Cattle genomics and its implications for future nutritional strategies for dairy cattle

Genotype-by-environment interactions in beef and dairy cattle populations: A review of methodologies and perspectives on research and applications

Modern livestock production systems are characterized by a greater focus on intensification, involving managing larger numbers of animals to achieve higher productive efficiency and animal health and welfare within herds. Therefore, animal breeding programs need to be strategically designed to select animals that can effectively enhance production performance and animal welfare across a range of environmental conditions. Thus, this review summarizes the main methodologies used for assessing the levels of genotype-by-environment interaction (G × E) in cattle populations. In addition, we explored the importance of integrating genomic and phenotypic information to quantify and account for G × E in breeding programs. An overview of the structure of cattle breeding programs is provided to give insights into the potential outcomes and challenges faced when considering G × E to optimize genetic gains in breeding programs. The role of nutrigenomics and its impact on gene expression related to metabolism in cattle are also discussed, along with an examination of current research findings and their potential implications for future research and practical applications. Out of the 116 studies examined, 60 and 56 focused on beef and dairy cattle, respectively. A total of 83.62% of these studies reported genetic correlations across environmental gradients below 0.80, indicating the presence of G × E. For beef cattle, 69.33%, 24%, 2.67%, 2.67%, and 1.33% of the studies evaluated growth, reproduction, carcass and meat quality, survival, and feed efficiency traits, respectively. By contrast, G × E research in dairy cattle populations predominantly focused on milk yield and milk composition (79.36% of the studies), followed by reproduction and fertility (19.05%), and survival (1.59%) traits. The importance of G × E becomes particularly evident when considering complex traits such as heat tolerance, disease resistance, reproductive performance, and feed efficiency, as highlighted in this review. Genomic models provide a valuable avenue for studying these traits in greater depth, allowing for the identification of candidate genes and metabolic pathways associated with animal fitness, adaptation, and environmental efficiency. Nutrigenetics and nutrigenomics are emerging fields that require extensive investigation to maximize our understanding of gene-nutrient interactions. By studying various transcription factors, we can potentially improve animal metabolism, improving performance, health, and quality of products such as meat and milk.

The evolutionary dynamics of microRNAs in domestic mammals

MiRNAs are crucial regulators of gene expression found across both the plant and animal kingdoms. While the number of annotated miRNAs deposited in miRBase has greatly increased in recent years, few studies provided comparative analyses across sets of related species, or investigated the role of miRNAs in the evolution of gene regulation. We generated small RNA libraries across 5 mammalian species (cow, dog, horse, pig and rabbit) from 4 different tissues (brain, heart, kidney and testis). We identified 1676 miRBase and 413 novel miRNAs by manually curating the set of computational predictions obtained from miRCat and miRDeep2. Our dataset spanning five species has enabled us to investigate the molecular mechanisms and selective pressures driving the evolution of miRNAs in mammals. We highlight the important contributions of intronic sequences (366 orthogroups), duplication events (135 orthogroups) and repetitive elements (37 orthogroups) in the emergence of new miRNA loci. We use this framework to estimate the patterns of gains and losses across the phylogeny, and observe high levels of miRNA turnover. Additionally, the identification of lineage-specific losses enables the characterisation of the selective constraints acting on the associated target sites. Compared to the miRBase subset, novel miRNAs tend to be more tissue specific. 20 percent of novel orthogroups are restricted to the brain, and their target repertoires appear to be enriched for neuron activity and differentiation processes. These findings may reflect an important role for young miRNAs in the evolution of brain expression plasticity. Many seed sequences appear to be specific to either the cow or the dog. Analyses on the associated targets highlight the presence of several genes under artificial positive selection, suggesting an involvement of these miRNAs in the domestication process. Altogether, we provide an overview on the evolutionary mechanisms responsible for miRNA turnover in 5 domestic species, and their possible contribution to the evolution of gene regulation.

The Use of "Omics" in Lactation Research in Dairy Cows

“Omics” is the application of genomics, transcriptomics, proteomics, and metabolomics in biological research. Over the years, tremendous amounts of biological information has been gathered regarding the changes in gene, mRNA and protein expressions as well as metabolites in different physiological conditions and regulations, which has greatly advanced our understanding of the regulation of many physiological and pathophysiological processes. The aim of this review is to comprehensively describe the advances in our knowledge regarding lactation mainly in dairy cows that were obtained from the “omics” studies. The “omics” technologies have continuously been preferred as the technical tools in lactation research aiming to develop new nutritional, genetic, and management strategies to improve milk production and milk quality in dairy cows.

Global Metabolic Reconstruction and Metabolic Gene Evolution in the Cattle Genome

The sequence of cattle genome provided a valuable opportunity to systematically link genetic and metabolic traits of cattle. The objectives of this study were 1) to reconstruct genome-scale cattle-specific metabolic pathways based on the most recent and updated cattle genome build and 2) to identify duplicated metabolic genes in the cattle genome for better understanding of metabolic adaptations in cattle. A bioinformatic pipeline of an organism for amalgamating genomic annotations from multiple sources was updated. Using this, an amalgamated cattle genome database based on UMD_3.1, was created. The amalgamated cattle genome database is composed of a total of 33,292 genes: 19,123 consensus genes between NCBI and Ensembl databases, 8,410 and 5,493 genes only found in NCBI or Ensembl, respectively, and 266 genes from NCBI scaffolds. A metabolic reconstruction of the cattle genome and cattle pathway genome database (PGDB) was also developed using Pathway Tools, followed by an intensive manual curation. The manual curation filled or revised 68 pathway holes, deleted 36 metabolic pathways, and added 23 metabolic pathways. Consequently, the curated cattle PGDB contains 304 metabolic pathways, 2,460 reactions including 2,371 enzymatic reactions, and 4,012 enzymes. Furthermore, this study identified eight duplicated genes in 12 metabolic pathways in the cattle genome compared to human and mouse. Some of these duplicated genes are related with specific hormone biosynthesis and detoxifications. The updated genome-scale metabolic reconstruction is a useful tool for understanding biology and metabolic characteristics in cattle. There has been significant improvements in the quality of cattle genome annotations and the MetaCyc database. The duplicated metabolic genes in the cattle genome compared to human and mouse implies evolutionary changes in the cattle genome and provides a useful information for further research on understanding metabolic adaptations of cattle.

Genomic organization and evolution of ruminant lysozyme c genes

Ruminant stomach lysozyme is a long established model of adaptive gene evolution. Evolution of stomach lysozyme function required changes in the site of expression of the lysozyme c gene and changes in the enzymatic properties of the enzyme. In ruminant mammals, these changes were associated with a change in the size of the lysozyme c gene family. The recent release of near complete genome sequences from several ruminant species allows a more complete examination of the evolution and diversification of the lysozyme c gene family. Here we characterize the size of the lysozyme c gene family in extant ruminants and demonstrate that their pecoran ruminant ancestor had a family of at least 10 lysozyme c genes, which included at least two pseudogenes. Evolutionary analysis of the ruminant lysozyme c gene sequences demonstrate that each of the four exons of the lysozyme c gene has a unique evolutionary history, indicating that they participated independently in concerted evolution. These analyses also show that episodic changes in the evolutionary constraints on the protein sequences occurred, with lysozyme c genes expressed in the abomasum of the stomach of extant ruminant species showing the greatest levels of selective constraints.

Recent developments in lipid metabolism in ruminants – the role of fat in maintaining animal health and performance

Optimising farm animal performance has long been the key focus of worldwide livestock production research. Advances in the understanding of metabolism/phenotype associations have outlined the central role of the lipid metabolism of farm animals for economically relevant phenotypic traits, such as animal health (immune status, fertility/reproductive capacity, adaptability/metabolic flexibility, robustness, well being) and performance aspects (meat/milk quality and quantity) and have led to an extensive exploitation of lipid metabolism manipulation strategies (e.g. tailored nutritional regimes, alimentary/intravenous fat supplementation, rumen-protected fat feeding, hormone application). This contribution gives an overview of established concepts to tailor animals’ lipid metabolism and highlights novel strategies to expand these application-oriented approaches via improved analysis tools, omics-approaches, cell model systems and systems biology methods.