These kits are recommended for users who:

• wish to multiplex samples to reduce price per sample
• want to optimise their sequencing experiment for throughput
• require control over read length
• are interested in utilising upstream processes such as size selection or whole genome amplification

This protocol describes an efficient, low-cost method to sequence ASFV at scale. The method uses tiled PCR amplification of the virus to obtain good coverage, while enabling sample multiplexing to reduce run costs.

The kits used are the Native Barcoding Expansion 1-12 (EXP-NBD104) and 13-24 (EXP-NBD114), in conjunction with the Ligation Sequencing Kit (SQK-LSK109). There are 24 unique barcodes if using both expansion kits, allowing the user to pool up to 24 different samples in one sequencing experiment. It is highly recommended that a Lambda control experiment is completed first to become familiar with the technology.

Steps in the sequencing workflow:

Prepare for your experiment

You will need to:

• Extract your DNA, and check its length, quantity and purity The quality checks performed during the protocol are essential in ensuring experimental success
• 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:

• Amplify the viral genome using tiled primers, purify and pool the amplicons
• Repair the DNA, and prepare the DNA ends for barcode attachment
• Ligate Native barcodes supplied in the kit to the DNA ends
• Ligate sequencing adapters supplied in the kit to the DNA ends
• Prime the flow cell, and load your DNA library into the flow cell

Sequencing

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
• Assemble and analyse the ASF genome using bioinformatics tools of your choice (recommendations included in the "Downstream analysis" sections of the protocol)

For customers new to nanopore sequencing, we recommend buying the NEBNext® Companion Module for Oxford Nanopore Technologies® Ligation Sequencing (catalogue number E7180S or E7180L), which contains all the NEB reagents needed for use with the Ligation Sequencing Kit.

Please note, for our amplicon protocols, NEBNext FFPE DNA Repair Mix and NEBNext FFPE DNA Repair Buffer are not required.

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 vial	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

The native barcode sequences are the reverse complement of the corresponding barcode sequence in other kits. 24 unique barcodes are available in the Native Barcoding Expansion 1-12 and 13-24 (EXP-NBD104 and EXP-NBD114).

Native Barcoding Expansion 1-12 and 13-24 (EXP-NBD104 and EXP-NBD114)

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

ASFV primer sequences described in the protocol are subject to change. Any updates can be found at ASFV Lilo GitHub page.

Amplicon - primer pair	Forward sequence	Reverse sequence
ASFV1	GGCGTTCATTTCACAAGATGC	ACGGCATCTAAGCAGCTCAATG
ASFV2	CAGGCCGATATATCATTTCATCAATATTCA	ACCCAAAGCCCTGGAATCCTTA
ASFV3	GCAAACCAAGTGACTCACCCTC	ATTGTATGACGTCGGGGCAGAT
ASFV4	ACCTAGTAAAAGTCCTAGAAAAACCTTCA	CGCCATTGTTTTACACAGTCGC
ASFV5	TCGAGATTTTATTATTTGGATGCATCATCA	GGACTGATGAAAGCCGTGAA
ASFV6	TCCACGCGGTACTTGGCTCC	AGGCCTCGTTGGTGGAAAGGA
ASFV7	AGGGCTGATGCAAATCTCTTTTTCA	TCTCCGATTTTCGCATGCCAAA
ASFV8	AGTTTGCAAAGAGCCTAAAGATAGACT	AGCGTGGAACTGTAGATGACGA
ASFV9	TGCAGAAACCGCAGATGAATGT	ATAGGATTAGATGCGACGCCCA
ASFV10	GCATGTAGAGAGGTTTTGGTAGTCA	GGAAACAGCTGGAGAGTTGTGG
ASFV11	TGGTTTTGAAATAAAATGCCTTCTACGG	GGAATGCATGGACGAAGAAGCA
ASFV11 (alt)	CTATGGGATGGGAAGAGTGGTCAA	CGTCAACCGCCGCATTAGC
ASFV12	TCCTTGGGAGTTACAGCGAAGA	AATGAAATCATTCGCGGCGAGT
ASFV13	CAGACATTGGCAGTGATGGCTA	GAAATGCCGGGCCTTCTACAAA
ASFV14	GCTACTCCCCCAAATATCACATATAATTGT	TTTTTCGTGTTGCTGTTCGGGA
ASFV15	GGATGGCACCCTTCTCACAATC	TGCGTATGACCCGATGTTGTTG
ASFV16	GTCGACTTCACAGGAACAACGG	ACCCGCTTTACACAAAACACGT
ASFV17	TGGAATTTCCTGACGTGGCAAA	GCAACCGCTATTCCAAACAGGA
ASFV18	AGTTGTTGTCCTAGACCGTGGCA	TGAAAAGGAGGGCACGATCC
ASFV19	CCCGTATGCGGGCGTACTTT	TGGCCTCTTCTTTCCCCCGA
ASFV20	GGCCGCAACATTTGTGTCAAAG	GCTCGCGAACAAATTACTCCCA
ASFV21	GAATGGCAGCGATGATCTCAGG	TGCAGGGCAAGGGTATACTGAA
ASFV22	TGGCGTCGTTTAACAGCTTGAT	GCTGGATGGCAAATCGGTTGTA
ASFV23	AGGCGTGAAAATTCTTCTTCAAACA	AGACGTTTTAAGCTGCATGGCA
ASFV24	GGCAGCAGGATCTTAAAACCGG	TGCATAATGCCCAGCTTTTCGT
ASFV25	GCTGTTTAAGCGTTTCAAGCTGA	CTCCGCGGGGAACATTGTTTTA
ASFV26	CCCTGGGAGGAGTCATCATGAA	GGTCATTGACTTTGGAAGCGCT
ASFV27	ACTGTCTGCTAGACTCCCAGGA	CCCAAGAGGAGGAATGGTTTGC
ASFV28	GCCCCCTAGCGTCACCGAAT	CCAAGCCTGCTGCGAAGCTC
ASFV29	GACGCAATTTCGGCTGTTTTTAAAA	GACTTGGTCTCCGGCTCAAAAG
ASFV30	GTTGGGGTGTTGGAGCGAATAA	TTCTGCTTACGGACGATGCAAC
ASFV31	TAGTTGTGAAGCGTTCTCGGGT	GAGCACATGTTACTCGCCACTC
ASFV32	GGACTTCTTATGCTCAGATGGGC	ACTGCTGCAGGCGTTAAACATT

Sequencing on a MinION Mk1B requires a high-spec computer or laptop to keep up with the rate of data acquisition. For more information, refer to the MinION Mk1B IT requirements document.

The MinION Mk1C contains fully-integrated compute and screen, removing the need for any accessories to generate and analyse nanopore data. For more information refer to the MinION Mk1C IT requirements document.

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.

シークエンシング実験を開始する前に、フローセルのポアの数を確認することを強くお勧めします。このフローセルの確認は、MinION/GridION/PromethIONの場合は代理店への到着から１２週間以内に行ってください。またはFlongle Flow Cellの場合は代理店への到着から4週間以内に行う必要があります。Oxford Nanopore Technologiesは、フローセルチェックの実施から2日以内に結果が報告され、推奨される保管方法に従っていた場合に、以下の表に記載されているナノポアの有効数に満たさない場合には、フローセルを交換します。 フローセルのチェックを行うには、Flow Cell Check documentの指示に従ってください。

Flow cell	保証する最小有効ポア数（以下の数未満のフローセルが交換対象となります）
Flongle Flow Cell	50
MinION/GridION Flow Cell	800
PromethION Flow Cell	5000

Protocols that use the Native Barcoding Expansions require 5 μl of AMII per reaction. Native Barcoding Expansions EXP-NBD104/NBD114 contain sufficient AMII for 6 reactions (or 12 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).

For a full overview of nanopore data analysis, which includes options for basecalling and post-basecalling analysis, please refer to the Data Analysis document.

The sequencing device control, data acquisition and real-time basecalling are carried out by the MinKNOW software. Please ensure MinKNOW is installed on your computer or device. There are multiple options for how to carry out sequencing:

1. Data acquisition and basecalling in real-time using MinKNOW on a computer

Follow the instructions in the MinKNOW protocol beginning from the "Starting a sequencing run" section until the end of the "Completing a MinKNOW run" section.

2. Data acquisition and basecalling in real-time using the MinION Mk1B/Mk1D device

Follow the instructions in the MinION Mk1B user manual or the MinION Mk1D user manual.

3. Data acquisition and basecalling in real-time using the MinION Mk1C device

Follow the instructions in the MinION Mk1C user manual.

4. Data acquisition and basecalling in real-time using the GridION device

Follow the instructions in the GridION user manual.

5. Data acquisition and basecalling in real-time using the PromethION device

Follow the instructions in the PromethION user manual or the PromethION 2 Solo user manual.

6. Data acquisition using MinKNOW on a computer and basecalling at a later time using MinKNOW

Follow the instructions in the MinKNOW protocol beginning from the "Starting a sequencing run" section until the end of the "Completing a MinKNOW run" section. When setting your experiment parameters, set the Basecalling tab to OFF. After the sequencing experiment has completed, follow the instructions in the Post-run analysis section of the MinKNOW protocol.

Note: Information subject to change, please refer to No part gets left behind: Tiled nanopore sequencing of whole ASFV genomes stitched together using Lilo by Amanda Warr et al., 2021 for most recent updates.

The shotgun sequencing data were basecalled and demultiplexed using MinKNOW (v19.06.8) using Fast basecalling. Following basecalling the reads were aligned to an ASFV genome using minimap2 to identify ASFV reads, the .fast5 files for these reads were extracted using fast5_subset from the ont_fast5_api and these again using high accuracy basecalling (this reduces basecalling time, suitable for when working with lower spec laptops/computers that have low GPU capacity). The reads were assembled with Flye (v2.6) - additional Flye resources available following the link: Assembly of long, error-prone reads using repeat graphs and polished three times with Medaka (v0.7.1). Comparisons of quantity of data produced and the proportion of which were ASFV reads were done using NanoComp (v1.28.1) - additional Nanopack resources available following the link: NanoPack: visualizing and processing long-read sequencing data.

The data were basecalled and demultiplexed using Guppy (v5.0.14) using high or super accuracy model on a GPU.

The snakemake pipeline Lilo was used, taking the following steps:

1. Use Porechop (v0.2.3) to remove any sequencing adapters or barcodes that have made it through demultiplexing.
2. Align to a reference with minimap2 (v2.22) and samtools (v1.12) and separate reads into amplicons by alignment position with bedtools (v2.30.0).
3. Select reads of the expected amplicon length (+/-5%) and subset to 300X
4. Select the read with highest average base quality within +/-1% of the median length of reads for the amplicon to be the “reference” using bioawk v1 and remove any amplicons with fewer than 40 reads (targeting the median length allows for flexibility for large insertions or deletions).
5. Pool amplicon reads and references back into their original non-overlapping pools.
6. Polish the pools three times with Medaka (v1.4.4) and combine resulting polished amplicons.
7. Align to the reference with minimap2 and remove soft clipped bases (these likely represent missed barcodes or adapters).
8. Run porechop to remove primers from the amplicons.
9. Merge the amplicons with scaffold_builder (v2.3).

The required input to Lilo are demultiplexed reads in FASTQ format in a directory named “raw/”, a reference FASTA, a .bed file of primer alignments (as output by primal scheme), and a .csv of primer sequences (if there are ambiguous bases it is advised to expand them first) and a config file, described on the GitHub page. It is adaptable to any species (with a single genome fragment/chromosome) with any tiled primer scheme. The pipeline outputs a FASTA file containing the assembled genome.

A subset of genomes were also assembled using the ARTIC pipeline (v1.2.1) following the bioinformatics SOP using the Medaka method.

Quast (v5.0.2) was used to compare the assembled genomes to the most closely related publicly available ASFV assembly according to BLAST alignment (MN715134.1) - links and additional resources available following the link: Short and Long-Read Sequencing Survey of the Dynamic Transcriptomes of African Swine Fever Virus and the Host Cells. Samples where both WGS and tiled sequencing were used were compared for overall structure using nucmer (v4.0.0beta2) - links and aditional reources available following the link: MUMmer4: A fast and versatile genome alignment system.

The phylogeny analysis was limited to the tiled genomes, as these were the most accurate assemblies, and publicly available genomes. These were aligned using Mafft (v7.467) and maximum likelihood trees constructed using iqtree (v2.0.5).

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ご提案された解決策を試しても問題が解決しない場合は、テクニカルサポートに電子メール (support@nanoporetech.com)または LiveChat in the Nanopore Communityでご連絡ください。

Observation	Possible cause	Comments and actions
Low output from PCR	Insufficient primer	Increase the amount of primer pool in the PCR reaction by 0.25-1 µl, decrease water proportionally.
-	Insufficient DNA template	Use undiluted DNA.
-	Thermocycler fault	Ensure that you use a thermocycler that has been recently calibrated.
-	Insufficient viral DNA and an abundance of host DNA	Use a host depletion method such as NEBNext® Microbiome DNA Enrichment Kit before PCR*.
-	Low representation of a particular primer in the sequencing data	Spike in a small quantity of the primer in the 100 µM pool before future runs

* This may be prohibitively expensive at scale, but for precious samples this will have a noticeable impact on amplicon yield.

Nanopore Community Support セクションにFAQをご用意しています。

ご提案された解決策を試しても問題が解決しない場合は、テクニカルサポートに電子メール (support@nanoporetech.com)または LiveChat in the Nanopore Communityでご連絡ください。