Diagnosis of fetal submicroscopic chromosomal abnormalities in failed array CGH samples: copy number by sequencing as an alternative to microarrays for invasive fetal testing.

Abstract

Array comparative genomic hybridization (CGH) has become the technology of choice for high-resolution prenatal whole genome analysis. Limitations of microarrays are mainly related to the analog nature of the analysis, and poor-quality DNA can result in failed quality metrics with these platforms. We examined a cohort of abnormal fetuses with failed array CGH results using a next-generation sequencing algorithm, CNV-Seq. We assessed the ability of the platform to handle suboptimal prenatal samples and generate interpretable molecular karyotypes. Nine samples obtained from abnormal fetuses and one from a normal control fetus were sequenced using an Illumina GAIIx. A segmentation algorithm for sequencing data was used to determine regional copy number data on the sequencing datasets. Phred quality scores were satisfactory for analysis of all samples. CNV-Seq identified both large- and small-scale abnormalities in the cohort, and normal results were obtained for fetuses for which microarray data were previously uninterpretable. No variants of uncertain significance were detected. Analysis of the digital sequencing datasets offered some advantages over array CGH output. Using next-generation sequencing for the detection of genomic copy number variants may be advantageous for poor-quality, invasively-acquired prenatal samples. CNV-Seq could become a potential alternative to array CGH in this setting.