Skeletal muscles are a diverse family of highly specialized tissues that perform a wide array of physiological functions. These muscles originate from different developmental origins and have characteristic, specialized morphologies. Unsurprisingly, many disorders of skeletal muscle afflict a remarkably specific subset of tissues. Taken as a whole, these observations indicate that specific genetic programs establish and maintain physiological specialization of muscle tissues. Elucidating these genetic programs is essential to support research into the causes, treatment, and prevention of musculoskeletal diseases. Nevertheless, most gene expression studies performed to-date have not directly addressed intrinsic variability among different muscle tissues. To better understand the intrinsic differences between muscle tissues, our long term goal is to build a comprehensive, publicly-available gene expression atlas. Our strategy is to use RNA-sequencing to profile the expression of mRNA and small non-coding RNAs in mouse muscle tissues. We will exploit the single-base resolution of RNA-sequencing data to test hypotheses regarding specific post-transcriptional regulatory mechanisms, such as alternative splicing, RNA editing, and alternative polyadenylation. This proposal will thereby define transcriptional diversity within representative muscle tissues and make this resource available to the research and clinical community. These data will be a key reference for future studies of gene expression changes in disease, injury, and aging. Moreover, successful completion of this proposal will enable discovery-based approaches to identify and eventually manipulate tissue-specific factors that determine whether a given muscle group is susceptible to injury and disease.
Many disorders of skeletal muscle afflict remarkably specific subsets of tissues, indicating that intrinsic genetic programs determine their susceptibility to injury and disease. Nevertheless, most gene expression studies performed to-date have not examined variability among different muscle groups. This proposal will develop a comprehensive gene expression database for skeletal muscle, and thereby enable discovery-based approaches to identify and eventually manipulate factors that determine susceptibility to injury and disease.
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