Next-generation sequencing (NGS) has proven to be an efficient and versatile approach that has transformed the way genomics is approached and processed. From oncology to infectious disease monitoring and consumer genomics, the market for NGS solutions is expected to exceed $66 billion by 2033.
However, many labs still rely on manual methods that struggle to keep pace with the growing demand. Using manual methods is typically time-intensive, with little to no benefit when you're preparing delicate and finicky DNA or RNA samples. These workflows often involve repetitive pipetting, tube and plate transfers, centrifugation steps, and manual tracking across multiple instruments. Each additional “hands-on” step introduces another opportunity for variability, error, and delays that automation is designed to remove. Preparation time doesn't even factor in the potential losses for your lab if the ratio of reagents is improperly pipetted, or samples are stored in suboptimal conditions due to bottlenecks.
Furthermore, even the most skilled bench scientists have a limit when it comes to preparation volume. Hiring more staff may be counterproductive, depending on the layout and size of your lab, as it may slow down your operation. That’s where lab automation software comes in—enabling labs to scale efficiently without sacrificing precision or productivity.
How Lab Automation is Transforming Genomics
One lab found that integrating an automated liquid handling system into their library preparation workflow enabled them to process 48 DNA samples and 48 RNA samples in a single run, reducing the overall runtime from 42.5 hours to 24 hours.
Gaining over 18 hours, or two working days, due to automating repetitive tasks cannot be overstated. Technologies like liquid handlers, robotic arms, and advanced scheduling software are becoming standardized in labs precisely because of their unparalleled consistency.
This throughput translates directly into improved turnaround time, operational scalability, and significantly greater reproducibility of results.
Automating sample preparation and library construction also reduces the risk of contamination and alleviates the burden of standardization on your lab's bench scientists. With an extensive library of device drivers for leading liquid handlers, NGS instruments, and supporting devices, Biosero software can coordinate these steps across mixed-vendor systems so that protocols run the same way, every time.
Robotic arms integrated with scheduling software can move samples between devices with minimal idle time. Simultaneously, real-time monitoring flags inconsistencies before they compromise downstream analysis in a field where consistency is critical—whether for clinical diagnostics or large-scale population studies.
To ensure your lab gets the most out of automating DNA sequencing workflows, it's also essential to streamline data analysis and address system-wide inefficiencies. Biosero's integrated solutions can help your laboratory reduce turnaround time across workflows, enabling faster decision-making and accelerating time to insight.
Benefits of Automating DNA Sequencing Workflows
Automating DNA sequencing workflows goes beyond just speeding up processes; it redefines how efficiently and accurately your lab can operate. By reducing manual intervention and enabling system-wide visibility, automation facilitates more seamless and reliable outcomes, such as:
- Increased throughput: Automation enables high-volume labs to process more samples per run with fewer bottlenecks, maximizing overall productivity.
- Reduced manual intervention: Robotic systems automate time-consuming tasks, such as pipetting reagents, labeling tubes, and transferring samples between instruments.
- Full visibility: Workflow orchestration and real-time tracking provide transparency into every step of the automated DNA sequencing process, improving operational oversight.
- Optimal processing conditions: Biosero's sample management solutions ensure each specimen is handled under ideal conditions to maintain sample quality.
- Improved sample integrity: By limiting human contact and enforcing consistent protocols, automation reduces the risk of cross-contamination, supporting cleaner and more accurate data.
- Increased confidence in results: Higher-quality, reproducible data leads to fewer failed runs and more reliable results, which is especially critical for sensitive applications like rare variant detection and single-cell analysis.
- Enhanced staff focus: By offloading tasks to automation, your lab personnel can redirect their efforts to more strategic responsibilities like troubleshooting and workflow optimization.
Key Automation Steps in NGS Workflows
During the COVID-19 pandemic, Biosero's automation tools played a critical role in enabling large-scale genomic surveillance efforts. Leading sequencing providers collaborated with Biosero to enhance their high-throughput analysis of SARS-CoV-2 variants through a fully automated NGS workflow powered by Green Button Go (GBG). GBG coordinated everything from liquid handling to sample movement and scheduling, helping labs respond more quickly and accurately during a time of global urgency.
Here are three critical stages of the NGS workflow where automation offers the greatest impact:
1. Sample handling and barcoding
Accurate sample identification is foundational to streamlining the genomic sequencing workflow. Automating barcode application, sample registration, and plate movement reduces human error and ensures complete traceability from the moment samples enter your lab. Robotic arms and liquid handlers also improve throughput by handling dozens of samples simultaneously.
2. DNA fragmentation and normalization
Fragmentation and normalization require precise control over reagent volumes and timing. Automated systems consistently shear DNA and normalize concentrations with greater precision than manual methods, improving uniformity and reducing prep variability across batches.
3. NGS library preparation and pooling
This step is one of the most labor- and error-prone in NGS. Automation reduces cross-contamination risks, standardizes reagent handling, and enables scalable pooling. Liquid handlers accurately add master mixes, perform bead-based cleanups, and combine libraries for automated DNA sequencing, thereby reducing run failures and improving downstream data integrity.
By automating these steps, your lab can not only increase efficiency but also unlock greater reproducibility, scalability, and confidence in sequencing results.
The Future of DNA Sequencing
Next-generation sequencing (NGS) is rapidly evolving toward fully automated, end-to-end workflows that simplify sample prep, sequencing, and data analysis. One notable emerging trend is the use of AI-driven quality control, which improves accuracy and reduces the need for manual review.
Real-time tracking systems now monitor every step of the sequencing process, enhancing transparency and traceability. Moreover, scalable automation platforms are enabling labs to flexibly expand throughput without compromising precision. These advancements are making NGS automation faster, more reliable, and accessible to a broader range of applications: from clinical diagnostics to population genomics.
Is Your Lab Ready for NGS Automation?
If your lab is facing growing sample backlogs, frequent quality control (QC) issues, or signs of staff burnout, it may be time to consider automating the NGS workflow. Common starting points include automating high-impact, repetitive tasks such as library preparation or sample tracking.
Pilot projects can help validate return on investment (ROI) and ease the transition to full automation. By incrementally introducing scalable solutions, labs can boost throughput, minimize errors, and free up their bench scientists for higher-value tasks.
Ready to take the next step? Contact Biosero to explore customized automation strategies tailored to your lab.
FAQs
What is DNA sequencing automation?
DNA sequencing automation refers to the use of robotic systems and software to perform tasks like sample preparation, library construction, and data analysis. By automating these steps, labs can reduce errors, increase throughput, and ensure more consistent results.
Can small labs afford NGS automation?
Yes, small labs can afford NGS automation thanks to modular instruments, scalable workflows, and cloud-based orchestration tools. These solutions allow labs to start small—automating just one step—and expand as needs and budgets grow.
What tools are used for automating sequencing?
Tools for automating sequencing include liquid handling robots, plate movers, and software platforms like Green Button Go (GBG). These systems work together to streamline sample prep, track progress, and manage data flow efficiently.
