BioProject

To identify transcriptional targets altered in the embryonic heart after exposure to TCE, and possible protective effects of folate, we used DNA microarray technology to profile gene expression in embryonic mouse hearts with maternal TCE exposure and dietary changes in maternal folate. More...

To identify transcriptional targets altered in the embryonic heart after exposure to TCE, and possible protective effects of folate, we used DNA microarray technology to profile gene expression in embryonic mouse hearts with maternal TCE exposure and dietary changes in maternal folate. Results: Exposure to low doses of TCE (10ppb) caused extensive alterations in transcripts encoding proteins involved in transport, ion channel, transcription, differentiation, cytoskeleton, cell cycle and apoptosis. Exogenous folate did not offset the effects of TCE exposure on normal gene expression and both high and low levels of folate produced additional significant changes in gene expression. Conclusions: A mechanism where TCE induces a folate deficiency does not explain altered gene expression patterns in the embryonic mouse heart. The data further suggest that use of folate supplementation, in the presence of this toxin, may be detrimental and non-protective of the developing embryo. Overall design: Six sample groups (control and TCE exposed from each one of the three folate diet groups) were tested, each with two biological replicates for a total of 12 sample groups. Total RNA from each group was processed by the University of Arizona microarray facility (Genomics Shared Service, Tucson, AZ). RNA purity was evaluated using an Eppendorf BioPhotometer (Eppendorf North America, Westbury, NY) to obtain values of nucleotides, organics, proteins, and contaminants in the samples. Viable RNA had 260/280 ratios between 1.8 and 2.0 or higher. RNA integrity was confirmed using an Agilent 2100 Bioanalyzer (Agilent Technologies, Waldbronn, Germany) following the RNA 6000 Nano Chip Series II Assay protocol. Twelve Affymetrix Mouse Gene 1.0 ST arrays (Affymetrix, Santa Clara, CA) containing over 28,000 gene-level probe sets were used for genome wide expression profiling. The arrays were processed according to the protocol (GeneChip Whole Transcript) Sense Target Labeling Assay Manual, version 4) established by Affymetrix. Briefly, 400ng of total RNA were reverse transcribed into double stranded cDNA using the Affymetrix WT cDNA Synthesis and Amplification kit. The entire cDNA was then transcribed into cRNA overnight, cleaned using the Affymetrix GeneChip Sample Cleanup Module, and quantified on a NanoDrop 1000 (Thermo Scientific, Wilmington, DE). 8ug of cRNA were reverse transcribed into ssDNA, and labeled. Aliquots of the labeled DNA were combined with the hybridization solution overnight. The arrays were scanned using the Affymetrix GeneChip Scanner 3000 with 7G upgrade. The image generated was analyzed using the Affymetrix GeneChip Operating Software (GCOS) were .DAT (image), .CEL (cell intensity data), .CHP (probe analysis data) files were generated. Statistical analysis of DNA microarrays: The Affymetrix mouse gene ST arrays were processed with a bioconductor library (http://www.bioconductor.org) designed for this array. The arrays were then normalized using the RMA function in the oligo library of bioconductor. In order to identify poor quality arrays, Spearman correlation coefficients between all arrays were computed. A plot of the coefficients revealed that correlations between the arrays were 0.98 or greater, indicating that a relatively small number of genes were changing in response to the treatments. As a further control, the distribution of values for positive and negative control probes were examined on each array and found to have the correct expected separation. Since there were only two biological replicates due to the complexity of the sample preparation, a specific approach was used that identified probes that showed a consistent change between biological duplicates. A cutoff value for the change between treatments of 1.5 fold was chosen based on an examination of the distribution of expression values on these arrays and identified between 200-1000 probes that were varying to the greatest extent. Probe lists were generated as described below. Briefly, the objective was to find genes that were changing between treatments while reducing the effects of the biological variation between duplicate samples. To compare two treatments, probe expression ratios for all 4 possible combinations of the duplicate arrays were calculated. If 2 or more of these ratios were 1.5 fold or greater, the gene was considered to be changed. These probe sets were annotated using Affymetrix data files and the affected genes, biological functions, and pathways were identified. For the biochemical pathway analysis, lists of genes involved in pathways of biological interest were obtained from the KEGG database using the BIORAG resource (http://www.biorag.org ). Genes showing expression ratios between treatments of greater than 1.5 fold were then identified. The additional processed data files are linked on the Series record. Less...