Simplifying Next Generation Sequencing Workflow with QuantiFluor® ds-DNA System

DNA SequenceNext-generation sequencing (NGS), also known as high-throughput parallel sequencing, is the all-encompassing term used to describe a number of different modern sequencing technologies. These include Illumina (Solexa) sequencing, Roche 454 sequencing, Ion torrent: Proton / PGM sequencing and SOLiD sequencing to name a few [1].

With the advent of these technologies sequencing DNA and RNA has become much more facile and affordable in comparison to the previously used Sanger sequencing. For these reasons NGS has been the game-changer in the field of modern genomics and molecular biology.

A common starting point for template preparation for NGS platforms is random fragmentation of target DNA and addition of platform-specific adapter sequences to flanking ends. Protocols typically use sonication to shear input DNA, coupled with several rounds of enzymatic modification to produce a sequencer-ready product [2].

Accurate quantification of DNA preparations is essential to ensure high-quality reads and efficient generation of data. Too much DNA can lead to issues such as mixed signals, un-resolvable data and lower number of single reads. Too little DNA, on the other hand, might result in insufficient sequencing coverage, reduced read depth or empty runs, all of which would incur higher costs. The quality of DNA can also vary depending on the source or extraction method applied and further reinforces the need for appropriate management of the input material.

It is important to have a standardized and cost-effective workflow for the qualification of DNA preparations to ensure highly reproducible results that are consistent between different laboratories. DNA qualification consists of both the quantification of double stranded DNA (dsDNA) and the assessment of its suitability for downstream applications.

There are three most commonly used techniques for nucleic acids quantification: namely, UV spectrophotometry using NanoDrop® instrument; dsDNA-specific fluorometry using fluorescent dyes; quantitative PCR (qPCR), that simultaneously assesses DNA quantity and suitability for PCR amplification. These methods have been used individually or in combination to maximize the information needed to qualify DNA samples for NGS applications [3,4].

The QuantiFluor® System is a sensitive, dsDNA-specific fluorescent dye suitable for use in both research and clinical workflows [4]. The new dye system is integrated into the Quantus™ Fluorometer and GloMax® detection instruments, but is compatible with any fluorometer capable of measuring the appropriate fluorescence excitation and emission spectra. The dye system has significantly increased sensitivity compared to absorbance based systems and is highly specific to dsDNA, showing minimal binding to ssDNA, RNA, protein and interfering compounds.

Not surprisingly, NGS has found its way into plant, animal and microbial research laboratories and has helped to pioneer novel scientific studies. Using a combination of NGS and easily reproducible methods to analyze the chloroplast genome, Van der Merwe et al. have successfully obtained phylogeographically informative sequence data from a range of previously unstudied rainforest trees [5]. Another study led by Cabeza, R et al. explored the effects of nitrate exposure on nodule activity in legumes for which they sequenced the RNA transcriptome isolated from the nodules at different time points to identify differentially expressed genes [6]. To understand how the gene activation landscape changes as abundance of the regulatory protein CodY decreases, Brinsmade et al. performed genome-wide transcript profiling of wild type B. subtilis strains and a series of mutants that had varying levels of CodY expression. Comparison of the activation profiles provided insights into how the genes regulated by CodY are controlled depending on the level of activation of CodY by its ligands [7]. A novel genotyping-by-sequencing approach was adapted to genotype cattle from the US and Africa using blood samples as a source for genomic DNA which was processed downstream for next-generation sequencing [8].

Next generation sequencing has enabled researchers to rapidly sequence entire genomes, allowing access to an unprecedented wealth of data. DNA qualification forms a big part of successful NGS analysis. Limitations in the availability of many clinical specimens push the boundaries for low DNA inputs into molecular assays. dsDNA-specific dyes such as QuantiFluor® provide rapid, quantitative, high throughput solution to streamline nucleic acid preparation for sensitive applications and minimize sample waste.

Literature Cited

  1. The Power and Potential of Next-Generation Sequencing
  2. Parkinson N.J.  et al. 2012 Preparation of high-quality next-generation sequencing libraries from picogram quantities of target DNA. Genome Research 22(1):125-133. doi:10.1101/gr.124016.111.
  3. Simbolo M.  et al.  (2013) DNA Qualification Workflow for Next Generation Sequencing of Histopathological Samples. PLoS ONE 8(6): e62692.  doi: 10.1371/journal.pone.0062692
  4. Heydt C  et al.  (2014) Comparison of Pre-Analytical FFPE Sample Preparation Methods and Their Impact on Massively Parallel Sequencing in Routine Diagnostics. PLoS ONE 9(8): e104566.
  5. van der Merwe, M., McPherson, H., Siow, J. and Rossetto, M. (2014) Next-Gen phylogeography of rainforest trees: exploring landscape-level cpDNA variation from whole-genome sequencing. Mol. Ecol. Resour. 14(1):199-208. doi: 10.1111/1755-0998.
  6. Cabeza, R. et al. (2014) An RNA sequencing transcriptome analysis reveals novel insights into molecular aspects of the nitrate impact on the nodule activity of Medicago truncatula. Plant Physiol. 164, 400-11.
  7. Brinsmade S.R. et al. (2014) Hierarchical expression of genes controlled by the Bacillus subtilis global regulatory protein CodY. Proc Natl Acad Sci U S A. 111(22):8227-32.
  8. De Donato, M. et al. (2013) Genotyping-by-Sequencing (GBS): A novel, efficient and cost-effective genotyping method for cattle using next-generation sequencing. PLos ONE 8, e62137.
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Radhika Ganeshan

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