A framework for studying behavioral evolution by reconstructing ancestral repertoires.
A framework for studying behavioral evolution by reconstructing ancestral repertoires.
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DOI：
10.7554/elife.61806
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发表时间：
2021-09-02
期刊：
影响因子：
7.7
通讯作者：
Berman GJ
中科院分区：
文献类型：
--
作者：
Hernández DG;Rivera C;Cande J;Zhou B;Stern DL;Berman GJ
尽管不同动物物种在诸多行为上往往呈现出广泛的差异，但通常科学家在任何一项单独研究中，只会考察一种或少数几种行为。在此，我们提出一个新框架，用以同时研究多种行为的演化。我们运用无监督技术，测定了六个果蝇物种个体的行为库，并识别出每个物种所展现的所有刻板动作。随后，我们采用广义线性混合模型来估计物种内和物种间的行为协方差，并且借助已知的物种间系统发育关系，推测出祖先物种所表现出的（未观测到的）行为。我们发现，种内行为变异的很大一部分，其协方差结构与先前描述的个体行为在长时间尺度上的变异类似，这表明在我们的实验中，同一物种个体间测得的大部分变异，反映的是神经网络状态的差异，而非个体间的遗传或发育差异。接着，我们提出一种方法，用以识别那些看似以相关方式演化的行为组，以此说明行为集合而非单个行为可能是如何演化的。我们的方法为识别共同演化的行为提供了一个新框架，或许还为研究行为演化的机制基础带来新契机。
Although different animal species often exhibit extensive variation in many behaviors, typically scientists examine one or a small number of behaviors in any single study. Here, we propose a new framework to simultaneously study the evolution of many behaviors. We measured the behavioral repertoire of individuals from six species of fruit flies using unsupervised techniques and identified all stereotyped movements exhibited by each species. We then fit a Generalized Linear Mixed Model to estimate the intra- and inter-species behavioral covariances, and, by using the known phylogenetic relationships among species, we estimated the (unobserved) behaviors exhibited by ancestral species. We found that much of intra-specific behavioral variation has a similar covariance structure to previously described long-time scale variation in an individual’s behavior, suggesting that much of the measured variation between individuals of a single species in our assay reflects differences in the status of neural networks, rather than genetic or developmental differences between individuals. We then propose a method to identify groups of behaviors that appear to have evolved in a correlated manner, illustrating how sets of behaviors, rather than individual behaviors, likely evolved. Our approach provides a new framework for identifying co-evolving behaviors and may provide new opportunities to study the mechanistic basis of behavioral evolution.