Inferring chromosome segregation error stage and crossover in trisomic disorders with application to Down syndrome

Zhenhua Li (), Wenjian Yang, Gang Wu, Ti-Cheng Chang, Zhongshan Cheng, Meenakshi Devidas, Mary Shago, Andrew J. Carroll, Nyla A. Heerema, Julie M. Gastier-Foster, Brent L. Wood, Lauren Sanclemente, Elizabeth A. Raetz, Stephen P. Hunger, Mignon L. Loh, Eleanor Feingold, Tracie C. Rosser, Emily G. Allen, Stephanie L. Sherman, Karen R. Rabin, Philip J. Lupo and Jun J. Yang ()
Additional contact information
Zhenhua Li: St. Jude Children’s Research Hospital
Wenjian Yang: St. Jude Children’s Research Hospital
Gang Wu: St. Jude Children’s Research Hospital
Ti-Cheng Chang: St. Jude Children’s Research Hospital
Zhongshan Cheng: St. Jude Children’s Research Hospital
Meenakshi Devidas: St. Jude Children’s Research Hospital
Mary Shago: University of Toronto
Andrew J. Carroll: University of Alabama at Birmingham
Nyla A. Heerema: The Ohio State University
Julie M. Gastier-Foster: The Ohio State University
Brent L. Wood: University of Southern California
Lauren Sanclemente: Baylor College of Medicine
Elizabeth A. Raetz: New York University Langone Medical Center
Stephen P. Hunger: Children’s Hospital of Philadelphia
Mignon L. Loh: University of Washington
Eleanor Feingold: Oregon State University
Tracie C. Rosser: Emory University
Emily G. Allen: Emory University
Stephanie L. Sherman: Emory University
Karen R. Rabin: Baylor College of Medicine
Philip J. Lupo: Baylor College of Medicine
Jun J. Yang: St. Jude Children’s Research Hospital

Nature Communications, 2025, vol. 16, issue 1, 1-9

Abstract: Abstract Errors in chromosome segregation during gametogenesis, such as nondisjunction (NDJ) errors, have severe consequences in human reproduction, and a better understanding of their etiology is of fundamental interest in genetics. Mapping NDJ errors to meiotic/mitotic stages typically requires proband-parent comparison, limiting its applicability. Herein, we develop Mis-segregation Error Identification through Hidden Markov Models (MeiHMM), a method for inferring NDJ error stage and crossover events based on only genomic data of trisomic probands. Guided by triallelic genotype/haplotype configurations, MeiHMM discerns the allelic origin at each locus, which informs NDJ error during gamete formation, without identifying the parental origin of the trisomy. In 152 Down syndrome (DS) cases, MeiHMM achieved an accuracy of 96.1% in classifying NDJ errors, with a sensitivity of 91.6% in crossover identification, compared to proband-parents trio analysis. 17% of Meiosis II errors were misclassified as Meiosis I, mainly due to small proximal crossover events. Applying MeiHMM to 509 children with DS-associated childhood leukemia, we demonstrate that NDJ error is associated with the age of disease onset, somatic genomic abnormalities, and prognosis. Thus, MeiHMM is an effective method for trisomic NDJ error classification and crossover identification that can be applied broadly to study the etiology of congenital aneuploidy conditions.

Date: 2025
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DOI: 10.1038/s41467-025-61413-w

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