Illustration representation of exome sequencing data points on a blue background

Solving Challenges in Exome Sequencing

New solutions provide more coverage in a cost-effective way

May 18, 2022
Rachel Muenz
Peter Hahn, PhD

Peter Hahn, associate director R&D, NGS Technology Development—QIAGEN, received his PhD from the University of Saarland on cellular and molecular virology. He is currently leading a team responsible for library preparation development focusing on whole genome, whole exome, and hybrid capture-based sequencing applications.

Q: What does exome sequencing achieve and what are typical pitfalls associated with the exome enrichment process?

A: Exome sequencing is a great tool to reduce the target region size to less than 2 percent, as compared to human whole genome sequencing, by focusing on expressed regions. Exome sequencing solutions rely on hybrid capture probe-based enrichment of sequences of interest from whole genome libraries. Working with smaller amounts of DNA input can be challenging, but QIAGEN’s hybrid capture probes are dsDNA molecules that capture both strands of targeted library fragments. Poor coverage uniformity of the targeted regions can be another challenge, and is

exacerbated by high GC content. Libraries with low uniformity need increased sequencing effort to reach the required sequencing depth. QIAGEN kits use probe design and optimized experimental conditions to maximize coverage uniformity with minimal sequencing effort. Unlike other solutions, the coverage uniformity is largely independent of GC content, reducing the risk of drop-outs. 

Q: What is the difference between whole exome sequencing and the “actionable exome” and what does each provide to researchers?

A: Human whole exome sequencing covers all genes in the human genome. It allows the identification of known disease variants, and can be a discovery tool for the identification of novel disease-associated variants in genes that have not yet been described. Whole exome libraries have larger target regions compared to more clinically oriented exomes. More clinically oriented exome panels usually focus on disease-related genes only, enabling researchers to reduce the target region size, while reducing sequencing costs per sample. 

Q: What is the value of sequencing noncoding regions in the DNA, such as untranslated regions (UTRs) and promoters, and how does this affect cost?

A: The value of sequencing UTR and promoter regions is relatively low. The function of many variants in these regions is still unknown, therefore they are difficult to interpret. Including regulatory regions may be beneficial for basic research, but would significantly increase hybrid capture panel size and sequencing costs. QIAGEN whole exome kits keep the target region relatively small while covering the majority of regions that are of relevance for gene function. The kits cover more than 95 percent of all Human Genome Mutation Database (HGMD)-listed disease mutations. By also targeting disease-associated variants in promoters and other deep intronic regions to reach full HGMD representation, QIAGEN’s actionable exome kit keeps the target region at about 14 megabases. 

Q: Is there a cost-effective way to explore both exome- and real-world-curated variants?

A: The QIAseq xHYB Actionable Exome, launching soon, focuses on genes that harbor disease-related variants. The panel covers variants within the coding sequence and includes mutations in regulatory regions that can be far off the actual exons. This panel allows calling of HGMD variants irrespective of their genomic location in the context of a relatively small exome capture panel. 

For variant analysis, QIAGEN Digital Insights offers a comprehensive portfolio of bioinformatics solutions to analyze whole exome sequencing data, data from any other focused panel, or even whole genome sequencing data. QIAGEN’s CLC Genomics Workbench processes sequencing data using an optimized and ready-to-use workflow. Identified variants are then automatically transferred to QIAGEN Clinical Insight Interpret Translational (QCI-IT), a variant analysis and interpretation tool for basic and translational research.