Department of Environmental Sciences, Informatics and Statistics, Ca' Foscari University of Venice, via Torino 155, 30172, Mestre-Venezia, Italy.
Department of Comparative Biomedicine and Food Science, University of Padova, Viale dell'Università 16, 35020, Legnaro, Padova, Italy.
Environ Res. 2023 Jun 15;227:115745. doi: 10.1016/j.envres.2023.115745. Epub 2023 Mar 25.
The sharp decrease in the cost of RNA-sequencing and the rapid improvement in computational analysis of eco-toxicogenomic data have brought new insights into the adverse effects of chemicals on aquatic organisms. Yet, transcriptomics is generally applied qualitatively in environmental risk assessments, hampering more effective exploitation of this evidence through multidisciplinary studies. In view of this limitation, a methodology is here presented to quantitatively elaborate transcriptional data in support to environmental risk assessment. The proposed methodology makes use of results from the application of Gene Set Enrichment Analysis to recent studies investigating the response of Mytilus galloprovincialis and Ruditapes philippinarum exposed to contaminants of emerging concern. The degree of changes in gene sets and the relevance of physiological reactions are integrated in the calculation of a hazard index. The outcome is then classified according to five hazard classes (from absent to severe), providing an evaluation of whole-transcriptome effects of chemical exposure. The application to experimental and simulated datasets proved that the method can effectively discriminate different levels of altered transcriptomic responses when compared to expert judgement (Spearman correlation coefficient of 0.96). A further application to data collected in two independent studies of Salmo trutta and Xenopus tropicalis exposed to contaminants confirmed the potential extension of the methodology to other aquatic species. This methodology can serve as a proof of concept for the integration of "genomic tools" in environmental risk assessment based on multidisciplinary investigations. To this end, the proposed transcriptomic hazard index can now be incorporated into quantitative Weight of Evidence approaches and weighed, with results from other types of analysis, to elucidate the role of chemicals in adverse ecological effects.
RNA 测序成本的大幅下降和生态毒基因组学数据的计算分析的快速改进,为化学物质对水生生物的不良影响提供了新的见解。然而,转录组学通常在环境风险评估中定性应用,阻碍了通过多学科研究更有效地利用这一证据。鉴于这一局限性,本文提出了一种定量阐述转录组数据的方法,以支持环境风险评估。所提出的方法利用基因集富集分析在最近研究中的应用结果,该研究调查了贻贝和菲律宾蛤仔暴露于新兴关注污染物的反应。基因集变化程度和生理反应的相关性被整合到危害指数的计算中。然后根据五个危害等级(从不存在到严重)对结果进行分类,从而评估化学暴露对全转录组的影响。该方法应用于实验和模拟数据集的结果表明,与专家判断相比(Spearman 相关系数为 0.96),该方法可以有效地区分不同水平的转录组反应变化。将该方法进一步应用于暴露于污染物的鲑鱼和非洲爪蟾的两项独立研究中收集的数据,证实了该方法可以扩展到其他水生物种的潜力。该方法可以作为将“基因组工具”整合到基于多学科研究的环境风险评估中的概念验证。为此,所提出的转录组危害指数现在可以纳入定量证据权重方法,并与其他类型的分析结果一起权衡,以阐明化学物质在不良生态影响中的作用。