
pmid: 39267335
AbstractRegulatory genetic toxicology testing is essential for identifying potentially mutagenic hazards. Duplex Sequencing (DS) is an error‐corrected next‐generation sequencing technology that provides substantial advantages for mutation analysis over conventional mutagenicity assays including: improved accuracy of mutation detection, ability to measure changes in mutation spectrum, and applicability across diverse biological models. To apply DS for regulatory toxicology testing, power analyses are required to determine suitable sample sizes and study designs. In this study, we explored study designs to achieve sufficient power for various effect sizes in chemical mutagenicity assessment. We collected data from MutaMouse bone marrow and liver samples that were analyzed by DS using TwinStrand's Mouse Mutagenesis Panel. Average duplex reads achieved in two separates studies on liver and bone marrow were 8.4 × 108 (± 7.4 × 107) and 9.5 × 108 (± 1.0 × 108), respectively. Baseline mean mutation frequencies (MF) were 4.6 × 10−8 (± 6.7 × 10−9) and 4.6 × 10−8 (± 1.1 × 10−8), with estimated standard deviations for the animal‐to‐animal random effect of 0.15 and 0.20, for liver and bone marrow, respectively. We conducted simulation analyses based on these empirically derived parameters. We found that a sample size of four animals per group is sufficient to obtain over 80% power to detect a two‐fold change in MF relative to baseline. In addition, we estimated the minimal total number of informative duplex bases sequenced with different sample sizes required to retain power for various effect sizes. Our work provides foundational data for establishing suitable study designs for mutagenicity testing using DS.
Male, Mice, Liver, Mutation Rate, Bone Marrow, Mutagenicity Tests, Research Design, Mutagenesis, Mutation, Animals, High-Throughput Nucleotide Sequencing, Mutagens
Male, Mice, Liver, Mutation Rate, Bone Marrow, Mutagenicity Tests, Research Design, Mutagenesis, Mutation, Animals, High-Throughput Nucleotide Sequencing, Mutagens
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