在选择压力下模拟跨代全息基因组的RITHMS
Simulating transgenerational hologenomes under selection with RITHMS
AI总结：
RITHMS通过整合微生物群特性与选择策略，模拟跨代全息基因组，用于提升育种预测与微生物多样性平衡。
摘要：
一个合生体由宿主生物及其微生物群组成。在动物育种的背景下，合生体可以被视为选择作用的单一单位。因此，将微生物组数据整合到基因组预测模型中可能是一种改进表型和遗传价值预测的有前途的方法。然而，目前缺乏全息基因组跨代数据来验证这一假设，因此为了填补这一空白，我们提出了一种新的模拟框架。我们的方法，即基于全息基因组模型的模拟器RITHMS的R实现，是一个开源包。它基于模块化育种计划模拟器（MoBPS）包中的模拟跨代基因型，并纳入了微生物群的独特特性，特别是垂直和水平传播以及环境和宿主遗传对调节的影响。此外，RITHMS能够考虑多种选择策略，并适应不同的遗传架构。我们使用RITHMS在多种场景下模拟了跨代全息基因组数据，这些场景包括不同的遗传率、微生物性状和微生物群传播性。我们发现模拟数据在各代中准确保留了关键特征，特别是微生物多样性指标，表现出预期的菌群间相关性行为，以及垂直和水平传播的调节、对环境效应的响应以及根据选择策略演变的表型值。我们的结果支持了我们模拟框架的相关性，并展示了其可能用于构建平衡遗传增益和微生物多样性选择指数以及评估部分观察到的微生物群数据影响的用途。RITHMS是一个先进的、灵活的工具，用于在选择压力下生成跨代全息基因组，以整合遗传、微生物群和环境之间的复杂相互作用。
英文摘要：
A holobiont is made up of a host organism together with its microbiota. In the context of animal breeding, the holobiont can be viewed as the single unit upon which selection operates. Therefore, integrating microbiota data into genomic prediction models may be a promising approach to improve predictions of phenotypic and genetic values. Nevertheless, there is a paucity of hologenomic transgenerational data to address this hypothesis, and thus to fill this gap, we propose a new simulation framework. Our approach, an R Implementation of a Transgenerational Hologenomic Model-based Simulator (RITHMS) is an open-source package. It builds upon simulated transgenerational genotypes from the Modular Breeding Program Simulator (MoBPS) package and incorporates distinctive characteristics of the microbiota, notably vertical and horizontal transmission as well as modulation due to the environment and host genetics. In addition, RITHMS can account for a variety of selection strategies and is adaptable to different genetic architectures. We simulated transgenerational hologenomic data using RITHMS under a wide variety of scenarios, varying heritability, microbiability, and microbiota transmissibility. We found that simulated data accurately preserved key characteristics across generations, notably microbial diversity metrics, exhibited the expected behavior in terms of correlation between taxa and of modulation of vertical and horizontal transmission, response to environmental effects and the evolution of phenotypic values depending on selection strategy. Our results support the relevance of our simulation framework and illustrate its possible use for building a selection index balancing genetic gain and microbial diversity and for evaluating the impact of partially observed microbiota data. RITHMS is an advanced, flexible tool for generating transgenerational hologenomes under selection that incorporate the complex interplay between genetics, microbiota and environment.
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