Technical Key Points for Targeted Sequencing Panel Design and Laboratory Quality Control

Considerations for Target Region Selection and Probe or Primer Design

The starting point for designing a targeted sequencing panel is to define the target regions clearly. For tumor-related panels, it is typically necessary to cover the exons of major disease-associated genes, some intronic fusion breakpoints, promoter regions, and regions required for copy number variation analysis. During design, high-repeat sequences, homologous sequences, and regions with extreme GC content should be avoided as much as possible, because these regions may lead to reduced capture or amplification efficiency and increased alignment errors. A common practice is to use a reference genome and known variant databases for in silico evaluation during the design phase, and to adjust probe or primer concentration, length, or position for regions with poor coverage.

Probe or primer design also needs to consider inclusivity of known variants. For regions with high polymorphism or insertions and deletions, primer binding sites should avoid common variant loci as much as possible; for fusion detection, probes can be designed to span potential breakpoints or be placed on both sides of the breakpoint. Common strategies include adding redundant probes, adjusting probe density, and setting region boundary buffers to improve coverage uniformity.

Differences in Quality Control Between Amplicon-Based and Hybrid Capture-Based Methods

Amplicon-based library preparation directly amplifies target regions through multiplex PCR, has a shorter workflow, and is suitable for smaller panels and hotspot region detection. Its quality control focuses on primer dimers, nonspecific amplification, yield balance among different amplicons, and cross-contamination control. Multiplex PCR systems may need to be optimized in groups according to target fragment length and GC content to avoid suppression of low-abundance templates by high-abundance templates.

Hybrid capture-based methods enrich target regions by hybridizing probes with libraries and are more suitable for covering larger regions and simultaneously detecting variant types such as SNV/Indel, CNV, and fusions. Its quality control focuses on hybridization temperature and time, washing conditions, probe-to-library ratio, adapter contamination, and on-target rate. The on-target rate of hybrid capture is generally affected by probe design, use of blocking sequences, and washing stringency. Laboratories should determine parameters suitable for their own systems through preliminary experiments rather than directly copying default conditions.

Coverage Depth, Uniformity, and Positive and Negative Quality Control

The detection capability of a targeted sequencing panel depends not only on the average coverage depth, but also on the uniformity of coverage in target regions and the proportion of low-coverage regions. Common quality control metrics include on-target rate, target region coverage, uniformity parameters, duplicate sequence proportion, and strand bias. Laboratories can set acceptable ranges based on the intended use; for example, for samples used for low-abundance mutation detection, it is necessary to assess whether the minimum coverage depth can support the preset analytical sensitivity.

Each batch of experiments should include negative controls, positive reference materials, and blank controls to monitor cross-contamination, nucleic acid extraction efficiency, library preparation efficiency, and abnormalities in the sequencing process. For low-abundance samples such as ctDNA, molecular tags and background error correction strategies can be introduced to improve the credibility of variant identification. All quality control data should be included in batch records to facilitate trend analysis and abnormality traceability.

Reproducibility of Bioinformatics Analysis and Result Reporting

From raw sequencing data to variant results, the process involves steps such as alignment, deduplication, local realignment, base quality recalibration, variant detection, filtering, annotation, and evidence grading. Targeted sequencing panels should have a fixed-version analysis pipeline and reference datasets to avoid incomparable results caused by frequent parameter changes. It is recommended to use known variant sets and negative sample sets for pipeline validation and to regularly assess the risk of false positives and false negatives.

At the reporting stage, variant naming conventions, detection scope, and technical limitations should be clearly stated. For insufficient coverage, homologous regions, or complex structural variants, possible limitations should be explained in the report to help users interpret the results reasonably.