Overcoming Challenges in NGS Target Enrichment

Contributed Commentary by Steven Henck, PhD, Vice President, R&D at Integrated DNA Technologies

May 9, 2022 | The advancement of next generation sequencing (NGS) technologies has represented a large step forward in the speed and throughput of sequencing capabilities and make it more affordable to sequence an entire genome. While NGS has dramatically lowered the cost of sequencing a sample, it can still be relatively costly to sequence an entire genome if you are only interested in a small portion of it. For these situations, target enrichment can be used to selectively sequence regions of interest. This allows for greater depth of sequencing, or the sequencing of more samples, while minimizing costs.

Although there are a number of ways to enrich for sequences of interest, there are two main methods which are commonly used to achieve target enrichment: amplicon-based and hybrid capture-based enrichment. Amplicon-based enrichment uses a panel of PCR primers to amplify the region of interest, which is then purified and sequenced. Hybrid capture enrichment uses a panel of hybridizing probes to pull down the regions of interest for sequencing while unbound DNA fragments are washed away.

Like any molecular biology approach, target enrichment comes with its own set of challenges. Here are some tips to help you navigate them.

Get Your Panels Right

It is worth the investment in time to make sure that your primers or hybridization probes will selectively enrich your regions of interest before starting. For amplicon-based enrichment, primer design is paramount as they can be ineffective at priming if there is too much sequence variation under the primers or the primers form dimers. Consider using available design tools or even a design service to simplify the panel design process.

Use Hybrid Capture for Large, Variable, or Novel Targets

Larger regions of interest require more primers, which raises the possibility of primers binding to each other and creating primer dimers, making amplicon-based enrichment challenging. However, hybrid capture probes do not produce unwanted sequences when they interact, making this approach ideal for larger regions of interest.

Another advantage of the hybrid capture approach is that it requires less knowledge about the regions of interest. Outside of the hybridization sequence, the target sequence does not need to be known. That’s why hybrid capture is especially useful when you’re sequencing samples where the sequences are not entirely known or could contain complex or large numbers of variations or mutations.

One application that leverages hybrid capture’s capabilities is cancer biomarker discovery. In addition to point mutations, oncogenes can form when different genes fuse together at DNA breakpoints. These difficult-to-sequence fusion genes can alter the expression, activity, or function of the genes, making them oncogenic. There could be breaks in the DNA, and one piece of DNA ends up being fused and connected to another piece of DNA, which you don't necessarily know about. But with hybrid capture, as long as you capture that first piece, you'll be able to sequence across that fusion junction and detect that gene fusion mutation.

Overlap Primers for Targets with Variation

While hybrid capture enrichment is useful for regions of interest that contain variations, amplicon-based enrichment is still possible for these regions. One example where modifications have made amplicon-based enrichment a success is the sequencing of SARS-CoV-2 variants. This has proven challenging for some traditional amplicon-based approaches to SARS-CoV-2 sequencing since primers designed for the original viral strain have had trouble amplifying and detecting the Delta and Omicron mutants. However, the use of primers paired with overlapping coverages can help to maintain effectiveness and allow for sequencing of new variants without gaps or dropouts.

Ensure the Right Normalization

Sequencing runs are expensive. Costs start to climb if it is necessary to achieve a minimum depth of sequence coverage as areas of high representation will be over-sequenced to ensure that areas of low representation achieve the minimum depth. To prevent this, get the normalization right. Some people have turned to approaches like a test-run on a small desktop sequencer with much lower run costs, quantitation of each library by mass, or enzymatic quantitation by molarity. Using these approaches to normalize your target enrichment pools can cost significantly less than over-sequencing, which can waste thousands of dollars.

Target enrichment is a useful tool for streamlining NGS by focusing on regions of interest and cutting away the clutter of sequencing areas of the genome which may not be of interest. This allows for more samples to be sequenced at greater depth and, with these tips, can be used to sequence highly variable or unknown regions. This gives the researcher a lot of flexibility in planning an approach that can speed up their sequencing projects by providing the results they are interested in from more samples. These benefits have made target enrichment impactful for many crucial research areas, from fighting the pandemic to detecting oncogenic mutations, and the number of applications are sure to grow in the coming years.

Steven Henck, PhD, is Vice President of R&D at Integrated DNA Technologies, a global genomics solutions provider helping to accelerate scientific breakthroughs. IDT has developed proprietary technologies for genomics applications such as next generation sequencing, CRISPR genome editing, synthetic biology, digital PCR, and RNA interference. Email Henck at shenck@idtdna.com.