References of "Gengler, Nicolas"
     in
Bookmark and Share    
Full Text
Peer Reviewed
See detailNon-genetic sources of variation of milk production and reproduction and interactions between both classes of traits in Sicilo-Sarde dairy sheep.
Merai, A.; Gengler, Nicolas ULg; Hammami, Hedi ULg et al

in Animal (2014), 8(9), 1534-9

This work aimed to study the sources of variation in productive and reproductive traits of the dairy Sicilo-Sarde ewes and to further investigate the interaction between both classes of traits. After ... [more ▼]

This work aimed to study the sources of variation in productive and reproductive traits of the dairy Sicilo-Sarde ewes and to further investigate the interaction between both classes of traits. After edits, a database containing 5935 lactation records collected during 6 successive years in eight dairy flocks in the North of Tunisia was used. Total milked milk (TMM) in the milking-only period was retained as productive trait. The interval from the start of the mating period to the subsequent lambing (IML) and the lambing status (LS) were designed as reproductive traits. Sicilo-Sarde ewes had an average TMM of 60.93 l (+/-44.12) during 132.8 days (+/-46.6) after a suckling period of 100.4 days (+/-24.9). Average IML was 165.7 days. In a first step, the major factors influencing milk production and reproductive traits were determined. The significant sources of variation identified for TMM were: flock, month of lambing, year of lambing, parity, suckling length, litter size and milking-only length. Flockxmonth of the start of the mating period, parity, year of mating and litter size were identified as significant factors of variation for IML, while flockxmonth of the start of the mating period, parity and year of mating were identified as significant sources of variation for LS. In a second step, variance components were estimated using a three traits threshold mixed model, which combined LS as categorical trait and TMM and IML as continuous traits. Repeatability estimates were 0.21 (+/-0.03) for TMM, 0.09 (+/-0.02) for IML, and 0.10 (+/-0.05) for LS. Moreover, TMM and IML were found to be favorably associated for the flockx year of lambing effect (-0.45+/-0.18) but unfavorably associated for the animal effect (0.20+/-0.09). [less ▲]

Detailed reference viewed: 19 (6 ULg)
Full Text
Peer Reviewed
See detailA review of inversion techniques related to the use of relationship matrices in animal breeding
Faux, Pierre ULg; Gengler, Nicolas ULg

in Biotechnologie, Agronomie, Société et Environnement = Biotechnology, Agronomy, Society and Environment [=BASE] (2014), 18(3), 319-468

In animal breeding, prediction of genetic effects is usually obtained through the use of mixed models. For any of these genetic effects, mixed models require the inversion of the covariance matrix ... [more ▼]

In animal breeding, prediction of genetic effects is usually obtained through the use of mixed models. For any of these genetic effects, mixed models require the inversion of the covariance matrix associated to that effect, which is equal to the associated relationship matrix times the associated component of the genetic variance. Given the size of many genetic evaluation systems, computing the inverses of these relationship matrices is not trivial. In this review, we aim to cover computational techniques that ease inversion of relationship matrices used in animal breeding for prediction of the following different types of genetic effects: additive effect, gametic effect, effect due to presence of marked quantitative trait loci, dominance effect and different epistasis effects. Construction rules and inversion algorithms are detailed for each relationship matrix. In the final discussion, we draw up a common theoretical frame to most of the reviewed techniques. Two computational constraints come out of this theoretical frame: setting up the matrix of dependencies between levels of the effect and setting up some parts (diagonal or block-diagonal elements) of the relationship matrix to be inverted. [less ▲]

Detailed reference viewed: 37 (9 ULg)
Full Text
Peer Reviewed
See detailGenetic analysis of pig survival up to commercial weight in a crossbred population
Dufrasne, Marie ULg; Misztal, Ignacy; Tsuruta, Shogo et al

in Livestock Science (2014), 167

Records from 99,384 crossbred pigs from Duroc sires and Large White x Landrace dams were used to estimate genetic parameters for survival traits at different stages of the fattening period, and their ... [more ▼]

Records from 99,384 crossbred pigs from Duroc sires and Large White x Landrace dams were used to estimate genetic parameters for survival traits at different stages of the fattening period, and their relations with final weight. Traits analyzed were preweaning mortality (PWM), culling between weaning and harvesting (Call), culling during the farrowing period (Cfar), in the nursery site (Cnur), during the finishing phase (Cfin), and hot carcass weight (HCW). Because of the binary nature of PWM and culling traits, threshold-linear models were used: Model 1, including PWM, Call, and HCW; Model 2, including PWM, Cfar, Cnur, Cfin, and HCW. Both models included sex and parity number as fixed effects for all traits. Contemporary groups were considered as fixed effect for HCW and as random effects for the binary traits. Random effects were sire additive genetic, common litter, and residual effects for all traits and models. Heritability estimates were 0.03 for PWM, and 0.15 for HCW with both models, 0.06 for Call with Model 1, and 0.06 for Cfar, 0.14 for Cnur, and 0.10 for Cfin with Model 2. Litter variance explained a large part of the total variance and its influence declined slightly with age. For Model 1, genetic correlations were -0.36 between PWM and Call, -0.02 between PWM and HCW, and -0.25 between Call and HCW; correlations for litter effect were -0.15 between PWM and Call, -0.19 between PWM and HCW, and -0.21 between Call and HCW. For Model 2, genetic correlations were all positive between PWM and culling traits, except between PWM and Cnur (-0.61). Genetic correlations between HCW and the other traits were moderate and negative to null. Correlations for common litter effect were all negative between traits, except between Cfar and Cfin, and between Cnur and Cfin. Heritability of PWM and culling traits increased with age period. Therefore, selection for survival after weaning may be more efficient. The low genetic correlations between PWM and culling traits suggest that different genes influence pre- and postweaning mortality. The HCW was not correlated with the other traits. However, relationships are not strongly unfavorable, therefore selection for survival and high final weight is possible. [less ▲]

Detailed reference viewed: 33 (8 ULg)
Full Text
Peer Reviewed
See detailA method to approximate the inverse of a part of the additive relationship matrix
Faux, Pierre ULg; Gengler, Nicolas ULg

in Journal of Animal Breeding & Genetics (2014)

Single-step genomic predictions need the inverse of the part of the additive relationship matrix between genotyped animals (A22). Gains in computing time are feasible with an algorithm that sets up the ... [more ▼]

Single-step genomic predictions need the inverse of the part of the additive relationship matrix between genotyped animals (A22). Gains in computing time are feasible with an algorithm that sets up the sparsity pattern of A22inv (SP algorithm) using pedigree searches, when A22inv is close to sparse. The objective of this study is to present a modification of the SP algorithm (RSP algorithm) and to assess its use in approximating A22inv when the actual A22inv is dense. The RSP algorithm sets up a restricted sparsity pattern of A22inv by limiting the pedigree search to a maximum number of searched branches. We have tested its use on four different simulated genotyped populations, from 10 000 to 75 000 genotyped animals. Accuracy of approximation is tested by replacing the actual A22inv by its approximation in an equivalent mixed model including only genotyped animals. Results show that limiting the pedigree search to four branches is enough to provide accurate approximations of A22inv, which contain approximately 80% of zeros. Computing approximations is not expensive in time but may require a great amount of memory (at maximum, approximately 81 min and approximately 55 Gb of RAM for 75 000 genotyped animals using parallel processing on four threads). [less ▲]

Detailed reference viewed: 15 (2 ULg)
Full Text
Peer Reviewed
See detailGenotype x Climate interactions for protein yield using four European Holstein Populations
Hammami, Hedi ULg; Carabaño, Maria-Jesus; Logar, Betka et al

in Proceedings of the 10th World Congress on Genetics Applied to Livestock Production (2014)

Reaction norm models were applied to investigate genetic variation in heat tolerance of Holsteins across environments using long term protein milk yield test-day records and weather variables as proxy of ... [more ▼]

Reaction norm models were applied to investigate genetic variation in heat tolerance of Holsteins across environments using long term protein milk yield test-day records and weather variables as proxy of climate change. Data represented four European regions characterized by different management systems and environments. Daily protein yield changed across the trajectory of temperature humidity index (THI) for all studied populations, pointing out negative associations between warm conditions and cow performance. For most regions, additive genetic variances for daily protein yield decrease when THI increases. Antagonistic relationships between level and intercept were relatively limited for Slovenia compared to the three other regions. Rank correlations of estimated breeding values for three proposed heat tolerance measures ranged from 0.56 (Spain and Slovenia) to 0.81 (Walloon Region of Belgium and Luxembourg), indicating a possibility of genotype by environment (G x E) for some pairs of regions. [less ▲]

Detailed reference viewed: 50 (15 ULg)
Full Text
Peer Reviewed
See detailEstimation of dominance variance for live body weight in a crossbred population of pigs
Dufrasne, Marie ULg; Faux, Pierre ULg; Piedboeuf, Maureen et al

in Journal of Animal Science (2014), 92

The objective of this study was to estimate the dominance variance for repeated live BW records in a crossbred population of pigs. Data were provided by the Walloon Pig Breeding Association and included ... [more ▼]

The objective of this study was to estimate the dominance variance for repeated live BW records in a crossbred population of pigs. Data were provided by the Walloon Pig Breeding Association and included 22,197 BW records of 2,999 crossbred Piétrain × Landrace K+ pigs from 50 to 210 d of age. The BW records were standardized and adjusted to 210 d of age for analysis. Three single-trait random regression animal models were used: Model 1 without parental subclass effect, Model 2 with parental subclasses considered unrelated, and Model 3 with the complete parental dominance relationship matrix. Each model included sex, contemporary group, and heterosis as fixed effects as well as additive genetic, permanent environment, and residual as random effects. Variance components and their SE were estimated using a Gibbs sampling algorithm. Heritability tended to increase with age: from 0.50 to 0.64 for Model 1, from 0.19 to 0.42 for Model 2, and from 0.31 to 0.53 for Model 3. Permanent environmental variance tended to decrease with age and accounted for 29 to 44% of total variance with Model 1, 29 to 37% of total variance with Model 2, and 34 to 51% of total variance with Model 3. Residual variance explained <10% of total variance for the 3 models. Dominance variance was computed as 4 times the estimated parental subclass variance. Dominance variance accounted for 22 to 40% of total variance for Model 2 and 5 to 11% of total variance for Model 3, with a decrease with age for both models. Results showed that dominance effects exist for growth traits in pigs and may be reasonably large. The use of the complete dominance relationship matrix may improve the estimation of additive genetic variances and breeding values. Moreover, a dominance effect could be especially useful in selection programs for individual matings through the use of specific combining ability to maximize growth potential of crossbred progeny. [less ▲]

Detailed reference viewed: 42 (12 ULg)
Full Text
Peer Reviewed
See detailGenetic parameters for individual birth weight, weaning weight and final weight of crossbred pigs from Piétrain boars
Dufrasne, Marie ULg; Wavreille, José; Piedboeuf, Maureen et al

Poster (2014)

Genetic parameters for birth weight (BWT), weaning weight (WWT), and final weight (BW) were estimated for crossbred pigs from Piétrain boars raised in test station. Estimates of direct heritability were ... [more ▼]

Genetic parameters for birth weight (BWT), weaning weight (WWT), and final weight (BW) were estimated for crossbred pigs from Piétrain boars raised in test station. Estimates of direct heritability were moderate (0.25 to 0.42), suggesting that genetic improvement of growth would be possible. Estimates of maternal heritability were 0.24 for BWT and WWT, and 0.05 for BW, indicating that the genetic influence of the dam on growth was not negligible until weaning. Genetic correlations between direct and maternal effects for BWT and WWT were moderate and unfavorable (-0.52 and -0.57 respectively). Direct genetic correlations were high and favorable between traits (0.40 to 0.75), suggesting that a high BWT is a good predictor to produce pigs with high final weight. Maternal genetic correlations between traits were low (0.01 to 0.03). Selection for higher BWT would increase final market weight but should be balanced with survival traits. [less ▲]

Detailed reference viewed: 27 (10 ULg)
See detailUse of high performance computing in animal breeding
Vandenplas, Jérémie ULg; Gengler, Nicolas ULg

in Book of Abstracts of the 65th Annual Meeting of the European Federation of Animal Science (2014)

High-perfomance computing facilities proposing shared-memory and distributed-memory multiprocessors are becoming available. With those clusters, parallel computing could lead to increased performances and ... [more ▼]

High-perfomance computing facilities proposing shared-memory and distributed-memory multiprocessors are becoming available. With those clusters, parallel computing could lead to increased performances and problem sizes. However, to our knowledge and especially for variance components estimations, most software available in animal breeding, based on sparse matrices computations, do not allow parallel computing and are limited by memory accessible by the central processing unit, or allow parallel computing only for options with dense matrices computations, which limits anyway problem sizes due to storage of dense matrices. The aim was to propose simple and effective modifications for the BLUPF90 family of programs to reduce computing time with consideration of required memory. Modifications were based on academic free packages proposing solver and sparse inversion for sparse symmetric indefinite linear systems. First, modifications concerned the sparse inversion subroutine implemented in the package FSPAK. Rearrangements of 'do' loops to allow optimizations of computer operations by some compilers and addition of OpenMP directives were performed. The ordering operation was modified to more easily compare a multiple minimum degree algorithm (MMD; implemented in FSPAK) and a multilevel nested dissection algorithm (implemented in METIS 4.0.3). Second, the package PARDISO Version 5.0.0 was used instead of FSPAK. This package proposes in particular a parallel solver and sparse inversion on shared-memory multiprocessors. Modified FSPAK and PARDISO were compared to original FSPAK using MMD through REMLF90. Different models, such as univariate or bivariate (random regressions) test-day animal and single-step genomic models, were tested. All jobs were run 5 times. With an appropriate ordering algorithm, speedup for each REMLF90 iteration were up to 7.5 for modified FSPAK and up to 22.8 for PARDISO with 2 threads. With 4 threads, speedup increased to 8.3 and 32.5, respectively. [less ▲]

Detailed reference viewed: 18 (3 ULg)
See detailUse of high performance computing in animal breeding
Vandenplas, Jérémie ULg; Gengler, Nicolas ULg

in Book of Abstracts of the 65th Annual Meeting of the European Federation of Animal Science (2014)

High-perfomance computing facilities proposing shared-memory and distributed-memory multiprocessors are becoming available. With those clusters, parallel computing could lead to increased performances and ... [more ▼]

High-perfomance computing facilities proposing shared-memory and distributed-memory multiprocessors are becoming available. With those clusters, parallel computing could lead to increased performances and problem sizes. However, to our knowledge and especially for variance components estimations, most software available in animal breeding, based on sparse matrices computations, do not allow parallel computing and are limited by memory accessible by the central processing unit, or allow parallel computing only for options with dense matrices computations, which limits anyway problem sizes due to storage of dense matrices. The aim was to propose simple and effective modifications for the BLUPF90 family of programs to reduce computing time with consideration of required memory. Modifications were based on academic free packages proposing solver and sparse inversion for sparse symmetric indefinite linear systems. First, modifications concerned the sparse inversion subroutine implemented in the package FSPAK. Rearrangements of 'do' loops to allow optimizations of computer operations by some compilers and addition of OpenMP directives were performed. The ordering operation was modified to more easily compare a multiple minimum degree algorithm (MMD; implemented in FSPAK) and a multilevel nested dissection algorithm (implemented in METIS 4.0.3). Second, the package PARDISO Version 5.0.0 was used instead of FSPAK. This package proposes in particular a parallel solver and sparse inversion on shared-memory multiprocessors. Modified FSPAK and PARDISO were compared to original FSPAK using MMD through REMLF90. Different models, such as univariate or bivariate (random regressions) test-day animal and single-step genomic models, were tested. All jobs were run 5 times. With an appropriate ordering algorithm, speedup for each REMLF90 iteration were up to 7.5 for modified FSPAK and up to 22.8 for PARDISO with 2 threads. With 4 threads, speedup increased to 8.3 and 32.5, respectively. [less ▲]

Detailed reference viewed: 28 (2 ULg)
Full Text
Peer Reviewed
See detailShort communication: Alteration of priors for random effects in Gaussian linear mixed models
Vandenplas, Jérémie ULg; Christensen, Ole F.; Gengler, Nicolas ULg

in Journal of Dairy Science (2014), 97(9), 5880-5884

Linear mixed models, for which the prior multivariate normal distributions of random effects are assumed to have a mean equal to 0, are commonly used in animal breeding. However, some statistical analyses ... [more ▼]

Linear mixed models, for which the prior multivariate normal distributions of random effects are assumed to have a mean equal to 0, are commonly used in animal breeding. However, some statistical analyses (e.g., the consideration of a population under selection into a genomic scheme breeding, multiple-trait predictions of lactation yields, Bayesian approaches integrating external information into genetic evaluations) need to alter both the mean and (co)variance of the prior distributions and, to our knowledge, most software packages available in the animal breeding community do not permit such alterations. Therefore, the aim of this study was to propose a method to alter both the mean and (co)variance of the prior multivariate normal distributions of random effects of linear mixed models while using currently available software packages. The proposed method was tested on simulated examples with three different software packages available in animal breeding. The examples showed the possibility of the proposed method to alter both the mean and (co)variance of the prior distributions with currently available software packages through the use of an extended data file and a user supplied (co)variance matrix. [less ▲]

Detailed reference viewed: 22 (12 ULg)
Full Text
See detailEstimation of dominance variance for growth traits with sire-dam subclass effects in a crossbred population of pigs
Dufrasne, Marie ULg; Faux, Pierre ULg; Piedboeuf, Maureen et al

Poster (2014)

Nonadditive genetic effects may be not negligible but are often ignored in genetic evaluations. The most important nonadditive effect is probably dominance. Prediction of dominance effects should allow a ... [more ▼]

Nonadditive genetic effects may be not negligible but are often ignored in genetic evaluations. The most important nonadditive effect is probably dominance. Prediction of dominance effects should allow a more precise estimation of the total genetic merit, particularly in populations that use specialized sire and dam lines, and with large number of full-sibs, like pigs. Computation of the inverted dominance relationship matrix, D-1, is difficult with large datasets. But, D-1 can be replaced by the inverted sire-dam subclass relationship matrix F-1, which represents the average dominance effect of full-sibs. The aim of this study was to estimate dominance variance for longitudinal measurements of body weight (BW) in a crossbred population of pigs The dataset consisted of 20,120 BW measurements recorded between 50 and 210 d of age on 2,341 crossbred pigs (Piétrain X Landrace). A random regression model was used to estimate variance components. Fixed effects were sex and date of recording. Random effects were additive genetic, permanent environment, parental dominance and residual. Dominance variance represented 7 to 9% of the total variance and 11 to 30% of additive variance. Those results showed that dominance variance exists for growth traits in pigs and may be relatively large. The estimation of dominance effects may be useful for mate selection program to maximize genetic merit of progeny. [less ▲]

Detailed reference viewed: 48 (6 ULg)
Full Text
Peer Reviewed
See detailInversion of a part of the numerator relationship matrix using pedigree information
Faux, Pierre ULg; Gengler, Nicolas ULg

in Genetics, Selection, Evolution (2013), 45

Background. In recent theoretical developments, the information available (e.g. genotypes) divides the original population into two groups: animals with this information (selected animals) and animals ... [more ▼]

Background. In recent theoretical developments, the information available (e.g. genotypes) divides the original population into two groups: animals with this information (selected animals) and animals without this information (excluded animals). These developments require inversion of the part of the pedigree-based numerator relationship matrix that describes the genetic covariance between selected animals (A22). Our main objective was to propose and evaluate methodology that takes advantage of any potential sparsity in the inverse of A22 in order to reduce the computing time required for its inversion. This potential sparsity is brought out by searching the pedigree for dependencies between the selected animals. Jointly, we expected distant ancestors to provide relationship ties that increase the density of matrix A22 but that their effect on A22i might be minor. This hypothesis was also tested. Methods. The inverse of A22 can be computed from the inverse of the triangular factor (T-1 ) obtained by Cholesky root-free decomposition of A22 . We propose an algorithm that sets up the sparsity pattern of T-1 using pedigree information. This algorithm provides positions of the elements of T-1 worth to be computed (i.e. different from zero). A recursive computation of A22i is then achieved with or without information on the sparsity pattern and time required for each computation was recorded. For three numbers of selected animals (4000; 8000 and 12 000), A22 was computed using different pedigree extractions and the closeness of the resulting A22i to the inverse computed using the fully extracted pedigree was measured by an appropriate norm. Results. The use of prior information on the sparsity of T-1 decreased the computing time for inversion by a factor of 1.73 on average. Computational issues and practical uses of the different algorithms were discussed. Cases involving more than 12 000 selected animals were considered. Inclusion of 10 generations was determined to be sufficient when computing A22. Conclusions. Depending on the size and structure of the selected sub-population, gains in time to compute A22 are possible and these gains may increase as the number of selected animals increases. Given the sequential nature of most computational steps, the proposed algorithm can benefit from optimization and may be convenient for genomic evaluations. [less ▲]

Detailed reference viewed: 46 (16 ULg)
Full Text
See detailPotentiel d'utilisation de la spectrometrie moyen infrarouge pour prédire le rendement fromager du lait et étudier sa variabilité génétique
Colinet, Frédéric ULg; Troch, Thibault ULg; Abbas, O. et al

Conference (2013, December 04)

Providing a quick, reliable and cheap indication of the expected cheese yield for a milk sample by avoiding (empirical or theoretical) formulas based on previously determined milk constituents would be an ... [more ▼]

Providing a quick, reliable and cheap indication of the expected cheese yield for a milk sample by avoiding (empirical or theoretical) formulas based on previously determined milk constituents would be an economically valuable tool useful for farmers and the dairy industry. In order to study the genetic variability of cheese yield on a large scale, mid-infrared (MIR) chemometric methods were used to predict fresh or dry Individual Laboratory Cheese Yield (RdFF and RdFS, respectively). RdFF and RdFS were determined on a total of 258 milks samples also analyzed by a MIR spectrometer. Equations to predict RdFF and RdFS from milk MIR spectra were developed using partial least square regression (PLS) after first derivative pre-traitment applied to the spectra. The cross-validation coefficients of determination (R²cv) of the two equations were equal to 0.81 for the prediction of RdFF and 0.82 for the prediction RdFS. The ratios of performance to deviation (RPD) of the two equations were both equal to 2.3. Therefore, these results suggest a practical utility of these two equations, i.e. for genetic research. Both equations were applied on the spectral database generated during the Walloon routine milk recording. The variances components were estimated using univariate random regressions animal test-day model. The dataset included 51 537 predicted records from 7 870 Holstein first-parity cows. Estimated daily heritabilities ranged from 0.31 (at 5th day in milk (DIM)) to 0.59 (at 279th DIM) for RdFF and from 0.31 (at 5th DIM) to 0.57 (at 299th DIM) for RdFS. Those moderate to high daily heritabilities indicated potential of selection for both traits. [less ▲]

Detailed reference viewed: 53 (17 ULg)
Full Text
Peer Reviewed
See detailPotentiel d'utilisation de la spectrometrie moyen infrarouge pour prédire le rendement fromager du lait et étudier sa variabilité génétique
Colinet, Frédéric ULg; Troch, Thibault ULg; Abbas, O. et al

in 20èmes Rencontres Recherches Ruminants, Paris, les 4 et 5 Décembre 2013 (2013, December)

Fournir une indication rapide, fiable et bon marché du rendement fromager pour un lait donné, sans devoir appliquer des formules (empiriques ou théoriques) à partir des concentrations préalablement ... [more ▼]

Fournir une indication rapide, fiable et bon marché du rendement fromager pour un lait donné, sans devoir appliquer des formules (empiriques ou théoriques) à partir des concentrations préalablement déterminées pour différents constituants du lait, serait un outil utile et économiquement intéressant tant pour les éleveurs que pour l’industrie laitière. En vue d’étudier la variabilité génétique du rendement fromager à l’échelle du cheptel bovin wallon, des méthodes chimiométriques ont été utilisées afin de développer des équations de prédictions basées sur des spectres moyen infrarouge (MIR) pour les rendements fromagers déterminés en laboratoire et exprimés en frais (RdFF) ou en sec (RdFS). Ceux-ci ont été déterminés sur 258 échantillons de lait analysés en spectrométrie MIR. Les équations de prédiction à partir du spectre MIR du lait ont été développées en utilisant la régression des moindres carrés partiels (PLS) avec une validation croisée interne appliquée sur la dérivée première des spectres MIR. Les coefficients de détermination de validation croisée (R²cv) des équations étaient de 0,81 pour les prédictions du RdFF et de 0,82 pour les celles du RdFS. Les rapports des performances sur les variabilités (RPD) étaient égaux à 2,3. Ces résultats peuvent permettre d’envisager une bonne utilité pratique pour leur prédiction respective, notamment dans le cadre de recherches génétiques. Ces équations ont été appliquées sur la base de données spectrales générée dans le cadre du contrôle laitier wallon. Les composantes de la variance ont été estimées séparément pour le RdFF et le RdFS basées sur un modèle animal « contrôles élémentaires » utilisant des régressions aléatoires. Le jeu de données utilisé comportait 51 537 prédictions pour 7 870 vaches primipares Holstein. Les héritabilités journalières moyennes variaient entre 0,31 (au 5ème jour de lactation (JDL)) et 0,59 (au 279ème JDL) pour le RdFF et entre 0,31 (au 5ème JDL) et 0,57 (au 299ème JDL) pour le RdFS. Ces héritabilités journalières modérées à élevées ont indiqué le potentiel de sélection génétique pour ces deux caractères. [less ▲]

Detailed reference viewed: 61 (16 ULg)
Full Text
See detailCombinaison d'informations génomiques, phénotypiques et généalogiques
Vandenplas, Jérémie ULg; Gengler, Nicolas ULg

Conference given outside the academic context (2013)

Detailed reference viewed: 23 (12 ULg)
Full Text
Peer Reviewed
See detailGenetic variance in micro-environmental sensitivity for milk and milk quality in Walloon Holstein cattle
Vandenplas, Jérémie ULg; Bastin, Catherine ULg; Gengler, Nicolas ULg et al

in Journal of Dairy Science (2013), 96

Animals that are robust to environmental changes are desirable in the current dairy industry. Genetic differences in micro-environmental sensitivity can be studied through heterogeneity of residual ... [more ▼]

Animals that are robust to environmental changes are desirable in the current dairy industry. Genetic differences in micro-environmental sensitivity can be studied through heterogeneity of residual variance between animals. However, residual variance between animals is usually assumed homogeneous in traditional genetic evaluations. The aim of this study was to investigate genetic heterogeneity of residual variance by estimating variance components in residual variance for milk yield, somatic cell score, contents in milk (g/dL) of two groups of milk fatty acids (i.e. saturated fatty acids and unsaturated fatty acids) and the content in milk of one individual fatty acid (i.e. the oleic acid, C18:1 cis-9), for first-parity Holstein cows in the Walloon Region of Belgium. A total of 146,027 test-day records from 26,887 cows in 747 herds were available. All cows had at least three records and had a known sire. These sires had at least 10 cows with records and each herd x test-day had at least five cows. The five traits were analyzed separately based on fixed lactation curve and random regression test-day models for the mean. Estimation of variance components was performed by running iteratively Expectation Maximization-Restricted Maximum Likelihood algorithm by the implementation of double hierarchical generalized linear models. Based on fixed lactation curve test-day mean models, heritability for residual variances ranged between 1.01*10-3 and 4.17*10-3 for all traits. The genetic standard deviation in residual variance (i.e. approximately the genetic coefficient of variation of residual variance) ranged between 0.12 and 0.17. Therefore, some genetic variance in micro-environmental sensitivity existed in the Walloon Holstein dairy cattle for the five studied traits. The standard deviations due to herd x test-day and permanent environment in residual variance ranged between 0.36 and 0.45 for herd x test-day effect and between 0.55 and 0.97 for permanent environmental effect. Therefore, non-genetic effects also contributed substantially to the micro-environmental sensitivity. Results also showed that the addition of random regressions to the mean model did not reduce heterogeneity in residual variance and that genetic heterogeneity of residual variance was not simply an effect of an incomplete mean model. [less ▲]

Detailed reference viewed: 85 (54 ULg)