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accession-icon GSE60760
Gene expression responses to chronic low dose arsenite exposure
  • organism-icon Homo sapiens
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Transcriptome Array 2.0 (hta20)

Description

Arsenic (As) exposure is a significant worldwide environmental health concern. Low dose, chronic arsenic exposure has been associated with higher risk of skin, lung, and bladder cancer, as well as cardiovascular disease and diabetes. While arsenic-induced biological changes play a role in disease pathology, little is known about the dynamic cellular changes due to arsenic exposure and withdrawal. In these studies, we seek to understand the molecular mechanisms behind the biological changes induced by chronic low doses of arsenic exposure. We used a comprehensive approach involving chromatin structural studies and mRNA microarray analyses to determine how chromatin structure and gene expression patterns change in response to chronic low dose arsenic exposure and its subsequent withdrawal. Our results show that cells exposed to low doses of sodium arsenite have distinct temporal and coordinated chromatin, gene expression and miRNA changes that are consistent with differentiation and activation of multiple biochemical pathways. Most of these temporal patterns in gene expression are reversed when arsenic was withdrawn. However, some of the gene expression patterns remained altered, plausibly as a result of an adaptive response by these cells. Additionally, these gene expression patterns correlated with changes in chromatin structure, further solidifying the role of chromatin structure in gene regulatory changes due to arsenite exposure. Lastly, we show that arsenite exposure influences gene regulation both at the transcription initiation as well as at the splicing level. Thus our results suggest that general patterns of alternative splicing, as well as expression of particular gene regulators, can be indicative of arsenite-induced cell transformation.

Publication Title

Inorganic Arsenic-induced cellular transformation is coupled with genome wide changes in chromatin structure, transcriptome and splicing patterns.

Sample Metadata Fields

Cell line

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accession-icon E-TABM-63
Transcription profiling by array of Arabidopsis overexpressing artifical microRNAs
  • organism-icon Arabidopsis thaliana
  • sample-icon 20 Downloadable Samples
  • Technology Badge Icon Affymetrix Arabidopsis ATH1 Genome Array (ath1121501)

Description

Tissues of Arabidopsis plants overexpressing artificial microRNAs were compared to wild_type and respective target gene mutants (duplicate arrays)

Publication Title

Highly specific gene silencing by artificial microRNAs in Arabidopsis.

Sample Metadata Fields

Specimen part

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accession-icon GSE9807
Expression data from RNAi SNCA treated human neuroblastoma cell line
  • organism-icon Homo sapiens
  • sample-icon 5 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The pre-synaptic protein -synuclein is a key player in the pathogenesis of Parkinson's disease. Together with accumulation and missfolding of -synuclein protofibrils serve as seed structures for the aggregation of numerous proteins in the cytoplasm of neuronal cells, the so-called Lewy bodies. Furthermore, missense mutations in the SNCA gene and gene multiplications lead to autosomal dominant forms of familiar PD. However, so far the exact biological role of -synuclein in normal brain is elusive. To gain more insights into the biological function of this protein we monitored whole genome expression changes in dopaminergic neuroblastoma cells (SH-SY5Y) caused by a 90% reduction of -synuclein by RNA interference.

Publication Title

Microarray expression analysis of human dopaminergic neuroblastoma cells after RNA interference of SNCA--a key player in the pathogenesis of Parkinson's disease.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP123526
Single-cell RNAseq (SMART-seq2) of wild-type (TLAB) and MZoep (tz57) zebrafish embryos at 50% epiboly stage
  • organism-icon Danio rerio
  • sample-icon 415 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

SMART-seq2 was performed on single cells isolated from visually staged zebrafish embryos. Overall design: Samples were all sequenced in one batch. Some were generated with a 5'' UMI-tagged method, and others are full-length SMART-seq2.

Publication Title

Single-cell reconstruction of developmental trajectories during zebrafish embryogenesis.

Sample Metadata Fields

Subject

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accession-icon GSE38124
Characterization of cisplatin-induced transcriptomics responses in primary mouse hepatocytes, HepG2 cells and mouse embryonic stem cells shows a strong conservation of involved transcription factors
  • organism-icon Mus musculus, Homo sapiens
  • sample-icon 30 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

Characterisation of cisplatin-induced transcriptomics responses in primary mouse hepatocytes, HepG2 cells and mouse embryonic stem cells shows conservation of regulating transcription factor networks.

Sample Metadata Fields

Cell line, Treatment, Time

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accession-icon SRP124289
Drop-seq analysis of wild-type (TLAB) zebrafish embryos from high to 6-somite stage (12 timepoints)
  • organism-icon Danio rerio
  • sample-icon 28 Downloadable Samples
  • Technology Badge IconNextSeq 500

Description

Wild-type zebrafish embryos were mechanically dissociated and profiled using Drop-seq Overall design: Drop-seq was performed on 28 groups of 20-40 visually staged, mechanically dissociated embryos. Samples were combined and sequenced in batches DS2-DS5.

Publication Title

Single-cell reconstruction of developmental trajectories during zebrafish embryogenesis.

Sample Metadata Fields

Subject

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accession-icon SRP043080
Transcriptomic profiling of peripheral blood mononuclear cells from healthy individuals
  • organism-icon Homo sapiens
  • sample-icon 24 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2500

Description

Substantial effort is currently devoted to identifying cancer-associated alterations using genomics. Here, we show that standard blood collection procedures rapidly change the transcriptional and post-transcriptional landscapes of hematopoietic cells, resulting in biased activation of specific biological pathways, up-regulation of pseudogenes, antisense RNAs, and unannotated coding isoforms, and RNA surveillance inhibition. Affected genes include common mutational targets and thousands of other genes participating in processes such as chromatin modification, RNA splicing, T and B cell activation, and NF-?B signaling. The majority of published leukemic transcriptomes exhibit signals of this incubation-induced dysregulation, explaining up to 40% of differences in gene expression and alternative splicing between leukemias and reference normal transcriptomes. The effects of sample processing are particularly evident in pan-cancer analyses. We provide biomarkers that detect prolonged incubation of individual samples, and show that keeping blood on ice markedly reduces changes to the transcriptome. In addition to highlighting the potentially confounding effects of technical artifacts in cancer genomics data, our study emphasizes the need to survey the diversity of normal as well as neoplastic cells when characterizing tumors. This study is complemented by GSE61410: transcriptomic profiling of bone marrow cells from healthy individuals. Overall design: Peripheral blood mononuclear cells (PBMCs) were isolated from four healthy individuals, following an ex vivo incubation of variable length at either room temperature or on ice. RNA transcriptomes were measured using the Illumina HiSeq.

Publication Title

Sample processing obscures cancer-specific alterations in leukemic transcriptomes.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE38122
Expression Profiles of HepG2 cells treated with 7M of the genotoxic compound cisplatin
  • organism-icon Homo sapiens
  • sample-icon 18 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The transcriptomic changes induced in the human liver cell line HepG2 by 7M of cisplatin after treatment for 12, 24 and 48h

Publication Title

Characterisation of cisplatin-induced transcriptomics responses in primary mouse hepatocytes, HepG2 cells and mouse embryonic stem cells shows conservation of regulating transcription factor networks.

Sample Metadata Fields

Cell line, Treatment, Time

View Samples
accession-icon GSE38123
Expression Profiles of PMH treated with 7M of the genotoxic compound cisplatin
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The transcriptomic changes induced in primary mouse hepatocytes (C57BL/6 ) by 7M of cisplatin after treatment for 24 and 48h

Publication Title

Characterisation of cisplatin-induced transcriptomics responses in primary mouse hepatocytes, HepG2 cells and mouse embryonic stem cells shows conservation of regulating transcription factor networks.

Sample Metadata Fields

Cell line, Treatment, Time

View Samples
accession-icon SRP137889
10x analysis of wild-type (TLAB) and MZoep zebrafish embryos at 6-somite stage
  • organism-icon Danio rerio
  • sample-icon 2 Downloadable Samples
  • Technology Badge IconNextSeq 500

Description

Wild-type and MZoep zebrafish embryos were mechanically dissociated and profiled using 10x Genomics pipeline. Overall design: 10x scRNA-seq was performed on visually staged, mechanically dissociated embryos. Samples were combined and sequenced in one batch.

Publication Title

Single-cell reconstruction of developmental trajectories during zebrafish embryogenesis.

Sample Metadata Fields

Subject

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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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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