**5. Conclusions**

*Gene Expression and Control*

ruminant products, and reduce carbon footprint.

ated with meat quality traits in beef cattle [123].

*Example of nutrigenomics linkage between beef and dairy cattle.*

in developing countries, and such demand is expected to increase in the future [119]. To face this demand, advancements in ruminant nutrition and physiology will require improvements on feed efficiency and development of novel functional foods from ruminants by enriching specific compounds associated with health benefits in humans. The latter will need a deep understanding and wealth of knowledge of molecular regulatory mechanisms in response to physiological conditions and nutrition. In this context, this vast amount of multilayered data in terms of mRNA, proteins, metabolites, and phenotypes can only be undertaken with powerful tools such as omics technologies and bioinformatics. In fact, these are the foundations of modern system biology, a field of study with the aim to enhance the understanding of complex biological models and interactions occurring within cells and tissues. Understanding this complexity and the outcomes of nutritional interventions and physiological conditions will allow the formulation of novel theories and ideas to enhance feed efficiency, development of new functional foods derived from

Even though the outcome is different, there are similarities in dairy and beef cattle from a nutrigenomic perspective. For instance, both the synthesis of milk fat in dairy cows and the synthesis of intramuscular fat in beef steers are regulated by a similar network of TF. Nutrients or stimulus received with the diet (PUFAs, insulin, etc.), activates PPARα in the liver of the dairy cow and PPARγ in the intramuscular preadipocyte of a beef steer. The activated PPARs form a heterodimer with retinoic X receptor alpha (RXRA), leading to the upregulation of their lipogenesis-related target genes (**Figure 2**). Furthermore, in the same way, the activation of the PI3K/ Akt/mTOR signaling pathway will lead to the synthesis of milk protein in dairy cows [120], the activation of the same metabolic pathway might lead to muscle hypertrophy in beef cattle, but this is a concept that has not been completely elucidated [121]. It is also worth to mention the importance of fatty acid binding proteins (FABPs) in ruminants, which bind and transport LCFA. FABP4 affects milk yield and milk protein content, both economically important traits in the dairy industry [122], and FABP4 also presents gene polymorphisms that have been associ-

**134**

**Figure 2.**

The general nutrigenomic model for ruminants needs to be updated based on emerging nuance information with the ever-growing pace in ruminant nutrition research with "omics" technologies. The dissection of what intermediate components or processes such as intermediate metabolites, signal transduction, TF, etc., are utilized by specific nutrients will allow for accurate predictions of the nutrigenomic outcomes of such nutrients in a practical setting. However, the multilayered and multifactorial nature of the nutrigenomic model will require the implementation of additional tools such as system biology and network theory in order to have a more holistic approach to understand how nutrients regulate milk synthesis or skeletal muscle gain and marbling.

One of the greatest challenges in ruminant nutrigenomics is to account for the final products from rumen fermentation, where several factors such as rate of passage, intake, particle size of the diet can affect rumen fermentation and kinetics. The latter can be avoided by feeding nutrients encapsulated or protected from ruminal degradation; however, this does not eliminate the need to account for the substantial impact the rumen fermentation and its products may have on the overall nutrigenomic effect from a particular diet. Because of this reason, the resurgence of the field of the microbiome in ruminant nutrition research promise to add valuable information on rumen microbes response to nutrients in the diet and correlate this with final nutrigenomic responses at the whole animal level.

Our understanding of the impact of nutrition on regulatory mechanisms at the cellular level in the ruminant animal has grown an accelerated pace over the last decades. As pointed out by Drackley 12 year ago [125], the marriage between "omics" technologies with measurements of tissue metabolism and the final performance (e.g., milk yield and skeletal muscle gain) has been enlightening and essential to identify key responses to nutritional changes and physiology. However, there is still too much to learn in the complex nutrient-gene interactions in the context of the ruminant animal. The future of nutrigenomics in ruminants is to develop technologies and algorithms to predict the final molecular outcomes of nutrients and diets fed to ruminants in a practical setting. This monumental task can only be accomplished by generating a wealth of knowledge in several orders of magnitude of what we currently have on nutrigenomics in ruminants.

*Gene Expression and Control*
