Abstract
Next generation sequencing has disrupted genetic testing, allowing far more scope in the tests applied. The appropriate sections of the genome to be tested can now be readily selected, from single mutations to whole-genome sequencing. One product offering within this spectrum are focused exomes, targeting ~5,000 genes know to be implicated in human disease. These are designed to offer a flexible platform offering high diagnostic yield with a reduction in sequencing requirement compared to whole exome sequencing. Here, we have undertaken sequencing of control DNA samples and compare two kits, the Illumina TruSight One and the Agilent SureSelect Focused Exome. Characteristics of the kits are comprehensively evaluated. Despite the larger design region of the Agilent kit, we find that the Illumina kit performs better in terms of gene coverage, as well as coverage of clinically relevant loci. We provide exhaustive coverage statistics for each kit to aid the assessment of their suitability and provide read data for control DNA samples to allow for bioinformatic benchmarking by users developing pipelines for these data.
Highlights
Generation sequencing has disrupted genetic testing, allowing far more scope in the tests applied
We assessed the biases in base composition along the reads, as biases in this composition can be introduced during DNA fragmentation[11,12,13,14]
Both the SureSelect Focused Exome kit (SSFE) and TruSight One kit (TSO) kits do exhibit a bias, TSO has a greater degree of deviation from the expected frequency in the first 20 bases of the read (p < 0.001, mean residual from 25% of 5.0% and 7.2% for SSFE and TSO respectively (Supplementary Figure 1); this is as expected owing to the enzymatic fragmentation for TSO
Summary
Generation sequencing has disrupted genetic testing, allowing far more scope in the tests applied. Pre-sequencing target capture, enriching a defined genomic region of interest, allows for the cost-effective application of NGS to patient samples, with a range of capture platforms available for this[4]. As with the use of any clinical testing methodology, it is essential that appropriate quality assurance procedures are in place prior to the utilisation of a method for diagnostics[7] This includes the validation of a tool, and verification that the tool is performing as expected[8,9]. A recent meta-analysis showed the diagnostic utility to be 42% for WGS and 38% or WES in studies published in 20172 This mere 4% difference in diagnostic rate highlights the increased density of pathogenic variants in the exome, whilst reflecting our ability to better interpret coding variants and assign pathogenicity to them[10]
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