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DRP004758
Danio rerio
12 Downloadable Samples
Illumina HiSeq 2500
Description
Two essential processes, oocyte maturation and ovulation, before oocytes become fertilizable that are independently induced but co-operatively proceeded at the final step in oogenesis. Eventhough these two processes are induced by same maturation-inducing steroid, 17, 20 beta-dihydroxy-4-pregnen-3-one (17, 20 beta-DHP), in teleost, the receptor for each pathway is suggested to be different and thus signal transduction pathways are different. While much progresses achieved on the molecular mechanisms for induction of oocyte maturation, the mechanisms to induce ovulation is under elucidation. Previously we established the procedure that can make it possible to prepare the ovarian tissue which contains oocyte maturation-induced oocytes in vivo. In the same way, ovulation can be induced in alive zebrafish. Thus it became possible to select the genes up-regulated according to ovulation by compare the gene expression between maturation-inducing genes in matured oocytes and both maturation and ovulation-inducing genes in ovulated eggs. In vivo bioassay has been applied to prepare maturated and ovulated ovarian samples. Specifically up-regulated genes to induce ovulation will be selected by RNA-seq analysis. The mRNA abundance of highly up-regulated genes will be confirmed by q-PCR analysis. By this project, ovulation-inducing genes will be selected and its roles in induction of ovulation will be addressed in the future.
Publication Title
No associated publication
Sample Metadata Fields
No sample metadata fields
View Samples- Danio rerio
- 10 Downloadable Samples
- Illumina HiSeq 2500
Description
To identify ovulation-inducing genes, RNAseq analysis was carried out using samples prepared by in vivo assay system in zebrafish.
Publication Title
No associated publication
Sample Metadata Fields
Specimen part, Cell line
View Samples- Mus musculus
- 2 Downloadable Samples
Affymetrix Mouse Genome 430 2.0 Array (mouse4302)
Description
Expression profile of liver of ICR mice (13-week old) treated with control diet (CRF-1) or CRF-1 containing 500 ppm diosgenin for 4 weeks.
Publication Title
No associated publication
Sample Metadata Fields
Specimen part, Treatment
View Samples- Homo sapiens
- 2 Downloadable Samples
- Affymetrix Human Exon 1.0 ST Array [probe set (exon) version (huex10st)
Description
Analysis to find splicing variants that are differentially expressed in a highly metastatic stomach cancer cell line, MKN45P, versus its parental cell line, MKN45
Publication Title
Identification of a novel protein isoform derived from cancer-related splicing variants using combined analysis of transcriptome and proteome.
Sample Metadata Fields
Specimen part, Cell line
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