Tips on Keeping NGS Costs Down

Next-generation sequencing (NGS) has become increasingly accessible as its costs steadily decline, but it remains an expensive tool when used often. While individual scientists can’t change the basic price tag, there is plenty they can do in their own labs to save on overall NGS costs. Here are some expert tips on keeping NGS costs down.

1. Sample quality control

It makes sense that ultimately your results will never be higher in quality than your original starting material, so start with the highest quality sample possible. Though often said, it bears repeating: garbage in means garbage out. Next, choose the extraction method best suited to it. “One of the easiest ways to reduce costs begins with sample extraction,” says Adam Blatter, Product Manager at Promega. “Ensuring highly pure and abundant nucleic acid for downstream analysis is accomplished through deploying sample purification methods specific to the sample type and nucleic acid of interest.”

Quality control for samples is important because this directly impacts the quality of NGS libraries. “Knowing the quality of the sample input into the library-preparation workflows can allow the researcher to adjust the workflow to accommodate samples of different quality,” says Dustin Masser, a Field Application Scientist for Roche Sequencing & Life Science. “Researchers working with low-quality samples might observe variable library quality or complete library-preparation failures if sample quality is not properly assessed and taken into account.” Needless to say, this will increase NGS costs because you might need to obtain new samples, make new libraries, and/or re-run sequencing.

Blatter notes that the enzymatic reactions that occur during library preparation are sensitive to the quantity and quality of the sample used. Thus, quantifying the sample (by qPCR, fluorometry, or electrophoresis) is an important step, especially for challenging samples such as fixed tissue, contaminated, or low-abundance samples. “Assays such as the ProNex^® DNA QC Assay can not only determine precise and accurate quantity, but also produce a quantitative measure of degradation or contamination levels that can be correlated to downstream performance,” says Blatter.

2. Choose the correct library-prep method

Roche believes that the easiest way to reduce NGS costs is to choose the right library-preparation method for the intended downstream sequencing application. “For example, if I’m only interested in variant calling within coding regions of the genome, I may want to choose a sample-preparation method like Hybrid Capture target enrichment that enriches for my regions of interest prior to sequencing,” says Masser. “Enriching for and sequencing only my regions of interest requires less sequencing per sample, allowing for more samples per flow cell used for a sequencing run, ultimately maximizing the data generated and lowering the overall cost per sample.” This strategy is less costly than whole genome sequencing, which requires significantly more sequencing per sample.

Once you’ve chosen the best approach, a library-prep kit can help reduce costs. “Choosing a fast, reliable library-prep method to prepare similar sample types will reduce hands-on time as well as the need to repeat failed samples,” says Amanda Hoppers, Field Application Scientist for NGS at New England Biolab. “Once a robust method is in place, it can free up personnel and equipment for more complicated NGS strategies that require substantial hands-on effort but offer a higher return on investment.”

Hoppers suggests looking for library prep kits that save time by combining or eliminating steps. “For example, the NEBNext^® Ultra™ II FS DNA Library Prep Kit combines enzymatic shearing of DNA, dA-tailing, end-repair, and 5’-phosphorylation, all in one step, removing the need for costly and time-consuming mechanical shearing in most cases,” she says. “A PCR-free version of this kit, which obviates the need for library amplification, can save yet more time.”

3. Library QC and pooling

Besides sample QC, library QC and library pooling are additional, important measures that can—when implemented properly—help to keep NGS costs down. “Sample QC, library QC, and library pooling can be difficult cost-reducing methods to adhere to because they can be laborious, and come with their own expense,” says Masser. However, they are also instrumental to maximizing sequencing output. “Improper pooling of your sample library can produce a sequencing run with variable (unbalanced) sequence read coverage per sample, requiring downsampling of reads bioinformatically during analysis and wasted sequencing reads,” he says. Thus QC measures reduce NGS costs by helping to ensure that you only sequence high-quality libraries.

Quantifying an NGS library is a critical step prior to pooling and sequencing, and is accomplished using qPCR, fluorometry, or electrophoresis methods. “Accurately controlling the amounts of library at this step will positively affect sequencing coverage depth, sample uniformity, and flow cell clustering,” says Blatter, suggesting Promega’s qPCR-based kit, the ProNex^® NGS Library Quant Kit for Illumina sequencing.

4. Understand sequencing quality metrics

Optimize your NGS workflow by understanding the metrics of sequencing quality and data analysis, which can help to improve data quality. “Poor sequencing quality metrics will reduce the overall usable data from sequencing runs, meaning additional costly sequencing is required,” says Masser. “Understanding the data analysis metrics helps researchers identify the best reagents and workflows to generate the highest quality data to answer experimental questions.”

5. Don’t over- or under-sequence

Getting the most information possible out of every sequencing read can also reduce costs by avoiding over- or under-sequencing your libraries. Over-sequencing leads to obvious unwanted waste. In contrast, “under-sequencing can reduce overall confidence in variant calling due to minimal variant-supporting reads,” says Masser. “Additional sequencing is then required to increase the read depth in hopes of increasing confidence in variant calling, resulting in increased sequencing costs.”

6. Use multiplexing and automation

Multiplexing NGS samples whenever possible is a dependable source of savings. “This can require some coordination of indexing schemes but, if a process is in place to keep sample submissions orderly, many samples can be run simultaneously on a single lane of a NovaSeq to save costs,” says Hoppers. This requires some planning and forethought, but molecular indexing and bioinformatics makes this relatively straightforward.

Automation is another dependable cost-cutter, as it increases throughput and eliminates human errors. However, its implementation is not without occasional growing pains. “Perhaps one of the most difficult, but potentially dramatic, ways to save on NGS is investing in a high-quality liquid-handing automation system,” says Hoppers. “The upfront costs of purchasing and optimizing such a system can be prohibitive, but if the expense can be tolerated, the savings in time, increased reproducibility, and much higher throughput will offset the initial costs over time.”

7. Ignorance isn’t bliss

One of the biggest hidden NGS costs that can creep up over time is ignorance. Periodic reassessment of workflows, reagents, and techniques can save time and money. Your lab’s sample throughput may have increased over time to the extent that automation is now advisable, even if it wasn’t last year. “While implementing automation solutions can be challenging initially, because of capital equipment costs and validation work, they will yield long-term cost savings compared to continuing with manual library generation,” says Masser. Additionally, reagent suppliers regularly release updated or new products to make NGS library prep faster or more efficient, so a periodic check—like updating your computer’s operating system—is a good idea.

Lastly, try to keep abreast of the latest NGS techniques. “The biggest thief of potential cost savings is being unaware of new techniques in NGS,” says Hoppers. “NGS is a fast-changing field, so it can be difficult to keep up with changing strategies, and challenging to change an established protocol or workflow in the lab when everything is already working well enough.” But occasionally trying a new NGS technique or library-prep kit might be worth much more in future savings.