TY - JOUR
T1 - Optimality in evolution
T2 - New insights from synthetic biology
AU - de Vos, Marjon G J
AU - Poelwijk, Frank J.
AU - Tans, Sander J.
N1 - Funding Information:
Work in the laboratory of SJT is part of the research program of the Stichting voor Fundamenteel Onderzoek der Materie (FOM), which is financially supported by the Nederlandse Organisatie voor Wetenschappelijke Onderzoek (NWO) . FJP gratefully acknowledges funding by the Helen Hay Whitney Foundation sponsored by the Howard Hughes Medical Institute .
PY - 2013/8
Y1 - 2013/8
N2 - Whether organisms evolve to perform tasks optimally has intrigued biologists since Lamarck and Darwin. Optimality models have been used to study diverse properties such as shape, locomotion, and behavior. However, without access to the genetic underpinnings or the ability to manipulate biological functions, it has been difficult to understand an organism's intrinsic potential and limitations. Now, novel experiments are overcoming these technical obstacles and have begun to test optimality in more quantitative terms. With the use of simple model systems, genetic engineering, and mathematical modeling, one can independently quantify the prevailing selective pressures and optimal phenotypes. These studies have given an exciting view into the evolutionary potential and constraints of biological systems, and hold the promise to further test the limits of predicting future evolutionary change.
AB - Whether organisms evolve to perform tasks optimally has intrigued biologists since Lamarck and Darwin. Optimality models have been used to study diverse properties such as shape, locomotion, and behavior. However, without access to the genetic underpinnings or the ability to manipulate biological functions, it has been difficult to understand an organism's intrinsic potential and limitations. Now, novel experiments are overcoming these technical obstacles and have begun to test optimality in more quantitative terms. With the use of simple model systems, genetic engineering, and mathematical modeling, one can independently quantify the prevailing selective pressures and optimal phenotypes. These studies have given an exciting view into the evolutionary potential and constraints of biological systems, and hold the promise to further test the limits of predicting future evolutionary change.
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U2 - 10.1016/j.copbio.2013.04.008
DO - 10.1016/j.copbio.2013.04.008
M3 - Review article
C2 - 23684729
AN - SCOPUS:84880954081
SN - 0958-1669
VL - 24
SP - 797
EP - 802
JO - Current Opinion in Biotechnology
JF - Current Opinion in Biotechnology
IS - 4
ER -