TY - JOUR
T1 - Emergence of Hierarchical Modularity in Evolving Networks Uncovered by Phylogenomic Analysis
AU - Caetano-Anollés, Gustavo
AU - Aziz, M. Fayez
AU - Mughal, Fizza
AU - Gräter, Frauke
AU - Koç, Ibrahim
AU - Caetano-Anollés, Kelsey
AU - Caetano-Anollés, Derek
N1 - Publisher Copyright:
© The Author(s) 2019.
PY - 2019
Y1 - 2019
N2 - 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.
AB - 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.
KW - Accretion
KW - biphasic bow-tie pattern
KW - evolutionary diversification
KW - molecular structure
KW - phylogenomic analysis
KW - ribosome
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U2 - 10.1177/1176934319872980
DO - 10.1177/1176934319872980
M3 - Review article
C2 - 31523127
AN - SCOPUS:85072177579
SN - 1176-9343
VL - 15
JO - Evolutionary Bioinformatics
JF - Evolutionary Bioinformatics
ER -