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Targeted sequencing

Overview

Targeted next generation sequencing (NGS) focuses on specific regions of interest in the genome. With targeted NGS, researchers can target specific genes, coding regions, or even chromosomal segments at deeper coverage than alternative sequencing methods, obtaining fast, accurate, and precise genomic insights.

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What is targeted sequencing?

Targeted next generation sequencing focuses on specific genomic areas of interest. This technology is ideal for examining genes in specific pathways or for follow-up experiments (targeted resequencing) from whole genome sequencing (WGS). It is rapid and more cost-effective than WGS, and because it allows for deeper sequencing. Targeted sequencing is an especially sensitive and powerful method for identifying variants and mutations, including rare variants. Additional advantages of targeted NGS compared to WGS include:

  • Smaller datasets requiring less computational resources
  • More scalable (can handle more samples/sequencing run)
  • More appropriate for industrial applications where cost and speed are critical

How does targeted sequencing work?

Targeted sequencing is similar to WGS, but the sample preparation workflow requires an extra step: target enrichment. The two main target enrichment methods are hybridization capture and amplicon sequencing. Hybridization capture uses biotinylated oligonucleotide probes to capture regions of interest, while amplification uses PCR for target enrichment (see Table 1).

One major difference between the two approaches is the point at which samples can be multiplexed, or pooled. Multiplexing requires adding a barcode (index) to samples so they can be identified after sequencing. Samples used for hybridization capture can be multiplexed after library preparation, but before target capture (enrichment). Samples used for amplicon sequencing must be transformed into libraries and enriched via PCR amplification individually before they can be multiplexed for sequencing.

When using hybridization capture, additional indexes, called unique molecular identifiers (UMIs) can be used to identify specific molecules within a sample. Using adapters with UMIs facilitates the removal of PCR duplicates for better quantitation or the use of multiple duplicate reads for in silico error correction to reduce false positives and increase accuracy.

The appropriate method for target capture depends on several variables, including the desired accuracy, budgetary constraints, and the downstream sequencing application. Table 1 below can help you determine which targeted sequencing method is best for your research applications.

Table 1. Comparison of targeted sequencing methods.

FeatureHybridization captureAmplicon sequencing
Input amount1–250 ng for library prep, 500 ng of library into capture10–100 ng
Number of stepsMore stepsFewer steps
Number of targets per panelVirtually unlimited by panel sizeFewer than 10,000 amplicons
Variant allele frequency sensitivityDown to 1% without UMIsDown to 5%
Total timeMore timeLess time
Cost per sampleVaries Generally lower cost per sample
Best-suited applications

Exome sequencing
Genotyping
Oncology
Detecting rare variants
Gene discovery
Detecting low-frequency somatic SNVs* and indels

Genotyping by sequencing
Detecting CRISPR editing events
Detecting disease-associated variants
Detecting germline inherited SNPs** and indels

*single nucleotide variant

**single nucleotide polymorphism

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Targeted sequencing application guide

This detailed overview walks you through major advances in capture and enrichment technology, types of targeted next generation sequencing, their applications, and more.

IDT products for targeted NGS

Whether you need custom, exome, or other predesigned hybridization panels, or targeted amplicons, IDT has the solution you need. Explore our amplicon sequencing and xGen™ Hybridization product lines.

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xGen Exome Research Panel v2 white paper

Learn how our large-scale production platform, using PCR-free synthesis, provides a unique advantage over array-based platforms by delivering consistent exome panel performance over time.

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