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accession-icon GSE23129
The effects of bud removal on soybean leaf gene expression.
  • organism-icon Glycine max
  • sample-icon 22 Downloadable Samples
  • Technology Badge Icon Affymetrix Soybean Genome Array (soybean)

Description

The paraveinal mesophyll (PVM) of soybean leaves is a layer of laterally expanded cells sandwiched between the palisade and spongy mesophyll chlorenchyma. The vacuoles of PVM cells contain an abundance of a putative vegetative storage protein, VSP (, ). VSP is is constitutively produced, but is up-regulated during sink limitation experiments involving flower, fruit, or vegetative bud removal. Soybean vegetative lipoxygenases (Vlx), consisting of 5 isozymes (Vlx, A-D), have been identified as potential storage proteins because they accumulate to high levels with experimental sink limitation and have been co-localized with VSP to the vacuoles of PVM cells. We re-investigated the sub-cellular locations of these enzymes with TEM immuno-cytochemistry. We employed laser micro-dissection to compared RNA expression of PVM cells with mesophyll chlorenchyma cells, and we performed a micro-array analysis of soybean leaf samples representing a time-course, sink-limitation, experiment. We found that none of the Vlx isozymes co-localize with putative storage proteins in PVM vacuoles, and that our sink limitation experiment (typical of those used in the past) induced a strong up-regulation of stress response genes, simultaneous with the up-regulation of the Vlx isozymes. Our findings do not support a storage function for soybean Vlx.

Publication Title

Experimental sink removal induces stress responses, including shifts in amino acid and phenylpropanoid metabolism, in soybean leaves.

Sample Metadata Fields

Specimen part, Disease

View Samples
accession-icon GSE23128
Comparison of RNA expression in paravienal mesophyll (PVM) and palisade parenchyma (PP) cells.
  • organism-icon Glycine max
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Soybean Genome Array (soybean)

Description

The paraveinal mesophyll (PVM) of soybean leaves is a layer of laterally expanded cells sandwiched between the palisade and spongy mesophyll chlorenchyma. The vacuoles of PVM cells contain an abundance of a putative vegetative storage protein, VSP (, ). VSP is is constitutively produced, but is up-regulated during sink limitation experiments involving flower, fruit, or vegetative bud removal. Soybean vegetative lipoxygenases (Vlx), consisting of 5 isozymes (Vlx, A-D), have been identified as potential storage proteins because they accumulate to high levels with experimental sink limitation and have been co-localized with VSP to the vacuoles of PVM cells. We re-investigated the sub-cellular locations of these enzymes with TEM immuno-cytochemistry. We employed laser micro-dissection to compared RNA expression of PVM cells with mesophyll chlorenchyma cells; and we performed a micro-array analysis of soybean leaf samples representing a time-course, sink-limitation, experiment. We found that none of the Vlx isozymes co-localize with putative storage proteins in PVM vacuoles, and that our sink limitation experiment (typical of those used in the past) induced a strong up-regulation of stress response genes, simultaneous with the up-regulation of the Vlx isozymes. Our findings do not support a storage function for soybean Vlx.

Publication Title

Experimental sink removal induces stress responses, including shifts in amino acid and phenylpropanoid metabolism, in soybean leaves.

Sample Metadata Fields

Specimen part

View Samples
accession-icon SRP059850
Using single-cell RNA-Seq for unbiased analysis of developmental hierarchies (single cell RNA Seq of GMP)
  • organism-icon Mus musculus
  • sample-icon 123 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2500

Description

Single cell RNA seq and bioinformatic analysis is used to characterize myeloid differentiation to uncover novel transcriptional networks and key drivers of hematoipoietic development Overall design: Single cell RNA seq of different hematopoietic populations integrated with Chip seq involving multiple markers

Publication Title

Single-cell analysis of mixed-lineage states leading to a binary cell fate choice.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon SRP059903
Using single-cell RNA-Seq for unbiased analysis of developmental hierarchies (single cell RNA Seq from CMP)
  • organism-icon Mus musculus
  • sample-icon 85 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2500

Description

Single cell RNA seq and bioinformatic analysis is used to characterize myeloid differentiation to uncover novel transcriptional networks and key drivers of hematoipoietic development Overall design: Single cell RNA seq of different hematopoietic populations integrated with Chip seq involving multiple markers

Publication Title

Single-cell analysis of mixed-lineage states leading to a binary cell fate choice.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon SRP059844
Using single-cell RNA-Seq for unbiased analysis of developmental hierarchies (single cell RNA Seq of bone marrow lineage-negative Sca1+ CD117+ cells)
  • organism-icon Mus musculus
  • sample-icon 88 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Single cell RNA seq and bioinformatic analysis is used to characterize myeloid differentiation to uncover novel transcriptional networks and key drivers of hematoipoietic development Overall design: Single cell RNA seq of different hematopoietic populations integrated with Chip seq involving multiple markers

Publication Title

Single-cell analysis of mixed-lineage states leading to a binary cell fate choice.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon SRP059848
Using single-cell RNA-Seq for unbiased analysis of developmental hierarchies (single cell RNA Seq of Gfi1-/- GMP)
  • organism-icon Mus musculus
  • sample-icon 71 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2500

Description

Single cell RNA seq and bioinformatic analysis is used to characterize myeloid differentiation to uncover novel transcriptional networks and key drivers of hematoipoietic development Overall design: Single cell RNA seq of different hematopoietic populations integrated with Chip seq involving multiple markers

Publication Title

Single-cell analysis of mixed-lineage states leading to a binary cell fate choice.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon SRP059873
Using single-cell RNA-Seq for unbiased analysis of developmental hierarchies (single cell RNA Seq of Irf8 KO GMP)
  • organism-icon Mus musculus
  • sample-icon 63 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Single cell RNA seq and bioinformatic analysis is used to characterize myeloid differentiation to uncover novel transcriptional networks and key drivers of hematoipoietic development Overall design: Single cell RNA seq of different hematopoietic populations integrated with Chip seq involving multiple markers

Publication Title

Single-cell analysis of mixed-lineage states leading to a binary cell fate choice.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon SRP071150
Using single-cell RNA-Seq for unbiased analysis of developmental hierarchies (single cell RNA Seq of Gfi1-/- Irf8-/- GMP)
  • organism-icon Mus musculus
  • sample-icon 47 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Single cell RNA seq and bioinformatic analysis is used to characterize myeloid differentiation to uncover novel transcriptional networks and key drivers of hematoipoietic development Overall design: Single cell RNA seq of different hematopoietic populations integrated with Chip seq involving multiple markers

Publication Title

Single-cell analysis of mixed-lineage states leading to a binary cell fate choice.

Sample Metadata Fields

Specimen part, Cell line, Subject

View Samples
accession-icon GSE41993
Expression data from the reproductive tracts of WT, Hoxa9,10,11, and Hoxd9,10,11 mutant mice
  • organism-icon Mus musculus
  • sample-icon 42 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

Hox genes are key regulators of development. In mammals, the study of these genes is greatly confounded by their large number, overlapping functions, and their interspersed shared enhancers. In this report, we describe a novel recombineering strategy that was used to introduce simultaneous frameshift mutations into the flanking Hoxa9, Hoxa10, and Hoxa11 genes, as well as their paralogs on the HoxD cluster. The resulting mutant mice displayed dramatic homeotic transformations of the reproductive tracts, with uterus anteriorized towards oviduct and the vas deferens anteriorized towards epididymis. The Hoxa9,10,11 mutant mice provided a sensitized genetic background that allowed the discovery of Hoxd9,10,11 reproductive tract patterning function. Both shared and distinct Hox functions were defined. The HoxD genes played a crucial role in the regulation of the uterine immune function. Non-coding nonpolyadenylated RNAs were among the key Hox targets. In addition, we observed a surprising anti-dogmatic posteriorization of the uterine epithelium.

Publication Title

Recombineering-based dissection of flanking and paralogous Hox gene functions in mouse reproductive tracts.

Sample Metadata Fields

Sex, Specimen part

View Samples
accession-icon SRP059847
Using single-cell RNA-Seq for unbiased analysis of developmental hierarchies (single cell RNA Seq of Gfi1-GFP GMP)
  • organism-icon Mus musculus
  • sample-icon 38 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Single cell RNA seq and bioinformatic analysis is used to characterize myeloid differentiation to uncover novel transcriptional networks and key drivers of hematoipoietic development Overall design: Single cell RNA seq of different hematopoietic populations integrated with Chip seq involving multiple markers

Publication Title

Single-cell analysis of mixed-lineage states leading to a binary cell fate choice.

Sample Metadata Fields

No sample metadata fields

View Samples
...

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)

fund-icon Fund the CCDL

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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