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accession-icon SRP119119
Gene expression profiles of migrating cell types Drosophila embryogenesis
  • organism-icon Drosophila melanogaster
  • sample-icon 4 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Cell migration is an instrumental process that ensures cells are properly positioned to support the specification of distinct tissue types during development. To provide insight, we used fluorescence activated cell sorting (FACS) to isolate two migrating cell types from the Drosophila embryo: caudal visceral mesoderm (CVM) cells, precursors of longitudinal muscles of the gut, and hemocytes (HCs), the Drosophila equivalent of blood cells. ~350 genes were identified from each of the sorted samples using RNA-seq, and in situ hybridization was used to confirm expression within each cell type or, alternatively, within other interacting, co-sorted cell types. To start, the two gene expression profiling datasets were compared to identify cell migration regulators that are potentially generally-acting. 73 genes were present in both CVM cell and HC gene expression profiles, including the transcription factor zinc finger homeodomain-1 (zfh1). Comparisons with gene expression profiles of Drosophila border cells that migrate during oogenesis had a more limited overlap, with only the genes neyo (neo) and singed (sn) found to be expressed in border cells as well as CVM cells and HCs, respectively. Neo encodes a protein with Zona pellucida domain linked to cell polarity, while sn encodes an actin binding protein. Tissue specific RNAi expression coupled with live in vivo imaging was used to confirm cell-autonomous roles for zfh1 and neo in supporting CVM cell migration, whereas previous studies had demonstrated a role for Sn in supporting HC migration. In addition, comparisons were made to migrating cells from vertebrates. Seven genes were found expressed by chick neural crest cells, CVM cells, and HCs including extracellular matrix (ECM) proteins and proteases. In summary, we show that genes shared in common between CVM cells, HCs, and other migrating cell types can help identify regulators of cell migration. Our analyses show that neo in addition to zfh1 and sn studied previously impact cell migration. This study also suggests that modification of the extracellular milieu may be a fundamental requirement for cells that undergo cell streaming migratory behaviors. Overall design: Examination of genes expressed in two migrating cell populations (CVM and hemocytes) during their active cell migration and the rest of cell types of corresponding stages

Publication Title

Comparative analysis of gene expression profiles for several migrating cell types identifies cell migration regulators.

Sample Metadata Fields

Specimen part, Subject

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accession-icon GSE8269
Uterus_Gravid_d18_WT vs. Cox-1 KO
  • organism-icon Mus musculus
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Background: Preterm birth is the leading cause of all infant mortality. In 2004, 12.5% of all births were preterm. In order to understand preterm labor, we must first understand normal labor. Since many of the myometrial changes that occur during pregnancy are similar in mice and humans and mouse gestation is short, we have studied the uterine genes that change in the mouse during pregnancy. Here, we used microarray analysis to identify uterine genes in the gravid mouse that are differentially regulated in the cyclooxygenase-1 knockout mouse model of delayed parturition.

Publication Title

Identification of 9 uterine genes that are regulated during mouse pregnancy and exhibit abnormal levels in the cyclooxygenase-1 knockout mouse.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE3726
Prognostic gene signatures can be measured with samples stored in RNAlater
  • organism-icon Homo sapiens
  • sample-icon 104 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

A number of breast or colon specific genes predictive of the relapse status were used in comparing the outcome from matched fresh frozen and stored in RNAlater preservative.

Publication Title

Prognostic gene expression signatures can be measured in tissues collected in RNAlater preservative.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP126516
Transcriptome response of human skeletal muscle to divergent exercise stimuli
  • organism-icon Homo sapiens
  • sample-icon 29 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

While acute aerobic and resistance exercise stimulate a number of shared genes, each exercsie mode stimlutes a number of uniquely responsive genes, thus highlighting that different forms of exercise facilitate distinct molecular responses in skeletal muscle. Overall design: Randomized, counter-balanced, cross-over design (n=6) in which subjects performed an acute bout aerobic and resistance exercise separated by ~1 week.

Publication Title

Transcriptome response of human skeletal muscle to divergent exercise stimuli.

Sample Metadata Fields

Sex, Subject, Time

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accession-icon SRP007896
Non-coding small RNA profiling by high throughput sequencing of bovine primary retinal microvascular endothelial cells
  • organism-icon Bos taurus
  • sample-icon 1 Downloadable Sample
  • Technology Badge IconIllumina Genome Analyzer II

Description

The aim of this study was to identify and quantify microRNAs and other small regulatory RNAs expressed in primary retinal microvascular endothelial cells (RMECs) using deep sequencing. RMECs were isolated, RNA extracted, a small RNA library prepared and deep sequencing performed. A total of 6.8 million reads were mapped to 250 known microRNAs in miRBase (release 16). Several novel microRNAs and multiple new members of the miR-2284/2285 family were detected. Several ~30 nucleotide sno-miRNAs were identified, with the most highly expressed being derived from snoRNA U78. Highly expressed microRNAs previously associated with endothelial cells included miR-126 and miR-378, but the most highly expressed was miR-21, comprising more than one third of all mapped reads. The independence from prior sequence knowledge provided by deep sequencing facilitates analysis of novel microRNAs and other small RNAs. This approach also enables quantitative evaluation of microRNA expression, which has highlighted the predominance of a small number of microRNAs in RMECs. Further characterisation of the functions of the highly expressed microRNAs will provide insights into endothelial biology. Overall design: Single sample of primary cell culture

Publication Title

Deep sequencing reveals predominant expression of miR-21 amongst the small non-coding RNAs in retinal microvascular endothelial cells.

Sample Metadata Fields

Specimen part, Subject

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accession-icon SRP055478
Myelodysplastic syndrome: NUP98-HoxD13 (NHD13) expression effect on hematopoietic stem cells
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Analysis of Lin-c-Kit+Sca-1- haematopoietic stem cells (HSCs) expressing the Nup98-HoxD13 (NHD13) fusion gene. NHD13 induces myelodysplastic syndrome (MDS) in mice. Results provide insight into the molecular basis of the myelodysplastic phenotype Overall design: WT mouse HSCs were compared to an NHD13 mutant sequenced in triplicate on a HiSeq 2000

Publication Title

PUMA promotes apoptosis of hematopoietic progenitors driving leukemic progression in a mouse model of myelodysplasia.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE10304
Gene expression in AES-2 clonal isolates of Pseudomonas aeruginosa
  • organism-icon Pseudomonas aeruginosa
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Pseudomonas aeruginosa Array (paeg1a)

Description

Pseudomonas aeruginosa (P. aeruginosa) lung infection is a significant cause of mortality in patients with cystic fibrosis (CF). Most CF patients acquire unique P. aeruginosa strains from the environment; however clonal strains have been identified in CF communities in several countries. Two clonal strains infect 10% to 40% of patients in three CF clinics in mainland eastern Australia. The expression profiles of four planktonically-grown isolates of one Australian clonal strain (AES-2), and four nonclonal CF P. aeruginosa isolates were compared to each other and to the reference strain PAO1 using the Affymetrix P. aeruginosa PAO1 genome array, to gain insight into properties mediating the enhanced infectivity of AES-1. The isolates were subsequently grown as 3-day old biofilms and similarly extracted for RNA and compared as above. Data analysis was carried out using BIOCONDUCTOR software.

Publication Title

Transcriptome analyses and biofilm-forming characteristics of a clonal Pseudomonas aeruginosa from the cystic fibrosis lung.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE58081
Analysis of gene expression in CD8+ T cells activated in vitro or in vivo
  • organism-icon Mus musculus
  • sample-icon 36 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

c-Myc-induced transcription factor AP4 is required for host protection mediated by CD8+ T cells.

Sample Metadata Fields

Specimen part

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accession-icon SRP076395
Benomyl toxicity links histone H3 lysine 4 methylation to cell cycle control
  • organism-icon Saccharomyces cerevisiae
  • sample-icon 20 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 1500

Description

The PAT-seq approach was utilised to determine the gene expression changes over the cell-cycle of wildtype and delta-set1 yeast strains. The cell were synchronised by alpha-factor arrest and cell-cycle release Overall design: Analysis gene expresson across the S. cerevisiae cell cycle.

Publication Title

Coordination of Cell Cycle Progression and Mitotic Spindle Assembly Involves Histone H3 Lysine 4 Methylation by Set1/COMPASS.

Sample Metadata Fields

Cell line, Subject, Time

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accession-icon GSE58078
Microarray analysis of WT and Tfap4-KO CD8 T cells during early activation
  • organism-icon Mus musculus
  • sample-icon 14 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

Gene expression of Tfap4/ and WT CD8+ T cells were compared after activation with anti-CD3 and anti-CD28 antibodies in vitro or with Listeria monocytogenes infection in vivo

Publication Title

c-Myc-induced transcription factor AP4 is required for host protection mediated by CD8+ T cells.

Sample Metadata Fields

No sample metadata fields

View Samples
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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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