Firmat Cyril, Litrico Isabelle
AGIR, INRAE, University of Toulouse, Castanet-Tolosan, France.
P3F UR 004, INRAE, Le Chêne RD150, Lusignan, France.
Front Plant Sci. 2022 Oct 19;13:733996. doi: 10.3389/fpls.2022.733996. eCollection 2022.
Plant breeding is focused on the genotype and population levels while targeting effects at higher levels of biodiversity, from crop covers to agroecosystems. Making predictions across nested levels of biodiversity is therefore a major challenge for the development of intercropping practices. New prediction tools and concepts are required to design breeding strategies with desirable outcomes at the crop community level. We reviewed theoretical advances in the field of evolutionary ecology to identify potentially operational ways of predicting the effects of artificial selection on community-level performances. We identified three main types of approaches differing in the way they model interspecific indirect genetic effects (IIGEs) at the community level: (1) The community heritability approach estimates the variance for IIGE induced by a focal species at the community level; (2) the joint phenotype approach quantifies genetic constraints between direct genetic effects and IIGE for a set of interacting species; (3) the community-trait genetic gradient approach decomposes the IIGE for a focal species across a multivariate set of its functional traits. We discuss the potential operational capacities of these approaches and stress that each is a special case of a general multitrait and multispecies selection index. Choosing one therefore involves assumptions and goals regarding the breeding target and strategy. Obtaining reliable quantitative, community-level predictions at the genetic level is constrained by the size and complexity of the experimental designs usually required. Breeding strategies should instead be compared using theoretically informed qualitative predictions. The need to estimate genetic covariances between traits measured both within and among species (for IIGE) is another obstacle, as the two are not determined by the exact same biological processes. We suggest future research directions and strategies to overcome these limits. Our synthesis offers an integrative theoretical framework for breeders interested in the genetic improvement of crop communities but also for scientists interested in the genetic bases of plant community functioning.
植物育种聚焦于基因型和种群水平，同时目标是在从作物覆盖到农业生态系统等更高生物多样性水平上产生影响。因此，跨嵌套生物多样性水平进行预测是间作实践发展面临的一项重大挑战。需要新的预测工具和概念来设计在作物群落水平上具有理想结果的育种策略。我们回顾了进化生态学领域的理论进展，以确定预测人工选择对群落水平表现影响的潜在可行方法。我们确定了三种主要方法，它们在群落水平上模拟种间接遗传效应（IIGEs）的方式有所不同：（1）群落遗传力方法估计由一个焦点物种在群落水平上诱导的IIGE的方差；（2）联合表型方法量化一组相互作用物种的直接遗传效应和IIGE之间的遗传限制；（3）群落性状遗传梯度方法将一个焦点物种的IIGE分解为其多元功能性状集。我们讨论了这些方法的潜在操作能力，并强调每种方法都是一般多性状和多物种选择指数的一个特例。因此，选择一种方法涉及关于育种目标和策略的假设和目标。在遗传水平上获得可靠的定量群落水平预测受到通常所需实验设计的规模和复杂性的限制。相反，育种策略应该使用理论上有依据的定性预测进行比较。估计物种内和物种间测量的性状之间的遗传协方差（用于IIGE）的必要性是另一个障碍，因为两者不是由完全相同的生物学过程决定的。我们提出了未来的研究方向和策略来克服这些限制。我们的综述为对作物群落遗传改良感兴趣的育种者以及对植物群落功能的遗传基础感兴趣的科学家提供了一个综合的理论框架。
