The Benefits of Automating NGS Library Prep

Automating NGS library preparation can increase your lab’s throughput and accuracy while saving time and money

Next-generation sequencing (NGS) has seen increased adoption across clinical laboratories, and has since been a valuable tool in the diagnostic odyssey of many patients. However, the conversion of native DNA to a barcoded library capable of detection by NGS is a highly technical process requiring significant time and reagents as well as being error-prone—a hurdle that can lead many laboratories to rely on send-out services for their NGS testing. Dedicated automation solutions for NGS library preparation, such as liquid handling instruments and integrated microfluidic systems, have the benefits of saving time and cost while reducing error, among other advantages. Taken together, the benefits of automating NGS library preparation cannot be understated in the clinical laboratory environment.

What is NGS library preparation?

The process leading up to NGS sequencing involves two main components, both of which can be automated. The first is sample preparation, which involves chemically or mechanically disrupting cells in the collected tissue (e.g., blood, saliva) to release DNA from within the nucleus, then isolating the DNA into a highly purified and concentrated solution. The second step is the library preparation, which involves many highly repetitive and sensitive steps. The steps involved in library preparation for short-read sequencing are as follows:

1.    Fragment DNA into small pieces capable of being read by a sequencer

2.    Ligate the fragmented DNA to adapters that identify the sample

3.    Bind the DNA–adapter hybrids to a solid-state for amplification and sequencing

Cost and time savings

NGS library preparation is a time-consuming and repetitive process that is considered the bottleneck of DNA sequencing.1 Using a manual process requires additional work to prepare reagents, and is repetitive as well as error-prone, and therefore leads to both time and cost inefficiencies for clinical genetics laboratories.2 Automating NGS library preparation holds the potential to increase the throughput and accuracy of the process in a cost-effective manner. One recent study found that 5 percent of the total cost of NGS sequencing with manual library preparation was related to laboratory personnel.3 A simple way to reduce the cost of library preparation is to minimize hands-on work time for laboratory personnel, which frees employees to perform other laboratory tasks that cannot be automated. Automation can significantly reduce hands-on time. For example, Agilent’s automated NGS prep workflow can reportedly reduce hands-on time from 675 minutes to 75 minutes with a reported increase in throughput from 48 samples to 192 samples per week.4 While consumables such as pipette tips need to be considered, the savings from reduced dedicated staff, training time, and errors can easily offset this cost with increased sample volume.5 Automation is also highly scalable.  Once a protocol has been programmed, it can easily be replicated on additional instruments, saving time and money in hiring and training additional staff compared to using a manual process.

Reduction in error

The process of manual NGS library preparation intrinsically involves numerous repetitive small-volume pipetting steps in multiwell containers. As such, high precision is required from the laboratory professionals performing these steps to avoid pipetting errors or contamination as small differences in pipetting techniques can result in considerable variability in library quality and yield. These errors are rarely detected until after the sequencing run has been completed, resulting in significant loss of reagents and supplies. Automated liquid handling instruments are highly calibrated to handle small microliter volumes of reagents and can minimize the batch effect caused by slight differences in pipetting techniques between users.

Other common errors in manual NGS library preparation include: 

  • Sample mix up, a catch-all term for losing track of a sample. This can occur by pipetting the patient sample into the incorrect well of the reaction plate, losing the orientation of the reaction plate, etc.
  • Reagent pipetting errors, which include adding the incorrect reagent, missing a row of wells during pipetting steps, etc.6

Even a small error can result in the loss of hundreds to thousands of dollars in reagents and consumables. By implementing an automated workflow, the risk of these types of errors are minimized by preprogramming them into an instrument designed to accurately perform repetitive tasks. Furthermore, many automated solutions have error-reporting built in, allowing scientists to correct the error or terminate the process to minimize reagent and supply waste if an error cannot be corrected.

Clinical genetics laboratories stand to benefit

Although the cost and time savings of automation depend on an individual laboratory’s throughput, the benefits of automating NGS library preparation can be great. By reducing cost, time, and loss due to error, clinical genetics laboratories stand to benefit greatly from adopting this technology.


1. Tyler AD, Christianson S, Knox NC, et al. Comparison of sample preparation methods used for the next-generation sequencing of Mycobacterium tuberculosis. PLoS One. 2016;11(2):e0148676.

2. Christensen KD, Dukhovny D, Siebert U, Green RC. Assessing the costs and cost-effectiveness of genomic sequencing. J Pers Med. 2015;5(4):470-86.

3. Schwarze K, Buchanan J, Fermont JM, et al. The complete costs of genome sequencing: a microcosting study in cancer and rare diseases from a single center in the United Kingdom. Genet Med. 2020;22(1):85-94.

4.  Agilent. Fast, accurate sequencing starts here. [ebook] Santa Clara, CA; 2017. Accessed 3 September 2021.

5.  Tegally H, San JE, Giandhari J, de Oliveira T. Unlocking the efficiency of genomics laboratories with robotic liquid-handling. BMC Genomics. 2020;21(1):729.

6.  PerkinElmer. The top ten things that can (and do) go wrong with manual library prep. Accessed 3 September 2021.