Q&A with the methylation analysis experts: your epigenomic questions answered
In a recent webinar, “Unlock liquid biopsy samples with NGS-based methylation detection from 10 ng DNA”, we discussed how to take your targeted methylation analysis to the next level using an NGS-based approach. The audience had some insightful questions! Our resident experts in epigenomics and gene expression analysis, Brian Dugan, Associate Director of Global Product Management, Genomics, and Dr. Ioanna Andreou, Associate Director of NGS Application Development, joined us for a Q&A session. Find the answers to your methylation analysis questions and get better insights into improving your methylation research workflow.
Missed the webinar? Watch it on-demand here.
What tools do you offer for custom panel design?
You can find easy-to-use design tools to suit your specific NGS needs at GeneGlobe. For example, if you’re looking to design a custom methyl panel, just go to “Customize Products”, click “Next-Generation Sequencing”, and then go to “QIAseq Targeted Methyl Custom Panels”. You’ll need to log in or quickly create a free QIAGEN.com account, and then you can start designing. Enter genomic coordinates into the designer, and the designer will work in the background and send you an email when your design is complete.
What is the maximum size for a custom QIAseq Targeted Methyl panel?
It is possible to multiplex up to 3000 primers in a custom-designed panel.
How complex is this approach compared to WGBS or hybrid capture?
Compared to WGBS workflows, the targeted approach has a similar easy reaction setup. The difference between these two workflows is that WGBS needs extended sequencing effort while the QIAseq approach allows you to sequence a region of interest at very high depth but extremely low sequencing costs.
Compared to hybrid capture procedures, the QIAseq approach is much simpler. Rather than requiring hybridization or centrifugation, QIAseq technology is based on single primer extension. The reaction can be easily done by hand or automated on a liquid handler.
Is shearing required for genomic DNA?
No, shearing is not needed for the QIAseq approach.
How is the amplification balanced to ensure uniformity across different regions of interest?
Multiple primers are designed to ensure coverage of all regions of interest. Remember, coverage is not only dependent on primer enrichment uniformity, but also on the quality of the starting material.
How uniform are the QIAseq Targeted Methyl Panels?
The primer design uniformly covers the CpG sites included in a region. The uniformity of enrichment is high. For example, 10 ng ccfDNA (circulating cell-free DNA) results in ~93% of primers with read numbers higher than 0.2 of the mean. Uniformity in-between different regions is affected by the quality of the sample and bisulfite treatment. That means if a region is not represent or is shortened, then the coverage will be affected.
ccfDNA samples usually require input amounts between 10-40 ng. However, for our samples, we are not able get 10ng DNA. Can we reduce the input to 1ng?
Yes, 1 ng will work and generate high quality libraries, as the QIAseq Targeted Methyl Panels are designed to handle very low starting amounts from liquid biopsy samples. But you always have to consider that reduction of the input amount will also reduce the UMI coverage.
Are UMIs (unique molecular indices) added pre-amplification? If so, how is bias prevented during the amplification process?
UMIs are added during the adapter ligation step to capture unique molecules. After that step, enrichment is performed. Library amplification is the last step of the library generation workflow. Amplification errors will be filtered during the analysis since these are the ones that will deliver singletons. The pre-built and integrated bioinformatics pipeline returns the UMI reads/Cytosine site, Strand reads/site, and Context Reads/site, which helps to identify sequencing errors or SNVs.
What is the minimum fragment size required for this protocol?
The minimum tested fragment size was that of ccfDNA, which is ~170 bp.
What is the smallest number of genes included in a custom targeted methyl panel?
Because of the need for sequencing base diversity, we recommend a minimum of 100 unique primers at the lowest panel size.
What is the recommended depth in sequencing?
The sequencing depth varies based on what level of sensitivity is required and the sample type being sequenced.
Can you use a bigger panel but only look at a subset of sites?
The primers are designed to cover 150-250 bp regions of the genome. There may be one or many CpG sites in those regions. If the primer is able to cover those regions, you will be able to analyze them. CLC gives you the ability to filter the results on a subset of sites, including longer regions or even single CpG sites.
Does the required amount of input DNA (as low as 1ng input DNA from cells and tissues, or 10ng from FFPE samples and liquid biopsies) refer to before bisulfite conversion or after bisulfite conversion?
The amounts refer to the DNA put into the bisulfite conversion reaction.
Do you have a pre-defined set of UMIs (unique molecular indices) or is it a random 12-mer UMI?
With the QIAseq Targeted Methyl UMI Design we can theoretically tag 65.500 molecules per primer.
When you are collapsing your reads, do you collapse only based on the UMI sequence or are you using the bisulfite-converted sequence as well? How do you deal with sequencing errors in the 12-mer UMI sequence?
The QIAGEN workflow collapses reads that: 1) Start at the same position based on the end of the read to which the UMI is ligated (i.e., Read2 for paired data), 2) Are from the same strand and 3) Have UMIs that differ by at most one mismatch.
What is the average coverage for each targeted region that you usually obtain with ccfDNA? How many reads are necessary to reach the plateau for a panel of 2000 regions for ccfDNA?
Using 10ng ccfDNA with the EpiTect Bisulfite and ~1400 primers, we produced ~480000 total reads and ~10300 CpG sites were covered. The average UMI read per CpG site was ~80 and there were 2 reads per UMI.
What are the controls for bisulfite treatment to ensure that a 100% conversion has occurred for the input DNA?
You can use the EpiTect Control DNA, which includes both 100% methylation and 0% methylation samples. In mammalian cells, cytosines in CHH and CHG contexts are typically unmethylated and will represent the degree of the bisulfite conversion efficiency in the individual samples.
How well will this method fare with repetitive regions of the genome - how long are your primers? What is the max amplicon size? Can you look at multiple CpGs with one target?
Typically, repetitive regions of the genome are difficult to capture. With single primer extension, however, it’s possible to target the region distal to a specific site of interest to cover it. In addition, our in-silico primer design can be adjusted to test the limits for coverage. This service is available through our Enterprise Genomics Solutions.
The library fragment size is driven by the random fragmentation during the bisulfite conversion, and ranges between 300 bp to 1000 bp for gDNA and FFPE samples with an average fragment size of 450 bp.
One primer can cover one or multiples CpG sites.
Can we use this approach for DNA extracted from stool, which contains PCR inhibitors?
This is for sure a very interesting application. Since the first step of the workflow – the bisulfite treatment – is a chemical treatment that works under high salt concentrations and extreme pH, we don’t expect it would be inhibited by inhibitors that affect enzymatic reactions. A column-based cleanup is also performed during the bisulfite conversion, so that the material applied to the targeted methyl reactions has undergone two rounds of purification, significantly reducing the levels of inhibitors. A possible inhibition of bisulfite conversion can be visualized by the methylation status of cytosine in CHH and CHG contexts, which is normally 0.7-1.4% in mammalian samples. This sample type has not been tested so far, but it would be interesting to see samples from cancer research analyzed using the QIAseq approach.
What would be the recommended input amount of gDNA extracted from human stool (oncology research applications) that has been cleaned with Agencourt RNAclean XP beads?
There are no specific recommendations for the input requirements after use of Agencourt beads. However, the recommended input range for EpiTect Bisulfite, which is the first step in the workflow, is 1-100 ng. If you are reliably able to apply 40-50+ ng of input DNA into the conversion, this should yield high quality results with maximal coverage.
Learn more about our epigenomic solutions here, and make your next methylation analysis a breeze with our QIAseq Targeted Methyl Panels and Custom Panels.
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