Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Transcription profiling of vastus lateralis muscle from healthy young (21-31 year old) and older (62-77 year old) men

ABSTRACT: RNA from vastus lateralis of healthy young (21-31 year old) and older (62-77 year old) men. Signal data normalized to mean intensity of 500 over all probes sets. Analysis done with Affymetrix Microarray Suite 5.0 software.

ORGANISM(S): Homo sapiens

SUBMITTER: Stephen Welle

PROVIDER: E-GEOD-80 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Publications

Computational method for reducing variance with Affymetrix microarrays.

Welle Stephen S Brooks Andrew I AI Thornton Charles A CA

BMC bioinformatics 20020830

<h4>Background</h4>Affymetrix microarrays are used by many laboratories to generate gene expression profiles. Generally, only large differences (> 1.7-fold) between conditions have been reported. Computational methods to reduce inter-array variability might be of value when attempting to detect smaller differences. We examined whether inter-array variability could be reduced by using data based on the Affymetrix algorithm for pairwise comparisons between arrays (ratio method) rather than data ba ...[more]

PMID: 12204100

Similar Datasets

Project description:This study was undertaken to test the hypothesis that short term exposure (4 hours) to physiologic hyperinsulinemia in normal, healthy subjects without a family history of diabetes would induce a low grade inflammatory response, independently of glycemic status. We performed euglycemic hyperinsulinemic (80 mU/m2/min) clamps in 12 healthy, insulin sensitive subjects with no family history of diabetes followed by biopsies of the vastus lateralis muscle taken basally and after 30 and 240 minutes of insulin infusion. Gene expression profiles were generated using Affymetrix HG-U133A arrays. No probe sets had significantly altered expression at 30 minutes of the insulin clamp, but 121 probe sets (117 upregulated and 4 downregulated) were significantly altered after 240 minutes. Hyperinsulinemia in normal, healthy human subjects increased the mRNAs for a number of inflammatory genes and transcription factors. Microarray and quantitative RT-PCR revealed the upregulation of chemokine, cc motif, ligand 2 (CCL2), CCL8, thrombomodulin (THBD), ras-related associated with diabetes (RRAD), metallothionein (MT), and serum/glucocorticoid regulated kinase (SGK), and downregulation of CITED2 (a CREB-binding protein-interacting transactivator), a known coactivator of PPAR-alpha. Interestingly, SGK and CITED2 are located at chromosome 6q23, where we previously detected strong linkage to hyperinsulinemia. A control saline infusion performed on 3 normal, healthy subjects without a family history of diabetes demonstrated that the genes altered following the euglycemic-hyperinsulinemic clamp were due to insulin and independent of biopsy removal. This study demonstrates that insulin acutely regulates the expression of genes involved in inflammation and transcription, and identifies several candidate genes/pathways for further investigation. Experiment Overall Design: Twelve subjects received a vastus lateralis muscle biopsy followed by a 180-min euglycemic, hyperinsulinemic (80 mU/m2.min) clamp. Muscle biopsies from each subject were homogenized in RNAStat solution (Tel-Test Inc., Friendswood, TX), using a Polytron homogenizer (Brinkmann Instruments Westbury, NY). Total RNA was purified with RNeasy and DNase I treatment (Qiagen, Chatsworth, CA). RNA was prepared for hybridization to Affymetrix (Santa Clara, CA) HG-U133A arrays according to the manufacturerâs instructions.

Project description:Sulfur mustard (SM) is a potent alkylating agent. We are developing medical countermeasures to reduce the injury caused by SM exposure. Screening in the mouse ear vesicant model has identified three effective compounds: dimercaprol (British anti-lewisite), indomethacin, and octyl homovanillamide (OHV). To identify gene expression changes that correlate with compound efficacy we used oligonucleotide microarrays to compare gene expression profiles in vehicle-exposed skin, SM-exposed skin, and skin pretreated with each compound before SM exposure. Mice were topically exposed on the inner surface of the right ear to SM alone or pretreated for 15 min with one of the compounds and then exposed to SM. Left ears were vehicle-exposed. Ear tissue was harvested 24 hr later for ear weight determination (an endpoint indicating compound efficacy). The exposure groups were: methylene chloride (sulfur mustard vehicle); ethanol (drug vehicle); 0.08 mg sulfur mustard; 6.25 mg dimercaprol 15 min before 0.08 mg sulfur mustard; 1.34 mg indomethacin 15 min before 0.08 mg sulfur mustard; 0.6 mg octylhomovanillamide 15 min before 0.08 mg sulfur mustard; 6.25 mg dimercaprol alone; 1.34 mg indomethacin alone; 0.6 mg octylhomovanillamide alone. RNA was extracted from the tissues and used to generate oligonucleotide microarray probes. Principal component analysis of the gene expression data revealed partitioning of the samples based on drug treatment and SM exposure. Vehicle-exposed mouse ears clustered away from the other treatment groups. SM-exposed mouse ears pretreated with dimercaprol or OHV clustered more closely with vehicle-exposed ears, while SM-exposed mouse ears pretreated with indomethacin clustered more closely with SM-exposed ears. This clustering of the samples is supported by the ear weight data, in which the indomethacin group has ear weights closer to the SM-exposed group, whereas the dimercaprol and OHV groups have ear weights closer to the vehicle-exposed group. Correlation coefficients were calculated for each gene based on the correlation between gene expression level and ear weight. These data provide the basis for understanding what gene expression changes are important in the development of effective SM medical countermeasures. Experiment Overall Design: Exposure of mouse ears to sulfur mustard alone, sulfur mustard preceded by drug treatment, or vehicle compounds. Naive controls were also included. Biological replicates of at least n=3 were examined for each exposure condition.

Project description:Purpose. Insulin resistant muscle is resistant to gene expression changes induced by acute exercise. This study was undertaken to identify transcription factors that differentially respond to exercise in insulin resistance. Candidate transcription factors were identified from analysis of 5’-untranslated regions (5’-UTRs) of exercise responsive genes and from analysis of the 5’-UTRs of genes coding for proteins that differ in abundance in insulin resistance. Research design and methods. Muscle biopsies were obtained from lean and obese subjects before and after a single exercise bout. Euglycemic glucose clamps assessed insulin sensitivity. Global proteomics analysis identified differentially abundant proteins. The 5’-UTRs of genes coding for significant proteins were subjected to transcription factor enrichment analysis to identify candidate transcription factors. Q-rt-PCR to determine expression of candidate transcription factors was performed on RNA from resting and post-exercise muscle biopsies; immunoblots quantified protein abundance. Results. Obese subjects were insulin resistant compared to lean but performed exercise at the same intensity. Proteins involved in mitochondrial function, protein targeting and translation, and metabolism were among those significantly different between the groups. Transcription factor enrichment analysis of genes coding for these proteins revealed new candidate transcription factors. Q-rt-PCR analysis of RNA and immunoblot analysis from pre- and post-exercise muscle biopsies revealed several transcription and growth factors that had altered responses to exercise in insulin resistant subjects. Conclusions. These results confirm findings of an association between insulin sensitivity and transcription factor mRNA response to exercise and extend these results to show that obesity also may be a sufficient prerequisite for exercise resistance. Analysis of the muscle proteome together with determination of effects of exercise on expression of transcription factors suggests that abnormal responses of transcription factors to exercise may be responsible for differences in protein abundances in insulin resistant muscle.

Dataset Information

Transcription profiling of vastus lateralis muscle from healthy young (21-31 year old) and older (62-77 year old) men

Publications

Computational method for reducing variance with Affymetrix microarrays.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets