In addition to the barcodes, there are also flanking sequences which add an extra level of context during analysis.

Barcode flanking sequences:

Forward sequence: 5' - AAGGTTAA - barcode - CAGCACCT - 3' Reverse sequence: 5' - GGTGCTG - barcode - TTAACCTTAGCAAT - 3'

Native barcode sequences

Component	Forward sequence	Reverse sequence
NB01	CACAAAGACACCGACAACTTTCTT	AAGAAAGTTGTCGGTGTCTTTGTG
NB02	ACAGACGACTACAAACGGAATCGA	TCGATTCCGTTTGTAGTCGTCTGT
NB03	CCTGGTAACTGGGACACAAGACTC	GAGTCTTGTGTCCCAGTTACCAGG
NB04	TAGGGAAACACGATAGAATCCGAA	TTCGGATTCTATCGTGTTTCCCTA
NB05	AAGGTTACACAAACCCTGGACAAG	CTTGTCCAGGGTTTGTGTAACCTT
NB06	GACTACTTTCTGCCTTTGCGAGAA	TTCTCGCAAAGGCAGAAAGTAGTC
NB07	AAGGATTCATTCCCACGGTAACAC	GTGTTACCGTGGGAATGAATCCTT
NB08	ACGTAACTTGGTTTGTTCCCTGAA	TTCAGGGAACAAACCAAGTTACGT
NB09	AACCAAGACTCGCTGTGCCTAGTT	AACTAGGCACAGCGAGTCTTGGTT
NB10	GAGAGGACAAAGGTTTCAACGCTT	AAGCGTTGAAACCTTTGTCCTCTC
NB11	TCCATTCCCTCCGATAGATGAAAC	GTTTCATCTATCGGAGGGAATGGA
NB12	TCCGATTCTGCTTCTTTCTACCTG	CAGGTAGAAAGAAGCAGAATCGGA
NB13	AGAACGACTTCCATACTCGTGTGA	TCACACGAGTATGGAAGTCGTTCT
NB14	AACGAGTCTCTTGGGACCCATAGA	TCTATGGGTCCCAAGAGACTCGTT
NB15	AGGTCTACCTCGCTAACACCACTG	CAGTGGTGTTAGCGAGGTAGACCT
NB16	CGTCAACTGACAGTGGTTCGTACT	AGTACGAACCACTGTCAGTTGACG
NB17	ACCCTCCAGGAAAGTACCTCTGAT	ATCAGAGGTACTTTCCTGGAGGGT
NB18	CCAAACCCAACAACCTAGATAGGC	GCCTATCTAGGTTGTTGGGTTTGG
NB19	GTTCCTCGTGCAGTGTCAAGAGAT	ATCTCTTGACACTGCACGAGGAAC
NB20	TTGCGTCCTGTTACGAGAACTCAT	ATGAGTTCTCGTAACAGGACGCAA
NB21	GAGCCTCTCATTGTCCGTTCTCTA	TAGAGAACGGACAATGAGAGGCTC
NB22	ACCACTGCCATGTATCAAAGTACG	CGTACTTTGATACATGGCAGTGGT
NB23	CTTACTACCCAGTGAACCTCCTCG	CGAGGAGGTTCACTGGGTAGTAAG
NB24	GCATAGTTCTGCATGATGGGTTAG	CTAACCCATCATGCAGAACTATGC
NB25	GTAAGTTGGGTATGCAACGCAATG	CATTGCGTTGCATACCCAACTTAC
NB26	CATACAGCGACTACGCATTCTCAT	ATGAGAATGCGTAGTCGCTGTATG
NB27	CGACGGTTAGATTCACCTCTTACA	TGTAAGAGGTGAATCTAACCGTCG
NB28	TGAAACCTAAGAAGGCACCGTATC	GATACGGTGCCTTCTTAGGTTTCA
NB29	CTAGACACCTTGGGTTGACAGACC	GGTCTGTCAACCCAAGGTGTCTAG
NB30	TCAGTGAGGATCTACTTCGACCCA	TGGGTCGAAGTAGATCCTCACTGA
NB31	TGCGTACAGCAATCAGTTACATTG	CAATGTAACTGATTGCTGTACGCA
NB32	CCAGTAGAAGTCCGACAACGTCAT	ATGACGTTGTCGGACTTCTACTGG
NB33	CAGACTTGGTACGGTTGGGTAACT	AGTTACCCAACCGTACCAAGTCTG
NB34	GGACGAAGAACTCAAGTCAAAGGC	GCCTTTGACTTGAGTTCTTCGTCC
NB35	CTACTTACGAAGCTGAGGGACTGC	GCAGTCCCTCAGCTTCGTAAGTAG
NB36	ATGTCCCAGTTAGAGGAGGAAACA	TGTTTCCTCCTCTAACTGGGACAT
NB37	GCTTGCGATTGATGCTTAGTATCA	TGATACTAAGCATCAATCGCAAGC
NB38	ACCACAGGAGGACGATACAGAGAA	TTCTCTGTATCGTCCTCCTGTGGT
NB39	CCACAGTGTCAACTAGAGCCTCTC	GAGAGGCTCTAGTTGACACTGTGG
NB40	TAGTTTGGATGACCAAGGATAGCC	GGCTATCCTTGGTCATCCAAACTA
NB41	GGAGTTCGTCCAGAGAAGTACACG	CGTGTACTTCTCTGGACGAACTCC
NB42	CTACGTGTAAGGCATACCTGCCAG	CTGGCAGGTATGCCTTACACGTAG
NB43	CTTTCGTTGTTGACTCGACGGTAG	CTACCGTCGAGTCAACAACGAAAG
NB44	AGTAGAAAGGGTTCCTTCCCACTC	GAGTGGGAAGGAACCCTTTCTACT
NB45	GATCCAACAGAGATGCCTTCAGTG	CACTGAAGGCATCTCTGTTGGATC
NB46	GCTGTGTTCCACTTCATTCTCCTG	CAGGAGAATGAAGTGGAACACAGC
NB47	GTGCAACTTTCCCACAGGTAGTTC	GAACTACCTGTGGGAAAGTTGCAC
NB48	CATCTGGAACGTGGTACACCTGTA	TACAGGTGTACCACGTTCCAGATG
NB49	ACTGGTGCAGCTTTGAACATCTAG	CTAGATGTTCAAAGCTGCACCAGT
NB50	ATGGACTTTGGTAACTTCCTGCGT	ACGCAGGAAGTTACCAAAGTCCAT
NB51	GTTGAATGAGCCTACTGGGTCCTC	GAGGACCCAGTAGGCTCATTCAAC
NB52	TGAGAGACAAGATTGTTCGTGGAC	GTCCACGAACAATCTTGTCTCTCA
NB53	AGATTCAGACCGTCTCATGCAAAG	CTTTGCATGAGACGGTCTGAATCT
NB54	CAAGAGCTTTGACTAAGGAGCATG	CATGCTCCTTAGTCAAAGCTCTTG
NB55	TGGAAGATGAGACCCTGATCTACG	CGTAGATCAGGGTCTCATCTTCCA
NB56	TCACTACTCAACAGGTGGCATGAA	TTCATGCCACCTGTTGAGTAGTGA
NB57	GCTAGGTCAATCTCCTTCGGAAGT	ACTTCCGAAGGAGATTGACCTAGC
NB58	CAGGTTACTCCTCCGTGAGTCTGA	TCAGACTCACGGAGGAGTAACCTG
NB59	TCAATCAAGAAGGGAAAGCAAGGT	ACCTTGCTTTCCCTTCTTGATTGA
NB60	CATGTTCAACCAAGGCTTCTATGG	CCATAGAAGCCTTGGTTGAACATG
NB61	AGAGGGTACTATGTGCCTCAGCAC	GTGCTGAGGCACATAGTACCCTCT
NB62	CACCCACACTTACTTCAGGACGTA	TACGTCCTGAAGTAAGTGTGGGTG
NB63	TTCTGAAGTTCCTGGGTCTTGAAC	GTTCAAGACCCAGGAACTTCAGAA
NB64	GACAGACACCGTTCATCGACTTTC	GAAAGTCGATGAACGGTGTCTGTC
NB65	TTCTCAGTCTTCCTCCAGACAAGG	CCTTGTCTGGAGGAAGACTGAGAA
NB66	CCGATCCTTGTGGCTTCTAACTTC	GAAGTTAGAAGCCACAAGGATCGG
NB67	GTTTGTCATACTCGTGTGCTCACC	GGTGAGCACACGAGTATGACAAAC
NB68	GAATCTAAGCAAACACGAAGGTGG	CCACCTTCGTGTTTGCTTAGATTC
NB69	TACAGTCCGAGCCTCATGTGATCT	AGATCACATGAGGCTCGGACTGTA
NB70	ACCGAGATCCTACGAATGGAGTGT	ACACTCCATTCGTAGGATCTCGGT
NB71	CCTGGGAGCATCAGGTAGTAACAG	CTGTTACTACCTGATGCTCCCAGG
NB72	TAGCTGACTGTCTTCCATACCGAC	GTCGGTATGGAAGACAGTCAGCTA
NB73	AAGAAACAGGATGACAGAACCCTC	GAGGGTTCTGTCATCCTGTTTCTT
NB74	TACAAGCATCCCAACACTTCCACT	AGTGGAAGTGTTGGGATGCTTGTA
NB75	GACCATTGTGATGAACCCTGTTGT	ACAACAGGGTTCATCACAATGGTC
NB76	ATGCTTGTTACATCAACCCTGGAC	GTCCAGGGTTGATGTAACAAGCAT
NB77	CGACCTGTTTCTCAGGGATACAAC	GTTGTATCCCTGAGAAACAGGTCG
NB78	AACAACCGAACCTTTGAATCAGAA	TTCTGATTCAAAGGTTCGGTTGTT
NB79	TCTCGGAGATAGTTCTCACTGCTG	CAGCAGTGAGAACTATCTCCGAGA
NB80	CGGATGAACATAGGATAGCGATTC	GAATCGCTATCCTATGTTCATCCG
NB81	CCTCATCTTGTGAAGTTGTTTCGG	CCGAAACAACTTCACAAGATGAGG
NB82	ACGGTATGTCGAGTTCCAGGACTA	TAGTCCTGGAACTCGACATACCGT
NB83	TGGCTTGATCTAGGTAAGGTCGAA	TTCGACCTTACCTAGATCAAGCCA
NB84	GTAGTGGACCTAGAACCTGTGCCA	TGGCACAGGTTCTAGGTCCACTAC
NB85	AACGGAGGAGTTAGTTGGATGATC	GATCATCCAACTAACTCCTCCGTT
NB86	AGGTGATCCCAACAAGCGTAAGTA	TACTTACGCTTGTTGGGATCACCT
NB87	TACATGCTCCTGTTGTTAGGGAGG	CCTCCCTAACAACAGGAGCATGTA
NB88	TCTTCTACTACCGATCCGAAGCAG	CTGCTTCGGATCGGTAGTAGAAGA
NB89	ACAGCATCAATGTTTGGCTAGTTG	CAACTAGCCAAACATTGATGCTGT
NB90	GATGTAGAGGGTACGGTTTGAGGC	GCCTCAAACCGTACCCTCTACATC
NB91	GGCTCCATAGGAACTCACGCTACT	AGTAGCGTGAGTTCCTATGGAGCC
NB92	TTGTGAGTGGAAAGATACAGGACC	GGTCCTGTATCTTTCCACTCACAA
NB93	AGTTTCCATCACTTCAGACTTGGG	CCCAAGTCTGAAGTGATGGAAACT
NB94	GATTGTCCTCAAACTGCCACCTAC	GTAGGTGGCAGTTTGAGGACAATC
NB95	CCTGTCTGGAAGAAGAATGGACTT	AAGTCCATTCTTCTTCCAGACAGG
NB96	CTGAACGGTCATAGAGTCCACCAT	ATGGTGGACTCTATGACCGTTCAG

请为MinION Mk1B配备一台高规格的计算机或笔记本电脑，以适配数据采集的速度。您可以在MinION Mk1B的IT配置要求文件中了解更多。

MinION Mk1C是一款集计算功能和触控屏幕于一体的便携式测序分析仪，它无需依赖任何额外设备，即可生成并分析纳米孔测序数据。您可以在 MinION Mk1C的IT配置要求文件中了解更多。

Sequencing on a MinION Mk1D requires a high-spec computer or laptop to keep up with the rate of data acquisition. For more information, refer to the MinION Mk1D IT requirements document.

MinKNOW

The MinKNOW software controls the nanopore sequencing device, collects sequencing data and basecalls in real time. You will be using MinKNOW for every sequencing experiment to sequence, basecall and demultiplex if your samples were barcoded.

For instructions on how to run the MinKNOW software, please refer to the MinKNOW protocol.

EPI2ME (optional)

The EPI2ME cloud-based platform performs further analysis of basecalled data, for example alignment to the Lambda genome, barcoding, or taxonomic classification. You will use the EPI2ME platform only if you would like further analysis of your data post-basecalling.

For instructions on how to create an EPI2ME account and install the EPI2ME Desktop Agent, please refer to this link.

我们强烈建议您在开始测序实验前，对测序芯片的活性纳米孔数进行质检。质检需在您收到MinION /GridION /PremethION测序芯片12周之内进行，或者在您收到Flongle测序芯片四周内进行。Oxford Nanopore Technologies会对活性孔数量少于以下标准的芯片进行替换** ：

测序芯片	芯片上的活性孔数确保不少于
Flongle 测序芯片	50
MinION/GridION 测序芯片	800
PromethION 测序芯片	5000

** 请注意：自收到之日起，芯片须一直贮存于Oxford Nanopore Technologies推荐的条件下。且质检结果须在质检后的两天内递交给我们。请您按照 测序芯片质检文档中的说明进行芯片质检。

To generate tiled PCR amplicons from the SARS-CoV-2 viral cDNA, primers were designed by Josh Quick using Primal Scheme. These primers are designed to generate 400 bp amplicons that overlap by approximately 20 bp. These primer sequences can be found here. Where we show example data outputs in this protocol, the same parameters were used to design primers to the human coronavirus 229E to provide guideline statistics.

During initial method development, it is useful to analyse 1 µl on an Agilent Bioanalyzer chip or an appropriate amount on an agarose gel. The traces below show expected results where a dilution series of coronavirus 229E was spiked into 100 ng of human RNA extracted from GM12878 (primers were designed against the human coronavirus 229E reference genome using Primal Scheme). Here, Qubit hsDNA results and Agilent Bioanalyser (DNA 12000 assay) traces are shown for 30 and 35 cycles of PCR with input concentrations ranging from 10 pg to 0.001 pg in 100 ng human RNA. While not directly comparable to Ct values of a real biological sample, these give a rough approximation of high to low viral titres. A human-only and reverse transcription negative control were also included.

Note: The viral RNA that was used for this spike-in experiment was obtained from ATCC and is total RNA extracted from human cell lines infected with coronavirus 229E. So, 10 pg of spike-in represents a mix of human and viral RNA, spiked into 100 ng of human RNA extracted from GM12878 cells.

Figure 1. DNA yield after PCR and AMPure XP clean-up for decreasing viral input and different PCR cycle numbers in a background of 100 ng human RNA.

For a 400 bp amplicon, approximately 50 ng (~0.2 pmol) is required for the end-prep step. PCR cycles can be adjusted based on initial results to minimise the number of cycles. For samples that provide less than 50 ng total yield, further PCRs may be carried out on the remaining reverse transcription reaction.

Figure 2. Bioanalyser traces of 1 µl of post-PCR cleaned up samples with decreasing input quantities, spiked into 100 ng human RNA amplified with 30 and 35 cycles. RT negative controls and human-only negative controls show no product in the 300–400 bp range.

Protocols that use the Native Barcoding Expansions require 5 μl of AMII per reaction. Native Barcoding Expansions EXP-NBD104/NBD114 and EXP-NBD196 contain sufficient AMII for 6 and 12 reactions, respectively (or 12 and 24 reactions when sequencing on Flongle). This assumes that all barcodes are used in one sequencing run.

The Adapter Mix II expansion provides additional AMII for customers who are running subsets of barcodes, and allows a further 12 reactions (24 on Flongle).

有关纳米孔数据分析的完整概述，包括碱基识别和次级分析，请参阅 数据分析 文档。

MinKNOW软件负责仪器控制，数据采集和实时碱基识别。如您已在计算机上安装MinKNOW，则可选择以下几种途径开展测序：

1. 使用计算机上的MinKNOW进行实时数据采集和碱基识别

请按照 MinKNOW 实验指南 的说明操作：从“开始测序”部分起，到“MinKNOW运行结束”部分止。

2. 使用MinION Mk1B/Mk1D测序仪进行实时数据采集和碱基识别

请按照 MinION Mk1B 用户手册 或 MinION Mk1D 用户手册中的说明操作。

3. 使用MinION Mk1C测序仪进行实时数据采集和碱基识别

请参照 MinION Mk1C 用户手册中的说明操作。

4. 使用GridION进行实时数据采集和碱基识别

请参照 GridION 用户手册 中的说明操作。

5. 使用PromethION测序仪进行实时数据采集和碱基识别

请参照 PromethION 用户手册 或 PromethION 2 Solo 用户手册中的说明操作。

6. 使用计算机上的MinKNOW进行数据采集，过后再用NinKNOW进行线下碱基识别

请按照 MinKNOW 实验指南 中的说明操作：从“开始测序”部分起，到“MinKNOW运行结束”部分止。 当您设置实验参数时，请将 碱基识别 选项设为“关”。 测序实验结束后，请按照 MinKNOW 实验指南的本地分析 部分操作。

The recommended workflows for the bioinformatics analyses are provided by the ARTIC network and are documented on their web pages at https://artic.network/ncov-2019/ncov2019-bioinformatics-sop.html.

The reference guided genome assembly and variant calling are also performed according to the bioinformatics protocol provided by the ARTIC network. Their best practices guide uses the software contained within the FieldBioinformatics project on GitHub.

This workflow uses only the basecalled FASTQ files to perform a high-quality reference-guided assembly of the SARS-CoV-2 genome. Sequenced reads are re-demultiplexed with the requirement that reads must contain a barcode at both ends of the sequence (this only applies to the Classic and Eco PCR tiling of SARS-CoV-2 protocols but not the Rapid Barcoding PCR tiling of SARS-CoV-2), and must not contain internal barcodes. The reads are mapped to the reference genome, primer sequences are excluded and the consensus sequence is polished. The Medaka software is used to call single-nucleotide variants while the ARTIC software reports the high-quality consensus sequence from the workflow.

The FieldBioinformatics workflow for SARS-CoV-2 sequence analysis is provided as a Jupyter notebook tutorial in the EPI2ME Labs software. The coronavirus workflow has been augmented to include additional steps that help with the quality control of individual libraries, and aid in the presentation of summary statistics and the final sets of called variants.

The FieldBioinformatics workflow for SARS-CoV-2 sequence analysis is also provided as an EPI2ME workflow – this provides a more accessible interface to a bioinformatics workflow and the provided cloud-based analysis also performs some secondary interpretation by preparing an additional report using the Nextclade software.

Here, results are shown based on human coronavirus 229E spiked into 100 ng of human RNA derived from GM12878 cell line. 10 pg–0.001 pg of viral RNA obtained from ATCC was spiked into the human RNA and human-only and reverse transcription negative controls were carried through the prep to sequencing. Every sample underwent 30 and 35 cycles of PCR to determine sensitivity and specificity guidelines, as well as the expected amplicon drop-out rate for each sample.

Note: The viral RNA from ATCC is generated from cell lines infected with human coronavirus 229E. The RNA supplied is total RNA extracted from the cell lines and includes both human and viral RNA. Therefore, the levels of sensitivity are likely to be higher than those reported here.

The graph below shows the expected sequence balancing if the protocol is followed. Here, equal masses went into the end-prep and native barcode ligation prior to pooling by equal mass for adapter ligation.

Figure 3. Number of reads per sample after native barcode demultiplexing in MinKNOW. All 14 samples were run on a single flow cell.

Sequences from each demultiplexed sample were aligned to the human coronavirus 229E genome using minimap2. The proportion of primary alignments per sample are reported below.

Figure 4. Proportion of reads for each sample aligning to the human coronavirus 229E reference genome.

After 12 hours of sequencing, the number of reads from the negative control samples aligning to the viral reference genome is shown in the graph below and is compared with the absolute number of sequences aligning to the lowest input (0.001 pg).

Figure 5. Absolute number of reads aligning to the human coronavirus 229E reference genome in the negative controls compared with the lowest input of viral RNA. Sequencing was carried out for 12 hours to pick up low levels of sequences assigned to barcodes representing these samples.

To assess the impact of PCR dropout with lowering input viral load and increasing PCR cycles, Mosdepth was used to calculate the proportion of the viral genome covered to different depth levels. These numbers were calculated after 12 hours of sequencing with 14 samples multiplexed.

Figure 6. Coverage and depth of the human coronavirus 229E genome for different input quantities of viral RNA and different cycle numbers after 12 hours of sequencing on a single flow cell.

This is unknown in real clinical samples. The graph below can be used to determine the proportion of the genome that could be covered to a given depth with different numbers of reads (30 cycles) at different input amounts in a background of 100 ng human RNA. Note: this is absolute depth.

Figure 7. Subsampled sequences to give an indication of the depth of sequencing achievable covering different amounts of the human coronavirus 229E genome. Input quantities and cycle number titrations show that high cycle numbers should be avoided where possible to minimise amplicon drop out.

This protocol provides amplification of low copy number viral genomes in a tiled method with low off-target amplification and minimal cross-contamination between samples. With <60 copies per reaction (0.001 pg viral input) in 100 ng background human RNA, under ideal circumstances, one should expect to cover >75% of the targeted genome at a depth of 200X within under 50,000 reads in the samples with the lowest viral titre and <20,000 reads in those with a higher viral titre.

我们还在 Nanopore 社区的“Support”板块 提供了常见问题解答（FAQ）。

如果以下方案仍无法解决您的问题，请通过电邮(support@nanoporetech.com)）或微信公众号在线支持（NanoporeSupport）联系我们。

我们还在 Nanopore 社区的“Support”板块 提供了常见问题解答（FAQ）。

如果以下方案仍无法解决您的问题，请通过电邮(support@nanoporetech.com)）或微信公众号在线支持（NanoporeSupport）联系我们。