Abstract
Optimal management of acutely ill infants with monogenetic diseases requires rapid identification of causative haplotypes. Whole-genome sequencing (WGS) has been shown to identify pathogenic nucleotide variants in such infants. Deletion structural variants (DSVs, >50 nt) are implicated in many genetic diseases, and tools have been designed to identify DSVs using short-read WGS. Optimisation and integration of these tools into a WGS pipeline could improve diagnostic sensitivity and specificity of WGS. In addition, it may improve turnaround time when compared with current CNV assays, enhancing utility in acute settings. Here we describe DSV detection methods for use in WGS for rapid diagnosis in acutely ill infants: SKALD (Screening Konsensus and Annotation of Large Deletions) combines calls from two tools (Breakdancer and GenomeStrip) with calibrated filters and clinical interpretation rules. In four WGS runs, the average analytic precision (positive predictive value) of SKALD was 78%, and recall (sensitivity) was 27%, when compared with validated reference DSV calls. When retrospectively applied to a cohort of 36 families with acutely ill infants SKALD identified causative DSVs in two. The first was heterozygous deletion of exons 1–3 of MMP21 in trans with a heterozygous frame-shift deletion in two siblings with transposition of the great arteries and heterotaxy. In a newborn female with dysmorphic features, ventricular septal defect and persistent pulmonary hypertension, SKALD identified the breakpoints of a heterozygous, de novo 1p36.32p36.13 deletion. In summary, consensus DSV calling, implemented in an 8-h computational pipeline with parameterised filtering, has the potential to increase the diagnostic yield of WGS in acutely ill neonates and discover novel disease genes.
Highlights
Mendelian diseases, in toto, consume substantial healthcare resources.[1,2,3] Recent advances in genomics technologies and computational analysis have yielded unprecedented progress towards understanding the relationship of genomic variation to infant morbidity and mortality.[4]
We report an initial application of SKALD for molecular is hybridised, and single nucleotide polymorphism (SNP) probe log ratios are used to detect copy number variants (CNV) gains or losses.[28]
Evaluation of BD and GS with four experimental whole-genome sequencing (WGS) replicates of NA12878 NA12878, a HapMap CEU trio proband[35] was chosen for experimental analysis of deletion SVs (DSV) detection methods, as it had been extensively sequenced by the 1,000 genomes project (1KGP),[36] and has been selected as SV benchmark by the National Institutes of Standards and Technology.[37]
Summary
In toto, consume substantial healthcare resources.[1,2,3] Recent advances in genomics technologies and computational analysis have yielded unprecedented progress towards understanding the relationship of genomic variation to infant morbidity and mortality.[4] Genetic diseases, chromosomal aberrations and congenital malformations are the leading cause of infant mortality in the US.[5,6,7] By detecting disease causing single nucleotide (nt) variants (SNVs) and small nucleotide (o 50 nt) insertions and deletions (indels), rapid whole-genome sequencing (WGS) has accelerated and improved the sensitivity for the diagnosis of genetic illness in neonates.[8,9,10] We have recently shown that over one half of acutely ill newborns with likely genetic diseases, enroled from a neonatal intensive care unit (NICU), were diagnosed using rapid WGS, with a median time of 23 days between consent and reporting of results.[9,10] disease-causative alleles are not always nucleotide variants
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