Transcriptome profile of CD200-deficient cervical lymph nodes and spleens
ABSTRACT: Comparative study between the cervical lymph nodes and spleens of C57BL/6 mice. The focus of our study was the examination of the transcriptome profiles in the lymphoid organs of C57BL/6 mice (wild type and CD200-deficient).
Project description:Reference datasets are often used to compare, interpret or validate experimental data and analytical methods. In the field of gene expression, a dozen reference datasets have been published. Typically, they consist of individual baseline or spike-in experiments carried out in a single laboratory and representing a particular set of conditions. For most organisms, however, few or no such reference datasets are publicly available. Here, we describe a new type of datasets highly representative for the spatial, temporal and response dimensions of gene expression. They result from integrating expression data from a large number of globally normalized and quality controlled public experiments and aggregating results by anatomical parts, stages of development, perturbations, drugs, diseases, neoplasms, and genotypes. The proposed datasets were created for human and several model organisms and are publicly available at www.expressiondata.org. PMI: 18 Samples were used with 2 different experimental factors: 1. 2 harvesting times (morning/afternoon) 2. 3 pos-harvesting times. 3 biological replicates were used.
Project description:It has long been appreciated that striped pair-rule transcription factor expression is necessary for convergent extension in the early Drosophila embryo, although the mechanisms that link these transcriptional regulators to planar polarity in this tissue have long been elusive. The goal of this study was to determine the transcriptional tragets of the pair-rule transcription factors Eve and Runt in Drosophila blastoderm embryos. We compared the transcriptional profiles of late blastoderm embryos injected with either water or dsRNAs against both eve and runt to identify differentially expressed genes that may directly contribute to the establishment of planar polarity during Drosophila convergent extension. Comparing the mRNA profiles from late blastoderm Drosophila embryos injected with either water (Water) or eve+runt dsRNAs (Eve), in triplicate, using Illumina HiSeq.
Project description:Genomic, proteomic, and metabolomic technologies continue to receive increasing interest from environmental toxicologists. This interest is due to the great potential of these technologies to identify detailed modes of action and to provide assistance in the evaluation of a contaminants risk to aquatic organisms. Our experimental model is the zebrafish (Danio rerio) exposed to reference endocrine disrupting compounds in order to investigate compound-induced changes in gene transcript profiles. Adult, female zebrafish were exposed to 0, 15, 40, and 100 ng/L of 17 alpha-ethynylestradiol (EE2) and concentration and time-dependent changes in hepatic gene expression were examined using Affymetrix GeneChip® Zebrafish Genome Microarrays. At 24, 48, and 168 hours, fish were sacrificed and liver mRNA was extracted for gene expression analysis (24 and 168 hours only). In an effort to link gene expression changes to effects on higher levels of biological organization, body and ovary weights were measured and blood was collected for measurement of plasma steroid hormones (17 beta-estradiol (E2), testosterone (T)) and vitellogenin (VTG) using ELISA. EE2 exposure significantly affected GSI, E2, T, VTG and gene expression. We observed 1575 genes that were significantly affected (up- or down-regulated by at least 1.5-fold (p ? 0.001) in a concentration-dependent manner by EE2 exposure at either 24 or 168 hours. EE2 exposure altered transcription of genes involved in steroid hormone homeostasis, cholesterol homeostasis, retinoic acid metabolism, and cell growth and proliferation. Plasma VTG was significantly increased at 24, 48, and 168 hours (p<0.05) at 40 and 100 ng/L and at 15 ng/L at 168 hours. E2 and T were significantly reduced following EE2 exposure at 48 and 168 hours. GSI was decreased in a dose-dependent manner at 168 hours. In this study, we identified genes involved in a variety of biological functions that have the potential to be used as markers of exposure to estrogenic substances. Future work will evaluate the use of these genes in zebrafish exposed to weak estrogens to determine if these genes are indicative of exposure to estrogens with varying potencies.
Project description:Comparison of transcriptional profiling between the 3 Neisseria meningitidis strains [serogroup A (Z2491), Serogroup B (MC58), and Serogroup C (FAM18)] and the 2 Neisseria gonorrhoeae strain (FA1090 and MS11).
Project description:transcription profiles of two groups each containing 5 strains of Disseminated gonorrhoeae (DG) and Undisseminated (superficial) gonorrhoeae (UG) were compared. An additional set of comparisons was done between 4 strains from group one Disseminated gonorrhoeae (DG) and another 4 strains from the same group.
Project description:Background: Development and application of transcriptomics-based gene classifiers for ecotoxicological applications lag far behind those of human biomedical science. Many such classifiers discovered thus far lack vigorous statistical and experimental validations, with their stability and reliability unknown. A combination of genetic algorithm/support vector machines and genetic algorithm/K nearest neighbors were used in this study to search for classifiers of endocrine disrupting chemicals (EDCs) in zebrafish. Searches were conducted on both tissue-specific and all tissue combined datasets, either across the entire transcriptome or within individual transcription factor (TF) networks previously linked to EDC effects. Candidate classifiers were evaluated by gene set enrichment analysis (GSEA) on both the original training data and a dedicated validation dataset. Results: Multi-tissue dataset yielded no classifiers. Among the 19 chemical-tissue conditions evaluated, the transcriptome-wide searches yielded classifiers for six of them, each having approximately 20 to 30 gene features unique to a condition. Searches within individual TF networks produced classifiers for 15 chemical-tissue conditions, each containing 100 or fewer top-ranked gene features pooled from those of multiple TF networks and also unique to each condition. For the training dataset, 10 out of 11 classifiers successfully identified the gene expression profiles (GEPs) of their intended chemical-tissue conditions by GSEA. For the validation dataset, classifiers for prochloraz-ovary and flutamide-ovary also correctly identified the GEPs of corresponding conditions while no classifier could predict the GEP from prochloraz-brain. Conclusions: The discrepancies in the performance of these classifiers were attributed in part to varying data complexity among the conditions, as measured to some degree by Fisher’s discriminant ratio statistic. This variation in data complexity could likely be compensated by adjusting sample size for individual chemical-tissue conditions, thus suggesting a need for a preliminary survey of transcriptomic responses before launching a full scale classifier discovery effort. While GSEA appeared to provide a flexible and effective tool for application of gene classifiers, a similar but more refined algorithm, connectivity mapping, should also be explored for ecotoxicological applications. The distribution characteristics of classifiers across tissues, chemicals, and TF networks suggested a differential biological impact among the EDCs on zebrafish transcriptome involving some basic cellular functions. chemical abbreviations: EE2, 17α-ethynyl estradiol; FAD, fadrozole; TRB, 17 -trenbolone; FIP, fipronil; PRO, prochloraz; FLU, flutamide; MUS, muscimol; KET, ketoconazole; TRI, trilostane; VIN, vinclozolin Since this study was conducted in several phases, three different version of Agilent zebrafish two color microarrays were used based on their availability at the time. These include G2518A (designID 013223) and G2519F (designID 015064, 019161). There were a total of 58 treatment conditions with various combinations of chemical, tissue type, exposure time, and gender. Each condition contained eight to 12 independent samples, half from chemical-treated fish and half from water- control fish.