We investigated the effects of diabetes, physical training, and their combination on the gene expression of cardiac muscle. Mice were divided to control (C), training (T), streptozotocin-induced diabetic (D), and diabetic training (DT) groups. Training groups performed 1, 3, or 5 weeks of endurance training on a motor-driven treadmill. Muscle samples from T and DT groups together with respective controls were collected 24 hours after the last training session. Gene expression of cardiac muscles were analyzed using Affymetrix Gene chip MG U74Av2 (Affymetrix , Inc., Santa Clara, CA).
Effects of streptozotocin-induced diabetes and physical training on gene expression of titin-based stretch-sensing complexes in mouse striated muscle.
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Effects of streptozotocin-induced diabetes and physical training on gene expression of extracellular matrix proteins in mouse skeletal muscle.
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View SamplesWe show that Bmx-deficiency reduces angiotensin II -induced cardiac hypertrophy and pathological gene expression
Endothelial Bmx tyrosine kinase activity is essential for myocardial hypertrophy and remodeling.
Sex
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VEGF-B-induced vascular growth leads to metabolic reprogramming and ischemia resistance in the heart.
Sex, Age, Specimen part
View SamplesWe show that an excess of VEGF-B protects the heart via adaptive cardiac hypertrophy and increased coronary arterial reserve, and by inducing a shift from lipid to glucose metabolism.
VEGF-B-induced vascular growth leads to metabolic reprogramming and ischemia resistance in the heart.
Sex, Age, Specimen part
View SamplesThis SuperSeries is composed of the SubSeries listed below.
Genome-wide screen of cell-cycle regulators in normal and tumor cells identifies a differential response to nucleosome depletion.
Specimen part, Cell line
View SamplesGene-expression in siRNA treated U2OS and hTERT-RPE1 cells showed that CASP8AP2, NPAT and HINFP do not regulate expression of each other, and do not have any common target genes, except histones. Most histone genes are downregulated in U2OS cells following loss of CASP8AP2, NPAT or HINFP. In normal cells, highly-expressed histone genes were downregulated, albeit less than in tumor cells following loss of CASP8AP2. The p53 target genes were upregulated relatively late, clearly after the changes in expression of histone genes were observed.
Genome-wide screen of cell-cycle regulators in normal and tumor cells identifies a differential response to nucleosome depletion.
Cell line
View SamplesThe tumor suppressor p53 can induce various biological responses. Yet it is not clear whether it is p53 in vivo promoter selectivity that triggers different transcription programs leading to different outcomes. Our analysis of genome-wide chromatin occupancy by p53 using ChIP-seq (deposited in Sequence Read Archive database as SRP007261) revealed p53 default program, i.e. the pattern of major p53-bound sites that is similar upon p53 activation by nutlin3a, RITA or 5-FU in breast cancer cells, despite different biological outcomes triggered by these compounds. Parallel analysis of gene expression allowed identification of 280 previously unknown p53 target genes, including p53-repressed AURKA. The consensus p53 binding motif was present more frequently in p53-induced, than in repressed targets, indicating different mechanisms of gene activation versus repression. We identified several possible cofactors of p53, and found that STAT3 antagonised p53-mediated repression of a subset of genes, including AURKA. Finally, we showed that the expression of the novel p53 targets correlates with p53 status and survival in breast cancer patients.
Insights into p53 transcriptional function via genome-wide chromatin occupancy and gene expression analysis.
Cell line, Treatment
View SamplesComparison of acetylcholine receptor immunization between RIIIS/J and B10.RIII mice.
Periodic gene expression program of the fission yeast cell cycle.
Specimen part
View SamplesCell-penetrating peptides (CPP) uptake mechanism is still to be clarified to have a better understanding of their action in the mediation of oligonucleotide transfection. In this study, the effect on early events (1 h treatment) in transfection by Pepfect 14, with or without oligonucleotide cargo on gene expression, on HeLa cells, have been investigated. The RNA expression was characterized by RNA sequencing. Overall design: The quality of purified total RNA was estimated by Agilent 2200 TapeStation analysis (Agilent Technologies, Santa Clara, USA). One µg of total RNA was used as an input to prepare next-generation sequencing libraries according to the Illumina TruSeq Stranded mRNA sample preparation protocol (Illumina, San Diego, USA). Final library mixtures were quantified by Qubit 2.0 Fluorometer (Life Technologies, Grand Island, USA) and validated with Agilent 2200 TapeStation analysis. Libraries were quantified by qPCR with Kapa Library Quantification Kit (Kapa Biosystems, Woburn, USA) to optimize cluster generation and sequenced on HiSeq2500 platform (Illumina, San Diego, USA) with 2 x 50 bp paired-end reads. Over 93.9% of the bases sequenced were above the quality of Q30. Demultiplexing was done with CASAVA 1.8.2. (Illumina, San Diego, USA) Allowing one mismatch in 6 bp index read. Initial data analysis was conducted by the RNA-Seq pipeline of Estonian Genome Centre, University of Tartu. Shortly, fastQ files were trimmed (removal of adapter sequences and bases below the quality Q20) with FASTX-Toolkit version 0.013 (http://hannonlab.cshl.edu/fastx_toolkit) and then aligned to the human reference genome (hg19/GRCh37) with Bowtie version 2.1.019 in combination with TopHat version 2.0.1320. Transcript quantification (measured as FPKM) was conducted with Cuffdiff program from Cufflinks version 2.2.121 with reference annotation Homo_sapiens.GRCh37.72.gtf (http://ftp.ensembl.org/pub/release-72/gtf/homo_sapiens) Cuffdiff analysis, which summarizes expression changes for all annotated gene variations, was filtered by lowest q-values (corrected p-values for multiple testing) from output file gene_exp.diff and the top list of differentially expressed genes were analyzed through the use of QIAGEN’s Ingenuity® Pathway Analysis (IPA®, QIAGEN Redwood City, www.qiagen.com/ingenuity).
Role of autophagy in cell-penetrating peptide transfection model.
Cell line, Treatment, Subject
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