The genomic fabric paradigm (GFP) characterizes the transcriptome topology by the transcripts' abundances, the variability of the expression profile, and the inter-coordination of gene expressions in each pathophysiological condition. The expression variability analysis provides an indirect estimate of the cell capability to limit the stochastic fluctuations of the expression levels of key genes, while the expression coordination analysis determines the gene networks in functional pathways. This report illustrates the theoretical bases and the mathematical framework of the GFP with applications to our microarray data from mouse models of post ischemic, and constant and intermittent hypoxia-induced heart failures. GFP analyses revealed the myocardium priorities in keeping the expression of key genes within narrow intervals, determined the statistically significant gene interlinkages, and identified the gene master regulators in the mouse heart left ventricle under normal and ischemic conditions. We quantified the expression regulation, alteration of the expression control, and remodeling of the gene networks caused by the oxygen deprivation and determined the efficacy of the bone marrow mono-nuclear stem cell injections to restore the normal transcriptome. Through the comprehensive assessment of the transcriptome, GFP would pave the way towards the development of personalized gene therapy of cardiac diseases.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9410512PMC
http://dx.doi.org/10.3390/jpm12081246DOI Listing

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