HoloSimR: a comprehensive framework for simulating breeding programs including the hologenome scenario

Abstract

Background Including microbiome information in breeding schemes may be helpful to improve the selection response of livestock populations. However, the complexity of the microbiome makes modelling across species and traits difficult. The estimation of the microbiability and the identification of the microbial species are highly dependent on the methodology used. Indeed, it is complicated to decide which is the best one because we fail to know the true underlying scenario. This study proposes an R package named HoloSimR for simulating the coevolution of the genome and the microbiota under a selection process. HoloSimR allows the user to explore the effect of the microbiota on the phenotypic response to selection and the effects of the environment, host genetics and symbiosis between microbial species on the composition of the microbiota. Results To illustrate the use of HoloSimR, a divergent selection process was simulated over ten generations. This example considered the most complete simulation that the HoloSimR package can perform; a divergent selection process, for six different scenarios, and with and without the symbiosis effect. The scenarios simulated the different approximations for calculating the phenotype (genome only, microbiota or both), as well as the host genetic effect on the microbiota composition. The most complex example took 898.47 minutes (~ 15 hours) on a standard laptop with 16 GB of RAM, for ten generations of selection, repeated ten times. Conclusion HoloSimR provides a valuable research platform, allowing researchers to test hypotheses and develop new approaches in a controlled in silico environment before applying them to real-world breeding programmes. This ultimately advances our understanding of host-microbiota interactions in the context of animal breeding.