Detection of structural mosaicism from targeted and whole-genome sequencing data

Abstract

Structural mosaic abnormalities are large post-zygotic mutations present in a subset of cells and have been implicated in developmental disorders and cancer. Such mutations have been conventionally assessed in clinical diagnostics using cytogenetic or microarray testing. Modern disease studies rely heavily on exome sequencing, yet an adequate method for the detection of structural mosaicism using targeted sequencing data is lacking. Here, we present a method, called MrMosaic, to detect structural mosaic abnormalities using deviations in allele fraction and read coverage from next-generation sequencing data. Whole-exome sequencing (WES) and whole-genome sequencing (WGS) simulations were used to calculate detection performance across a range of mosaic event sizes, types, clonalities, and sequencing depths. The tool was applied to 4911 patients with undiagnosed developmental disorders, and 11 events among nine patients were detected. For eight of these 11 events, mosaicism was observed in saliva but not blood, suggesting that assaying blood alone would miss a large fraction, possibly >50%, of mosaic diagnostic chromosomal rearrangements.

Next Generation Sequencing Methods for Diagnosis of Epilepsy Syndromes

“…Stosser et al ( 2017 ) were able to detect mosaicism in epilepsy patients through gene panels and WES with the sequencing depth of mosaic variants ranging from 42X to 2574X. In addition, King et al developed a method for detecting mosaicism (MrMosaic) (King et al, 2017 ) and determined the accuracy for detecting mosaicism in targeted NGS (gene panels and WES) and WGS increased with sequencing depth. An example of this is the detection of heteroplasmic variants in mtDNA sequences via WGS for epilepsy syndromes (Ding et al, 2015 ; Smith, 2016 ).…”

Recurrent de novo mutations in neurodevelopmental disorders: properties and clinical implications

“…Recent reductions in cost and more rapid implementation due to improvements in bioinformatics have led to routine use of these assays for diagnostics and genetic testing, particularly for families with children affected with NDDs [ 19 ]. The transition from low-resolution microarray-based technology to high-resolution NGS platforms has dramatically accelerated NDD gene discovery [ 6 – 8 , 10 , 12 – 14 , 20 – 23 ] and facilitated the exploration of underexplored variant classes, such as DNMs, which was previously restricted to large copy number variants (CNVs) (Table 1 ) [ 24 – 35 ]. Moreover, NGS has enabled the curation of both common and rare genetic variation to create new population-based resources that have been paramount for the interpretation of variants and elucidation of key pathways and mechanisms underlying NDDs [ 36 – 39 ].…”

Next‐generation sequencing approaches and challenges in the diagnosis of developmental anomalies and intellectual disability

“…63 In parallel, cheaper technologies such synthetic long reads and optical mapping have been developed to efficiently detect SVs. 66,67 Another potential improvement in GS are bioinformatics tools and algorithms to detect triplet expansion, 37 retrotransposition events, 68 mosaic SVs, 69 or regulatory variants within non-coding regions such as promoters and enhancers, [70][71][72] or miRNA binding sites. 73 These improvements could increase the diagnostic yield of about 1% to 10%.…”