Limitations of Whole Exome Sequencing

Genetic testing for both clinical and recreational purposes has become more widely available in the past decade due to advances in sequencing technology. With the variety of testing options, it is becoming increasingly important to understand the implications and limitations specific to the type of genetic testing before proceeding.

Whole exome sequencing (WES) has its advantages over single gene or panel tests and whole genome sequencing (WGS) tests. By sequencing the protein-coding exonic regions of the human genome, i.e. the exome, more genetic information is obtained than by targeting a select set of genes while simultaneously achieving better time and cost efficiency than WGS¹. Thus, WES results can prove to be insightful for patients with complex diseases of uncertain or heterogeneous genetic origin, as well as increase accessibility to clinical genetic testing. However, as with most scientific methods, WES also has its limitations, most notably the following.

1. WES does not cover 100% of the exome.
   Not all exons may be captured. The exon of importance may not be included in the current standard annotations of the human genome²; and it is simply challenging to cover 100% of the exome with the current WES technology. As a result, disease-causing variants in these “missed” exons will go undetected. If the most comprehensive coverage of exons is needed, WGS has shown to provide more complete coverage of the exome than WES³.
2. WES is not validated for the detection of structural variations (SVs), including copy number variants (CNVs), inversions, and translocations.
   WES has low sensitivity for structural variations, so detection is limited¹. Though some CNVs, including indels and duplications, can be detected by WES, the technical limitation means that others are likely missed⁴. For example, Huntington’s is a disease caused by an SV and diagnosed based on CAG repeat expansion. Huntington’s would instead have to be confirmed through a test that specifically counts the number of CAG repeats in the HTT gene as it cannot be reliably detected by WES. Currently, there is no single method that identifies all types of structural variations, but WGS or chromosomal microarrays (CMA) may identify SVs more accurately than WES.
3. WES does not include the sequencing of non-coding intron regions.
   There may be functional variants in non-coding regions that regulate gene expression, such as enhancers and long-noncoding RNAs. However, these non-coding variants (NCVs), even if genetically identifiable, are not covered by WES and thus cannot be detected. For example, non-coding regulatory SNPs of RBM8A in combination with a coding variant explained the majority of patients affected with TAR syndrome⁵. While the exome can provide some inferential insight into the non-coding regions, whole genome association studies may be more suitable for accurate insight.

In 2023, 3billion have made significant progress! We successfully increased the depth-of-coverage for a substantial part of these regions.

Due to such limitations, additional testing may be required to capture missed regions, confirm detected variants, or look for elusive variants. Nevertheless, there is a key process that could increase the utility of WES. More communication between clinical and analysis entities to clarify phenotypic information used for variant prioritization can help narrow the clinical interpretation, making WES application more efficient and effective⁴.

Ultimately, there are various factors to consider when deciding which type of genetic testing is most fitting for a patient, such as the phase of diagnostic evaluation, symptoms and personal health history, affordability, and family history. Though there is no crystal ball to tell which method will work best for each patient affected by a complex genetic disease, there are some silver linings from the continuous advances in diagnostic technology and research for treatments to look forward to.

References

1. Goh, G. and Choi, M. Application of Whole Exome Sequencing to Identify Disease-Causing Variants in Inherited Human Diseases. Genomics & Informatics 10(4), 214-219 (2012).
2. Parla, J.S., Iossifov, I., Grabill, I. et al. A comparative analysis of exome capture. Genome Biol 12, R97 (2011).
3. Meienberg, J., Bruggmann, R., et al. Clinical sequencing: is WGS the better WES? Hum Genet. 135, 359–362 (2016).
4. Burdick, K.J., Cogan, J.D. et al. Limitations of exome sequencing in detecting rare and undiagnosed diseases. Am J Med Genet A. 182(6), 1400–1406 (2020).
5. Zhang, F. and Lupski, J.R. Non-coding genetic variants in human disease. Hum Mol Genet. 15; 24(R1), R102–R110 (2015).