Copy Number Variant Detection with Low-Coverage Whole-Genome Sequencing Represents a Viable Alternative to the Conventional Array-CGH.

Marcel Kucharík,Tomáš Szemes,Gabriel Minárik,Michaela Hýblová,Jaroslav Budiš

doi:10.3390/diagnostics11040708

Marcel Kucharík, Tomáš Szemes + Show 3 more

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Copy number variations (CNVs) represent a type of structural variant involving alterations in the number of copies of specific regions of DNA that can either be deleted or duplicated. CNVs contribute substantially to normal population variability, however, abnormal CNVs cause numerous genetic disorders. At present, several methods for CNV detection are applied, ranging from the conventional cytogenetic analysis, through microarray-based methods (aCGH), to next-generation sequencing (NGS). In this paper, we present GenomeScreen, an NGS-based CNV detection method for low-coverage, whole-genome sequencing. We determined the theoretical limits of its accuracy and obtained confirmation in an extensive in silico study and in real patient samples with known genotypes. In theory, at least 6 M uniquely mapped reads are required to detect a CNV with the length of 100 kilobases (kb) or more with high confidence (Z-score > 7). In practice, the in silico analysis required at least 8 M to obtain >99% accuracy (for 100 kb deviations). We compared GenomeScreen with one of the currently used aCGH methods in diagnostic laboratories, which has mean resolution of 200 kb. GenomeScreen and aCGH both detected 59 deviations, while GenomeScreen furthermore detected 134 other (usually) smaller variations. When compared to aCGH, overall performance of the proposed GenemoScreen tool is comparable or superior in terms of accuracy, turn-around time, and cost-effectiveness, thus providing reasonable benefits, particularly in a prenatal diagnosis setting.

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Copy number variations (CNVs) represent a phenomenon in which sections of the genome are repeated while the number of repeats in the genome varies between individuals
Array-based comparative genomic hybridization delivers genome-wide coverage at a great resolution, even on the scale of dozens of kilobases (10–25 kb) [2]. This fact resulted in aCGH having been the gold standard in CNVs detection for several years
We present GenomeScreen—a low-coverage, whole-genome next-generation sequencing (NGS)-based CNV detection method and estimate its accuracy in theoretical and in silico settings

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Copy number variations (CNVs) represent a phenomenon in which sections of the genome are repeated while the number of repeats in the genome varies between individuals. Array-based comparative genomic hybridization (aCGH) delivers genome-wide coverage at a great resolution, even on the scale of dozens of kilobases (10–25 kb) [2]. This fact resulted in aCGH having been the gold standard in CNVs detection for several years. In prenatal diagnosis from amniotic fluid, micrograms of genomic DNA are typically needed to hybridize to an array. This can be accomplished either by time-consuming culturing taking up to two weeks, or by whole-genome amplification, which can introduce bias into the analysis. NGS provides a sensitive and accurate approach for the detection of the major types of genomic variations, including CNVs [4,5]

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