Emergence of Hierarchical Modularity in Evolving Networks Uncovered by Phylogenomic Analysis. (September 2019)

• Record Type: Journal Article
• Authors: Caetano-Anollés, Gustavo; Aziz, M Fayez; Mughal, Fizza; Gräter, Frauke; Koç, Ibrahim; Caetano-Anollés, Kelsey; Caetano-Anollés, Derek
• Is Part Of: Evolutionary bioinformatics online. Volume 15(2019)
• Publication Date: 2019-09
• Subjects: Accretion -- biphasic bow-tie pattern -- molecular structure -- evolutionary diversification -- phylogenomic analysis -- ribosome; Bioinformatics -- Periodicals; Evolutionary computation -- Periodicals; Genetic programming (Computer science) -- Periodicals; Computational Biology; Evolution, Molecular; Bioinformatics; Electronic journals; Periodicals; Fulltext; Internet Resources; Periodicals; Periodicals; 576.8
• DOI: 10.1177/1176934319872980
• Languages: English
• ISSNs: 1176-9343

Abstract

Networks describe how parts associate with each other to form integrated systems which often have modular and hierarchical structure. In biology, network growth involves two processes, one that unifies and the other that diversifies. Here, we propose a biphasic (bow-tie) theory of module emergence. In the first phase, parts are at first weakly linked and associate variously. As they diversify, they compete with each other and are often selected for performance. The emerging interactions constrain their structure and associations. This causes parts to self-organize into modules with tight linkage. In the second phase, variants of the modules diversify and become new parts for a new generative cycle of higher level organization. The paradigm predicts the rise of hierarchical modularity in evolving networks at different timescales and complexity levels. Remarkably, phylogenomic analyses uncover this emergence in the rewiring of metabolomic and transcriptome-informed metabolic networks, the nanosecond dynamics of proteins, and evolving networks of metabolism, elementary functionomes, and protein domain organization.