This protocol describes an end-to-end process to prepare, sequence gDNA from cultured cells samples and analyse using the “Human variant workflow” in Epi2Me. The identification of structural variants (SVs) and single nucleotide variants (SNVs) play a pivotal role in our understanding of genetic diversity, disease mechanisms, and evolutionary biology1,2. The protocol aims to produce libraries with a read N50 ~30 kb and generate ~30-40x coverage of the genome, to provide robust calling of small and large variants as well as provide methylation and phasing information.

Briefly, genomic DNA is extracted from 5 million cultured cells, and is extracted 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), and libraries prepared with the Ligation Sequencing Kit V14 (SQK-LSK114).
Libraries are sequenced on PromethION and we detail instructions for washing and reloading the flow cell twice to maximise data output using the Flow Cell Wash Kit (EXP-WSH004) and Sequencing Auxiliary Vials V14 (EXP-AUX003). Data is basecalled and aligned by MinKNOW and the aligned BAM output data is analysed using the wf-human-variation workflow which uses Sniffles2, Clair3 and modbam2bed software to call structural variants (SVs), single nucleotide polymorphisms (SNPs) and for reporting DNA methylation.

†Note: Users who do not have access to the Megaruptor and wish to omit this step are likely to observe a drop in coverage from ~40x to ~30x.

Steps in the sequencing workflow:

Prepare for your experiment

You will need to:

• Extract your input sample (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 extraction method, extract the gDNA from your cells, 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

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	20 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 and convert it into basecalled reads.
• Analyse data using the wf-human-variation workflow.

For this end-to-end workflow, we recommend extracting high molecular weight gDNA from 5 x 10⁶ cells (e.g. cell culture or tissue sample) using the QIAGEN Puregene Cell Kit in the Sample Preparation step.

Other extraction protocols are available but have not been tested by Oxford Nanopore Technologies.

DNA质控

选择符合质量和浓度要求的起始DNA至关重要的。使用过少或过多的DNA，或者质量较差的DNA（如，高度碎片化、含有RNA或化学污染物的DNA）都会影响文库制备。

有关如何对DNA样品进行质控，请参考起始DNA/RNA质控实验指南 。

化学污染物

从原始样本中提取DNA的方法不同，可能会导致经纯化的DNA中所残留的化学污染物不同。这会影响文库的制备效率和测序质量。请在牛津纳米孔社区的 Contaminants（污染物）页面 了解更多信息。

Oxford Nanopore Technologies推荐您使用本实验指南中提及的所有第三方试剂，并已对其加以验证。我们尚未对其它替代试剂进行测试。

我们建议您按制造商说明准备待用的第三方试剂.

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。

请注意： 我们正在将部分试剂的包装形式由单次管装改为瓶装。

单次管装试剂：

部分试剂改为瓶装：

声明： 本产品包含由贝克曼库尔特公司（Beckman Coulter, Inc）生产的 AMPure XP 试剂，并可与试剂盒一起于-20°C 下储存（试剂稳定性将不受损害）。

请注意： DNA参照（DCS）是一段可比对到Lambda基因组的3'端、长度为3.6 kb 的标准扩增子。

Overlay of fragment length profiles of a) gDNA extracted using the Puregene cell Kit, b) gDNA extracted and size selected using SFE buffer. c) gDNA extracted, size selected and fragmented using Megaruptor 3 (MR).

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.

Below you can find example data for pore states observed on a flow cell before and after wash steps are performed. Additionally, you can observe an example for the cummulative sequencing data output, including the wash and reload steps. The red asterisks indicate the flow cell wash and reloads.

Figure 1. Channel state over a 72 hour run. The flow cell washes are incorporated into the method to restore blocked pores, to allow continuous data acquisition. Red asterisks denote when a flush was performed.

Figure 2. Cumulative sequencing data output, over a 72 hour run. Red asterisks denote when a flush was performed.

Figure 3. Read length profile for a 30 kb N50 library. The approximately gaussian shape is characteristic of gDNA that has undergone SFE size selection and Megaruptor shearing. The short distribution of reads at ~5kb is due to premature termination of reads at the mux scan.

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

We recommend basecalling with the high accuracy (HAC) basecaller in real-time with BAM selected as output type using the P2 Solo or P24/P48 device.

You must generate a BAM file from your sequening run, as this is required for input into the wf-human-variation workflow.

Refer to the links below containing the detailed instructions for setting up the device and sequencing run:

• PromethION 24 and 48: "Starting a sequencing run with PromethION 24 and 48"

• PromethION 2 Solo: "Starting a sequencing run on PromethION 2 Solo"

Below are the recommended sequencing parameters for MinKNOW.

For inputs of 30 kb, we recommend increasing the run time to 100 hours to accommodate for the two flow cell washes, using the modified bases option for basecalling and ensuring a BAM output is selected. All other sequencing parameters can be kept to their default settings. 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 [default] Modified bases: On with '5mC & 5hmC CG contexts' selected Model: High-accuracy basecalling (HAC) [default]

Barcoding: Disabled [default]

Alignment: Off [default]
We do not currently recommend live alignment during sequencing, as it can slow down system processing.

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: 100 hours [default]

Output

Output format .POD5: On [default] .FASTQ: On [default] .BAM: On

Filtering: On [default] Qscore: 9 [default] Minimum read length: 200 bp [default]

For the analysis of human cell DNA sequence data, we recommend the wf-human-variation workflow. This end-to-end software pipeline is implemented using the Nextflow workflow language and implements methods for the calling of single nucleotide polymorphisms (SNPs), structural variants (SVs), and for reporting DNA methylation information.

The wf-human-variation workflow is best run from the BAM file produced by MinKNOW when the modified base model for basecalling is selected. If sequence read mapping to the reference genome is not performed by MinKNOW, we recommend to perform the basecalling using the wf-basecalling workflow. Ensure you save the outputs in BAM format by providing the --output_bam option.

The tools below are used in the analysis workflow and can be run in isolation or together:

1. Sniffles2 calls SVs and file output include an HTML report of QC metrics and VCF format list of variants and their quality scores.

2. Clair3 calls SNPs and file output includes an HTML report of QC metrics and VCF format list of variants and their quality scores.

3. modkit extracts methylation information from the provided BAM file which is summarised in a BEDmethyl format file.

The wf-human-variation workflow is preconfigured using appropriate parameters and requires tuning only for the choice of reference genome and Clair3 model. Please see the project’s documentation for further details.

The results from the wf-human-variation workflow can be further explored by viewing in a track-based genome browser such as IGV can be assessed for known pathogenicity through tertiary analysis software.

The wf-human-variation workflow is intended to be run using the Nextflow software.

We recommend performing downstream analysis using EPI2ME which facilitates bioinformatic analyses by allowing users to run Nextflow workflows in a Graphical User Interfaces (GUI). EPI2ME maintains a collection of bioinformatic workflows which are curated and actively maintained by experts in long-read sequence analysis. The collection of all our available EPI2ME workflows can be found here.

For new users, the quick start guide can be found here outlining how to use this interface.

The primary workflow outputs include:

• gzipped VCF file containing the SNPs in the dataset from --snp
• gzipped VCF file containing the SVs in the dataset from --sv
• gzipped bedMethyl file aggregating modified base counts from --mod
• HTML report detailing the primary findings of the workflow for QC metrics, and SNP and SV calling
• If an unaligned BAM file was provided, the workflow will ouput a CRAM file containing the alignments used to make the downstream variant calls.

The secondary workflow outputs:

• mosdepth ouputs include:
  • {sample_name}.mosdepth.global.dist.txt: a cumulative distribution indicating the proportion of total bases for each and all reference sequences
    
  • {sample_name}.regions.bed.gz: the mean coverage for each region in the provided BED file
    
  • {sample_name}.thresholds.bed.gz: the number of bases in each region that are covered at or above each threshold value (1, 10, 20, 30X)

• bamstats ouputs include:
  • {sample_name}.readstats.tsv.gz: a gzipped TSV summarising per-alignment statistics produced by bamstats
  • {sample_name}.ftagstat.tsv: a text file with summary alignment statistics for each reference sequence

It is possible to phase SNPs, SVs and modified bases by providing the --phased option.

To improve the accuracy of SV calling, specify a suitable tandem repeat BED for your reference with --tr_bed.

Aggregation of methylation calls with --mod requires data to be basecalled with a model that includes base modifications, providing the MM and ML BAM tags. To do so on MinKNOW, ensure 'Modified bases' option is selected during basecalling set up, with the '5mC' model selected.

Ensure to retain the input reference when basecalling or alignment is performed as CRAM files cannot be read without the corresponding input reference.

For a full list of available basecalling models, refer to the Dorado documentation.

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。