Detection of DNA Contamination in Prenatal Samples from Whole Exome Sequencing Data

Abstract

Abstract Background Maternal cell contamination (MCC) in prenatal samples poses a risk for misdiagnosis, and therefore, testing for contamination is necessary during genetic analysis of prenatal specimens. MCC testing is currently performed as a method separate from the diagnostic method. With the increasing application of whole exome sequencing (WES) in prenatal diagnosis, we sought to develop a method to estimate the level of contamination from WES data, aiming to eliminate the need for a separate MCC test. Methods To investigate the impact of MCC on the distribution of the variant allele fraction in WES data, contamination was both simulated in silico and artificially induced. Subsequently, a bioinformatic WES contamination method was developed and validated by comparing its performance to that of the gold standard (short tandem repeat [STR]) MCC test, validated for detecting ≥5% contamination. Finally, post-implementation performance was monitored for a 15-month period. Results During validation, 270 prenatal samples underwent analysis with both WES and the gold standard test. In 259 samples, the results were concordant (248 not contaminated, 11 contaminated with both tests). In 11 samples, contamination was only detected in WES data (2 of which contained ≥5% contamination with WES, which is above the detection limit of the gold standard test). The data of the post-implementation evaluation on 361 samples, of which 68 were contaminated, were in line with the validation data. Conclusions Contamination can reliably be detected in WES data, rendering a separate contamination test unnecessary for the majority of samples.