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accession-icon GSE14585
Expression data from mouse normal thymus, thymus tumor, and XIST resistant thymus tumor
  • organism-icon Mus musculus
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

The non-coding Xist RNA triggers silencing of one of the two female X chromosomes during X inactivation in mammals. Gene silencing by Xist is restricted to special developmental contexts found in cells of the early embryo and specific hematopoietic precursors. The absence of critical silencing factors might explain why Xist cannot silence outside these contexts. Here, we show that Xist can also initiate silencing in a lymphoma model. Using the tumor context we identify the special AT rich binding protein SATB1 as an essential silencing factor. We show that loss of SATB1 in tumor cells abrogates the silencing function of Xist. In normal female lymphocytes Xist localizes along SATB1 filaments and, importantly, forced Xist expression can relocalize SATB1 into the Xist cluster. This reciprocal influence on localization suggests a molecular interaction between Xist and SATB1. SATB1 and its close homologue SATB2 are expressed during the initiation window for X inactivation in embryonic stem cells and are recruited to surround the Xist cluster. Furthermore, ectopic expression SATB1 or SATB2 enables gene silencing by Xist in embryonic fibroblasts, which normally do not provide an initiation context. Thus, SATB1 functions as a crucial initiation factor and may act to organize genes for silencing by Xist during the initiation of X inactivation.

Publication Title

SATB1 defines the developmental context for gene silencing by Xist in lymphoma and embryonic cells.

Sample Metadata Fields

Specimen part

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accession-icon GSE23711
Expression profiling of nhp6 mutants and wildtype yeast cells (Saccharomyces cerevisiae)
  • organism-icon Saccharomyces cerevisiae
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Yeast Genome 2.0 Array (yeast2)

Description

The basic unit of genome packaging is the nucleosome, and nucleosomes have long been proposed to restrict DNA accessibility both to damage and to transcription. However, nucleosome number in cells was considered fixed, and no condition was described where nucleosome number was reduced. We show here that mammalian cells lacking High Mobility Group Box 1 protein (HMGB1) contain a reduced amount of core, linker and variant histones, and a correspondingly reduced number of nucleosomes. Yeast nhp6 mutants lacking NHP6A and B proteins, which are related to HMGB1, also have a reduced amount of histones and fewer nucleosomes. Nucleosome limitation in both mammalian and yeast cells increases the sensitivity of DNA to damage, increases transcription globally, and the relative expression of about 10% of genes. In yeast nhp6 cells the loss of more than one nucleosome in four does not affect the location of nucleosomes and their spacing, but nucleosomal occupancy. The decrease in nucleosomal occupancy is non-uniform, and our results can be modelled assuming that different nucleosomal sites compete for the available histones: sites with high affinity are almost always packaged into nucleosomes both in wt and nucleosome-depleted cells, whereas sites with low affinity are less frequently packaged in nucleosome-depleted cells. We suggest that by modulating the occupancy of nucleosomes histone availability may constitute a novel layer of epigenetic regulation.

Publication Title

Substantial histone reduction modulates genomewide nucleosomal occupancy and global transcriptional output.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE61451
Gene Expression Changes in Nemaline Myopathy
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Skeletal muscle microRNA and messenger RNA profiling in cofilin-2 deficient mice reveals cell cycle dysregulation hindering muscle regeneration.

Sample Metadata Fields

Specimen part

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accession-icon GSE61404
mRNA Expression Changes with Cofilin-2 Deficiency
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

mRNA Expression in Quadriceps Muscle from Cofilin-2 Null Mice Compared to WT Littermates on Day 7

Publication Title

Skeletal muscle microRNA and messenger RNA profiling in cofilin-2 deficient mice reveals cell cycle dysregulation hindering muscle regeneration.

Sample Metadata Fields

Specimen part

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accession-icon GSE58015
Gene Expression Data in Human Monocyte-derived Dendritic Cell (MoDC) from Young and Aged Donors
  • organism-icon Homo sapiens
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A 2.0 Array (hgu133a2)

Description

Dendritic cells (DCs) are major antigen-presenting cells that play a key role in initiating and regulating innate and adaptive immune responses. DCs are critical mediators of tolerance and immunity. The functional properties of DCs changes with age.

Publication Title

Alterations in gene array patterns in dendritic cells from aged humans.

Sample Metadata Fields

Age, Specimen part, Subject

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accession-icon SRP056784
Omic Personality: Implications of Stable Transcript and Methylation Profiles for Personalized Medicine [RNA-Seq]
  • organism-icon Homo sapiens
  • sample-icon 35 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2000

Description

Background: Personalized medicine is predicated on the notion that individual biochemical and genomic profiles are relatively constant in times of good health and to some extent predictive of disease or therapeutic response. We report a pilot study quantifying gene expression and methylation profile consistency over time, addressing the reasons for individual uniqueness, and its relation to N=1 phenotypes. Methods: Whole blood samples from 4 African American women, 4 Caucasian women, and 4 Caucasian men drawn from the Atlanta Center for Health Discovery and Well Being study at three successive 6-month intervals were profiled by RNASeq, miRNASeq, and Illumina Methyl-450 arrays. Standard regression approaches were used to evaluate the proportion of variance for each type of omic measure that is among individuals, and to quantify correlations among measures and with clinical attributes related to wellness. Results: Longitudinal omic profiles are in general highly consistent over time, with an average of 67% of the variance in transcript abundance, 42% of CpG methylation level (but 88% for the most differentiated CpG per gene), and 50% of miRNA abundance among individuals, which are all comparable to 74% of the variance among individuals for 74 clinical traits. One third of the variance can be attributed to differential blood cell type abundance, which is also fairly stable over time, and a lesser amount to eQTL effects, whereas seven conserved axes of covariance that capture diverse aspects of immune function explain over half of the variance. These axes also explain a considerable proportion of individually extreme transcript abundance, namely approximately 100 genes that are significantly up- or down-regulated in each person and are in some cases enriched for relevant gene activities that plausibly associate with clinical attributes. A similar fraction of genes have individually divergent methylation levels, but these do not overlap with the transcripts, and fewer than 20% of genes have significantly correlated methylation and gene expression. Conclusions: People express an “omic personality” consisting of peripheral blood transcriptional and epigenetic profiles that are constant over the course of a year and reflect various types of immune activity. Baseline genomic profiles can provide a window into the molecular basis of traits that might be useful for explaining medical conditions or guiding personalized health decisions. Overall design: Whole blood samples from 12 subjects drawn from the Atlanta Center for Health Discovery and Well Being study at three successive 6-month intervals were profiled by RNASeq, miRNASeq, and Illumina Methyl-450 arrays.

Publication Title

Omic personality: implications of stable transcript and methylation profiles for personalized medicine.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP052238
Gene expression profile for male SD Rats with and without traumatic brain injury (TBI) by RNA-Seq
  • organism-icon Rattus norvegicus
  • sample-icon 10 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

To investigate the effects of TBI on affecting the gene expressions in the hippocampus of male SD rats by RNA-Seq.. Overall design: Male Sprague–Dawley (SD) rats weighing between 200 and 240 g were housed in cages and maintained in environmentally-controlled rooms (22–24C) with a 12-h light/dark cycle. After acclimatization for 1 week on standard rat chow, the rats were subjected to TBI by fluid percussion injury (FPI) or sham surgery. At 1 week post-surgery the rats were tested for learning abilities, and then were sacrificed by decapitation. The fresh tissues including the hippocampus were dissected out, flash frozen, and stored at -70°C for later transcriptome and DNA methylome sequencing experiments. All experiments were performed in accordance with the United States National Institutes of Health Guide for the Care and Use of Laboratory Animals and were approved by the University of California at Los Angeles Chancellor’s Animal Research Committee.

Publication Title

Traumatic Brain Injury Induces Genome-Wide Transcriptomic, Methylomic, and Network Perturbations in Brain and Blood Predicting Neurological Disorders.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE12413
Prediction of left ventricle systolic dysfunction in mice using gene expression profiling
  • organism-icon Mus musculus
  • sample-icon 86 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

We tested the hypothesis that a set of differentially expressed genes could be used to predict cardiovascular phenotype in mice after prolonged catecholamine stress.

Publication Title

Gene expression profiling: classification of mice with left ventricle systolic dysfunction using microarray analysis.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP076298
A-to-I RNA editing promotes developmental-stage specific gene and lncRNA expression
  • organism-icon Caenorhabditis elegans
  • sample-icon 27 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

A-to-I RNA editing is a conserved and widespread phenomenon in which adenosine (A) is converted to inosine (I) by adenosine deaminases (ADARs) in double-stranded RNA regions. Although human RNAs contain millions of A-to-I editing sites, most of these occur in noncoding regions and their function is unknown. Knockdown of ADAR enzymes in C. elegans causes defects in normal development but is not lethal as it is in human and mouse, making C. elegans an ideal organism for studying the regulatory effects of RNA editing on the transcriptome. Previous studies in C. elegans indicated competition between RNA interference (RNAi) and RNA editing mechanisms, with the observation that lack of both mechanisms can suppress defects observed when only RNA editing is absent. To study the effects of RNA editing on gene expression and function, we established a novel screen that enabled to identify thousands of RNA editing sites in non-repetitive regions in the genome. These include dozens genes that are edited at their 3’UTR region. We found that these genes are mainly germline and neuronal genes and that they are downregulated in the absence of ADAR enzymes. Moreover, we discovered that almost half of these genes are edited in a developmental-specific manner. In addition, we found that many pseudogenes and other lncRNAs are also extensively downregulated in the absence of ADARs in embryo but not L4 larva developmental stage, while this downregulation is not observed in additional knockout of RNAi. Taken together, our results suggest a role for RNA editing in normal growth and development by regulating silencing via RNAi. Overall design: RNA-seq samples were generated from: 1. wildtype (N2) at embryo stage 2. wildtype (N2) at L4 stage 3. ADAR mutant (BB21 or BB4) worms at L4 stage 4. ADAR mutant (BB21 or BB4) worms at embryo stage 5. ADAR mutant and RNAi mutant (BB23, BB24) at embryo stage RNA in high and low molecular weight fractions was extracted by mirVana kit (ambion). mRNA was sequenced from the high molecular weight fraction by means of Illumina TruSeq® RNA Sample Preparation kit automated by Agilent Bravo Automated Liquid Handling Platform. The resulting libraries were sequences with an Illumina HiSeq 2500.

Publication Title

A-to-I RNA editing promotes developmental stage-specific gene and lncRNA expression.

Sample Metadata Fields

Specimen part, Cell line, Subject

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accession-icon GSE8994
A Comparison of microarray and MPSS Technology Platforms for Expression Analysis of Arabidopsis
  • organism-icon Arabidopsis thaliana
  • sample-icon 21 Downloadable Samples
  • Technology Badge Icon Affymetrix Arabidopsis ATH1 Genome Array (ath1121501)

Description

A comparison of microarray and MPSS technologies can help to establish the metrics for data comparisons across these technology platforms and determine some of the factors affecting the measurement of mRNA abundances using different platforms. Here, different Treatments/Conditions based on different Arabidopsis tissues were used for three different platforms include MPSS, Affymetrix and Agilent.

Publication Title

A comparison of microarray and MPSS technology platforms for expression analysis of Arabidopsis.

Sample Metadata Fields

No 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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