Targeted resequencing is a genetic analysis method that focuses on sequencing specific, pre-selected regions of the genome. This approach allows for an in-depth look at areas of interest rather than the entire genetic code, providing a way to examine particular genes with high precision.
Imagine the human genome as a vast library. Whole genome sequencing would be like reading every book, while targeted resequencing is like choosing to read only specific chapters known to contain important information. This focused strategy allows for a much more detailed examination of those chosen sections.
This method is effective when researchers or clinicians have a clear idea of which parts of the genome to investigate. By concentrating sequencing resources on a limited number of targets, it is possible to read those specific DNA sequences many times over. This high level of repetition ensures accuracy and sensitivity in detecting genetic variations.
The Targeted Resequencing Process
The first step is the selection of the DNA regions of interest, known as target selection. Scientists design a custom “panel,” which is a set of genes or genomic regions associated with a specific condition or research question. This panel design is based on existing knowledge about the genetic basis of a disease or biological pathway.
Once targets are defined, the next stage is isolating these DNA sequences from the rest of the genome in a process called target enrichment. This uses molecular “baits,” which are short, synthetic DNA sequences designed to be complementary to the target regions. These baits bind to the desired DNA fragments, effectively fishing them out from the other genomic material. The two primary methods for this are hybrid capture, which uses baits to pull down target DNA, and amplicon-based enrichment, which uses PCR to create many copies of only the desired sequences.
After enrichment, the isolated DNA fragments are loaded onto a next-generation sequencing (NGS) instrument. This machine reads the precise order of the nucleotide bases (A, C, G, and T) in the captured fragments. Because the sample is enriched for the target regions, the sequencer dedicates its resources to reading these areas at a very high depth.
The final step is data analysis, where sequencing data is processed by bioinformatic pipelines. The generated sequences are aligned to a reference genome to identify any differences or variations. This analysis can pinpoint mutations within the targeted regions, providing the specific genetic information researchers were seeking.
Applications in Diagnostics and Research
In oncology, targeted resequencing is used to analyze cancer-related genes using “cancer panels.” These panels target genes known to drive tumor growth or confer resistance to certain therapies. For example, testing for mutations in the BRCA1 and BRCA2 genes assesses hereditary risk for breast and ovarian cancers, which can guide treatment decisions.
This method is also instrumental in diagnosing hereditary diseases. For monogenic disorders, where a single gene mutation is the cause, targeted panels can efficiently confirm a diagnosis. Conditions like cystic fibrosis or Huntington’s disease are often diagnosed this way, as it is more direct than sequencing the entire genome when potential causative genes are known.
Pharmacogenomics, the study of how genes affect a person’s response to drugs, is another area where targeted sequencing is applied. Panels can check for specific genetic variants that influence drug metabolism. For instance, variations in the CYP2D6 gene affect how individuals process many common medications, and this knowledge helps doctors prescribe the correct dosage.
The utility of targeted resequencing extends to infectious disease surveillance. During viral outbreaks like the COVID-19 pandemic, this technique is used to track the evolution of the virus. By sequencing specific parts of the viral genome, scientists can identify new variants, monitor their spread, and assess their potential impact on vaccines.
Comparison with Other Sequencing Methods
Targeted resequencing differs from other techniques like Whole Genome Sequencing (WGS) and Whole Exome Sequencing (WES). WGS sequences an individual’s entire genetic code, including all genes and non-coding regions. WES focuses only on the exome—the protein-coding regions of genes—which constitutes about 1-2% of the genome. While WES is more focused than WGS, it is still much broader than a typical targeted panel.
The most distinct difference is the depth of coverage. Because targeted resequencing concentrates on a very small fraction of the genome, it can achieve extremely high sequencing depth, often 500x or more. WGS and WES, covering much larger areas, have lower depths, often in the 30-100x range. This higher depth makes targeted resequencing more sensitive for detecting rare variants.
Another distinction is the volume of data produced and the complexity of its analysis. Targeted resequencing generates a smaller, more manageable dataset, which simplifies and speeds up the bioinformatics analysis. In contrast, WGS produces a massive amount of data that requires significant computational power and storage, making the analysis more complex.
Key Advantages and Considerations
One of the primary benefits of targeted resequencing is its high sensitivity. The deep coverage achieved by focusing on a limited number of genes allows for the confident detection of rare variants that might be missed by broader methods. This is valuable in cancer genetics, where a mutation might be present in a small fraction of tumor cells.
The method is also highly cost-effective compared to WGS and WES. By sequencing only the necessary regions, both sequencing costs and data analysis expenses are reduced. This economic advantage makes it feasible to analyze a large number of samples for population studies or screening efforts.
The focused nature of the data leads to a faster turnaround time. With less data to generate and analyze, results from targeted resequencing can be delivered more quickly. This speed is an advantage in clinical settings where timely diagnostic information can influence patient care.
A main consideration is that the approach requires prior knowledge of the genes or regions to be analyzed. It is not a tool for discovery outside of the pre-selected targets. If a disease-causing mutation lies in a gene that was not included in the panel, it will not be found.
The utility of the test is entirely dependent on the design of the panel. A poorly designed or outdated panel may fail to include relevant genes and could miss important mutations. As scientific understanding of genetic diseases evolves, these panels must be updated to remain effective.