Microsatellite imputation using SNP data for parentage verification in four Italian sheep breeds.

Microsatellite markers (MS) have been widely used for parentage verification in most of the livestock species over the past decades mainly due to their high polymorphic information content. In the genomic era, the spread of genotype information as single-nucleotide polymorphism (SNP) has raised the question to effectively use SNPs also for parentage testing. Despite the clear advantages of SNP panels in terms of cost, accuracy, and automation, the transition from MS to SNP markers for parentage verification is still very slow and, so far, only routinely applied in cattle. A major difficulty during this transition period is the need of SNP data for parents and offspring, which in most cases is not yet feasible due to the genotyping cost. To overcome the unavailability of same genotyping platform during the transition period, in this study we aimed to assess the feasibility of a MS imputation pipeline from SNPs in four native sheep dairy breeds: Comisana (N = 331), Massese (N = 210), Delle Langhe (N = 59) and Sarda (N = 1003). Those sheep were genotyped for 11 MS and with the Ovine SNP50 Bead Chip. Prior to imputation, a quality control (QC) was performed, and SNPs located within a window of 2 Mb from each MS were selected. The core of the developed pipeline was made up of three steps: (a) storing of both MS and SNP data in a Variant Call Format file, (b) masking MS information in a random sample of individuals (10%), (c) imputing masked MS based on non-missing individuals (90%) using an imputation program. The feasability of the proposed methodology was assessed also among different training - testing split ratio, population size, number of flanking SNPs as well as within and among breeds. The accuracy of the MS imputation was assessed based on the genotype concordance as well as at parentage verification level in a subset of animals in which assigned parents' MS were available. A total of 8 MS passed the QC, and 505 SNPs were located within the ±2 Mb window from each MS, with an average of 63 SNPs per MS. The results were encouraging since when excluding the worst imputed MS (OARAE129), and regardless on the analyses performed (within and across breeds) for all breeds, we achieved an overall concordance rate over 94%. In addition, on average, the imputed offspring MS resulted in equivalent parentage outcome in 94% of the cases when compared to verification using original MS, highlighting both the feasibility and the eventual practical advantage of using this imputation pipeline.

Genetic evaluation of gestation length in Italian Holstein breed.

Gestation length (GL) can potentially affect health and performance of both the dam and the newborn calf, and it is controlled by two genetic components, direct and maternal. This means that both the calf (direct effect) and the cow (maternal effect) genotypes contribute to determine GL and its variability. The aims of the present study were to estimate direct and maternal variance components of GL, develop a routine genetic evaluation of GL in Italian Holstein and evaluate potential (un)favourable associations with traits for which selection is undertaken in this population. A multiple-trait repeatability linear animal model was employed for the estimation of variance components considering GL in first and later parities as different traits. The posterior mean (PM) of heritability of the direct effect was 0.43 for first parity and 0.35 for later parities. The PM of heritability of the maternal effect was lower, being 0.08 for primiparae and 0.06 for pluriparae. The posterior standard deviation (PSD) of the heritability estimates was small, ranging from 0.001 to 0.005. The relationship of direct and maternal effects with important traits such as milk yield and fertility indicated that selecting for extreme GL, longer or shorter, may have negative consequences on several traits, suggesting that GL has an intermediate optimum in dairy cattle. In conclusion, this study reveals that selecting an intermediate GL in the Italian Holstein population is advisable. Although scarcely variable compared to other conventional traits for which Italian Holstein is selected, GL is heritable and a deeper knowledge can be useful for decision-making at the farm level.

Integration of beef cattle international pedigree and genomic estimated breeding values into national evaluations, with an application to the Italian Limousin population.

BACKGROUND: International evaluations combine data from different countries allowing breeders to have access to larger panels of elite bulls and to increase the accuracy of estimated breeding values (EBV). However, international and national evaluations can use different sources of information to compute EBV (EBVINT and EBVNAT, respectively), leading to differences between them. Choosing one of these EBV results in losing the information that is contained only in the discarded EBV. Our objectives were to define and validate a procedure to integrate publishable sires' EBVINT and their associated reliabilities computed from pedigree-based or single-step international beef cattle evaluations into national evaluations to obtain "blended" EBV. The Italian (ITA) pedigree-based national evaluation was used as a case study to validate the integration procedure. METHODS: Publishable sires' international information, i.e. EBVINT and their associated reliabilities, was included in the national evaluation as pseudo-records. Data were available for 444,199 individual age-adjusted weaning weights of Limousin cattle from eight countries and 17,607 genotypes from four countries (ITA excluded). To mimic differences between international and national evaluations, international evaluations included phenotypes (and genotypes) of animals born prior to January 2019, while national evaluations included ITA phenotypes of animals born until April 2019. International evaluations using all available information were considered as reference scenarios. Publishable sires were divided into three groups: sires with ≥ 15, < 15 and no recorded offspring in ITA. RESULTS: Overall, for these three groups, integrating either pedigree-based or single-step international information into national pedigree-based evaluations improved the similarity of the blended EBV with the reference EBV compared to national evaluations without integration. For instance, the correlation with the reference EBV for direct (maternal) EBV went from 0.61 (0.79) for a national evaluation without integration to 0.97 (0.88) when integrating single-step international information, on average across all groups of publishable sires. CONCLUSIONS: Our proposed one-animal-at-a-time integration procedure yields blended EBV that are in close agreement with full international EBV for all groups of animals analysed. The procedure can be directly applied by countries since it does not rely on specific software and is computationally inexpensive, allowing straightforward integration of publishable sires' EBVINT from pedigree-based or single-step based international beef cattle evaluations into national evaluations.

Genome-wide association study for antibody response to Mycobacterium avium ssp. paratubeculosis in goats.

Mycobacterium avium ssp. paratuberculosis (MAP), causes Johne's disease (JD), or paratuberculosis, a chronic enteritis of ruminants, which in goats is characterized by ileal lesions. The work described here is a case-control association study using the Illumina Caprine SNP50 BeadChip to unravel the genes involved in susceptibility of goats to JD. Goats in herds with a high occurrence of Johne's disease were classified as healthy or infected based on the level of serum antibodies against MAP, and 331 animals were selected for the association study. Goats belonged to the Jonica (157) and Siriana breeds (174). Whole-genome association analysis identified one region suggestive of significance associated with an antibody response to MAP on chromosome 7 (p-value = 1.23 × 10-5 ). These results provide evidence for genetic loci involved in the antibody response to MAP in goats.

Using Pedigree and Genomic Data toward Better Management of Inbreeding in Italian Dairy Sheep and Goat Breeds.

The inbreeding coefficient is an important parameter for livestock management. Small ruminant breeders and associations mainly rely on pedigree information, but genomic tools are gaining relevance, overcoming possible pedigree inconsistencies. This study investigates the relationship between pedigree-based and genomic inbreeding in two goat and four sheep dairy breeds. Pedigree and genomic data (medium-density SNPchip) were obtained for 3107 goats and 2511 sheep. We estimated pedigree depth (number of fully traced generations, FullGen) and inbreeding (FPED), as well as two genomic inbreeding indexes, using runs of the homozygosity (FROH) and genomic relationship matrix (FGRM). The correlation between the inbreeding coefficients was assessed. A linear regression model (LRM) was fitted for estimating FPED from FROH. After quality control on genomic data, we retained 5085 animals. Mean inbreeding values were low, with higher FROH than FPED and FGRM. Breed differences can partially depend on different managements. The correlation between FPED and FROH was the highest and directly related to pedigree depth. The best LRM was chosen for FullGen ≥4 and ≥6 for goats and sheep, respectively; after excluding animals with extreme residuals, a new refined regression equation was calculated. Since massive genotyping is not affordable to small ruminant breeders, it is important to understand the distinction and relationship between differently calculated inbreeding coefficients, also in view of the introduction of genomic enhanced breeding values. Our study highlights the importance of accurate pedigree information and, especially if not obtainable, of calculating genomic-based inbreeding coefficients. A better estimation of animals' relatedness contributes to improve animal breeding and conservation.

Relationship among Milk Conductivity, Production Traits, and Somatic Cell Score in the Italian Mediterranean Buffalo.

The measurement of milk electrical conductivity (EC) is a relatively simple and inexpensive technique that has been evaluated as a routine method for the diagnosis of mastitis in dairy farms. The aim of this study was to obtain further knowledge on relationships between EC, production traits and somatic cell count (SCC) in Italian Mediterranean Buffalo. The original dataset included 5411 records collected from 808 buffalo cows. Two mixed models were used to evaluate both the effect of EC on MY, PP and FP and EC at test-day, and the effect of EC on somatic cell score (SCS) by using five different parameters (EC_param), namely: EC collected at the official milk recording test day (EC_day0), EC collected 3 days before official milk recording (EC_day3), and three statistics calculated from EC collected 1, 3 and 5 days before each test-day, respectively. All effects included in the model were significant for all traits, with the only exception of the effect of EC nested within parity for FP. The relationship between EC and SCS was always positive, but of different magnitude according to the parity. The regression of EC on SCS at test-day using different EC parameters was always significant except when the regression parameter was the slope obtained from a linear regression of EC collected over the 5-day period. Moreover, in order to evaluate how well the different models fit the data, three parameters were used: the Average Information Criteria (AIC), the marginal R2 and the conditional R2. According to AIC and to both the Marginal and Conditional R2, the best results were obtained when the regression parameter was the mean EC estimated over the 5-day period.

Machine Learning Algorithms Highlight tRNA Information Content and Chargaff's Second Parity Rule Score as Important Features in Discriminating Probiotics from Non-Probiotics.

Probiotic bacteria are microorganisms with beneficial effects on human health and are currently used in numerous food supplements. However, no selection process is able to effectively distinguish probiotics from non-probiotic organisms on the basis of their genomic characteristics. In the current study, four Machine Learning algorithms were employed to accurately identify probiotic bacteria based on their DNA characteristics. Although the prediction accuracies of all algorithms were excellent, the Neural Network returned the highest scores in all the evaluation metrics, managing to discriminate probiotics from non-probiotics with an accuracy greater than 90%. Interestingly, our analysis also highlighted the information content of the tRNA sequences as the most important feature in distinguishing the two groups of organisms probably because tRNAs have regulatory functions and might have allowed probiotics to evolve faster in the human gut environment. Through the methodology presented here, it was also possible to identify seven promising new probiotics that have a higher information content in their tRNA sequences compared to non-probiotics. In conclusion, we prove for the first time that Machine Learning methods can discriminate human probiotic from non-probiotic organisms underlining information within tRNA sequences as the most important genomic feature in distinguishing them.

Automated image analysis to assess hygienic behaviour of honeybees.

Focus of this study is to design an automated image processing pipeline for handling uncontrolled acquisition conditions of images acquired in the field. The pipeline has been tested on the automated identification and count of uncapped brood cells in honeybee (Apis Mellifera) comb images to reduce the workload of beekeepers during the study of the hygienic behavior of honeybee colonies. The images used to develop and test the model were acquired by beekeepers on different days and hours in summer 2020 and under uncontrolled conditions. This resulted in images differing for background noise, illumination, color, comb tilts, scaling, and comb sizes. All the available 127 images were manually cropped to approximately include the comb area. To obtain an unbiased evaluation, the cropped images were randomly split into a training image set (50 images), which was used to develop and tune the proposed model, and a test image set (77 images), which was solely used to test the model. To reduce the effects of varied illuminations or exposures, three image enhancement algorithms were tested and compared followed by the Hough Transform, which allowed identifying individual cells to be automatically counted. All the algorithm parameters were automatically chosen on the training set by grid search. When applied to the 77 test images the model obtained a correlation of 0.819 between the automated counts and the experts' counts. To provide an assessment of our model with publicly available images acquired by a different equipment and under different acquisition conditions, we randomly extracted 100 images from a comb image dataset made available by a recent literature work. Though it has been acquired under controlled exposure, the images in this new set have varied illuminations; anyhow, our pipeline obtains a correlation between automatic and manual counts equal to 0.997. In conclusion, our tests on the automatic count of uncapped honey bee comb cells acquired in the field and on images extracted from a publicly available dataset suggest that the hereby generated pipeline successfully handles varied noise artifacts, illumination, and exposure conditions, therefore allowing to generalize our method to different acquisition settings. Results further improve when the acquisition conditions are controlled.

Genetic diversity and population history of eight Italian beef cattle breeds using measures of autozygosity.

In the present study, GeneSeek GGP-LDv4 33k single nucleotide polymorphism chip was used to detect runs of homozygosity (ROH) in eight Italian beef cattle breeds, six breeds with distribution limited to Tuscany (Calvana, Mucca Pisana, Pontremolese) or Sardinia (Sarda, Sardo Bruna and Sardo Modicana) and two cosmopolitan breeds (Charolais and Limousine). ROH detection analyses were used to estimate autozygosity and inbreeding and to identify genomic regions with high frequency of ROH, which might reflect selection signatures. Comparative analysis among breeds revealed differences in length and distribution of ROH and inbreeding levels. The Charolais, Limousine, Sarda, and Sardo Bruna breeds were found to have a high frequency of short ROH (~ 15.000); Calvana and Mucca Pisana presented also runs longer than 16 Mbp. The highest level of average genomic inbreeding was observed in Tuscan breeds, around 0.3, while Sardinian and cosmopolitan breeds showed values around 0.2. The population structure and genetic distances were analyzed through principal component and multidimensional scaling analyses, and resulted in a clear separation among the breeds, with clusters related to productive purposes. The frequency of ROH occurrence revealed eight breed-specific genomic regions where genes of potential selective and conservative interest are located (e.g. MYOG, CHI3L1, CHIT1 (BTA16), TIMELESS, APOF, OR10P1, OR6C4, OR2AP1, OR6C2, OR6C68, CACNG2 (BTA5), COL5A2 and COL3A1 (BTA2)). In all breeds, we found the largest proportion of homozygous by descent segments to be those that represent inbreeding events that occurred around 32 generations ago, with Tuscan breeds also having a significant proportion of segments relating to more recent inbreeding.

Effects of Heated Drinking Water on the Growth Performance and Rumen Functionality of Fattening Charolaise Beef Cattle in Winter.

The effects of heated drinking water on growth performance and rumen functionality in fattening beef cattle during winter were evaluated. Newly received Charolaise bulls (n = 224) were allocated to two experimental groups: (i) water at room temperature (RTW) (weight 408 ± 34 kg); (ii) constantly heated water (25 °C) (HW) (weight 405 ± 38 kg). Growth performances, feed intake, feed conversion rate, water intake and carcass characteristics were evaluated. Internal reticuloruminal wireless boluses were used to collect rumen pH and temperature values every 10 min. Bodyweight was not affected by the water temperature, but the overall average daily gain (ADG) was significantly higher in the HW group (1.486 vs. 1.438 kg/head/day in the RTW; p = 0.047). Dry matter intake was significantly higher in the HW group (p = 0.001), even though the final feed conversion rate (FCR) was not influenced. There was also a tendency for better cold carcass weight (CCW) and carcass yield (CY) in the HW group. Drinking heated water reduced the time (min/day) during which the ruminal pH was below pH 5.8 or 5.5, and the time during which the temperature was lower than 37 or 39 °C (p < 0.001). The use of heated drinking water is a plausible a strategy for enhancing ruminal stability and the overall production efficiency in fattening beef cattle, which will lead to both better growth performance and higher ruminal stability.

Effect of Weeping Teats on Intramammary Infection and Somatic Cell Score in Dairy Goats.

Mastitis is the most common disease affecting dairy goats and causing economic losses. Although it is accepted that increased somatic cell count (SCC) is mainly a response to infection, its reliability for subclinical mastitis detection in goats is controversial. Indeed, many physiological and extrinsic variables can increase SCC, including breed, parity, age, stage of lactation, seasonal variations, and milking methods. In some animals, milk-secreting tissue is present in the wall of the teat and, in some instances, milk can filter through pores in the skin to the udder surface. This condition is known as "weeping teat" (WT). In these animals, mammary tissue might be prone to develop bacterial infections, although limited information is provided. Weeping teat seems to have a genetic background and is reported to be especially found in goat breeds selected for high milk production. Moreover, it is observed a genetic correlation between WT and decreased milk yield as well as increased somatic cell scores (SCS). Since information on this topic is very limited, this study aimed at investigating any possible relationship between WT, high SCC, and the presence of bacteria in goat milk. Alpine goat farms in Northern Italy were selected based on the presence of WT. Each herd was divided into two age-matched groups, identified as case (WT+) and control (WT-). Half-udder milk samples were collected aseptically at three timepoints; bacteriological analysis was performed, and SCC were determined and transformed in SCS. There was a positive association between SCS and the presence of bacteria in milk (P = 0.037) overall, whereas WT udder defect was associated with positive bacterial culture in just one herd (P = 0.053). Thus, this herd was further investigated, repeating the sampling and the analysis on the following year. The positive association between high SCS and the presence of bacteria in milk was then confirmed (P = 0.007), whereas no association with WT condition was found. These results indicate that WT defect is usually unrelated to both the outcome of milk bacterial culture and SCS. As a side outcome, we could confirm the role of bacterial infection in increasing SCS.

Comparison of machine learning methods to predict udder health status based on somatic cell counts in dairy cows.

Bovine mastitis is one of the most important economic and health issues in dairy farms. Data collection during routine recording procedures and access to large datasets have shed the light on the possibility to use trained machine learning algorithms to predict the udder health status of cows. In this study, we compared eight different machine learning methods (Linear Discriminant Analysis, Generalized Linear Model with logit link function, Naïve Bayes, Classification and Regression Trees, k-Nearest Neighbors, Support Vector Machines, Random Forest and Neural Network) to predict udder health status of cows based on somatic cell counts. Prediction accuracies of all methods were above 75%. According to different metrics, Neural Network, Random Forest and linear methods had the best performance in predicting udder health classes at a given test-day (healthy or mastitic according to somatic cell count below or above a predefined threshold of 200,000 cells/mL) based on the cow's milk traits recorded at previous test-day. Our findings suggest machine learning algorithms as a promising tool to improve decision making for farmers. Machine learning analysis would improve the surveillance methods and help farmers to identify in advance those cows that would possibly have high somatic cell count in the subsequent test-day.

Accounting for Genetic Differences Among Unknown Parents in Bubalus bubalis: A Case Study From the Italian Mediterranean Buffalo.

The use of genetic evaluations in the Water Buffalo by means of a Best Linear Unbiased Prediction (BLUP) animal model has been increased over the last two-decades across several countries. However, natural mating is still a common reproductive strategy that can increase the proportion of missing pedigree information. The inclusion of genetic groups in variance component (VC) and breeding value (EBV) estimation is a possible solution. The aim of this study was to evaluate two different genetic grouping strategies and their effects on VC and EBV for composite (n = 5) and linear (n = 10) type traits in the Italian Mediterranean Buffalo (IMB) population. Type traits data from 7,714 buffalo cows plus a pedigree file including 18,831 individuals were provided by the Italian National Association of Buffalo Breeders. VCs and EBVs were estimated for each trait fitting a single-trait animal model and using the official DNA-verified pedigree. Successively, EBVs were re-estimated using modified pedigrees with two different proportion of missing genealogies (30 or 60% of buffalo with records), and two different grouping strategies, year of birth (Y30/Y60) or genetic clustering (GC30, GC60). The different set of VCs, estimated EBVs and their standard errors were compared with the results obtained using the original pedigree. Results were also compared in terms of efficiency of selection. Differences among VCs varied according to the trait and the scenario considered. The largest effect was observed for two traits, udder teat and body depth in the GC60 genetic cluster, whose heritability decreased by -0.07 and increased by +0.04, respectively. Considering buffalo cows with record, the average correlation across traits between official EBVs and EBVs from different scenarios was 0.91, 0.88, 0.84, and 0.79 for Y30, CG30, Y60, and CG60, respectively. In bulls the correlations between EBVs ranged from 0.90 for fore udder attachment and udder depth to 0.96 for stature and body length in the GC30 scenario and from 0.75 for udder depth to 0.90 for stature in the GC60 scenario. When a variable proportion of missing pedigree is present using the appropriate strategy to define genetic groups and including them in VC and EBV is a worth-while and low-demanding solution.

'Meta-analysis of dry matter intake and neutral detergent fiber intake of hair sheep raised in tropical areas'.

Inadequate estimates of fiber and dry matter intake of sheep raised in tropical conditions may explain part of the inefficiency of those production systems. Therefore, we aimed to estimate dry matter intake (DMI) and neutral detergent fiber intake (NDFI) of hair sheep raised under tropical conditions. A meta-analysis of 61 independent performance experiments, comprising a total of 413 experimental units (treatment means or animals), was performed. Trials were conducted in tropical conditions, using hair sheep in growing and finishing phases and endowed with the following information: neutral detergent fiber (NDF) in diet, initial and final body weight (BW), average daily gain (ADG), DMI and NDFI of treatment means (51 studies) or individual data (10 studies). Data on organic matter and NDF digestibilities were collected to estimate D-value (Dv) and B-value (Bv) (20 and 33 studies, respectively). The equations obtained were: [Formula: see text] DMI (g/kg BW) as a function of Dv (g/kg DM) revealed a quadratic relationship, whose point of maximum DMI (38.69 g/kg BW) was obtained at 634.1 g/kg DM Dv. On the other hand, DMI decreased linearly as Bv (g/kg DM) increased. In conclusion, equations to predict DMI from BW and ADG as well to predict NDFI from dietary NDF were fitted with great accuracy and are recommended for hair sheep raised in tropical regions. DMI values were, in general, greater than those reported by the NRC, AFRC and INRA systems, which may be a reflection of the sheep breeds used in this study. Using Dv and Bv concepts was satisfactory to describe an integrated mechanism between metabolic and bulking regulation of DMI in sheep.

Heritability of Teat Condition in Italian Holstein Friesian and Its Relationship with Milk Production and Somatic Cell Score.

In spite of the impressive advancements observed on both management and genetic factors, udder health still represents one of most demanding objectives to be attained in the dairy cattle industry. Udder morphology and especially teat condition might represent the first physical barrier to pathogens' access. The objectives of this study were to investigate the genetic component of teat condition and to elucidate its relationship with both milk yield and somatic cell scores in dairy cattle. Moreover, the effect of selection for both milk yield and somatic cell scores on teat condition was also investigated. A multivariate analysis was conducted on 10,776 teat score records and 30,160 production records from 2469 Italian Holstein cows. Three teat scoring traits were defined and included in the analysis. Heritability estimates for the teat score traits were moderate to low, ranging from 0.084 to 0.238. When teat score was based on a four-classes ordinal scoring, its genetic correlation with milk yields and somatic cell score were 0.862 and 0.439, respectively. The scale used to classify teat-end score has an impact on the magnitude of the estimates. Genetic correlations suggest that selection for milk yield could deteriorate teat health, unless more emphasis is given to somatic cell scores. Considering that both at national and international level, the current selection objectives are giving more emphasis to health traits, a further genetic deterioration in teat condition is not expected.

Genetic parameters of weeping teats in Italian Saanen and Alpine dairy goats and their relationship with milk production and somatic cell score.

This paper reports a quantitative genetics analysis of weeping teats (WT), an abnormality of the mammary gland in goats. Weeping teats are characterized by milk oozing out of the teat or by the presence of multiple cysts near its base. This abnormality has been routinely recorded in Italian Alpine and Saanen goats since 2000 using a score of 0 or 1 (0 = defect not present, 1 = defect present). No information is available on the genetic background of WT or its relationship with production or other udder-related traits. Data obtained by the Italian National Sheep and Goat Breeders Association (Rome, Italy) were used to estimate both heritability of WT and its genetic correlation with milk yield, somatic cell score, and udder traits. The final data set used in the analysis included 2,178 Saanen and 2,309 Alpine primiparous goats kidding from 2009 to 2014. The pedigree data included 7,333 Saanen and 7,421 Alpines, respectively. A threshold-linear multivariate animal model was used to estimate variance and covariance components. A genealogical data analysis was also implemented, including genealogical data completeness, inbreeding, and identification of possible most recent common ancestors. On average, around 4 and 13% of primiparous Saanen and Alpine females kidding from 2009 to 2014 showed mammary gland abnormality, respectively. Weeping teats heritability was 0.27 and 0.26 for Saanen and Alpine, respectively. Genetic correlations between milk production or somatic cell score ranged from -0.16 in Saanen to 0.43 in Alpine, but the standard error of the estimates was very large. Positive genetic correlations were observed among WT and teat characteristics in both Saanen and Alpine. The average inbreeding of abnormality carriers was 2.4 and 5.1 for Saanen and Alpine, respectively. The genealogical data analysis identified 4 common ancestors of affected does in Saanen and 2 in Alpine. These results indicate that WT have a possible genetic background. A genome-wide association study might help in understanding the polygenic or monogenic determination of this abnormality.

Population Structure and Genetic Diversity of Italian Beef Breeds as a Tool for Planning Conservation and Selection Strategies.

The aim was to investigate the population structure of eight beef breeds: three local Tuscan breeds under extinction, Calvana (CAL), Mucca Pisana (MUP), and Pontremolese (PON); three local unselected breeds reared in Sardinia, Sarda (SAR), Sardo Bruna (SAB), and Sardo Modicana (SAM); and two cosmopolitan breeds, Charolais (CHA) and Limousine (LIM), reared in the same regions. An effective population size ranges between 14.62 (PON) to 39.79 (SAM) in local breeds, 90.29 for CHA, and 135.65 for LIM. The average inbreeding coefficients were higher in Tuscan breeds (7.25%, 5.10%, and 3.64% for MUP, CAL, and PON, respectively) compared to the Sardinian breeds (1.23%, 1.66%, and 1.90% in SAB, SAM, and SAR, respectively), while for CHA and LIM they were <1%. The highest rates of mating between half-siblings were observed for CAL and MUP (~9% and 6.5%, respectively), while the highest rate of parent-offspring mating was ~8% for MUP. Our findings describe the urgent situation of the three Tuscan breeds and support the application of conservation measures and/or the development of breeding programs. Development of breeding strategies is suggested for the Sardinian breeds.

Rumination time as a potential predictor of common diseases in high-productive Holstein dairy cows.

We examined the hypothesis that rumination time (RT) could serve as a useful predictor of various common diseases of high producing dairy cows and hence improve herd management and animal wellbeing. We measured the changes in rumination time (RT) in the days before the recording of diseases (specifically: mastitis, reproductive system diseases, locomotor system issues, and gastroenteric diseases). We built predictive models to assess the association between RT and these diseases, using the former as the outcome variable, and to study the effects of the latter on the former. The average Pseudo-R 2 of the fitted models was moderate to low, and this could be due to the fact that RT is influenced by other additional factors which have a greater effect than the predictors used here. Although remaining in a moderate-to-low range, the average Pseudo-R 2 of the models regarding locomotion issues and gastroenteric diseases was higher than the others, suggesting the greater effect of these diseases on RT. The results are encouraging, but further work is needed if these models are to become useful predictors.

Design and validation of a 90K SNP genotyping assay for the water buffalo (Bubalus bubalis).

BACKGROUND: The availability of the bovine genome sequence and SNP panels has improved various genomic analyses, from exploring genetic diversity to aiding genetic selection. However, few of the SNP on the bovine chips are polymorphic in buffalo, therefore a panel of single nucleotide DNA markers exclusive for buffalo was necessary for molecular genetic analyses and to develop genomic selection approaches for water buffalo. The creation of a 90K SNP panel for river buffalo and testing in a genome wide association study for milk production is described here. METHODS: The genomes of 73 buffaloes of 4 different breeds were sequenced and aligned against the bovine genome, which facilitated the identification of 22 million of sequence variants among the buffalo genomes. Based on frequencies of variants within and among buffalo breeds, and their distribution across the genome, inferred from the bovine genome sequence, 90,000 putative single nucleotide polymorphisms were selected to create an Axiom® Buffalo Genotyping Array 90K. RESULTS: This 90K "SNP-Chip" was tested in several river buffalo populations and found to have ∼70% high quality and polymorphic SNPs. Of the 90K SNPs about 24K were also found to be polymorphic in swamp buffalo. The SNP chip was used to investigate the structure of buffalo populations, and could distinguish buffalo from different farms. A Genome Wide Association Study identified genomic regions on 5 chromosomes putatively involved in milk production. CONCLUSION: The 90K buffalo SNP chip described here is suitable for the analysis of the genomes of river buffalo breeds, and could be used for genetic diversity studies and potentially as a starting point for genome-assisted selection programmes. This SNP Chip could also be used to analyse swamp buffalo, but many loci are not informative and creation of a revised SNP set specific for swamp buffalo would be advised.

Virulence Genes of S. aureus from Dairy Cow Mastitis and Contagiousness Risk.

Staphylococcus aureus (S. aureus) is a major agent of dairy cow intramammary infections: the different prevalences of mastitis reported might be related to a combination of S. aureus virulence factors beyond host factors. The present study considered 169 isolates from different Italian dairy herds that were classified into four groups based on the prevalence of S. aureus infection at the first testing: low prevalence (LP), medium-low (MLP), medium-high (MHP) and high (HP). We aimed to correlate the presence of virulence genes with the prevalence of intramammary infections in order to develop new strategies for the control of S. aureus mastitis. Microarray data were statistically evaluated using binary logistic regression and correspondence analysis to screen the risk factors and the relationship between prevalence group and gene. The analysis showed: (1) 24 genes at significant risk of being detected in all the herds with infection prevalence >5%, including genes belonging to microbial surface components recognizing adhesive matrix molecules (MSCRAMMs), immune evasion and serine proteases; and (2) a significant correlation coefficient between the genes interacting with the host immune response and HP isolates against LP ones. These results support the hypothesis that virulence factors, in addition to cow management, could be related to strain contagiousness, offering new insights into vaccine development.