Copy-number variants in clinical genome sequencing: deployment and interpretation for rare and undiagnosed disease

Andrew M Gross,Krista Bluske,Stephen Tanner,Egor Dolzhenko,Vani Rajan,Subramanian S Ajay,Alka Malhotra,Bryan R Lajoie ,Aditi Chawla,Trilochan Sahoo,John W Belmont ,Erin Thorpe,Denise Perry ,Eric Roller,Alicia Scocchia,Julia Mceachern,R Tanner Hagelstrom,Alison J Coffey,Sergii Ivakhno,Shimul Chowdhury,Amirah Khouzam,Natasa Dzidic,Nicole Burns ,Michael A Eberle ,David Bentley ,Tina Hambuch,Carolyn M Brown ,Karine Hovanes,Ryan J Taft

doi:10.1038/s41436-018-0295-y

Abstract

PurposeCurrent diagnostic testing for genetic disorders involves serial use of specialized assays spanning multiple technologies. In principle, genome sequencing (GS) can detect all genomic pathogenic variant types on a single platform. Here we evaluate copy-number variant (CNV) calling as part of a clinically accredited GS test. MethodsWe performed analytical validation of CNV calling on 17 reference samples, compared the sensitivity of GS-based variants with those from a clinical microarray, and set a bound on precision using orthogonal technologies. We developed a protocol for family-based analysis of GS-based CNV calls, and deployed this across a clinical cohort of 79 rare and undiagnosed cases. ResultsWe found that CNV calls from GS are at least as sensitive as those from microarrays, while only creating a modest increase in the number of variants interpreted (~10 CNVs per case). We identified clinically significant CNVs in 15% of the first 79 cases analyzed, all of which were confirmed by an orthogonal approach. The pipeline also enabled discovery of a uniparental disomy (UPD) and a 50% mosaic trisomy 14. Directed analysis of select CNVs enabled breakpoint level resolution of genomic rearrangements and phasing of de novo CNVs. ConclusionRobust identification of CNVs by GS is possible within a clinical testing environment.

Highlights

Variation in DNA copy number is a well-described cause of human genetic disease.[1]
Note that while all cell lines contain pathogenic copy-number variant (CNV), which established the baseline for our sensitivity analysis, we examined all other CNVs detected in these samples by either microarray or clinical genome sequencing (cGS)
Genome sequencing (GS) CNV calling performance An assessment of 17 reference samples with reported pathogenic CNVs (Table S1) demonstrated that cGS had greater sensitivity to detect known CNVs compared with microarrays (86% vs. 64%, McNemar’s test P < 0.01, Methods, Table 1, Table S2) with the greatest difference in smaller (

Summary

Introduction

Variation in DNA copy number is a well-described cause of human genetic disease.[1]. Copy-number variants (CNVs) associated with human pathologies range from chromosomal aneuploidy, to microduplication and microdeletion syndromes, and include smaller structural variants (SVs) that affect single genes and exons.[1,2,3,4,5] Karyotype and microarray analyses have served as gold standards in molecular diagnostics for CNVs, but the increasing number and complexity of possible genomic changes requires testing that can simultaneously address the complete range of cytogenetic abnormalities and smaller SVs.Genome sequencing (GS) can be used to detect almost all classes of alleles. Approaches have been developed to enable CNV detection as a component of gene panel or exome sequencing analyses, which have improved diagnostic yield.[13,14,15] Despite this success, such targeted approaches have technical limitations arising from nonuniform sequencing depth, polymerase chain reaction (PCR) artifacts, GC bias, and a high variance in allele fraction.[16,17,18] In contrast, GS sequencing depth is predictable

Methods

Results

Conclusion