Replicate exome-sequencing in a multiple-generation family: improved interpretation of next-generation sequencing...

Whole-exome sequencing (WES) is rapidly evolving into a tool of choice for rapid, and inexpensive identification of molecular genetic lesions within targeted regions of the human genome. While biases in WES coverage of nucleotides in targeted regions are recognized, it is not well understood how repetition of WES improves the interpretation of sequencing results in a clinical diagnostic setting.

To address this, we compared independently generated exome-capture of six individuals from three-generations sequenced in triplicate. This generated between 48x-86x mean target depth of high-quality mapped bases (>Q20) for each technical replicate library. Cumulatively, we achieved 179 - 208x average target coverage for each individual in the pedigree. Using this experimental design, we evaluated stochastics in WES interpretation, genotyping sensitivity, and accuracy to detect de novo variants.

In this study, we show that repetition of WES improved the interpretation of the capture target regions after aggregating the data (93.5 - 93.9 %). Compared to 81.2 - 89.6 % (50.2-55.4 Mb of 61.7 M) coverage of targeted bases at ≥20x in the individual technical replicates, the aggregated data covered 93.5 - 93.9 % of targeted bases (57.7 - 58.0 of 61.7 M) at ≥20x threshold, suggesting a 4.3 - 12.7 % improvement in coverage. Each individual's aggregate dataset recovered 3.4 - 6.4 million bases within variable targeted regions. We uncovered technical variability (2-5 %) inherent to WES technique. We also show improved interpretation in assessing clinically important regions that lack interpretation under current conditions, affecting 12-16 of the 56 genes recommended for secondary analysis by American College of Medical Genetics (ACMG). We demonstrate that comparing technical replicate WES datasets and their derived aggregate data can effectively address overall WES genotyping discrepancies.

We describe a method to evaluate the reproducibility and stochastics in exome library preparation, and delineate the advantages of aggregating the data derived from technical replicates. The implications of this study are directly applicable to improved experimental design and provide an opportunity to rapidly, efficiently, and accurately arrive at reliable candidate nucleotide variants.