Prenatal diagnosis · 2026
Structural Variation Sequencing of 26 Amniotic Fluid Samples With Partial Gene Duplications and Postnatal Follow-Up of the Fetuses.
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Qin Shengfang, Wang Xueyan, Yan Mengjia, He Yuxia, Zhang Zhuo, Yin Yan, Wang Jin, Guo Beibei, Wang Jing, Xi Na, Li Zhaokai
Аннотация
OBJECTIVES: Partial gene duplications (PGDups) are a significant contributor to genetic disease. The precise genomic location and structure of PGDups are often unresolved using conventional methods, so prenatal diagnosis for PGDups is challenging, especially without ultrasound abnormalities.
METHODS: We retrospectively applied structural variation sequencing (SVseq) to 26 amniotic fluid samples with PGDups initially identified by chromosomal microarray or sequencing. SVseq utilized mate-pair library construction and high-throughput sequencing to map PGDup structures. Pathogenicity was classified using ACMG guidelines, followed by postnatal phenotypic follow-up.
RESULTS: SVseq deciphered the PGDup structure for all twenty-six cases. Twenty-two (84.62%) were tandem duplications (TDs), three (11.54%) chromosomal complex rearrangements (CCRs), and one (3.85%) had no duplication. Among twenty-two TDs, thirteen were extragenic (TDEG), preserving gene integrity, and were classified as benign or variants of uncertain significance (VUS). Nine were intragenic (TDIG), disrupting gene structure, and were rated pathogenic or likely pathogenic (P/LP) or VUS. Postnatal follow-up revealed obvious abnormal phenotypes in only two TDIG cases (one inherited and one de novo).
CONCLUSION: SVseq effectively resolves PGDup location and structure, allowing confident pathogenicity assessment and clear genotype-phenotype correlation. SVseq is a robust method for prenatal PGDup evaluation that could be adopted in diagnostic protocols to improve clinical outcomes.
METHODS: We retrospectively applied structural variation sequencing (SVseq) to 26 amniotic fluid samples with PGDups initially identified by chromosomal microarray or sequencing. SVseq utilized mate-pair library construction and high-throughput sequencing to map PGDup structures. Pathogenicity was classified using ACMG guidelines, followed by postnatal phenotypic follow-up.
RESULTS: SVseq deciphered the PGDup structure for all twenty-six cases. Twenty-two (84.62%) were tandem duplications (TDs), three (11.54%) chromosomal complex rearrangements (CCRs), and one (3.85%) had no duplication. Among twenty-two TDs, thirteen were extragenic (TDEG), preserving gene integrity, and were classified as benign or variants of uncertain significance (VUS). Nine were intragenic (TDIG), disrupting gene structure, and were rated pathogenic or likely pathogenic (P/LP) or VUS. Postnatal follow-up revealed obvious abnormal phenotypes in only two TDIG cases (one inherited and one de novo).
CONCLUSION: SVseq effectively resolves PGDup location and structure, allowing confident pathogenicity assessment and clear genotype-phenotype correlation. SVseq is a robust method for prenatal PGDup evaluation that could be adopted in diagnostic protocols to improve clinical outcomes.