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accession-icon GSE28446
Expression data from Arabidopsis mature siliques
  • organism-icon Arabidopsis thaliana
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Arabidopsis ATH1 Genome Array (ath1121501)

Description

Analysis of the transcriptomes of nearly ripe siliques (18-19 DAP) of the rdo2-1, rdo3 and hub1-2 (rdo4) mutants in comparison with wild-type Ler, using Affymetrix GeneChip Arabidopsis ATH1 Genome Array.

Publication Title

Identification of the Arabidopsis REDUCED DORMANCY 2 gene uncovers a role for the polymerase associated factor 1 complex in seed dormancy.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE27669
Expression data from Arabidopsis Col-0 expressing FLAG-SUB1A or FLAG-SUB1C rice ERFs
  • organism-icon Arabidopsis thaliana
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Arabidopsis ATH1 Genome Array (ath1121501)

Description

In rice (Oryza sativa L.), the haplotype at the multigenic SUBMERGENCE 1 (SUB1) locus determines survival of prolonged submergence. SUB1 encodes two or three group VII Ethylene Response Factor (ERF) family transcription factors, SUB1A, SUB1B and SUB1C. A highly submergence-inducible SUB1A allele is present in lines that are submergence tolerant. This gene is the determinant of submergence tolerance. Here, the heterologous ectopic expression of rice SUB1A and SUB1C in Arabidopsis thaliana was employed to assess the transcriptional network mobilized by ectopic expression of SUB1A and SUB1C.

Publication Title

Expression of rice SUB1A and SUB1C transcription factors in Arabidopsis uncovers flowering inhibition as a submergence tolerance mechanism.

Sample Metadata Fields

Specimen part

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accession-icon GSE50786
Comparison of histone deacetylase 9-1 mutant (SALK_001723) dry seed transcriptome with Col wild-type
  • organism-icon Arabidopsis thaliana
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Arabidopsis ATH1 Genome Array (ath1121501)

Description

Analysis of the transcriptome of dry hda9-1 mutant seeds with those of Col wild-type seeds, using Affymetrix GeneChip Arabidopsis ATH1 Genome Array.

Publication Title

HISTONE DEACETYLASE 9 represses seedling traits in Arabidopsis thaliana dry seeds.

Sample Metadata Fields

Specimen part

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accession-icon GSE36151
Identification of a complex genetic network involved in Saccharomyces cerevisiae colony morphology
  • organism-icon Saccharomyces cerevisiae
  • sample-icon 18 Downloadable Samples
  • Technology Badge Icon Affymetrix Yeast Genome 2.0 Array (yeast2)

Description

When grown on solid substrates, different microorganisms often form colonies with very specific morphologies. Whereas the pioneers of microbiology often used colony morphology to discriminate between species and strains, the phenomenon has not received much recent attention. In this study, we use a genome-wide assay in the model yeast Saccharomyces cerevisiae to identify all genes that affect colony morphology. We show that several major signaling cascades, including the MAPK, TORC, SNF1 and RIM101 pathways play a role, indicating that morphological changes are a reaction to changing environments. Other genes that affect colony morphology are involved in protein sorting and epigenetic regulation. Interestingly, the screen reveals only few genes that are likely to play a direct role in establishing colony morphology, one notable exception being FLO11, a gene encoding a cell-surface adhesin that has already been implicated in colony morphology, biofilm formation, and invasive and pseudohyphal growth. Using a series of modified promoters to tune FLO11 expression, we confirm the central role of Flo11 and show that differences in FLO11 expression result in distinct colony morphologies. Together, our results provide a first comprehensive looks at the complex genetic network that underlies the diversity in the morphologies of yeast colonies.

Publication Title

Identification of a complex genetic network underlying Saccharomyces cerevisiae colony morphology.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE26511
Involvement of the TGF- and -catenin pathways in pelvic lymph node metastasis in early stage cervical cancer
  • organism-icon Homo sapiens
  • sample-icon 38 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Purpose: Presence of pelvic lymph node metastases is the main prognostic factor in early stage cervical cancer patients, primarily treated with surgery. Aim of this study was to identify cellular tumor pathways associated with pelvic lymph node metastasis in early stage cervical cancer.

Publication Title

Involvement of the TGF-beta and beta-catenin pathways in pelvic lymph node metastasis in early-stage cervical cancer.

Sample Metadata Fields

Age

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accession-icon GSE102235
Regulation of gene expression by HIF-2alpha in multiple myeloma
  • organism-icon Homo sapiens
  • sample-icon 2 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Proliferation of neoplastic plasma cells within the bone marrow leads to reduced oxygen availability. In response to hypoxia, the transcription factor hypoxia-inducible factor-2alpha (HIF-2) is activated and stabilised. We hypothesise that activation of HIF-2 is a central driver of multiple myeloma disease progression, leading to the induction of transcription of genes associated with angiogenesis, osteoclast activation and cell migration. In this study we assessed the affects of HIF-2 overexpression on gene expression in the human myeloma cell line LP-1.

Publication Title

HIF-2α Promotes Dissemination of Plasma Cells in Multiple Myeloma by Regulating CXCL12/CXCR4 and CCR1.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE118985
The pattern of Mesenchymal stem cell expression is an independent marker of outcome in multiple myeloma
  • organism-icon Homo sapiens
  • sample-icon 750 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Mesenchymal stem cells (MSCs) are an essential component of the bone marrow (BM) microenvironment and have shown to support cancer evolution in multiple myeloma (MM). Despite the increasing evidence that MM MSCs differ from their healthy counterparts, little knowledge exists as to whether MSCs independently influence disease outcome. The aim of the present study was to determine the importance of MSCs in disease progression and outcome in MM.

Publication Title

The Pattern of Mesenchymal Stem Cell Expression Is an Independent Marker of Outcome in Multiple Myeloma.

Sample Metadata Fields

Specimen part, Disease, Subject

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accession-icon GSE5900
Gene Expression of Bone Marrow Plasma Cells from Healthy Donors (N=22), MGUS (N=44), and Smoldering Myeloma (N=12)
  • organism-icon Homo sapiens
  • sample-icon 68 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

This series represents bone marrow aspirates from smoldering multiple myeloma patients

Publication Title

Gene-expression signature of benign monoclonal gammopathy evident in multiple myeloma is linked to good prognosis.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP066152
Transcriptome-wide regulation of pre-mRNA splicing and expression by the RNA-binding protein Quaking during monocyte to macrophage differentiation [RNA-Seq]
  • organism-icon Homo sapiens
  • sample-icon 4 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2000

Description

Expression levels of the RNA-binding protein Quaking (QKI) are low in monocytes of early, human atherosclerotic lesions, but abundant in macrophages of advanced plaques. Specific depletion of QKI protein impaired monocyte adhesion, migration, differentiation into macrophages, and foam cell formation in vitro and in vivo. RNA-seq and microarray analysis of human monocyte and macrophage transcriptomes, including those of a unique QKI haploinsufficient patient, revealed striking changes in QKI-dependent mRNA levels and splicing of RNA transcripts. Overall design: RNA-seq analysis of primary monocytes and macrophages from a QKI haploinsufficient patient and their (control) sibling.

Publication Title

Quaking promotes monocyte differentiation into pro-atherogenic macrophages by controlling pre-mRNA splicing and gene expression.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE57695
Osteoclasts Control Re-activation of Dormant Myeloma Cells by Remodeling the Endosteal Niche
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 2.0 ST Array (mogene20st)

Description

Multiple myeloma is largely incurable, despite development of therapies that target myeloma cell-intrinsic pathways. Disease relapse is thought to originate from dormant myeloma cells, localized in specialized niches, which resist therapy and re-populate the tumor. However, little is known about the niche, and how it exerts cell-extrinsic control over myeloma cell dormancy and re-activation. In this study we track individual myeloma cells by intravital imaging as they colonize the endosteal niche, enter a dormant state and subsequently become activated to form colonies. We demonstrate that dormancy is a reversible state which is switched on by engagement with bone lining cells or osteoblasts, and switched off by osteoclasts remodeling the endosteal niche. Dormant myeloma cells are resistant to chemotherapy targeting dividing cells. The demonstration that the endosteal niche is pivotal in controlling myeloma cell dormancy highlights the potential for targeting cell-extrinsic mechanisms to overcome cell-intrinsic drug resistance and prevent disease relapse.

Publication Title

Osteoclasts control reactivation of dormant myeloma cells by remodelling the endosteal niche.

Sample Metadata Fields

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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Developed by the Childhood Cancer Data Lab

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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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