Next-generation sequencing (NGS) has revolutionized biological research and clinical diagnostics. However, the accuracy and reliability of NGS data are crucial, especially in clinical applications where accurate identification of mutations can significantly impact patient care. Current methods for quality control often rely on external reference standards or spike-in controls, which can be cumbersome, expensive, and may not fully address the complexities of NGS library preparation and sequencing. This study introduces a novel approach using Control Library Adaptors (CAPTORS), which are integrated directly into the library preparation workflow. CAPTORS offer a simple yet effective method to measure both qualitative (sequencing accuracy) and quantitative (library bias) aspects of NGS performance. The seamless integration of CAPTORS eliminates the need for additional steps and provides a more comprehensive assessment of sequencing performance within each individual sample. The advantages are particularly pronounced in applications such as nanopore sequencing, which is known for its relatively higher error rate compared to other NGS platforms. The researchers aimed to design and validate CAPTORS for use in nanopore sequencing, showing their capacity to enhance the accuracy and reliability of sequencing experiments, enabling robust comparisons between different samples, reagents, and laboratories.

Existing methods for assessing NGS accuracy and reliability have limitations. External reference materials, while providing ground truth, lack the ability to account for sample-specific variations. Spike-in controls, although offering internal controls, require extra steps in library preparation and can introduce bias, especially when dealing with low-input or degraded samples. Previous studies have highlighted the challenges of accurate quantitative analysis in NGS, particularly in metagenomics and RNA-seq where accurate normalization between samples is crucial for valid comparisons. The use of unique molecular identifiers (UMIs) has been explored to improve accuracy and mitigate PCR amplification biases, but these are not comprehensive solutions for addressing the systematic errors inherent in NGS technologies. Therefore, a need existed for a more integrated and robust method of quality control that could seamlessly measure both qualitative and quantitative aspects of NGS performance.

The researchers designed 72 unique 90-nucleotide (nt) CAPTORS for Oxford Nanopore Technologies (ONT) sequencing. Each CAPTOR consisted of three regions: a 5' constant region, a central variable region, and a 3' constant region. The variable region contained a diversity of 6-mers to evaluate ONT base-calling accuracy. CAPTORS were manufactured using enzymatic DNA synthesis and integrated into standard library preparation protocols for both DNA and RNA sequencing. Libraries were sequenced on ONT MinION instruments, and the resulting data were analyzed. To evaluate quantitative performance, a master mix of CAPTORS at different concentrations was used to create a staggered reference ladder. This ladder served as an internal control for assessing quantitative accuracy and enabling normalization between different samples. For error correction in clinical applications, custom BRCAPTORS were designed to target the BRCA1 and BRCA2 genes, known for their high mutation rates in breast cancer. NA12878 human genome DNA was used to test the efficacy of BRCAPTOR-guided error correction. Metagenomic experiments used mock microbial communities, and RNA-seq experiments used Universal Human Reference RNA (UHRR). Statistical analyses, including comparisons of sequencing error rates, quantitative accuracy assessments, and normalization strategies, were performed to evaluate the performance of CAPTORS.

CAPTORS successfully measured sequencing accuracy across diverse libraries with a mean per-base error rate consistent with previously reported rates for MinION sequencing. The error rate varied among 6-mers, with higher rates observed for repetitive and low-complexity k-mers, reflecting known biases in nanopore base-calling. Replicate libraries showed high reproducibility in sequencing error profiles, indicating the systematic nature of these errors. Analysis of individual pores revealed significant variations in sequencing accuracy and throughput, suggesting that CAPTORS can provide real-time assessment of pore performance. Comparison of different nanopore versions (R9.4.1 and R10.3) demonstrated that CAPTORS accurately reflected the differences in their error profiles, particularly for homopolymer regions. In quantitative analyses, CAPTORS generated a reliable reference ladder that enabled accurate measurement of library sensitivity and bias. Normalization using CAPTORS, combined with RUVg normalization, significantly improved the detection of true fold-change differences in metagenomic experiments compared to other methods like TMM normalization. In RNA-seq, CAPTORS accurately estimated the limit of quantification (LOQ) for gene expression measurements. For error correction, BRCAPTORS effectively modeled the sequencing error profiles of BRCA genes, allowing for improved accuracy in the identification of clinically relevant mutations. The error correction approach was most effective for deletion errors, significantly reducing the error rate in the corrected sequences, improving the diagnostic accuracy. The minimum sequencing coverage required for reliable quantification was determined using CAPTORS, showing a minimum threshold of around 5 × 10⁴ reads.

This study successfully demonstrates the utility of CAPTORS as a simple yet powerful tool for improving the accuracy and reliability of NGS data. The seamless integration of CAPTORS into library preparation workflows provides a significant advancement over existing methods. The ability of CAPTORS to measure both qualitative and quantitative aspects of sequencing performance, combined with their capacity for normalization and error correction, positions them as a valuable tool for various applications, particularly in clinical diagnostics where high accuracy is paramount. The ability to monitor real-time performance and customize CAPTORS for specific gene targets expands their applicability and increases their value across diverse NGS workflows. The findings highlight the importance of using integrated reference controls to enhance the interpretation and use of NGS data, particularly for nanopore sequencing where error rates are higher. The demonstrated improved detection of true fold-change differences in metagenomic studies showcases the value of using CAPTORS for normalizing and reducing technical variation across different samples and laboratories.

CAPTORS offer a novel, efficient, and effective approach to enhancing the accuracy and reliability of NGS. Their seamless integration into standard library preparation protocols provides a comprehensive, quantitative, and qualitative assessment of sequencing performance. The improved normalization capabilities, along with successful error correction for critical genes in clinical applications, underscore the potential for broader adoption of CAPTORS to improve the accuracy and interpretation of NGS data. Future research could explore the application of CAPTORS to other sequencing platforms and the development of automated analysis tools to streamline data interpretation.

While CAPTORS provide a significant advancement in NGS quality control, there are some limitations. The study primarily focused on nanopore sequencing; further validation across other NGS platforms is warranted. The design and synthesis of custom CAPTORS for specific genes is currently not scalable for large gene panels. While the BRCAPTOR approach demonstrated effectiveness for error correction in BRCA genes, the approach might not be equally effective for all genes. The minimum sequencing coverage required for reliable quantification of CAPTORS might vary depending on the specific experiment and application.