This protocol describes an end-to-end process to prepare and sequence gDNA for chromatin accessibility from cell samples, and basecall and analyse the data using the information outlined in our chromatin accessibility data and tool release on the EPI2ME page.

Chromatin Accessibility (CA) is a technique designed to infer the genomic landscape of open chromatin in isolated nuclei using DNA methylation tagging. The method employs the nonspecific adenine methyltransferase EcoGII which selectively methylates accessible adenine residues (A → 6mA) within the nuclei when supplied with the methyl group donor S-adenosylmethionine (SAM). Because 6mA is not a naturally occurring modification in the human genome, its incorporation serves as a proxy for identifying regions of open chromatin.

For more information, please see our chromatin accessibility know-how document.

Briefly, samples undergo 6mA conversion and DNA is extracted from the cell samples using the QIAGEN Puregene Cell Kit. DNA is size selected using the Short Fragment Eliminator Kit (EXP-SFE001) and then sheared with Megaruptor® 3 (Diagenode).
Note: Users who do not have access to the Megaruptor and wish to omit this step are likely to observe a drop in coverage.

The extracted DNA input is then prepared using our Ligation Sequencing Kit V14 (SQK-LSK114) and sequenced on a PromethION device. Detailed instructions for setting up the sequencing run on MinKNOW, washing and reloading the flow cell and downstream analysis are also included for a complete end-to-end protocol.

Your sequencing data is basecalled post-sequencing run using the Dorado basecaller. Downstream analysis is then performed via command line using Modkit.

Steps in the workflow

Prepare for your experiment

You will need to:

• Harvest your cultured lymphoblast cells
• 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

Sample preparation

Using the outlined method, perform 6mA conversion and extract the gDNA from your cell samples. Then perform size selection using the Short Fragment Eliminator Kit (EXP-SFE001), and fragment your gDNA using the Megaruptor.

Check the length, quantity and purity of your extracted material. The quality checks performed during the protocol are essential in ensuring experimental success.

Library preparation and sequencing

The table below is an overview of the steps required in the library preparation, including timings and optional stopping points.

Library preparation	Process	Time	Stop option
DNA repair and end-prep	Repair and prepare the DNA ends for adapter attachment	35 minutes	4°C overnight
Adapter ligation and clean-up	Attach the sequencing adapters to the DNA ends	55 minutes	4°C short-term storage or for repeated use, such as re-loading your flow cell -80°C for single-use, long-term storage. We strongly recommend sequencing your library as soon as it is adapted.
Priming and loading the flow cell	Prime the flow cell and load the prepared library for sequencing	5 minutes
Washing and reloading the flow cell (x2)	Pause your sequencing run. Wash your flow cell with nuclease to remove the previous library load and unblock pores. Prime the flow cell and reload the prepared library to continue sequencing	60 minutes (x2)

Sequencing and analysis

You will need to:

• Start a sequencing run using the MinKNOW software which will collect raw data from the device.
• Basecall your sequencing reads using the Dorado basecaller.
• Analyse your data using Modkit.
• (Optional) Alternatively, external tools can be used to further analyse and explore your data.

Input requirements per sample for the extraction method:

• ≥ 2 million freshly cultured lymphoblast cells

Input requirements per sample for the library preparation:

• 3 µg of SFE size selected and Megaruptor fragmented gDNA

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.

We highly recommend that you check the number of pores in your flow cell prior to starting a sequencing experiment. This should be done within 12 weeks of purchasing for MinION/GridION/PromethION or within four weeks of purchasing Flongle Flow Cells. Oxford Nanopore Technologies will replace any flow cell with fewer than the number of pores in the table below, when the result is reported within two days of performing the flow cell check, and when the storage recommendations have been followed. To do the flow cell check, please follow the instructions in the Flow Cell Check document.

Flow cell	Minimum number of active pores covered by warranty
Flongle Flow Cell	50
MinION/GridION Flow Cell	800
PromethION Flow Cell	5000

Note: We are in the process of reformatting our kits with single-use tubes into a bottle format.

Single-use tubes format:

Bottle format:

Note: This Product Contains AMPure XP Reagent Manufactured by Beckman Coulter, Inc. and can be stored at -20°C with the kit without detriment to reagent stability.

Note: The DNA Control Sample (DCS) is a 3.6 kb standard amplicon mapping the 3' end of the Lambda genome.

If sample recovery is >3 μg:

Proceed to gDNA Fragmentation using the Megaruptor.

For this method, the flow cell is washed after ~22 hours of sequencing to restore pores to ensure efficient data acquisition. After an additional 22 hours of sequencing, the flow cell is washed and reloaded a second time. For this reason, enough library was generated for 3 flow cell loads in the adapter ligation step of the protocol.

• This washing procedure aims to remove most of the initial library and unblock the pores to prepare the flow cell for the loading of a subsequent library.
• Data acquisition in MinKNOW should be paused during the wash procedure and library loading.
• After the flow cell has been washed, the next library can be loaded.

You can navigate to the Pore Activity or the Pore Scan Results plot to see pore availability.

A representative read length distribution, along with Pore Activity and Pore Scan reports on for Chromatin Accessibility library are shown below — captured on a flow cell before and after wash steps. Additionally, an example of the cumulative sequencing data output, including data from wash and reload steps, is also provided.

Figure 1. Typical Read length distribution for a Chromatin Accessibility library.

Figure 2. Pore Activity Report. The Chromatin Accessibility protocol is optimised to maintain a high pore occupancy during sequencing, represented by the high ratio of pore sequencing (light green) to pore available to sequence (dark green). Red asterisks denote when a flush was performed.

Figure 3. Pore Scan Report. Expected pore scan results for channels over a 72-hour run of Chromatin Accessibility. Following wash steps, a significant number of previously unavailable pores are expected to be recovered. Red asterisks denote when a flush was performed.

Figure 4. Cumulative sequence data output of Chromatin Accessibility, over 72 hours run. Red asterisks denote when a flush was performed.

This video will show you how to wash a flow cell after a sequencing run and how to load a new library.

The sequencing device control and data acquisition are carried out by the MinKNOW software. Please ensure MinKNOW is installed on your computer or device. Further instructions for setting up a sequencing run can be found in the MinKNOW protocol.

We recommend setting up your sequencing run using the recommendations outlined below. All other parameters can be left to their default settings.

Basecalling of sequencing data will be performed post-sequencing using the Dorado basecaller.

To produce MinKNOW sequencing metrics during your sequencing run, you should use the Fast basecalling model. Please note, this is only used for the sequencing metrics and all data generated will need to be re-basecalled after sequencing.

We recommend setting the run time to 100 hours to accommodate for the two flow cell washes. Below are our current recommendations:

Positions

Flow cell position: [user defined]

Experiment name: [user defined]

Flow cell type: FLO-PRO114M

Sample ID: [user defined]

Kit

Kit selection: Ligation Sequencing Kit (SQK-LSK114)

Run configuration

Sequencing and analysis

Basecalling: On
Modified bases: Off [default]
Model: Fast basecalling (for sequencing metrics)

Barcoding: Disabled [default]

Alignment: Off [default]

Adaptive sampling: Off [default]

Advanced options
Active channel selection: On [default]
Time between pore scans: 1.5 [default]
Reserve pores: On [default]

Data targets

Run limit: Stop run when sequencing reaches 100 hours [default]

Output

Output format .BAM: Off
.FASTQ: Off
Raw reads: On [default]
.POD5: On [default]

Filtering: On [default]
Qscore: 8 [default]
Minimum read length: 200 bp [default]

Chromatin accessibility data can be processed and analysed using the tools outlined in the chromatin accessibility data and tool release page.

Note: To ensure the compute on your device can keep up with the requirements for sequencing and/or analysis, we strongly recommend against running both processes at the same time.

The script outlined below runs Oxford Nanopore’s Dorado basecaller on the sequencing reads generated from your chromatin accessibility library. Please ensure you use Dorado v1.0.0 software or newer.

The script requires Dorado to be installed and the location available in the command line path.

Basecalling your sequencing reads doesn’t require any special settings; simply using Dorado with the v5.2 models and 6mA models will suffice. Detecting 5hmC/5mC concurrently is optional, but recommended, below is an example command to detect 6mA at all sequence contexts and 5hmC/5mC at CpG dinucleotides.

dorado version 1.0:

$ dorado basecaller hac,5mCG_5hmCG,6mA raw/pod5 --reference ${genome_fasta} > basecalls.bam

Predict accessible regions with Modkit

As of version 0.5.0, Modkit contains a command to predict regions of open chromatin and produce a BedGraph file that can be visualized on commonly used browsers. For additional details see the online Modkit documentation. We plan to continue to add functionality to the Modkit open-chromatin suite of tools.

predict regions of open chromatin with Modkit

$ modkit open-chromatin predict \
  basecalls/PAY82297/calls.sorted.bam \
  --region "chr19" \ # optional
  -o chr19_open_chromatin.bedgraph \
  --device 0 \
  --model dist_modkit_v0.5.0_5120ef7_tch/models/r1041_e82_400bps_hac_v5.2.0@v0.1.0

As you may notice by the --device 0 option, this is the first machine learning model in Modkit and it will take advantage of a GPU if you have one available. The GPU resources required for this command are modest and the model can be run on a CPU as well (--device cpu ). In the two IGV screen shots below, one of the HLA-C locus and one of the ZNF locus we can see the similarity of the the 6mA enrichment between the two runs. In both images, the top track is the output of modkit open-chromatin predict which predicted probability of the chromatin being accessible.

Enrichment of 6mA around HLA-C, two runs are broadly very similar.

Enrichment of 6mA is evident around TSS at the ZNF locus.

Quantifying 6mA enrichment

One of the project aims was to develop a protocol that achieves high “signal over background”, meaning 6mA is enriched in regions of open chromatin and regions of heterochromatin have low 6mA levels. We can get an estimate of this measure by using modkit localize in regions where we expect chromatin to be accessible to the methyltransferase, such as house keeping gene promoters, shown below.

Elevated levels of 6mA are observed in promoter regions.

Relative 6mA enrichment levels are reproducible across preparations

Methods that use enzymatic treatment will almost always come with some amount of variability due to changes in reagents, measurement error, etc. Above we see both runs have similar but not identical peak 6mA levels. At a finer resolution, below we show that there is a strong correspondence between the 6mA levels between samples at ATAC-seq peaks.

6mA levels at ATAC peaks show good correlation between replicates.

Accurate endogenous methylation calls maintained with chromatin accessibility protocol

One important utility of this method is that endogenous 5mC/5hmC methylation detection performance is preserved, making it possible to observe concurrent changes in regulation due to DNA methylation as well as chromatin accessibility. Below we show the CpG methylation frequency for two matched samples, one with the chromatin accessibility methyltransferase treatment and one prepared using the typical human variation workflow.

Chromatin accessibility protocol does not change reporting of CpG methylation.

Read-level accuracy is maintained through MTase treatment

Finally, with the v5.2 High-Accuracy basecalling models, there is little to no difference in basecalling accuracy when a sample is subjected to the chromatin accessibility protocol.

Identity Q for the released samples, filtered to reads >= 5000kb.

Similarly we have not observed a change in variant calling performance with Clair3 on these samples, results summarized below:

Name	Flow cell ID	Median Accuracy (Q)	Mean Accuracy (Q)	CA-treatment	Mean Coverage	SNP F1 Score, %, 30X	Indel F1 Score, no_HPs, %, 30X
Chromatin Accessibility Replicate 1	PBA15156	19.99	19.82	+	34.11	99.14	97.69
Chromatin Accessibility Replicate 2	PAY22766	20.25	20.39	+	35.0	99.15	97.7
Native Sample	PBA15131	20.40	19.83	-	48.56	99.15	97.82

Raw nanopore data in POD5 format as well as basecalled modBAMs with 5-hydroxymethylcytosine (5hmC), 5mC, and 6mA base modification calls are available for download from a public Amazon Web Services S3 bucket.

The data is located in the bucket at:

s3://ont-open-data/chrom_acc_2025.06

These datasets can be used as a reference to compare your experiments to as well as general exploration and testing.

See the tutorials page for information on downloading the dataset.

Due to the extended sequencing time, and the multiple flow cell washes and library reloads, we do not recommend re-using the flow cells used in this method.

Re-using these flow cells for subsequent sequencing experiments may result in insufficient data generation for analysis.

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.

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.