Determining Performance Metrics for Targeted Next-Generation Sequencing Panels Using Reference Materials

Metagenomics-enabled microbial surveillance

Lessons learnt from the COVID-19 pandemic include increased awareness of the potential for zoonoses and emerging infectious diseases that can adversely affect human health. Although emergent viruses are currently in the spotlight, we must not forget the ongoing toll of morbidity and mortality owing to antimicrobial resistance in bacterial pathogens and to vector-borne, foodborne and waterborne diseases. Population growth, planetary change, international travel and medical tourism all contribute to the increasing frequency of infectious disease outbreaks. Surveillance is therefore of crucial importance, but the diversity of microbial pathogens, coupled with resource-intensive methods, compromises our ability to scale-up such efforts. Innovative technologies that are both easy to use and able to simultaneously identify diverse microorganisms (viral, bacterial or fungal) with precision are necessary to enable informed public health decisions. Metagenomics-enabled surveillance methods offer the opportunity to improve detection of both known and yet-to-emerge pathogens.

Congenital Hyperinsulinism: Current Laboratory-Based Approaches to the Genetic Diagnosis of a Heterogeneous Disease

Congenital hyperinsulinism is characterised by the inappropriate release of insulin during hypoglycaemia. This potentially life-threatening disorder can occur in isolation, or present as a feature of syndromic disease. Establishing the underlying aetiology of the hyperinsulinism is critical for guiding medical management of this condition especially in children with diazoxide-unresponsive hyperinsulinism where the underlying genetics determines whether focal or diffuse pancreatic disease is present. Disease-causing single nucleotide variants affecting over 30 genes are known to cause persistent hyperinsulinism with mutations in the KATP channel genes (ABCC8 and KCNJ11) most commonly identified in children with severe persistent disease. Defects in methylation, changes in chromosome number, and large deletions and duplications disrupting multiple genes are also well described in congenital hyperinsulinism, further highlighting the genetic heterogeneity of this condition. Next-generation sequencing has revolutionised the approach to genetic testing for congenital hyperinsulinism with targeted gene panels, exome, and genome sequencing being highly sensitive methods for the analysis of multiple disease genes in a single reaction. It should though be recognised that limitations remain with next-generation sequencing with no single application able to detect all reported forms of genetic variation. This is an important consideration for hyperinsulinism genetic testing as comprehensive screening may require multiple investigations.

Interplay between probe design and test performance: overlap between genomic regions of interest, capture regions and high quality reference calls influence performance of WES-based assays

Whole exome sequencing (WES)-based assays undergo rigorous validation before being implemented in diagnostic laboratories. This validation process generates experimental evidence that allows laboratories to predict the performance of the intended assay. The NA12878 Genome in a Bottle (GIAB) HapMap reference sample is commonly used for validation in diagnostic laboratories. We investigated what data points should be taken into consideration when validating WES-based assays using the GIAB reference in a diagnostic setting. We delineate specific factors that require special consideration and identify OMIM genes associated with diseases that may 'bypass' validation. Four replicates of the NA12878 sample were sequenced at the CHEO Genetics Diagnostic Laboratory on a NextSeq 500; the data were analyzed using the bcbio_nexgen v1.1.2 pipeline. The hap.py validation engine, Real Time Genomics vcfeval tool, and high confidence (HC) variant calls in HC regions available for the GIAB sample were used to validate the obtained variant calls. The same validation process was then used to evaluate variant calls obtained for the same sample by two other clinical diagnostic laboratories. We showed that variant calls in NA12878 can be confidently measured only in the regions that intersect between the GIAB HC regions and the target regions of exome capture. Of the 4139 (as of October 2019) OMIM genes associated with a phenotype and having a known molecular basis of disease, 84 were fully outside of the GIAB HC regions and many of the remaining OMIM genes were only partially covered by the HC regions. A significant proportion of variants identified in the NA12878 sample outside of the HC regions have unknown (UNK) status due to the absence of HC reference alleles. Verification of such calls is possible either by an alternative truth set or by orthogonal testing. Similarly, many variants outside of exome capture regions, if not accounted for, will be deemed false negatives due to insufficient probe coverage. Our results demonstrate the importance of the intersection between genomic regions of interest, capture regions, and the high confidence regions. If not considered, false and ambiguous variant calls could have a negative impact on diagnostic accuracy of the intended WES-based diagnostic assay and increase the need for confirmatory testing. To enable laboratories to identify 'problematic' regions and optimize validation efforts, we have made our VCF and BED files available in UCSC Genome Browser: NA12878 WES Benchmark. Relevant genes and genome annotations are evolving, we implemented a general purpose algorithm to cross-reference OMIM genes with the genomic regions of interest that can be applied to capture genes/regions outside HC regions (see repository of data material section).

A robust benchmark for detection of germline large deletions and insertions

New technologies and analysis methods are enabling genomic structural variants (SVs) to be detected with ever-increasing accuracy, resolution, and comprehensiveness. To help translate these methods to routine research and clinical practice, we developed the first sequence-resolved benchmark set for identification of both false negative and false positive germline large insertions and deletions. To create this benchmark for a broadly consented son in a Personal Genome Project trio with broadly available cells and DNA, the Genome in a Bottle (GIAB) Consortium integrated 19 sequence-resolved variant calling methods from diverse technologies. The final benchmark set contains 12745 isolated, sequence-resolved insertion (7281) and deletion (5464) calls ≥50 base pairs (bp). The Tier 1 benchmark regions, for which any extra calls are putative false positives, cover 2.51 Gbp and 5262 insertions and 4095 deletions supported by ≥1 diploid assembly. We demonstrate the benchmark set reliably identifies false negatives and false positives in high-quality SV callsets from short-, linked-, and long-read sequencing and optical mapping.

Multilaboratory Assessment of a New Reference Material for Quality Assurance of Cell-Free Tumor DNA Measurements

We conducted a multilaboratory assessment to determine the suitability of a new commercially available reference material with 40 cancer variants in a background of wild-type DNA at four different variant allele frequencies (VAFs): 2%, 0.50%, 0.125%, and 0%. The variants include single nucleotides, insertions, deletions, and two structural variations selected for their clinical importance and to challenge the performance of next-generation sequencing (NGS) methods. Fragmented DNA was formulated to simulate the size distribution of circulating wild-type and tumor DNA in a synthetic plasma matrix. DNA was extracted from these samples and characterized with different methods and multiple laboratories. The various extraction methods had differences in yield, perhaps because of differences in chemistry. Digital PCR assays were used to measure VAFs to compare results from different NGS methods. Comparable VAFs were observed across the different NGS methods. This multilaboratory assessment demonstrates that the new reference material is an appropriate tool to determine the analytical parameters of different measurement methods and to ensure their quality assurance.