This SuperSeries is composed of the SubSeries listed below.
Integrative miRNA and whole-genome analyses of epicardial adipose tissue in patients with coronary atherosclerosis.
Age, Specimen part, Disease, Disease stage
View SamplesGene expression profiles of Human EAT vs. SAT (CTRL & CAD). The aim of the present study was to assess a gene expression chart characterizing EAT vs. SAT, and CAD vs. CTRL. Results provide the information that EAT is characterized by a differential expression of different genes when compared to its reference tissue (SAT), and that EAT is characterized by specific gene expression changes in patients with CAD.
Integrative miRNA and whole-genome analyses of epicardial adipose tissue in patients with coronary atherosclerosis.
Age, Specimen part, Disease, Disease stage
View SamplesThis SuperSeries is composed of the SubSeries listed below.
Enhanced stability of microRNA expression facilitates classification of FFPE tumour samples exhibiting near total mRNA degradation.
Specimen part, Cell line
View SamplesReprogramming of somatic cells produces induced pluripotent stem cells (iPSCs) that are invaluable resources for biomedical research. Transcriptional and epigenetic changes have been investigated to facilitate our understanding of the reprogramming process. Here, we extended the previous transcriptome studies by performing RNA-seq on cells defined by a combination of multiple cellular surface markers. We found that transcriptome changes during early reprogramming occur independently from the opening of closed chromatin by OCT4, SOX2, KLF4 and MYC (OSKM). Furthermore, our data identify multiple spliced forms of genes uniquely expressed at each progressive stage of reprogramming. In particular, we found a pluripotency-specific spliced form of CCNE1 that significantly enhances reprogramming. In addition, single nucleotide polymorphism (SNP) expression analysis reveals that monoallelic gene expression is induced in the intermediate stages of reprogramming while biallelic expression is recovered upon completion of reprogramming. Our transcriptome data provide unique opportunities in understanding human iPSC reprogramming. Overall design: RNA samples from intermediates of hiPSC reprogramming were obtained. Gene expression of those cells were analyzed.
Transcriptome Signature and Regulation in Human Somatic Cell Reprogramming.
No sample metadata fields
View SamplesMammalian genomes contain numerous DNA elements with potential transcription regulatory function but unknown target genes. We used transgenic, gain-of-function mice with an ectopic copy of the beta-globin locus control region (LCR) to better understand how regulatory elements dynamically search the genome for target genes. We find that the LCR samples a restricted nuclear sub-volume in which it forms preferential contacts with genes controlled by shared transcription factors. One contacted gene, betah1, located on another chromosome, is upregulated, providing genetic demonstration that mammalian enhancers can function between chromosomes. Upregulation is not pan-cellular but confined to selected jackpot cells significantly enriched for inter-chromosomal LCR-betah1 interactions. This implies that long-range DNA contacts are relatively stable and cell-specific and, when functional, cause variegated expression. We refer to this as spatial effect variegation (SEV). The data provide a dynamic and mechanistic framework for enhancer action, important for assigning function to the one- and three-dimensional structure of DNA.
Variegated gene expression caused by cell-specific long-range DNA interactions.
Specimen part, Disease
View SamplesWe have determined the whole genome sequence of an individual at high accuracy and performed an integrated analysis of omics profiles over a 1.5 year period that included healthy and two virally infected states. Omics profiling of transcriptomes, proteomes, cytokines, metabolomes and autoantibodyomes from blood components have revealed extensive, dynamic and broad changes in diverse molecular components and biological pathways that occurred during healthy and disease states. Many changes were associated with allele- and edit-specific expression at the RNA and protein levels, which may contribute to personalized responses. Importantly, genomic information was also used to predict medical risks, including Type II Diabetes (T2D), whose onset was observed during the course of our study using standard clinical tests and molecular profiles, and whose disease progression was monitored and subsequently partially managed. Our study demonstrates that longitudinal personal omics profiling can relate genomic information to global functional omics activity for physiological and medical interpretation of healthy and disease states. Overall design: Examination of blood component in 20 different time points over 1.5 years which includes 2 disease state and 18 healty state Related exome studies at: SRX083314 SRX083313 SRX083312 SRX083311
Personal omics profiling reveals dynamic molecular and medical phenotypes.
Specimen part, Disease, Subject
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