Non-invasive prenatal testing by low coverage genomic sequencing: Detection limits of screened chromosomal microdeletions

Abstract Objective To study the detection limits of chromosomal microaberrations in non-invasive prenatal testing with aim for five target microdeletion syndromes, including DiGeorge, Prader-Willi/Angelman, 1p36, Cri-Du-Chat, and Wolf-Hirschhorn syndromes. Method We used known cases of pathogenic deletions from ISCA database to specifically define regions critical for the target syndromes. Our approach to detect microdeletions, from whole genome sequencing data, is based on sample normalization and read counting for individual bins. We performed both an in-silico study using artificially created data sets and a laboratory test on mixed DNA samples, with known microdeletions, to assess the sensitivity of prediction for varying fetal fractions, deletion lengths, and sequencing read counts. Results The in-silico study showed sensitivity of 79.3% for 10% fetal fraction with 20M read count, which further increased to 98.4% if we searched only for deletions longer than 3Mb. The test on laboratory-prepared mixed samples was in agreement with in-silico results, while we were able to correctly detect 24 out of 29 control samples. Conclusion Our results suggest that it is possible to incorporate microaberration detection into basic NIPT as part of the offered screening/diagnostics procedure, however, accuracy and reliability depends on several specific factors. What’s already known about this topic? Microdeletion detection accuracy, similarly to most common trisomies detection, was found to be dependent mostly on technical and biological parameters of the test and tested samples, such as coverage of target region, fetal fraction, size and positions of the deletions. What does this study add? Estimation of relevant regions for five chosen microdeletion syndromes. Confirmation and improvement upon previous methods. Systematic evaluation of sensitivity of microdeletion detection with read counts from 10M to 20M.