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GSE35480
Homo sapiens
9 Downloadable Samples
Affymetrix Human Exon 1.0 ST Array [transcript (gene) version (huex10st)
Description
Alternative mRNA splicing is the main reason vast mammalian proteomic complexity can be achieved with a limited number of genes. Splicing is physically and functionally coupled to transcription and the rate of transcript elongation has a profound effect on splicing. As the nascent pre-mRNA emerges from transcribing RNA polymerase II (RNAPII), it is assembled into a messenger ribonucleoprotein (mRNP) particle that represents its functional form, and the composition of which determines the fate of the mature transcript4. However, factors that connect the transcribing polymerase with the mRNP particle and help integrate transcript elongation with mRNA splicing remain obscure. Here, we characterized the interactome of chromatin-associated mRNP particles and thereby identified Deleted in Breast Cancer 1 (DBC1) and a protein we named ZIRD. These proteins are subunits of a novel protein complex, named DBIRD, which binds directly to RNAPII. DBIRD regulates alternative splicing of a large set of exons embedded in A/T-rich DNA, and is present at the affected exons. RNAi-mediated DBIRD depletion results in region-specific decreases in transcript elongation, particularly across areas encompassing affected exons. These data indicate that DBIRD complex acts at the interface between mRNP particles and RNAPII, integrating transcript elongation with regulation of alternative splicing.
Publication Title
DBIRD complex integrates alternative mRNA splicing with RNA polymerase II transcript elongation.
Sample Metadata Fields
Cell line
View Samples- Homo sapiens
- 6 Downloadable Samples
- Affymetrix Human Genome U133A 2.0 Array (hgu133a2)
Description
Constitutive activation of EGFR- and NF-kB-dependent pathways is a hallmark of cancer, yet signaling proteins that connect both oncogenic cascades are poorly characterized. Here we define KIAA1199 as a BCL-3- and p65-dependent gene in transformed keratinocytes. KIAA1199 expression is enhanced upon human papillomavirus (HPV) infection and is aberrantly expressed in clinical cases of cervical (pre)neoplastic lesions. Mechanistically, KIAA1199 binds Plexin A2 and protects from Semaphorin 3A-mediated cell death by promoting EGFR stability and signaling. Moreover, KIAA1199 is an EGFR-binding protein and KIAA1199 deficiency impairs EGF-dependent Src, MEK1 and ERK1/2 phosphorylations. Therefore, EGFR stability and signaling to downstream kinases requires KIAA1199. As such, KIAA1199 promotes EGF-mediated epithelial-mesenchymal transition (EMT). Taken together, our data define KIAA1199 as an oncogenic protein induced by HPV infection and constitutive NF-kB activity that transmits pro-survival and invasive signals through EGFR signaling.
Publication Title
NF-κB-induced KIAA1199 promotes survival through EGFR signalling.
Sample Metadata Fields
Specimen part, Cell line, Treatment
View Samples- Mus musculus
- 1 Downloadable Sample
- Affymetrix Mouse Genome 430A 2.0 Array (mouse430a2)
Description
Effect of Irf3 deficiency on the response of inflammatory monocytes to immunization with the alum adjuvant
Publication Title
No associated publication
Sample Metadata Fields
Sex, Age, Specimen part
View Samples- Homo sapiens
- 2886 Downloadable Samples
- Affymetrix Human Genome U133A 2.0 Array (hgu133a2)
Description
Consider the problem of designing a panel of complex biomarkers to predict a patient's health or disease state when one can pair his or her current test sample, called a target sample, with the patient's previously acquired healthy sample, called a reference sample. As contrasted to a population averaged reference, this reference sample is individualized. Automated predictor algorithms that compare and contrast the paired samples to each other could result in a new generation of test panels that compare to a person's healthy reference to enhance predictive accuracy. This study develops such an individualized predictor and illustrates the added value of including the healthy reference for design of predictive gene expression panels. The objective is to predict each subject's state of infection, e.g., neither exposed nor infected, exposed but not infected, pre-acute phase of infection, acute phase of infection, post-acute phase of infection. Using gene microarray data collected in a large-scale serially sampled respiratory virus challenge study, we quantify the diagnostic advantage of pairing a person's baseline reference with his or her target sample.
Publication Title
An individualized predictor of health and disease using paired reference and target samples.
Sample Metadata Fields
Specimen part, Subject, Time
View Samples- Homo sapiens
- 711 Downloadable Samples
- Affymetrix Human Transcriptome Array 2.0 (hta20)
Description
African-American individuals of the GENOA cohort
Publication Title
Genetic Architecture of Gene Expression in European and African Americans: An eQTL Mapping Study in GENOA.
Sample Metadata Fields
Sex, Age, Specimen part
View Samples- Homo sapiens
- 97 Downloadable Samples
- Affymetrix Human Exon 1.0 ST Array [probe set (exon) version (huex10st)
Description
The NIH Roadmap Epigenomics Mapping Consortium aims to produce a public resource of epigenomic maps for stem cells and primary ex vivo tissues selected to represent the normal counterparts of tissues and organ systems frequently involved in human disease.
Publication Title
The NIH Roadmap Epigenomics Mapping Consortium.
Sample Metadata Fields
Sex, Specimen part, Disease, Subject
View Samples- Homo sapiens
- 724 Downloadable Samples
Illumina human-6 v2.0 expression beadchip, Affymetrix Human Genome U219 Array (hgu219)
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
Innate immune activity is detected prior to seroconversion in children with HLA-conferred type 1 diabetes susceptibility.
Sample Metadata Fields
Sex, Specimen part
View Samples- Homo sapiens
- 667 Downloadable Samples
- Affymetrix Human Genome U133A Array (hgu133a)
Description
A cardinal symptom of Major Depressive Disorder (MDD) is the disruption of circadian patterns. Yet, to date, there is no direct evidence of circadian clock dysregulation in the brains of MDD patients. Circadian rhythmicity of gene expression has been observed in animals and peripheral human tissues, but its presence and variability in the human brain was difficult to characterize. Here we applied time-of-death analysis to gene expression data from high-quality postmortem brains, examining 24-hour cyclic patterns in six cortical and limbic regions of 55 subjects with no history of psychiatric or neurological illnesses ('Controls') and 34 MDD patients. Our dataset covered ~12,000 transcripts in the dorsolateral prefrontal cortex (DLPFC), anterior cingulate cortex (AnCg), hippocampus (HC), amygdala (AMY), nucleus accumbens (NAcc) and cerebellum (CB). Several hundred transcripts in each region showed 24-hour cyclic patterns in Controls, and >100 transcripts exhibited consistent rhythmicity and phase-synchrony across regions. Among the top ranked rhythmic genes were the canonical clock genes BMAL1(ARNTL), PER1-2-3, NR1D1(REV-ERB), DBP, BHLHE40(DEC1), and BHLHE41(DEC2). The phasing of known circadian genes was consistent with data derived from other diurnal mammals. Cyclic patterns were much weaker in MDD brains, due to shifted peak timing and potentially disrupted phase relationships between individual circadian genes. This is the first transcriptome-wide analysis of cyclic patterns in the human brain and demonstrates a rhythmic rise and fall of gene expression in regions outside of the suprachiasmatic nucleus in control subjects. The description of its breakdown in MDD suggest novel molecular targets for treatment of mood disorders.
Publication Title
Circadian patterns of gene expression in the human brain and disruption in major depressive disorder.
Sample Metadata Fields
Subject
View Samples- Homo sapiens
- 419 Downloadable Samples
- Affymetrix Human Gene 1.1 ST Array (hugene11st)
Description
With aging, significant changes in circadian rhythms occur, including a shift in phase toward a morning chronotype and a loss of rhythmicity in circulating hormones. However, the effects of aging on molecular rhythms in the human brain have remained elusive. Here we employed a previously-described time-of-death analyses to identify transcripts throughout the genome that have a significant circadian rhythm in expression in the human prefrontal cortex (Brodmanns areas (BA) 11 and 47). Expression levels were determined by microarray analysis in 146 individuals. Rhythmicity in expression was found in ~10% of detected transcripts (p<0.05). Using a meta-analysis across the two brain areas, we identified a core set of 235 genes (q<0.05) with significant circadian rhythms of expression. These 235 genes showed 92% concordance in the phase of expression between the two areas. In addition to the canonical core circadian genes, a number of other genes were found to exhibit rhythmic expression in the brain. Notably, we identified more than one thousand genes (1186 in BA11; 1591 in BA47) that exhibited age-dependent rhythmicity or alterations in rhythmicity patterns with aging. Interestingly, a set of transcripts gained rhythmicity in older individuals, which may represent a compensatory mechanism due to a loss of canonical clock function. Thus, we confirm that rhythmic gene expression can be reliably measured in human brain and identified for the first time significant changes in molecular rhythms with aging that may contribute to altered cognition, sleep and mood in later life.
Publication Title
Effects of aging on circadian patterns of gene expression in the human prefrontal cortex.
Sample Metadata Fields
Sex, Age, Specimen part, Race
View Samples- Homo sapiens
- 391 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
Histologic diagnosis of T cell-mediated rejection in kidney transplant biopsies has limited reproducibility because it is based on non-specific lesions using arbitrary rules that are subject to differing interpretations. We used microarray results from 403 indication biopsies previously given histologic diagnoses to develop a molecular classifier that assigned a molecular T cell-mediated rejection score to each biopsy. Independent assessment of the biopsies by multiple pathologists confirmed considerable disagreement on the presence of TCMR features: 79-88% accuracy and 35-69% sensitivity. The agreement of the molecular T cell-mediated rejection score with the histology diagnosis was similar to agreement among individual pathologists: accuracy 89%, sensitivity 51%. However, the score also predicted the consensus among pathologists, being highest when all agreed. Many discrepancies between the scores and the histologic diagnoses were in situations where histology is unreliable e.g. scarred biopsies. The score correlated with histologic lesions and gene sets associated with T cell-mediated rejection. The transcripts most often selected by the classifier were expressed in effector T cells, dendritic cells, or macrophages or inducible by interferon-gamma. Thus the T cell-mediated rejection score offers an objective assessment of kidney transplant biopsies, predicting the consensus opinion among multiple pathologists, and offering insights into underlying disease mechanisms.
Publication Title
Molecular diagnosis of T cell-mediated rejection in human kidney transplant biopsies.
Sample Metadata Fields
Disease
View Samples