This protocol describes the process for library preparation and Adaptive Sampling sequencing for three samples per PromethION Flow Cell, using the Native Barcoding Kit and the Adaptive Sampling target enrichment function in MinKNOW. All Oxford Nanopore Technologies supplied reagents required for this protocol are included in the Multiplex Adaptive Sampling bundles available in 18-sample or 72-sample formats. These bundles include the Native Barcoding Kit and all necessary sequencing components, and is the standard configuration for implementing this workflow.

You can use an Oxford Nanopore ready-to-use, research-use-only digital panel as your BED-file-defined panel, or create a custom digital panel using the Adaptive Sampling, Digital Panel Designer. If you would like to create a custom panel, refer to the Adaptive Sampling technical guide - Digital Panel Designer for more information.

Data analysis is not part of this protocol. The Data outputs and analysis (section 13) describes which exported BED file to use, and the workflow for each panel: wf-hereditary-cancer for the Hereditary Cancer Panel and wf-human-variation for custom germline panels.

The Multiplex Adaptive Sampling protocol is intended mainly for germline applications, in which each sample needs moderate coverage across the panel, rather than the depth needed to detect low-frequency variants.

For panels covering 0.1–5% of the genome, we expect each of the three samples on a flow cell to reach a mean coverage of about 30x across the targets, with ~90% of target bases covered at more than 20x. Custom panels differ in size, gene content and sequence context, so the coverage your panel reaches may differ. Coverage also depends on the number of available pores on the flow cell, the fragment length of the library, and how evenly the three samples are represented in the pool.

We recommend running a pilot with your panel and confirming the coverage you need, before processing large numbers of samples.

Oxford Nanopore digital panel specification

Ready-to-use digital panels:

	Hereditary Cancer	Pan-Caner	Pan-Haematological Cancer
Enriched genes	258 inherited cancer risk genes	723 cancer associated genes	144 haematological malignancies associated genes
Validated Adaptive Sampling protocols	Multiplex Adaptive Sampling	Ultra-rapid singleplex Adaptive Sampling Singleplex Adaptive Sampling	Singleplex Adaptive Sampling
Input amount†	1 µg	Ultra-rapid singleplex: 1 µg Singleplex: 500 ng to 1 µg*	1 µg
Input sample type	Blood	Solid tumour tissue	Blood Bone marrow
Recommended extraction kits	Genomic DNA extraction from human blood using the Qiagen Puregene kit‡	1. QIAamp Fast DNA Tissue Kit (Qiagen, 51404) Recommended for Ultra-rapid singleplex Adaptive Sampling 2. Puregene Tissue Kit (Qiagen, 158063) 3. MagAttract HMW DNA Kit (Qiagen, 67563)	1. Genomic DNA extraction from human blood using the Qiagen Puregene kit‡ 2. QIAamp DSP DNA Mini Kit (Qiagen, 61304) 3. GenFind V3 Genomic DNA Extraction Kit (Beckman Coulter, C34880)
QC info (Femto Pulse)	Extracted gDNA samples may be assessed on the Femto Pulse System to visualise the unsheared/sheared gDNA profiles. For example profiles refer to the Input DNA section.	Extracted gDNA samples may be assessed on the Femto Pulse System to visualise the unsheared/sheared gDNA profiles. For example profiles refer to the DNA QC section. For the Ultra-rapid singleplex AS protocol, perform gDNA quality control assessment after completion of the sequencing run using aliquots reserved during the relevant sample preparation steps.	Extracted gDNA samples may be assessed on the Femto Pulse System to visualise the unsheared/sheared gDNA profiles. For example profiles refer to the DNA QC section.
Shearing conditions (speed and time)	Three centrifugation steps at ~3,381 RCF for 1 minute each. Refer to the corresponding protocol step for further details.	Two centrifugation steps at ~3,381 RCF for 30 seconds each. Refer to the corresponding protocol step for further details.	Two centrifugation steps at ~4,868 RCF for 1 minute each. Refer to the corresponding protocol step for further details.
Reference genomes	GRCh38_GIABv3	GRCh38_GIABv3	GCA_000001405.15_GRCh38_no_alt_analysis_set.fna
Enrichment BED file (links to the BED files can be found on the Adaptive Sampling page)	ONT_AS_HCP_GRCh38_enrichment_v1.bed	ONT_AS_PanCancer_GRCh38_enrichment_v1.bed	ONT_AS_PanHaem_GRCh38_enrichment_v1.bed

*A lower input limit of 500 ng can be used; however 1 µg is recommended whenever possible to improve pore occupancy.

^†A maximum of 2 µg input can be used to maximise pore occupancy.

^‡This Oxford Nanopore adapted extraction method uses the Puregene Blood Kit (Qiagen, 158023). It has gentler mixing conditions and resuspends the final DNA at 50°C rather than 65°C.

Prepare for your experiment

You will need to:

• Extract HMW gDNA from each whole blood sample. You can use the following recommended protocol for blood extraction, Genomic DNA extraction from human blood using the Qiagen Puregene kit.
• Design a custom panel in the Digital Panel Designer and export the BED files, or download the BED files for a ready-to-use panel and download the matching reference FASTA file (section 4).
• Ensure you have your sequencing kit, the correct equipment, and third-party reagents.
• Check your flow cell to ensure it has sufficient pores for a good sequencing run.

Sample preparation, library preparation, and sequencing timing overview

Step in workflow	Process	Time	Stop option
Sample preparation	Extract gDNA from sample and quantify. Fragment the gDNA and quantify. Check the length, quantity and purity of your extracted material. The quality checks performed during the protocol are recommended to ensure experimental success.	Dependent on extraction kit used ~15 minutes for shearing	At this stage, the extracted gDNA or fragmented gDNA can be stored at –20°C for later use.
DNA repair and end-prep	Repair the gDNA, and prepare the DNA ends for adapter attachment.	60 minutes	4°C overnight
Native barcode ligation	Ligate the native barcodes to the DNA ends.	70 minutes	4°C overnight
Sequencing adapter ligation and clean-up	Ligate sequencing adapters to the DNA ends.	60 minutes	4°C overnight
Priming and loading the flow cell	Prime the flow cell, and load your DNA library into the flow cell.	10 minutes
Sequencing	Sequence your library using your sequencing device.	72 hours
Data analysis	Analyse using one of our EPI2ME workflows.

For a successful Adaptive Sampling run, MinKNOW needs two files: an enrichment BED file, which lists the regions to enrich for, and a reference FASTA file for the same genome build. Enrichment BED files can be created in the Digital Panel Designer, or you can start from one of our ready-to-use panels. Instructions for using the Digital Panel Designer, including the design checks and buffer settings, are given in the Adaptive Sampling technical guide.

The export produces three BED files and a summary report. The files are named by date and panel name, in the form:

YYYY-MM-DD_panel-name_enrichment.bed

Only the enrichment BED file is loaded into MinKNOW.

File	Contents	Used in
*_enrichment.bed	Two rows per target, one for the plus strand and one for the minus strand, each with buffer at the 5′ end.	MinKNOW in the Adaptive Sampling BED field (section 12).
*_analysis.bed	One row per target, with no buffer.	Coverage and variant calling over the targets (section 13).
*_exons.bed	One row per exon of the MANE Select transcript of each gene, or of the Ensembl canonical transcript where there is none.	Exon-level coverage analysis (section 13).
summary.html	Panel statistics, design checks, the target table and a genome browser view of the targets and buffers.	Your record of the panel design.

MinKNOW needs a reference FASTA file to align reads and make Adaptive Sampling decisions. The reference must be the same genome build that was selected in the Digital Panel Designer when the panel was exported. We recommend the following files:

Panel	Build	Reference FASTA file for MinKNOW	Source
Custom panel	GRCh38	GCA_ 000001405. 15_ GRCh38_ no_ alt_ analysis_ set. fna. gz	NCBI
Custom panel	GRCh37	hg19. fa. gz	UCSC
Hereditary Cancer Panel	GRCh38	GRCh38_ GIABv3_ no_ alt_ analysis_ set_ maskedGRC_ decoys_ MAP2K3_ KMT2C_ KCNJ18. fasta. gz	Genome in a Bottle

For the Hereditary Cancer Panel, we recommend the Genome in a Bottle (GIAB) v3 GRCh38 reference, which was used to establish the performance of the panel. It is the GRCh38 no-alt analysis set with falsely duplicated regions of the assembly masked, so it uses the same coordinates, and the panel BED files exported from the Digital Panel Designer can be used with it unchanged.

The GRCh38 files above contain no alternate locus contigs. If a reference that includes alternate contigs is used instead, reads from regions with alternate haplotypes, such as the HLA genes, can be split between the primary assembly and the alternate contigs. The hg19 file contains a small number of haplotype contigs in the MHC region, and the same applies to panels with targets in that region.

If you use another reference file whose chromosome names differ from the BED files, rename the chromosomes in the BED files to match the reference. Do not rename the reference. We do not advise pre-indexing the reference before uploading it, as MinKNOW indexes it automatically at the start of the run. Reference requirements are described in more detail in the Adaptive Sampling technical guide.

All Oxford Nanopore Technologies reagents required for this protocol are included in the Multiplex Adaptive Sampling bundles, available in the Nanopore Store in 18-sample or 72-sample formats.

These bundles include the Native Barcoding Kit and all necessary sequencing components, and are the standard configuration for implementing this workflow.

For more information on specific kit components found within these bundles, please refer to the relevant products found in the Nanopore Store page:

• Multiplex Adaptive Sampling bundle 18: for 18 samples
• Multiplex Adaptive Sampling bundle 72: for 72 samples

• ~1 µg of sheared gDNA

This protocol has been validated with gDNA extracted from fresh human whole blood collected in EDTA K2 tubes, using the Puregene Blood Kit (Qiagen, 158023) from 1 ml of blood with an Oxford Nanopore adapted method. The adapted method uses gentler mixing and resuspends the final DNA at 50°C rather than 65°C. It is described in the Genomic DNA extraction from human blood using the Qiagen Puregene kit protocol.

Other extraction kits have not been tested with this protocol. gDNA from whole blood extracted with another kit may perform well, if it meets the requirements below, but meeting them does not guarantee the performance, as the fragment length and purity profile of the DNA can affect enrichment and output. If you use another kit, we recommend running a pilot and confirming the coverage you need before processing large numbers of samples.

Requirement	Value	How to check
Quantity	>1 µg per sample, at a concentration of at least 20 ng/µl, so that 1 µg fits in the 50 µl g-TUBE input	Qubit dsDNA BR Assay, in triplicate
Purity	OD 260/280 ≥1.8 and OD 260/230 of 2.0–2.2	NanoDrop or equivalent
Fragment length	HMW gDNA Figure 1 shows a typical Puregene extraction.	Femto Pulse or equivalent (optional)

Figure 1: Example fragment length profile of gDNA extracted from human blood using the adapted Puregene method.

The g-TUBE shears DNA to a target length but cannot lengthen it. gDNA that is already shorter than expected after extraction will be shorter after shearing, and read length will be lower as a result.

How to QC your input DNA

It is important that the input DNA meets the quantity and quality requirements. Using too little or too much DNA, or DNA of poor quality (e.g. highly fragmented or containing RNA or chemical contaminants) can affect your library preparation.

For instructions on how to perform quality control of your DNA sample, please read the Input DNA/RNA QC protocol.

Chemical contaminants

Depending on how the DNA is extracted from the raw sample, certain chemical contaminants may remain in the purified DNA, which can affect library preparation efficiency and sequencing quality. Read more about contaminants on the Contaminants page of the Community.

We have validated and recommend the use of all the third-party reagents used in this protocol. Alternatives have not been tested by Oxford Nanopore Technologies.

For all third-party reagents, we recommend following the manufacturer's instructions to prepare the reagents for use, unless specified in this protocol.

We highly recommend that you check the number of pores in your flow cell prior to starting a sequencing experiment, within the warranty period. Flow cells should be removed from refrigeration and their packaging and allowed to come to room temperature for 30 minutes before they are used.

To perform the flow cell check, please follow the instructions in the Flow Cell Check document. As part of your flow cell check, you will see the number of pores in your new flow cell. The warranty on your flow cell covers a minimum pore count of 5,000 pores for a PromethION Flow Cell. You can find more information about the warranty period, stability and storage conditions of flow cells on the Oxford Nanopore Store. If you have any concerns or questions, please contact Oxford Nanopore.

Oxford Nanopore will replace any unused PromethION Flow Cell with fewer than 5,000 pores, when the result is reported within two days of performing the flow cell check, and when the storage recommendations have been followed.

A recommended protocol for gDNA extraction from blood is provided below:

Genomic DNA extraction from human blood using the Qiagen Puregene kit

The sequencing device control, data acquisition and real-time basecalling are carried out by MinKNOW.

Refer to the PromethION 24 or PromethION 2 Integrated documentation for detailed instructions on setting up the device and the sequencing run. The same run settings are used on both devices.

Before starting the run, ensure that:

• The reference FASTA file for your panel (see Reference genome in section 4) and the enrichment BED file are available on the device.

• You have enough storage space on the device for each flow cell.

• You have decided whether to switch On Basecall on-target reads only, as described below.

We recommend basecalling in real-time with the high accuracy (HAC) model, with BAM as the output format. The Basecall on-target reads only setting in MinKNOW decides which reads are basecalled during the run. The right choice depends on whether you need the reads that Adaptive Sampling rejects.

Basecall on-target reads only	Reads basecalled during the run	Flow cells at once
Off	All reads, including the short reads rejected by Adaptive Sampling. The rejected reads give a low-pass view of the whole genome and its methylation alongside the targets.	Fewer, as every read is basecalled
On	On-target reads only. Rejected reads are written to a pod5skip folder in the run folder and can be basecalled after the run if they are needed.	All device positions

The number of flow cells each device can basecall live, with and without Basecall on-target reads only, is given in the Device limits section of the Adaptive Sampling technical guide. If you run more flow cells than your device can basecall live, basecalling falls behind sequencing and enrichment may be reduced.

To run more flow cells at once and still keep the off-target data, switch Basecall on-target reads only On and basecall the rejected reads after the run. This takes additional time on the device, once sequencing has finished. Instructions are given in Basecalling rejected reads after the run, in the Data outputs and analysis section below.

Setting up your sequencing run in MinKNOW

1. In MinKNOW, select Start sequencing, then enter the flow cell position, experiment name and a sample ID.
   The sample ID applies to the whole flow cell, not to each sample; the three samples are identified by their barcode numbers (for example, barcode01, barcode02 and barcode03) in the output folders and files. Record which sample has which barcode.
   To name each sample instead, start from a sample sheet, as described below in Optional: Starting from a sample sheet.

2. Apply the settings below. Leave all other settings at their defaults.

Screen	Setting	Set to
Kit	Kit selection	Native Barcoding Kit 24 V14 (SQK-NBD114.24) or Native Barcoding Kit 96 V14 (SQK-NBD114.96)
Run configuration	Modified bases	On, with 5mC and 5hmC CG contexts selected
	Alignment	On. Upload the reference FASTA file for your panel: GIAB v3 for the Hereditary Cancer Panel, or the file for your build for a custom panel (refer to Reference genome in section 4).
	Adaptive sampling	On, with Enrich selected. Upload the enrichment BED file (*_enrichment.bed) and the same reference FASTA file.
	Basecall on-target reads only	Off or On, as described above
Output	FASTQ	Off
	POD5	Off, or On if you plan to basecall the rejected reads after the run

3. Start the run.

Starting from a sample sheet allows you to give each of the three samples its own name, which is carried through to the output folders and files in place of the barcode number. Use the same run settings provided in the Table above.

• Prepare a CSV file with one row per barcode. It needs the following columns:

  • experiment_id (your experiment name, the same in every row)
  • kit (SQK-NBD114.24)
  • barcode (for example barcode01)
  • alias (the sample name for that barcode)
    Sample names in the alias column can contain only letters, numbers, hyphens, underscores and full stops, with no spaces, and must be 1–40 characters long.
  • either position_id (the slot on the device)
  • or flow_cell_id (the ID printed on the flow cell)

• Save the file with a visible .csv extension, or MinKNOW will not recognise it.

• In MinKNOW, select Start from a sample sheet in place of Start sequencing, and select your CSV file. The flow cell position, experiment name and sample names are read from the file, so you do not need to enter them on screen. Then apply the settings provided in the Table above.

• Further sample sheet options are described in the sample sheet section of the MinKNOW documentation.

At the end of the run, the data for each of the three samples is in its own barcode folder. Each BAM file contains basecalled reads aligned to the reference FASTA file uploaded in MinKNOW. Modified base calls (5mC and 5hmC in CpG context) are stored in the read records only if modified base calling was turned On, when the run was set up.

With Basecall on-target reads only switched Off, the BAM files also contain the short reads rejected by Adaptive Sampling. With it switched On, rejected reads are not basecalled and are written to the pod5skip folder.

Output	Description
Aligned BAM files, one folder per barcode	Basecalled, aligned reads for each sample, with modified base calls if they were turned On.
Sequencing summary and run report	Run-level metrics, including read length, output and Adaptive Sampling decisions.

If Basecall on-target reads only was switched On, the reads rejected by Adaptive Sampling are written to the pod5skip folder in the run folder. They can only be basecalled if POD5 output was switched On when the run was set up. Wait until the sequencing run has finished before basecalling them, as both processes compete for the compute on the device. Use the same basecalling model, modified base setting, reference FASTA file and barcode kit as the run, so that the rejected reads can be analysed alongside the BAM files from the run.

In the EPI2ME Desktop App, use the wf-basecalling workflow with the pod5skip folder as input, the HAC model and 5mC and 5hmC modified base model used for the run, the reference FASTA file, barcode kit SQK-NBD114.24 (or SQK-NBD114.96) and BAM output. The workflow writes aligned BAM files for each barcode.

On the command line, use the standalone Dorado software in two steps.
First basecall, align and identify the barcodes, replacing the file names with your own:

dorado basecaller hac,5mCG_5hmCG pod5skip/ --recursive --reference reference.fasta --kit-name SQK-NBD114.24 > rejected.bam 

Then split the reads by barcode, keeping the alignment:

dorado demux --output-dir rejected_by_barcode --no-classify --no-trim --sort-bam rejected.bam 

The --no-trim option is needed because dorado demux removes the alignment when it trims barcodes; the barcodes have already been trimmed during basecalling.
The --sort-bam option sorts and indexes the files for each barcode, and --recursive reads any sub-folders of the pod5skip folder.
The hac model name selects the current HAC model, which may be newer than the model used during the run; for an exact match, use the full model name shown in the run report.

Use *_analysis.bed, not *_enrichment.bed, to calculate coverage over your targets and to restrict variant calling to them. If coverage is calculated over the enrichment BED file, the result includes the buffer and no longer describes your targets. Use *_exons.bed where coverage is reported per exon.

For custom germline panels, variant calling, phasing and methylation analysis can be performed per sample with the wf-human-variation workflow in the EPI2ME Desktop App or on the command line, supplying the BAM files for one barcode, the reference FASTA file and the analysis BED file.

For the Hereditary Cancer Panel, use the wf-hereditary-cancer workflow.

Due to the extended sequencing time, we do not recommend reusing the flow cells used in this method.

Reusing these flow cells for subsequent sequencing experiments may result in insufficient data generation for analysis.

Below is a list of the most commonly encountered issues, with some suggested causes and solutions.

We also have an FAQ section available on the Nanopore Community Support section.

If you have tried our suggested solutions and the issue persists, please contact Technical Support via email (support@nanoporetech.com) or via LiveChat in the Nanopore Community.

Low sample quality

Observation	Possible cause	Comments and actions
Low DNA purity (Nanodrop reading for DNA OD 260/280 is <1.8 and OD 260/230 is <2.0–2.2)	The DNA extraction method does not provide the required purity	The effects of contaminants are shown in the Contaminants know-how piece. Please try an alternative extraction method that does not result in contaminant carryover. Consider performing an additional AMPure bead clean-up step.

Low DNA recovery after AMPure bead clean-up

Observation	Possible cause	Comments and actions
Low recovery	DNA loss due to a lower than intended AMPure beads-to-sample ratio	1. AMPure beads settle quickly, so ensure they are well resuspended before adding them to the sample. 2. When the AMPure beads-to-sample ratio is lower than 0.4:1, DNA fragments of any size will be lost during the clean-up.
Low recovery	DNA fragments are shorter than expected	The lower the AMPure beads-to-sample ratio, the more stringent the selection against short fragments. Please always determine the input DNA length on an agarose gel (or other gel electrophoresis methods) and then calculate the appropriate amount of AMPure beads to use.
Low recovery after end-prep	The wash step used ethanol <70%	DNA will be eluted from the beads when using ethanol <70%. Make sure to use the correct percentage.

Below is a list of the most commonly encountered issues, with some suggested causes and solutions.

We also have an FAQ section available on the Nanopore Community Support section.

If you have tried our suggested solutions and the issue still persists, please contact Technical Support via email (support@nanoporetech.com) or via LiveChat in the Nanopore Community.

Fewer pores at the start of sequencing than after Flow Cell Check

Observation	Possible cause	Comments and actions
MinKNOW reported a lower number of pores at the start of sequencing than the number reported by the Flow Cell Check	An air bubble was introduced into the nanopore array	After the Flow Cell Check it is essential to remove any air bubbles near the priming port before priming the flow cell. If not removed, the air bubble can travel to the nanopore array and irreversibly damage the nanopores that have been exposed to air. The best practice to prevent this from happening is demonstrated in this video how to load a PromethION Flow Cell.
MinKNOW reported a lower number of pores at the start of sequencing than the number reported by the Flow Cell Check	The flow cell is not correctly inserted into the device	Stop the sequencing run, remove the flow cell from the sequencing device and insert it again, checking that the flow cell is firmly seated in the device and that it has reached the target temperature. If applicable, try a different position on the device.
MinKNOW reported a lower number of pores at the start of sequencing than the number reported by the Flow Cell Check	Contaminations in the library damaged or blocked the pores	The pore count during the Flow Cell Check is performed using the QC DNA molecules present in the flow cell storage buffer. At the start of sequencing, the library itself is used to estimate the number of active pores. Because of this, variability of about 10% in the number of pores is expected. A significantly lower pore count reported at the start of sequencing can be due to contaminants in the library that have damaged the membranes or blocked the pores. Alternative DNA extraction or purification methods may be needed to improve the purity of the input material. The effects of contaminants are shown in the Contaminants know-how piece. Please try an alternative extraction method that does not result in contaminant carryover.

MinKNOW script failed

Observation	Possible cause	Comments and actions
MinKNOW shows "Script failed"		Restart the computer and then restart MinKNOW. If the issue persists, please collect the MinKNOW log files and contact Technical Support. If you do not have another sequencing device available, we recommend storing the flow cell and the loaded library at 4°C and contact Technical Support for further storage guidance.

Pore occupancy below 40%

Observation	Possible cause	Comments and actions
Pore occupancy <40%	Not enough library was loaded on the flow cell	For the human genome sequencing protocols, 250-300 ng of good quality library should be loaded on to an R10.4.1 flow cell to keep pore occupancy high.
Pore occupancy close to 0	Ethanol was used instead of LFB or SFB at the wash step after sequencing adapter ligation	Ethanol can denature the motor protein on the sequencing adapters. Make sure the LFB or SFB buffer was used after ligation of sequencing adapters.
Pore occupancy close to 0	No tether on the flow cell	Tethers are added during flow cell priming (FCT tube). Make sure FCT was added to FCF before priming.

Shorter than expected read length

Observation	Possible cause	Comments and actions
Shorter than expected read length	Unwanted fragmentation of DNA sample	Read length reflects input DNA fragment length. Input DNA can be fragmented during extraction and library prep. 1. Please review the extraction methods in the Nanopore Community for best practice for extraction. 2. Visualise the input DNA fragment length distribution on an agarose gel before proceeding to the library prep. In the image above, Sample 1 is of high molecular weight, whereas Sample 2 has been fragmented. 3. During library prep, avoid pipetting and vortexing when mixing reagents. Flicking or inverting the tube is sufficient.

Large proportion of unavailable pores

Observation	Possible cause	Comments and actions
Large proportion of unavailable pores (shown as blue in the channels panel and pore activity plot) The pore activity plot above shows an increasing proportion of "unavailable" pores over time.	Contaminants are present in the sample	Some contaminants can be cleared from the pores by the unblocking function built into MinKNOW. If this is successful, the pore status will change to "sequencing pore". If the portion of unavailable pores stays large or increases: A nuclease flush using the Flow Cell Wash Kit (EXP-WSH004) can be performed.

Large proportion of inactive pores

Observation	Possible cause	Comments and actions
Large proportion of inactive/unavailable pores (shown as light blue in the channels panel and pore activity plot. Pores or membranes are irreversibly damaged)	Air bubbles have been introduced into the flow cell	Air bubbles introduced through flow cell priming and library loading can irreversibly damage the pores. Watch the how to load a PromethION Flow Cell video for best practice.
Large proportion of inactive/unavailable pores	Certain compounds co-purified with DNA	Known compounds, include polysaccharides. Clean-up using the QIAGEN PowerClean Pro kit.
Large proportion of inactive/unavailable pores	Contaminants are present in the sample	The effects of contaminants are shown in the Contaminants know-how piece. Please try an alternative extraction method that does not result in contaminant carryover.

Temperature fluctuation

Observation	Possible cause	Comments and actions
Temperature fluctuation	The flow cell has lost contact with the device	Check that there is a heat pad covering the metal plate on the back of the flow cell. Re-insert the flow cell and press it down to make sure the connector pins are firmly in contact with the device. If the problem persists, please contact Technical Services.

Failed to reach target temperature

Observation	Possible cause	Comments and actions
MinKNOW shows "Failed to reach target temperature"	The instrument was placed in a location that is colder than normal room temperature, or a location with poor ventilation (which leads to the flow cells overheating)	MinKNOW has a default timeframe for the flow cell to reach the target temperature. Once the timeframe is exceeded, an error message will appear and the sequencing experiment will continue. However, sequencing at an incorrect temperature may lead to a decrease in throughput and lower q-scores. Please adjust the location of the sequencing device to ensure that it is placed at room temperature with good ventilation, then re-start the process in MinKNOW.