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表征转录组剂量反应建模相关的变异性和不确定性。

Characterizing Variability and Uncertainty Associated with Transcriptomic Dose-Response Modeling.

机构信息

Faculty of Agricultural and Environmental Sciences, McGill University, Ste-Anne-de-Bellevue H9X 3V9, Canada.

Ecotoxicology and Wildlife Health Division, National Wildlife Research Centre, Environment and Climate Change Canada, Ottawa K1A 0H3, Canada.

出版信息

Environ Sci Technol. 2022 Nov 15;56(22):15960-15968. doi: 10.1021/acs.est.2c04665. Epub 2022 Oct 21.

Abstract

Transcriptomics dose-response analysis (TDRA) has emerged as a promising approach for integrating toxicogenomics data into a risk assessment context; however, variability and uncertainty associated with experimental design are not well understood. Here, we evaluated = 55 RNA-seq profiles derived from Japanese quail liver tissue following exposure to chlorpyrifos (0, 0.04, 0.1, 0.2, 0.4, 1, 2, 4, 10, 20, and 40 μg/g; = 5 replicates per group) via egg injection. The full dataset was subsampled 637 times to generate smaller datasets with different dose ranges and spacing (designs A-E) and number of replicates ( = 2-5). TDRA of the 637 datasets revealed substantial variability in the gene and pathway benchmark doses, but relative stability in overall transcriptomic point-of-departure (tPOD) values when tPODs were calculated with the "pathway" and "mode" methods. Further, we found that tPOD values were more dependent on the dose range and spacing than on the number of replicates, suggesting that optimal experimental designs should use fewer replicates ( = 2 or 3) and more dose groups to reduce uncertainty in the results. Finally, tPOD values ranged by over ten times for all surveyed experimental designs and tPOD types, suggesting that tPODs should be interpreted as order-of-magnitude estimates.

摘要

转录组剂量反应分析(TDRA)已成为将毒理基因组学数据整合到风险评估中的一种很有前途的方法;然而,与实验设计相关的可变性和不确定性尚未得到很好的理解。在这里,我们通过卵内注射评估了 55 个源自日本鹌鹑肝脏组织的 RNA-seq 图谱,这些组织在暴露于毒死蜱(0、0.04、0.1、0.2、0.4、1、2、4、10、20 和 40 μg/g;每组 5 个重复)后。通过对全数据集进行 637 次抽样,生成了具有不同剂量范围和间距(设计 A-E)和重复次数(2-5 个)的较小数据集。对 637 个数据集进行的 TDRA 分析显示,基因和途径基准剂量存在很大差异,但当使用“途径”和“模式”方法计算总转录组起点(tPOD)值时,总体转录组 tPOD 值相对稳定。此外,我们发现 tPOD 值更多地取决于剂量范围和间距,而不是重复次数,这表明最佳实验设计应使用更少的重复次数(2 或 3)和更多的剂量组,以减少结果的不确定性。最后,对于所有调查的实验设计和 tPOD 类型,tPOD 值的范围都超过了十倍,这表明 tPOD 应该被解释为数量级的估计。

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