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accession-icon SRP150775
Self-organization and symmetry breaking in intestinal organoid development [scRNA-Seq]
  • organism-icon Mus musculus
  • sample-icon 2 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Intestinal organoids are complex three-dimensional structures that mimic cell type composition and tissue organization of the intestine by recapitulating the self-organizing capacity of cell populations derived from a single stem cell. Crucial in this process is a first symmetry-breaking event, in which only a fraction of identical cells in a symmetrical cyst differentiate into Paneth cells, which in turn generates the stem cell niche and leads to asymmetric structures such as crypts and villi. We here combine a quantitative single-cell gene expression and imaging approach to characterize the development of intestinal organoids from a single cell. We show that intestinal organoid development follows a regeneration process driven by transient Yap1 activation. Cell-to-cell variability in Yap1, emerging in symmetrical cysts, initiates a Notch/Dll1 lateral inhibition event driving the symmetry-breaking event and the formation of the first Paneth cell. Our findings reveal how single cells exposed to a uniform growth-promoting environment have the intrinsic ability to generate emergent, self-organized behavior resulting in the formation of complex multicellular asymmetric structures. Overall design: Single cell RNA sequencing of single cells isolated from intestinal organoids day3 and intestinal organoids day 5

Publication Title

Self-organization and symmetry breaking in intestinal organoid development.

Sample Metadata Fields

Age, Specimen part, Cell line, Subject

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accession-icon GSE11039
Expression Data from wild type and E2F4 null MEFs
  • organism-icon Mus musculus
  • sample-icon 20 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430A 2.0 Array (mouse430a2)

Description

We have used primary MEFs derived from wild type and E2F4 null mice growing asynchrounously in serum to generate a signature for E2F4 pathway activation. 10 wild type and 10 E2F4 null samples were each assayed using the Affymetrics Mouse Genome 430A 2.0 array.

Publication Title

Patterns of cell signaling pathway activation that characterize mammary development.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE99861
The effect of EDI3 inhibition in MCF7 breast cancer cells
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

EDI3 was shown to be relevant in cell migration, adhesion and spreading. Gene expression analysis was performed to determine the effect of EDI3 silencing in MCF7 cells in order to gain insight into potential underlying mechanisms.

Publication Title

EDI3 links choline metabolism to integrin expression, cell adhesion and spreading.

Sample Metadata Fields

Specimen part, Cell line

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accession-icon GSE29247
Expression data from junctional zone of placenta in Brown Norway and Holtzman-Sprague Dawley rat strains at gestation day 18.5
  • organism-icon Rattus norvegicus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Genome 230 2.0 Array (rat2302)

Description

Placentation differs in the BN rat strain when compared to HSD and DSS rat strains. Intrauterine trophoblast invasion is shallow and the junctional zone is underdeveloped in the BN rat. These structural differences are striking but their quantification is not conducive to high throughput analyses. In the rat, the junctional zone can be readily dissected and is more homogenous than other components of the placentation site. HSD and BN rat gestation day 18.5 junctional zone gene expression profiles were determined using DNA microarray analysis to identity placenta-associate quantitate traits.

Publication Title

Chromosome-substituted rat strains provide insights into the genetics of placentation.

Sample Metadata Fields

Specimen part

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accession-icon GSE7897
Expression data from Mouse Lymphoma
  • organism-icon Mus musculus
  • sample-icon 57 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

We have made use of the E-myc transgenic mouse, a model for the study of B-cell lymphoma development that is initiated through a defined genetic alteration, to explore the contributions of additional somatic alterations that contribute to the heterogeneity of the resulting tumors. As one example of such heterogeneity, we have focused on the observation that lymphomas develop in E-myc mice with a variable time of onset. Twenty-five early-onset, 25 late-onset lymphomas and 10 normal samples were each assayed on an Affymetrix Mouse Genome 430 2.0 array.

Publication Title

Utilization of pathway signatures to reveal distinct types of B lymphoma in the Emicro-myc model and human diffuse large B-cell lymphoma.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE40760
The E-myc Mouse Model Represents Heterogeneity Across Human Aggressive B-cell Lymphomas
  • organism-icon Mus musculus
  • sample-icon 115 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Utilization of the Eμ-Myc mouse to model heterogeneity of therapeutic response.

Sample Metadata Fields

Specimen part

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accession-icon GSE40758
Transgenic E-myc mouse lymphoma expression data for test dataset [Mouse430A_2]
  • organism-icon Mus musculus
  • sample-icon 44 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

We used gene expression data from E-myc mouse lymphomas to test various genomic signatures and select lymphomas for further study

Publication Title

Utilization of the Eμ-Myc mouse to model heterogeneity of therapeutic response.

Sample Metadata Fields

Specimen part

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accession-icon GSE40756
Transgenic E-myc mouse lymphoma expression data for training dataset
  • organism-icon Mus musculus
  • sample-icon 39 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

We used gene expression data from E-myc mouse lymphomas to perform unsupervised analyses that identified two lymphoma subgroups.

Publication Title

Utilization of the Eμ-Myc mouse to model heterogeneity of therapeutic response.

Sample Metadata Fields

Specimen part

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accession-icon GSE40757
Transgenic E-myc mouse lymphoma expression data for test dataset [Mouse430_2]
  • organism-icon Mus musculus
  • sample-icon 32 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

We used gene expression data from E-myc mouse lymphomas to test various genomic signatures and select lymphomas for further study

Publication Title

Utilization of the Eμ-Myc mouse to model heterogeneity of therapeutic response.

Sample Metadata Fields

Specimen part

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accession-icon GSE13314
Gene expression profiling of pulmonary MALT lymphoma
  • organism-icon Homo sapiens
  • sample-icon 33 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Molecular pathways activated in MALT lymphoma are not well defined.

Publication Title

Gene expression profiling of pulmonary mucosa-associated lymphoid tissue lymphoma identifies new biologic insights with potential diagnostic and therapeutic applications.

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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