Traditional single nucleotide polymorphism (SNP) genome-wide association analysis (GWAA) can be inefficient because single SNPs provide limited genetic information about genomic regions. On the other hand, using haplotypes in the statistical analysis may increase the extent of linkage disequilibrium (LD) between haplotypes and causal variants and may also potentially capture epistastic interactions between variants within a haplotyped locus, providing an increase in the power and robustness of the association studies. We performed GWAA (413,355 SNP markers) using haplotypes based on variable-sized sliding windows and compared the results to a single-SNP GWAA using Warner-Bratzler shear force measured in the longissimus thorasis muscle of 3161 Nelore bulls to ascertain the optimal window size for identifying the genomic regions that influence meat tenderness. The GWAA using single SNPs identified eight variants influencing meat tenderness on BTA 3, 4, 9, 10 and 11. However, thirty-three putative meat tenderness QTL were detected on BTA 1, 3, 4, 5, 8, 9, 10, 11, 15, 17, 18, 24, 25, 26 and 29 using variable-sized sliding haplotype windows. Analyses using sliding window haplotypes of 3, 5, 7, 9 and 11 SNPs identified 57, 61, 42, 39, and 21% of all thirty-three putative QTL regions, respectively; however, the analyses using the 3 and 5 SNP haplotypes, cumulatively detected 88% of the putative QTL. The genes associated with variation in meat tenderness participate in myogenesis, neurogenesis, lipid and fatty acid metabolism and skeletal muscle structure or composition processes. GWAA using haplotypes based on variable-sized sliding windows allowed the detection of more QTL than traditional single-SNP GWAA. Analyses using smaller haplotypes (3 and 5 SNPs) detected a higher proportion of the putative QTL.

Despite two extensive reprogramming events during early embryogenesis and gametogenesis, epigenetic information can be passed to the next generations, which constitutes the transgenerational epigenetic inheritance of phenotypes. Considering its utmost importance, there have been few studies focused on the transgenerational effects of dietary interventions, such as methionine supplementation, in livestock. Using whole-genome bisulfite sequencing, we implemented a single-base resolution differential methylation analysis for the F3 and F4 descendants of control vs. methionine-supplemented F0 twin-pair rams. Based on the results of our previous study on F0, F1, and F2 generations, we compared current results of 2981 and 1726 differentially methylated cytosines (DMCs), as well as 798 and 553 unique differentially methylated genes (DMGs), in F3 and F4, respectively. We identified 41 DMGs that exhibited transgenerational epigenetic inheritance (TEI-DMGs) across four generations and 11 TEI-DMGs across five generations. Finally, we estimated the effect size of F0 diet group on F3 and F4 growth and fertility-related phenotypes, providing evidence for transgenerational effects of diet group accompanying inherited differentially methylated genes. Here, for the first time using gene-level and phenotypic data, we demonstrate that a moderate dietary intervention can exert long-lasting transgenerational effects on offspring phenotypes extending beyond the F2 generation in sheep.

Bovine babesiosis is a tick-borne disease caused by intraerythrocytic protozoa and leads to substantial economic losses for the livestock industry throughout the world. Babesia bovis is considered the most pathogenic species, which causes bovine babesiosis in Brazil. Genomic data could be used to evaluate the viability of improving resistance against B. bovis infection level (IB) through genomic selection, and, for that, knowledge of genetic parameters is needed. Furthermore, genome-wide association studies (GWAS) could be conducted to provide a better understanding of the genetic basis of the host response to B. bovis infection. No previous work in quantitative genetics of B. bovis infection was found. Thus, the objective of this study was to estimate the genetic correlation between IB and tick count (TC), evaluate predictive ability and applicability of genomic selection, and perform GWAS in Hereford and Braford cattle. The single-step genomic best linear unbiased prediction method was used, which allows the estimation of both breeding values and marker effects. Standard phenotyping was conducted for both traits. IB quantifications from the blood of 1,858 animals were carried using quantitative PCR assays. For TC, one to three subsequent tick counts were performed by manually counting adult female ticks on one side of each animal's body that was naturally exposed to ticks. Animals were genotyped using the Illumina BovineSNP50 panel. The posterior mean of IB heritability, estimated by the Bayesian animal model in a bivariate analysis, was low (0.10), and the estimations of genetic correlation between IB and TC were also low (0.15). The cross-validation genomic prediction accuracy for IB ranged from 0.18 to 0.35 and from 0.29 to 0.32 using k-means and random clustering, respectively, suggesting that genomic predictions could be used as a tool to improve genetics for IB, especially if a larger training population is developed. The top 10 single nucleotide polymorphisms from the GWAS explained 5.04% of total genetic variance for IB, which were located on chromosomes 1, 2, 5, 6, 12, 17, 18, 16, 24, and 26. Some candidate genes participate in immunity system pathways indicating that those genes are involved in resistance to B. bovis in cattle. Although the genetic correlation between IB and TC was weak, some candidate genes for IB were also reported in tick infestation studies, and they were also involved in biological resistance processes. This study contributes to improving genetic knowledge regarding infection by B. bovis in cattle.

Breeding animals able to effectively respond to stress could be a long-term, sustainable, and affordable strategy to improve resilience and welfare in livestock systems. In the present study, the concentrations of 29 plasma biomarkers were used as candidate endophenotypes for metabolic stress response in single-SNP, gene- and haplotype-based GWAS using 739 healthy lactating Italian Holstein cows and 88,271 variants. Significant genetic associations were found in all the 3 GWAS approaches for plasma γ-glutamyl transferase concentration on BTA17, for paraoxonase on BTA4, and for alkaline phosphatase and zinc on BTA2. On these chromosomes, single-SNP and gene-based chromosome-wide association studies were performed, confirming GWAS findings. The signals identified for paraoxonase, γ-glutamyl transferase, and alkaline phosphatase were in proximity of the genes coding for them. The heritability of these 4 biomarkers ranged from moderate to high (from 0.39 to 0.54). Plasma biomarkers are known to undergo large changes in concentration during metabolic stress in the transition period, with an inter-individual variability in the rate of change and recovery time. Genetics may account in part for these differences. To assess this, we studied a subset of 139 periparturient cows homozygous at 3 SNPs known to be respectively associated with concentration of plasma ceruloplasmin, paraoxonase and γ-glutamyl transferase. We compared the immune-metabolic profile measured in plasma at -7, +5 and +30 d relative to calving between groups of opposite homozygotes. A significant effect of the genotype was found on paraoxonase and γ-glutamyl transferase plasma concentration at all the 3 time points. No evidence for genotype effect was detected for ceruloplasmin. Understanding the genetic control underlying metabolic stress response may suggest new approaches to foster resilience in dairy cows.

A common goal of the dairy industry is to shorten the calving interval to reap several benefits associated with improved fertility. Early pregnancy detection is crucial to shorten this interval, allowing for prompt re-insemination of cows that failed to conceive after the first service. Currently, the industry lacks a method to accurately predict pregnancy within the first 3 wk. The polypeptide cytokine IFN-tau (IFNT) is the primary signal for maternal recognition of pregnancy in ruminants. As IFNT is released from the early conceptus, it initiates a cascade of effects, including upregulation of IFN-stimulated genes (ISG). Expression of ISG can be detected in the peripheral blood. The present study aimed to characterize peripheral transcriptomic changes, including the ISG, as early as d 7 after embryo transfer. A total of 170 Holstein heifers received in vitro-produced embryos. Whole blood was collected from these heifers within 24 h of the embryo transfer (d 0), d 7, and d 14 after embryo transfer. The heifers were divided into 2 groups, pregnant and nonpregnant, based on pregnancy diagnosis on d 28 via ultrasound. Total RNA was extracted from the peripheral blood of pregnant and nonpregnant heifers, pooled and sequenced. Expression analysis on d 7 heifers resulted in 13 significantly differentially expressed genes mostly related to innate immunity. Differential expression analysis comparing pregnant heifers on d 0 to the same heifers on d 14 showed 51 significantly differentially expressed genes. Eight genes were further quantified through reverse-transcription quantitative real-time PCR for biological validation. On d 7 after embryo transfer, mRNA transcriptions of EDN1, CXCL3, CCL4, and IL1A were significantly upregulated in pregnant heifers (n = 14) compared with nonpregnant heifers (n = 14), with respective fold changes of 8.10, 18.12, 29.60, and 29.97. Although on d 14 after embryo transfer, mRNA transcriptions of ISG15, MX2, OASY1, and IFI6 were significantly upregulated in the blood of pregnant heifers (n = 14) compared with the same heifers on d 0, with respective fold changes of 5.09, 2.59, 3.89, and 3.08. These findings demonstrate that several immune-related genes and ISG are activated during the first 2 wk after embryo transfer, which may explain how the maternal immune system accommodates the allogenic conceptus. To further investigate the diagnostic potentials of these genes, future studies are warranted to analyze the specificity and sensitivity of these biomarkers to predict early pregnancy.

Background: Understanding the genetic basis of genotype-by-environment interactions (GxE) is crucial to understand environmental adaptation in mammals and improve the sustainability of agricultural production. In addition, GxE information could also be useful to predict the vulnerability of populations to climate change.Results: Here, we present an extensive study investigating the interaction of genome-wide SNP markers with a vast assortment of environmental variables and searching for SNPs controlling phenotypic variance (vQTL) using a large beef cattle dataset. We showed that GxE contribute 10%, 4%, and 3% of the phenotypic variance of birth weight, weaning weight, and yearling weight, respectively. GxE genome-wide association analysis (GWAA) detected a large number of GxE loci affecting growth traits, which the traditional GWAA did not detect, showing that functional loci may have non-additive genetic effects between genotype classes regardless of differences in genotypic means. We also showed that variance-heterogeneity GWAA can detect loci enriched with GxE effects without requiring prior knowledge of the interacting environmental factors. Functional annotation and pathway analysis of GxE genes revealed biological mechanisms by which cattle respond to changes in their environment, such as neural signaling, metabolic, hypoxia-induced, and immune system pathways. Knowledge of these pathways will be important as climate change becomes a burden on animal health and productivity. In addition, ecoregion-specific GxE SNPs detected in this study may play a crucial role in identifying resilient and adapted beef cattle across divergent environments.Conclusions: We detected novel trait associations with large GxE effects for birth weight, weaning weight, and yearling weight. Functional annotation and pathway analysis uncovered genomic regions involved in response to environmental stimuli. We unraveled the relevance and complexity of the genetic basis of GxE underlying growth traits, providing new insights into how different environmental conditions interact with specific genes influencing adaptation and productivity in beef cattle and potentially across mammals