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accession-icon GSE36643
Ganglioside GD2 identifies Breast Cancer Stem Cells: Targeting GD3 Synthase Inhibits GD2 Expression and Tumor Growth
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

We FACS sorted Ras-transformed human mammary epithelial cells (HMLER cells) into GD2+ and GD2- as well as CD44high/CD24low and CD44low/Cd24highcells and comapred the four different population by array.

Publication Title

Ganglioside GD2 identifies breast cancer stem cells and promotes tumorigenesis.

Sample Metadata Fields

Cell line

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accession-icon SRP091680
Assessing characteristics of RNA amplification methods for single cell RNA sequencing
  • organism-icon Homo sapiens
  • sample-icon 124 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000, Illumina HiSeq 2500

Description

We conducted a large-scale control experiment to assess the transfer function of three scRNA-seq methods and factors modulating the function. Our approach was to dilute bulk total RNA (from a single source) to levels bracketing single-cell levels of total RNA (10 pg and 100 pg) in replicates and amplifying the RNA to levels sufficient for RNA sequencing. Overall design: We performed replicate transcriptome amplifications of Universal Human Reference RNA (UHR) and Human Brain Reference RNA (HBR) that were diluted to single-cell and ten-cell abundances (10 and 100 picograms (pg.) total RNA or ~200,000 and 2 million mRNA molecules, respectively) and were amplified using three single-cell RNA amplification methods. Methods included the antisense RNA IVT protocol (aRNA), a custom C1 SMARTer protocol (SmartSeq Plus) performed on a Fluidigm C1 96-well chip, and a modified NuGen Ovation RNA sequencing protocol (NuGen). Bulk ribo-depleted UHR and HBR RNA were sequenced and served as a reference. The general experimental scheme was consistent for all dilution replicates; however, there were differences across experimental groups in the specifics of experimental protocols, necessitated by particular methodologies. Because of these experimental differences, head-to-head comparison of methods is not appropriate and our goal is to provide quantitative analyses of factors affecting individual methods. Current results should be used in experimental planning, data analysis, and method optimization rather than as a performance test of any particular method. Detailed experimental design: Each collaborating center obtained reference RNA with the same lot number for Universal Human Reference (UHR) RNA (Agilent 740000, Lot 0006141415) and Human Brain Reference (HBR) (Ambion AM6050, Lot-105P055201A) and performed replicate amplification using a single amplification method, detailed below. SmartSeq Plus: Reference RNA was diluted to an intermediate stock solution by serial dilution. A final 1000-fold dilution occurred on the C1 chip, such that individual wells in a given batch contained 9.99 pg. sampled from a common intermediate dilution. ERCC spike-in RNA mix 1 (Ambion 4456740) was also added for a final mass of approximately 7 femtograms (fg.) per sample, a 4,000,000x dilution from stock. Samples for each source RNA were prepared in single batches. After amplification, cDNA from the entire C1 96-well plate was quantified using picogreen. C1 chips with an average yield of less than 3 nanograms were discarded. The top 15 reactor wells by cDNA concentration were selected as representative 10 pg. samples for sequencing library preparation. Another 50 wells were selected by the same criteria. These were pooled in sets of 10, generating 5 100 pg. samples for each HBR and UHR. All samples for a given source were prepared in a single sequencing library preparation batch using Nextera XT C1 protocol. NuGen: HBR samples were prepared in a single batch using amplification protocol 1, generating 4 10 pg. and 4 100 pg. amplified replicates. UHR samples were prepared in two batches, using either amplification protocol 1 or 2, generating 15 10 pg. and 11 100 pg. samples. A single sequencing library preparation was performed for each batch of samples using either Lucigen NxSeq or NuGen Ovation Rapid protocol. aRNA: Amplification was performed as previously described (Morris J, Singh JM, Eberwine JH. Transcriptome analysis of single cells. J. Vis. Exp. [Internet]. 2011; Available from: http://www.jove.com/video/2634/transcriptome-analysis-of-single-cells). HBR samples were prepared in 4 batches from separate dilutions of reference RNA, generating 19 10 pg. and 3 100 pg. amplified replicates. ERCC spike-ins were added to 5 of the 10 pg. replicates before amplification at a dilution of 4,000,000x from stock. UHR samples were diluted and amplified in 2 batches from separate dilutions of reference RNA, generating 12 10 pg. and 7 100 pg. amplified replicates. A single sequencing library preparation was performed using Illumina TruSeq Stranded mRNA protocol modified to begin with amplified aRNA. A small numbers of reads were assigned to ERCC transcripts in replicates from the batch where ERCCs had been added that did not have spike-ins added (average of 0.5% of the number of reads assigned in spiked samples). 18 additional HBR 10 pg. replicates were amplified using aRNA for protocol optimization experiments. These samples were treated separately and were excluded from primary analysis. Bulk UHR and HBR: For each reference RNA, three sequencing libraries were generated from bulk material at the same laboratory as the SmartSeq Plus replicates. Cytoplasmic and mitochondrial ribosomal RNA (rRNA) were depleted using Ribo-Zero Gold as part of Illumina TruSeq Stranded Total RNA protocol. Samples were sequenced on Illumina HiSeq 2000. Because of differences in experimental design, direct comparison across methods of precision and the effect of input RNA abundance is difficult. For example, input RNA amount as a factor have different meanings for the different amplification methods: for SmartSeq Plus, because 100pg samples were constructed by pooling 10 pg. samples after cDNA amplification, any resulting effects involve library construction, while for aRNA and NuGen resulting effects reflect both cDNA amplification steps and library steps.

Publication Title

Assessing characteristics of RNA amplification methods for single cell RNA sequencing.

Sample Metadata Fields

Subject

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accession-icon SRP162873
RNA sequencing in healthy controls, intermittent claudicant, and CLI patient skeletal muscle
  • organism-icon Homo sapiens
  • sample-icon 50 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 4000

Description

Gastrocnemius muscle biopsies were obtained from 15 health older adults without peripheral artery disease (PAD), 20 PAD patients with intermittent claudication, and 16 patients with critical limb ischemia undergoing limb amputation. Gene expression analysis was performed using RNA sequencing analysis. Overall design: Examination of gene expression differences across the clinical spectrum of PAD (healthy vs. claudicant vs. critical limb ischemia)

Publication Title

Extensive skeletal muscle cell mitochondriopathy distinguishes critical limb ischemia patients from claudicants.

Sample Metadata Fields

Specimen part, Disease, Subject

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accession-icon GSE9482
GAL-NMD2
  • organism-icon Saccharomyces cerevisiae
  • sample-icon 40 Downloadable Samples
  • Technology Badge Icon Affymetrix Yeast Genome S98 Array (ygs98)

Description

The goal of this set of experiments was to identify transcripts that are differentially expressed upon reactivation of NMD in an nmd2::HIS3 strain by galactose-induced expression of the NMD2 gene.

Publication Title

Association of yeast Upf1p with direct substrates of the NMD pathway.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE18113
Expression data from Human MicroVascular Endothelial Cells (HMVECS)
  • organism-icon Homo sapiens
  • sample-icon 18 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The activation of endothelium by tumor cells is one of the main steps by tumor metastasis. The role of the blood components (platelets and leukocytes) in this process remain unclear.

Publication Title

Selectin-mediated activation of endothelial cells induces expression of CCL5 and promotes metastasis through recruitment of monocytes.

Sample Metadata Fields

Specimen part

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accession-icon SRP108720
RNA-Seq of polysome profiling fractions and whole cell lysates of UVB-irradiated N-TERT keratinocytes
  • organism-icon Homo sapiens
  • sample-icon 18 Downloadable Samples
  • Technology Badge IconNextSeq 500

Description

In response to UVB irradiation, human keratinocytes transiently block cell cycle progression to allow ample time for DNA repair and cell fate determination. These cellular processes are important for evading the initiation of carcinogenesis in skin. We previously showed that repression of mRNA translation initiation through phosphorylation of eIF2a (eIF2a-P) protects keratinocytes from UVB-induced apoptosis. In this study, we elucidate the mechanism of eIF2a-P cytoprotection in response to UVB. Loss of eIF2a-P induced by UVB diminished G1 arrest, DNA repair rate, and cellular senescence coincident with enhanced cell death in human keratinocytes. Genome-wide translation analyses revealed that the mechanism for these critical changes directed by eIF2a-P involved induced expression of CDKN1A encoding p21 protein. p21 is a major regulator of the cell cycle, and we show that human CDKN1A mRNA splice variant 4 is preferentially translated by eIF2a-P during stress in a mechanism mediated in part by upstream ORFs situated in the 5'-leader of CDKN1A mRNA. We conclude that eIF2a-P is cytoprotective in response to UVB by a mechanism featuring translation of a specific splice variant of CDKN1A that facilitates G1 arrest and subsequent DNA repair. Overall design: Untreated and irradiated N-TERT keratinocytes are split into 3 groups: monosome fraction, polysome fraction, and whole cell lysate. N=3.

Publication Title

Translational control of a human <i>CDKN1A</i> mRNA splice variant regulates the fate of UVB-irradiated human keratinocytes.

Sample Metadata Fields

Specimen part, Cell line, Treatment, Subject

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accession-icon GSE9486
Upf1p-associated transcripts in S. cerevisiae
  • organism-icon Saccharomyces cerevisiae
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Yeast Genome S98 Array (ygs98)

Description

The goal of this experiment was to identify transcripts associated with the S. cerevisiae Upf1 protein.

Publication Title

Association of yeast Upf1p with direct substrates of the NMD pathway.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE68761
Analyzing synergistic and non-synergistic interactions in signalling pathways using Boolean Nested Effect Models
  • organism-icon Homo sapiens
  • sample-icon 74 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Understanding the structure and interplay of cellular signalling pathways is one of the great challenges in molecular biology. Boolean Networks can infer signalling networks from observations of protein activation. In situations where it is difficult to assess protein activation directly, Nested Effect Models are an alternative. They derive the network structure indirectly from downstream effects of pathway perturbations. To date, Nested Effect Models cannot resolve signalling details like the formation of signalling complexes or the activation of proteins by multiple alternative input signals. Here we introduce Boolean Nested Effect Models (B-NEM). B-NEMs combine the use of downstream effects with the higher resolution of signalling pathway structures in Boolean Networks. We show that B-NEMs accurately reconstruct signal flows in simulated data. Using B-NEM we then resolve BCR signalling via PI3K and TAK1 kinases in BL2 lymphoma cell lines.

Publication Title

Analyzing synergistic and non-synergistic interactions in signalling pathways using Boolean Nested Effect Models.

Sample Metadata Fields

Specimen part, Cell line, Treatment

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accession-icon E-MEXP-26
Transcription profiling by array of yeast with deletions in the nonsense-mediated and 5' to 3' mRNA decay pathways
  • organism-icon Saccharomyces cerevisiae
  • sample-icon 26 Downloadable Samples
  • Technology Badge Icon Affymetrix Yeast Genome S98 Array (ygs98)

Description

Genome-wide analysis of mRNAs regulated by the nonsense-mediated and 5' to 3' mRNA Decay Pathways in Yeast

Publication Title

Genome-wide analysis of mRNAs regulated by the nonsense-mediated and 5' to 3' mRNA decay pathways in yeast.

Sample Metadata Fields

Sex

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accession-icon E-MEXP-27
Transcription profiling by array of yeast mutants
  • organism-icon Saccharomyces cerevisiae
  • sample-icon 20 Downloadable Samples
  • Technology Badge Icon Affymetrix Yeast Genome S98 Array (ygs98)

Description

To determine the effects of inactivation of both the nosense-mediated mRNA decay pathway and the general 5' to 3' decay pathway on yeast mRNA decay, we compared the expression profiles of the wild-type, xrn1, xrn1 upf1, xrn1 nmd2, and xrn1 upf3 strains.

Publication Title

Genome-wide analysis of mRNAs regulated by the nonsense-mediated and 5' to 3' mRNA decay pathways in yeast.

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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