de novo variant calling identifies cancer mutation profiles in the 1000 Genomes Project

ABSTRACT Detection of de novo variants (DNVs) is critical for studies of disease-related variation and mutation rates. We developed a GPU-based workflow to call DNVs, using 602 trios from the 1000 Genomes Project as a control. We detected 445,711 DNVs, having a bimodal distribution, with peaks at 200 and 2000 DNVs. The excess DNVs are cell line artifacts that are increasing with cell passage. Reduction in DNVs at CpG sites and in percent of DNVs with a paternal parent-of-origin with increasing number of DNVs supports this finding. Detailed assessment of individual NA12878 across multiple genome datasets from 2012 to 2020 reveals increasing number of DNVs over time. Mutation signature analysis across the set revealed individuals had either 1) age-related, 2) B-cell lymphoma, or 3) no prominent signatures. Our approach provides an important advancement for DNV detection and shows cell line artifacts present in lymphoblastoid cell lines are not always random.