OMKar automates genome karyotyping using optical maps to identify constitutional abnormalities

Abstract

The whole-genome karyotype refers to the sequence of large chromosomal segments comprising an individual's genotype. Karyotype analysis, which includes identifying aneuploidies and structural rearrangements, is essential for understanding genetic risk factors, informing diagnosis and treatment, and guiding genetic counseling in constitutional disorders. The current karyotyping standard relies on microscopic chromosome examination, a complex and expertise-dependent process with megabase-scale resolution. Optical genome mapping (OGM) technology offers an efficient approach to detect large-scale genomic lesions. Here, we introduce OMKar, a computational method that generates virtual karyotypes from OGM data. OMKar integrates structural variants (SVs) and copy number (CN) variants into a breakpoint graph representation. It re-estimates CNs using integer linear programming to enforce CN balance and then identifies constrained Eulerian paths corresponding to full chromosome structures. OMKar is evaluated on 38 whole-genome simulations of constitutional disorders, achieving 88% precision and 95% recall for SV concordance and a 95% Jaccard score for CN concordance. We further apply OMKar to 154 clinical samples including 50 prenatal, 41 postnatal, and 63 parental genomes collected across 10 sites. It correctly reconstructs the karyotype in 144 cases, including 25 of 25 aneuploidies, 32 of 32 balanced translocations, and 72 of 82 unbalanced rearrangements. Identified disorders include cri-du-chat, Wolf–Hirschhorn, Prader–Willi, Down, and Turner syndromes. Notably, OMKar uncovers plausible genetic mechanisms in five previously unexplained cases. These results demonstrate the accuracy and utility of OMKar for OGM-based constitutional karyotyping.