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accession-icon SRP068468
INTS8 mutations cause severe neurodevelopmental syndrome
  • organism-icon Homo sapiens
  • sample-icon 4 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2000

Description

Integrator (INT) is an RNA polymerase II (RNAPII)-associated complex that was recently identified to have a broad role in both RNA processing and transcription regulation. INT has at least 14 subunits, but INT germline mutations causing human disease have not been reported. We identified mutations in the Integrator Complex Subunit 8 gene (INTS8) causing a rare neurodevelopmental syndrome. In patient cells we identified significant disturbance of gene expression and RNA processing. Also, we show that injection of ints8 oligonucleotide morpholinos into zebrafish embryos leads to prominent underdevelopment of the head demonstrating the evolutionary conserved requirement of INTS8 in brain development. Overall design: RNA sequencing was carried out using RNA samples from fibroblasts from two individuals with germline bi-allelic INTS8 mutations and from two healthy individuals

Publication Title

Human mutations in integrator complex subunits link transcriptome integrity to brain development.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE43952
Integration of Metabolic and Gene Regulatory Networks Modulates The C. elegans Dietary Response
  • organism-icon Caenorhabditis elegans
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix C. elegans Genome Array (celegans)

Description

Analysis of wildtype C. elegans (N2) and pcca-1(ok2282) and metr-1(ok521) mutants fed Comamonas DA1877

Publication Title

Integration of metabolic and gene regulatory networks modulates the C. elegans dietary response.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE87125
Effects of starter microbiota and early life feeding of medium chain triglycerides on the gastric transcriptome profile of 3 weeks old caesarean derived pigs
  • organism-icon Sus scrofa
  • sample-icon 24 Downloadable Samples
  • Technology Badge Icon Porcine Gene 1.1 ST Array (porgene11st)

Description

An early settlement of a complex gut microbiota can protect against gastro-intestinal dysbiosis, but the effects of neonatal microbiota colonization and early life feeding of medium chain triglycerides on the maturation of the porcine gastric mucosa are largely unknown.

Publication Title

The effects of starter microbiota and the early life feeding of medium chain triglycerides on the gastric transcriptome profile of 2- or 3-week-old cesarean delivered piglets.

Sample Metadata Fields

Specimen part

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accession-icon GSE87124
Effects of starter microbiota on the gastric transcriptome profile of 2 weeks old caesarean derived pigs
  • organism-icon Sus scrofa
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Porcine Gene 1.1 ST Array (porgene11st)

Description

An early settlement of a complex gut microbiota can protect against gastro-intestinal dysbiosis, but the effects of neonatal microbiota colonization on the maturation of the porcine gastric mucosa are largely unknown.

Publication Title

The effects of starter microbiota and the early life feeding of medium chain triglycerides on the gastric transcriptome profile of 2- or 3-week-old cesarean delivered piglets.

Sample Metadata Fields

Specimen part

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accession-icon GSE77787
Early microbial colonisation affects transcriptome of pig jejunum perfused with E. coli F4, F4 fimbria or Lact. amylovorus
  • organism-icon Sus scrofa
  • sample-icon 48 Downloadable Samples
  • Technology Badge Icon Porcine Gene 1.1 ST Array (porgene11st)

Description

An early settlement of a complex gut microbiota can protect against gastro-intestinal dysbiosis, but the effects of neonatal microbiota colonization on the gut barrier upon the further encounter of favorable bacteria or not, are largely unknown.

Publication Title

Molecular networks affected by neonatal microbial colonization in porcine jejunum, luminally perfused with enterotoxigenic Escherichia coli, F4ac fimbria or Lactobacillus amylovorus.

Sample Metadata Fields

Specimen part, Treatment

View Samples
accession-icon SRP139927
Transcriptomic analysis of myosin IIa-deficient B cells
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Myosin IIa-deficient follicular B cells have a hyperactivated phenotype. To identify what pathways are regulated by myosin IIa, we performed RNA-seq of coding RNA on flow cytometry sorted follicular B cells from CD23Cre+Myh9fl/fl and CD23Cre+Myh9wt/fl mice. Overall design: B220+AA4.1-CD23+CD21lo follicular B cells were sorted from 3 CD23Cre+Myh9fl/fl and 3 CD23Cre+Myh9wt/fl mice and mRNA was isolated and sequenced.

Publication Title

Myosin IIa Promotes Antibody Responses by Regulating B Cell Activation, Acquisition of Antigen, and Proliferation.

Sample Metadata Fields

Cell line, Subject

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accession-icon SRP015982
Small RNA analysis of Tu And SJD zebrafish strain and their progeny
  • organism-icon Danio rerio
  • sample-icon 20 Downloadable Samples
  • Technology Badge IconIlluminaGenomeAnalyzerIIx

Description

Small RNA libraries from total RNA isolated from adult ovaries Overall design: Small RNA libraries were derived from Ovaries of the Founder strain and their offspring and their reciprocal offspring. RNA from 5 individual ovaries was pooled .

Publication Title

piRNA dynamics in divergent zebrafish strains reveal long-lasting maternal influence on zygotic piRNA profiles.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE99340
Transcriptome-based network analysis reveals renal cell type-specific dysregulation of hypoxia-associated transcripts
  • organism-icon Homo sapiens
  • sample-icon 402 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

Transcriptome-based network analysis reveals renal cell type-specific dysregulation of hypoxia-associated transcripts.

Sample Metadata Fields

Specimen part

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accession-icon GSE99339
Transcriptome-based network analysis reveals renal cell type-specific dysregulation of hypoxia-associated transcripts [glomeruli]
  • organism-icon Homo sapiens
  • sample-icon 187 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Accumulating evidence suggests that dysregulation of hypoxia-regulated transcriptional mechanisms is involved in development of chronic kidney diseases (CKD). However, it remains unclear how hypoxia-induced transcription factors (HIFs) and subsequent biological processes contribute to CKD development and progression. In our study, genome-wide expression profiles of more than 200 renal biopsies from patients with different CKD stages revealed significant correlation of HIF-target genes with eGFR in glomeruli and tubulointerstitium. These correlations were positive and negative and in part compartment-specific. Microarrays of proximal tubular cells and podocytes with stable HIF1 and/or HIF2 suppression displayed cell type-specific HIF1/HIF2-dependencies as well as dysregulation of several pathways. WGCNA analysis identified gene sets that were highly coregulated within modules. Characterization of the modules revealed common as well as cell group- and condition-specific pathways, GO-Terms and transcription factors. Gene expression analysis of the hypoxia-interconnected pathways in patients with different CKD stages revealed an increased dysregulation with loss of renal function. In conclusion, our data clearly point to a compartment- and cell type-specific dysregulation of hypoxia-associated gene transcripts and might help to improve the understanding of hypoxia, HIF dysregulation, and transcriptional program response in CKD.

Publication Title

Transcriptome-based network analysis reveals renal cell type-specific dysregulation of hypoxia-associated transcripts.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE99325
Transcriptome-based network analysis reveals renal cell type-specific dysregulation of hypoxia-associated transcripts [Tub-FE]
  • organism-icon Homo sapiens
  • sample-icon 169 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Accumulating evidence suggests that dysregulation of hypoxia-regulated transcriptional mechanisms is involved in development of chronic kidney diseases (CKD). However, it remains unclear how hypoxia-induced transcription factors (HIFs) and subsequent biological processes contribute to CKD development and progression. In our study, genome-wide expression profiles of more than 200 renal biopsies from patients with different CKD stages revealed significant correlation of HIF-target genes with eGFR in glomeruli and tubulointerstitium. These correlations were positive and negative and in part compartment-specific. Microarrays of proximal tubular cells and podocytes with stable HIF1 and/or HIF2 suppression displayed cell type-specific HIF1/HIF2-dependencies as well as dysregulation of several pathways. WGCNA analysis identified gene sets that were highly coregulated within modules. Characterization of the modules revealed common as well as cell group- and condition-specific pathways, GO-Terms and transcription factors. Gene expression analysis of the hypoxia-interconnected pathways in patients with different CKD stages revealed an increased dysregulation with loss of renal function. In conclusion, our data clearly point to a compartment- and cell type-specific dysregulation of hypoxia-associated gene transcripts and might help to improve the understanding of hypoxia, HIF dysregulation, and transcriptional program response in CKD.

Publication Title

Transcriptome-based network analysis reveals renal cell type-specific dysregulation of hypoxia-associated transcripts.

Sample Metadata Fields

Specimen part

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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