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accession-icon SRP104440
Changes in gene expression due to alpha-crystallin mutations cryaa-R49C and cryab-R120G in mutant knock-in mouse lenses
  • organism-icon Mus musculus
  • sample-icon 54 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

To investigate the relationship between histones, chaperone function, and cataracts, we performed RNA-seq, isothermal titration calorimetry (ITC), size-exclusion chromatography, and gel electrophoresis of histones. The RNA-seq of postnatal lenses from 2-day-old cryaa -R49C  mice revealed increased histone gene expression, suggesting that a a-crystallin mutation regulates histones via a transcriptional mechanism . Overall design: RNA-seq studies on lenses of 2-day-old wild-type and 2-day-old cryaa-R49C heterozygous mutant and cryaa-R49C homozygous mutant knock-in mice; and 14-day old wild-type and 14-day-old cryab-R120G heterozygous mutant and cryab-R120G homozygous mutant knock-in mice

Publication Title

Probing the changes in gene expression due to α-crystallin mutations in mouse models of hereditary human cataract.

Sample Metadata Fields

Cell line, Subject

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accession-icon SRP052991
RNA-seq and Microarray in Transcriptome Profiling of Anterior Cruciate Ligament Tears: Implications for Prognostic Biomarkers Discovery
  • organism-icon Homo sapiens
  • sample-icon 8 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2500

Description

Injury to anterior cruciate ligament (ACL) is common in young individuals and a frequent cause of functional instability and early onset of osteoarthritis. The healing potential of an injured ACL is known to decay over time. The molecular origin of this healing deficiency largely remains elusive but plausibly involves gene transcripts associated with tissue healing. To explore this possibility, we set out to identify transcript expression differences in injured ACL remnants recovered at the time of surgical reconstruction, via microarray (n=24) and RNA-seq (n=8) technologies in transcriptome profiling. We found that time-from-injury was an important determinant of changes in gene expression signatures predominately resulting in repression of several biological processes as identified by gene ontology. The most interesting observation was a time-dependent decline in the gene transcripts as well as the biological processes common to both microarray and RNA-seq analyses. Compared to acute tears, in chronic several important biological processes were namely extracellular matrix organization, angiogenesis, cell adhesion, wound healing, mesenchyme transition, and response to hypoxia. Furthermore, the cross-platform concordance in terms of differentially expressed transcripts or enriched pathways was linearly correlated (r=0.64). Microfluidic digital PCR confirmed the expression of selected differentially expressed transcripts. These intriguing findings suggest an initial attempt of the injured ACL to repair, which drops with time. These findings have implications for efforts to repair the ACL and may be relevant for its reconstruction. These findings also emphasize the utility of differentially expressed transcripts as prognostic biomarkers in patients with ACL injury. Overall design: Examination of transcript expression differences by time-from-injury in anterior cruciate ligament

Publication Title

Advantages of RNA-seq compared to RNA microarrays for transcriptome profiling of anterior cruciate ligament tears.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE6120
CTNNB1 mutations and overexpression of Wnt/beta-catenin target genes in WT1-mutant Wilms' tumors
  • organism-icon Homo sapiens
  • sample-icon 39 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U95A Array (hgu95a)

Description

Gain-of-function mutations in exon 3 of beta-catenin (CTNNB1) are specific for Wilms' tumors that have lost WT1, but 50% of WT1-mutant cases lack such "hot spot" mutations. To ask whether stabilization of beta-catenin might be essential after WT1 loss, and to identify downstream target genes, we compared expression profiles in WT1-mutant versus WT1 wild-type Wilms' tumors. Supervised and nonsupervised hierarchical clustering of the expression data separated these two classes of Wilms' tumor. The WT1-mutant tumors overexpressed genes encoding myogenic and other transcription factors (MOX2, LBX1, SIM2), signaling molecules (TGFB2, FST, BMP2A), extracellular Wnt inhibitors (WIF1, SFRP4), and known beta-catenin/TCF targets (FST, CSPG2, CMYC). Beta-Catenin/TCF target genes were overexpressed in the WT1-mutant tumors even in the absence of CTNNB1 exon 3 mutations, and complete sequencing revealed gain-of-function mutations elsewhere in the CTNNB1 gene in some of these tumors, increasing the overall mutation frequency to 75%. Lastly, we identified and validated a novel direct beta-catenin target gene, GAD1, among the WT1-mutant signature genes. These data highlight two molecular classes of Wilms' tumor, and indicate strong selection for stabilization of beta-catenin in the WT1-mutant class. Beta-Catenin stabilization can initiate tumorigenesis in other systems, and this mechanism is likely critical in tumor formation after loss of WT1.

Publication Title

CTNNB1 mutations and overexpression of Wnt/beta-catenin target genes in WT1-mutant Wilms' tumors.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon SRP150077
Transcriptional dysregulation in a primary cortical neuron model of Huntington''s disease
  • organism-icon Mus musculus
  • sample-icon 24 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Transcriptional dysregulation in a primary cortical neuron model of Huntington''s disease Overall design: RNA-seq of primary cortical neurons transduced with control vector, wildtype Htt or Mutant Htt.

Publication Title

The role of Twist1 in mutant huntingtin-induced transcriptional alterations and neurotoxicity.

Sample Metadata Fields

Cell line, Subject

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accession-icon GSE66649
Multi-platform assessment of transcriptional profiling technologies utilizing a precise probe mapping methodology
  • organism-icon Homo sapiens
  • sample-icon 28 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Transcriptome Array 2.0 (hta20), Agilent-014850 Whole Human Genome Microarray 4x44K G4112F (Feature Number version), Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Multi-platform assessment of transcriptional profiling technologies utilizing a precise probe mapping methodology.

Sample Metadata Fields

Specimen part, Disease

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accession-icon GSE66628
Multi-platform assessment of transcriptional profiling technologies utilizing a precise probe mapping methodology (Affymetrix_Gene1.0) (exon analysis)
  • organism-icon Homo sapiens
  • sample-icon 19 Downloadable Samples
  • Technology Badge IconAgilent-014850 Whole Human Genome Microarray 4x44K G4112F (Feature Number version), Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

We present a more extensive and yet precise assessment to elucidate differences and similarities in performance at numerous aspects including signal range, sensitivity to fold-change, and fidelity with TaqMan qRT-PCR. There were three levels of data examined: entire data sets, data derived from gene name annotation oriented subset of 15442 RefSeq genes, and data derived from transcript pattern defined subset of 7034 RefSeq genes. Our results showed a fair degree of overall correlation between all 6 platforms evaluated; but, to varying degrees, two RNA-seq protocols outperformed three of the microarray platforms in most categories. Notably, a fourth microarray platform, Agilent, was comparable, or marginally superior, to the RNA-seq protocols within these same assessments. Furthermore, 3 platforms (Agilent and two RNA-seq methods) demonstrated over 80% concordance with the gold standard TaqMan assay in terms of fold-change accuracy. Our study suggests that the use of transcript patterns can enhance a number of the observed cross-platform correlations, indicating a potential usefulness for similar evaluations.

Publication Title

Multi-platform assessment of transcriptional profiling technologies utilizing a precise probe mapping methodology.

Sample Metadata Fields

Disease

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accession-icon GSE66648
Multi-platform assessment of transcriptional profiling technologies utilizing a precise probe mapping methodology (Affymetrix_HTA2.0)
  • organism-icon Homo sapiens
  • sample-icon 9 Downloadable Samples
  • Technology Badge IconAgilent-014850 Whole Human Genome Microarray 4x44K G4112F (Feature Number version), Affymetrix Human Transcriptome Array 2.0 (hta20)

Description

We present a more extensive and yet precise assessment to elucidate differences and similarities in performance at numerous aspects including signal range, sensitivity to fold-change, and fidelity with TaqMan qRT-PCR. There were three levels of data examined: entire data sets, data derived from gene name annotation oriented subset of 15442 RefSeq genes, and data derived from transcript pattern defined subset of 7034 RefSeq genes. Our results showed a fair degree of overall correlation between all 6 platforms evaluated; but, to varying degrees, two RNA-seq protocols outperformed three of the microarray platforms in most categories. Notably, a fourth microarray platform, Agilent, was comparable, or marginally superior, to the RNA-seq protocols within these same assessments. Furthermore, 3 platforms (Agilent and two RNA-seq methods) demonstrated over 80% concordance with the gold standard TaqMan assay in terms of fold-change accuracy. Our study suggests that the use of transcript patterns can enhance a number of the observed cross-platform correlations, indicating a potential usefulness for similar evaluations.

Publication Title

Multi-platform assessment of transcriptional profiling technologies utilizing a precise probe mapping methodology.

Sample Metadata Fields

Disease

View Samples
accession-icon SRP055917
Multi-platform assessment of transcriptional profiling technologies utilizing a precise probe mapping methodology (RNA-seq_ClonTech)
  • organism-icon Homo sapiens
  • sample-icon 5 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2500

Description

We present a more extensive and yet precise assessment to elucidate differences and similarities in performance at numerous aspects including signal range, sensitivity to fold-change, and fidelity with TaqMan qRT-PCR. There were three levels of data examined: entire data sets, data derived from gene name annotation oriented subset of 15442 RefSeq genes, and data derived from transcript pattern defined subset of 7034 RefSeq genes. Our results showed a fair degree of overall correlation between all 6 platforms evaluated; but, to varying degrees, two RNA-seq protocols outperformed three of the microarray platforms in most categories. Notably, a fourth microarray platform, Agilent, was comparable, or marginally superior, to the RNA-seq protocols within these same assessments. Furthermore, 3 platforms (Agilent and two RNA-seq methods) demonstrated over 80% concordance with the gold standard TaqMan assay in terms of fold-change accuracy. Our study suggests that the use of transcript patterns can enhance a number of the observed cross-platform correlations, indicating a potential usefulness for similar evaluations. Overall design: The study assessed differences and similarities in performance at numerous aspects including signal range, sensitivity to fold-change, and fidelity with TaqMan qRT-PCR. There were three levels of data examined: entire data sets, data derived from gene name annotation oriented subset of 15442 RefSeq genes, and data derived from transcript pattern defined subset of 7034 RefSeq genes.

Publication Title

Multi-platform assessment of transcriptional profiling technologies utilizing a precise probe mapping methodology.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon SRP055916
Multi-platform assessment of transcriptional profiling technologies utilizing a precise probe mapping methodology (RNA-seq_RiboZero)
  • organism-icon Homo sapiens
  • sample-icon 5 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2500

Description

We present a more extensive and yet precise assessment to elucidate differences and similarities in performance at numerous aspects including signal range, sensitivity to fold-change, and fidelity with TaqMan qRT-PCR. There were three levels of data examined: entire data sets, data derived from gene name annotation oriented subset of 15442 RefSeq genes, and data derived from transcript pattern defined subset of 7034 RefSeq genes. Our results showed a fair degree of overall correlation between all 6 platforms evaluated; but, to varying degrees, two RNA-seq protocols outperformed three of the microarray platforms in most categories. Notably, a fourth microarray platform, Agilent, was comparable, or marginally superior, to the RNA-seq protocols within these same assessments. Furthermore, 3 platforms (Agilent and two RNA-seq methods) demonstrated over 80% concordance with the gold standard TaqMan assay in terms of fold-change accuracy. Our study suggests that the use of transcript patterns can enhance a number of the observed cross-platform correlations, indicating a potential usefulness for similar evaluations. Overall design: The study assessed differences and similarities in performance at numerous aspects including signal range, sensitivity to fold-change, and fidelity with TaqMan qRT-PCR. There were three levels of data examined: entire data sets, data derived from gene name annotation oriented subset of 15442 RefSeq genes, and data derived from transcript pattern defined subset of 7034 RefSeq genes.

Publication Title

Multi-platform assessment of transcriptional profiling technologies utilizing a precise probe mapping methodology.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon SRP124524
Transcriptome analysis of C. elegans embryos lacking ADARs and the 26G pathway
  • organism-icon Caenorhabditis elegans
  • sample-icon 24 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Adenosine deaminases that act on RNA (ADARs) catalyze the conversion of adenosine to inosine in dsRNA. C. elegans ADARs, ADR-1 and ADR-2, promote the expression of genes containing dsRNA structures by preventing their processing into siRNAs and silencing by RNAi. The 26G endogenous siRNA (endo-siRNA) pathway generates a subset of siRNAs distinct from those made in adr-1;adr-2 mutants, but using many of the same factors. We found that adr-1;adr-2;rrf-3 mutants, lacking both ADARs and the RNA-dependent RNA polymerase RRF-3 required for the 26G pathway, display a bursting phenotype rescued by the RNAi factors RDE-1 and RDE-4. To determine what gene expression changes underlie the synthetic phenotype of adr-1;adr-2;rrf-3 mutants, we sequenced poly(A)+ RNA from adr-1;adr-2;rrf-3 embryos, their parent strains, and strains rescued with mutations in rde-1 and rde-4. We found that genes associated with edited structures were robustly downregulated in adr-1;adr-2;rrf-3 mutants in a manner partially dependent on rde-1 and rde-4. Additionally, genes induced during Orsay virus infections were induced in rrf-3 mutants and further upregulated in adr-1;adr-2;rrf-3 mutants, again dependent in part on rde-1 and rde-4. Overall design: RNAseq of poly(A)+ RNA from C.elegans mixed-stage embryos, four biological replicates per genotype, six genotypes: wildtype (Bristol N2), adr-1(uu49);adr-2(uu28), rrf-3(uu56), adr-1(uu49);adr-2(uu28);rrf-3(uu56), adr-1(uu49);adr-2(uu28);rrf-3(uu56);rde-1(uu51), and adr-1(uu49);adr-2(uu28);rrf-3(uu56);rde-4(uu53).

Publication Title

<i>C. elegans</i> ADARs antagonize silencing of cellular dsRNAs by the antiviral RNAi pathway.

Sample Metadata Fields

Subject

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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)

fund-icon Fund the CCDL

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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