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Updated: Jun 5, 2025

Chromosome Screening of Human Preimplantation Embryos by Using Spent Culture Medium: Sample Collection and Chromosomal Ploidy Analysis
Published on: September 7, 2021
Comprehensive analysis of chromosome abnormalities by chromosome conformation based karyotyping (C-MoKa) in patients
Xiao Bao1, Yuxia Yang2, Wenbin Niu1
1Center for Reproductive Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China; Henan Key Laboratory of Reproduction and Genetics, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
Background:
Chromosome abnormalities are a leading cause of conception failure and pregnancy loss. While traditional cytogenetics technologies like karyotyping have been helpful in identifying structural variations (SVs), they face challenges in detecting complex rearrangements and cryptic structures. In this study, we developed a new method called chromosome conformation based karyotyping (C-MoKa) to comprehensively detect different types of chromosomal abnormalities in patients with conception failure and pregnancy loss.
Methods:
A total of 70 clinical samples exhibiting known results of SVs, mosaic aneuploidies, copy number variations (CNVs) and uniparental disomy (UPD) were included in our cohort and underwent C-MoKa analysis. The results obtained from different techniques, including karyotyping, CNV-seq, and CMA were compared and analyzed.
Results:
Distinct chromosomal conformation patterns of various variations were observed and analyzed in clinical samples. Our C-MoKa method not only validated all the findings of karyotyping, CNV-seq and CMA, but also provided more detailed results. It demonstrated superior fragment resolution (<500 Kb) and more precise breakpoints (>100 kb). Moreover, C-MoKa showed higher sensitivity in decoding intricate rearrangements in a single test.
Conclusions:
Our results highlight the potential utility of C-MoKa in precisely unraveling SVs, mosaic aneuploidies, CNVs, and UPD in clinical settings, which can significantly impact further clinical decision-making.
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