Mutations in the dysferlin gene cause limb girdle muscular dystrophy type 2B and Miyoshi myopathy. We report here the results of expression profile analyses and in vitro investigations that point to an interaction between dysferlin and the Ca2+ and lipid-binding proteins, annexins A1 and A2, and define a role for dysferlin in Ca2+-dependent repair of sarcolemmal injury through a process of vesicle fusion. Expression profiling identified a network of genes that are co-regulated in dysferlinopathic mice. Co-immunofluorescence, co-immunoprecipitation, and fluorescence lifetime imaging microscopy revealed that dysferlin normally associates with both annexins A1 and A2 in a Ca2+ and membrane injury-dependent manner. The distribution of the annexins and the efficiency of sarcolemmal wound-healing are significantly disrupted in dysferlin-deficient muscle. We propose a model of muscle membrane healing mediated by dysferlin that is relevant to both normal and dystrophic muscle and defines the annexins as potential muscular dystrophy genes.

The nemaline myopathies (NMs) are a clinically and genetically heterogeneous group of disorders characterized by nemaline rods and skeletal muscle weakness. Mutations in five sarcomeric thin filament genes have been identified. However, the molecular consequences of these mutations are unknown. Using Affymetrix oligonucleotide microarrays, we have analyzed the expression patterns of >21,000 genes and expressed sequence tags in skeletal muscles of 12 NM patients and 21 controls. Multiple complementary approaches were used for data analysis, including geometric fold analysis, two-tailed unequal variance t test, hierarchical clustering, relevance network, and nearest-neighbor analysis. We report the identification of high satellite cell populations in NM and the significant down-regulation of transcripts for key enzymes of glucose and glycogen metabolism as well as a possible regulator of fatty acid metabolism, UCP3. Interestingly, transcript level changes of multiple genes suggest possible changes in Ca(2+) homeostasis. The increased expression of multiple structural proteins was consistent with increased fibrosis. This comprehensive study of downstream molecular consequences of NM gene mutations provides insights in the cellular events leading to the NM phenotype.

The primary cause of Duchenne muscular dystrophy (DMD) is a mutation in the dystrophin gene, leading to absence of the corresponding protein, disruption of the dystrophin-associated protein complex, and substantial changes in skeletal muscle pathology. Although the primary defect is known and the histological pathology well documented, the underlying molecular pathways remain in question. To clarify these pathways, we used expression microarrays to compare individual gene expression profiles for skeletal muscle biopsies from DMD patients and unaffected controls. We have previously published expression data for the 12,500 known genes and full-length expressed sequence tags (ESTs) on the Affymetrix HG-U95Av2 chips. Here we present comparative expression analysis of the 50,000 EST clusters represented on the remainder of the Affymetrix HG-U95 set. Individual expression profiles were generated for biopsies from 10 DMD patients and 10 unaffected control patients. Two methods of statistical analysis were used to interpret the resulting data (t-test analysis to determine the statistical significance of differential expression and geometric fold change analysis to determine the extent of differential expression). These analyses identified 183 probe sets (59 of which represent known genes) that differ significantly in expression level between unaffected and disease muscle. This study adds to our knowledge of the molecular pathways that are altered in the dystrophic state. In particular, it suggests that signaling pathways might be substantially involved in the disease process. It also highlights a large number of unknown genes whose expression is altered and whose identity therefore becomes important in understanding the pathogenesis of muscular dystrophy.

The potential for gene discovery, fueled by DNA microchip technology and the sequencing of hundreds of genomes, is unprecedented. In this context, trying to discover genes that are actually of significance rather than merely appearing so due to noise is of utmost importance. We present a web application, CHIP TUNER, which assists in this gene discovery process. Our system uses evidence-based noise reduction to help delineate candidate target genes of biological importance. Specifically, CHIP TUNER learns from redundant experiments an "identity mask" that defines a region of noise inherent to biological sampling and DNA microarray processing; it then takes this into account during actual sample comparisons. The goal of CHIP TUNER is to improve the chances that newly discovered "important" genes are actually of importance before large amounts of time and resources are invested.

Hedgehog pathway activation is required for proliferation of cerebellar granule cell neuron precursors during development and is etiologic in certain cerebellar tumors. To identify genes expressed specifically in granule cell neuron precursors, we used oligonucleotide microarrays to analyze regulation of 13,179 genes/expressed sequence tags in heterogeneous primary cultures of neonatal mouse cerebellum that respond to the mitogen Sonic hedgehog. In conjunction, we applied experiment-specific noise models to render a gene-by-gene robust indication of up-regulation in Sonic hedgehog-treated cultures. Twelve genes so identified were tested, and 10 (83%) showed appropriate expression in the external granular layer (EGL) of the postnatal day (PN) 7 cerebellum and down-regulation by PN 15, as verified by in situ hybridization. Whole-organ profiling of the developing cerebellum was carried out from PN 1 to 30 to generate a database of temporal gene regulation profiles (TRPs). From the database an algorithm was developed to capture the TRP typical of EGL-specific genes. The "TRP-EGL" accurately predicted expression in vivo of an additional 18 genes/expressed sequence tags with a sensitivity of 80% and a specificity of 88%. We then compared the positive predictive value of our analytical procedure with other widely used methods, as verified by the TRP-EGL in silico. These findings suggest that replicate experiments and incorporation of noise models increase analytical specificity. They further show that genome-wide methods are an effective means to identify stage-specific gene expression in the developing granule cell lineage.

The primary cause of Duchenne muscular dystrophy (DMD) is a mutation in the dystrophin gene leading to the absence of the corresponding RNA transcript and protein. Absence of dystrophin leads to disruption of the dystrophin-associated protein complex and substantial changes in skeletal muscle pathology. Although the histological pathology of dystrophic tissue has been well documented, the underlying molecular pathways remain poorly understood. To examine the pathogenic pathways and identify new or modifying factors involved in muscular dystrophy, expression microarrays were used to compare individual gene expression profiles of skeletal muscle biopsies from 12 DMD patients and 12 unaffected control patients. Two separate statistical analysis methods were used to interpret the resulting data: t test analysis to determine the statistical significance of differential expression and geometric fold change analysis to determine the extent of differential expression. These analyses identified 105 genes that differ significantly in expression level between unaffected and DMD muscle. Many of the differentially expressed genes reflect changes in histological pathology. For instance, immune response signals and extracellular matrix genes are overexpressed in DMD muscle, an indication of the infiltration of inflammatory cells and connective tissue. Significantly more genes are overexpressed than are underexpressed in dystrophic muscle, with dystrophin underexpressed, whereas other genes encoding muscle structure and regeneration processes are overexpressed, reflecting the regenerative nature of the disease.