chromosomal abnormalities (cas) can cause spontaneous miscarriage and increase the incidence of subsequent pregnancy loss and other complications. Presently, cas are detected mainly by array comparative genomic hybridization (cGH) and single nucleotide polymorphism microarrays. The present study developed a low-coverage next-generation sequencing method to detect cas in spontaneous miscarriage and assess its clinical performance. in total, 1,401 patients who had experienced an abortion were enrolled in the present study and divided into two groups. in group i, 437 samples that had been previously validated by array cGH were used to establish a method to detect cas using a semiconductor sequencing platform. in group ii, 964 samples, which were not verified, were assessed using established methods with respect to clinical significance. Copy number variant (CNV)-positive and euploidy samples were verified by array CGH and short tandem repeat profiling, respectively, based on quantitative fluorescent PCR. The low-coverage sequencing method detected CNVs >1 Mb in length and a total of 3.5 million unique reads. Similar results to array cGH were obtained in group I, except for six CNVs <1 Mb long. In group II, there were 341 aneuploidies, 195 CNVs, 25 mosaicisms and 403 euploi-dies. overall, among the 1,401 abortion samples, there were 536 aneuploidies, 263 CNVs, 34 mosaicisms, and 568 euploidies. Trisomies were present in all autosomal chromosomes. The most common aneuploidies were T16, monosomy X, T22, T15, T21 and T13. Furthermore, one tetrasomy 21, one CNV associated with Wolf-Hirschhorn syndrome, one associated with diGeorge syndrome and one associated with both Prader-Willi and Angelman syndromes were identified. These four cases were confirmed by short tandem repeat profiling and array CGH. Quantitative fluorescent PCR revealed nine polyploidy samples. The present method demonstrated equivalent efficacy to that of array CGH in detecting CNVs >1 Mb, with advantages of requiring less input dna and lower cost.

Rare autosomal aneuploidies (RAAs) can cause miscarriage or other pregnancy complications and lead to inconsistent results of noninvasive prenatal testing (NIPT), but many NIPT providers have not yet started to provide related services. Our aim was to develop a semiconductor sequencing platform (SSP)-based method for detecting RAAs when pregnant women performed NIPT. Fifty-three aneuploidy samples with verified karyotyping or array comparative genomic hybridization (aCGH) results were collected and subjected to RAAs detection using an SSP to develop a method by genomic sequencing. Various trisomies on all chromosomes other than chromosomes 17 and 19, four multiple aneusomies, one monosomy and five sex chromosome abnormalities were got by our method which can directly identify RAAs via a z-score. Then, artificial mixtures of 10% and 5% DNA were created by adding fragmented fifty-three tissue samples and used in an NIPT simulation to develop a bioinformatics analysis method which can use in NIPT. And the results were in accordance with those of karyotyping and aCGH. Therefore, our method has potential for use in NIPT. Finally, 23,823 clinical plasma samples were tested to verify the performance of our approach. Karyotyping or aCGH was performed on the positive clinical samples. In total, 188 of 23,823 clinical samples were positive (T2, n = 1; T7, n = 1; T13, n = 15; T18, n = 45; T21, n = 125; and multiple aneusomies, n = 1) and verified by karyotyping or aCGH; no sample was a false negative. Several false positives were detected, one of which showed maternal copy number variation (CNV). One case of multiple aneusomies was caused by a maternal tumor. The method developed enables detection of RAAs without increasing costs.

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