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accession-icon SRP049605
Identification of a Molecular Signature for Acute Lyme Disease by Human Transcriptome Profiling
  • organism-icon Homo sapiens
  • sample-icon 97 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2000

Description

Lyme disease is challenging to diagnose, as clinical manifestations are variable and current tools to detect nucleic acid or antibody responses from Borrelia burgdorferi infection have low sensitivity. Here we conducted the first study of the global transcriptome of patients with Lyme disease to identify potential diagnostic biomarkers. Twenty-nine patients were enrolled and compared to 13 healthy controls at three time points after infection. Fifteen publicly available transcriptome datasets from patients in vivo or infection models in vitro were used to assess specificity of differentially expressed genes (DEGs). We found that Lyme disease results in profound and sustained changes in the patient transcriptomes, with a specific signature that shares =44% DEGs with other infections. Overall design: Gene expression profile from peripheral mononuclear blood cells (PBMC) of Lyme disease patients against healthy controls was undertaken. A total of 29 Lyme disease patients were sampled at 3 time points: acute Lyme pre-treatment (V1), 3 weeks later, immediately following completion of a standard course of antibiotics (V2), and 6 months following treatment completion (V5). 13 healthy controls were also sampled at one time point. Total RNA was extracted from 10e7 PBMC, followed by mRNA purification, paired-end barcode library preparation and sequencing on an Illumina Hiseq 2000.

Publication Title

Longitudinal Transcriptome Analysis Reveals a Sustained Differential Gene Expression Signature in Patients Treated for Acute Lyme Disease.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP187984
Whole blood human transcriptome and virome analysis of ME/CFS patients experiencing post-exertional malaise following cardiopulmonary exercise testing
  • organism-icon Homo sapiens
  • sample-icon 94 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Myalgic encephalomyelitis / chronic fatigue syndrome (ME/CFS) is a syndrome of unknown etiology characterized by profound fatigue exacerbated by physical activity, also known as post-exertional malaise (PEM). Previously, we did not detect evidence of immune dysregulation or virus reactivation outside of PEM periods. Here we sought to determine whether cardiopulmonary exercise stress testing of ME/CFS patients could trigger such changes. ME/CFS patients (n=14) and matched sedentary controls (n=11) were subjected to cardiopulmonary exercise on 2 consecutive days and followed up to 7 days post-exercise, and longitudinal whole blood samples analyzed by RNA-seq. Although ME/CFS patients showed significant worsening of symptoms following exercise versus controls, with 8 of 14 ME/CFS patients showing oxygen consumption (V?O2) on day 2, transcriptome analysis yielded only 6 differentially expressed gene (DEG) candidates when comparing ME/CFS patients to controls across all time points. None of the DEGs were related to immune signaling, and no DEGs were found in ME/CFS patients before and after exercise. Virome composition (P=0.746 by chi-square test) and number of viral reads (P = 0.098 by paired t-test) were not significantly associated with PEM. These observations do not support transcriptionally-mediated immune cell dysregulation or viral reactivation in ME/CFS patients during symptomatic PEM episodes. Overall design: RNAseq of whole blood samples from ME/CFS patients and controls following exercise.

Publication Title

Whole blood human transcriptome and virome analysis of ME/CFS patients experiencing post-exertional malaise following cardiopulmonary exercise testing.

Sample Metadata Fields

Specimen part, Disease, Disease stage, Treatment, Subject

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accession-icon SRP098918
Hippocampus CA1 pyramidal cells Transcriptomic profile in WT and Fmr1 KO mice, using Wfs1-CreERT2:RiboTag:Frm1 knockout and wildtype mice
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Comparing WT mice to a mouse model of mental retardation, this work identifies genes which display differences in ribosome-bound mRNAs, in hippocampus CA1 pyramidal cells. These genes products are potent functional components of neuronal plasticity and hippocampus-dependent memory. Overall design: Using a triple transgenic mouse line, we immunoprecipitated the HA-Rpl22 protein to isolate and sequence ribosome-associated mRNA in CA1 pyramidal cells. Pairwise comparison of wild type and Fmr1 KO mice defined a specific gene expression profile.

Publication Title

Cell Type-Specific mRNA Dysregulation in Hippocampal CA1 Pyramidal Neurons of the Fragile X Syndrome Mouse Model.

Sample Metadata Fields

Specimen part, Subject

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accession-icon GSE7491
Expression data from rat lung alveolar development
  • organism-icon Rattus norvegicus
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Genome 230 2.0 Array (rat2302)

Description

Lung alveolarization is a complex process that involves interactions between several cell types and leads to considerable increase in gas-exchange surface area. The step designated secondary septation includes elastogenesis from interstitial fibroblasts.

Publication Title

Gene expression profiling in lung fibroblasts reveals new players in alveolarization.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE102067
An RNAi screen reveals an essential role for HIPK4 in human skin epithelial differentiation from iPSCs
  • organism-icon Homo sapiens
  • sample-icon 21 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V4.0 expression beadchip

Description

Molecular mechanisms that are responsible for the development of human skin epithelial cells are not completely understood so far. As a consequence, the efficiency to establish a pure skin epithelial cell population from human induced pluripotent stem cells (hiPSC) remains poor. Using an approach including RNA interference and high-throughput imaging of early epithelial cells, we could identify candidate kinases which are involved in skin epithelial differentiation. Among them, we found HIPK4 to be an important inhibitor of this process. Indeed, its silencing increased the amount of generated skin epithelial precursors, increased the amount of generated keratinocytes and improved growth and differentiation of organotypic cultures, allowing for the formation of a denser basal layer and stratification with the expression of several keratins. Our data bring substantial input in the regulation of human skin epithelial differentiation and for improving differentiation protocols from pluripotent stem cells.

Publication Title

An RNAi Screen Reveals an Essential Role for HIPK4 in Human Skin Epithelial Differentiation from iPSCs.

Sample Metadata Fields

Specimen part, Time

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accession-icon SRP186927
AmpliSeq transcriptome profiling of human adipose tissue progenitor cell types
  • organism-icon Homo sapiens
  • sample-icon 26 Downloadable Samples
  • Technology Badge IconNextSeq 500

Description

Three different progenitor cell subsets in subcutaneous and visceral adipose tissues derived from 5 obese patients were subjected to AmpliSeq transcriptome profiling. Transcriptomic profiles were analyzed to compare progenitor cell subsets and the impact of subcutaneous and visceral adipose tissue location. Overall design: Transcriptomic profiling of 3 different progenitor cell types in subcutaneous and visceral adipose tissues derived from 5 obese patients (3X2X5=30 samples).

Publication Title

Lobular architecture of human adipose tissue defines the niche and fate of progenitor cells.

Sample Metadata Fields

Subject

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accession-icon GSE137110
Chronic mucocutaneous candidiasis and connective tissue disorder in humans with impaired JNK1-dependent responses to IL-17A/F and TGF-?
  • organism-icon Homo sapiens
  • sample-icon 16 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 2.0 ST Array (hugene20st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Chronic mucocutaneous candidiasis and connective tissue disorder in humans with impaired JNK1-dependent responses to IL-17A/F and TGF-β.

Sample Metadata Fields

Specimen part, Disease, Disease stage, Treatment, Time

View Samples
accession-icon GSE16458
A simple method to integrate different versions of Affymetrix microarrays using duplicate samples
  • organism-icon Rattus norvegicus
  • sample-icon 48 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Expression 230A Array (rae230a)

Description

The size and scope of microarray experiments continue to increase. However, datasets generated on different platforms or at different centres contain biases. Improved techniques are needed to remove platform- and batch-specific biases. One experimental control is the replicate hybridization of a subset of samples at each site or on each platform to learn the relationship between the two platforms. To date, no algorithm exists to specifically use this type of control. LTR is a linear-modelling-based algorithm that learns the relationship between different microarray batches from replicate hybridizations. LTR was tested on a new benchmark dataset of 20 samples hybridized to different Affymetrix microarray platforms. Before LTR, the two platforms were significantly different; application of LTR removed this bias. LTR was tested with six separate data pre-processing algorithms, and its effectiveness was independent of the pre-processing algorithm. Sample-size experiments indicate that just three replicate hybridizations can significantly reduce bias. An R library implementing LTR is available.

Publication Title

LTR: Linear Cross-Platform Integration of Microarray Data.

Sample Metadata Fields

Sex

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accession-icon GSE73599
Celiac disease T cell clone response to CD3/CD28 stimulation
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

To identify the CD4+ T cell cytokines responsible for the proliferation of the Lin-IEL lines CD4+ T cell clone L10, which recognises DQ2-glia-1, one of the immunodominant T cell epitopes in celiac disease, was stimulated for 3 hours in IMDM with plate-bound CD3/CD28-specific (2.5 g/ml each) or control antibodies coated onto 6-well non-tissue culture treated plates. Three independent biological replicates were performed, each time including 6 million Ficoll-purified live cells per condition. RNA was purified from these cells using the RNAeasy mini kit (Qiagen, Venlo, the Netherlands). cDNA was amplified using the Applause WT-Amp system (NuGEN technologies, Bemmel, the Netherlands) and biotin-labelled with the Encore Biotin Module (NuGEN). Human Gene 1.0 ST arrays (Affymetrix, High Wycombe, UK) were employed to quantify global gene expression.

Publication Title

CD4 T-cell cytokines synergize to induce proliferation of malignant and nonmalignant innate intraepithelial lymphocytes.

Sample Metadata Fields

Specimen part

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accession-icon GSE70421
SMARCB1-deficient rhaboid tumors of the kidney and renal medullary carcinomas.
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

We used microarrays to compared gene expression profilings in various tumors of the kidney.

Publication Title

Balanced Translocations Disrupting SMARCB1 Are Hallmark Recurrent Genetic Alterations in Renal Medullary Carcinomas.

Sample Metadata Fields

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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