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DOI 10.1186/s12920-021-00899-x

Медицинская библиотека · BMC medical genomics · 2021

Integrated CNV-seq, karyotyping and SNP-array analyses for effective prenatal diagnosis of chromosomal mosaicism.

Ma Na, Xi Hui, Chen Jing, Peng Ying, Jia Zhengjun, Yang Shuting, Hu Jiancheng, Pang Jialun, Zhang Yanan, Hu Rong, Wang Hua, Liu Jing

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Аннотация

BACKGROUND

Emerging studies suggest that low-coverage massively parallel copy number variation sequencing (CNV-seq) more sensitive than chromosomal microarray analysis (CMA) for detecting low-level mosaicism. However, a retrospective back-to-back comparison evaluating accuracy, efficacy, and incremental yield of CNV-seq compared with CMA is warranted.

METHODS

A total of 72 mosaicism cases identified by karyotyping or CMA were recruited to the study. There were 67 mosaic samples co-analysed by CMA and CNV-seq, comprising 40 with sex chromosome aneuploidy, 22 with autosomal aneuploidy and 5 with large cryptic genomic rearrangements.

RESULTS

Of the 67 positive mosaic cases, the levels of mosaicism defined by CNV-seq ranged from 6 to 92% compared to the ratio from 3 to 90% by karyotyping and 20% to 72% by CMA. CNV-seq not only identified all 43 chromosomal aneuploidies or large cryptic genomic rearrangements detected by CMA, but also provided a 34.88% (15/43) increased yield compared with CMA. The improved yield of mosaicism detection by CNV-seq was largely due to the ability to detect low level mosaicism below 20%.

CONCLUSION

In the context of prenatal diagnosis, CNV-seq identified additional and clinically significant mosaicism with enhanced resolution and increased sensitivity. This study provides strong evidence for applying CNV-seq as an alternative to CMA for detection of aneuploidy and mosaic variants.

Для цитирования: Ma Na, Xi Hui, Chen Jing, Peng Ying, Jia Zhengjun, Yang Shuting, Hu Jiancheng, Pang Jialun, Zhang Yanan, Hu Rong, Wang Hua, Liu Jing. Integrated CNV-seq, karyotyping and SNP-array analyses for effective prenatal diagnosis of chromosomal mosaicism.. BMC medical genomics. 2021. DOI: 10.1186/s12920-021-00899-x.

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