It has long been appreciated that genetic analysis of fetal or trophoblast cells in maternal blood could revolutionize prenatal diagnosis. We implemented a protocol for single circulating trophoblast (SCT) testing using positive selection by magnetic-activated cell sorting and single-cell low-coverage whole-genome sequencing to detect fetal aneuploidies and copy-number variants (CNVs) at $1 Mb resolution. In 95 validation cases, we identified on average 0.20 putative trophoblasts/mL, of which 55% were of high quality and scorable for both aneuploidy and CNVs. We emphasize the importance of analyzing individual cells because some cells are apoptotic, in S-phase, or otherwise of poor quality. When two or more high-quality trophoblast cells were available for singleton pregnancies, there was complete concordance between all trophoblasts unless there was evidence of confined placental mosaicism. SCT results were highly concordant with available clinical data from chorionic villus sampling (CVS) or amniocentesis procedures. Although determining the exact sensitivity and specificity will require more data, this study further supports the potential for SCT testing to become a diagnostic prenatal test.

Objective To gather additional data on the ability to detect subchromosomal abnormalities of various sizes in single fetal cells isolated from maternal blood, using low‐coverage shotgun next‐generation sequencing for cell‐based noninvasive prenatal testing (NIPT). Method Fetal trophoblasts were recovered from approximately 30 mL of maternal blood using maternal white blood cell depletion, density‐based cell separation, immunofluorescence staining, and high‐resolution scanning. These trophoblastic cells were picked as single cells and underwent whole genome amplification for subsequent genome‐wide copy number analysis and genotyping to confirm the fetal origin of the cells. Results Applying our fetal cell isolation method to a series of 125 maternal blood samples, we detected on average 4.17 putative fetal cells/sample. The series included 15 cases with clinically diagnosed fetal aneuploidies and five cases with subchromosomal abnormalities. This method was capable of detecting findings that were 1 to 2 Mb in size, and all were concordant with the microarray or karyotype data obtained on a fetal sample. A minority of fetal cells showed evidence of genome degradation likely related to apoptosis. Conclusion We demonstrate that this cell‐based NIPT method has the capacity to reliably diagnose fetal chromosomal abnormalities down to 1 to 2 Mb in size.

A major challenge for cell-based non-invasive prenatal testing (NIPT) is to distinguish individual presumptive fetal cells from maternal cells in female pregnancies. We have sought a rapid, robust, versatile, and low-cost next-generation sequencing method to facilitate this process. Toward this goal, single isolated cells underwent whole genome amplification prior to genotyping. Multiple highly polymorphic genomic regions (including HLA-A and HLA-B) with 10–20 very informative single nucleotide polymorphisms (SNPs) within a 200 bp interval were amplified with a modified method based on other publications. To enhance the power of cell identification, approximately 40 Human Identification SNP (Applied Biosystems) test amplicons were also utilized. Using SNP results to compare to sex chromosome data from NGS as a reliable standard, the true positive rate for genotyping was 83.4%, true negative 6.6%, false positive 3.3%, and false negative 6.6%. These results would not be sufficient for clinical diagnosis, but they demonstrate the general validity of the approach and suggest that deeper genotyping of single cells could be completely reliable. A paternal DNA sample is not required using this method. The assay also successfully detected pathogenic variants causing Tay Sachs disease, cystic fibrosis, and hemoglobinopathies in single lymphoblastoid cells, and disease-causing variants in three cell-based NIPT cases. This method could be applicable for any monogenic diagnosis.

GRHL2, are predicted targets of the identified miRNA. Three lncRNA (RP11-403P17.3, RP11-290L1.3, and MYLK-AS1) were upregulated in pregnancy. CONCLUSION: Pregnancy was associated with a novel cervical ncRNA signature. Gene ontology clustering revealed biological pathways through which these molecules may orchestrate normal pregnancy physiology, providing opportunity for early disease recognition. These data suggest that the cervix may function as a window into the health of the developing pregnancy.

A major challenge for cell-based non-invasive prenatal testing (NIPT) is to distinguish individual presumptive fetal cells from maternal cells in female pregnancies. We have sought a rapid, robust, versatile, and low-cost next-generation sequencing method to facilitate this process. Toward this goal, single isolated cells underwent whole genome amplification prior to genotyping. Multiple highly polymorphic genomic regions (including HLA-A and HLA-B) with 10-20 very informative single nucleotide polymorphisms (SNPs) within a 200 bp interval were amplified with a modified method based on other publications. To enhance the power of cell identification, approximately 40 Human Identification SNP (Applied Biosystems) test amplicons were also utilized. This method allowed reliable differentiation of fetal and maternal cells. In fully informative cases, two haplotypes were found within the maternal reads, and fetal cells showed reads with one but not the second maternal haplotype while also showing a novel paternal haplotype absent in the mother. For SNP typing, at least 2 SNPs and 10% of informative SNPs were required to differentiate a fetal cell from a maternal cell. A paternal DNA sample is not required using this method. The assay also successfully detected point mutations causing Tay Sachs disease, cystic fibrosis, and hemoglobinopathies in single lymphoblastoid cells, and monogenic disease-causing mutations in three cell-based NIPT cases. This method could be applicable for any monogenic diagnosis.