Power analyses to inform Duplex Sequencing study designs for MutaMouse liver and bone marrow

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
Elena Esina, Annette E. Dodge, Andrew Williams, David M. Schuster, Danielle P. M. LeBlanc, Francesco Marchetti, Carole L. Yauk
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Abstract

Regulatory 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.

Abstract Image

功率分析为 MutaMouse 肝脏和骨髓的双工测序研究设计提供依据
监管遗传毒理学检测对于确定潜在的致突变危害至关重要。双工测序(DS)是一种误差校正的新一代测序技术,与传统的诱变性检测方法相比,它在突变分析方面具有很大的优势,包括:提高了突变检测的准确性,能够测量突变谱的变化,适用于各种生物模型。要将 DS 应用于监管毒理学测试,需要进行功率分析,以确定合适的样本量和研究设计。在本研究中,我们探讨了在化学致突变性评估中如何设计研究设计,以达到各种效应大小的足够功率。我们收集了来自 MutaMouse 骨髓和肝脏样本的数据,并通过 DS 使用 TwinStrand 的小鼠突变面板进行了分析。在对肝脏和骨髓进行的两项分离研究中,获得的平均双工读数分别为 8.4 × 108 (± 7.4 × 107) 和 9.5 × 108 (± 1.0 × 108)。肝脏和骨髓的基线平均突变频率 (MF) 分别为 4.6 × 10-8 (± 6.7 × 10-9) 和 4.6 × 10-8 (± 1.1 × 10-8),动物间随机效应的估计标准偏差分别为 0.15 和 0.20。我们根据这些经验得出的参数进行了模拟分析。我们发现,每组 4 只动物的样本量足以获得超过 80% 的功率,以检测 MF 相对于基线的两倍变化。此外,我们还估算了在不同样本量下,为保持不同效应大小的功率所需的最小信息双链测序碱基总数。我们的工作为利用 DS 进行诱变性测试建立合适的研究设计提供了基础数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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