Semiconductor Sequencing Analysis of Chromosomal Copy Number Variations in Spontaneous Miscarriage

利用半导体测序分析自然流产中染色体拷贝数变异

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Abstract

BACKGROUND Array CGH is the criterion standard for identifying copy number variations (CNV), but the restrictive requirement of DNA quality and relatively high cost prevent the use of this method as a general assay in hospitals in developing countries. Our principal objective was to determine whether the semiconductor sequencing platform (SSP) could be an alternative method in CNV detection for spontaneous miscarriage. MATERIAL AND METHODS A total of 443 spontaneous miscarriage samples were collected and subjected to low-coverage (0.1X) whole-genome analysis by SSP. These samples were verified by array CGH and 8 low-quality DNA samples were analyzed by SSP and validated by MLPA. RESULTS SSP detected 195 chromosomal numerical abnormalities, 74 CNVs, and 9 mosaicisms among the 435 samples. Among 74 CNV abnormalities, SSP detected an equal number (56) of CNVs 56 >1 Mb with array CGH. However, SSP missed more 6 cases CNVs <1 Mb than array CGH (12 vs. 18). SSP detected more mosaicisms than array CGH (9 vs. 7, p=0.5). Interestingly, SSP detected the mosaicism which had only 8% X monosomy, which was much lower than the minimal percentage of monosomy that was detected by array CGH. CONCLUSIONS SSP is of equivalent efficacy as array CGH in detecting CNVs >1 Mb, and performs better in identifying mosaicism. With the merits of low cost and less demand of input DNA, SSP is a good alternative for use in genetic diagnosis.

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