Biop-C enables genome-wide detection of balanced and unbalanced rearrangements in preimplantation human embryos

Preimplantation genetic testing for structural rearrangements (PGT-SR) is critical for embryo selection. Most advanced PGT-SR platforms rely on sequence- or marker-based analysis near chromosomal breakpoints, which is costly, labor-intensive, and time-consuming. As a result, clinical practice often defaults to using PGT-A, a platform that cannot detect balanced rearrangements affecting the offspring's reproductive potential. In this study, we introduce Biop-C, a Hi-C–based technique enabling the comprehensive detection of both unbalanced and balanced translocations, including Robertsonian ones, as well as copy number variations (CNV). By developing custom algorithms for translocation detection, we achieved high accuracy in embryo and biopsy samples. We show that using machine-learning-based approaches allows detecting CNVs using low-coverage Hi-C without control euploid human embryos, which are typically unavailable. In a cohort of over 100 samples, Biop-C delivered ploidy status concordant with standard PGT for 93% of embryos and 76% re-biopsies. Out of 36 samples derived from patients carrying balanced chromosomal rearrangements, Biop-C correctly identified 83% translocations: 15 unbalanced and 4 balanced. Notably, Biop-C identified an unbalanced translocation t(18;21) in an embryo derived from a couple with a previously undiagnosed parental translocation 46,XY,t(18;21)(q22.1;q21.3), demonstrating its diagnostic value. These findings establish Biop-C as a powerful PGT-SR approach for distinguishing between normal and balanced embryos, with significant implications for embryo selection and genetic counseling in IVF.