Next-generation sequencing (NGS) is an effective research instrument that is becoming more widely used. There is a plethora of library-preparation methods, and library quality control has become an enormously crucial component in the NGS template. Preparing an NGS library takes a lot of time and effort. DNA fragmentation (mechanical or enzymatic), DNA repair and end-polishing, and platform-specific adaptor ligation are frequently used.
The quality and quantity of the library material are two factors that influence sequencing success. Underutilization of sequencing runs is caused by using too little DNA, libraries with improper fragment size ranges, or libraries rich in adapter-adapter dimers, leading to lowered coverage and read depth, empty runs, and higher costs. Mixed signals, unresolved data, and lesser single reads result from loading too much DNA onto the sequencer. When numerous libraries are pooled for parallel sequencing, precise library concentrations become even more essential. To guarantee that all specimens in the library pool produce the same amount of sequence, the library must be balanced.
Quantitative real-time PCR (qPCR)
Quantitative real-time PCR (qPCR) is a fluorescence-based PCR assay that utilizes dyes to connect double-stranded DNA (dsDNA) or fluorophore-labeled oligonucleotide probes to attach specific target sequences. The fluorescence in the specimen increases as the PCR process creates more dsDNA. To evaluate library concentration, this growth is tracked in real-time and compared to recognized concentration standards. Only fragments containing the necessary adapter sequences can be quantified in qPCR assays. This guarantees that only sequenceable DNA is quantified.
Digital PCR (dPCR)
dPCR systems divide nucleic-acid molecules into many partitions, each containing a separate PCR reaction. Droplets microwell plates or capillaries can partition. Without the use of standard curves, the starting concentration of a DNA template in a specimen can be measured with high precision using standard PCR, fluorescence-based detection, and Poisson statistics. Unlike qPCR, dPCR does not assume that all sequences will amplify with the same efficiency. This method also reduces the number of input samples required. For detecting library concentration and quality, dPCR assays can be constructed. End-users can select to remake their library if it contains a high concentration of adapter-adapter dimers, saving time and money.
Agarose gel electrophoresis
The use of agarose gel electrophoresis to evaluate library purity and fragment size is a simple and inexpensive method. The size range is calculated using a standard DNA ladder, and RNA contamination and primer dimers are noticeable at the bottom of the gel as a small-molecular-weight smear. This method's concentrations are estimations, and libraries with huge fragment size ranges are especially hard to quantify precisely. Furthermore, regardless of whether it is flanked by the required adapter sequences or defines adapter-adapter dimers without the DNA insert, all dsDNA is quantified using this technique.
Spectrophotometry
A standard UV spectrophotometer can also be used to evaluate nucleic-acid concentration by quantifying sample absorption at 260 nm. UV spectrophotometers are standard laboratory instruments, making library quantification a simple and inexpensive process. The readings should be within your spectrophotometer's linear range, which is typically between 0.1 and 1.0. Unfortunately, many other molecules absorb light at 260 nm, which could lead to an overestimation of DNA concentration.
The A260/A280 ratio can be used to determine the quality of DNA by measuring absorbance at 280 nm. The A260/A280 ratio of "pure" DNA should be around 1.8, but DNA quality is regarded as acceptable if it is between 1.7 and 2.0. Protein or phenol contamination, as well as very low DNA concentrations, can cause low A260/A280 readings.
The bioinformatics analysis department of CD Genomics provides novel solutions for data-driven innovation aimed at discovering the hidden potential in biological data, tapping new insights related to life science research, and predicting new prospects.
References