Impact of prenatal maternal nutrition and parental residual feed intake (RFI) on mRNA abundance of metabolic drivers of growth and development in young Angus bulls

Identification of consensus homozygous regions and their associations with growth and feed efficiency traits in American mink

The recent chromosome-based genome assembly and the newly developed 70K single nucleotide polymorphism (SNP) array for American mink (Neogale vison) facilitate the identification of genetic variants underlying complex traits in this species. The objective of this study was to evaluate the association between consensus runs of homozygosity (ROH) with growth and feed efficiency traits in American mink. A subsample of two mink populations (n = 2,986) were genotyped using the Affymetrix Mink 70K SNP array. The identified ROH segments were included simultaneously, concatenated into consensus regions, and the ROH-based association studies were carried out with linear mixed models considering a genomic relationship matrix for 11 growth and feed efficiency traits implemented in ASReml-R version 4. In total, 298,313 ROH were identified across all individuals, with an average length and coverage of 4.16 Mb and 414.8 Mb, respectively. After merging ROH segments, 196 consensus ROH regions were detected and used for genome-wide ROH-based association analysis. Thirteen consensus ROH regions were significantly (P < 0.01) associated with growth and feed efficiency traits. Several candidate genes within the significant regions are known for their involvement in growth and body size development, including MEF2A, ADAMTS17, POU3F2, and TYRO3. In addition, we found ten consensus ROH regions, defined as ROH islands, with frequencies over 80% of the population. These islands harbored 12 annotated genes, some of which were related to immune system processes such as DTX3L, PARP9, PARP14, CD86, and HCLS1. This is the first study to explore the associations between homozygous regions with growth and feed efficiency traits in American mink. Our findings shed the light on the effects of homozygosity in the mink genome on growth and feed efficiency traits, that can be utilized in developing a sustainable breeding program for mink.

Effects of Different Prenatal Nutrition Strategies on the Liver Metabolome of Bulls and Its Correlation with Body and Liver Weight

This study investigated the effect of prenatal nutrition on liver metabolome and on body (BW) and liver weight (LW) of Nellore bulls at slaughter. Three treatments were applied in 126 cows during pregnancy: NP—control (mineral supplementation); PP—protein-energy supplementation in the third trimester; and FP—protein-energy supplementation during the entire pregnancy. Offspring BW and LW were evaluated, and a targeted metabolomics analysis was performed on their livers (n = 18, 22.5 ± 1 months of age). Data were submitted to principal component analysis (PCA), analysis of variance (ANOVA), enrichment analysis, and Pearson’s correlation analysis. The phenotypes did not show differences between treatments (p > 0.05). Metabolites PCA showed an overlap of treatment clusters in the analysis. We found significant metabolites in ANOVA (p ≤ 0.05; Glycine, Hydroxytetradecadienylcarnitine, Aminoadipic acid and Carnosine). Enrichment analysis revealed some biological processes (Histidine metabolism, beta-Alanine metabolism, and Lysine degradation). Pearson’s correlation analysis showed 29 significant correlated metabolites with BW and 1 metabolite correlated with LW. In summary, prenatal nutrition did not show effects on the phenotypes evaluated, but affected some metabolites and biological pathways, mainly related to oxidative metabolism. In addition, BW seems to influence the hepatic metabolome more than LW, due to the amount and magnitude of correlations found.

Exploring Biological Impacts of Prenatal Nutrition and Selection for Residual Feed Intake on Beef Cattle Using Omics Technologies: A Review

Approximately 70% of the cost of beef production is impacted by dietary intake. Maximizing production efficiency of beef cattle requires not only genetic selection to maximize feed efficiency (i.e., residual feed intake (RFI)), but also adequate nutrition throughout all stages of growth and development to maximize efficiency of growth and reproductive capacity, even during gestation. RFI as a measure of feed efficiency in cattle has been recently accepted and used in the beef industry, but the effect of selection for RFI upon the dynamics of gestation has not been extensively studied, especially in the context of fluctuating energy supply to the dam and fetus. Nutrient restriction during gestation has been shown to negatively affect postnatal growth and development as well as fertility of beef cattle offspring. This, when combined with the genetic potential for RFI, may significantly affect energy partitioning in the offspring and subsequently important performance traits. In this review, we discuss: 1) the importance of RFI as a measure of feed efficiency and how it can affect other economic traits in beef cattle; 2) the influence of prenatal nutrition on physiological phenotypes in calves; 3) the benefits of investigating the interaction of genetic selection for RFI and prenatal nutrition; 4) how metabolomics, transcriptomics, and epigenomics have been employed to investigate the underlying biology associated with prenatal nutrition, RFI, or their interactions in beef cattle; and 5) how the integration of omics information is adding a level of deeper understanding of the genetic architecture of phenotypic traits in cattle.

Genetic potential for residual feed intake and diet fed during early- to mid-gestation influences post-natal DNA methylation of imprinted genes in muscle and liver tissues in beef cattle

Discovery of epigenetic modifications associated with feed efficiency or other economically important traits would increase our understanding of the molecular mechanisms underlying these traits. In combination with known genetic markers, this would provide opportunity to improve genomic selection accuracy in cattle breeding programs. It would also allow cattle to be managed to improve favorable gene expression. The objective of this study was to identify variation in DNA methylation between beef cattle of differential pre-natal nutrition and divergent genetic potential for residual feed intake (RFI). Purebred Angus offspring with the genetic potential for either high (HRFI) or low (LRFI) RFI were prenatally exposed to either a restricted maternal diet of 0.5 kg/d average daily gain (ADG) or a moderate maternal diet of 0.7 kg/d ADG from 30 to 150 d of gestation. We performed DNA methylation analysis of differentially methylated regions (DMR) of imprinted genes (Insulin-like growth factor 2 (IGF2) DMR2, IGF2/H19 imprinting control region (ICR) and IGF2 receptor (IGF2R) DMR2) using post-natal samples of longissimus dorsi (LD) muscle taken from male and female calves at birth and weaning, and of LD muscle, semimembranosus (SM) muscle, and liver samples collected from steers at slaughter (17 months of age). Interestingly, for all three DMR investigated in liver, LRFI steers had higher levels of methylation than HRFI steers. In LD muscle, IGF2/H19 ICR methylation differences for heifers at birth were due to pre-natal diet, while for steers at birth they were mostly the result of genetic potential for RFI with LRFI steers again having higher levels of methylation than HRFI steers. While results from repeated measures analysis of DNA methylation in steers grouped by RFI revealed few differences, in steers grouped by diet, we found higher methylation levels of IGF2 DMR2 and IGF2R DMR2 in LD muscle of restricted diet steers at weaning and slaughter than at birth, as well as increased methylation in LD muscle of restricted diet steers compared with moderate diet steers at weaning and/or slaughter. Our results suggest that differential pre-natal nutrition, and divergent genetic potential for RFI, induces tissue- and sex-specific alterations in post-natal IGF2 and IGF2R methylation patterns and that these patterns can vary with age in Angus beef cattle.