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accession-icon SRP128491
RNA-seq analysis of miR-324-5p overexpression upon H5N1 infection in A549 cells
  • organism-icon Homo sapiens
  • sample-icon 3 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

The goals of this study are to compare NGS-derived whole transcriptome profiles (RNA-seq) of H5N1 infected A549 cells overexpressing either negative control mimic or miR-324-5p mimic Overall design: A549 cells were either mock transfected or transfected with either negative control or mir-324-5p mimic. After 12 hours cells were either mock infected (mock transfected cells) or infected with A/duck/India/02CA10/2011 - H5N1 virus (negative control and miR-324-5p overexpressing cells)

Publication Title

MicroRNA hsa-miR-324-5p Suppresses H5N1 Virus Replication by Targeting the Viral PB1 and Host CUEDC2.

Sample Metadata Fields

Specimen part, Cell line, Subject

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accession-icon GSE61631
Comparative transcriptional profiling between the organs of the scion and rootstock of a homograft (Arabidopsis thaliana)
  • organism-icon Arabidopsis thaliana
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Arabidopsis ATH1 Genome Array (ath1121501)

Description

Analyses of expression differences in flower bud and leaf of scion and rootstock, in homografts of Arabidopsis

Publication Title

Grafting triggers differential responses between scion and rootstock.

Sample Metadata Fields

Specimen part

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accession-icon GSE18285
Characterization of the transcriptional roles of NME2
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Non-metastatic 2 (NME2)-mediated suppression of lung cancer metastasis involves transcriptional regulation of key cell adhesion factor vinculin.

Sample Metadata Fields

Specimen part, Cell line

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accession-icon GSE38490
Comparative analysis of transcriptome profiles of G. hirsutum L. cv. MCU5 and its fuzzless-lintless mutant during fiber development stages.
  • organism-icon Gossypium hirsutum
  • sample-icon 30 Downloadable Samples
  • Technology Badge Icon Affymetrix Cotton Genome Array (cotton)

Description

Cotton is one of the most commercially important Fiber crops in the world and used as a source for natural textile Fiber and cottonseed oil. The fuzzless-lintless ovules of cotton mutants are ideal source for identifying genes involved in Fiber development by comparing with Fiber bearing ovules of wild-type. To decipher molecular mechanisms involved in Fiber cell development, transcriptome analysis has been carried out by comparing G. hirsutum cv. MCU5 (wild-type) with its fuzzless-lintless mutant (MUT). Cotton bolls were collected at Fiber initiation (0 dpa/days post anthesis), elongation (5, 10 and 15 dpa) and secondary cell wall synthesis stage (20 dpa) and gene expression profiles were analyzed in wild-type and MUT using Affymetrix cotton GeneChip Genome array.

Publication Title

Functional genomics of fuzzless-lintless mutant of Gossypium hirsutum L. cv. MCU5 reveal key genes and pathways involved in cotton fibre initiation and elongation.

Sample Metadata Fields

Specimen part

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accession-icon SRP043463
Genome-wide identification of rat long non-coding RNAs
  • organism-icon Rattus norvegicus
  • sample-icon 3 Downloadable Samples
  • Technology Badge IconIllumina Genome Analyzer

Description

In the current study, we have focused on a distinct group of non-coding elements, lncRNA, and profiled renal tissues from three different inbred rat strains. We chose the three strains S, SHR and R for the main purpose of cataloging lncRNA annotations from the most widely used rat models of cardiovascular and renal disease. Overall design: Identification of lncRNAs on the rat genome by next generation RNA sequencing (NGS)

Publication Title

Genome-wide identification of long noncoding RNAs in rat models of cardiovascular and renal disease.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE29810
Global gene expression analysis of cotton (Gossypium hirsutum L.) under drought stress in leaf tissue and during fibre development stages.
  • organism-icon Gossypium hirsutum
  • sample-icon 30 Downloadable Samples
  • Technology Badge Icon Affymetrix Cotton Genome Array (cotton)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Genome-wide transcriptomic analysis of cotton under drought stress reveal significant down-regulation of genes and pathways involved in fibre elongation and up-regulation of defense responsive genes.

Sample Metadata Fields

Specimen part, Treatment

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accession-icon GSE29567
Global gene expression analysis of cotton (Gossypium hirsutum L.) under drought stress during fibre development stages.
  • organism-icon Gossypium hirsutum
  • sample-icon 24 Downloadable Samples
  • Technology Badge Icon Affymetrix Cotton Genome Array (cotton)

Description

Transcriptome analysis in cotton during fibre development stages.

Publication Title

Genome-wide transcriptomic analysis of cotton under drought stress reveal significant down-regulation of genes and pathways involved in fibre elongation and up-regulation of defense responsive genes.

Sample Metadata Fields

Treatment

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accession-icon GSE29566
Global gene expression analysis of cotton (Gossypium hirsutum L.) under drought stress in leaf tissue.
  • organism-icon Gossypium hirsutum
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Cotton Genome Array (cotton)

Description

Transcriptome analysis in cotton under drought stress.

Publication Title

Genome-wide transcriptomic analysis of cotton under drought stress reveal significant down-regulation of genes and pathways involved in fibre elongation and up-regulation of defense responsive genes.

Sample Metadata Fields

Specimen part, Treatment

View Samples
accession-icon SRP136108
RNA-seq of nine primary human cell types exposed in vitro to methylprednisolone
  • organism-icon Homo sapiens
  • sample-icon 130 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000, Illumina HiSeq 3000

Description

Glucocorticoids remain the most widely used class of anti-inflammatory and immunosuppressive agents. They act primarily by binding to the glucocorticoid receptor, resulting in direct and indirect effects on gene expression. The current understanding of glucocorticoid effects on transcription in human cells is based mostly on studies of cancer cell lines, immortalized cell lines, or highly mixed populations of primary cells (such as peripheral blood mononuclear cells). To advance the understanding of the transcriptome-wide effects of glucocorticoids on highly pure populations of primary human cells, we performed RNA-seq on nine such cell populations at two time points after in vitro exposure to methylprednisolone or vehicle. Overall design: Nine cell types were studied: four hematopoietic (circulating B cells, CD4+ T cells, monocytes, and neutrophils) and five non-hematopoietic (endothelial cells, fibroblasts, myoblasts, osteoblasts, and preadipocytes). Each cell type was obtained from a separate cohort of 4 unrelated healthy human donors (4 biological replicates per cell type: BR1 - BR4). Cells form each donor were independently cultured and exposed in vitro to glucocorticoid or vehicle. Non-hematopoietic cells were incubated until the early plateau phase of growth, then exposed to methylprednisolone or vehicle. Hematopoietic cells were collected from peripheral blood, purified by magnetic selection (negative selection for B cells, CD4+ T cells and neutrophils; positive selection for monocytes). Purified B cells, CD4+ T cells, and monocytes were incubated overnight, then exposed to methylprednisolone or vehicle. Purified neutrophils were cultured for 4 hours, then exposed to methylprednisolone or vehicle. Ethanol was used as a vehicle for methylprednisolone. Estimated final concentrations were 8500 mcg/L (22.7 mcM) for methylprednisolone and 0.07% (15.57 mM) for ethanol (vehicle). For each cell type, samples were collected at two time points after treatment with methylprednisolone or vehicle: 2 hours and 6 hours. Samples were collected into TRIzol reagent and frozen at -80°C prior to RNA extraction. RNA-seq data for all samples is made available in this GEO Series.

Publication Title

Immune regulation by glucocorticoids can be linked to cell type-dependent transcriptional responses.

Sample Metadata Fields

Specimen part, Subject, Time

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accession-icon GSE23643
Cardiac transcriptome profiles of S.LEW congenic strain compared with the hypertensive Dahl S rat
  • organism-icon Rattus norvegicus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Genome 230 2.0 Array (rat2302)

Description

Despite inheritance of hypertension in families, identifying genetic mechanisms predisposing individuals to hypertension has remained challenging. The effects of single genes contributing to the development of hypertension may not be readily detected in individuals whose genomes also contain other genetic factors that resist hypertension. By using a highly permissive rat genome for inherited hypertension, we demonstrate that increased expression of one such gene, Rififylin (Rffl), is a novel inherited risk factor for hypertension and increased mortality. Animals overexpressing Rffl demonstrated delayed endocytic recycling, accumulated polyubiquitinated proteins, increased beats/min of neonatal cardiomyocytes, had shorter QT-intervals and developed salt-insensitive hypertension very early in their life (50-52 days). Thus, the discovery of a physiological link between overexpression of rififylin and the development of hypertension constitutes a novel mechanism that could be targeted for rectifying normal QT-interval and preventing hypertension.

Publication Title

Augmented rififylin is a risk factor linked to aberrant cardiomyocyte function, short-QT interval and hypertension.

Sample Metadata Fields

Age, 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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