Community Structure Analysis of Gene Interaction Networks in Duchenne Muscular Dystrophy

Abstract

Duchenne Muscular Dystrophy (DMD) is an important pathology associated with the human skeletal muscle and has been studied extensively. Gene expression measurements on skeletal muscle of patients afflicted with DMD provides the opportunity to understand the underlying mechanisms that lead to the pathology. Community structure analysis is a useful computational technique for understanding and modeling genetic interaction networks. In this paper, we leverage this technique in combination with gene expression measurements from normal and DMD patient skeletal muscle tissue to study the structure of genetic interactions in the context of DMD. We define a novel framework for transforming a raw dataset of gene expression measurements into an interaction network, and subsequently apply algorithms for community structure analysis for the extraction of topological communities. The emergent communities are analyzed from a biological standpoint in terms of their constituent biological pathways, and an interpretation that draws correlations between functional and structural organization of the genetic interactions is presented. We also compare these communities and associated functions in pathology against those in normal human skeletal muscle. In particular, differential enhancements are observed in the following pathways between pathological and normal cases: Metabolic, Focal adhesion, Regulation of actin cytoskeleton and Cell adhesion, and implication of these mechanisms are supported by prior work. Furthermore, our study also includes a gene-level analysis to identify genes that are involved in the coupling between the pathways of interest. We believe that our results serve to highlight important distinguishing features in the structural/functional organization of constituent biological pathways, as it relates to normal and DMD cases, and provide the mechanistic basis for further biological investigations into specific pathways differently regulated between normal and DMD patients. These findings have the potential to serve as fertile ground for therapeutic applications involving targeted drug development for DMD.

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“…Communities having the highest node strength (total probability for their nodes to connect to distinct communities) hold the most significant functional interactions in the network [ 27 , 30 , 31 ]. Therefore, the subsequent analysis of gene communities in DE and CO networks was performed considering not only the gene/node hierarchy but, and principally, the networks' CGCSs.…”

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“…2c,d for MM-DE and MF-DE, respectively). Communities having the highest node strength (total probability for community’s nodes to connect to distinct communities) hold the most significant functional interactions in the network 5 , 13 , 14 . DE network’s CGCSs are further addressed in the context of subsequent analyses on gene hierarchy, gene communities and microRNA-target interactions.…”

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“…Coarse-grained community structure (CGCS) was obtained for each network, yielding the relationships between each community in the network ( Fig 6 ). Communities with the strongest connection weights (fraction of edges linking distinct communities) hold the most significant functional interactions in the network [ 30 , 44 , 45 ]. Therefore, the subsequent analysis of gene communities in DE and CO networks was performed considering not only the gene/node hierarchy but, and principally, the networks’ CGCS.…”