{"title":"评估毒理学剂量反应 RNA-seq 中的重复数量和测序深度","authors":"A. Rasim Barutcu","doi":"10.1016/j.comtox.2024.100307","DOIUrl":null,"url":null,"abstract":"<div><p>Sequencing depth and biological replication represent key experimental design considerations in toxicogenomics and risk assessment. However, their relative impacts on differential gene expression analysis remain unclear. Using an 8-dose chemical (Prochloraz) perturbation RNA-seq dataset in A549 cells, we systematically subsampled sequencing depth (5–100 %) and replicates (2–4) to evaluate effects on number of differentially expressed genes. While dose was the primary variance driver, replication had a greater influence than depth for optimizing detection power. With only 2 replicates, over 80% of the ∼2000 differential genes were unique to specific depths, indicating high variability. Increasing to 4 replicates substantially improved reproducibility, with over 550 genes consistently identified across most depths, representing 30% of the total differential genes. Higher replicates also increased the rate of overlap of benchmark dose pathways and precision of median benchmark dose estimates. However, key gene ontology pathways related to DNA replication, cell cycle, and division were consistently captured even at lower replicates. Thus, replication enhanced confidence but did not fundamentally expand biological findings. Our study delineates key trade-offs between sequencing depth and replication for toxicogenomic experimental design. While additional replicates fundamentally improve reproducibility, gains from depth exhibit diminishing returns. Prioritizing biological replication over depth provides a cost-effective approach to enhance interpretation without sacrificing detection of core gene expression patterns. Altogether, this study provides important insights into the experimental design of toxicogenomics experiments.</p></div>","PeriodicalId":37651,"journal":{"name":"Computational Toxicology","volume":null,"pages":null},"PeriodicalIF":3.1000,"publicationDate":"2024-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Evaluation of Replicate Number and Sequencing Depth in Toxicology Dose-Response RNA-seq\",\"authors\":\"A. Rasim Barutcu\",\"doi\":\"10.1016/j.comtox.2024.100307\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Sequencing depth and biological replication represent key experimental design considerations in toxicogenomics and risk assessment. However, their relative impacts on differential gene expression analysis remain unclear. Using an 8-dose chemical (Prochloraz) perturbation RNA-seq dataset in A549 cells, we systematically subsampled sequencing depth (5–100 %) and replicates (2–4) to evaluate effects on number of differentially expressed genes. While dose was the primary variance driver, replication had a greater influence than depth for optimizing detection power. With only 2 replicates, over 80% of the ∼2000 differential genes were unique to specific depths, indicating high variability. Increasing to 4 replicates substantially improved reproducibility, with over 550 genes consistently identified across most depths, representing 30% of the total differential genes. Higher replicates also increased the rate of overlap of benchmark dose pathways and precision of median benchmark dose estimates. However, key gene ontology pathways related to DNA replication, cell cycle, and division were consistently captured even at lower replicates. Thus, replication enhanced confidence but did not fundamentally expand biological findings. Our study delineates key trade-offs between sequencing depth and replication for toxicogenomic experimental design. While additional replicates fundamentally improve reproducibility, gains from depth exhibit diminishing returns. Prioritizing biological replication over depth provides a cost-effective approach to enhance interpretation without sacrificing detection of core gene expression patterns. Altogether, this study provides important insights into the experimental design of toxicogenomics experiments.</p></div>\",\"PeriodicalId\":37651,\"journal\":{\"name\":\"Computational Toxicology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.1000,\"publicationDate\":\"2024-03-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computational Toxicology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2468111324000094\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"TOXICOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computational Toxicology","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2468111324000094","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"TOXICOLOGY","Score":null,"Total":0}
Evaluation of Replicate Number and Sequencing Depth in Toxicology Dose-Response RNA-seq
Sequencing depth and biological replication represent key experimental design considerations in toxicogenomics and risk assessment. However, their relative impacts on differential gene expression analysis remain unclear. Using an 8-dose chemical (Prochloraz) perturbation RNA-seq dataset in A549 cells, we systematically subsampled sequencing depth (5–100 %) and replicates (2–4) to evaluate effects on number of differentially expressed genes. While dose was the primary variance driver, replication had a greater influence than depth for optimizing detection power. With only 2 replicates, over 80% of the ∼2000 differential genes were unique to specific depths, indicating high variability. Increasing to 4 replicates substantially improved reproducibility, with over 550 genes consistently identified across most depths, representing 30% of the total differential genes. Higher replicates also increased the rate of overlap of benchmark dose pathways and precision of median benchmark dose estimates. However, key gene ontology pathways related to DNA replication, cell cycle, and division were consistently captured even at lower replicates. Thus, replication enhanced confidence but did not fundamentally expand biological findings. Our study delineates key trade-offs between sequencing depth and replication for toxicogenomic experimental design. While additional replicates fundamentally improve reproducibility, gains from depth exhibit diminishing returns. Prioritizing biological replication over depth provides a cost-effective approach to enhance interpretation without sacrificing detection of core gene expression patterns. Altogether, this study provides important insights into the experimental design of toxicogenomics experiments.
期刊介绍:
Computational Toxicology is an international journal publishing computational approaches that assist in the toxicological evaluation of new and existing chemical substances assisting in their safety assessment. -All effects relating to human health and environmental toxicity and fate -Prediction of toxicity, metabolism, fate and physico-chemical properties -The development of models from read-across, (Q)SARs, PBPK, QIVIVE, Multi-Scale Models -Big Data in toxicology: integration, management, analysis -Implementation of models through AOPs, IATA, TTC -Regulatory acceptance of models: evaluation, verification and validation -From metals, to small organic molecules to nanoparticles -Pharmaceuticals, pesticides, foods, cosmetics, fine chemicals -Bringing together the views of industry, regulators, academia, NGOs