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accession-icon GSE110531
Developmental and Functional Heterogeneity of White Adipocytes within a Single Fat Depot
  • organism-icon Mus musculus
  • sample-icon 23 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

We and others have previously observed that adipocytes and preadipocytes taken from different adipose tissue depots are characterized by differential expression of developmental and patterning genes (Dankel et al., 2010; Ferrer-Lorente et al., 2014; Gesta et al., 2006; Lee et al., 2017a; Lee et al., 2013; Macotela et al., 2012; Tchkonia et al., 2007; Yamamoto et al., 2010). To investigate how adipocyte heterogeneity and differences in the expression of developmental genes might impact the biology of adipocytes and preadipocytes, we created preadipocyte cell lines from the stromovascular fraction (SVF) isolated from the scapular white, inguinal, perigonadal, perirenal, and mesenteric fat pads of 6-week old male Immortomouse (Jat et al., 1991).During routine culture of the subcutaneous and visceral/perigonadal clonal cell lines, we observed extreme variation in media acidification rates that was unrelated to the fat pad of origin, the differentiation capacity of the cells, or the rate of their proliferation, suggesting metabolic heterogeneity. To further investigate this possibility, 24 clonal cell lines (12 each from subcutaneous and perigonadal fat) were selected based on variable media acidification rates, and their mRNA expression pattern determined by microarray analysis. The expression data was clustered using three different algorythms, and the consensus was used to categorize each type of adipose tissue.

Publication Title

Developmental and functional heterogeneity of white adipocytes within a single fat depot.

Sample Metadata Fields

Specimen part, Cell line

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accession-icon GSE34681
Effects of Ars2 or DGCR8 siRNA on gene and microRNA expression
  • organism-icon Homo sapiens
  • sample-icon 18 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Ars2 promotes proper replication-dependent histone mRNA 3' end formation.

Sample Metadata Fields

Specimen part, Cell line, Treatment

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accession-icon GSE19891
Regulation of Splicing by Clinical Drugs
  • organism-icon Homo sapiens
  • sample-icon 15 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [probe set (exon) version (huex10st)

Description

Alternative splicing analysis after treatment with three clinically aproved drugs

Publication Title

Rapid-response splicing reporter screens identify differential regulators of constitutive and alternative splicing.

Sample Metadata Fields

Cell line, Treatment

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accession-icon GSE34679
Effects of Ars2 or DGCR8 siRNA on gene expression
  • organism-icon Homo sapiens
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Ars2 is a component of the nuclear cap-binding complex that is required for cellular proliferation and contributes to microRNA biogenesis. Arrays were performed to determine the repertoire of genes that change following knock-down of Ars2. Knock-down of DGCR8 was also performed to determine which changes in Ars2 knock-down cells resulted from defects in microRNA expression.

Publication Title

Ars2 promotes proper replication-dependent histone mRNA 3' end formation.

Sample Metadata Fields

Specimen part, Cell line, Treatment

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accession-icon GSE72179
Increased activity of canonical NF-kB signaling in muscle fibers alters the satellite cell niche and restrains muscle stem cell function during aging
  • organism-icon Mus musculus
  • sample-icon 7 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 2.0 ST Array (mogene20st)

Description

It has been known for some time that muscle repair potential becomes increasingly compromised with advancing age, and that this age-related defect is associated with reduced activity of muscle satellite cells and with the presence of chronic, low grade inflammation in the muscle. Working from the hypothesis that a heightened inflammatory tone in aged muscle could contribute to poor regenerative capacity, we developed genetic systems to inducibly alter inflammatory gene expression in satellite cells or muscle fibers by modulation of the activity of nuclear factor B (NF-B), a master transcriptional regulator of inflammation whose activity is upregulated in many cell types and tissues with age. These studies revealed that activation of NF-B activity in muscle fibers, but not in satellite cells, drives muscle dysfunction and that lifelong inhibition of NF-B activity in myofibers preserves muscle regenerative potential with aging via cell-non-autonomous effects on satellite cell function. Further analysis of differential gene expression in muscles with varying NF-B activity identified a secreted phospholipase (PLA2G5) as a myofiber-expressed NF-B-regulated gene that governs muscle regenerative capacity with age. Together, these data suggest a model in which NF-B activation in muscle fibers increases PLA2G5 expression and drives the impairment in regenerative function characteristic of aged muscle. Importantly, inhibition of NF-B function reverses this impairment, suggesting that FDA-approved drugs, like salsalate, a prodrug form of sodium salicylate, may provide new therapeutic avenues for elderly patients with reduced capacity to recover effectively from muscle injury.

Publication Title

Age-associated NF-κB signaling in myofibers alters the satellite cell niche and re-strains muscle stem cell function.

Sample Metadata Fields

Age

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accession-icon SRP026297
Genome wide mapping of effects of U6atac knockdown on pre-mRNA splicing
  • organism-icon Homo sapiens
  • sample-icon 2 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

This project looks into experimentally identifying all minor introns by knocking down the minor spliceosome''s catalytic snRNP, U6atac. Overall design: Knockdown of U6atac by antisense morpholino followed by examining mRNA splicing by RNA-seq

Publication Title

Minor introns are embedded molecular switches regulated by highly unstable U6atac snRNA.

Sample Metadata Fields

Specimen part, Cell line, Subject

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accession-icon GSE12814
Identifying the molecular signature of the interstitial del(7q) subgroup of uterine leiomyomata using a paired analysis
  • organism-icon Homo sapiens
  • sample-icon 33 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Uterine leiomyomata (UL), the most common neoplasm in reproductive-age women, have recurrent cytogenetic abnormalities including del(7)(q22q32). To develop a molecular signature, matched del(7q) and non-del(7q) tumors identified by FISH or karyotyping from 11 women were profiled with expression arrays. Our analysis using paired t-tests demonstrates this matched design is critical to eliminate confounding effects of genotype and environment that underlie patient variation. A gene list ordered by genome-wide significance showed enrichment for the 7q22 target region. Modification of the gene list by weighting each sample for percent of del(7q) cells to account for the mosaic nature of these tumors further enhanced the frequency of 7q22 genes. Pathway analysis revealed two of the 19 significant functional networks were associated with development and the most represented pathway was protein ubiquitination, which can influence tumor development by stabilizing oncoproteins and destabilizing tumor suppressor proteins. Array CGH (aCGH) studies determined the only consistent genomic imbalance was deletion of 9.5 megabases from 7q22-7q31.1. Combining the aCGH data with the del(7q) UL mosacism-weighted expression analysis resulted in a list of genes that are commonly deleted and whose copy number is correlated with significantly decreased expression. These genes include the proliferation inhibitor HPB1, the loss of expression of which has been associated with invasive breast cancer, as well as the mitosis integrity-maintenance tumor suppressor RINT1. This study provides a molecular signature of the del(7q) UL subgroup and will serve as a platform for future studies of tumor pathogenesis.

Publication Title

Identifying the molecular signature of the interstitial deletion 7q subgroup of uterine leiomyomata using a paired analysis.

Sample Metadata Fields

Disease

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accession-icon GSE18096
Identifying the molecular signature of the t(12;14) subgroup of uterine leiomyomata using a paired analysis
  • organism-icon Homo sapiens
  • sample-icon 24 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Uterine leiomyomata (UL), the most common neoplasm in reproductive age women, have recurrent cytogenetic abnormalities including t(12;14). To develop a molecular signature, matched t(12;14) and non-t(12;14) tumors identified by FISH or karyotyping from each of 9 women were profiled using Affymetrix GeneChip U133 Plus 2.0 oligonucleotide arrays. Model analysis demonstrated the necessity for a matched design to eliminate the confounding effect of genotype and environment that underlay patient to patient variation.

Publication Title

Expression profiling of uterine leiomyomata cytogenetic subgroups reveals distinct signatures in matched myometrium: transcriptional profilingof the t(12;14) and evidence in support of predisposing genetic heterogeneity.

Sample Metadata Fields

Sex, Specimen part

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accession-icon SRP049596
RNA-seq analysis of germline stem cell removal and loss of SKN-1 in C. elegans
  • organism-icon Caenorhabditis elegans
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

In C. elegans, ablation of germline stem cells (GSCs) extends lifespan, but also increases fat accumulation and alters lipid metabolism, raising the intriguing question of how these effects might be related. Here we show that a lack of GSCs results in a broad transcriptional reprogramming, in which the conserved detoxification regulator SKN-1/Nrf increases stress resistance, proteasome activity, and longevity. SKN-1 also activates diverse lipid metabolism genes and reduces fat storage, thereby alleviating the increased fat accumulation caused by GSC absence. Surprisingly, SKN-1 is activated by signals from this fat, which appears to derive from unconsumed yolk that was produced for reproduction. We conclude that SKN-1 plays a direct role in maintaining lipid homeostasis, in which it is activated by lipids. This SKN-1 function may explain the importance of mammalian Nrf proteins in fatty liver disease, and suggests that particular endogenous or dietary lipids might promote health through SKN-1/Nrf. Overall design: Samples were prepared from ~5,000 synchronized, L1 arrested day-one adult animals cultured at 25°C. Worms were synchronized by sodium hypochlorite (bleach) treatment, as previously described (Porta-de-la-Riva et al., 2012). Bleach solution (9 mL ddH2O; 1 mL 1 N NaOH; 4 mL Clorox bleach) was freshly prepared before each experiment. Worms were bleached for 5 minutes, washed 5x in M9, and arrested at the L1 stage at 25°C in M9 containing 10 µg/mL cholesterol. Feeding RNAi was started at the L1 stage. This approach only partially reduces skn-1 function, but allows analysis of larger samples than would be feasible with skn-1 mutants, which are sterile (Bowerman et al., 1992). Because these animals were not treated with FUdR, the WT adults contained an intact germline and eggs. As is explained in the Results section, we therefore confined our analysis to genes that were overrepresented in glp-1(ts) animals, which lack eggs and most of the germline, and established a high-confidence cutoff for genes that were upregulated by GSC absence as opposed to simply being expressed specifically in somatic tissues. RNA was extracted using the same protocol for qRT-PCR samples. Purified RNA samples were DNase treated and assigned a RIN quality score using a Bioanalyzer 2100 (Agilent Technologies, Santa Clara, CA). Only matched samples with high RIN scores were sent for sequencing. Single read 50 bp RNA sequencing with poly(A) enrichment was performed at the Dana-Farber Cancer Institute Center for Computational Biology using a HiSeq 2000 (Illumina, San Diego, CA). FASTQ output files were aligned to the WBcel235 (Feb 2014) C. elegans reference genome using STAR (Dobin et al., 2013). These files have been deposited at the Gene Expression Omnibus (GEO) with the accession number GSE63075. Samples averaged 75% mapping of sequence reads to the reference genome. Differential expression analysis was performed using a custom R and Bioconductor RNA-seq pipeline (http://bioinf.wehi.edu.au/RNAseqCaseStudy/) (Gentleman et al., 2004; Anders et al., 2013; R Core Team, 2014). Quantification of mapped reads in the aligned SAM output files was performed using featureCounts, part of the Subread package (Liao et al., 2013, 2014). We filtered out transcripts that didn't have at least one count per million reads in at least two samples. Quantile normalization and estimation of the mean-variance relationship of the log-counts was performed by voom (Law et al., 2014). Linear model fitting, empirical Bayes analysis and differential expression analysis was then conducted using limma (Smyth, 2005). To identify genes that are upregulated in a SKN-1-dependent manner by GSC loss, we sought genes for which glp-1(ts) expression was higher than WT, and for which glp-1(ts);skn-1(-) expression was reduced relative to glp-1(ts). To test for this pattern, if a gene's expression change was higher in the comparison of glp-1(ts) vs. WT and lower in the comparison of glp-1(ts);skn-1(-) vs. glp-1(ts), then we calculated the minimum (in absolute value) of the t-statistics from these two comparisons, and assessed the significance of this statistic by comparing to a null distribution derived by applying this procedure to randomly generated t-statistics. We corrected for multiple testing in this and the differential expression analysis using the false discovery rate (FDR) (Benjamini and Hochberg, 1995). Heatmaps were generated using heatmap.2 in the gplots package (Warnes et al., 2014). Functional annotations and phenotypes were obtained from Wormbase build WS246. SKN-1 transcription factor binding site analysis of hits was conducted with biomaRt, GenomicFeatures, JASPAR, MotifDb, motifStack, MotIV, and Rsamtools (Sandelin et al., 2004; Durinck et al., 2005; Durinck et al., 2009; Lawrence et al., 2013; Ou et al., 2013; Mercier and Gottardo, 2014; Shannon, 2014). JASPAR analysis was performed with the SKN-1 matrix MA0547.1 using 2 kb upstream sequences obtained from Ensembl WBcel235 (Staab et al., 2013). modENCODE SKN-1::GFP ChIP-seq analysis of hits was performed using biomaRt, ChIPpeakAnno, IRanges, and multtest (Durinck et al., 2005; Durinck et al., 2009; Gerstein et al., 2010; Zhu et al., 2010; Niu et al., 2011; Lawrence et al., 2013). SKN-1::GFP ChIP-seq peaks were generated by Michael Snyder's lab. We used the peak data generated from the first 3 larval stages: L1 (modENCODE_2622; GSE25810), L2 (modENCODE_3369), and L3 (modENCODE_3838; GSE48710). Human ortholog matching was performed using Wormbase, Ensembl, and OrthoList (Shaye and Greenwald, 2011). Gene lists were evaluated for functional classification and statistical overrepresentation with Database for Annotation, Visualization and Integrated Discovery (DAVID) version 6.7 (Dennis et al., 2003).

Publication Title

Lipid-mediated regulation of SKN-1/Nrf in response to germ cell absence.

Sample Metadata Fields

Cell line, Subject

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accession-icon GSE148702
The effects of SGLT-2 inhibitors canagliflozin on hepatic transcription
  • organism-icon Mus musculus
  • sample-icon 13 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 2.0 ST Array (mogene20st)

Description

We assessed the change in hepatic transciptional pattern after treatment with SGLT-2 inhibitors canagliflozin in a mice model of diet-induced obesity.

Publication Title

SGLT2 inhibition reprograms systemic metabolism via FGF21-dependent and -independent mechanisms.

Sample Metadata Fields

Sex

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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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