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accession-icon GSE12152
Genome scale transcriptome analysis of shoot organogenesis in poplar
  • organism-icon Populus tremula x populus alba
  • sample-icon 10 Downloadable Samples
  • Technology Badge Icon Affymetrix Poplar Genome Array (poplar)

Description

Regeneration of transgenic cells remains a major obstacle to research and commercial deployment of transgenic plants for most species.

Publication Title

Genome scale transcriptome analysis of shoot organogenesis in Populus.

Sample Metadata Fields

Sex

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accession-icon E-MEXP-2506
Transcription profiling by array of rice grown in different light and temperature cycles
  • organism-icon Oryza sativa
  • sample-icon 78 Downloadable Samples
  • Technology Badge Icon Affymetrix Rice Genome Array (rice)

Description

Rice (Oryza sativa, ssp. Japonica, cv. Nipponbare 1) plants were grown in a Conviron PGR 15 growth chamber using precise control of temperature, light, and humidity.<br></br>Diurnal (driven) conditions included 12L:12D light cycles and 31C/20C thermocycles in three different combinations. These were: photocycles (LDHH), 12 hrs. light (L)/12 hrs. dark (D) at a constant temperature (31C; HH); photo/thermocycles (LDHC): 12 hrs. light (L) /12 hrs. dark (D) with a high day temperature (31C) and a low night temperature (20C); and thermocycles (LLHC): continuous light (LL) with 12 hrs. high/12 hrs. low temperature (31C, day; 20C, night). Light intensity and relative humidity were 1000 micromol m-2s-2 and 60%, respectively.<br></br>Three-month-old rice plants were entrained for at least one week under the respective condition prior to initiation of each experiment. Leaves and stems from individual rice plants were collected every four hours for 48 hrs in driven (diurnal) conditions followed by a two day freerun spacer under continuous light/temperature followed by two additional days of sampling under the same continuous free run condition.<br></br>

Publication Title

Global profiling of rice and poplar transcriptomes highlights key conserved circadian-controlled pathways and cis-regulatory modules.

Sample Metadata Fields

Age, Specimen part, Time

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accession-icon E-MTAB-275
Transcription profiling by array of rice Indica 93-11 after growth in different light and temperature conditions
  • organism-icon Oryza sativa
  • sample-icon 37 Downloadable Samples
  • Technology Badge Icon Affymetrix Rice Genome Array (rice)

Description

Rice (Oryza sativa, spp. Indica, cv. 93-11) plants were grown in a Conviron PGR 15 growth chamber using precise control of temperature, light, and humidity.<br></br>Diurnal (driven) conditions included 12L:12D light cycles and 31C/20C thermocycles in three different combinations. These were: photocycles (LDHH), 12 hrs. light (L)/12 hrs. dark (D) at a constant temperature (31C; HH); photo/thermocycles (LDHC): 12 hrs. light (L) /12 hrs. dark (D) with a high day temperature (31C) and a low night temperature (20C); and thermocycles (LLHC): continuous light (LL) with 12 hrs. high/12 hrs. low temperature (31C, day; 20C, night). Light intensity and relative humidity were 1000 micromol m-2s-2 and 60%, respectively.<br></br>Three-month-old rice plants were entrained for at least one week under the respective condition prior to initiation of each experiment. Leaves and stems from individual rice plants were collected every four hours for 48 hrs in driven (diurnal) conditions followed by a two day freerun spacer under continuous light/temperature followed by two additional days of sampling under the same continuous free run condition.

Publication Title

Global profiling of rice and poplar transcriptomes highlights key conserved circadian-controlled pathways and cis-regulatory modules.

Sample Metadata Fields

Age, Specimen part, Time

View Samples
accession-icon GSE8021
Expression data from human donor lung biopsies
  • organism-icon Homo sapiens
  • sample-icon 50 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A 2.0 Array (hgu133a2)

Description

Expression profile of human donor lungs that have developed primary graft dysfunction (PGD) after lung transplantation and those that have not.

Publication Title

Expression profiling of human donor lungs to understand primary graft dysfunction after lung transplantation.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP017407
The Aurora B kinase and the polycomb protein Ring1B combine to regulate active promoters in quiescent lymphocytes [RNA-Seq]
  • organism-icon Mus musculus
  • sample-icon 4 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Expression profiling of resting B cells to classify active and silent genes based on expression levels Overall design: 4 biological replicates of mRNA extracted from freshly purified mouse CD43 negative resting B cells

Publication Title

The aurora B kinase and the polycomb protein ring1B combine to regulate active promoters in quiescent lymphocytes.

Sample Metadata Fields

Specimen part, Cell line, Subject

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accession-icon SRP202046
Single-cell transcriptomics of the embryonic mouse pancreas
  • organism-icon Mus musculus
  • sample-icon 58 Downloadable Samples
  • Technology Badge IconNextSeq 500

Description

Data accompaning to van Gurp et al. Development 2019. single-cell sequencing of the developing mouse pancreas followed by Seurat analysis to discover genes important for alpha and beta cell differentiation. Overall design: Single-cells from mouse embryonic pancreas at E12.5, E13.5, E14.5, E15.5 and E18.5 were isolated and enriched for MIP-GFP and sorted into 384-well plates. Afterwards, SORT-seq was performed and single-cell transcriptomics profiles were obtained.

Publication Title

A transcriptomic roadmap to α- and β-cell differentiation in the embryonic pancreas.

Sample Metadata Fields

Subject

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accession-icon SRP080991
A single-cell transcriptome atlas of the human pancreas [CEL-seq2]
  • organism-icon Homo sapiens
  • sample-icon 32 Downloadable Samples
  • Technology Badge IconNextSeq 500

Description

To understand organ function it is important to have an inventory of the cell types present in the tissue and of the corresponding markers that identify them. This is a particularly challenging task for human tissues like the pancreas, since reliable markers are limited. Transcriptome-wide studies are typically done on pooled islets of Langerhans, which obscures contributions from rare cell types and/or potential subpopulations. To overcome this challenge, we developed an automated single-cell sequencing platform to sequence the transcriptome of thousands of single pancreatic cells from deceased organ donors, allowing in silico purification of all main pancreatic cell types. We identify cell type-specific transcription factors, a subpopulation of REG3A-positive acinar cells, and cell surface markers that allow sorting of live alpha and beta cells with high purity. This resource will be useful for developing a deeper understanding of pancreatic biology and pathophysiology of diabetes mellitus. Overall design: Islets of Langerhans were extracted from human cadaveric pancreata and kept in culture until single-cell dispersion and FACS sorting. Single-cell transcriptomics was performed on live cells from this mixture using an automated version of CEL-seq2 on live, FACS sorted cells. The StemID algorithm was used to identify clusters of cells corresponding to the major pancreatic cell types and to mine for novel cell type-specific genes as well as subpopulations within the known pancreatic cell types.

Publication Title

A Single-Cell Transcriptome Atlas of the Human Pancreas.

Sample Metadata Fields

Specimen part, Subject

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accession-icon SRP148693
Next generation sequencing of distal colon glial cells with DNBS-induced inflammation and neurokinin-2 receptor antagonism utilizing RiboTag mice
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 4000

Description

Purpose:We have the first-reported set of glial-specific transcripts utilizing the Ribotag model. We use this model to explore glial changes in DNBS-induced inflammation and neurokinin-2 receptor (NK2R) antagonism. Methods: Actively translated mRNA profiles of the distal colon myeneteric plexi of Rpl22(+/-)Sox10(+/-) male and female mice 8-10 weeks old were obtained utilizing the HA-tagged ribosomal immunoprecipitation and downstream RNA extraction. Samples meeting RNA quality standards by 18S and 28S rRNA peaks by 2100 Bioanalyzer and RNA 6000 Nano LabChip Kit (Agilent) were deep sequenced with the Illumina HiSeq 4000. Results: We mapped approximately 30-50 millions reads per sample to the mouse genome (v88) and identified approximately 100K ribosome-associated transcripts, with Tuxedo workflow, in distal colon glial cells with DNBS-induced inflammation and NK2R antagonism and their respective controls. Of these transcripts, changes in biological processes associated with inflammation and other important enteric nervous system communications between samples have been identified. Conclusions: Our study demonstrates the first use of the Ribotag model to provide glial cell-specific actively-translated mRNA changes in DNBS-induced inflammation with and without functional NK2R signalling. Overall design: Distal colon glial mRNA samples from Ribotag Rpl22(+/-)Sox10(+/-) mice administered either saline or DNBS and DMSO vehicle or NK2R antagonism.

Publication Title

Communication Between Enteric Neurons, Glia, and Nociceptors Underlies the Effects of Tachykinins on Neuroinflammation.

Sample Metadata Fields

Sex, Specimen part, Cell line, Subject

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accession-icon SRP100157
Coupling shRNA screening with single-cell RNA-Seq identifies mechanisms regulating senescence during reprogramming
  • organism-icon Homo sapiens
  • sample-icon 376 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Ectopic expression of the transcription factors Oct4, Sox2, Klf4 and c-Myc (OSKM) can reprogram somatic cells into induced pluripotent stem cells (iPSCs). These iPSCs are highly similar to embryonic stem cells and can be used for regenerative medicine, drug screening and disease modelling. Despite recent advances, reprogramming is a slow and inefficient process. This suggests that there are several safeguarding mechanisms to counteract cell fate conversion. Cellular senescence is one of these barriers, which is mediated through activation of the tumour suppressors p53/p21CIP1, p15INK4b and p16INK4a. In this study, we have screened for shRNAs blunting reprogramming-induced senescence. We integrated single-cell RNA sequencing (scRNA-Seq) with shRNA screening to investigate the mechanism of action of the identified candidates. Overall design: 376 samples: 280 IMR90 cells expressing OSKM and shRNA library derived from the shRNA screen (bypassing senescence), 64 OSKM-expressing IMR90 cells (senescent), 32 IMR90 cells expressing control vector

Publication Title

Coupling shRNA screens with single-cell RNA-seq identifies a dual role for mTOR in reprogramming-induced senescence.

Sample Metadata Fields

Specimen part, Subject

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accession-icon GSE38200
Ikaros target genes in the mouse pre-B cell line B3
  • organism-icon Mus musculus
  • sample-icon 19 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302), Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Genome-wide identification of Ikaros targets elucidates its contribution to mouse B-cell lineage specification and pre-B-cell differentiation.

Sample Metadata Fields

Specimen part, Cell line

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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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