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accession-icon SRP111925
Gene expression profile during wound-induced callus formation in Arabidopsis thaliana
  • organism-icon Arabidopsis thaliana
  • sample-icon 17 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Wounding is a primary trigger of organ regeneration but how wound stress reactivates cell proliferation and promotes cellular reprogramming remains elusive. In this study we combined the transcriptome analysis with quantitative hormonal analysis to investigate how wounding induces callus formation in Arabidopsis thaliana. Our time-course RNA-seq analysis revealed that wounding induces dynamic transcriptional changes that can be categorized into five clusters with distinct temporal patterns. Gene ontology analyses uncovered that wounding modifies the expression of hormone biosynthesis and response genes, and quantitative analysis of endogenous plant hormones revealed accumulation of cytokinin prior to callus formation. Mutants defective in cytokinin synthesis and signalling display reduced efficiency in callus formation, indicating that de novo synthesis of cytokinin has major contribution in wound-induced callus formation. We further demonstrate that type-A ARABIDOPSIS RESPONSE REGULATOR (ARR)-mediated cytokinin signalling regulates the expression of CYCLIN D3;1 (CYCD3;1) and mutations in CYCD3;1 and its homologs CYCD3;2-3 cause defects in callus formation. Our transcriptome data, in addition, showed that wounding activates multiple developmental regulators, and we found novel roles of ETHYLENE RESPONSE FACTOR 115 (ERF115) and PLETHORA3 (PLT3), PLT5, PLT7 in wound-induced callus formation. Together, this study provides novel mechanistic insights into how wounding reactivates cell proliferation during callus formation. Overall design: Examination of transcriptome at 0, 1, 3, 6, 12,24 h after wounding.

Publication Title

Wounding Triggers Callus Formation via Dynamic Hormonal and Transcriptional Changes.

Sample Metadata Fields

Specimen part, Subject, Time

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accession-icon GSE21858
Patterns of gene expression and evolution in the human developing cerebral cortex
  • organism-icon Homo sapiens
  • sample-icon 7 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The cerebral cortex underwent a rapid expansion and complexification during recent primate evolution, but the underlying developmental mechanisms remain essentially unknown.

Publication Title

Genes expressed in specific areas of the human fetal cerebral cortex display distinct patterns of evolution.

Sample Metadata Fields

Age, Specimen part

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accession-icon GSE41257
Transcriptional changes in intraepithelial CD4 lymphocytes
  • organism-icon Mus musculus
  • sample-icon 2 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

We investigated transcriptional changes in CD4CD8aa and CD4 intraepthelial lymphocytes.

Publication Title

Transcriptional reprogramming of mature CD4⁺ helper T cells generates distinct MHC class II-restricted cytotoxic T lymphocytes.

Sample Metadata Fields

Specimen part

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accession-icon GSE28582
Gene Copy Number Aberrations are Associated with Survival in Histological Subgroups of Non-Small Cell Lung Cancer
  • organism-icon Homo sapiens
  • sample-icon 100 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Gene copy number aberrations are associated with survival in histologic subgroups of non-small cell lung cancer.

Sample Metadata Fields

Specimen part

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accession-icon GSE28571
Gene Copy Number Aberrations are Associated with Survival in Histological Subgroups of Non-Small Cell Lung Cancer (expression data)
  • organism-icon Homo sapiens
  • sample-icon 100 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Hypothesis: Non-small cell lung cancer (NSCLC) is characterized by a multitude of genetic aberrations with unknown clinical impact. In this study, we aimed to identify gene copy number changes that correlate with clinical outcome in NSCLC. To maximize the chance to identify clinically relevant events, we applied a strategy involving two prognostically extreme patient groups.

Publication Title

Gene copy number aberrations are associated with survival in histologic subgroups of non-small cell lung cancer.

Sample Metadata Fields

Specimen part

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accession-icon GSE33363
CD99 is a novel prognostic stromal marker in non-small cell lung cancer
  • organism-icon Homo sapiens
  • sample-icon 10 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The delicate interaction between cancer cells and the surrounding stroma plays an essential role in all stages of tumourigenesis. Despite the significance of this interplay, alterations in protein composition underlying tumour-stroma interactions are largely unknown. The aim of this study was to identify stromal proteins with clinical relevance in non-small cell lung cancer.

Publication Title

CD99 is a novel prognostic stromal marker in non-small cell lung cancer.

Sample Metadata Fields

Specimen part, Subject

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accession-icon GSE22259
BRCA1 depletion effect on HeLa cells
  • organism-icon Homo sapiens
  • sample-icon 5 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Analysis of HeLa cells following depletion of BRCA1 tumor supressor using RNAi against BRCA1. Results provide insight into the molecular mechanisms underlying loss of the BRCA1 function.

Publication Title

BRCA1 represses amphiregulin gene expression.

Sample Metadata Fields

Treatment

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accession-icon SRP026126
The ABRF Next-Generation Sequencing Study (ABRF-NGS): Multi-platform and cross-methodological reproducibility of transcriptome profiling by RNA-seq [Illumina HiSeq 2500]
  • organism-icon Homo sapiens
  • sample-icon 419 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Next-generation sequencing (NGS) technology applications like RNA-sequencing (RNA-seq) have dramatically expanded the potential for novel genomics discoveries, but the proliferation of various platforms and protocols for RNA-seq has created a need for reference data sets to help gauge the performance characteristics of these disparate methods. Here we describe the results of the ABRF-NGS Study on RNA-seq, which leverages replicate experiments across multiple sites using two reference RNA standards tested with four protocols (polyA selected, ribo-depleted, size selected, and degraded RNA), and examined across five NGS platforms (Illumina’s HiSeqs, Life Technologies’ Personal Genome Machine and Proton, Roche 454 GS FLX, and Pacific Biosciences RS). These results show high (R2 >0.9) intra-platform consistency across test sites, high inter-platform concordance (R2 >0.8) for transcriptome profiling, and a large set of novel splice junctions observed across all platforms. Also, we observe that protocols using ribosomal RNA depletion can both salvage degraded RNA samples and also be readily compared to polyA-enriched fractions. These data provide a broad foundation for standardization, evaluation and improvement of RNA-seq methods. Overall design: Two reference RNA standards tested with four protocols (polyA selected, ribo-depleted, size selected, and degraded RNA), and examined across five NGS platforms (Illumina’s HiSeqs, Life Technologies’ Personal Genome Machine and Proton, Roche 454 GS FLX, and Pacific Biosciences RS). Please note that the samples were named following the ABRF-Platform-Site-Sample-Replicate# format. For example, ABRF-454-CNL-A-1 means Sample A was run on 454 platform at Cornell and this is the first replicate, and ABRF-454-CNL-A-2 means the same exact sample was ran with same machine at same location and is 2nd replicate.

Publication Title

RNA-seq of human reference RNA samples using a thermostable group II intron reverse transcriptase.

Sample Metadata Fields

Specimen part, Subject

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accession-icon GSE42220
Gene expression data from differentiated 3T3-L1 preadipocytes treated with Palmitic Acid, Stearic Acid, Palmitoleic Acid, or Oleic Acid
  • organism-icon Mus musculus
  • sample-icon 19 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.1 ST Array (mogene11st)

Description

Saturated fatty acids (SFA) are widely thought to induce inflammation in adipose tissue (AT), while monounsaturated fatty acids (MUFA) are purported to have the opposite effect; however, it is unclear if individual SFA and MUFA behave similarly. Our goal was to examine adipocyte transcriptional networks regulated by individual SFA (palmitic acid, PA; stearic acid, SA) and MUFA (palmitoleic acid, PMA; oleic acid, OA).

Publication Title

Individual saturated and monounsaturated fatty acids trigger distinct transcriptional networks in differentiated 3T3-L1 preadipocytes.

Sample Metadata Fields

Specimen part

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accession-icon GSE74143
Whole blood gene expression from subjects with moderate to severe rheumatoid arthritis
  • organism-icon Homo sapiens
  • sample-icon 376 Downloadable Samples
  • Technology Badge Icon Affymetrix HT HG-U133+ PM Array Plate (hthgu133pluspm)

Description

Whole blood (paxgene) gene expression was measured using Affymetrix microarray from 377 individuals with rheumatoid arthritis.

Publication Title

Integrative genomic deconvolution of rheumatoid arthritis GWAS loci into gene and cell type associations.

Sample Metadata Fields

Sex, Age, Specimen part, Disease

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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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