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Gene Regulatory Networks (Grns) Are the On- Off Switches of a Cell Operating at the Gene Level

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Gene Regulatory Networks (Grns) Are the On- Off Switches of a Cell Operating at the Gene Level CS 4491/CS 7990 SPECIAL TOPICS IN BIOINFORMATICS Mingon Kang, Ph.D Computer Science, Kennesaw State University Biological Networks Provide a mathematical representation of connections found in ecological, evolutionary, and physiological studies, such as neural networks Represent complex biological systems using graphs Nodes: units in the network Edges: interactions between the units Biological Networks Network analysis is increasingly recognized as a powerful approach to understanding biological organization and the function of cellular components and may help us to understand the principles deriving the evolution of living organisms. Most genes and proteins do not have a function on their own, rather their role is realized through a complex web of interactions with other proteins, genes, and biomolecules. Reference: http://homepages.ulb.ac.be/~dgonze/TEACHING/network_motifs.pdf Biological Networks Gene regulatory network: two genes are connected if the expression of one gene modulates expression of another one by either activation of inhibition Protein interaction network: proteins that are connected in physical interactions or metabolic and signaling pathways of the cell; Metabolic network: metabolic products and substrates that participate in one reaction; Reference: http://dna.cs.byu.edu/bio465/slides/regulatory-network.ppt Biological Networks These networks can be obtained from A collection of database MIPS, String -> protein interaction network A high-throughout experiments Microarray -> regulation network Large-scale bioinformatics predictions Regulatory motif detection -> transcriptional network Reference: http://homepages.ulb.ac.be/~dgonze/TEACHING/network_motifs.pdf What is Gene Regulatory Network? Gene regulatory networks (GRNs) are the on- off switches of a cell operating at the gene level. Two genes are connected if the expression of one gene modulates expression of another one by either activation or inhibition Reference: http://dna.cs.byu.edu/bio465/slides/regulatory-network.ppt Why Study GRN? Genes are not independent They regulate each other and act collectively This collective behavior can be observed using microarray Some genes control the response of the cell to changes in the environment by regulating other genes Potential discovery of triggering mechanism and treatments for disease Reference: http://dna.cs.byu.edu/bio465/slides/regulatory-network.ppt Background Knowledge Cell reproduction, metabolism, and responses to the environment are all controlled by proteins Each gene is responsible for constructing a single protein Some genes manufacture proteins which control the rate at which other genes manufacture proteins (either promoting or suppressing) Hence some genes regulate other genes (via the proteins they create) Reference: http://dna.cs.byu.edu/bio465/slides/regulatory-network.ppt Learning Causal Relationships High-throughput genetic technologies empowers to study how genes interact with each other If gene A consistently turns on after Gene C, then gene C may be causing gene A to turn on We have to have a lot of carefully controlled time series data to infer this Reference: http://dna.cs.byu.edu/bio465/slides/regulatory-network.ppt Biological Networks Represented by graphs Nodes represent objects (genes, proteins) Edges represent interactions (physical interaction between 2 proteins, metabolic reaction, regulation) Directed/Undirected graph If edges are oriented, as for chemical reactions or regulations, they are called arcs and the graph is said directed. Otherwise undirected graph. Often correlation between genes are investigated. Reference: http://homepages.ulb.ac.be/~dgonze/TEACHING/network_motifs.pdf Biological Networks Reference: http://homepages.ulb.ac.be/~dgonze/TEACHING/network_motifs.pdf Kegg http://www.genome.jp/kegg/pathway.html Reference: http://dna.cs.byu.edu/bio465/slides/regulatory-network.ppt Pathgen Reference: http://dna.cs.byu.edu/bio465/slides/regulatory-network.ppt Microarray data Samples Genes Gene up-regulate, down-regulate; Reference: http://dna.cs.byu.edu/bio465/slides/regulatory-network.ppt Modules in networks Modules (sub-networks) A common feature of large, complex biological networks Connected molecular components Reference: http://homepages.ulb.ac.be/~dgonze/TEACHING/network_motifs.pdf Modules in networks Examine their modularity e.g. comparative analyses of structurally similar modules across different species Identify mutually shared functions, associate a modular structure with a new function, and provide insight into the evolution of various network structures. Reference: http://homepages.ulb.ac.be/~dgonze/TEACHING/network_motifs.pdf Network Motifs Important local property of networks Patterns of interconnections that recur in many different parts of a network at frequencies much higher than those found in randomized networks Reference: http://homepages.ulb.ac.be/~dgonze/TEACHING/network_motifs.pdf Network Motifs Three types of Network Motifs Feed-forward loop (FFL) Single input motif (SIM) Dense overlapping regulons (DOR) Reference: http://homepages.ulb.ac.be/~dgonze/TEACHING/network_motifs.pdf Feed-forward loop (FFL) Transcription factor X that regulates a second transcription factor Y, such that both X and Y jointly regulate on operon Z. X: general transcription factor Y: specific transcription factor Z: effector operon Reference: http://homepages.ulb.ac.be/~dgonze/TEACHING/network_motifs.pdf Single input motif (SIM) A set of operons that are controlled by a single transcription factor. Reference: http://homepages.ulb.ac.be/~dgonze/TEACHING/network_motifs.pdf Dense overlapping regulons (DOR) A layer of overlapping interactions between operons and a group of input transcription factors that is much more dense than corresponding structures in randomized networks. Reference: http://homepages.ulb.ac.be/~dgonze/TEACHING/network_motifs.pdf Network Motifs Reference: http://homepages.ulb.ac.be/~dgonze/TEACHING/network_motifs.pdf Network Motifs Reference: http://homepages.ulb.ac.be/~dgonze/TEACHING/network_motifs.pdf Network Analysis Maximum Spanning tree A maximum spanning tree is a spanning tree of a weighted graph having maximum weight. Cliques subset of vertices of an undirected graph such that its induced subgraph is complete.
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