March 1, 2015 (Vol. 35, No. 5)
gDNA Metric, Larger Fragments, Higher Sample Sensitivity
Over the brief history of next-generation sequencing (NGS), methods for the creation of libraries for the various NGS instrument platforms have evolved considerably and continue to be in a constant state of flux. Companies are creating new kits for an ever increasing number of sample types. Nucleic acids are being sequenced from a wider diversity of organisms and in some cases, just a portion of an organism such as formalin fixed tissues, biopsies, and fine needle aspirates. Newer library preparation methods also require ever decreasing amounts of input DNA, and in some cases do not require PCR amplification.
Another area of progress is the continued march toward long-read sequencing technologies, which allow for more efficient genome assembly.
Although the cost of sequencing has significantly declined in recent years, it is still relatively expensive per sample. To avoid the cost of poorly generated sequencing data on the back end of experiments, NGS labs are making key investments on the front end to perform quality control of sample libraries for proper size distribution and concentration.
With a widening range of kits and methods for NGS library preparation, the QC tools used for quality/quantity assessment need to continually evolve. NGS labs now need technology with capabilities to handle an increasing work load, the flexibility to switch between different sample preparations and fragment lengths, a reduced sample preparation time for analysis, and the sensitivity to analyze lower concentration samples. The Fragment Analyzer™ from Advanced Analytical Technologies is designed to meet these future needs.
Genomic Quality Number (GQN)
Following the extraction of gDNA, it is important to assess the integrity and concentration of the recovered nucleic acid sample to ensure it has the quality and appropriate concentration to provide good sequencing data. However, depending on the application, “quality” can be a relative term.
For example, genomic DNA extracted from formalin fixed paraffin embedded (FFPE) tissue can be significantly degraded as compared to freshly extracted gDNA, necessitating a different set of comparative criteria to assess sample suitability.
Recently, Advanced Analytical has developed an intuitive approach to aid researchers in determining the quality of genomic DNA. Based on user-defined parameters, a Genomic DNA Quality Number (GQN) provides a reliable, flexible method to compare the relative quality of different samples and enable faster decisions to be made in regard to the suitability of extracted gDNA samples.
To utilize the GQN feature in PROSize® Analytical Software, the user first defines a Size Threshold for their specific application (e.g., 1,000 bp or 10,000 bp). The software then calculates a GQN based upon the fraction of total measured concentration that lies above or below the specified threshold. The GQN scores the sample on a scale of 0 to 10, with 0 indicating 100% of the sample concentration lies below the threshold and 10 indicating 100% of the sample concentration lies above the threshold value.
Figure 1 shows an overlay of four different gDNA samples containing various proportions of different size fragments, with various GQN values from 8.6 (highest quality) to 1.8 (lowest quality), using a Size Threshold of 10,000 bp.
Figure 1. Overlay of various extracted gDNA samples analyzed with the High Sensitivity Genomic DNA Fragment Analysis Kit (DNF-488) using a fast-running lower marker (set to 1 bp), and scored using the GQN function of the PROSize® data analysis software. Faster migrating lower markers provide more accurate results when working with highly degraded or heterogeneous samples.
Large Fragment Analysis
While sequencing long fragments allows for faster genome assembly, qualification and quantification by electrophoresis methods requires the ability to effectively resolve small differences in size as well as normalize differences between runs to achieve accurate sizing.
Advanced Analytical has developed a unique Large Fragment Analysis kit for assessing size and concentration of long fragments. Figure 2 shows the separation and quantification of a large fragment DNA smear sample, analyzed under the specified kit conditions, with an expected size of ~10,000 bp. This unique method utilizes both a fast-moving lower marker and a slow-moving upper marker bracketing a wide size range of fragments (75–20,000 bp) for accurate sizing and analysis.
Figure 2. Large fragment DNA smear sample analyzed with the High Sensitivity Large Fragment Analysis Kit (DNF-493) using a fast-running lower marker and slow-running upper marker. Total sample concentration was measured to be 0.332 ng/µL. Peak maximum is annotated by size in bp.
Higher Sensitivity Detection
Figure 3 shows the successful detection of a low concentration NGS library of ~70 pM (8 pg/μL) using a slightly modified experimental method. The ability to adjust experimental methodology provides added advantages over locked-out chip-based platforms that do not allow end-users to optimize their methods.
Figure 3. Low-concentration NGS library sample analyzed with the High Sensitivity NGS Fragment Analysis Kit (DNF-486) with an adjusted dilution and increased injection time. The total sample concentration is 70 pM (8 pg/µL) prior to analysis.
Conclusion
Combining the correct elements into an NGS platform is critical to achieving effective, efficient, and economical data generation. QC analysis of library preparation ultimately affects sequence assembly. Sequencing has a large appetite for time, labor, and cost of operation. The key to streamlining NGS is not by applying more of the same resources, but via innovation. The Fragment Analyzer brings such innovations to the marketplace—automation, sample capacity, useful metrics such as GQN, high sensitivity, instrument accessibility, and the ability to analyze both large and small NGS library preparations.
Kit-Sum Wong, Ph.D. ([email protected]), is director of consumable product development & Jolita Uthe, Ph.D., is a development scientist at Advanced Analytical Technologies.
