Skin transcriptomic analysis reveals candidate genes and pathways associated with thermotolerance in hair sheep.

The skin plays an important role in thermoregulation. Identification of genes on the skin that contribute to increased heat tolerance can be used to select animals with the best performance in warm environments. Our objective was to identify candidate genes associated with the heat stress response in the skin of Santa Ines sheep. A group of 80 sheep assessed for thermotolerance was kept in a climatic chamber for 8 days at a stress level temperature of 36 °C (10 am to 04 pm) and a maintenance temperature of 28 °C (04 pm to 10 am). Two divergent groups, with seven animals each, were formed after ranking them by thermotolerance using rectal temperature. From skin biopsy samples, total RNA was extracted, quantified, and used for RNA-seq analysis. 15,989 genes were expressed in sheep skin samples, of which 4 genes were differentially expressed (DE; FDR < 0.05) and 11 DE (FDR 0.05-0.177) between the two divergent groups. These genes are involved in cellular protection against stress (HSPA1A and HSPA6), ribosome assembly (28S, 18S, and 5S ribosomal RNA), and immune response (IGHG4, GNLY, CXCL1, CAPN14, and SAA-4). The candidate genes and main pathways related to heat tolerance in Santa Ines sheep require further investigation to understand their response to heat stress in different climatic conditions and under solar radiation. It is essential to verify whether these genes and pathways are present in different breeds and to understand the relationship between heat stress and other genes identified in this study.

Metabolomic signature of spermatozoa established during holding time is responsible for differences in boar sperm freezability†.

Holding at room temperature is the first step in most boar semen cryopreservation protocols. It is well accepted that a holding time (HT) of 24 h increases sperm cryotolerance. However, the effect of HT on ejaculates with different freezability is not entirely clear. The aim of this study was to understand how HT influences spermatic and seminal plasma metabolite profiles of boar ejaculates and how these possible changes affect freezability. A total of 27 ejaculates were collected and extended to 1:1 (v: v) with BTS and split into two aliquots. The first aliquot was cryopreserved without HT (0 h), and the second was held at 17°C for 24 h before cryopreservation. Spermatozoa and seminal plasma were collected by centrifugation at two times, before HT (0 h) and after HT (24 h), and subsequently frozen until metabolite extraction and UPLC-MS analysis. After thawing, the semen samples were evaluated for kinetics, membrane integrity, mitochondrial potential, membrane lipid peroxidation, and fluidity. The ejaculates were then allocated into two phenotypes (good ejaculate freezers [GEF] and poor ejaculate freezers [PEF]) based on the percent reduction in sperm quality (%RSQ) as determined by the difference in total motility and membrane integrity between raw and post-thaw samples cryopreserved after 24 h of HT. The metabolic profile of the seminal plasma did not seem to influence ejaculate freezability, but that of the spermatozoa were markedly different between GEF and PEF. We identified a number of metabolic markers in the sperm cells (including inosine, hypoxanthine, creatine, ADP, niacinamide, spermine, and 2-methylbutyrylcarnitine) that were directly related to the improvement of ejaculate freezability during HT; these were components of metabolic pathways associated with energy production. Furthermore, PEF showed an upregulation in the arginine and proline as well as the glutathione metabolism pathways. These findings help to better understand the effect of HT on boar sperm freezability and propose prospective metabolic markers that may predict freezability; this has implications in both basic and applied sciences.

Identification of a metabolomic signature associated with feed efficiency in beef cattle.

BACKGROUND: Ruminants play a great role in sustainable livestock since they transform pastures, silage, and crop residues into high-quality human food (i.e. milk and beef). Animals with better ability to convert food into animal protein, measured as a trait called feed efficiency (FE), also produce less manure and greenhouse gas per kilogram of produced meat. Thus, the identification of high feed efficiency cattle is important for sustainable nutritional management. Our aim was to evaluate the potential of serum metabolites to identify FE of beef cattle before they enter the feedlot. RESULTS: A total of 3598 and 4210 m/z features was detected in negative and positive ionization modes via liquid chromatography-mass spectrometry. A single feature was different between high and low FE groups. Network analysis (WGCNA) yielded the detection of 19 and 20 network modules of highly correlated features in negative and positive mode respectively, and 1 module of each acquisition mode was associated with RFI (r = 0.55, P < 0.05). Pathway enrichment analysis (Mummichog) yielded the Retinol metabolism pathway associated with feed efficiency in beef cattle in our conditions. CONCLUSION: Altogether, these findings demonstrate the existence of a serum-based metabolomic signature associated with feed efficiency in beef cattle before they enter the feedlot. We are now working to validate the use of metabolites for identification of feed efficient animals for sustainable nutritional management.

Identification of selection signatures involved in performance traits in a paternal broiler line.

BACKGROUND: Natural and artificial selection leads to changes in certain regions of the genome resulting in selection signatures that can reveal genes associated with the selected traits. Selection signatures may be identified using different methodologies, of which some are based on detecting contiguous sequences of homozygous identical-by-descent haplotypes, called runs of homozygosity (ROH), or estimating fixation index (FST) of genomic windows that indicates genetic differentiation. This study aimed to identify selection signatures in a paternal broiler TT line at generations 7th and 16th of selection and to investigate the genes annotated in these regions as well as the biological pathways involved. For such purpose, ROH and FST-based analysis were performed using whole genome sequence of twenty-eight chickens from two different generations. RESULTS: ROH analysis identified homozygous regions of short and moderate size. Analysis of ROH patterns revealed regions commonly shared among animals and changes in ROH abundance and size between the two generations. Results also suggest that whole genome sequencing (WGS) outperforms SNPchip data avoiding overestimation of ROH size and underestimation of ROH number; however, sequencing costs can limited the number of animals analyzed. FST-based analysis revealed genetic differentiation in several genomic windows. Annotation of the consensus regions of ROH and FST windows revealed new and previously identified genes associated with traits of economic interest, such as APOB, IGF1, IGFBP2, POMC, PPARG, and ZNF423. Over-representation analysis of the genes resulted in biological terms of skeletal muscle, matrilin proteins, adipose tissue, hyperglycemia, diabetes, Salmonella infections and tyrosine. CONCLUSIONS: Identification of ROH and FST-based analyses revealed selection signatures in TT line and genes that have important role in traits of economic interest. Changes in the genome of the chickens were observed between the 7th and 16th generations showing that ancient and recent selection in TT line may have acted over genomic regions affecting diseases and performance traits.

Exploring candidate genes for heat tolerance in ovine through liver gene expression.

Thermotolerance has become an essential factor in the prevention of the adverse effects of heat stress, but it varies among animals. Identifying genes related to heat adaptability traits is important for improving thermotolerance and for selecting more productive animals in hot environments. The primary objective of this research was to find candidate genes in the liver that play a crucial role in the heat stress response of Santa Ines sheep, which exhibit varying levels of heat tolerance. To achieve this goal, 80 sheep were selected based on their thermotolerance and placed in a climate chamber for 10 days, during which the average temperature was maintained at 36 °C from 10 a.m. to 4 p.m. and 28 °C from 4 p.m. to 10 a.m. A subset of 14 extreme animals, with seven thermotolerant and seven non-thermotolerant animals based on heat loss (rectal temperature), were selected for liver sampling. RNA sequencing and differential gene expression analysis were performed. Thermotolerant sheep showed higher expression of genes GPx3, RGS6, GPAT3, VLDLR, LOC101108817, and EVC. These genes were mainly related to the Hedgehog signaling pathway, glutathione metabolism, glycerolipid metabolism, and thyroid hormone synthesis. These enhanced pathways in thermotolerant animals could potentially mitigate the negative effects of heat stress, conferring greater heat resistance.

Vaginal Microbiota Diversity in Response to Lipopolysaccharide in Gilts Housed Under Three Housing Systems.

The United Kingdom and European Union have banned crates for pregnant sows. However, animals are kept in a restrictive environment for up to four weeks after mating, leading to stress and different responses of the animals' immune system. Here, we used vaginal flushing of gilts to investigate whether housing systems or an experimental inflammatory challenge with lipopolysaccharide (LPS) can modify the gilt vaginal microbiome. Alpha-diversity indices showed differences in the microbiota of gilts housed under different systems (q = 0.04). Shannon alpha-diversity richness was higher in gilts group-housed in pens than in gilts housed in crates (q = 0.035), but not higher than in other groups. The relative abundance of the operational taxonomic unit (OTU) (q < 0.05) revealed specific differences in housing systems before a LPS or saline (SAL control) challenge. We found different abundances in taxa of Actinobacteria, Bacteroidetes, Cyanobacteria, Firmicutes, and Proteobacteria in gilts housed in the different systems before challenge. After the LPS challenge, significant differences were detected in the relative abundance of OTUs (q < 0.05) for the LPS-challenged group compared with SAL animals for each housing system. The phylum Staphylococcus showed higher abundance among the LPS-challenged gilts than in SAL-challenged animals. Furthermore, Enterobacter was more abundant in the LPS-challenged gilts housed in crates than in SAL-challenged gilts housed in crates. Streptococcus suis, Conchiformibius, Globicatella and Actinobacillus were more abundant in LPS-challenged gilts in indoor group housing than in SAL gilts in the same housing system. Gilts kept outdoors did not show changes in vaginal microbiota after an LPS challenge. Gilts housed in crates showed clinical signs of urogenital infection, whereas gilts housed outdoors and in indoor group housing did not. The relationship between environment, immune response, and microbiota suggested that animals in a poor environments experience difficulties responding to a challenge and their vaginal microbiota is altered as a consequence, with decreased richness of normal vaginal microbiota, and increased opportunistic bacteria. Welfare indicators measured by gilts' responses to housing systems however, do not fully explain mechanisms associated with the unique signature in vaginal microbiota encountered in the different housing systems.

Multi-omic data integration for the study of production, carcass, and meat quality traits in Nellore cattle.

Data integration using hierarchical analysis based on the central dogma or common pathway enrichment analysis may not reveal non-obvious relationships among omic data. Here, we applied factor analysis (FA) and Bayesian network (BN) modeling to integrate different omic data and complex traits by latent variables (production, carcass, and meat quality traits). A total of 14 latent variables were identified: five for phenotype, three for miRNA, four for protein, and two for mRNA data. Pearson correlation coefficients showed negative correlations between latent variables miRNA 1 (mirna1) and miRNA 2 (mirna2) (-0.47), ribeye area (REA) and protein 4 (prot4) (-0.33), REA and protein 2 (prot2) (-0.3), carcass and prot4 (-0.31), carcass and prot2 (-0.28), and backfat thickness (BFT) and miRNA 3 (mirna3) (-0.25). Positive correlations were observed among the four protein factors (0.45-0.83): between meat quality and fat content (0.71), fat content and carcass (0.74), fat content and REA (0.76), and REA and carcass (0.99). BN presented arcs from the carcass, meat quality, prot2, and prot4 latent variables to REA; from meat quality, REA, mirna2, and gene expression mRNA1 to fat content; from protein 1 (prot1) and mirna2 to protein 5 (prot5); and from prot5 and carcass to prot2. The relations of protein latent variables suggest new hypotheses about the impact of these proteins on REA. The network also showed relationships among miRNAs and nebulin proteins. REA seems to be the central node in the network, influencing carcass, prot2, prot4, mRNA1, and meat quality, suggesting that REA is a good indicator of meat quality. The connection among miRNA latent variables, BFT, and fat content relates to the influence of miRNAs on lipid metabolism. The relationship between mirna1 and prot5 composed of isoforms of nebulin needs further investigation. The FA identified latent variables, decreasing the dimensionality and complexity of the data. The BN was capable of generating interrelationships among latent variables from different types of data, allowing the integration of omics and complex traits and identifying conditional independencies. Our framework based on FA and BN is capable of generating new hypotheses for molecular research, by integrating different types of data and exploring non-obvious relationships.

Genetic parameters associated with meat quality of Nellore cattle at different anatomical points of longissimus: Brazilian standards.

The present study estimated genetic parameters and evaluated the genetic and phenotypic correlations between meat quality characteristics of Nellore cattle evaluated at different anatomical points of the longissimus. Data from 1329 Nellore young bulls were used to evaluate, in the 5th and 12th ribs, marbling score (MAR), shear force (SF), cooking weight losses (CWL) and intramuscular fat (IMF). In addition, the subcutaneous fat thickness was measured at the 12th rib (SFT12) and between the last lumbar and the first sacral vertebrae (SFTLR), in the separation of loin and round. Results yielded moderate heritability coefficients for evaluated characteristics, except CWL. High genetic correlations (0.61) were found between measurements of SFT12 and SFTLR. MAR, IMF and SF were evaluated at the 5th and 12th rib. Meat quality and subcutaneous fat thickness measured at different anatomical points of the longissimus are genetically correlated and can be used in genetic selection programs to improve meat quality characteristics in Nellore cattle.

Predicting the shear value and intramuscular fat in meat from Nellore cattle using Vis-NIR spectroscopy.

Visible and near-infrared spectroscopy (Vis-NIRS) was tested for its effectiveness in predicting intramuscular fat (IMF) and WBSF in Nellore steers. Beef samples from longissimus thoracis, aged for either 2 or 7 days, had their spectra collected for wavelengths ranging from 400 to 1395 nm. Partial least squares regression models were developed for each trait. Determination coefficients of calibration models for WBSF ranged from 0.17 to 0.53. Considering WBSF in samples aged for 2 days, Vis-NIR correctly classified 100% of tough samples (>45 N), but wrongly classified all tender samples (≤45 N) as tough. Determination coefficients of calibration models for IMF ranged from 0.12 to 0.14. Vis-NIRS is a useful tool for identifying tough beef, but it is less effective in predicting tender samples and IMF. Additional studies are necessary to generate more robust models for the prediction of intramuscular fat in intact meat samples of Nellore cattle.

Circulating leptin and its muscle gene expression in Nellore cattle with divergent feed efficiency.

BACKGROUND: Leptin has a strong relation to important traits in animal production, such as carcass composition, feed intake, and reproduction. It is mainly produced by adipose cells and acts predominantly in the hypothalamus. In this study, circulating leptin and its gene expression in muscle were evaluated in two groups of young Nellore bulls with divergent feed efficiency. Individual dry matter intake (DMI) and average daily gain (ADG) of 98 Nellore bulls were evaluated in feedlot for 70 d to determinate the residual feed intake (RFI) and select 20 animals for the high feed efficient (LRFI) and 20 for the low feed efficient (HRFI) groups. Blood samples were collected on d 56 and at slaughter (80 d) to determine circulating plasma leptin. Samples of Longissimus dorsi were taken at slaughter for leptin gene expression levels. RESULTS: DMI and RFI were different between groups and LRFI animals showed less back fat and rump fat thickness, as well as less pelvic and kidney fat weight. Circulating leptin increased over time in all animals. Plasma leptin was greater in LRFI on 56 d and at slaughter (P = 0.0049). Gene expression of leptin were greater in LRFI animals (P = 0.0022) in accordance with the plasma levels. The animals of the LRFI group were leaner, ate less, and had more circulating leptin and its gene expression. CONCLUSION: These findings demonstrated that leptin plays its physiological role in young Nellore bulls, probably controlling food intake because feed efficient animals have more leptin and lower residual feed intake.