N.P.P. Macciotta

Association Between a Polymorphism at the Stearoyl-CoA Desaturase Locus and Milk Production Traits in Italian Holsteins

Associations between stearoyl-CoA desaturase (SCD) gene polymorphisms and milk production traits (milk, fat, and protein yields, fat and protein contents, somatic cell score) were investigated on a sample of 701 lactations of 313 Italian Holsteins. Test-day records (5,097) were analyzed with a mixed linear model that included the fixed effects of herd, date of test, parity, genotype at the SCD locus, and lactation interval nested within SCD genotype, and the random effect of cow. An effect of the SCD genotype on milk and protein yields was detected, with VV cows producing more milk (about 2 kg/d) and protein (about 0.07 kg/d) compared with AA cows. The contribution of the SCD locus to the phenotypic variance of the 2 traits was about 0.015. These results suggest a possible use of the SCD locus in gene-assisted selection programs for the improvement of milk production traits in dairy cattle, although large-scale studies in different breeds are required.

Genome-wide analysis of Italian sheep diversity reveals a strong geographic pattern and cryptic relationships between breeds.

Italy counts several sheep breeds, arisen over centuries as a consequence of ancient and recent genetic and demographic events. To finely reconstruct genetic structure and relationships between Italian sheep, 496 subjects from 19 breeds were typed at 50K single nucleotide polymorphism loci. A subset of foreign breeds from the Sheep HapMap dataset was also included in the analyses. Genetic distances (as visualized either in a network or in a multidimensional scaling analysis of identical by state distances) closely reflected geographic proximity between breeds, with a clear north-south gradient, likely because of high levels of past gene flow and admixture all along the peninsula. Sardinian breeds diverged more from other breeds, a probable consequence of the combined effect of ancient sporadic introgression of feral mouflon and long-lasting genetic isolation from continental sheep populations. The study allowed the detection of previously undocumented episodes of recent introgression (Delle Langhe into the endangered Altamurana breed) as well as signatures of known, or claimed, historical introgression (Merino into Sopravissana and Gentile di Puglia; Bergamasca into Fabrianese, Appenninica and, to a lesser extent, Leccese). Arguments that would question, from a genomic point of view, the current breed classification of Bergamasca and Biellese into two separate breeds are presented. Finally, a role for traditional transhumance practices in shaping the genetic makeup of Alpine sheep breeds is proposed. The study represents the first exhaustive analysis of Italian sheep diversity in an European context, and it bridges the gap in the previous HapMap panel between Western Mediterranean and Swiss breeds.

Multivariate factor analysis of detailed milk fatty acid profile: Effects of dairy system, feeding, herd, parity, and stage of lactation

We investigated the potential of using multivariate factor analysis to extract metabolic information from data on the quantity and quality of milk produced under different management systems. We collected data from individual milk samples taken from 1,158 Brown Swiss cows farmed in 85 traditional or modern herds in Trento Province (Italy). Factor analysis was carried out on 47 individual fatty acids, milk yield, and 5 compositional milk traits (fat, protein, casein, and lactose contents, somatic cell score). According to a previous study on multivariate factor analysis, a variable was considered to be associated with a specific factor if the absolute value of its correlation with the factor was ≥0.60. The extracted factors were representative of the following 12 groups of fatty acids or functions: de novo fatty acids, branched fatty acid-milk yield, biohydrogenation, long-chain fatty acids, desaturation, short-chain fatty acids, milk protein and fat contents, odd fatty acids, conjugated linoleic acids, linoleic acid, udder health, and vaccelenic acid. Only 5 fatty acids showed small correlations with these groups. Factor analysis suggested the existence of differences in the metabolic pathways for de novo short- and medium-chain fatty acids and Δ9-desaturase products. An ANOVA of factor scores highlighted significant effects of the dairy farming system (traditional or modern), season, herd/date, parity, and days in milk. Factor behavior across levels of fixed factors was consistent with current knowledge. For example, compared with cows farmed in modern herds, those in traditional herds had higher scores for branched fatty acids, which were inversely associated with milk yield; primiparous cows had lower scores than older cows for de novo fatty acids, probably due to a larger contribution of lipids mobilized from body depots on milk fat yield. The statistical approach allowed us to reduce a large number of variables to a few latent factors with biological meaning and able to represent groups of fatty acids with a common origin and function. Multivariate factor analysis would therefore be a valuable tool for studying the influence of different production environments and individual animal factors on milk fatty acid composition, and for developing nutritional strategies able to manipulate the milk fatty acid profile according to consumer demand.

Somatic variability of Sarda goat breed analysed by multivariate methods

Somatic measurements of 780 Sarda goats were analysed by multivariate statistical methods to investigate the morphostructural variability of this breed. Discriminant analysis highlighted a gradual increase in size passing from flocks located on mountain (M) to hill (H) and coast (C) (Mahalanobis distances 1.159, 1.07 and 3.37 between M–H, H–C and M–C, respectively; P<0.001). Four latent common factors explained different quotas of original somatic (co)variances (70, 90 and 56% in mountain, hill and coast, respectively). Such behaviour can be related to the effect of both different environmental conditions and crosses with other breeds on body development of goats. The same reasons can also explain differences in the relative frequencies of udder conformation types, as in the case of pear-shaped udders between mountain and coast flocks (12 vs. 18%, respectively, P<0.001).

Derivation of multivariate indices of milk composition, coagulation properties, and individual cheese yield in dairy sheep.

Milk composition and its technological properties are traits of interest for the dairy sheep industry because almost all milk produced is processed into cheese. However, several variables define milk technological properties and a complex correlation pattern exists among them. In the present work, we measured milk composition, coagulation properties, and individual cheese yields in a sample of 991 Sarda breed ewes in 47 flocks. The work aimed to study the correlation pattern among measured variables and to obtain new synthetic indicators of milk composition and cheese-making properties. Multivariate factor analysis was carried out on individual measures of milk coagulation parameters; cheese yield; fat, protein, and lactose percentages; somatic cell score; casein percentage; NaCl content; pH; and freezing point. Four factors that were able to explain about 76% of the original variance were extracted. They were clearly interpretable: the first was associated with composition and cheese yield, the second with udder health status, the third with coagulation, and the fourth with curd characteristics. Factor scores were then analyzed by using a mixed linear model that included the fixed effect of parity, lambing month, and lactation stage, and the random effect of flock-test date. The patterns of factor scores along lactation stages were coherent with their technical meaning. A relevant effect of flock-test date was detected, especially on the 2 factors related to milk coagulation properties. Results of the present study suggest the existence of a simpler latent structure that regulates relationships between variables defining milk composition and coagulation properties in sheep. Heritability estimates for the 4 extracted factors were from low to moderate, suggesting potential use of these new variables as breeding goals.

The shape of sarda ewe lactation curve analysed by a compartimental model

Abstract The lactation curve of the dairy Sarda sheep breed is characterised by a notable dimorphism. Empirical mathematical models used to represent the lactation curve of dairy cattle can describe the regular curves but in the case of ‘irregular’ (or decayed) curves, they give parameter estimates which are out of the range of significance. For this reason, a mechanistic mathematical model of the milk secretion process, based on a physiological theory of the mammary gland, was analysed. According to the different evolution of the processes of activation and inactivation of mammary secretory cells, the output of the model is a biexponential function or a monoexponential function. Lactations of sixty-four mature Sardinian ewes were analysed. The biexponential function fitted regular lactation curves ( R 2 = 0.87) and the monoexponential form fitted decayed curves ( R 2 = 0.80). Parameter estimates were submitted to analysis of variance to estimate the influence of production level, type of lambing and udder health. The dimorphism of the lactation curve of the sheep does not seem to be affected by main environmental factors but a genetic influence could be hypothesised.

Detection of selection signatures in Piemontese and Marchigiana cattle, two breeds with similar production aptitudes but different selection histories

BackgroundDomestication and selection are processes that alter the pattern of within- and between-population genetic variability. They can be investigated at the genomic level by tracing the so-called selection signatures. Recently, sequence polymorphisms at the genome-wide level have been investigated in a wide range of animals. A common approach to detect selection signatures is to compare breeds that have been selected for different breeding goals (i.e. dairy and beef cattle). However, genetic variations in different breeds with similar production aptitudes and similar phenotypes can be related to differences in their selection history.MethodsIn this study, we investigated selection signatures between two Italian beef cattle breeds, Piemontese and Marchigiana, using genotyping data that was obtained with the Illumina BovineSNP50 BeadChip. The comparison was based on the fixation index (Fst), combined with a locally weighted scatterplot smoothing (LOWESS) regression and a control chart approach. In addition, analyses of Fst were carried out to confirm candidate genes. In particular, data were processed using the varLD method, which compares the regional variation of linkage disequilibrium between populations.ResultsGenome scans confirmed the presence of selective sweeps in the genomic regions that harbour candidate genes that are known to affect productive traits in cattle such as DGAT1, ABCG2, CAPN3, MSTN and FTO. In addition, several new putative candidate genes (for example ALAS1, ABCB8, ACADS and SOD1) were detected.ConclusionsThis study provided evidence on the different selection histories of two cattle breeds and the usefulness of genomic scans to detect selective sweeps even in cattle breeds that are bred for similar production aptitudes.

XVI th QTLMAS: simulated dataset and comparative analysis of submitted results for QTL mapping and genomic evaluation

BackgroundA common dataset was simulated and made available to participants of the XVIth QTL-MAS workshop. Tasks for the participants were to detect QTLs affecting three traits, to assess their possible pleiotropic effects, and to evaluate the breeding values in a candidate population without phenotypes using genomic information.MethodsFour generations consisting of 20 males and 1000 females were generated by mating each male with 50 females. The genome consisted of 5 chromosomes, each of 100 Mb size and carrying 2,000 equally distributed SNPs. Three traits were simulated in order to mimic milk yield, fat yield and fat content. Genetic (co)variances were generated from 50 QTLs with pleiotropic effects. Phenotypes for all traits were expressed only in females, and were provided for the first 3 generations. Fourteen methods for detecting single-trait QTL and 3 methods for investigating their pleiotropic nature were proposed. QTL mapping results were compared according to the following criteria: number of true QTL detected; number of false positives; and the proportion of the true genetic variance explained by submitted positions. Eleven methods for estimating direct genomic values of the candidate population were proposed. Accuracies and bias of predictions were assessed by comparing estimated direct genomic values with true breeding values.ResultsThe number of true detections ranged from 0 to 8 across methods and traits, false positives from 0 to 15, and the proportion of genetic variance captured from 0 to 0.82, respectively. The accuracy and bias of genomic predictions varied from 0.74 to 0.85 and from 0.86 to 1.34 across traits and methods, respectively.ConclusionsThe best results in terms of detection power were obtained by ridge regression that, however, led to a large number of false positives. Good results both in terms of true detections and false positives were obtained by the approaches that fit polygenic effects in the model. The investigation of the pleiotropic nature of the QTL permitted the identification of few additional markers compared to the single-trait analyses. Bayesian and grouped regularized regression methods performed similarly for genomic prediction while GBLUP produced the poorest results.

Modelling phenotypic (co)variances of test day records in dairy ewe

Abstract Two thousand six hundred and thirty test day (TD) records of dairy ewes on milk yield, fat and protein content were analysed by mixed linear models with different phenotypic (co)variance structures. In the first one (UN), (co)variances among TD records taken at different days in milk (DIM) intervals were not mathematically modelled. The second structure was the classical Compound Symmetry (CS) approach that assumes equal (co)variances among TD records within lactation. In the third one, the CS structure was combined with a first-order autoregressive process [AR(1)] in order to model both a time dependent and a time independent component of covariation between TDs. The different (co)variance models did not result in relevant variations in fixed effect estimates and in average lactation curves, whereas they gave contrasting results as far as individual TD covariations around the mean evolution pattern are concerned. The CS+AR(1) structure best fitted the data and pointed out the relevance of both a constant component of covariation within lactation and a lag dependent component, whose pattern exponentially decreases as the time interval between TD measures increases. Furthermore, interesting differences in the relative importance of these two components of covariation among the traits have been observed. Correlations among TD measures within lactation resulted more persistent for milk yield and protein content, whereas showed a lower magnitude and a more rapid decrease for fat content.

Use of a partial least-squares regression model to predict test day of milk, fat and protein yields in dairy goats

A model able to predict missing test day data for milk, fat and protein yields on the basis of few recorded tests was proposed, based on the partial least squares (PLS) regression technique, a multivariate method that is able to solve problems related to high collinearity among predictors. A data set of 1731 lactations of Sarda breed dairy Goats was split into two data sets, one for model estimation and the other for the evaluation of PLS prediction capability. Eight scenarios of simplified recording schemes for fat and protein yields were simulated. Correlations among predicted and observed test day yields were quite high (from 0·50 to 0·88 and from 0·53 to 0·96 for fat and protein yields, respectively, in the different scenarios). Results highlight great flexibility and accuracy of this multivariate technique.