Whole-genome sequencing is more powerful than whole-exome sequencing for detecting exome variants

Abstract

We compared whole-exome sequencing (WES) and whole-genome sequencing (WGS) in six unrelated individuals. In the regions targeted by WES capture (81.5% of the consensus coding genome), the mean numbers of single-nucleotide variants (SNVs) and small insertions/deletions (indels) detected per sample were 84,192 and 13,325, respectively, for WES, and 84,968 and 12,702, respectively, for WGS. For both SNVs and indels, the distributions of coverage depth, genotype quality, and minor read ratio were more uniform for WGS than for WES. After filtering, a mean of 74,398 (95.3%) high-quality (HQ) SNVs and 9,033 (70.6%) HQ indels were called by both platforms. A mean of 105 coding HQ SNVs and 32 indels was identified exclusively by WES whereas 692 HQ SNVs and 105 indels were identified exclusively by WGS. We Sanger-sequenced a random selection of these exclusive variants. For SNVs, the proportion of false-positive variants was higher for WES (78%) than for WGS (17%). The estimated mean number of real coding SNVs (656 variants, ∼3% of all coding HQ SNVs) identified by WGS and missed by WES was greater than the number of SNVs identified by WES and missed by WGS (26 variants). For indels, the proportions of false-positive variants were similar for WES (44%) and WGS (46%). Finally, WES was not reliable for the detection of copy-number variations, almost all of which extended beyond the targeted regions. Although currently more expensive, WGS is more powerful than WES for detecting potential disease-causing mutations within WES regions, particularly those due to SNVs.

Keywords: Mendelian disorders; exome; genetic variants; genome; next-generation sequencing.

Fig. 1.

Distribution of the three main quality parameters for the variations detected by WES or WGS. (A) Coverage depth (CD), (B) genotype quality (GQ) score, and (C) minor-read ratio (MRR). For each of the three parameters, we show the average over the six WES (red) and the six WGS (turquoise) samples in SNVs (Left), insertions (Center), and deletions (Right).

Fig. 2.

Diagram of the losses of single nucleotide variants (SNVs) at various levels associated with the use of WES. (A) Exons that were covered by the Agilent Sure Select Human All Exon kit 71 Mb (V4 + UTR) with the 50-bp flanking regions. Exons fully covered are represented by boxes filled entirely in red; exons partly covered, by boxes filled with red stripes; and exons not covered at all, by white boxes. Numbers are shown in Table 1. Exons from protein-coding genes include exons encoding exclusively or partially UTRs, as well as exons mapping entirely to coding regions. (B) Number of high-quality coding SNVs called by WES and WGS (white box), by WES exclusively (red box), or by WGS exclusively (turquoise box). Details for the SNVs called exclusively by one method are provided below the figure. TRUE, estimate based on SNVs detected by Sanger sequencing; FALSE, estimate based on SNVs that were not detected by Sanger sequencing (Table 2). Darker boxes (red, gray, or turquoise) represent homozygous SNVs. Lighter boxes (red, gray, or turquoise) represent heterozygous SNVs.