Optical genome mapping (OGM), an emerging next-generation cytogenetics tool enables a comprehensive analysis of genomic aberrations. Recently, OGM has been shown to identify (genome-wide) all classes of SVs including, copy number changes, deletions, duplications, balanced/unbalanced genomic rearrangements (insertions, inversions, and translocations), repeat array expansions/contractions, and absence of heterozygosity (AOH). In the same assay, a concurrent or stepwise data analysis pipeline allows for sizing pathogenic FMR1 repeat expansions (FXS) as well as D4Z4 repeat contractions (FSHD1). Here, we perform a multi-site validation study with 331 independent flow cells runs (including replicates), representing 202 unique retrospective clinical samples to determine the robustness and sensitivity of OGM in detecting SVs associated with constitutional genetic disorders compared to standard of care (SOC) cytogenomic technologies. The data were analyzed by laboratory analysts at each site (5 sites) in a blinded fashion using ACMG guidelines for SV interpretation and reviewed by expert board-certified laboratory directors to assess concordance with SOC testing results. Of the 331 datasets, 219 were assessed for concordance at the time of abstract submission, which included samples that harbored known variants, of which 214/219 were detected by OGM resulting in a concordance of 97.7% compared to SOC testing. OGM demonstrated 100% reproducibility in detecting pathogenic SVs in 47 samples that were run in replicates. Additionally, OGM has been successful in identifying novel variants in undiagnosed cases. One specific example is a 5.9 kbp insertion in the RORB gene, a gene involved in causing symptoms matching the case. In conclusion, we demonstrated that OGM can detect all classes of SVs in a single assay, including pathogenic FMR1 repeat expansions, and D4Z4 repeat contractions (FSHD1 cases). Overall, this study demonstrated OGM as a potential tier1 cytogenetic testing platform to replace existing SOC cytogenomic methods for postnatal chromosome diagnosis.

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DOI: https://doi.org/10.1016/j.cancergen.2022.05.009

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