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Evolutionary Trade-Offs, Pareto Optimality, and the Geometry of Phenotype Space
Author(s) -
Oren Shoval,
Hila Sheftel,
Guy Shinar,
Yuval Hart,
Omer Ramote,
Avi Mayo,
E. Dekel,
Kathryn D. Kavanagh,
Uri Alon
Publication year - 2012
Publication title -
science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 12.556
H-Index - 1186
eISSN - 1095-9203
pISSN - 0036-8075
DOI - 10.1126/science.1217405
Subject(s) - phenotype , trait , pareto principle , biology , space (punctuation) , evolutionary biology , dimension (graph theory) , darwin (adl) , matching (statistics) , computer science , gene , genetics , mathematics , combinatorics , statistics , software engineering , programming language , operating system
Biological systems that perform multiple tasks face a fundamental trade-off: A given phenotype cannot be optimal at all tasks. Here we ask how trade-offs affect the range of phenotypes found in nature. Using the Pareto front concept from economics and engineering, we find that best-trade-off phenotypes are weighted averages of archetypes--phenotypes specialized for single tasks. For two tasks, phenotypes fall on the line connecting the two archetypes, which could explain linear trait correlations, allometric relationships, as well as bacterial gene-expression patterns. For three tasks, phenotypes fall within a triangle in phenotype space, whose vertices are the archetypes, as evident in morphological studies, including on Darwin's finches. Tasks can be inferred from measured phenotypes based on the behavior of organisms nearest the archetypes.

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