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WES vs WGS Sequencing: Pros and Cons



Wes vs wgs sequencing: pros and cons


Massively parallel DNA-sequencing has created a new era for genomic technology, enabling the sequencing of thousands to millions of DNA molecules simultaneously. Remarkable advancement has taken place in the fields of personalized medicine, genetics, and clinical diagnostics. The evolution of sequencing technology has created innumerable opportunities and applications in the field of biological sciences and has dramatically reduced sequencing costs. Furthermore, the software to interpret and analyze DNA-seq data has also improved (Berglund, Kiialainen, & Syvänen, 2011).

Routine clinical practices have begun to incorporate whole-genome sequencing (WGS) and whole-exome sequencing (WES). The applications of WES and WGS has already accelerated the discovery and diagnosis of genetic disorders (Bick & Dimmock, 2011).

Although sequencing technologies have become cost and time-efficient, many researchers continue to prefer WES over WGS. The exome is considered a blueprint of an organism and tends to hold all the answers. Recently, a debate has been raised that this protein-coding entity does not hold all the answers. Mutations outside the protein-coding regions can equally affect the phenotype of an organism by affecting the gene activity.

Whole exome sequencing vs. Whole genome sequencing

WES is a next-generation sequencing (NGS) technique for sequencing the protein-coding regions of the genome, collectively called an exome, which only constitutes 1% of the genome. WGS, on the other hand, is a technique for sequencing the complete DNA sequence of an organism at a single time.


Sequencing techniques and platforms for WES and WGS are more or less the same except for one additional step required in WES called the target enrichment. Target enrichment is done prior to sequencing in order to capture the genomic region (exome) selectively. Techniques for target enrichment includes solid-phase hybridization capture and liquid-phase hybridization (Teer & Mullikin, 2010).

DNA-seq data analysis

After the completion of the sequencing, DNA-seq analysis is performed. DNA-seq analysis includes a variety of bioinformatics assessments, which are more or less the same for both WGS and WES. Somatic and germline mutations can also be identified that may help in the diagnosis of a disease or genetic condition. There are many free online tools and software packages able to perform DNA-seq analysis, though most require some programming and bioinformatics knowledge (Grada & Weinbrecht, 2013).

Nature of study: when to use WGS and WES?

Non-exonic regions occupy about 98.8% of the genome, but are poorly characterized and understood. Therefore, WGS is mostly carried out in research-based DNA-seq analysis studies to better understand these non-exonic regions of the genome.

Clinicians, on the other hand, consider WES a more favorable technique for the diagnosis of diseases at a genetic level. Clinicians utilize WES to identify the gene mutations responsible for a wide variety of disorders, including intellectual disabilities, cancer, immunological diseases, and others (Angelo DePalma, 2018). WES, however, can overlook incidental mutations responsible for rare disorders. These disorders can cause a potential phenotypic disruption in an individual’s life. Therefore, WGS is usually conducted to investigate these rare disorders (Grada & Weinbrecht, 2013).

Cost and time

The estimated cost of WES ranges from 5 to ,169 and it is mostly used in clinical investigations to save money and time. Previously, the estimated cost of WGS was $15,146 in 2013 for an unspecified platform, but the recent launch of the Illumina HiSeq X Ten sequencing platform has substantially reduced WGS cost to $1,906. WES doesn’t have a price advantage over WGS anymore for the study of lower organisms (e.g., bacteria); however, in clinical studies, WES still takes the lead over WGS (Schwarze, Buchanan, Taylor, & Wordsworth, 2018).


  • Whole exome sequencing (WES)

A phenotype can be a result of a single mutation (Mendelian disorders) or multiple mutations in a genome. These mutations usually occur in an exome, protein-coding regions of the genome, but non-exonic mutations can also affect gene activity. WES potentially misses the non-exonic variations, and it also fails to capture the incidental mutations.

  • Whole-genome sequencing (WGS)

Most of the non-exonic regions in a genome are poorly characterized and understood. Therefore, data generated by WGS is complex and difficult to interpret. The cost and time barrier have been recently lifted with the launch of Illumina HiSeq X Ten sequencing platform.

Ultimately, both WES and WGS have strong proponents. It is difficult to say one is better or worse than the other, however, as their utility is highly dependent on the purpose of a study or experiment. What is clear is that both whole-genome and whole-exome sequencing are highly popular next generation sequencing technologies that have helped researchers better understand the interplay between genetics and disease.

Amit U Sinha, PhD (Machine Learning and Genomics) is the founder and CEO of Basepair, an online NGS analysis platform. Amit is an expert in genomics and bioinformatics, with over a decade of experience in the field. Prior to founding Basepair, Amit worked as an investigator at Memorial Sloan Kettering Cancer Center. Additionally, he has held research faculty positions at the Dana Farber Cancer Institute and Harvard Medical School. Amit’s work focuses on leveraging technology to improve healthcare research by enabling scientists to make sense of big data quickly and accurately.


Bick, D., & Dimmock, D. (2011). Whole exome and whole genome sequencing. Current Opinion in Pediatrics, 23(6), 594–600.

Grada, A., & Weinbrecht, K. (2013). Next-Generation Sequencing : Methodology and Application. Journal of Investigative Dermatology, 133(8), e11-4.

Guaragna, M. S., de Brito Lutaif, A. C. G., de Souza, M. L., Maciel-Guerra, A. T., Belangero, V. M. S., Guerra-Júnior, G., & de Mello, M. P. (2019). Promises and pitfalls of whole-exome sequencing exemplified by a nephrotic syndrome family. Molecular Genetics and Genomics, (0123456789).

Schuster, S. C. (2008). Next-generation sequencing transforms today’s biology. Nature Methods, 5(1), 16–18.

Teer, J. K., & Mullikin, J. C. (2010). Exome sequencing : the sweet spot before whole genomes. 19(2), 145–151.

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