TY - JOUR
T1 - Extinctions in heterogeneous environments and the evolution of modularity
AU - Kashtan, Nadav
AU - Parter, Merav
AU - Dekel, Erez
AU - Mayo, Avi E.
AU - Alon, Uri
PY - 2009/8
Y1 - 2009/8
N2 - Extinctions of local subpopulations are common events in nature. Here, we ask whether such extinctions can affect the design of biological networks within organisms over evolutionary timescales. We study the impact of extinction events on modularity of biological systems, a common architectural principle found on multiple scales in biology. As a model system, we use networks that evolve toward goals specified as desired input-output relationships. We use an extinction-recolonization model, in which metapopulations occupy and migrate between different localities. Each locality displays a different environmental condition (goal), but shares the same set of subgoals with other localities. We find that in the absence of extinction events, the evolved computational networks are typically highly optimal for their localities with a nonmodular structure. In contrast, when local populations go extinct from time to time, we find that the evolved networks are modular in structure. Modular circuitry is selected because of its ability to adapt rapidly to the conditions of the free niche following an extinction event. This rapid adaptation is mainly achieved through genetic recombination of modules between immigrants from neighboring local populations. This study suggests, therefore, that extinctions in heterogeneous environments promote the evolution of modular biological network structure, allowing local populations to effectively recombine their modules to recolonize niches.
AB - Extinctions of local subpopulations are common events in nature. Here, we ask whether such extinctions can affect the design of biological networks within organisms over evolutionary timescales. We study the impact of extinction events on modularity of biological systems, a common architectural principle found on multiple scales in biology. As a model system, we use networks that evolve toward goals specified as desired input-output relationships. We use an extinction-recolonization model, in which metapopulations occupy and migrate between different localities. Each locality displays a different environmental condition (goal), but shares the same set of subgoals with other localities. We find that in the absence of extinction events, the evolved computational networks are typically highly optimal for their localities with a nonmodular structure. In contrast, when local populations go extinct from time to time, we find that the evolved networks are modular in structure. Modular circuitry is selected because of its ability to adapt rapidly to the conditions of the free niche following an extinction event. This rapid adaptation is mainly achieved through genetic recombination of modules between immigrants from neighboring local populations. This study suggests, therefore, that extinctions in heterogeneous environments promote the evolution of modular biological network structure, allowing local populations to effectively recombine their modules to recolonize niches.
KW - Biological networks
KW - Extinction-recolonization
KW - Genetic recombinations
KW - Metapopulation
KW - Modularity
UR - http://www.scopus.com/inward/record.url?scp=68149110046&partnerID=8YFLogxK
U2 - 10.1111/j.1558-5646.2009.00684.x
DO - 10.1111/j.1558-5646.2009.00684.x
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C2 - 19473401
AN - SCOPUS:68149110046
SN - 0014-3820
VL - 63
SP - 1964
EP - 1975
JO - Evolution
JF - Evolution
IS - 8
ER -