Whole Exome Sequencing in Inborn Errors of Immunity

Use the Power but Mind the Limits

Giorgia Bucciol; Erika Van Nieuwenhove; Leen Moens; Yuval Itan; Isabelle Meyts


Curr Opin Allergy Clin Immunol. 2017;17(6):421-430. 

In This Article

Next-generation Sequencing

NGS is a high-throughput sequencing method in which thousands or millions of small DNA fragments are sequenced in parallel.[2] Starting from the patient's genomic DNA, a sequencing library is prepared by random fragmentation of the DNA into short strands that are then fused with adaptors. These fragments are amplified and sequenced in parallel multiple times, usually at least 20 times for any nucleotide, to attain sufficient read depth. The obtained sequences are then mapped to a reference human genome and the differences between the patient's DNA and the reference are 'called' as variants (Figure 1). A read depth of at least 20 is essential to discriminate sequencing errors from true variants. These variants must be analyzed in the setting of the patient's clinical and cellular phenotype and pedigree to disregard irrelevant variants and to instead detect known or novel mutations in known disease-causing genes or in potentially novel candidate genes.[5]

Figure 1.

The scheme illustrates the process of WGS and WES. The files that are finally derived from the analysis are of three types: FASTQ files, including all the raw data; BAM files, for the alignment to the reference sequence; and VCF files, subsequently convertible to Excel files, for the variant calling. WES, whole exome sequencing; WGS, whole genome sequencing. Adapted with permission [5*].

NGS can be used to sequence the entire genome [whole genome sequencing (WGS)], a targeted panel such as the WES, or a more limited set of genes of interest. The exome is defined as all the exons for about 20 000 protein-coding genes and for microRNA, small nucleolar RNA, and large intergenic noncoding RNA genes, constituting about 1% of the human genome.[10] In the construction of the DNA library, WES and panel sequencing require enrichment in exons through hybridization with target-specific probes and PCR amplification of the selected regions.[11] This additional step generates bias at different levels: as the enrichment process is not perfectly homogeneous and there is an a priori reference bias with the choice of probes, some exons are underrepresented or missing in the library; moreover, the PCR amplification step can introduce errors in the sequences of nucleotides because of polymerase errors, guanine–cytosine related errors, stochastic errors and template switch errors.[5,12] Accordingly, WGS was shown to be more powerful than WES for detecting exome variants (single nucleotide variants) as well as small insertions/deletions (indels) and copy number variations (CNVs). WGS provides a much more uniform distribution of sequencing-quality parameters and a more homogeneous coverage of the genome.[13]