Project description:Individual stress coping style has profound effects on how animals respond to environmental change, and individuals within a population strikingly differ in how gene expression shifts in response to challenge. This study used a wild type Zebrafish (Danio rerio) population to: 1) identify and screen for individual coping style using a screening protocol for risk taking in groups and 2) do global transcriptomics of brains from proactive, reactive or randomly chosen individuals (n=10/group) under control conditions. Results show that within our population proactive and reactive individual coping styles can be accurately identified and may represent 10-30% of individuals within the population. Microarray data analyses identify fundamental differences between the three different groups where variance in gene expression values are reduced by using coping style as an explanatory variable. Furthermore, significant differences in mRNAs and related biological processes suggest that even under identical environmental conditions the molecular mechanisms that underpin physiological processes are very different between proactive and reactive individuals within a population.
Project description:Fathead minnow and zebrafish are among the most intensively studied fish species in environmental toxicogenomics. To aid the assessment and interpretation of subtle transcriptomic effects from treatment conditions of interest, there needs to be a better characterization and understanding of the natural variation in gene expression among fish individuals within populations. Little effort, however, has been made in this area. Leveraging the transcriptomics data from a number of our toxicogenomics studies conducted over the years, we conducted a meta-analysis of nearly 600 microarrays generated from the ovary tissue of untreated, reproductively mature fathead minnow and zebrafish samples. As expected, there was considerable batch-to-batch transcriptomic variation; this “batch-effect” appeared to impact the fish transcriptomes randomly. The overall level of variation within-batch was quite low in fish ovary tissue, making it a suitable system for studying chemical stressors with subtle biological effects. The within-batch variation, however, differed considerably among individual genes and molecular pathways. This difference in variability is probably both technical and biological, thus suggesting a need to take into account both the expression levels and variance in evaluating and interpreting the transcriptional impact on genes and pathways by experimental conditions. There was significant conservation of both the genomes and transcriptomes between fathead minnow and zebrafish. The conservation to such a degree would enable not only a comparative biology approach in studying the mechanisms of action underlying environmental stressors, but also effective sharing of a large amount of existing public transcriptomics data for future development of toxicogenomics applications.
Project description:According to the Mainz Coping Inventory (MCI) (Krohne & Egloff, 1999) people use four main strategies for coping (i.e. Non-defensive, Repressing, High-Anxious and Sensitizing). To bridge the gap between psychology and genetics, the Affymetrix GeneChip miRNA 3.0 Array (Affymetrix, Santa Clara, USA) was used to analyze blood plasma of healthy male individuals with differing MCI coping styles to gain miRNA profiles associated with the MCI assessment and to predict biomarkers for the MCI coping modes.
Project description:To gain a better understanding of the diurnal variation in gene expression, we analyzed the changes in gene expression in the eye of zebrafish. Dual color oligonucleotide microarrays were used to compare total RNA harvested from eyes of adult zebrafish at midday and midnight. Statistical analyses identified 44 genes which showed significant, 2-fold or more change; 26 genes showed decreased expression at midnight (D/L ≤ 0.5) and 18 genes showed increased expression at midnight (D/L ≥ 2). Seven genes were further analyzed using qPCR. The results of qPCR identified AANAT, Mel1a1, Mel1a3, Mel1b1, Mel1b2 and Melc as genes that showed significant change in expression at dawn, dusk, midday and midnight. These results suggest that expression of melatonin receptors is subject to diurnal regulation.