Accuracy: Innovative digital sequencing (incorporating molecular barcodes) eliminates PCR duplication and amplification bias to confidently detect known and novel fusions.
Specificity: The unique combination of our proprietary primer design algorithm and rigorous testing of every primer assay guarantees high specificity and accurate results.
Content: The QIAseq targeted RNAscan panels offer a high degree of flexibility in content and sample multiplexing. Several cataloged panels have been developed for a wide range of applications. One can also build a custom panel for specific content, or to extend the contents of an existing cataloged panel. Up to 384 samples can be multiplexed using the QIAseq indexes.
Flexibility: Because the QIAseq targeted RNAscan panels use single primer extension, primers can be designed to detect known fusions based on characterized breakpoints or to discover novel fusions.
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Principle
PCR duplicates are a major issue in targeted RNA sequencing for gene fusion detection, since – through PCR amplification – they turn unique RNA molecules into identical RNA molecules that cannot be distinguished from each other. This, in turn, results in the inability to confidently detect gene fusions. To overcome the issue of PCR duplicates, the QIAseq targeted RNAscan panels use digital sequencing by incorporating molecular barcodes into the starting RNA material before any amplification takes place – thereby preserving the uniqueness of the starting RNA molecules and overcoming the issues of not only PCR duplicates and amplification bias.
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Procedure
The entire workflow of the QIAseq Targeted RNAscan Panels – from extracted RNA to sequencing-ready libraries – can be completed in 9 hours. Extracted RNA is converted to cDNA, targets are molecularly barcoded and enriched, and libraries are constructed. Sequencing files can be fed into the QIAseq pipeline – a cloud-based data analysis pipeline – which will filter, map and align reads, as well as count unique molecular barcodes associated with targeted regions and call fusions. This data can then be fed into QCI for interpretation.