Residual feed intake (RFI), a measure of feed efficiency (FE), is defined as the difference between the observed and the predictable feed intake considering size and growth of the animal. It is extremely important to beef production systems due to its impact on the allocation of land areas to alternative agricultural production, animal methane emissions, food demand and cost of production. Global differential gene expression analysis between high and low RFI groups (HRFI and LRFI: less and more efficient, respectively) revealed 73 differentially expressed (DE) annotated genes in Longissimus thoracis (LT) muscle of Nelore steers. These genes are involved in the overrepresented pathways Metabolism of Xenobiotics by Cytochrome P450 and Butanoate and Tryptophan Metabolism. Among the DE transcripts were several proteins related to mitochondrial function and the metabolism of lipids. Our findings indicate that observed gene expression differences are primarily related to metabolic processes underlying oxidative stress. Genes involved in the metabolism of xenobiotics and antioxidant mechanisms were primarily down-regulated, while genes responsible for lipid oxidation and ketogenesis were up-regulated in HRFI group. By using LT muscle, this study reinforces our previous findings using liver tissue and reveals new genes and likely tissue-specific regulators playing key-roles in these processes.

Improving feed efficiency (FE) is a major goal of pig breeding, reducing production costs and providing sustainability to the pig industry. Reliable predictors for fe could assist pig producers. We carried out untargeted blood metabolite profiling in uncastrated males from Danbred Duroc (n = 59) and Danbred Landrace (n = 50) pigs at the beginning and end of a FE testing phase to identify biomarkers and biological processes underlying fe and related traits. By applying linear modeling and clustering analyses coupled with WGCNA framework, we identified 102 and 73 relevant metabolites in Duroc and Landrace based on two sampling time points. Among them, choline and pyridoxamine were hub metabolites in Duroc in early testing phase, while, acetoacetate, cholesterol sulfate, xanthine, and deoxyuridine were identified in the end of testing. In Landrace, cholesterol sulfate, thiamine, L-methionine, chenodeoxycholate were identified at early testing phase, while, D-glutamate, pyridoxamine, deoxycytidine, and L-2-aminoadipate were found at the end of testing. Validation of these results in larger populations could establish fe prediction using metabolomics biomarkers. We conclude that it is possible to identify a link between blood metabolite profiles and FE. These results could lead to improved nutrient utilization, reduced production costs, and increased fe.With the expanding human population and requirement for nutrient-rich food, there is an increasing demand for improvement of meat production, but simultaneously, to decrease the input costs in terms of feed 1 . Thus, feed efficiency (FE) is the most important trait in commercial pig farming 2 as increasing the amount of meat produced per feed is beneficial both economically and environmentally. Thereby, improving FE is beneficial for producers and increases the sustainability of pork meat production. Fortunately, FE is a highly heritable trait in Danish pigs (ranging from 0.34 in Duroc to 0.40 in Landrace), thus suitable for the genetic selection of pigs with high breeding values in breeding programs aimed at improving this economically important phenotype 3 .Since FE cannot be measured directly, feed conversion ratio (FCR) and residual feed intake (RFI) have been used to evaluate the animal efficiency 4 . FCR determines the ratio of feed intake (FI) to output and found to correlate with growth rate and body weight 3,5 . RFI calculates the difference between the actual and expected FI 6 predicted based on production traits such as average daily gain (ADG) 7 . ADG is also considered important in commercial pig production as pigs with higher ADG can achieve a target market weight within a shorter period than those with lower ADG, thereby saving feeding costs 8 . Thus, selection for RFI has proved to be effective in improving the FE in pigs 3,9,10 . Selection for FCR will results in co-selection for other traits, such as body composition and ADG. In contrast, RFI selects for increased metabolic efficiency without the same side effects [11][12][13] . RFI and FCR are well c...

Residual Feed Intake (RFI) is an economically relevant trait in beef cattle. Among the molecular regulatory mechanisms, microRNAs (miRNAs) are an important dimension in post-transcriptional regulation and have been associated with different biological pathways. Here, we performed differential miRNAs expression and weighted gene co-expression network analyses (WGCNA) to better understand the complex interactions between miRNAs and mRNAs expressed in bovine skeletal muscle and liver. MiRNA and mRNA expression data were obtained from Nelore steers that were genetically divergent for RFI (N = 10 [low RFI or feed efficient]; N = 10 [high RFI or feed inefficient]). Differentially expressed and hub miRNAs such as bta-miR-486, bta-miR-7, bta-miR15a, bta-miR-21, bta-miR 29, bta- miR-30b, bta-miR-106b, bta-miR-199a-3p, bta-miR-204, and bta-miR 296 may have a potential role in variation of RFI. Functional enrichment analysis of differentially expressed (DE) miRNA’s target genes and miRNA–mRNA correlated modules revealed that insulin, lipid, immune system, oxidative stress and muscle development signaling pathways might potentially be involved in RFI in this population. Our study identified DE miRNAs, miRNA - mRNA regulatory networks and hub miRNAs related to RFI. These findings suggest a possible role of miRNAs in regulation of RFI, providing new insights into the potential molecular mechanisms that control feed efficiency in Nelore cattle.

Mineral content affects the biological processes underlying beef quality. Muscle mineral concentration depends not only on intake-outtake balance and muscle type, but also on age, environment, breed, and genetic factors. To unveil the genetic factors involved in muscle mineral concentration, we applied a pairwise differential gene expression analysis in groups of Nelore steers genetically divergent for nine different mineral concentrations. Here, based on significant expression differences between contrasting groups, we presented candidate genes for the genetic regulation of mineral concentration in muscle. Functional enrichment and protein-protein interaction network analyses were carried out to search for gene regulatory processes concerning each mineral. The core genetic regulation for all minerals studied, except Zn, seems to rest on interactions between components of the extracellular matrix. Regulation of adipogenesis-related pathways was also significant in our results. Antagonistic patterns of gene expression for fatty acid metabolism-related genes may explain the Cu and Zn antagonistic effect on fatty acid accumulation. Our results shed light on the role of these minerals on cell function.

Meat quality is a complex trait that is influenced by genetic and environmental factors, which includes mineral concentration. However, the association between mineral concentration and meat quality, and the specific molecular pathways underlying this association, are not well explored. We therefore analyzed gene expression as measured with RNA-seq in Longissimus thoracis muscle of 194 Nelore steers for association with three meat quality traits (intramuscular fat, meat pH, and tenderness) and the concentration of 13 minerals (Ca, Cr, Co, Cu, Fe, K, Mg, Mn, Na, P, S, Se, and Zn). We identified seven sets of co-expressed genes (modules) associated with at least two traits, which indicates that common pathways influence these traits. From pathway analysis of module hub genes, we further found an over-representation for energy and protein metabolism (AMPK and mTOR signaling pathways) in addition to muscle growth, and protein turnover pathways. Among the identified hub genes FASN, ELOV5, and PDE3B are involved with lipid metabolism and were affected by previously identified eQTLs associated to fat deposition. The reported hub genes and over-represented pathways provide evidence of interplay among gene expression, mineral concentration, and meat quality traits. Future studies investigating the effect of different levels of mineral supplementation in the gene expression and meat quality traits could help us to elucidate the regulatory mechanism by which the genes/pathways are affected.

Iron (Fe) is an essential mineral for metabolism and plays a central role in a range of biochemical processes. Therefore, this study aimed to identify differentially expressed (DE) genes and metabolic pathways in Longissimus dorsi (LD) muscle from cattle with divergent iron content, as well as to investigate the likely role of these DE genes in biological processes underlying beef quality parameters. Samples for RNA extraction for sequencing and iron, copper, manganese, and zinc determination were collected from LD muscles at slaughter. Eight Nelore steers, with extreme genomic estimated breeding values for iron content (Fe-GEBV), were selected from a reference population of 373 animals. From the 49 annotated DE genes (FDR<0.05) found between the two groups, 18 were up-regulated and 31 down-regulated for the animals in the low Fe-GEBV group. The functional enrichment analyses identified several biological processes, such as lipid transport and metabolism, and cell growth. Lipid metabolism was the main pathway observed in the analysis of metabolic and canonical signaling pathways for the genes identified as DE, including the genes FASN, FABP4, and THRSP, which are functional candidates for beef quality, suggesting reduced lipogenic activities with lower iron content. Our results indicate metabolic pathways that are partially influenced by iron, contributing to a better understanding of its participation in skeletal muscle physiology.

Maternal nutrients are essential for proper fetal and placental development and function. However, the effects of vitamin and mineral supplementation under two rates of maternal weight gain on placental genome-wide gene expression have not been investigated so far. Furthermore, biological processes and pathways in the placenta that act in response to early maternal nutrition are yet to be elucidated. Herein, we examined the impact of maternal vitamin and mineral supplementation (from pre-breeding to day 83 post-breeding) and two rates of gain during the first 83 days of pregnancy on the gene expression of placental caruncles (CAR; maternal placenta) and cotyledons (COT; fetal placenta) of crossbred Angus beef heifers. We identified 267 unique differentially expressed genes (DEG). Among the DEGs from CAR, we identified ACAT2, SREBF2, and HMGCCS1 that underlie the cholesterol biosynthesis pathway. Furthermore, the transcription factors PAX2 and PAX8 were over-represented in biological processes related to kidney organogenesis. The DEGs from COT included SLC2A1, SLC2A3, SLC27A4, and INSIG1. Our over-representation analysis retrieved biological processes related to nutrient transport and ion homeostasis, whereas the pathways included insulin secretion, PPAR signaling, and biosynthesis of amino acids. Vitamin and mineral supplementation and rate of gain were associated with changes in gene expression, biological processes, and KEGG pathways in beef cattle placental tissues.

The molecular basis underlying fetal programming in response to maternal nutrition remains unclear. Herein, we investigated the regulatory relationships between genes in fetal cerebrum, liver, and muscle tissues to shed light on the putative mechanisms that underlie the effects of early maternal nutrient restriction on bovine developmental programming. To this end, cerebrum, liver, and muscle gene expression were measured with RNA-Seq in 14 fetuses collected on day 50 of gestation from dams fed a diet initiated at breeding to either achieve 60% (RES, n = 7) or 100% (CON, n = 7) of energy requirements. To build a tissue-to-tissue gene network, we prioritized tissue-specific genes, transcription factors, and differentially expressed genes. Furthermore, we built condition-specific networks to identify differentially co-expressed or connected genes. Nutrient restriction led to differential tissue regulation between the treatments. Myogenic factors differentially regulated by ZBTB33 and ZNF131 may negatively affect myogenesis. Additionally, nutrient-sensing pathways, such as mTOR and PI3K/Akt, were affected by gene expression changes in response to nutrient restriction. By unveiling the network properties, we identified major regulators driving gene expression. However, further research is still needed to determine the impact of early maternal nutrition and strategic supplementation on pre- and post-natal performance.