Dynamic network-based epistasis analysis: Boolean examples

被引:12
作者
Azpeitia, Eugenio [1 ,2 ]
Benitez, Mariana [2 ,3 ,4 ]
Padilla-Longoria, Pablo [2 ,5 ]
Espinosa-Soto, Carlos [2 ,6 ]
Alvarez-Buylla, Elena R. [1 ,2 ]
机构
[1] Univ Nacl Autonoma Mexico, Inst Ecol, Mexico City 04510, DF, Mexico
[2] Univ Nacl Autonoma Mexico, Ctr Ciencias Complejidad, Mexico City 04510, DF, Mexico
[3] Masaryk Univ, Dept Funct Genom & Prote, Brno, Czech Republic
[4] Masaryk Univ, Cent European Inst Technol, Brno, Czech Republic
[5] Inst Invest Matemat Aplicadas & Sistemas, Mexico City, DF, Mexico
[6] Cinvestav IPN, Irapuato, Mexico
关键词
epistasis; gene regulatory networks; Boolean networks; feedback loops; feed-forward loops; temporal dynamics; modeling; gene interactions; PATTERN-FORMATION; FEEDFORWARD LOOP; FEEDBACK LOOPS; STEM-CELL; REGULATORY NETWORKS; MODEL; EVOLUTION; SYSTEMS; SIMULATION; TOPOLOGY;
D O I
10.3389/fpls.2011.00092
中图分类号
Q94 [植物学];
学科分类号
071001 [植物学];
摘要
In this article we focus on how the hierarchical and single-path assumptions of epistasis analysis can bias the inference of gene regulatory networks. Here we emphasize the critical importance of dynamic analyses, and specifically illustrate the use of Boolean network models. Epistasis in a broad sense refers to gene interactions, however, as originally proposed by Bateson, epistasis is defined as the blocking of a particular allelic effect due to the effect of another allele at a different locus (herein, classical epistasis). Classical epistasis analysis has proven powerful and useful, allowing researchers to infer and assign directionality to gene interactions. As larger data sets are becoming available, the analysis of classical epistasis is being complemented with computer science tools and system biology approaches. We show that when the hierarchical and single-path assumptions are not met in classical epistasis analysis, the access to relevant information and the correct inference of gene interaction topologies is hindered, and it becomes necessary to consider the temporal dynamics of gene interactions. The use of dynamical networks can overcome these limitations. We particularly focus on the use of Boolean networks that, like classical epistasis analysis, relies on logical formalisms, and hence can complement classical epistasis analysis and relax its assumptions. We develop a couple of theoretical examples and analyze them from a dynamic Boolean network model perspective. Boolean networks could help to guide additional experiments and discern among alternative regulatory schemes that would be impossible or difficult to infer without the elimination of these assumption from the classical epistasis analysis. We also use examples from the literature to show how a Boolean network-based approach has resolved ambiguities and guided epistasis analysis. Our article complements previous accounts, not only by focusing on the implications of the hierarchical and single-path assumption, but also by demonstrating the importance of considering temporal dynamics, and specifically introducing the usefulness of Boolean network models and also reviewing some key properties of network approaches.
引用
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页数:12
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