Short communication: Imputing genotypes using PedImpute fast algorithm combining pedigree and population information

Routine genomic evaluations frequently include a preliminary imputation step, requiring high accuracy and reduced computing time. A new algorithm, PedImpute (http://dekoppel.eu/pedimpute/), was developed and compared with findhap (http://aipl.arsusda.gov/software/findhap/) and BEAGLE (http://faculty.washington.edu/browning/beagle/beagle.html), using 19,904 Holstein genotypes from a 4-country international collaboration (United States, Canada, UK, and Italy). Different scenarios were evaluated on a sample subset that included only single nucleotide polymorphism from the Bovine low-density (LD) Illumina BeadChip (Illumina Inc., San Diego, CA). Comparative criteria were computing time, percentage of missing alleles, percentage of wrongly imputed alleles, and the allelic squared correlation. Imputation accuracy on ungenotyped animals was also analyzed. The algorithm PedImpute was slightly more accurate and faster than findhap and BEAGLE when sire, dam, and maternal grandsire were genotyped at high density. On the other hand, BEAGLE performed better than both PedImpute and findhap for animals with at least one close relative not genotyped or genotyped at low density. However, computing time and resources using BEAGLE were incompatible with routine genomic evaluations in Italy. Error rate and allelic squared correlation attained by PedImpute ranged from 0.2 to 1.1% and from 96.6 to 99.3%, respectively. When complete genomic information on sire, dam, and maternal grandsire are available, as expected to be the case in the close future in (at least) dairy cattle, and considering accuracies obtained and computation time required, PedImpute represents a valuable choice in routine evaluations among the algorithms tested

Relationship among production traits, somatic cell score and temperature–humidity index in the Italian Mediterranean Buffalo

The temperature–humidity index (THI) has been commonly used to analyse heat stress in dairy cattle, but little is known about its effects on buffaloes. In this study, daily milk yield (MY), fat percentage (FP), protein percentage (PP) and somatic cell count (SCC) data from 808 buffalo cows plus environmental temperature and relative humidity were used to investigate the consequence of heat stress. Two mixed models were used to evaluate the impact of THI on MY, FP, PP and log transformed SCC (SCS). The effect of THI was significant for PP, FP and SCS, whereas its interaction with parity was statistically significant for PP and SCS. The relationship between PP and FP and THI was positive but of different magnitude according to the parity. When THI was below 62, an unfavourable effect was observed, especially in primiparous buffalo cows. A significant interaction between SCS and THI across parities was also observed. The effect of THI on MY across parities was not definite but overall a favourable relationship was observed. Our findings depict a susceptibility of buffaloes to low values of THI, suggesting an optimal THI range for water buffaloes between 59 and 63, although some deleterious effects were observed in primiparous buffaloes at THI values lower than 62. Additional investigations are needed to better elucidate the influence of THI on buffalo species.HIGHLIGHTS The overall effect of THI on buffalo diverges from what commonly observed in dairy cattle Cold stress affects milk and udder health in buffaloes The effect of THI on buffaloes’ performance depends on parity, with a larger susceptibility in primiparous than pluriparous buffalo cows Udder health in buffaloes, evaluated using somatic cell count, is also affected by THI

Genomic investigation of milk production in Italian buffalo

The aim of this study was to test the feasibility of genomic selection in the Italian Mediterranean water buffalo, which is farmed mainly in the south Italy for milk, and mozzarella, production. A total of 498 animals were genotyped at 49,164 loci. Test day records (80,417) of milk (MY), fat (FY) and protein (PY) yields from 4127 cows, born between 1975 and 2009, were analysed in a three-trait model. Cows born in 2008 and 2009 with phenotypes and genotypes were selected as validation animals (n = 50). Variance components (VC) were estimated with BLUP and ssGBLUP. Heritabilities for BLUP were 0.25 ± 0.02 (MY), 0.16 ± 0.01 (FY) and 0.25 ± 0.01 (PY). Breeding values were computed using BLUP and ssGBLUP, using VC estimated from BLUP. ssGBLUP was applied in five scenarios, each with a different number of genotypes available: (A) bulls (35); (B) validation cows (50); (C) bulls and validation cows (85); (D) all genotyped cows (463); (E) all genotypes (498). Model validation was performed using the LR method: correlation, accuracy, dispersion, and bias statistics were calculated. Average correlations were 0.71 ± 0.02 and 0.82 ± 0.01 for BLUP and ssGBLUP-E, respectively. Accuracies were also higher in ssGBLUP-E (0.75 ± 0.03) compared to BLUP (0.57 ± 0.03). The best dispersions (i.e. closer to 1) were found for ssGBLUP-C. The use of genotypes only for the 35 bulls did not change the validation values compared to BLUP. Results of the present study, even if based on small number of animals, showed that the inclusion of genotypes of females can improve breeding values accuracy in the Italian Buffalo.Highlights The genotypes of males did not improve the predictions. Genotypes of females improve breeding values accuracy. Slight increase in prediction accuracy with weighted ssGBLUP

Genetic diversity derived from pedigree information and estimation of genetic parameters for reproductive traits of Limousine and Charolais cattle raised in Italy

Limousine and Charolais cattle breeds are assuming increasing importance in the Italian beef cattle sector. Indeed, both breeds are involved in a national rural development project. The success of a breeding programme depends heavily not only on the defined breeding objective but also on the selected criteria used to attain it. Data from the Charolais and Limousine Italian Association (born between 1960 and 2017) were used to estimate both genetic parameters and trends for calving interval (CI) and age at first calving (AFC) and genetic diversity. Population structures were investigated through probabilities of gene origin approach whereas variance components estimation was used to obtain breeding values of reproductive parameters. Heritabilities for AFC and CI were 0.24 and 0.03 for Limousine and 0.32 and 0.02 for Charolais, respectively. An increasing genetic trend was observed for AFC. For CI, no significant gains of genetic origin have been verified. In both breeds, pedigree completeness was moderate, and the observed inbreeding coefficient was low. No herd is classified as a nucleus or isolated and they all use external bulls. Heritability for AFC in both breeds suggests possible improvements when selected. Limited improvements are expected for CI by means of a traditional genetic breeding scheme. A reduction in the generation interval might represent a cost-effective solution to increase annual genetic gain. Pedigree analysis suggests population bottleneck in both breeds.HIGHLIGHTS Limousine and Charolais breeds are involved in the national project for the genetic improvement of cattle populations raised in Italy. Genetic indexes will be developed following a genomic approach. This study is preparatory for the implementation of a selective programme of this type. The breeds presented a reduced number of animals in the genetic formation. High ‘bottleneck effect’. Moderate heritability for age at first calving

Genome wide association analysis of the 16th QTL- MAS Workshop dataset using the Random Forest machine learning approach

Genome wide association studies are now widely used in the livestock sector to estimate the association among single nucleotide polymorphisms (SNPs) distributed across the whole genome and one or more trait. As computational power increases, the use of machine learning techniques to analyze large genome wide datasets becomes possible

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\u2013low (MLP), medium\u2013high (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

Genomic characteristics of Staphylococcus aureus strains associated with high within-herd prevalence of intramammary infections in dairy cows

Staphylococcus aureus is one of the most important causes of mastitis in dairy cattle. Based on previous research, Staph. aureus genotypes with different pathogenic and contagious properties can cause intramammary infection (IMI) and coexist in the same herd. Our study aimed to compare Staph. aureus strains from herds that differed in IMI prevalence using different molecular approaches such as ribosomal spacer (RS)-PCR, multilocus sequence typing (MLST), spa typing, ribotyping, pulsed-field gel electrophoresis (PFGE), and multiplex PCR. For this purpose, 31 dairy herds with Staph. aureus IMI were selected, and 16 of these were chosen for a comparison study: the 8 high-prevalence (HP) herds had Staph. aureus IMI prevalence >28% and the 8 low-prevalence (LP) herds had an IMI prevalence <4%. A total of 650 isolates of Staph. aureus from mammary quarters of all positive cows were genotyped with RS-PCR, a technique based on amplification of a portion of the intergenic spacer 16S-23S rRNA, and a subset of 54 strains was also analyzed by multiplex PCR, ribotyping, PFGE, MLST, and spa typing. The RS-PCR analysis revealed 12 different profiles. Staphylococcus aureus strains isolated from 5 out of 8 HP herds showed a profile identical to the genotype B (GTB), described in previous studies as being strongly associated with high within-herd prevalence of Staph. aureus mastitis and the presence of the genes coding for enterotoxins sea, sed, and sej, a long x-region of spa gene, and 3 lukE fragments. Moreover, all strains isolated in the HP herds possessed genes coding for staphylococcal enterotoxins. In LP herds, a limited number of strains of 6 genotypes, different from those isolated in HP herds, were identified and GTB was not found. Within these genotypes, 4 strains were positive for the mecA gene. Preliminary results and comparison with other genotyping methods confirmed that genotyping by RS-PCR is an accurate, rapid, and inexpensive tool for future field studies on Staph. aureus mastitis strains and generates clinically relevant results