2025/10/14 by Yoo-Jin Ha, Dominika Maziec, Julia Markowski +43 · 1 voice · 1 citation
Biochemistry, Genetics and Molecular Biology · #Cancer Genomics and Diagnostics #Genomics and Rare Diseases #Gene expression and cancer classification
paper · pdf · doi:10.1101/2025.10.13.681545
openalex publication_date 2025/10/14 · openalex created_date 2025/10/15 · openalex updated_date 2026/07/22
Mosaic mutations in normal tissues occur at low variant allele fractions (VAFs), complicating detection. To benchmark strategies, the SMaHT Network created a cell-line mixture (1:49) and produced ultra-deep whole-genome sequencing using short and long reads (five centers, 180-500× each). We assembled a reference of 44,008 mosaic SNVs and 2,059 Indels, cross-validation between platforms to expose limits of short-read analysis. We also partitioned the genome by mappability to examine the impact of genomic context, added a negative reference set, and accounted for culture-derived mutations. When seven institutions applied eleven algorithms to mixture data, call sets were largely discordant across tools and replicates, partly reflecting stochastic presence of low-VAF mutations in biological replicants. For >2% VAF SNVs, sensitivity and precision approached ~80% at ≥300×, with little gain from additional sequencing. This work provides a comprehensive framework for reliable detection of low-VAF mutations in non-cancer tissues and a valuable resource for the community.