Project description:This SuperSeries is composed of the following subset Series:; GSE11940: Topoisomerase II inhibition involves characteristic chromosomal expression patterns: Doxorubicin study; GSE11941: Topoisomerase II inhibition involves characteristic chromosomal expression patterns: Trovafloxacin study Experiment Overall Design: Refer to individual Series
Project description:This SuperSeries is composed of the following subset Series:; GSE13136: Identification of candidate neuroblastoma genes by combining genomic and expression microarrays: expression data; GSE13137: Identification of candidate neuroblastoma genes by combining genomic and expression microarrays: SNP data Experiment Overall Design: Refer to individual Series
Project description:An appendix to the published Gaulton et al. work (PMID: 20118932; E-GEOD-17616). In the original paper, the authors note that samples 1 and 2 are not as pure as the third sample. This appendix provides FAIRE-Seq data obtained from a purified islet sample to replace the problematic published data. The goal of the original experiment was to identify active regulatory DNA in human pancreatic islets. This was accomplished using high-throughput sequencing of genomic regions isolated using FAIRE from three purified pancreatic islet samples to identify sites of open chromatin.
Project description:Background; Mouse and rat models are mainstays in pharmacology, toxicology and drug development â but differences between strains and between species complicate data interpretation and application to human health. Dioxin-like polyhalogenated aromatic hydrocarbons represent a major class of environmentally and economically relevant toxicants. In mammals dioxin exposure leads to a broad spectrum of adverse affects, including hepatotoxicity of varying severity. Several studies have shown that dioxins extensively alter hepatic mRNA levels. Surprisingly, though, analysis of a limited portion of the transcriptome revealed that rat and mouse responses diverge greatly (Boverhof et al. Toxicol Sci 94:398â416, 2006). Results; We employed oligonucleotide arrays to compare the response of 8,125 rat and mouse orthologs. We confirmed that there is limited inter-species overlap in dioxin-responsive genes. Rat-specific and mouse-specific genes are enriched for specific functional groups which differ between species, conceivably accounting for species-specificities in liver histopathology. While no evidence for the involvement of copy-number variation was found, extensive inter-species variation in the transcriptional-regulatory network was identified; Nr2f1 and Fos emerged as candidates to explain species-specific and species-independent responses, respectively. Conclusion; Our results suggest that a small core of genes is responsible for mediating the similar features of dioxin hepatotoxicity in rats and mice but non-overlapping pathways are simultaneously at play to result in distinctive histopathological outcomes. The extreme divergence between mouse and rat transcriptomic responses appears to reflect divergent transcriptional-regulatory networks. Taken together, these data suggest that both rat and mouse models should be used to screen the acute hepatotoxic effects of drugs and toxic compounds. Experiment Overall Design: Wild-type Long-Evans(Kuopio) rats were treated with 100 ug/kg TCDD (n=4) or with cornoil vehicle as control (n=4) for 19 hours. Their livers were then excised, RNA extracted, and the resulting samples hybridized to Affymetrix RAE230A arrays to survey changes in the transcriptome profile.
Project description:Fear conditioning (FC) is a behavioral paradigm that measures an animal's ability to learn fear related information. FC is measured by pairing a mild foot-shock with the surroundings in which the shock was recieved. Upon being placed back in the context, mice exhibit freezing behavior, which is a species-specific response to fear. We have previously used selective breeding to produce lines of mice with high or low levels of freezing behavior. This experiment is a replication of a previous experiment that produced lines of mice with high or low levels of freezing behavior. These lines derive from different progenitor mouse strains. We are able to identify alleles that govern the genetic variability for FC by using chromosomal markers in these selected lines. Using microarrays, we will identify differences in gene expression in two key brain regions: amygdala and hippocampus. Gene expression differences and data regarding chromosomal regions involved in the behavior will be compared to identify particular genes that are both differentially expressed and whose expression is governed by alleles that fall into critical chromosomal regions.,We will compare gene expresion in the amygdala and hippocampus (brain regions known to be relevant to fear behavior) from the these two lines of mice and to the those in the previous experiment. Bayesian statistics will be used in an effort to identify gene expression that affects fear behavior.,We hypothesize that selection has acted in part by changing the frequency of alleles that cause differential expression of key genes in the amygdala and hippocampus of our selected lines. Slective breeding changes the frequency of trait relevand (FC) alleles. A relevant allele is expected to increas in one selected line and decrease in the oppositely selected line. Some trait relevant alleles are expected to cause changes in the level of expression at particular genes.,Amygdala and hippocampus will be rapidly dissected out of experimentally naïve mice from each line. Naïve mice will be used for expression studies since the behavior of the mice in the FC test can be reliably anticipated due to their lineage. We have practiced these procedures, and can accurately and reproducibly remove these regions in less than 5 minutes. Different mice will be used to collect each brain region, since the dissection of hippocampus disrupts the removal of amygdala. We will collect enough samples from each region to accommodate a total of 6 microarrays per brain region, per line, thus we will use a total of 24 microarrays. We anticipate that a single brain region will be sufficient to for a microarray. However, we propose to utilize three samples per microarray, because this will reduce variability due to environmental factors and due to slight variability in our dissection procedures. Once this tissue is removed, we will isolate RNA for shipment to the Microarray consortium. We will also collect spleens from each subject as a source of genomic DNA, in order to permit direct comparison of genotype and expression phenotypes. Once we have the results of the microarray analysis, we use WebQTL.org to identify the chromosomal locations of alleles that are know to influence the expression of genes for which we have found differential expression. We will then superimpose this information on trait relevant chromosomal regions identified from our selected lines. This will allow us to rapidly identify genes which may account for genetic variability in FC due to differential expression. Such genes will then be subjected to further study.
Project description:Human urine samples measured using pHILIC LC-MS/MS and LC-MS in negative ionisation mode. Urine samples were from clinical cohort in which we expected to find substantial amounts of xenobiotics. Samples were used for MS2LDA substructure discovery to find the building blocks of metabolomics.
Project description:Human urine samples measured using pHILIC LC-MS/MS and LC-MS in positive ionisation mode. Urine samples were from clinical cohort in which we expected to find substantial amounts of xenobiotics. Samples were used for MS2LDA substructure discovery to find the building blocks of metabolomics.
Project description:Note that this only contains the positive fragmentation mode data obtained in the project filtered from the posneg combined mode from MSV000082971 - see further details on all parameters and settings there and in the paper.