在人工和传粉昆虫的选择下,甘蓝型油菜的花信号以可预测的方式进化。

IF 3.4 Q1 Agricultural and Biological Sciences BMC Evolutionary Biology Pub Date : 2020-09-24 DOI:10.1186/s12862-020-01692-7
Pengjuan Zu, Florian P Schiestl, Daniel Gervasi, Xin Li, Daniel Runcie, Frédéric Guillaume
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引用次数: 0

摘要

背景:被子植物利用各种各样的视觉和嗅觉花信号,这些信号通常被认为是在自然选择下进化而来的。这些形态和化学特征可以形成高度相关的特征集。目前尚不清楚哪些被传粉昆虫用作主要选择目标,哪些将通过与这些主要目标联系而被间接选择。长期以来,用于预测多个性状对选择的反应的定量遗传学工具已经开发出来,并促进了我们对各种生物系统中遗传相关性状进化的理解。我们使用这些工具来预测花性状的进化轨迹,并了解作用在它们身上的选择压力。结果:我们使用来自人工选择和快速循环的芸苔属植物的传粉昆虫(大黄蜂、气垫苍蝇)进化实验的数据,预测了12种花挥发物和4种形态花性状对选择的进化变化。利用观察到的选择梯度和性状的遗传方差协方差矩阵(G-matrix),我们发现在人工和大黄蜂选择实验中,包括挥发物在内的大多数花性状的观察到的反应都是朝着正确的方向预测的。遗传协方差对进化反应既有制约作用,也有促进作用。我们进一步揭示了G-矩阵也在选择过程中进化。结论:总的来说,我们的综合研究表明,花信号,尤其是挥发物,在选择下以一种最可预测的方式进化,至少在短期进化中是这样。源自遗传协方差的进化约束影响了性状的进化轨迹,因此,包括遗传协方差对于预测一组综合性状的进化变化很重要。为了更好地理解花的性状进化,还需要考虑其他过程,如资源限制和自交。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Floral signals evolve in a predictable way under artificial and pollinator selection in Brassica rapa.

Background: Angiosperms employ an astonishing variety of visual and olfactory floral signals that are generally thought to evolve under natural selection. Those morphological and chemical traits can form highly correlated sets of traits. It is not always clear which of these are used by pollinators as primary targets of selection and which would be indirectly selected by being linked to those primary targets. Quantitative genetics tools for predicting multiple traits response to selection have been developed since long and have advanced our understanding of evolution of genetically correlated traits in various biological systems. We use these tools to predict the evolutionary trajectories of floral traits and understand the selection pressures acting on them.

Results: We used data from an artificial selection and a pollinator (bumblebee, hoverfly) evolution experiment with fast cycling Brassica rapa plants to predict evolutionary changes of 12 floral volatiles and 4 morphological floral traits in response to selection. Using the observed selection gradients and the genetic variance-covariance matrix (G-matrix) of the traits, we showed that the observed responses of most floral traits including volatiles were predicted in the right direction in both artificial- and bumblebee-selection experiment. Genetic covariance had a mix of constraining and facilitating effects on evolutionary responses. We further revealed that G-matrices also evolved in the selection processes.

Conclusions: Overall, our integrative study shows that floral signals, especially volatiles, evolve under selection in a mostly predictable way, at least during short term evolution. Evolutionary constraints stemming from genetic covariance affected traits evolutionary trajectories and thus it is important to include genetic covariance for predicting the evolutionary changes of a comprehensive suite of traits. Other processes such as resource limitation and selfing also need to be considered for a better understanding of floral trait evolution.

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来源期刊
BMC Evolutionary Biology
BMC Evolutionary Biology 生物-进化生物学
CiteScore
5.80
自引率
0.00%
发文量
0
审稿时长
6 months
期刊介绍: BMC Evolutionary Biology is an open access, peer-reviewed journal that considers articles on all aspects of molecular and non-molecular evolution of all organisms, as well as phylogenetics and palaeontology.
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