Current Research in Toxicology · 2022 · 20 citations · 35 references
Veterinary MedicineToxicologyAquatic ToxicologyFish BiologyTranscriptomicsFish ToxicologyFreshwater ToxicologyTranscriptomics In FishAssayBioassay DevelopmentConcentration-response VariabilityHigh Throughput BioassaysHigh-throughput Screening AssaysLarval TranscriptomicsTranscriptome AnalysisTranscriptomics-based Toxicity Assessment
Concentrations at which global gene expression profiles in cells or animals exposed to a test substance start to differ significantly from those of controls have been proposed as an alternative point of departure for use in screening level hazard assessment. The present study describes pilot testing of a high throughput compatible transcriptomics assay with larval fathead minnows. One day post hatch fathead minnows were exposed to eleven different concentrations of three metals, three selective serotonin reuptake inhibitors, and four neonicotinoid-like compounds for 24 h and concentration response modeling was applied to whole body gene expression data. Transcriptomics-based points of departure (tPODs) were consistently lower than effect concentrations reported in apical endpoint studies in fish. However, larval fathead minnow-based tPODs were not always lower than concentrations reported to elicit apical toxicity in other aquatic organisms like crustaceans or insects. Random in silico subsampling of data from the pilot assays was used to evaluate various assay design and acceptance considerations such as transcriptome coverage, number of replicate individuals to sequence per treatment, and minimum number of differentially expressed genes to produce a reliable tPOD estimate. Results showed a strong association between the total number of genes for which a concentration response relationship could be derived and the overall variability in the resulting tPOD estimates. We conclude that, for our current assay design and analysis pipeline, tPODs based on fewer than 15 differentially expressed genes are likely to be unreliable for screening and that interindividual variability in gene expression profiles appears to be a more significant driver of tPOD variability than sample size alone. Results represent initial steps toward developing high throughput transcriptomics assays for use in ecological hazard screening.
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R: A Language and Environment for Statistical Computing
R Core Team · 2000 · 353K citations · Full text
Natural Sciences, Computer Science, Statistical Computing +10
The Ecoresponsive Genome of <i>Daphnia pulex</i>
John K. Colbourne, Michael E. Pfrender, Donald Gilbert et al. · Science · 2011 · 1.2K citations · Full text
Life Sciences, Biology, Genetics +13