Helene Larroque

Relationships between type and longevity in the Holstein breed

The relationship between type traits and longevity was studied in the French Holstein breed using a survival analysis model. In this model, the phenotypic value adjusted for systematic fixed effects, the estimated breeding value, or the residual value (defined as the difference between the adjusted phenotypic value and the estimated breeding value) of the cow for each type trait was included as a risk factor. This was done separately for two subpopulations (registered and nonregistered herds) and with or without adjustment for production traits, i.e., considering true or functional longevity. For both types of herds, udder traits (and above all, udder depth) clearly influenced the length of productive life. There seemed to be a more pronounced voluntary culling on type traits in registered herds. The correction for the within herd-year class of production traits, as a way to approximate functional longevity, increased the importance of udder traits and decreased the weight of capacity traits. The same results were obtained when the phenotypic value of the cow for type was replaced by her estimated breeding value, whereas residuals had little impact. The relationship between longevity and type traits was most often nonlinear, in particular for udder traits, but in this study, no trait with a clear intermediate optimum was found.

Genomic selection in the French Lacaune dairy sheep breed

Genomic selection aims to increase accuracy and to decrease generation intervals, thus increasing genetic gains in animal breeding. Using real data of the French Lacaune dairy sheep breed, the purpose of this study was to compare the observed accuracies of genomic estimated breeding values using different models (infinitesimal only, markers only, and joint estimation of infinitesimal and marker effects) and methods [BLUP, Bayes Cπ, partial least squares (PLS), and sparse PLS]. The training data set included results of progeny tests of 1,886 rams born from 1998 to 2006, whereas the validation set had results of 681 rams born in 2007 and 2008. The 3 lactation traits studied (milk yield, fat content, and somatic cell scores) had heritabilities varying from 0.14 to 0.41. The inclusion of molecular information, as compared with traditional schemes, increased accuracies of estimated breeding values of young males at birth from 18 up to 25%, according to the trait. Accuracies of genomic methods varied from 0.4 to 0.6, according to the traits, with minor differences among genomic approaches. In Bayes Cπ, the joint estimation of marker and infinitesimal effects had a slightly favorable effect on the accuracies of genomic estimated breeding values, and were especially beneficial for somatic cell counts, the less heritable trait. Inclusion of infinitesimal effects also improved slopes of predictive regression equations. Methods that select markers implicitly (Bayes Cπ and sparse PLS) were advantageous for some models and traits, and are of interest for further quantitative trait loci studies.

Anti-Müllerian hormone: a predictive marker of embryo production in cattle?

In cattle, the embryo production rate after superovulation varies between individuals and is difficult to predict. Recently, we proposed that anti-Müllerian hormone (AMH) plasma levels measured before treatment can help predict superovulatory responses. To establish whether blood measurement of AMH can help predict the number of embryos produced by a given cow after superovulation, data collected over 4 years from 45 dairy cows submitted to repeated embryo production were analysed in a retrospective study. A high within-animal repeatability (0.38 and 0.36) and a strong effect of the father of the donor cow (P < 0.01) were observed for the numbers of collected and transferable embryos, respectively. AMH concentration, measured in the plasma of donor cows during first lactation and several months before the start of the embryo production campaigns, was found to be highly correlated with the maximal number of collected (P < 0.0001) and transferable (P < 0.01) embryos per cow. In conclusion, the capacity of embryo production is a repeatable and probably heritable trait in the cow, and blood measurement of AMH in potential donor cows could be of value in determining a cows intrinsic capacity to produce transferable embryos.

Prediction of fatty acid profiles in cow, ewe, and goat milk by mid-infrared spectrometry

Mid-infrared (MIR) spectrometry was used to estimate the fatty acid (FA) composition in cow, ewe, and goat milk. The objectives were to compare different statistical approaches with wavelength selection to predict the milk FA composition from MIR spectra, and to develop equations for FA in cow, goat, and ewe milk. In total, a set of 349 cow milk samples, 200 ewe milk samples, and 332 goat milk samples were both analyzed by MIR and by gas chromatography, the reference method. A broad FA variability was ensured by using milk from different breeds and feeding systems. The methods studied were partial least squares regression (PLS), first-derivative pretreatment + PLS, genetic algorithm + PLS, wavelets + PLS, least absolute shrinkage and selection operator method (LASSO), and elastic net. The best results were obtained with PLS, genetic algorithm + PLS and first derivative + PLS. The residual standard deviation and the coefficient of determination in external validation were used to characterize the equations and to retain the best for each FA in each species. In all cases, the predictions were of better quality for FA found at medium to high concentrations (i.e., for saturated FA and some monounsaturated FA with a coefficient of determination in external validation >0.90). The conversion of the FA expressed in grams per 100mL of milk to grams per 100g of FA was possible with a small loss of accuracy for some FA.

A first step toward genomic selection in the multi-breed French dairy goat population.

The objectives of this study were to describe, using the goat SNP50 BeadChip (Illumina Inc., San Diego, CA), molecular data for the French dairy goat population and compare the effect of using genomic information on breeding value accuracy in different reference populations. Several multi-breed (Alpine and Saanen) reference population sizes, including or excluding female genotypes (from 67 males to 677 males, and 1,985 females), were used. Genomic evaluations were performed using genomic best linear unbiased predictor for milk production traits, somatic cell score, and some udder type traits. At a marker distance of 50kb, the average r(2) (squared correlation coefficient) value of linkage disequilibrium was 0.14, and persistence of linkage disequilibrium as correlation of r-values among Saanen and Alpine breeds was 0.56. Genomic evaluation accuracies obtained from cross validation ranged from 36 to 53%. Biases of these estimations assessed by regression coefficients (from 0.73 to 0.98) of phenotypes on genomic breeding values were higher for traits such as protein yield than for udder type traits. Using the reference population that included all males and females, accuracies of genomic breeding values derived from prediction error variances (model accuracy) obtained for young buck candidates without phenotypes ranged from 52 to 56%. This was lower than the average pedigree-derived breeding value accuracies obtained at birth for these males from the official genetic evaluation (62%). Adding females to the reference population of 677 males improved accuracy by 5 to 9% depending on the trait considered. Gains in model accuracies of genomic breeding values ranged from 1 to 7%, lower than reported in other studies. The gains in breeding value accuracy obtained using genomic information were not as good as expected because of the limited size (at most 677 males and 1,985 females) and the structure of the reference population.

Assessment of accuracy of genomic prediction for French Lacaune dairy sheep.

Genomic selection in Lacaune dairy sheep was investigated based on genotypes from the OvineSNP50 BeadChip (Illumina Inc., San Diego, CA). Historical artificial insemination progeny-tested rams formed a population of 2,892 genotyped rams. Additional ungenotyped rams and females were included by single-step genomic BLUP (ssGBLUP). Three prediction strategies were tried: pseudo-BLUP (using all rams and daughter yield deviations), pseudo-ssGBLUP (using all rams and daughter yield deviations), and regular ssGBLUP (using all phenotypes and pedigree in an animal model). The population linkage disequilibrium was determined, with an average squared correlation coefficient of 0.11 for markers closer than 0.1cM (lower than in dairy cattle). The estimated effective population is 370 individuals. Gain in accuracy of genomic selection over parent averages ranged from 0.10 to 0.20. Highest accuracies and lowest bias were found using regular ssGBLUP. Transition to a genomic breeding scheme is possible but costs need to be carefully evaluated.

Lactose in blood plasma and the ability of dairy cows to tolerate once-daily milking in terms of milk loss and milk recovery.

This experiment described the variability among cows with the aim of studying the ability of dairy cows to tolerate once-daily milking (ODM) in terms of milk losses and milk recoveries observed when cows are switched from twice- to once-daily milking and then back to twice-daily milking (TDM). It also aimed to investigate whether or not lactose in blood plasma, which indicates the mammary epithelium permeability, is correlated with milk losses and recoveries and, consequently, a potential candidate assessor of dairy cow tolerance to ODM. The study used 86 crossbred dairy cows (Holstein × Normande) split into 5 groups over 2 yr. The trial consisted of 3 successive periods: a 1-wk control period of TDM, then 3 wk of ODM, followed by 2 wk of TDM. Blood samples were collected 1 to 1.5h before the morning milking and 5 to 6h after milking on d -3, 0, 1, 3, 7, 21, 23, and 28, where d 0 is the last d of the control period. Milk losses measured as kilograms per day were higher in cows with highest control-period milk yields (r=-0.66). When expressed in relative terms (%), milk losses were weakly correlated with the control-period milk yield (r=-0.22). When switched back to TDM, cows recovered only 47% of the milk lost. Milk recovery (kg/d) was weakly correlated with control milk yield (r=0.34) and not correlated with ODM milk yield. Milk recovery was correlated with milk yield losses: the higher the milk yield losses (kg/d or %), the higher the milk recovery (kg/d; r=-0.59 and -0.52, respectively). Rate of milk recovery expressed as the quantity of milk recovered per kilogram of milk lost, was not correlated with milk loss expressed as a percentage. This means that to be considered well-adapted to ODM scheduling, a cow must be well adapted to milk loss, and be well adapted to milk recovery. Blood plasma lactose concentration (log(10)-transformed data) was not correlated with milk production levels in either control, ODM, or back-to-TDM periods. It was poorly correlated with milk loss but was positively correlated with milk recovery (kg/d) and rate of milk recovery. We conclude that blood plasma lactose needs to be coupled with other indicators for evaluating dairy cow tolerance to ODM.

L’hormone antimüllérienne, prédicteur endocrinien de la réponse à une stimulation ovarienne chez les bovins

The strong between-animal variability in the number of ovulations and embryos produced after ovarian stimulation by gonadotropins is a major limit to the development of embryo biotechnologies in cattle. In reproductive medicine, anti-mullerian hormone (AMH) is now widely used as an endocrine marker of the ovarian follicular reserve. In the cow, as in the woman, AMH is secreted by the granulosa cells of growing follicles. We have shown recently that in the cow, AMH is a very good endocrine marker of the population of small antral follicles that constitute the direct target of ovarian stimulatory treatments. AMH concentration measured in plasma before treatment varies between animals and is positively correlated to the number of ovulations and transferable embryos produced after an ovarian stimulatory treatment. Interestingly, AMH concentrations can remain stable over several months for each animal. Moreover, the number of embryos produced after ovarian stimulation is highly repeatable and has a relatively good heritability. From these observations, we propose the determination of AMH concentration in the plasma of a potential donor cow as a simple predictive method to evaluate both its level of ovarian activity and its capacity to produce high or low numbers of embryos. Optimal conditions for implementing this diagnostic test in cattle remain to be defined considering the age, the breed, the physiological status and the environmental factors related to breeding conditions for each animal.

Genetic parameter estimation for major milk fatty acids in Alpine and Saanen primiparous goats

Genetic parameters for 18 fatty acids or groups of fatty acids (FA), milk production traits, and somatic cell score (SCS) were estimated by restricted maximum likelihood with a repeatability animal model, using 45,259 test-day records from the first lactations of 13,677 Alpine and Saanen goats. Fatty acid data were collected as part of an extensive recording scheme (PhénoFinLait), and sample testing was based on mid-infrared spectra estimates. The total predicted FA content in milk was approximately 3.5% in Alpine and Saanen goats. Goat milk fat showed similar saturated FA to cattle and sheep, but higher contents of capric (C10:0) FA (~ 9.7 g/100g of milk fat). Heritability estimates ranged from 0.18 to 0.49 for FA and estimates were generally higher when FA were expressed in g/100g of milk fat compared with g/100g of milk. In general, the 3 specific short- and medium-chain goat FA, caproic acid (C6:0), caprylic acid (C8:0), and especially capric (C10:0) acid, had among the highest heritability estimates (from 0.21 to 0.37; average of 0.30). Heritability estimates for milk yield, fat and protein contents, and SCS were 0.22, 0.23, 0.39, 0.09, and 0.24, 0.20, 0.40, and 0.15, in Alpine and Saanen goats, respectively. When FA were expressed in g/100g of milk, genetic correlations between fat content and all FA were high and positive. Genetic correlations between the fat content and FA groups expressed in g/100g of fat led to further investigation of the association between fat content and FA profile within milk fat. Accordingly, in both Saanen and Alpine breeds, no significant genetic correlations were found between fat content and C16:0, whereas the correlations between fat content and specific goat FA (C6:0 to C10:0) were positive (0.17 to 0.59). In addition, the genetic correlation between fat content and C14:0 was negative (-0.17 to -0.35). The values of the genetic correlations between protein content and individual FA were similar, although genetic correlations between protein content and FA groups were close to zero. Genetic correlations of milk yield or SCS with the FA profile were weak. Results for genetic parameters for FA, however, should be further validated, because the low predicting ability of certain FA using mid-infrared spectra and the limited calibration data set might have resulted in low accuracy. In conclusion, our results indicated substantial genetic variation in goat milk FA that supported their amenability for genetic selection. In addition, selection on protein and fat contents is not expected to have an undesirable effect on the FA profile in regard to specificity of goat products and human health.

Diversity of dairy goat lactation curves in France

A high level of production at the peak of lactation may be associated with animal health disorders, high feeding costs, and reduced milk supply throughout the year. The objective of this study was to typologize the lactation curves in French dairy goats and analyze the influence of environmental and genetic factors on these curves. The data set consisted of 2,231,720 monthly test-day records of 213,534 French Saanen and Alpine goats recorded between September 2008 and June 2012. First, principal component analysis classified the shape of the lactation curves into 3 principal components: the first component accounted for milk yield level throughout lactation, the second component accounted for lactation persistency, and the third component accounted for milk yield in mid-lactation. Then, from the principal component scores, the lactations were clustered into 5 different groups. Most lactations had a similar shape to the mean curve, except 30% of the lactations that fell into 3 clusters that had a high production level at the peak and then a different persistency according to cluster. Estimated breeding value for milk yield and home region of breeding were the factors most related to lactation production level. Month of kidding, breed, and gestation stage had the biggest effect on persistency. Month of kidding was the factor most strongly linked to mid-lactation production. A herd effect was observed on all 3 principal components.