TargetSeq® hybridization capture sequencing technology uses probe hybridization to capture the target regions to detect genetic and tumor-related variation information. TargetSeq® adopts the "stacked tile" probe design strategy to design multi-layer probes in the target area. Meanwhile, efficient and uniform data performance can be obtained by using the self-developed and easy-to-use TargetSeq One® hybridization capture reagent kits.
TargetSeq® hybrid capture sequencing first requires the construction of a complete library, and then hybridization of the probe with the library to form hybridization products, followed by the use of streptavidin-coated magnetic beads for specific capture of library fragments with targeted sequences. After elution, amplification, purification and other steps, the enriched library of targeted sequences is obtained. When passing the quality control, the final library can be sequenced by using NGS platforms such as Illumina and MGI.
Higher effective coverage results from probe design, which is based on thermodynamic stability and special design scheme for hard-to-capture regions.
Over 1000 customizd TargetSeq® panels development experience, covering multiple application fields such as tumor companion diagnosis, drug evaluation, genetic screening, molecular breeding, and animal and plant evolution.
Suitable for target capture of region sizes of 1 kb to 100 Mb. Can detect SNV, InDel, CNV, STR, Fusion and other mutations in the target area. Can also design probes according to the type of mutation.
TargetSeq One® process only requires one single tube operation, which is simple, robust and compatible to different requirements.
Optimization of key product metrics prior to panel delivery for good performance of coverage rate and uniformity.
Accurate detection of mutation frequency greater than 1% with good repeatability. With UMI technology, the panels can be used for low-frequency mutation detection as low as 0.1%.
TargetSeq® hybridization capture sequencing technology is applicable to human, plant and animal, microbial, and other species with known genome. It is suitable for target capture of region sizes of 1 kb to 100 Mb. It can detect SNV, InDel, CNV, Fusion and other variants in the target region, and can be used for the detection of exogenous viruses and viral integration sites analysis. TargetSeq® panels are widely used in application fields such as oncology, genetic disorders, DTC genetic tests, immunology, microbiology, agriculture, and forensic science.
iGeneTech Bioscience provides both catalog and customized panels with reagent kits and automation upgrade solutions for the whole TargetSeq® workflow.
| Library Preparation Kits | Hybridization Capture Kits | Target Probes | Equipments |
The TargetSeq®️ probe is designed with 3× tiling design scheme based on thermodynamic stability to achieve better coverage of target regions. At the same time, there are complete design schemes for reference genome fix or novel patches, hard-to-capture regions, different variant types, CNV, etc.
With over 1000 TargetSeq®️ customized panel development experience in different application fields, TargetSeq®️ customized panels can meet the diverse needs of our customers. Customers can build their own customized TargetSeq®️ panels or build a semi-customized panels based on pre-designed TargetSeq®️ catalog panels with probes of extra selected regions or probes of some regions to be enhanced.
Simple-to-use TargetSeq One® workflow uses one single-tube operation and requires only two washing reagents during the whole workflow. The reagent kit is compatible with both DNA and RNA probes and can be used for single-hybridization, multiplex-hybridization, and fast-hybridization. It is stable, excellent in performance and cost-effective.
TargetSeq One® workflow is compatible with both fast and overnight hybridization strategy, providing excellent performance to meet the demands of good results with fast speed.
For qualified samples, most of the human DNA TargetSeq® panels can be evaluated by using the criteria of Coverage rate (%) > 99%, Target reads capture rate (%) > 50%, T 20% X coverage rate (%) > 97%. For TargetSeq® panels of other species, the performance might vary due to the differences of reference genome, target regions and strains.
We provide different design strategy to detect CNV according to its different sizes. For CNVs over 10 kb, a strategy called CNV backbone can be used by including high MAF SNPs at the intervals based on the target CNV sizes. For exon level CNVs (100 to 1000 bp), panels can be designed by covering all the related exon regions. The AIExome® Human Exome Panel V3 – Inherit includes the specially designed CNV backbone, which can be used for CNVs over 500 kb at whole genome level and CNVs over 50 kb at curated regions.
There are some regions in the genome that we classify as hard-to-capture regions, including high GC content sequences, repetitive sequences and homologous sequences. Based on the evaluation result, some of these target regions might be dropped as they might affect the overall performance or introduce errors. The probe coverage of most designs will be over 99% and the missed regions will be specified in probeMissed.bed.
No. DNA panels are designed based on the reference genome, while the RNA panels are designed based on the transcripts. RNA panels normally include additional probes at the edge of exons in order to increase the detection rate of fusions.
In our design report, we provide different versions of bed files for different analysis. Loci.bed and ProbeCov.bed are the bed files for target regions and the regions covered by actual probes, respectively. Please select the appropriate bed file according to your requirements. Please be noted that if the target is a point mutation or the panels includes the genome fixed/novel patches, the performance evaluated by using Loci.bed and ProbeCov.bed will be significantly different.
For human panels, TargetSeq® panel uses the 3X tiling design strategy based on thermodynamic stability, and a specifically optimized multi-factor strategy for hard-to-capture regions and different variation types to improve the overall performance and the detection rate of key markers. For other species, based on the self-developed algorithm, we will perform the evaluation of the genome first and design the panels using different tiling strategy to ensure the balance of the performance and the cost.
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