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From a sample CHAPTER for the publication: "Topics in Biotechnology and Animal Nutrition for Feeding and Production," - Vol III-in the set, (c) D. A. Flores. Skye Blue Publications. Port Coquitlam, B. C. Canada V3B 1G3.
Chapter 12. Nutrigenomics and Feeding for Translational Nutrition with Farm Animals.
The Problem and the Potential.
There is now a growing field exploring possible relationships between nutrient intake and genetic variation in response to them and the effect of nutritionals on genetic expression, in this case, with feed additives, called the field of nutrigenomics. We have placed in terms of a commitment to highlight this area of animal nutrition and further advancing it in concept innovation.
Translational or "tailor-made", in nature, this can be optimized or fine-tuned for delivery and for the desired results in both the fields of animal and human nutrition, in theory.
Qualities and Productive Response by Phenotypic Traits from Anabolism.
In a recent review (M. Bionez, et al., 2015) they stated that dietary compounds interact with transcription factors (TFs) with greatest potential showing for fatty acids, amino acids, level of feed intake and level of energy intake. The earliest and best e. g. of this known was interaction between C12-conjugated linoleic acid interacting with t10 involving sterol regulatory binding protein 1 (SREBP1) resulting in MF synthesis inhibition.
Another recent review (M. M. Ladeira et al., 2016) has also described a major investigation into dietary factors affect ing lipogenesis with use of different dietary sources of: PUFAs, starch concentration, forage ratios and vitamin; the nutrients or dietary components involved are believed to change lipogenesis in muscle ( i. e. the marbling effect on beef) via nuclear receptors (e. g. peroxisome proliferator-activated receptors (PPAR) and SREBPs (mentioned previously), and in turn, transcription factors at the level of DNA and together with their mRNA and their potentiated metabolic action.
Given the various forages and grains in animal feeding utilizable with use of feed enzyme treatments in studies where anabolic signaling markers can be related to explain growth and body composition response to increased nutrient inputs from treatments, for e. g., ensilage with enzyme additions with improvements in digestible energy (DE), metabolizable energy (ME), organic matter intake (OMI) and flow of duodenal amino acids (DAAs), and the feeding of functional amino acids (viz. selected one including histidine (HIS), an emerging one at this time, in addition methionine (MET) and leucine (LEU), it remains to be seen if there is scope in the identification, characterization and enumeration of markers in anabolic signaling at this time as the field is still in its infancy, including supplement feeding with functional ingredients and nutritionals. HIS has showed improvements is lactational performance in dairy cows given supplements. Sows and piglets have also improved reproductive performance and growth and rates of morbidity.
Genetic Markers and their Location via Quantitative Trait Loci (QTLs): determining a gene marker's locus.
A note on QTLs. Large herd backcroses with only one genotype resulting are performed and traits measured or asayed for each group with the genetic markers which indicates both the location and effect of the marker on the phenotype. A t-statistic is derived by an analysis of variance (ANOVA) to compare averages between groups. The QTL is usually not in the alleles itself but a closely located or related marker. The markers are variable sequences of DNA identified by the researcher who eventually locates the marker near an allele on a chromosomal number in offspring related or responsible for phenotypic traits. Genes may later be bracketed as candidates, after sequencing DNA, including their specific SNPs (i. e. single-base mutations) of interest to the particular effect on the phenotypic trait.
Optimizing Supplement Feeding of Farm Animals as a Form of Translational Nutrition.
Unlike in the health field, farmers when feeding nutritionally have in mind the ends of productivity such as: 1) the quality of the product, for e. g., improving the milk fat (MF) profile of milk or lipids profile with cholesterol in eggs with polyunsatu-rated fatty acids, PUFAs, 2) the feed efficiency towards individual or sets of nutrients that may act synergistically towards a productive end, 3) total product yield and as broken down by components (e. g. lean body mass (LBM), marbling, carcass yield, dressed weight, meat cuts and their yield), and all not on an individual basis as would be true for humans as feeding practices would make this prohibitive.
The next frontier for translational nutrition could be on an individual basis if relatable to health of the animal and of course their welfare or well-being over above those other factors more related to production.
As far as is can be reasoned intuitively the unit size or parameter amongst individual animals in translational approaches would be to address each animal's pedigree or degree of breeding for each trait bred or to any significant subgroup as typically in a herd subgroup, but not as we would expect, individually, per se, unless health-related as was referred to above.
There is already true at SkyeBlue in its beginnings regards pro-active Vit D-like drug supposedly with translational nutrition for immune health or balance and well-being or welfare. Productivity is expected to improve as a result in future.
It can be that the field and investigation of farm animal nutrigenomics is in its infancy and that little evidence, if any, in the literature addresses this subject matter. Because this begs the matter of opening yet another novel issue in a so-called "precision agriculture" in animal nutrition, now a growing movement in Australia in agro-cropping, as one country, and being taught through study exchange with exposure to Filipino scientists. We will monitor the field and continue to report on any new areas of interest in the field of agriculture for the future.
M. Bionez, J. J. Loor and J. Osorio. 2015. Nutrigenomics in Dairy Cows: nutrients, transcription factors and techniques. J. Ani. Sci. 93(12): 5531-5553.
M. M. Ladeira, J. P. Schoonmaker, M. P. Gionbelli, J. C. Dias, T. R. Gionbelli, J. R. Carvalho, and P. D. Teixeira. 2016. Nutrigenomics and Beef Quality: A Review about Lipogenesis. Int. J. Mol. Sci. 17(6): 918-954.
Last update of this entry: December 06, 2021