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accession-icon SRP105064
High-resolution gene expression datasets of ontogenetic zones in the root apical meristem
  • organism-icon Arabidopsis thaliana
  • sample-icon 24 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

In plants, apical meristems allow continuous growth along the body axis. Within the root apical meristem (RAM), a group of slowly dividing quiescent center (QC) cells is thought to limit stem cell activity to directly neighboring cells (Cowels, 1956; van den Berg et al., 1997), thus endowing them with unique properties, distinct from displaced daughters. This binary identity of the stem cells stands in apparent contradiction with the more gradual changes in cell division potential (Bennett and Scheres, 2010) and differentiation (Yamaguchi et al., 2008; 2010; Furuta et al, 2014; Geldner, 2013; Masucci et al., 1996; Dolan and Costa, 2001) that occur as cells move further away from the QC. To address this paradox and to infer molecular organization of the root meristem, we used a whole-genome approach to determine dominant transcriptional patterns along root ontogeny zones. We found that the prevalent patterns are expressed in two opposing gradients. One is characterized by genes associated with development, the other enriched in differentiation genes. We confirmed these transcript gradients, and demonstrate that these translate to gradients in protein accumulation and gradual changes in cellular properties. We also show that gradients are genetically controlled through multiple pathways. Based on these findings, we propose that cells in the Arabidopsis root meristem gradually transition from 'stemness' towards differentiation. Overall design: This study contains high-resolution datasets from cell populations from the enitre root meristem and xylem-specific cell populations. Using fluorescence activated cell sorting, three cell populations were isolated based on their GFP expression intensity. Two-Three replicates were used per sample

Publication Title

Framework for gradual progression of cell ontogeny in the <i>Arabidopsis</i> root meristem.

Sample Metadata Fields

Specimen part, Cell line, Subject

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accession-icon GSE89101
Nuclear and cellular expression data from the whole 16-cell stage Arabidopsis thaliana embryo and a cell type-specific expression atlas of the early Arabidopsis embryo
  • organism-icon Arabidopsis thaliana
  • sample-icon 44 Downloadable Samples
  • Technology Badge Icon Arabidopsis Gene 1.1 ST Array (aragene11st)

Description

SuperSeries contain expression data from the nuclei of cell types involved in patterning events, with focus on root apical stem cell formation, at 16-cell stage, early globular stage and late globular stage in the early Arabidopsis embryo (atlas). Expression data comparing nuclear and cellular RNA isolated from whole 16-cell stage Arabidopsis embryos is also included.

Publication Title

Transcriptome dynamics revealed by a gene expression atlas of the early Arabidopsis embryo.

Sample Metadata Fields

Specimen part

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accession-icon GSE89100
Cell type-specific expression atlas of the early Arabidopsis thaliana embryo
  • organism-icon Arabidopsis thaliana
  • sample-icon 38 Downloadable Samples
  • Technology Badge Icon Arabidopsis Gene 1.1 ST Array (aragene11st)

Description

The establishement of the first plant tissues occurs during embryo development. Indeed, cell types that will form the Arabidopsis root stem cell niche are first specified during 16-cell (16C), early globular (EG) and late globular (LG) stage of embryonic development. While some regulatory factors are known, we do not yet understand the genetic networks underlying the specification of these cell types. One main reason for this is the difficulties in adapting genome-wide approaches to the cellular level. Here, we have adapted such an approach (INTACT) to generate microarray-based cell type-specific transcriptomic profiles at 16C to LG stage for use in determining the role of the transcriptome in cell specification and differentiation during root stem cell niche formation.

Publication Title

Transcriptome dynamics revealed by a gene expression atlas of the early Arabidopsis embryo.

Sample Metadata Fields

Specimen part

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accession-icon GSE64472
Identification of HGF/c-MET as a biomarker of resistance to Vascular Endothelial Growth Factor Receptor (VEGFR) inhibitors
  • organism-icon Mus musculus, Homo sapiens
  • sample-icon 22 Downloadable Samples
  • Technology Badge IconIllumina HumanWG-6 v3.0 expression beadchip

Description

Therapeutic resistance to VEGFR signaling inhibitors is a major obstacle in the treatment of non-small cell lung cancer (NSCLC). We investigated the contribution of stromal and tumor cells to resistance of NSCLC to VEGFR tyrosine kinase inhibitors (TKIs).

Publication Title

The HGF/c-MET Pathway Is a Driver and Biomarker of VEGFR-inhibitor Resistance and Vascular Remodeling in Non-Small Cell Lung Cancer.

Sample Metadata Fields

Specimen part

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accession-icon GSE97969
Identification of mRNAs modulated by the HOXB7-MEK signaling cascade
  • organism-icon Homo sapiens
  • sample-icon 2 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 2.0 ST Array (hugene20st)

Description

Transcripts upregulated or downregulated by HOXB7-MEK signaling were identified for use on the microarray using the Affymetrix GeneChip WT PLUS Reagent Kit in comparison with HOXB7-knockdown S2-013 cells that were transfected with rescue-HOXB7 plasmid and treated with MEK inhibitor, and HOXB7-knockdown S2-013 cells that were transfected with rescue-HOXB7 plasmid but not treated with MEK inhibitor.

Publication Title

The transcription factor HOXB7 regulates ERK kinase activity and thereby stimulates the motility and invasiveness of pancreatic cancer cells.

Sample Metadata Fields

Specimen part

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accession-icon GSE60542
Revisiting the transcriptional analysis of primary tumors and associated nodal metastases with enhanced biological and statistical controls: application to thyroid cancer
  • organism-icon Homo sapiens
  • sample-icon 88 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The biology underlying nodal metastasis is poorly understood. Transcriptome profiling has helped to characterize both primary tumors seeding nodal metastasis and the metastasis themselves. The interpretation of these data, however, is not without ambiguities. Here we profiled the transcriptomes of 17 papillary thyroid cancer (PTC) nodal metastases, associated primary tumors and primary tumors from N0 patients. We also included patient-matched normal thyroid and lymph node samples as controls to address some limits of previous studies. We found that the transcriptomes of patient-matched primary tumors and metastases were more similar than of unrelated metastases/primary pairs, a result also reported in other organ systems, and that part of this similarity reflected patient background. We found that the comparison of patient-matched primary tumors and metastases was heavily confounded by the presence of lymphoid tissues in the metastasis samples. An original data adjustment procedure was developed to circumvent this problem. It revealed a differential expression of stroma-related gene expression signatures also regulated in other organ systems. The comparison of N0 vs. N+ primary tumors uncovered a signal irreproducible across independent PTC datasets. This signal was also detectable when comparing the normal thyroid tissues adjacent to N0 and N+ tumors, suggesting a cohort specific bias also likely to be present in previous studies with similar statistical power. Classification of N0 vs. N+ yielded an accuracy of 63%, but additional statistical controls not presented in previous studies, revealed that this is likely to occur by chance alone. To address this issue, we used large datasets from The Cancer Genome Atlas and showed that N0 vs. N+ classification rates could not be reached randomly for most cancers. Yet, it was significant, but of limited accuracy (<70%) for thyroid, breast and head and neck cancers.

Publication Title

Revisiting the transcriptional analysis of primary tumours and associated nodal metastases with enhanced biological and statistical controls: application to thyroid cancer.

Sample Metadata Fields

Sex

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accession-icon GSE80026
Comparison between WT and apl in a novel in vitro tissue culture system, VISUAL
  • organism-icon Arabidopsis thaliana
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Arabidopsis Gene 1.0 ST Array (aragene10st)

Description

We established a novel in vitro tissue culture system (named VISUAL), in which xylem and phloem differentiation can be induced with Arabidopsis thaliana cotyledons

Publication Title

Vascular Cell Induction Culture System Using Arabidopsis Leaves (VISUAL) Reveals the Sequential Differentiation of Sieve Element-Like Cells.

Sample Metadata Fields

Age, Specimen part, Time

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accession-icon GSE80027
Cell-sorting analysis with SEOR1pro::SEOR1-YFP in a novel in vitro tissue culture system, VISUAL
  • organism-icon Arabidopsis thaliana
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Arabidopsis Gene 1.0 ST Array (aragene10st)

Description

We established a novel in vitro tissue culture system (named VISUAL), in which xylem and phloem differentiation can be induced with Arabidopsis thaliana cotyledons

Publication Title

Vascular Cell Induction Culture System Using Arabidopsis Leaves (VISUAL) Reveals the Sequential Differentiation of Sieve Element-Like Cells.

Sample Metadata Fields

Specimen part, Time

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accession-icon SRP131516
RNA Sequencing analysis of different genetically characterized lung cancer cell lines
  • organism-icon Homo sapiens
  • sample-icon 36 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

We performed RNA sequencing to assess changes in gene expression in lung cancer cell lines with MET genetic alterations with or without co-occurrence of JAK2 inactivating mutations. Different treatments have been administrated to activate or inhibit selected pathways in order to define MET signature and IFNg (or JAK/STAT) signature. Overall design: Differential expression analysis of RNA sequencing of 4 different lung cancer cell lines with MET genetic alterations treated with different treatements to activate or inhibit selected pathways

Publication Title

<i>MET</i>-Oncogenic and <i>JAK2</i>-Inactivating Alterations Are Independent Factors That Affect Regulation of PD-L1 Expression in Lung Cancer.

Sample Metadata Fields

Disease, Disease stage, Cell line, Treatment, Subject

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accession-icon GSE18052
Analysis of gene expression levels in BBF2H7-/- chondrocytes
  • organism-icon Mus musculus
  • sample-icon 2 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

BBF2H7 (BBF2 human homolog on chromosome 7), an ER-resident basic leucine zipper transcription factor, is activated in response to ER stress and abundantly expresses in chondrocytes. While BBF2H7 is widely expressed in many tissues and organs, the most intense signals were detected in the proliferating zone of the cartilage. We compared gene expressions in primary cultured chondrocytes prepared from rib cartilage between WT and BBF2H7-/- mice at E18.5. Primary cultured chondrocytes were prepared from E18.5 rib cartilage of WT and BBF2H7-/- mice. Chondrocytes were isolated using 0.2% collagenase D (Roche) after adherent connective tissue was removed by 0.2% trypsin (Sigma) and collagenase pretreatment. Isolated chondrocytes were maintained in -MEM (Gibco) supplemented with 10% FCS and 50 g/mL ascorbic acid. Adenovirus vectors expressing the mouse p60 BBF2H7 (1-377 aa, BBF-N) were constructed with the AdenoX Expression system (Clontech), according to the manufacturers protocol. The cells were infected with adenoviruses 30 h before analysis.

Publication Title

Regulation of endoplasmic reticulum stress response by a BBF2H7-mediated Sec23a pathway is essential for chondrogenesis.

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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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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