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accession-icon GSE73351
The Arabidopsis thaliana map65-3 and ugt76b1 mutant transcriptomes upon the compatible interaction with Hyaloperonospora arabidopsidis
  • organism-icon Arabidopsis thaliana
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Arabidopsis ATH1 Genome Array (ath1121501)

Description

We used Arabidopsis full-genome microarrays to characterize plant transcript accumulations in map65-3 and ugt76b1 mutants, 3 days after water treatment and inoculation with the biotrophic oomycete downy mildew pathogen, Hyaloperonospora arabidopsidis (Hpa)

Publication Title

The Arabidopsis microtubule-associated protein MAP65-3 supports infection by filamentous biotrophic pathogens by down-regulating salicylic acid-dependent defenses.

Sample Metadata Fields

Specimen part, Time

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accession-icon E-MEXP-558
Transcription profiling by array of connexin30 knock-out mice
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430A 2.0 Array (mouse430a2)

Description

Effect of the ablation of connexin 30 in the stria vascularis

Publication Title

Connexin30 deficiency causes instrastrial fluid-blood barrier disruption within the cochlear stria vascularis.

Sample Metadata Fields

Age, Specimen part, Disease, Time

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accession-icon GSE13732
CIS (multiple sclerosis) (case-control) (time-series)
  • organism-icon Homo sapiens
  • sample-icon 112 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Clinically isolated syndrome (CIS) refers to the earliest clinical manifestation of multiple sclerosis (MS). Currently there are no prognostic biological markers that accurately predict conversion of CIS to clinically definite MS (CDMS). Furthermore, the earliest molecular events in MS are still unknown. We used microarrays to study gene expression in nave CD4+ T cells from 37 CIS patients at time of diagnosis and after one year. Supervised machine-learning methods were used to build predictive models of disease conversion. We identified 975 genes whose expression segregated CIS patients into 4 distinct subgroups. A subset of 108 genes further discriminated patients from one of these (group#1) from other CIS patients. Remarkably, 92% of patients from group #1 converted to CDMS within 9 months. Consistent downregulation of TOB1, a critical regulator of cell proliferation, was characteristic of group #1 patients. Decreased TOB1 expression at the RNA and protein levels was also confirmed in experimental autoimmune encephalomyelitis (EAE). Finally, a genetic association was observed between TOB1 variation and MS progression in an independent cohort. These results indicate that CIS patients at high risk of conversion have impaired regulation of T cell quiescence resulting in earlier activation of pathogenic CD4+ cells.

Publication Title

Abrogation of T cell quiescence characterizes patients at high risk for multiple sclerosis after the initial neurological event.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE33656
Gene expression in articular cartilage - subchondral bone of FRZB knockout mice
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Objective : To study molecular changes in the articular cartilage and subchondral bone of the tibial plateau from mice deficient in frizzled related protein (Frzb) compared to wild-type mice by transcriptome analysis.

Publication Title

Tight regulation of wingless-type signaling in the articular cartilage - subchondral bone biomechanical unit: transcriptomics in Frzb-knockout mice.

Sample Metadata Fields

Sex, Age, Specimen part

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accession-icon SRP048842
Genome-wide profiling of DNA methylation at single-base resolution based on MeDIP-bisulfite high-throughput sequencing and ridge regression (RNA)
  • organism-icon Homo sapiens
  • sample-icon 2 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Unraveling complexity of DNA methylome is essential to decipher DNA methylation mechanism in life. However, this has been subjected to technological constraints to balance between cost and accurate measurement of the DNA methylation level. In this study, by innovatively introducing C-hydroxylmethylated adapters, we have developed MeDIP-Bisulfite sequencing (MB-seq), which could obtain DNA methylome of repertoire CpGs at single-base resolution. We found MB-seq only costs 10% of MethylC-seq, but covers 85% of total CpGs in human genome. Unlike absolute methylation levels determined by MethylC-seq and RRBS, MB-seq presented relative methylation levels that are linearly inflated. This has enlightened us to develop a MB-seq corresponding correction method for methylation level based on ridge regression, which integrates the data of MB-seq and RRBS to predict the methylation level of total 28.2 million CpGs on human genome with high accuracy (Pearson correlation coefficient, PCC=0.90). Moreover, by employing MB-seq, we generated the DNA methylome of an ovarian epithelial cell line (T29) and its oncogenic counterpart (T29H), respectively. After ridge regression, we identified 131,790 differential methylation regions (DMRs) with high accuracy between T29 and T29H, far more than 7,567 obtained from RRBS. Taken together, our result demonstrated that the MB-seq combined with ridge regression is a wide applicable approach for profiling of DNA methylome. Overall design: Total RNAs were extracted from T29 and T29H with RNeasy Mini Kit (QIAGEN, Germany). RNA quality was quality-controlled by Bioanalyser 2100 (RNA nano kits, Agilent). mRNA-Seq libraries were generated from total RNA with polyA+ selection of mRNA using the TruSeq RNA Sample Prep Kit v2 (Illumina, San Diego, CA), and then subjected to transcriptome sequencing on the Illumina Hiseq 2000

Publication Title

MBRidge: an accurate and cost-effective method for profiling DNA methylome at single-base resolution.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP017670
Next Generation Sequencing Facilitates Quantitative Analysis of CNE1-mock, CNE1-BART1, CNE-BART3, CNE1-BART7 cells
  • organism-icon Homo sapiens
  • sample-icon 4 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

By using NGS-derived retinal transcriptome profiling (RNA-seq) to compare the gene expression profiling between 4 differently treated NPC cells Overall design: Examination of different gene expression in EBV-miRNA-BART1/3/7 lentivirus and their control infected nasopharyngeal carcinoma cells.

Publication Title

Epstein-Barr virus-encoded microRNA BART1 induces tumour metastasis by regulating PTEN-dependent pathways in nasopharyngeal carcinoma.

Sample Metadata Fields

Specimen part, Cell line, Subject

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accession-icon GSE39602
Comparative analysis of Gallus gallus cecal epithelia following Eimeria tenella infection
  • organism-icon Gallus gallus, Eimeria tenella
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Chicken Genome Array (chicken)

Description

Relative expression levels of mRNAs in chicken cecal epithelia experimentally infected with Eimeria tenella were measured at 4.5 days post-infection. Two weeks old chickens were uninfected (negative control) or were orally inoculated with sporulated oocysts of Eimeria tenella. Cecal epithelia samples were collected from >12 birds in infected or uninfected group at 4.5 d following infections, in which samples from 4 birds were pooled together to form a total 3 biological replicates in each group. Parasite merozoites were also collected from four infected chickens at 5 d after infections. Uninfected control samples, merozoites and infection group samples were selected for RNA extraction and hybridization on Affymetrix microarrays.

Publication Title

Transcriptome analysis in chicken cecal epithelia upon infection by Eimeria tenella in vivo.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE143166
Gene expression of 6 FFPE tissues of adults with T-cell lymphoblastic lymphoma
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 2.0 ST Array (hugene20st)

Description

Affymetrix Human Gene 2.0 ST microarray (ThermoFisher Scientific, Waltham, MA, USA) was used to select differentially expressed genes.

Publication Title

BRD2 induces drug resistance through activation of the RasGRP1/Ras/ERK signaling pathway in adult T-cell lymphoblastic lymphoma.

Sample Metadata Fields

Sex, Age

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accession-icon SRP049250
Hepatic transcriptome changes in testosterone-deficient pigs fed a high-fat diet
  • organism-icon Sus scrofa
  • sample-icon 3 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

To gain insight into the role of testosterone in modulating hepatic fat accumulation, we collected liver tissues from high fat diet-fed intact male pigs, castrated male pigs, and castrated male pigs with testosterone replacement. RNA-Seq was employed to profile hepatic gene expression in pigs with different testosterone levels. Overall design: Liver mRNA profiles of intact male pigs fed a HFC diet, castrated male pigs fed a HFC diet, and castrated male pigs treated with testosterone fed a HFC diet were generated by deep sequencing, using Illumina HiSeq 2000.

Publication Title

Transcriptomic analysis of hepatic responses to testosterone deficiency in miniature pigs fed a high-cholesterol diet.

Sample Metadata Fields

Specimen part, Cell line, Subject

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accession-icon SRP018525
Genetic Programs in Human and Mouse Early Embryos Revealed by Single-Cell RNA-Sequencing
  • organism-icon Mus musculus
  • sample-icon 17 Downloadable Samples
  • Technology Badge Icon

Description

Mammalian preimplantation development is a complex process involving dramatic changes in the transcriptional architecture. Through single-cell RNA-sequencing (RNA-seq), we report here a comprehensive analysis of transcriptome dynamics from oocyte to morula in both human and mouse embryos. Based on single nucleotide variants (SNVs) in blastomere mRNAs and paternal-specific SNPs, we identify novel stage-specific monoallelic expression patterns for a significant portion of polymorphic gene transcripts (25-53%). By weighted gene co-expression network analysis (WGCNA), we find that each developmental stage can be concisely delineated by a small number of functional modules of co-expressed genes. This result indicates a sequential order of transcriptional changes in pathways of cell cycle, gene regulation, translation, and metabolism in a step-wise fashion from cleavage to morula. Cross-species comparisons reveal that the majority of human stage-specific modules (7 out of 9) are remarkably preserved, only to diverge in developmental specificity and timing in mice. We further identify conserved key members (or hub genes) of the human and mouse networks. These genes represent novel candidates that are likely key players in driving mammalian preimplantation development. Collectively, we demonstrate that mammalian preimplantation development is orchestrated by evolutionarily conserved genetic programs that diverge in developmental timing. Our results provide a valuable resource to dissect gene regulatory mechanism underlying progressive development of early mammalian embryos. Overall design: single-cell RNA-seq of human and mouse blastomeres

Publication Title

Genetic programs in human and mouse early embryos revealed by single-cell RNA sequencing.

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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