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Experimental evolution, behavior and genetics: Associative learning as a case study

摘要The evolutionary dynamics of behavioral traits reflect phenotypic and genetic changes.Methodological difficulties in analyzing the genetic dynamics of complex traits have left open questions on the mechanisms that have shaped complex behaviors and cognitive abilities.A strategy to investigate the change of behavior across generations is to assume that genetic constraints have a negligible role in evolution (the phenotypic gambit) and focus on the phenotype as a proxy for genetic evolution.Empirical evidence and technologic advances in genomics question the choice of neglecting the genetic underlying the dynamics of behavioral evolution.I first discuss the relevance of genetic factors-e.g.genetic variability,genetic linkage,gene interactions -in shaping evolution,showing the importance of taking genetic factors into account when dealing with evolutionary dynamics.I subsequently describe the recent advancements in genetics and genomics that make the investigation of the ongoing evolutionary process of behavioral traits finally attainable.In particular,by applying genomic resequencing to experimental evolution-a method called Evolve & Resequence-it is possible to monitor at the same time phenotypic and genomic changes in populations exposed to controlled selective pressures.Experimental evolution of associative learning,a well-known trait that promptly responds to selection,is a convenient model to illustrate this approach applied to behavior and cognition.Taking into account the recent achievements of the field,I discuss how to design and conduct an effective Evolve & Resequence study on associative learning in Drosophila.By integrating phenotypic and genomic data in the investigation of evolutionary dynamics,new insights can be gained on longstanding questions such as the modularity of mind and its evolution [Current Zoology 61 (2):226-241,2015].

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发布时间 2015-05-14(万方平台首次上网日期,不代表论文的发表时间)
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动物学报(英文版)

动物学报(英文版)

2015年61卷2期

226-241页

SCIMEDLINEISTICCSCDBP

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