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accession-icon SRP034166
Silencing of odorant receptor gene expression by G protein ß? signaling ensures the expression of one odorant receptor per olfactory sensory neuron
  • organism-icon Danio rerio
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Olfactory sensory neurons express just one out of a possible ~1000 odorant receptor genes, reflecting an exquisite mode of gene regulation. In one model, once an odorant receptor is chosen for expression, other receptor genes are suppressed by a negative feedback mechanism, ensuring a stable functional identity of the sensory neuron for the lifetime of the cell. The signal transduction mechanism subserving odorant receptor gene silencing remains obscure, however. Here we demonstrate in the zebrafish that odorant receptor gene silencing is dependent on receptor activity. Moreover, we show that signaling through G protein ß? subunits is both necessary and sufficient to suppress the expression of odorant receptor genes, and likely acts through histone methylation to maintain the silenced odorant receptor genes in transcriptionally inactive heterochromatin. These results provide new insights linking receptor activity with the epigenetic mechanisms responsible for ensuring the expression of one odorant receptor per olfactory sensory neuron. Overall design: Total 6 samples were analyzed-3 controls & 3 samples

Publication Title

Normalization of RNA-seq data using factor analysis of control genes or samples.

Sample Metadata Fields

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accession-icon GSE4035
Selection for contextual fear conditioning affects anxiety-like behaviors and gene expression (palme-affy-mouse-84746)
  • organism-icon Mus musculus
  • sample-icon 20 Downloadable Samples
  • Technology Badge Icon

Description

These data are from the brains (amygdala and hippocampus) of mice originally derived from a cross between C57BL/6J and DBA/2J inbred strains. We used short-term selection to produce outbred mouse lines with differences in contextual fear conditioning, which is a measure of fear learning. We selected for a total of 4 generations. Fear learning differed in the selected lines and this difference was stronger with each successive generation of selection. These mice also showed differences for measures of anxiety-like behavior, but were not different for tests of non-fear motivated learning, suggesting that selection altered alleles that are specifically involved in emotional behaviors. We identified several QTLs for the selection response. We used Affymetrix microarrays to identify differentially expressed genes in the amygdala and hippocampus of mice from the final generation of selection. Amygdala and hippocampus samples were rapidly dissected out of experimentally nave mice f rom each selected line. Three samples were pooled and hybridized to each array. Experimentally nave mice were used because the behavior of the mice can be reliably anticipated due to their lineage. Thus, these gene expression differences are not due to the response to human handling, foot shock or fear-inducing conditioned stimuli. We have a second similar study that focuses on a different selected population that was based on C57BL/6J and A/J mice (see GES4034).

Publication Title

Selection for contextual fear conditioning affects anxiety-like behaviors and gene expression.

Sample Metadata Fields

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accession-icon SRP055573
RNA-seq of zebrafish brain, liver and skin during perturbation with rotenone at young and old age
  • organism-icon Danio rerio
  • sample-icon 68 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2000

Description

Zebrafish of two different age groups (12 and 36 months) were treated with low amounts of rotenone (mild stress) and compared to untreated zebrafish. Two different durations were used (3 and 8 weeks). Illumina sequencing (HiSeq2000) was applied to generate 50bp single-end reads. Jena Centre for Systems Biology of Ageing - JenAge (www.jenage.de) Overall design: 68 sample: 3 tissues (brain, liver, skin); 2 age groups (12 and 36 months); controls and rotenone treated samples; 2-6 biological replicates for each group

Publication Title

Longitudinal RNA-Seq Analysis of Vertebrate Aging Identifies Mitochondrial Complex I as a Small-Molecule-Sensitive Modifier of Lifespan.

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accession-icon SRP074847
mRNAs Establish and Maintain Uniform Cellular Phenotypes during the Architecture of Complex Tissues
  • organism-icon Danio rerio
  • sample-icon 4 Downloadable Samples
  • Technology Badge IconIlluminaGenomeAnalyzer

Description

Proper functioning of tissues requires cells to behave in uniform, well-organized ways. Conversely, many diseases involve increased cellular heterogeneity due to genetic and epigenetic alterations. Defining the mechanisms that counteract phenotypic variability is therefore critical to understand how tissues sustain homeostasis. Here, we carried out a single-cell resolution screen of zebrafish embryonic blood vessels upon mutagenesis of single microRNA (miRNA) genes and multi-gene miRNA families. We found that miRNA mutants exhibit a profound increase in cellular phenotypic variability of specific vascular traits. Genome-wide analysis of endothelial miRNA target genes identified antagonistic regulatory nodes of vascular growth and morphogenesis signaling that allow variable cell behaviors when derepressed. Remarkably, lack of such miRNA activity greatly sensitized the vascular system to microenvironmental changes induced by pharmacological stress. We uncover a previously unrecognized role of miRNAs as a widespread protective mechanism that limits variability in cellular phenotypes. This discovery marks an important advance in our comprehension of how miRNAs function in the physiology of higher organisms. Overall design: Analysis of differential genes expression in Zebrafish endothelial cells for 4 different developmental stages

Publication Title

MicroRNAs Establish Uniform Traits during the Architecture of Vertebrate Embryos.

Sample Metadata Fields

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refine.bio is a repository of uniformly processed and normalized, ready-to-use transcriptome data from publicly available sources. refine.bio is a project of the Childhood Cancer Data Lab (CCDL)

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Cite refine.bio

Casey S. Greene, Dongbo Hu, Richard W. W. Jones, Stephanie Liu, David S. Mejia, Rob Patro, Stephen R. Piccolo, Ariel Rodriguez Romero, Hirak Sarkar, Candace L. Savonen, Jaclyn N. Taroni, William E. Vauclain, Deepashree Venkatesh Prasad, Kurt G. Wheeler. refine.bio: a resource of uniformly processed publicly available gene expression datasets.
URL: https://www.refine.bio

Note that the contributor list is in alphabetical order as we prepare a manuscript for submission.

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