High resolution non-invasive detection of a fetal microdeletion using the GCREM algorithm.

BACKGROUND/OBJECTIVE: The non-invasive prenatal detection of fetal microdeletions becomes increasingly challenging as the size of the mutation decreases, with current practical lower limits in the range of a few megabases. Our goals were to explore the lower limits of microdeletion size detection via non-invasive prenatal tests using Minimally Invasive Karyotyping (MINK) and introduce/evaluate a novel statistical approach we recently developed called the GC Content Random Effect Model (GCREM). METHODS: Maternal plasma was obtained from a pregnancy affected by a 4.2-Mb fetal microdeletion and three normal controls. Plasma DNA was subjected to capture an 8-Mb sequence spanning the breakpoint region and sequence. Data were analyzed with our published method, MINK, and a new method called GCREM. RESULTS: The 8-Mb capture segment was divided into either 38 or 76 non-overlapping regions of 200 and 100 Kb, respectively. At 200 Kb resolution, using GCREM (but not MINK), we obtained significant adjusted p-values for all 20 regions overlapping the deleted sequence, and non-significant p-values for all 18 reference regions. At 100 Kb resolution, GCREM identified significant adjusted p-values for all but one 100-Kb region located inside the deleted region. CONCLUSION: Targeted sequencing and GCREM analysis may enable cost effective detection of fetal microdeletions and microduplications at high resolution.