Ultrasensitive detection of minor allele fractions in maternal samples based on microhaplotype analysis

Background: Tools for quantifying and studying genetic variation in heterogeneous cell populations have a limited sensitivity. However, many biological problems require ultrasensitive genetic deconvolution of cell mixtures. The detection of fetal cells in cervical samples from pregnant women presents such a challenge.
Methods: Using deep sequencing of microhaplotype loci and analysis of the error profiles in genetically pure and mixed samples, we increase the sensitivity for minor allele detection and demonstrate the potential for paternal allele detection in cervical samples from pregnant women.
Results: Using artificial DNA mixtures, we show that unique alleles can be readily identified in mixtures with a ratio of 1 in 10,000 (0.01%). By applying this method on ten non-invasive cervical samples from pregnant women we could identify the presence of paternal alleles in half of the samples. Unexpectedly, we demonstrate those alleles not to be of fetal origin but of sperm.
Conclusions: We developed a novel method that can deconvolute genetic mixtures to at least 0.01%, which can be applied to study minor allele fractions in genetic mixtures and, for example, could aid in trophoblast cell detection in maternal blood or cervix. Our results demonstrate the importance of discriminating fetal and paternal alleles when analyzing cervical fetal cells and may pinpoint a potential cause of erroneous results in previous trophoblast isolation studies.EGA study EGAS00001007057