Multi-layer Networks: Prospects in Study of Small RNA-mediated Gene Regulatory Network of Cassava in Diseased Condition

Network analysis has been a useful modeling tool in the study of complex systems like biological systems. The deluge of genomic data, owing to recent advancements in sequencing technologies produces different dimensions of information about a system. Since a single source of information provides only a partial view of the system, systems biology addresses this problem by combining multiple sources of information for better insights into the system. The techniques that have been applied to analyze networks before now seem inadequate to capture correctly the characteristics of such a heterogeneous system. In this paper we introduce Multilayer Networks (MLNs) for a holistic biological network analysis. Although not new to some disciplines, systems biology is yet to benefit from the strides made in other domains of knowledge where MLNs are applied. When using MLN, the parameters by which network structure and dynamics are studied automatically take on new definitions. We studied with MLNs the dynamics of susceptibility and/or resistance of Cassava small RNA-mediated gene regulatory network on infection with Cassava Mosaic Virus (CMV), using NGS data of RNA from two susceptible and resistant genotypes of Cassava to CMV. The targets of the small RNAs identified from the data provided a layer of interaction of the regulatory network, while the differential regulation information of the genes with RNA-seq made up another layer of information. The MLN approach adopted in this study provided a clearly different meaning to the dynamics of regulation of gene expression when compared with the single layer network approach.