References of "Gengler, Nicolas"
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See detailContributions à l’amélioration des systèmes d’évaluations génétiques
Vanderick, Sylvie ULg; Gengler, Nicolas ULg

Conference given outside the academic context (2014)

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See detailPhenotypic and genetic variability of methane emissions and milk fatty acid contents of Walloon Holstein dairy cows
Vanrobays, Marie-Laure ULg; Kandel, Purna Bhadra ULg; Soyeurt, Hélène ULg et al

Poster (2014, February 17)

There is a growing interest in reducing methane (CH4) emissions from enteric fermentation of dairy cows because these emissions contribute to climate change and represent losses of gross energy intake for ... [more ▼]

There is a growing interest in reducing methane (CH4) emissions from enteric fermentation of dairy cows because these emissions contribute to climate change and represent losses of gross energy intake for cows. Milk fatty acid (FA) profile is influenced by rumen fermentations. The aim of this study was to estimate phenotypic and genetic variability of enteric CH4 emissions of dairy cows and FA contents of milk. CH4 emissions (g/d) and milk FA contents are predicted from milk mid-infrared (MIR) spectra based on calibration equations developed by Vanlierde et al. (2013) and Soyeurt et al. (2011), respectively. Data included 161,681 records from 22,642 cows in 489 herds. Genetic parameters of MIR CH4 emissions and 7 groups of FA contents in milk were estimated for Walloon Holstein cows in first parity using bivariate (CH4 emission with a FA trait) random regression test-day models. Saturated FA presented higher genetic correlations with MIR CH4 production than unsaturated FA (0.25 vs. 0.10). Genetic correlations with MIR CH4 emissions were higher for short- (SC) and medium-chain (MC) FA (0.24 and 0.23, respectively) than for long-chain (LC) FA (0.13). Phenotypic correlations between MIR CH4 emissions and SC and MC FA were also higher than those between MIR CH4 emissions and LC FA (0.20 vs. -0.08). Finally, results showed that MIR milk FA profile and MIR CH4 emissions are correlated emphasizing indirect link between milk FA and CH4 emissions through rumen metabolism. [less ▲]

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See detailConsequences of Selection for Environmental Impact Trait in Dairy Cows
Kandel, Purna Bhadra ULg; Vanderick, Sylvie ULg; Vanrobays, Marie-Laure ULg et al

Scientific conference (2014, February 07)

Environmental sustainability is gaining importance in dairy industry due to enteric methane (CH4) emission from dairy cows. We predicted CH4 indicator trait (CH4 intensity: CH4 g/kg of milk) from Mid ... [more ▼]

Environmental sustainability is gaining importance in dairy industry due to enteric methane (CH4) emission from dairy cows. We predicted CH4 indicator trait (CH4 intensity: CH4 g/kg of milk) from Mid-infrared spectra of milk samples and recorded milk yield. Genetic correlations between CH4 intensity and milk production traits were estimated on Holstein cows from correlations of estimated breeding values. Genetic correlations between CH4 intensity and milk yield (MY) was -0.67, fat yield (FY) -0.13, protein yield (PY) -0.46, somatic cell score (SCS) 0.02, longevity -0.07, fertility 0.31, body condition score (BCS) 0.27 and average of confirmation traits -0.23. Currently, there is no CH4 emission trait in genetic evaluation selection index. Putting an hypothetical 25% weight on CH4 intensity on current Walloon genetic evaluation selection index and proportional reduction on other selection traits, the response to selection will be reduction of CH4 emission intensity by 24%, increase in MY by 30%, FY by 17%, PY by 29%, SCS by -15%, longevity by 24%, fertility by -11%, BCS by -13% and conformation traits by 24%. In conclusion, introduction of environmental traits in current selection index will affect selection responses. As there is no economic value of these traits presently alternative methods like putting correlated traits with clear economic value (e.g. feed efficiency) in the selection objective could generate appropriate index weights. [less ▲]

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See detailEfficient computation of genomically-enhanced inbreeding coefficients
Faux, Pierre ULg; Gengler, Nicolas ULg

Poster (2014, February 07)

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See detailPotential for assessing the pregnancy status of dairy cows by mid-infrared analysis of milk
Laine, Aurélie ULg; Bel Mabrouk, Hana ULg; Dale, Laura-Monica ULg et al

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

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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 ▲]

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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 ▲]

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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 ▲]

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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 ▲]

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See detailImpact of Heat Stress on Production in Holstein Cattle in four EU Regions. Selection Tools
Carabaño, Maria-Jesus; Hammami, Hedi ULg; Logar, Betka et al

Conference (2014)

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See detailImpact of Heat Stress on Production in Holstein Cattle in four EU Regions. Selection Tools
Carabaño, Maria-Jesus; Hammami, Hedi ULg; Logar, Betka et al

Scientific conference (2014)

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See detailGenotype x Climate interactions for protein yield using four European Holstein Populations
Hammami, Hedi ULg; Carabaño, Maria-Jesus; Logar, Betka et al

Conference (2014)

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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 ▲]

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See detailStrategies to Combine Novel Traits across Countries: Example of Heat Stress
Hammami, Hedi ULg; Vandenplas, Jérémie ULg; Carabaño, Maria-Jesus et al

in Interbull Bulletin (2014), 48

Nowadays, novel traits are of great interest. However, phenotypes are siloed and mainly not shared. Heat stress is becoming problematic affecting animals’ performances and their well-being. Heat stress ... [more ▼]

Nowadays, novel traits are of great interest. However, phenotypes are siloed and mainly not shared. Heat stress is becoming problematic affecting animals’ performances and their well-being. Heat stress tolerance as a novel trait is only addressed by isolated within-country research studies. Integration and combination of local and foreign information sources is needed for better accuracy genetic evaluations. Therefore, this study was aimed to test the potential combination of sources of external information towards the evaluation of heat stress tolerance of dairy cattle. Long-term cow performances linked to environmental descriptors (weather parameters as proxy to climate change) collected over 10 years under the temperate conditions of the Walloon Region of Belgium and the hotter and warm Mediterranean conditions of Andalusia and Castile-La-Mancha Spanish regions were available. A total of 1,604,775 milk, fat, and protein test-day (TD) records linked to average daily temperature humidity (THI) values for 3-day lag before each TD were considered. Under a first strategy considering free-access to raw-data (phenotype and pedigree), a joint evaluation was firstly run using reaction norm models where production traits were considered as function of THI. A Belgian and a Spanish evaluation were also run using the same model. An alternative strategy considering only access to external information (i.e. regression coefficients for additive genetic effects (â and their associated REL)) was tested. In this case, foreign â and their REL resulting from the Spanish evaluation were first converted to the Belgian trait and thereafter integrated in the Belgian evaluation using a Bayesian approach. Rank correlations between regression coefficients, â (of the 1,104 bulls having daughters only in Spain) estimated by Belgian evaluation and â estimated by the joint evaluation were moderate (<=0.70). Corresponding rank correlations between â estimated by joint and Bayesian evaluations were significantly higher (ranging from 0.967 to 0.998), indicating that the Bayesian evaluation integrating external information was in good concordance with the joint evaluation. Results from this study indicated that the integration of external information via the Bayesian approach has a good potential to improve the genetic evaluation of sparse and siloed novel traits. [less ▲]

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