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The Genomic Fabric Perspective on the Transcriptome Between Universal Quantifiers and Personalized Genomic Medicine

Numerous groups race to discover the gene biomarker whose alteration alone is indicative of a particular disease in all humans. Biomarkers are selected from the most frequently altered genes in large population cohorts. However, thousands of other genes are simultaneously affected, and, in each pers...

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Bibliographic Details
Published in:Biological theory 2016-09, Vol.11 (3), p.123-137
Main Author: Iacobas, Dumitru Andrei
Format: Article
Language:English
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Summary:Numerous groups race to discover the gene biomarker whose alteration alone is indicative of a particular disease in all humans. Biomarkers are selected from the most frequently altered genes in large population cohorts. However, thousands of other genes are simultaneously affected, and, in each person, the same disease results from a unique, never-repeatable combination of gene alterations. Therefore, our Genomic Fabric Paradigm (GFP) switches the focus from the alteration of one particular gene to the overall change in selected groups of functionally related genes. Biomarkers are of little therapeutic value, their high alterability indicating low protection by the homeostatic mechanisms as for minor players. Instead of these most alterable genes in all patients, GFP identifies in each patient the genes whose highly protected expression governs major functional pathways by controlling the expression of numerous other genes. Smart manipulation of such (commander) genes would have the maximum therapeutic benefit not for everybody but for the treated person. The genomic fabric is defined as the transcriptome associated with the most interconnected and stably expressed network of genes responsible for a particular functional pathway. The fabric exhibits specificity with respect to race/strain, sex, age, tissue/cell type, and lifestyle and environmental factors. It remodels during development, progression of a disease, and in response to external stimuli. GFP is powered by mathematically advanced analytical tools whose application is illustrated by reprocessing data from previously published gene expression experiments.
ISSN:1555-5542
1555-5550
DOI:10.1007/s13752-016-0245-3