Microbiome

Genetic selection of livestock leveraging gut microbial information

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Abstract

Gut microbial information can provide a large amount of information. This can be used for precise nutrition, management, and genetic improvement. Ultimately, gut microbial information can be considered as a layer of information in the 'phenomics' framework, but its conceptual and practical use is not well defined yet. Recent advances in research are shedding light on the intricate relationship between the genetic background of the host and the microbial symbionts that inhabit the gastrointestinal tract. While the former is known to affect the latter, we also see that the expression of the host's genetic potential can be mediated or moderated by the symbiont microbiota. This dynamic is better understood when we analyse its evolution throughout the life of the host, highlighting dynamic changes in gut microbial colonisation from birth to maturity. Here, the symbiotic link between the host and microbiota plays a pivotal role in selection and evolution. With the aim of implementing host selection, we propose an analytical model for microbiome composition, incorporating the influence of host genes, maternal effects, and the environment. The environmental impact on the microbiome is modelled as a sum of different factors (e.g. diet, stress, climate). We compare different ways to approach microbial analysis, with special focus on the use of the entero-signatures. The microbiota information can be used in genomic prediction models. The microbiota effect can be modelled as a whole, with the community make-up affecting the trait, or decomposed in its genetic and environmental components, or as a mediator of host genetic effects. The microbiota can also be an indicator trait to be included in the selection index. Literature reports contrasting results for the any of approaches mentioned. We aim at connecting the dots between the data structure, the model implemented, and the results obtained. Also, we aim at pointing out a number of things that could hamper the successfull outcome of the analysis.

Keywords: 2026

How to Cite:

Tiezzi, F., (2026) “Genetic selection of livestock leveraging gut microbial information”, World Congress on Genetics Applied to Livestock Production Digital Archive 2026(1): 2278689. doi: https://doi.org/10.31274/wcgalp.23432

Rights: 1