Preliminary analysis of species sensitivity distribution based on gene expression effect

Chironomidae (Midge) Sensitivities to Ammonia Using Multiple Endpoints in China and Australia for the Development of Water Quality Criteria for Freshwater River Systems in China

“…In the present study, multiple endpoints ranging from traditional acute and chronic endpoints such as survival and development to nontraditional biochemical and gene expression levels were investigated. Previous studies have shown that gene expression data were less sensitive than chronic data for cadmium, and the same trend was also found for zinc and copper (Fedorenkova et al, 2010;Yan et al, 2012a). The findings in the present study were not consistent with this; however, the present study includes only one species.…”

“…In addition, there remain uncertainties within the literature on the sensitivities of data based on biochemical and gene expression levels (Yan et al, 2012a). For example, depending on the biomarkers chosen, the toxicity response can vary significantly, as can be seen from the findings in the present study (the LOEC values of 4 different biochemical and gene expression endpoints vary from 0.19 to 0.98 mg/L), and there remains the real possibility that the biomarkers chosen were not the most sensitive for ammonia in the test species.…”

“…For example, the HC5 value of cadmium derived from data on gene expression level (0.72 μg/L) was compared with values derived from traditional acute (18.3 μg/L) and chronic (0.23 μg/L) data (Fedorenkova et al, 2010). Similarly, another study showed that cadmium HC5 values derived from gene expression data and acute and chronic survival and development levels were 0.717, 5.26, and 0.197 μg/L, respectively (Yan et al, 2012a). Toxicity data on gene expression levels have significant potential for use in risk assessment of aquatic ecosystem, but the paucity of such available data is the main constraint for their use in WQC derivation.…”

“…It should be noted that the estimation of LOEC was based on hypothesis testing rather than regression analysis, which is the most widely accepted method in deriving toxicity data (TenBrook et al, 2008). The best way to increase the confidence of toxicity data based on biochemical and gene expression levels might be to choose the appropriate target gene of specific species responding to pollutants by high-throughput screening and genomics technology (Yan et al, 2012a). Once the toxicity values generated indicate toxicant sensitivity and the data used to generate the toxicity values are verified to be of high quality and can be linked to quantifiable individual effect levels, WQC derivation would greatly benefit by incorporating such biochemical and gene expression data sets.…”

Toxic Pollutants in China

“…Davies et al (1994) brought up the question about the feasibility of using toxicity data of species from one geographical region to assess the ecological risk posed to species in a different region. In this study, the difference of SSD based on native and nonnative species was compared (Chapman et al 2006;Cheung et al 2007;Yan et al 2012a). In this study, the difference of SSD based on native and nonnative species was compared (Chapman et al 2006;Cheung et al 2007;Yan et al 2012a).…”