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      Muscle regeneration in dystrophin-deficient mdx mice studied by gene expression profiling

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          Abstract

          Background

          Duchenne muscular dystrophy (DMD), caused by mutations in the dystrophin gene, is lethal. In contrast, dystrophin-deficient mdx mice recover due to effective regeneration of affected muscle tissue. To characterize the molecular processes associated with regeneration, we compared gene expression levels in hindlimb muscle tissue of mdx and control mice at 9 timepoints, ranging from 1–20 weeks of age.

          Results

          Out of 7776 genes, 1735 were differentially expressed between mdx and control muscle at at least one timepoint (p < 0.05 after Bonferroni correction). We found that genes coding for components of the dystrophin-associated glycoprotein complex are generally downregulated in the mdx mouse. Based on functional characteristics such as membrane localization, signal transduction, and transcriptional activation, 166 differentially expressed genes with possible functions in regeneration were analyzed in more detail. The majority of these genes peak at the age of 8 weeks, where the regeneration activity is maximal. The following pathways are activated, as shown by upregulation of multiple members per signalling pathway: the Notch-Delta pathway that plays a role in the activation of satellite cells, and the Bmp15 and Neuregulin 3 signalling pathways that may regulate proliferation and differentiation of satellite cells. In DMD patients, only few of the identified regeneration-associated genes were found activated, indicating less efficient regeneration processes in humans.

          Conclusion

          Based on the observed expression profiles, we describe a model for muscle regeneration in mdx mice, which may provide new leads for development of DMD therapies based on the improvement of muscle regeneration efficacy.

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          Most cited references69

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          Quantitative monitoring of gene expression patterns with a complementary DNA microarray.

          A high-capacity system was developed to monitor the expression of many genes in parallel. Microarrays prepared by high-speed robotic printing of complementary DNAs on glass were used for quantitative expression measurements of the corresponding genes. Because of the small format and high density of the arrays, hybridization volumes of 2 microliters could be used that enabled detection of rare transcripts in probe mixtures derived from 2 micrograms of total cellular messenger RNA. Differential expression measurements of 45 Arabidopsis genes were made by means of simultaneous, two-color fluorescence hybridization.
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            Variance stabilization applied to microarray data calibration and to the quantification of differential expression.

            We introduce a statistical model for microarray gene expression data that comprises data calibration, the quantification of differential expression, and the quantification of measurement error. In particular, we derive a transformation h for intensity measurements, and a difference statistic Deltah whose variance is approximately constant along the whole intensity range. This forms a basis for statistical inference from microarray data, and provides a rational data pre-processing strategy for multivariate analyses. For the transformation h, the parametric form h(x)=arsinh(a+bx) is derived from a model of the variance-versus-mean dependence for microarray intensity data, using the method of variance stabilizing transformations. For large intensities, h coincides with the logarithmic transformation, and Deltah with the log-ratio. The parameters of h together with those of the calibration between experiments are estimated with a robust variant of maximum-likelihood estimation. We demonstrate our approach on data sets from different experimental platforms, including two-colour cDNA arrays and a series of Affymetrix oligonucleotide arrays.
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              Notch-mediated restoration of regenerative potential to aged muscle.

              A hallmark of aging is diminished regenerative potential of tissues, but the mechanism of this decline is unknown. Analysis of injured muscle revealed that, with age, resident precursor cells (satellite cells) had a markedly impaired propensity to proliferate and to produce myoblasts necessary for muscle regeneration. This was due to insufficient up-regulation of the Notch ligand Delta and, thus, diminished activation of Notch in aged, regenerating muscle. Inhibition of Notch impaired regeneration of young muscle, whereas forced activation of Notch restored regenerative potential to old muscle. Thus, Notch signaling is a key determinant of muscle regenerative potential that declines with age.
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                Author and article information

                Journal
                BMC Genomics
                BMC Genomics
                BioMed Central (London )
                1471-2164
                2005
                13 July 2005
                : 6
                : 98
                Affiliations
                [1 ]Center for Human and Clinical Genetics, Leiden University Medical Center, Wassenaarseweg 72, 2333 AL Leiden, Nederland
                [2 ]Leiden Genome Technology Center, Leiden University Medical Center, Wassenaarseweg 72, 2333 AL Leiden, Nederland
                [3 ]Department of Physiology and Biophysics, Howard Hughes Medical Institute, University of Iowa, 400 Eckstein Medical Research Building, Iowa City, IA52240-1101, U.S.A
                Article
                1471-2164-6-98
                10.1186/1471-2164-6-98
                1190170
                16011810
                963f06f1-407e-4cfc-99e4-27147ae221c6
                Copyright © 2005 Turk et al; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 8 February 2005
                : 13 July 2005
                Categories
                Research Article

                Genetics
                Genetics

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