Effect of the Season on Blood Changes of Oxidative Stress Index in the Italian Mediterranean Buffalo (Bubalis bubalis).

Studies in cattle have shown that high temperatures increase the production of reactive oxygen species (ROS) causing an imbalance between ROS and the ability of antioxidant systems to detoxify and remove the reactive intermediates. As such studies remain limited in buffalo, the effect of temperature on oxidative stress was investigated through the oxidative stress index (OSi). Blood samples were collected from 40 buffaloes over 12 time points distributed over two years (2021, 2022). Samples were taken monthly during the hot and cold seasons. Plasma free oxygen radicals were determined using the d-ROMs test (Diacron, Italy), modified for a microplate procedure, and the results were expressed in arbitrary Carratelli Units (U.CARR). Plasma antioxidants were determined by using the BAP test (Diacron) in a dedicated spectrophotometer (Carpe Diem Free, Diacron). The OSi parameter was calculated as d-ROMs/BAP × 100. Temperature and humidity were recorded daily during the trial to calculate the Temperature Humidity Index (THI). For statistical analysis, year and season and their interactions were included in the model. The results of this study showed for the first time the effect of season on the oxidative stress in buffalo. The minimum and maximum THI values for the hot and cold season recorded during the experimental period were 79.27 ± 2.20 and 63.42 ± 3.20, respectively. Levels of d-ROMs and BAP were affected by the seasons (133.0 vs. 145.1 U.CARR, p = 0.0189, and 2489.19 vs. 2392.43 mml/L, p = 0.033, in the hot and cold season, respectively). A significant year × season interaction was found both for d-ROMs and BAP (p = 0.06 and p < 0.0001, respectively). Moreover, OSi was affected by season, showing a growing trend from hot to cold season (5.35 vs. 6.17, p < 0.0001), but, interestingly, it was unaffected by annual variation. Therefore, Osi could be considered a better and independent marker of oxidative status in buffalo, with respect to the evaluation of single determinations of d-ROMs and BAP. Lastly, there were no differences in the plasma 25OHD levels between seasons; concentrations were 12.24 and 10.26 ng/mL in the hot and cold season, respectively.

Impact of Milk Storage and Heat Treatments on In Vitro Protein Digestibility of Soft Cheese.

Cheese is an important source of protein in the human diet, and its digestibility depends on its macro and microstructure. This study investigated the effect of milk heat pre-treatment and pasteurization level on the protein digestibility of produced cheese. An in vitro digestion method was used considering cheeses after 4 and 21 days of storage. The peptide profile and amino acids (AAs) released in digestion were analyzed to evaluate the level of protein degradation following in vitro digestion. The results showed the presence of shorter peptides in the digested cheese from pre-treated milk and 4-day ripening while this trend was not observed after 21 days of storage, showing the effect of storage period. A significantly higher content of AAs was found in digested cheese produced from milk subjected to a higher temperature of pasteurization, and there was a significant increase in total AA content in the cheese after 21 days of storage, confirming the positive effect of ripening on protein digestibility. From these results emerges the importance of the management of heat treatments on the digestion of proteins in soft cheese.

Visual Image Analysis for a new classification method of bovine carcasses according to EU legislation criteria.

In the European Community, conformation and fat cover of bovine carcasses is assessed using the SEUROP grading system. In this study we pursued the development of an application software (App) based on Visual Image Analysis, useful for SEUROP and Fat Cover grading of bovine carcasses using a smartphone. The App was trained using 500 bovine carcasses. Carcass conformation and Fat Cover classes were assessed in parallel by expert evaluators and by App. Overall, a high correspondence was found between the measurements of carcasses parameters by operators and by the App, as high as 84.2% for SEUROP and 86.4% for the Fat Cover. In the 15.8% of samples with discordant SEUROP evaluation, and in the 13.6% of samples with discordant Fat Cover evaluation, the operators' and App measurements deviated by only one class. All values also aligned with the requirements expected by the current legislation for the use of automated and/or semi-automated systems able to determine the market value of carcasses.

Relationships between EUROP carcass grading and backfat fatty acid composition in Italian Large White heavy pigs.

The amount and quality of covering adipose tissue affect the suitability of hind legs for the production of high-quality seasoned hams. To date, no studies exist on the correlation between EUROP carcass classification and backfat fatty acid (FA) composition in heavy pigs used for dry-cured hams. A sample of 898 Italian Large White heavy pigs was used to verify the relationship between carcass classification based on lean meat percentage and backfat FA composition. A Canonical Discriminant Analysis (CDA) was used to verify the power of individual FA and FA categories in discriminating among EUROP classes. The results proved that saturated FAs (i.e. palmitic, stearic and arachidic acids) and the n-6 polyunsaturated FAs have the highest discriminating power, thus permitting to differentiate among E, U, R, O carcass classes. For the first time, this work demonstrates the relationship between EUROP pig carcass grading, which is only based on an estimate of the percentage of lean meat, and backfat FA composition.

Assessment of Multicolor Flow Cytometry Panels to Study Leukocyte Subset Alterations in Water Buffalo (Bubalus bubalis) During BVDV Acute Infection.

The identification of cross-reactive monoclonal antibodies (mAbs) that recognize orthologous leukocyte differentiation molecules (LDM) in buffaloes has overcome a major impediment limiting research on the immune response to pathogens and development of vaccines. As reported, two pilot trials were conducted to accomplish two objectives: (1) demonstrate that multiparameter flow cytometry can be conducted equally well in buffalo with mAbs directly and indirectly labeled with fluorochromes in research and (2) flow cytometry can be used to compare and extend studies on diseases of economic importance to buffalo using bovine viral diarrhea virus (BVDV) as a model pathogen. Pregnant buffalo cows were infected with BVDV-1 at 81 (trial 1) and 203 (trial 2) days post artificial insemination and flow cytometric evaluations were performed at 0, 3, 4, and 14 days after infection (dpi). Fluorochrome conjugated mAbs were used in trial 1, and fluorochrome conjugated goat isotype specific anti-mouse antibodies were used to label mAbs in trial 2. Flow cytometric analysis revealed a transient lymphopenia occurs during the 1st days following infection similar to lymphopenia reported in cattle. In particular, significant differences were observed between pre- and post-infection absolute values of T lymphocytes (-56%, P < 0.01). CD21+ B lymphocytes (-65%, P = 0.04), and Natural Killer cells (-72%, P < 0.001). No significant differences were observed in monocytes and neutrophil absolute values, or the CD4:CD8 ratio. Animal health status was followed until 15 days after calving. No clinical signs of infection were observed during the evaluation period, however, animals in trial 1 developed complications later the infection. One cow aborted at 57 days post-infection, the second cow developed a prolapse a day after calving and died. These two animals also showed a more pronounced lymphopenia in comparison with animals infected at 203 days of pregnancy (e.g., -77 vs. -22% T lymphocytes at 3 dpi, respectively). The pilot studies have demonstrated that it is possible to use multicolour multiparameter flow cytometry to study the immune response to pathogens affecting the health of buffalo.

Genetic parameters of muscle fatty acid profile in a purebred Large White heavy pig population.

Semimembranosus muscle samples from 795 Large White heavy pigs were used to determine their intramuscular fatty acid composition and to estimate the heritability and the genetic correlations of these traits. Muscle fatty acids showed heritability estimates of low-to-moderate magnitude, ranging from 0.157 for total fatty acids to 0.237 for docosahexaenoic acid. Only small differences in heritability appeared among fatty acids based on their chain length, saturation and double bond position. Omega-6 polyunsaturated fatty acids showed positive genetic correlations with carcass lean % (0.563 ± 0.005) and loin thickness (0.438 ± 0.005) while being negatively related to backfat thickness measured both by calibre (-0.225 ± 0.008) and Fat-O-Meat'er (FOM) apparatus (-0.603 ± 0.004). Interestingly, the monounsaturated fatty acid class was not correlated with carcass measures and presented only a weak positive genetic correlation with intramuscular fat (0.145 ± 0.002). This result suggests that in heavy pig breeds monounsaturated fatty acids in muscle could be selected for without interfering with carcass traits.

Signatures of selection and environmental adaptation across the goat genome post-domestication.

BACKGROUND: Since goat was domesticated 10,000 years ago, many factors have contributed to the differentiation of goat breeds and these are classified mainly into two types: (i) adaptation to different breeding systems and/or purposes and (ii) adaptation to different environments. As a result, approximately 600 goat breeds have developed worldwide; they differ considerably from one another in terms of phenotypic characteristics and are adapted to a wide range of climatic conditions. In this work, we analyzed the AdaptMap goat dataset, which is composed of data from more than 3000 animals collected worldwide and genotyped with the CaprineSNP50 BeadChip. These animals were partitioned into groups based on geographical area, production uses, available records on solid coat color and environmental variables including the sampling geographical coordinates, to investigate the role of natural and/or artificial selection in shaping the genome of goat breeds. RESULTS: Several signatures of selection on different chromosomal regions were detected across the different breeds, sub-geographical clusters, phenotypic and climatic groups. These regions contain genes that are involved in important biological processes, such as milk-, meat- or fiber-related production, coat color, glucose pathway, oxidative stress response, size, and circadian clock differences. Our results confirm previous findings in other species on adaptation to extreme environments and human purposes and provide new genes that could explain some of the differences between goat breeds according to their geographical distribution and adaptation to different environments. CONCLUSIONS: These analyses of signatures of selection provide a comprehensive first picture of the global domestication process and adaptation of goat breeds and highlight possible genes that may have contributed to the differentiation of this species worldwide.

Genome-wide SNP profiling of worldwide goat populations reveals strong partitioning of diversity and highlights post-domestication migration routes.

BACKGROUND: Goat populations that are characterized within the AdaptMap project cover a large part of the worldwide distribution of this species and provide the opportunity to assess their diversity at a global scale. We analysed genome-wide 50 K single nucleotide polymorphism (SNP) data from 144 populations to describe the global patterns of molecular variation, compare them to those observed in other livestock species, and identify the drivers that led to the current distribution of goats. RESULTS: A high degree of genetic variability exists among the goat populations studied. Our results highlight a strong partitioning of molecular diversity between and within continents. Three major gene pools correspond to goats from Europe, Africa and West Asia. Dissection of sub-structures disclosed regional gene pools, which reflect the main post-domestication migration routes. We also identified several exchanges, mainly in African populations, and which often involve admixed and cosmopolitan breeds. Extensive gene flow has taken place within specific areas (e.g., south Europe, Morocco and Mali-Burkina Faso-Nigeria), whereas elsewhere isolation due to geographical barriers (e.g., seas or mountains) or human management has decreased local gene flows. CONCLUSIONS: After domestication in the Fertile Crescent in the early Neolithic era (ca. 12,000 YBP), domestic goats that already carried differentiated gene pools spread to Europe, Africa and Asia. The spread of these populations determined the major genomic background of the continental populations, which currently have a more marked subdivision than that observed in other ruminant livestock species. Subsequently, further diversification occurred at the regional level due to geographical and reproductive isolation, which was accompanied by additional migrations and/or importations, the traces of which are still detectable today. The effects of breed formation were clearly detected, particularly in Central and North Europe. Overall, our results highlight a remarkable diversity that occurs at the global scale and is locally partitioned and often affected by introgression from cosmopolitan breeds. These findings support the importance of long-term preservation of goat diversity, and provide a useful framework for investigating adaptive introgression, directing genetic improvement and choosing breeding targets.

Genomic Regions in Local Endangered Sheep Encode Potentially Favorable Genes.

The economic evaluation of farm animal genetic resources plays a key role in developing conservation programs. However, to date, the link between diversity as assessed by neutral genetic markers and the functional diversity is not yet understood. Two genome-wide comparisons, using over 44,000 Single Nucleotide Polymorphisms, identified the markers with the highest difference in allele frequency between the Alpago endangered breed and two clusters, composed of four specialized dairy sheep, and four meat breeds respectively. The genes in proximity of these markers were mapped to known pathways of the Gene Ontology to determine which ones were most represented. Our results indicated that the differences of the Alpago breed from the more productive sheep rely upon genes involved in cellular defense and repair mechanisms. A higher number of different markers and genes were detected in the comparison with the specialized dairy sheep. These genes play a role in complex biological processes: metabolic, homeostatic, neurological system, and macromolecular organization; such processes may possibly explain the evolution of gene function as a result of selection to improve milk yield.

Use of canonical discriminant analysis to study signatures of selection in cattle.

BACKGROUND: Cattle include a large number of breeds that are characterized by marked phenotypic differences and thus constitute a valuable model to study genome evolution in response to processes such as selection and domestication. Detection of "signatures of selection" is a useful approach to study the evolutionary pressures experienced throughout history. In the present study, signatures of selection were investigated in five cattle breeds farmed in Italy using a multivariate approach. METHODS: A total of 4094 bulls from five breeds with different production aptitudes (two dairy breeds: Italian Holstein and Italian Brown Swiss; two beef breeds: Piemontese and Marchigiana; and one dual purpose breed: Italian Simmental) were genotyped using the Illumina BovineSNP50 v.1 beadchip. Canonical discriminant analysis was carried out on the matrix of single nucleotide polymorphisms (SNP) genotyping data, separately for each chromosome. Scores for each canonical variable were calculated and then plotted in the canonical space to quantify the distance between breeds. SNPs for which the correlation with the canonical variable was in the 99th percentile for a specific chromosome were considered to be significantly associated with that variable. Results were compared with those obtained using an FST-based approach. RESULTS: Based on the results of the canonical discriminant analysis, a large number of signatures of selection were detected, among which several had strong signals in genomic regions that harbour genes known to have an impact on production and morphological bovine traits, including MSTN, LCT, GHR, SCD, NCAPG, KIT, and ASIP. Moreover, new putative candidate genes were identified, such as GCK, B3GALNT1, MGAT1, GALNTL1, PRNP, and PRND. Similar results were obtained with the FST-based approach. CONCLUSIONS: The use of canonical discriminant analysis on 50 K SNP genotypes allowed the extraction of new variables that maximize the separation between breeds. This approach is quite straightforward, it can compare more than two groups simultaneously, and relative distances between breeds can be visualized. The genes that were highlighted in the canonical discriminant analysis were in concordance with those obtained using the FST index.

Use of locally weighted scatterplot smoothing (LOWESS) regression to study selection signatures in Piedmontese and Italian Brown cattle breeds.

Selection is the major force affecting local levels of genetic variation in species. The availability of dense marker maps offers new opportunities for a detailed understanding of genetic diversity distribution across the animal genome. Over the last 50 years, cattle breeds have been subjected to intense artificial selection. Consequently, regions controlling traits of economic importance are expected to exhibit selection signatures. The fixation index (Fst ) is an estimate of population differentiation, based on genetic polymorphism data, and it is calculated using the relationship between inbreeding and heterozygosity. In the present study, locally weighted scatterplot smoothing (LOWESS) regression and a control chart approach were used to investigate selection signatures in two cattle breeds with different production aptitudes (dairy and beef). Fst was calculated for 42 514 SNP marker loci distributed across the genome in 749 Italian Brown and 364 Piedmontese bulls. The statistical significance of Fst values was assessed using a control chart. The LOWESS technique was efficient in removing noise from the raw data and was able to highlight selection signatures in chromosomes known to harbour genes affecting dairy and beef traits. Examples include the peaks detected for BTA2 in the region where the myostatin gene is located and for BTA6 in the region harbouring the ABCG2 locus. Moreover, several loci not previously reported in cattle studies were detected.

Signatures of selection identify loci associated with milk yield in sheep.

BACKGROUND: Identification of genomic regions that have been targets of selection for phenotypic traits is one of the most challenging areas of research in animal genetics, particularly in livestock where few annotated genes are available. In this study a genome-wide scan using the Illumina SNP50K Beadchip was performed in the attempt to identify genomic regions associated with milk productivity in sheep. The ovine genomic regions encoding putative candidate genes were compared with the corresponding areas in Bos taurus, as the taurine genome is better annotated. RESULTS: A total of 100 dairy sheep were genotyped on the Illumina OvineSNP50K Beadchip. The Fisher's exact test of significance of differences of allele frequency between each pair of the two tails of the distribution of top/worse milk yielders was performed for each marker. The genomic regions where highly divergent milk yielders showed different allele frequencies at consecutive markers was extracted from the OAR v3.1 Ovine (Texel) Genome Assembly, and was compared to the corresponding areas in Bos taurus, allowing the detection of two genes, the Palmdelphin and the Ring finger protein 145. These genes encoded non-synonymous mutations correlated with the marker alleles. CONCLUSION: The innovation of this study was to show that the DNA genotyping with the Illumina SNP50K Beadchip allowed to detect genes, and mutations in the genes, which have not yet been annotated in the livestock under investigation.

Use of partial least squares regression to impute SNP genotypes in Italian cattle breeds.

BACKGROUND: The objective of the present study was to test the ability of the partial least squares regression technique to impute genotypes from low density single nucleotide polymorphisms (SNP) panels i.e. 3K or 7K to a high density panel with 50K SNP. No pedigree information was used. METHODS: Data consisted of 2093 Holstein, 749 Brown Swiss and 479 Simmental bulls genotyped with the Illumina 50K Beadchip. First, a single-breed approach was applied by using only data from Holstein animals. Then, to enlarge the training population, data from the three breeds were combined and a multi-breed analysis was performed. Accuracies of genotypes imputed using the partial least squares regression method were compared with those obtained by using the Beagle software. The impact of genotype imputation on breeding value prediction was evaluated for milk yield, fat content and protein content. RESULTS: In the single-breed approach, the accuracy of imputation using partial least squares regression was around 90 and 94% for the 3K and 7K platforms, respectively; corresponding accuracies obtained with Beagle were around 85% and 90%. Moreover, computing time required by the partial least squares regression method was on average around 10 times lower than computing time required by Beagle. Using the partial least squares regression method in the multi-breed resulted in lower imputation accuracies than using single-breed data. The impact of the SNP-genotype imputation on the accuracy of direct genomic breeding values was small. The correlation between estimates of genetic merit obtained by using imputed versus actual genotypes was around 0.96 for the 7K chip. CONCLUSIONS: Results of the present work suggested that the partial least squares regression imputation method could be useful to impute SNP genotypes when pedigree information is not available.

A single nucleotide polymorphism in the promoter region of river buffalo stearoyl CoA desaturase gene (SCD) is associated with milk yield.

An association study between the milk yield trait and the stearoyl-CoA desaturase (SCD) polymorphism (g.133A > C) in Italian Mediterranean river buffalo was carried out. A full characterization of the river buffalo SCD promoter region was presented. Genotyping information was provided and a quick method for allelic discrimination was developed. The frequency of the C allele was 0·16. Test-day (TD) records (43 510) of milk production belonging to 226 lactations of 169 buffalo cows were analysed with a mixed linear model in order to estimate the effect of g.133A > C genotype, as well as the effect of parity and calving season. The SCD genotype was significantly associated with milk yield (P = 0·02). The genotype AC showed an over-dominance effect with an average daily milk yield approximately 2 kg/d higher than CC buffaloes. Such a difference represents about 28% more milk/d. The effect of the genotype was constant across lactation stages. The contribution of SCD genotype (r(2)SCD) to the total phenotypic variance in milk yield was equal to 0·12. This report is among the first indications of genetic association between a trait of economic importance in river buffalo. Although such results need to be confirmed with large-scale studies in the same and other buffalo populations, they might offer useful indications for the application of MAS programmes in river buffalo and in the future they might be of great economic interest for the river buffalo dairy industry.

An association analysis between OXT genotype and milk yield and flow in Italian Mediterranean river buffalo.

The aim of this study was to evaluate possible associations between three SNPs at the oxytocin locus (AM234538: g.28C>T; g.204A>G and g.1627G>T) and two productive traits, milk yield and milkability, in Italian Mediterranean river buffaloes. Effects of parity, calving season and month of production were also evaluated. A total of 41 980 test-day records belonging to 219 lactations of 163 buffalo cows were investigated. The allele call rate was 98·8% and the major allele frequency for all the investigated loci was 0·76. The OXT genotype was significantly associated with milk yield (P=0·029). The TT genotype showed an average daily milk yield approximately 1·7 kg higher than GT buffaloes. Such a difference represents about 23% more milk/d. A large dominance effect (-1·17±0·43 kg) was estimated, whereas the contribution of OXT genotype (r(2)(OXT)) to the total phenotypic variance in milk yield was equal to 0·06. The TT genotype showed higher values also for the milk flow, even though the estimated difference did not reach a level of statistical significance (P=0·07). Such an association, among the first reported for the oxytocin locus in ruminants, should be tested on a population scale and possible effects on milk composition traits should be evaluated in order to supply useful indications for the application of marker-assisted selection programmes in river buffaloes.

Pre-selection of most significant SNPS for the estimation of genomic breeding values.

The availability of a large amount of SNP markers throughout the genome of different livestock species offers the opportunity to estimate genomic breeding values (GEBVs). However, the estimation of many effects in a data set of limited size represent a severe statistical problem. A pre-selection of SNPS based on single regression may provide a reasonable compromise between accuracy of results, number of independent variables to be considered and computing requirements.A total of 595 and 618 SNPS were pre-selected using a simple linear regression for each SNP, based on phenotypes or polygenic EBVs, respectively, with an average distance of 9-10 cM between them. Chromosome four had the largest frequency of selected SNPS. Average correlations between GEBVs and TBVs were about 0.82 and 0.73 for the TRAINING generations when phenotypes or polygenic EBVs were considered as dependent variable, whereas they tend to decrease to 0.66 and 0.54 for the PREDICTION generations. The pre-selection of SNPs using the phenotypes as dependent variable together with a BLUP estimation of marker genotype effects using a variance contribution of each marker equal to sigma2a/nsnps resulted in a remarkable accuracy of GEBV estimation (0.77) in the PREDICTION generations.