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Data · dataset · 2017

Differential gene expression in the rat hippocampus and dorsal raphe nucleus following chronic low level exposure to the pesticide diazinon

Listed in Teesside University Research Data Repository

Excel files (hippocampus and dorsal raphe nucleus) containing differential brain gene expression data and Ingenuity pathway analysis values from rats chronically exposed to diazinon.

Description

Adult male Lister Hooded rats (Charles River, UK) were orally administered the organophosphate pesticide diazinon 0, 1 or 2 mg / kg (n = 12 per dose; 1 ml/kg olive oil) for 12 weeks, 5 consecutive days per week. Animals were overdosed with isoflurane, and trunk blood was collected and brains rapidly removed, cut into 3 mm coronal slices and stored at -80°C. The hippocampus from the right hemisphere (0, 2 mg / kg diazinon, n = 12 per dose) and whole dorsal raphe nucleus (0, 2 mg / kg diazinon, n = 6 per dose) was homogenised in Tri Reagent.

RNA was extracted from homogenate and shipped to AROS Applied Biotechnology (Denmark), who used Affymetrix GeneChip® HT RG-230 PM 24-Array Plate on the Gene Titan platform to conduct expression profiling. Statistical analysis was conducted by the Bioinformatics Service (Newcastle University). Raw data were exported to the Bioconductor package, RankProd, log-scale transformed (log, basis 2) and normalised (non-linear transformation employing the loess smoother).

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Probe sets (78,963) were detected in all samples (20% and 90% bound of the fluorescence intensity of the chip). For the detection of gene expression changes, an ANOVA was applied with a cut off at a false discovery rate p < 0.05. All up-regulated and All down-regulated worksheets = probe sets significantly detected in samples.

Significant worksheet = genes significantly different between vehicle and diazinon treated animals function, pathway and network worksheets = Ingenuity pathway analysis was conducted on genes that were significantly altered to generate functions and canonical pathways using the Ingenuity Systems reference set that were most significant to the data set. The p value was determined by the probability that the association between the genes in the dataset and the function or canonical pathway is explained by chance alone.

The significance of the association between the data set and the function or canonical pathway was calculated using Fischer’s exact test. Networks were generated using the IPA Network Generation Algorithm and scored based on the number of network eligible molecules they contained from the dataset. Funded by Health Protection Agency and a Department of Health Policy Research Programme grant (UK).

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