Invited review: Advances and challenges in application of feedomics to improve dairy cow production and health

How Does Nutrition Affect the Epigenetic Changes in Dairy Cows?

Dairy cows require a balanced diet that provides enough nutrients to support milk production, growth, and reproduction. Inadequate nutrition can lead to metabolic disorders, impaired fertility, and reduced milk yield. Recent studies have shown that nutrition can affect epigenetic modifications in dairy cows, which can impact gene expression and affect the cows' health and productivity. One of the most important epigenetic modifications in dairy cows is DNA methylation, which involves the addition of a methyl group to the DNA molecule. Studies have shown that the methylation status of certain genes in dairy cows can be influenced by dietary factors such as the level of methionine, lysine, choline, and folate in the diet. Other important epigenetic modifications in dairy cows are histone modification and microRNAs as regulators of gene expression. Overall, these findings suggest that nutrition can have a significant impact on the epigenetic regulation of gene expression in dairy cows. By optimizing the diet of dairy cows, it may be possible to improve their health and productivity by promoting beneficial epigenetic modifications. This paper reviews the main nutrients that can cause epigenetic changes in dairy cattle by analyzing the effect of diet on milk production and its composition.

Developmental programming: prenatal and postnatal consequences of hyperthermia in dairy cows and calves

With global warming, the incidence of heat stress in dairy cows is increasing in many countries. Temperatures outside the thermoneutral zone (heat stress) are one of the environmental factors with the greatest impact on milk production and reproductive performance of dairy cows. In addition to several biological mechanisms that may contribute to the effects of fetal programming, epigenetic modifications have also been investigated as possible mediators of the observed associations between maternal heat stress during late gestation and performance and health later in life. In utero programming of these offspring may coordinate changes in thermoregulation, mammary gland development, and milk production ability at different developmental stages. This review examines the effects of prenatal and postnatal hyperthermia on the developmental outcomes of dairy cows, as well as the physiological and molecular mechanisms that may be responsible for the negative phenotypic consequences of heat stress that persist throughout the neonatal and adult periods and may have multigenerational implications. The physiological and molecular mechanisms underlying the negative phenotypic consequences of heat stress are discussed. Research challenges in this area, future research recommendations, and therapeutic applications are also discussed. In summary, strategies to reduce heat stress during the dry period should consider not only the productivity of the pregnant cow but also the well-being of the newborn calf.

Applications of Omics Technology for Livestock Selection and Improvement

Conventional animal selection and breeding methods were based on the phenotypic performance of the animals. These methods have limitations, particularly for sex-limited traits and traits expressed later in the life cycle (e.g., carcass traits). Consequently, the genetic gain has been slow with high generation intervals. With the advent of high-throughput omics techniques and the availability of multi-omics technologies and sophisticated analytic packages, several promising tools and methods have been developed to estimate the actual genetic potential of the animals. It has now become possible to collect and access large and complex datasets comprising different genomics, transcriptomics, proteomics, metabolomics, and phonemics data as well as animal-level data (such as longevity, behavior, adaptation, etc.,), which provides new opportunities to better understand the mechanisms regulating animals’ actual performance. The cost of omics technology and expertise of several fields like biology, bioinformatics, statistics, and computational biology make these technology impediments to its use in some cases. The population size and accurate phenotypic data recordings are other significant constraints for appropriate selection and breeding strategies. Nevertheless, omics technologies can estimate more accurate breeding values (BVs) and increase the genetic gain by assisting the section of genetically superior, disease-free animals at an early stage of life for enhancing animal productivity and profitability. This manuscript provides an overview of various omics technologies and their limitations for animal genetic selection and breeding decisions.

Feedomics provides bidirectional omics strategies between genetics and nutrition for improved production in cattle

Increasing the efficiency and sustainability of cattle production is an effective way to produce valuable animal proteins for a growing human population. Genetics and nutrition are the 2 major research topics in selecting cattle with beneficial phenotypes and developing genetic potentials for improved performance. There is an inextricable link between genetics and nutrition, which urgently requires researchers to uncover the underlying molecular mechanisms to optimize cattle production. Feedomics integrates a range of omic techniques to reveal the mechanisms at different molecular levels related to animal production and health, which can provide novel insights into the relationships of genes and nutrition/nutrients. In this review, we summarized the applications of feedomics techniques to reveal the effect of genetic elements on the response to nutrition and investigate how nutrients affect the functional genome of cattle from the perspective of both nutrigenetics and nutrigenomics. We highlighted the roles of rumen microbiome in the interactions between host genes and nutrition. Herein, we discuss the importance of feedomics in cattle nutrition research, with a view to ensure that cattle exhibit the best production traits for human consumption from both genetic and nutritional aspects.

Nutritional Modulation, Gut, and Omics Crosstalk in Ruminants

Simple Summary

Over the last decade, animal nutrition science has been significantly developed, supported by the great advancements in molecular technologies. For scientists, the present "feedomics and nutrigenomics" era continues to evolve and shape how research is designed, performed, and understood. The new omics interpretations have established a new point of view for the nutrition–gene interaction, integrating more comprehensive findings from animal physiology, molecular genetics, and biochemistry. In the ruminant model, this modern approach addresses rumen microbes as a critical intermediate that can deepen the studies of diet–gut interaction with host genomics. The present review discusses nutrigenomics’ and feedomics’ potential contribution to diminishing the knowledge gap about the DNA cellular activities of different nutrients. It also presents how nutritional management can influence the epigenetic pathway, considering the production type, life stage, and species for more sustainable ruminant nutrition strategies.

Abstract

Ruminant nutrition has significantly revolutionized a new and prodigious molecular approach in livestock sciences over the last decade. Wide-spectrum advances in DNA and RNA technologies and analysis have produced a wealth of data that have shifted the research threshold scheme to a more affluent level. Recently, the published literature has pointed out the nutrient roles in different cellular genomic alterations among different ruminant species, besides the interactions with other factors, such as age, type, and breed. Additionally, it has addressed rumen microbes within the gut health and productivity context, which has made interpreting homogenous evidence more complicated. As a more systematic approach, nutrigenomics can identify how genomics interacts with nutrition and other variables linked to animal performance. Such findings should contribute to crystallizing powerful interpretations correlating feeding management with ruminant production and health through genomics. This review will present a road-mapping discussion of promising trends in ruminant nutrigenomics as a reference for phenotype expression through multi-level omics changes.

Multi-omics revealed the effects of rumen-protected methionine on the nutrient profile of milk in dairy cows

Cow's milk is a highly-nutritious dairy product part of human diet worldwide. Rumen-protected methionine (RPM) is widely used to improve lactation performance of dairy cows, but understanding of the effects of RPM on milk nutrients composition are still limited. In this study, twenty mid-lactating dairy cows were supplemented with 20 gm/day RPM for 8 weeks to investigate the responses of milk nutritional composition to RPM. Metabolomics was applied for analyzing milk metabolites and 16S rRNA gene sequencing was used for analysis of rumen microbial composition. Milk fat content and yield were significantly increased after RPM supplementation. Totally 443 compounds belonging to 15 classes were identified, among which 15 metabolites were significantly changed. The functional nutrient α-ketoglutaric acid were significantly increased in the milk after RPM supplementation. We found 48 significantly differing bacterial genera in the rumen after supplementing RPM. Multi-omics integrated analysis revealed the higher abundance of Acetobacter, unclassified_f_Lachnospiraceae and Saccharofermentan contributed to the improved milk fat. In addition, the enriched abundance of Thermoactinomyces, Asteroleplasma, and Saccharofermentan showed positive correlations with higher α-ketoglutaric acid of milk. Our results uncover the metabolomic fingerprint and the key functional metabolites in the milk after supplementing RPM in dairy cows, as well as the key rumen bacteria associated with them. These findings provide novel insights into the development of functional dairy products that enriched the functional nutrient α-ketoglutaric acid or high milk fat.

Genome-Wide Association Study Provides Insights into Important Genes for Reproductive Traits in Nelore Cattle

Simple Summary

In this study, we investigated the association between single nucleotide polymorphisms (SNPs) and reproductive traits in order to identify candidate genes and biological pathways associated with these traits in Nelore beef cattle. The genome-wide association analysis revealed genomic regions that could explain part of the genetic variance of the studied traits. The results revealed genes with important functions for reproductive traits, such as fertility and precocity. Some genes were associated with more than one trait, being important for reproductive efficiency. The identification of candidate genes that were associated with the studied traits as well as genes enriched in the functional terms and pathways may be useful for exploring the genetic architecture underlying reproductive traits and may be used in Nelore breeding programs.

Abstract

The identification of genomic regions associated with reproductive traits as well as their biological processes allows a better understanding of the phenotypic variability of these traits. This information could be applied to animal breeding programs to accelerate genetic gain. The aim of this study was to evaluate the association between single nucleotide polymorphisms (SNP) with a scrotal circumference at 365 days of age (SC365) and at 450 days of age (SC450), gestation length (GL) as a calf trait, age at first calving (AFC), accumulated productivity (ACP), heifer early calving until 30 months (HC30), and stayability (STAY) traits, in order to identify candidate genes and biological pathways associated with reproductive traits in Nelore cattle. The data set consisted of pedigree, phenotypes, and genotypes of Nelore cattle from the “Associação Nacional de Criadores e Pesquisadores” (ANCP). The association analyses were performed using the Weighted Single-Step Genome-Wide Association method; the regions, consisting of 10 consecutive SNP, which explained more than 0.5% of additive genetic variance, were considered as a significant association. A total of 3, 6, 7, 5, 10, 25, and 12 windows were associated with SC355, SC450, GL, AFC, ACP, HC30, and STAY, respectively. The results revealed genes with important functions for reproductive traits, such as fertility and precocity. Some genes were associated with more than one trait, among them CAMK1D, TASP1, ACOXL, RAB11FIP5, and SFXN5. Moreover, the genes were enriched in functional terms, like negative regulation of fat cell differentiation, fatty acid alpha-oxidation, and sphingolipids signaling pathway. The identification of the genes associated with the traits, as well as genes enriched in the terms and pathway mentioned above, should contribute to future biological validation studies and may be used as candidate genes in Nelore breeding programs.

The Dispensable Surplus Dairy Calf: Is This Issue a "Wicked Problem" and Where Do We Go From Here?

Surplus dairy calves consist of all dairy bull calves and any heifer calves not needed as replacements for the milking herd. The fate of these surplus calves varies by region; for example, in Australia and New Zealand they are often sold as "bobby" calves and slaughtered within the first weeks of life; whereas, in North America they are normally sold within the first weeks of life but reared for 16-18 weeks as veal or longer as dairy beef. Regardless of region, demand for these calves is often very low, driving down prices and in some cases leaving farmers with no alternative options other than on-farm euthanasia. The notion that dairy cows must give birth to produce milk and that the calves are immediately separated from the dam, many of which will end up immediately being sold as surplus calves, has become a topic of public concern. These concerns have increased given the growing number of pictures and stories in the media of on-farm euthanasia, dairy calves being transported at very young ages and frequently receiving sub-standard levels of care. In this paper we describe the status quo of this complex, value-laden issue that without transformative change is at great risk for continued criticism from the public. Moreover, despite many attempts at refinement of the existing approach (i.e., the pursuit of technical improvements), little has changed in terms of how these surplus dairy calves are managed and so we predict that on its own, this approach will likely fail in the long run. We then set out how the current surplus calf management practices could be viewed to fit the definition of a "wicked problem." We conclude by calling for new research using participatory methodologies that include the voice of all stakeholders including the public, as a first step in identifying sustainable solutions that resonate with both society and the livestock industry. We briefly discuss three participatory methodologies that have successfully been used to develop sustainable solutions for other complex problems. Adoption of these types of methodologies has the potential to help position the dairy industry as a leader in sustainable food production.

Genomic Analysis, Progress and Future Perspectives in Dairy Cattle Selection: A Review

Genomics comprises a set of current and valuable technologies implemented as selection tools in dairy cattle commercial breeding programs. The intensive progeny testing for production and reproductive traits based on genomic breeding values (GEBVs) has been crucial to increasing dairy cattle productivity. The knowledge of key genes and haplotypes, including their regulation mechanisms, as markers for productivity traits, may improve the strategies on the present and future for dairy cattle selection. Genome-wide association studies (GWAS) such as quantitative trait loci (QTL), single nucleotide polymorphisms (SNPs), or single-step genomic best linear unbiased prediction (ssGBLUP) methods have already been included in global dairy programs for the estimation of marker-assisted selection-derived effects. The increase in genetic progress based on genomic predicting accuracy has also contributed to the understanding of genetic effects in dairy cattle offspring. However, the crossing within inbred-lines critically increased homozygosis with accumulated negative effects of inbreeding like a decline in reproductive performance. Thus, inaccurate-biased estimations based on empirical-conventional models of dairy production systems face an increased risk of providing suboptimal results derived from errors in the selection of candidates of high genetic merit-based just on low-heritability phenotypic traits. This extends the generation intervals and increases costs due to the significant reduction of genetic gains. The remarkable progress of genomic prediction increases the accurate selection of superior candidates. The scope of the present review is to summarize and discuss the advances and challenges of genomic tools for dairy cattle selection for optimizing breeding programs and controlling negative inbreeding depression effects on productivity and consequently, achieving economic-effective advances in food production efficiency. Particular attention is given to the potential genomic selection-derived results to facilitate precision management on modern dairy farms, including an overview of novel genome editing methodologies as perspectives toward the future.

Impact of Nutrients on the Hoof Health in Cattle

Lameness is currently one of the most important and economically demanding diseases in cattle. It is manifested in a change in locomotion that is associated with lesions, especially the pelvic limbs. The disease of the hoof is painful, affecting the welfare of dairy cows. Important factors that influence the health of the limbs include nutrition, animal hygiene, stable technology, and genetic and breeding predispositions. Nutrition is one of the basic preventive factors affecting the quality and growth of the hoof horn, and the associated prevalence of hoof disease. The strength and structure of the hoof horn are affected by the composition of the feed ration (amino acids, minerals, vitamins, and toxic substances contaminating the feed ration, or arising in the feed ration as metabolites of fungi).

Variance components using genomic information for 2 functional traits in Italian Simmental cattle: Calving interval and lactation persistency

Functional traits, such as fertility and lactation persistency, are becoming relevant breeding goals for dairy cattle. Fertility is a key element for herd profitability and animal welfare; in particular, calving interval (CIN) is an indicator of female fertility that can be easily recorded. Lactation persistency (LPE; i.e., the ability of a cow to maintain a high milk yield after the lactation peak) is economically important and is related to several other traits, such as feed efficiency, health, and reproduction. The selection of these functional traits is constrained by their low heritability. In this study, variance components for CIN and LPE in the Italian Simmental cattle breed were estimated using genomic and pedigree information under the single-step genomic framework. A data set of 594,257 CIN records (from 275,399 cows) and 285,213 LPE records (from 1563,389 cows) was considered. Phenotypes were limited up to the third parity. The pedigree contained about 2 million animals, and 7,246 genotypes were available. Lactation persistency was estimated using principal component analysis on test day records, with higher values of the second extracted principal component (PC2) values associated with lower LPE, and lower PC2 values associated with higher LPE. Heritability of CIN and LPE were estimated using single-trait repeatability models. A multiple-trait analysis using CIN and production traits (milk, fat, and protein yields) was performed to estimate genetic correlations among these traits. Heritability for CIN in the single-trait model was low (0.06 ± 0.002). Unfavorable genetic correlations were found between CIN and production traits. A measure of LPE was derived using principal component analysis on test day records. The heritability and repeatability of LPE were 0.11 ± 0.004 and 0.20 ± 0.02, respectively. Genetic correlation between CIN and LPE was weak but had a favorable direction. Despite the low heritability estimates, results of the present work suggest the possibility of including these traits in the Italian Simmental breeding program. The use of a single-step approach may provide better results for young genotyped animals without their own phenotypes.