Using synthetic chromosome controls to evaluate the sequencing of difficult regions within the human genome

Next-generation sequencing (NGS) can identify mutations in the human genome that cause disease and has been widely adopted in clinical diagnosis. However, the human genome contains many polymorphic, low-complexity, and repetitive regions that are difficult to sequence and analyze. Despite their difficulty, these regions include many clinically important sequences that can inform the treatment of human diseases and improve the diagnostic yield of NGS.

To evaluate the accuracy by which these difficult regions are analyzed with NGS, a team led by researchers at the Garvan Institute of Medical Research built an in silico decoy chromosome, along with corresponding synthetic DNA reference controls, that encode difficult and clinically important human genome regions, including repeats, microsatellites, HLA genes, and immune receptors. These controls provide a known ground-truth reference against which to measure the performance of diverse sequencing technologies, reagents, and bioinformatic tools. Using this approach, the researchers provide a comprehensive evaluation of short- and long-read sequencing instruments, library preparation methods, and software tools and identify the errors and systematic bias that confound our resolution of these remaining difficult regions.

In silico chromosome design and experimental workflow

a The in silico decoy chromosome is designed to incorporate difficult and clinically important features of the human genome. The chromosome is divided into (i) small variants (including SNPs and indels) and simple repeats, (ii) structural variants (including large insertions, deletions, duplications, inversions, and translocations), (iii) HLA genes, and (iv) immune receptor genes. b The schematic diagram illustrates the use of synthetic DNA controls (sequins) and the in silico chromosome during the NGS workflow (upper panel). The range of experimental variables evaluated within this study, including difficult genetic features, library preparation methods, sequencing instruments, and bioinformatic tools, are indicated (lower panel)

This study provides an analytical validation of diagnosis using NGS in difficult regions of the human genome and highlights the challenges that remain to resolve these difficult regions.