Application of multiple mosaic callers improves post-zygotic mutation detection from exome sequencing data

Abstract

Purpose

The gold standard for identification of post-zygotic variants (PZVs) is droplet digital polymerase chain reaction or high-depth sequencing across multiple tissues types. These approaches are yet to be systematically implemented for monogenic disorders. We developed PZV detection pipelines for correct classification of de novo variants.

Method

Our pipelines detect PZV in parents (gonosomal mosaicism [pGoM]) and children (somatic mosaicism, “M3”). We applied them to research exome sequencing (ES) data from the Australian Cerebral Palsy Biobank (n = 145 trios) and Simons Simplex Collection (n = 405 families). Candidate mosaic variants were validated using deep amplicon sequencing or droplet digital polymerase chain reaction.

Results

69.2% (M3^trio), 63.9% (M3^single), and 92.7% (pGoM) of detected variants were validated, with 48.6%, 56.7%, and 26.2% of variants, respectively, meeting strict criteria for mosaicism. In the Australian Cerebral Palsy Biobank, 16.6% of probands and 20.7% of parents had at least 1 true-positive somatic or pGoM variant, respectively. A large proportion of PZVs detected in Simons Simplex Collection parents (79.8%) and child (94.5%) were not previously reported. We reclassified 3.7% to 8.0% of germline de novo variants as mosaic.

Conclusion

Many PZVs were incorrectly classified as germline variants or missed by previous approaches. Systematic application of our pipelines could increase genetic diagnostic rate, improve estimates of recurrence risk in families, and benefit novel disease gene identification.