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.

翻译：全息生物体由宿主生物及其微生物群共同构成。在动物育种背景下，全息生物体可被视为选择操作的基本单元。因此，将微生物群数据整合到基因组预测模型中，可能成为提高表型和遗传价值预测精度的有效途径。然而，目前缺乏用于验证该假设的跨代全息基因组数据。为填补这一空白，我们提出了一种新的模拟框架。我们的方法——跨代全息基因组模型模拟器的R语言实现（RITHMS）——是一个开源软件包。该工具基于模块化育种程序模拟器（MoBPS）生成的跨代模拟基因型，并整合了微生物群的关键特征，特别是垂直与水平传递机制，以及环境和宿主遗传因素的调控作用。此外，RITHMS能够兼容多种选择策略，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，包括不同的遗传力、微生物作用力和微生物传递率。研究发现：模拟数据能准确保持跨代关键特征（尤其是微生物多样性指标）；在分类群相关性、垂直/水平传递调控、环境效应响应以及表型值随选择策略的演化等方面均表现出预期行为。我们的结果验证了该模拟框架的适用性，并展示了其在构建平衡遗传增益与微生物多样性的选择指数、评估部分观测微生物群数据影响等方面的潜在应用价值。RITHMS是一个先进且灵活的工具，能够生成包含遗传、微生物群与环境复杂互作的选择作用下跨代全息基因组数据。