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Genome-wide expression analysis comparing hypertrophic changes in normal and dysferlinopathy mice.

Lee YS, Talbot CC, Lee SJ - Genom Data (2015)

Bottom Line: Because myostatin normally limits skeletal muscle growth, there are extensive efforts to develop myostatin inhibitors for clinical use.Hence, benefits of this approach should be weighed against these potential detrimental effects.Here, we present detailed experimental methods and analysis for the gene expression profiling described in our recently published study in Human Molecular Genetics (Lee et al., 2015).

View Article: PubMed Central - PubMed

Affiliation: Department of Molecular Biology and Genetics, Johns Hopkins University School of Medicine, 725 North Wolfe Street, PCTB 803, Baltimore, MD 21205, USA.

ABSTRACT
Because myostatin normally limits skeletal muscle growth, there are extensive efforts to develop myostatin inhibitors for clinical use. One potential concern is that in muscle degenerative diseases, inducing hypertrophy may increase stress on dystrophic fibers. Our study shows that blocking this pathway in dysferlin deficient mice results in early improvement in histopathology but ultimately accelerates muscle degeneration. Hence, benefits of this approach should be weighed against these potential detrimental effects. Here, we present detailed experimental methods and analysis for the gene expression profiling described in our recently published study in Human Molecular Genetics (Lee et al., 2015). Our data sets have been deposited in the Gene Expression Omnibus (GEO) database (GSE62945) and are available at http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE62945. Our data provide a resource for exploring molecular mechanisms that are related to hypertrophy-induced, accelerated muscular degeneration in dysferlinopathy.

No MeSH data available.


Related in: MedlinePlus

Ingenuity upstream regulator analysis generated signaling-related networks based on published interactions with the top upstream regulator, TGFb1, in F66 mouse muscle (versus wt) based on our experimental results. Red denotes upregulation, and blue denotes downregulation of the gene. The intensity of the gene color indicates the degree of up- or down-regulation. Orange lines indicate positive regulation, in accordance with the published interaction, blue lines indicate negative regulation, and yellow lines denote changes discordant from published expectation. The networks were generated through the use of Ingenuity Pathway Analysis.
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f0015: Ingenuity upstream regulator analysis generated signaling-related networks based on published interactions with the top upstream regulator, TGFb1, in F66 mouse muscle (versus wt) based on our experimental results. Red denotes upregulation, and blue denotes downregulation of the gene. The intensity of the gene color indicates the degree of up- or down-regulation. Orange lines indicate positive regulation, in accordance with the published interaction, blue lines indicate negative regulation, and yellow lines denote changes discordant from published expectation. The networks were generated through the use of Ingenuity Pathway Analysis.

Mentions: Microarray data were visualized by principal components analysis (PCA) mapping, volcano plots, and heat maps [6]. PCA analysis was performed with the Partek platform, while volcano plots and heat maps were generated with the Spotfire DecisionSite software (TIBCO Software Inc., Boston, MA). Linear regression analyses were performed with Spotfire to compare two different sets of transcriptome changes (Fig. 2). Gene Ontology (GO; www.geneontology.org) analysis was conducted for significantly differentially expressed 763 genes (fold change > 2.0, p < 0.01 in wt versus F66;Dysf−/−) using Spotfire's Gene Ontology Browser [7]. Canonical Pathways, Upstream Regulators, and Network analyses were generated using Ingenuity Pathway Analysis (IPA; QIAGEN Redwood City, CA, USA) and summarized in Table 1, Table 2, Table 3. Myostatin is a transforming growth factor-ß (TGF-ß) family member, and as expected, TGF-ß1 was a top upstream regulator in F66 mouse muscle (versus wt) (Fig. 3).


Genome-wide expression analysis comparing hypertrophic changes in normal and dysferlinopathy mice.

Lee YS, Talbot CC, Lee SJ - Genom Data (2015)

Ingenuity upstream regulator analysis generated signaling-related networks based on published interactions with the top upstream regulator, TGFb1, in F66 mouse muscle (versus wt) based on our experimental results. Red denotes upregulation, and blue denotes downregulation of the gene. The intensity of the gene color indicates the degree of up- or down-regulation. Orange lines indicate positive regulation, in accordance with the published interaction, blue lines indicate negative regulation, and yellow lines denote changes discordant from published expectation. The networks were generated through the use of Ingenuity Pathway Analysis.
© Copyright Policy - CC BY-NC-ND
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4664771&req=5

f0015: Ingenuity upstream regulator analysis generated signaling-related networks based on published interactions with the top upstream regulator, TGFb1, in F66 mouse muscle (versus wt) based on our experimental results. Red denotes upregulation, and blue denotes downregulation of the gene. The intensity of the gene color indicates the degree of up- or down-regulation. Orange lines indicate positive regulation, in accordance with the published interaction, blue lines indicate negative regulation, and yellow lines denote changes discordant from published expectation. The networks were generated through the use of Ingenuity Pathway Analysis.
Mentions: Microarray data were visualized by principal components analysis (PCA) mapping, volcano plots, and heat maps [6]. PCA analysis was performed with the Partek platform, while volcano plots and heat maps were generated with the Spotfire DecisionSite software (TIBCO Software Inc., Boston, MA). Linear regression analyses were performed with Spotfire to compare two different sets of transcriptome changes (Fig. 2). Gene Ontology (GO; www.geneontology.org) analysis was conducted for significantly differentially expressed 763 genes (fold change > 2.0, p < 0.01 in wt versus F66;Dysf−/−) using Spotfire's Gene Ontology Browser [7]. Canonical Pathways, Upstream Regulators, and Network analyses were generated using Ingenuity Pathway Analysis (IPA; QIAGEN Redwood City, CA, USA) and summarized in Table 1, Table 2, Table 3. Myostatin is a transforming growth factor-ß (TGF-ß) family member, and as expected, TGF-ß1 was a top upstream regulator in F66 mouse muscle (versus wt) (Fig. 3).

Bottom Line: Because myostatin normally limits skeletal muscle growth, there are extensive efforts to develop myostatin inhibitors for clinical use.Hence, benefits of this approach should be weighed against these potential detrimental effects.Here, we present detailed experimental methods and analysis for the gene expression profiling described in our recently published study in Human Molecular Genetics (Lee et al., 2015).

View Article: PubMed Central - PubMed

Affiliation: Department of Molecular Biology and Genetics, Johns Hopkins University School of Medicine, 725 North Wolfe Street, PCTB 803, Baltimore, MD 21205, USA.

ABSTRACT
Because myostatin normally limits skeletal muscle growth, there are extensive efforts to develop myostatin inhibitors for clinical use. One potential concern is that in muscle degenerative diseases, inducing hypertrophy may increase stress on dystrophic fibers. Our study shows that blocking this pathway in dysferlin deficient mice results in early improvement in histopathology but ultimately accelerates muscle degeneration. Hence, benefits of this approach should be weighed against these potential detrimental effects. Here, we present detailed experimental methods and analysis for the gene expression profiling described in our recently published study in Human Molecular Genetics (Lee et al., 2015). Our data sets have been deposited in the Gene Expression Omnibus (GEO) database (GSE62945) and are available at http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE62945. Our data provide a resource for exploring molecular mechanisms that are related to hypertrophy-induced, accelerated muscular degeneration in dysferlinopathy.

No MeSH data available.


Related in: MedlinePlus