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accession-icon SRP104995
Transcriptome profiling of Peyer's patch naive and germinal center B cells
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Germinal center (CD19+Fas+GL7+) and naive (CD19+Fas-GL7-) B cells were sorted from Peyer''s patches of littermate 12 weeks old WT C57BL/6 mice. Three biological replicates were analyzed, each composed of a pool of 5 female mice. RNA was purified from pellets of 2-2.5x10^4 cells and sequencing libraries were prepared from 100ng of total RNA per replicate. Overall design: Transcriptional profiling of germinal center and naive B cells from Peyer's patches of WT mice.

Publication Title

A broad atlas of somatic hypermutation allows prediction of activation-induced deaminase targets.

Sample Metadata Fields

Sex, Age, Specimen part, Cell line, Subject

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accession-icon SRP150708
Functional interplay between c-Myc and Max in B lymphocyte differentiation
  • organism-icon Mus musculus
  • sample-icon 8 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

The Myc proteins (N-, L- and c-Myc) are transcription factors involved in many biological functions such as regulation of cell proliferation, differentiation, metabolism and apoptosis. A large number of human cancers show enhanced expression of myc family proto-oncogenes as one of their hallmarks. These proteins contain a basic region/helix-loop-helix/leucine zipper (bHLHZip) domain that mediates DNA binding and heterodimerization with its partner Max (Myc/Max heterodimer). Among Myc proteins, c-Myc is the most widely expressed and relevant in primary B lymphocytes. Some reports have implied that c-Myc can perform some functions without Max in different cell contexts. However, the functional interplay in vivo between c-Myc and Max during B lymphocyte differentiation is not well-known. Here we show that c-Myc requires Max. However, key biological processes such as cell differentiation and DNA replication can initially progress without c-Myc/Max heterodimer in primary B lymphocytes. We found that B lymphocytes lacking Myc, Max or both showed upregulation of signalling pathways associated with the B cell receptor. Our data suggest that c-Myc/Max heterodimers are not essential for the initiation of certain biological processes in B lymphocytes. Rather, c-Myc/Max are necessary for fine-tuning the initial response in these cells after activation. Overall design: B cell mRNA profiles of 8-week old control (HET) Myc deficient (MycKO), Max deficient (MaxKO) and double deficient (DKO) mice were generated by deep sequencing, in duplicate, using a HiSeq2500 (Illumina.

Publication Title

Functional interplay between c-Myc and Max in B lymphocyte differentiation.

Sample Metadata Fields

Age, Specimen part, Subject

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accession-icon GSE14739
Impact of breed and sex on porcine endocrine transcriptome: A Bayesian biometrical analysis
  • organism-icon Sus scrofa
  • sample-icon 80 Downloadable Samples
  • Technology Badge Icon Affymetrix Porcine Genome Array (porcine)

Description

Background: Transcriptome variability is due to genetic and environmental causes, much like any other complex phenotype. Ascertaining the transcriptome differences between individuals is an important step to understand how selection and genetic drift may affect gene expression. To that end, extant divergent livestock breeds offer an ideal genetic material.

Publication Title

Impact of breed and sex on porcine endocrine transcriptome: a bayesian biometrical analysis.

Sample Metadata Fields

Sex, Specimen part

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accession-icon GSE74491
The response of Pseudomonas aeruginosa strains PAO1 and FRD1 to 10 mM calcium under planktonic and biofilm conditions
  • organism-icon Pseudomonas aeruginosa
  • sample-icon 3 Downloadable Samples
  • Technology Badge Icon Affymetrix Pseudomonas aeruginosa Array (paeg1a)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

The Pseudomonas aeruginosa PAO1 Two-Component Regulator CarSR Regulates Calcium Homeostasis and Calcium-Induced Virulence Factor Production through Its Regulatory Targets CarO and CarP.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE74444
Response of Pseudomonas aeruginosa strain PAO1 to 10 mM added calcium in planktonic culture
  • organism-icon Pseudomonas aeruginosa
  • sample-icon 3 Downloadable Samples
  • Technology Badge Icon Affymetrix Pseudomonas aeruginosa Array (paeg1a)

Description

PAO1 was cultured planktonically to stationary phase with 10 mM calcium and no added calcium. The transcriptional response to calcium addition was determined.

Publication Title

The Pseudomonas aeruginosa PAO1 Two-Component Regulator CarSR Regulates Calcium Homeostasis and Calcium-Induced Virulence Factor Production through Its Regulatory Targets CarO and CarP.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE89793
Loss of the Inhibitory Immune Checkpoint CD85j/LILRB1 on Malignant Plasma Cells Contributes to Immune Escape in Multiple Myeloma
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U219 Array (hgu219)

Description

Mechanisms of immune regulation may control proliferation of aberrant plasma cells (PCs) in patients with the asymptomatic monoclonal gammopathy of undetermined significance (MGUS) preventing progression to active multiple myeloma (MM). We investigated the role of CD85j (LILRB1), an inhibitory immune checkpoint for B cell function, in MM pathogenesis.

Publication Title

Loss of the Immune Checkpoint CD85j/LILRB1 on Malignant Plasma Cells Contributes to Immune Escape in Multiple Myeloma.

Sample Metadata Fields

Specimen part, Cell line

View Samples
accession-icon GSE10898
Transcriptome architecture across tissues in the pig
  • organism-icon Sus scrofa
  • sample-icon 63 Downloadable Samples
  • Technology Badge Icon Affymetrix Porcine Genome Array (porcine)

Description

Artificial selection has resulted in animal breeds with extreme phenotypes. As an organism is made up of many different tissues and organs, each with its own genetic programme, it is pertinent to ask what are the relative contributions of breed or sex when assessed across tissues.

Publication Title

Transcriptome architecture across tissues in the pig.

Sample Metadata Fields

Age

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accession-icon GSE48790
Expression data from GTF2i mutated ES cells
  • organism-icon Mus musculus
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Data present the expression analysis of different mouse ES cell line with altered expression of GTF2I.

Publication Title

TFII-I regulates target genes in the PI-3K and TGF-β signaling pathways through a novel DNA binding motif.

Sample Metadata Fields

Specimen part

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accession-icon GSE40439
Gene expression analysis of Ncor1 muscle-specific knockout and PGC-1alpha muscle-specific transgenic skeletal muscle
  • organism-icon Mus musculus
  • sample-icon 20 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

In the present study we have studied the mechanistic and functional aspects of NCoR1 function in mouse skeletal muscle. NCoR1 muscle-specific knockout mice exhibited an increased oxidative metabolism. Global gene expression analysis revealed a high overlap between the effects of NCoR1 deletion and peroxisome proliferator-activated receptor (PPAR) gamma coactivator 1alpha (PGC-1alpha) overexpression on oxidative metabolism in skeletal muscle. The repressive effect of NCoR1 on oxidative phosphorylation gene expression specifically antagonizes PGC-1alpha-mediated coactivation of ERRalpha. We therefore delineated the molecular mechanism by which a transcriptional network controlled by corepressor and coactivator proteins determines the metabolic properties of skeletal muscle, thus representing a potential therapeutic target for metabolic diseases.

Publication Title

The corepressor NCoR1 antagonizes PGC-1α and estrogen-related receptor α in the regulation of skeletal muscle function and oxidative metabolism.

Sample Metadata Fields

Sex, Disease

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accession-icon GSE38588
Liver transcriptome profile in pigs with extreme phenotypes of intramuscular fatty acid composition
  • organism-icon Sus scrofa
  • sample-icon 10 Downloadable Samples
  • Technology Badge Icon Affymetrix Porcine Genome Array (porcine)

Description

The liver transcriptomes of two female groups (High and Low) with phenotypically extreme intramuscular fatty acid composition were sequenced using RNA-Seq [accn: SRA053452, subid: 86092, Bioproject: PRJNA168072]. A total of 146 and 180 unannotated protein-coding genes were identified in intergenic regions for the L and H groups, respectively. In addition, a range of 5.8 to 7.3% of repetitive elements was found, with SINEs being the most abundant elements. The expression in liver of 186 (L) and 270 (H) lncRNAs was also detected. The higher reproducibility of the RNA-Seq data was validated by RT-qPCR and porcine expression microarrays, therefore showing a strong correlation between RT-qPCR and RNA-Seq data (ranking from 0.79 to 0.96), as well as between microarrays and RNA-Seq (r=0.72). A differential expression analysis between H and L animals identified 55 genes differentially-expressed between groups. Pathways analysis revealed that these genes belong to biological functions, canonical pathways and three gene networks related to lipid and fatty acid metabolism. In concordance with the phenotypic classification, the pathways analysis inferred that linolenic and arachidonic acids metabolism was altered between extreme individuals. In addition, a connection was observed among the top three networks, hence suggesting that these genes are interconnected and play an important role in lipid and fatty acid metabolism.

Publication Title

Liver transcriptome profile in pigs with extreme phenotypes of intramuscular fatty acid composition.

Sample Metadata Fields

Sex, Specimen part

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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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