References of "Vanderick, Sylvie"
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See detailLinking first lactation survival to milk yield and components and lactation persistency in Tunisian Holstein cows
Grayaa, Marwa ULiege; Vanderick, Sylvie ULiege; Rekik, Boulbaba et al

in Archiv für Tierzucht (2019), 65(1), 153160

Genetic parameters were estimated for first lactation survival defined as a binary trait (alive or dead to second calving) and the curve shape traits of milk yield, fat and protein percentages using ... [more ▼]

Genetic parameters were estimated for first lactation survival defined as a binary trait (alive or dead to second calving) and the curve shape traits of milk yield, fat and protein percentages using information from 25 981 primiparous Tunisian Holsteins. For each trait, shape curves (i.e. peak lactation, persistency), level of production adjusted to 305 days in milk (DIMs) for total milk yield (TMY), and average fat (TF %) and protein (TP %) percentages were defined. Variance components were estimated with a linear random regression model under three bivariate animal models. Production traits were modelled by fixed herd × test-day (TD) interaction effects, fixed classes of 25 DIMs × age of calving × season of calving interaction effects, fixed classes of pregnancy, random environment effects and random additive genetic effects. Survival was modelled by fixed herd × year of calving interaction effects and age of calving × season of calving interaction effects, random permanent environment effects, and random additive genetic effects. Heritability (h2) estimates were 0.03 (±0.01) for survival and 0.23 (±0.01), 0.31 (±0.01) and 0.31 (±0.01) for TMY, TF % and TP %, respectively. Genetic correlations between survival and TMY, TF % and TP % were 0.26 (±0.08), −0.24 (±0.06) and −0.13 (±0.06), respectively. Genetic correlations between survival and persistency for fat and protein percentages were −0.35 (±0.09) and −0.19 (±0.09), respectively. Cows that had higher persistencies for fat and protein percentages were more likely not to survive. [less ▲]

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See detailTemporal relationship between milk MIR predicted metabolic disorders and lameness events
Mineur, Axelle ULiege; Vanderick, Sylvie ULiege; Hammami, Hedi ULiege et al

in Book of Abstracts of the 68th Annual Meeting of the European Federation of Animal Science (2018, August 27)

Lameness is an often occurring consequence of various metabolic disorders, such as sub-acute ruminal acidosis (SARA) or ketosis. Recent research showed that these metabolic disorders can be predicted with ... [more ▼]

Lameness is an often occurring consequence of various metabolic disorders, such as sub-acute ruminal acidosis (SARA) or ketosis. Recent research showed that these metabolic disorders can be predicted with reasonable accuracy with mid-infrared (MIR) spectral data. In order to study the potentially complex temporal relationship between MIR predicted metabolic disorders and lameness events over the course of the lactation, data from 3895 cows on 122 farms, representing the Simmental, Brown-Swiss and Holstein breeds. A total of 38316 lameness and 11419 MIR records were collected over a period from July to December 2014 through the Efficient Cow Project. Lactations were subdivided into 30 days lactation stage classes. Milk MIR predicted metabolites such as ketone bodies, acetone, citrates and fatty acids (C18:1cis9), and lameness scores were averaged over animals and these classes. In order to assess the temporal link between occurrences of metabolic disorder and lameness events, correlations were computed between averaged metabolites and lameness scores across the lactation stage classes. Correlations tended to be higher when comparing predicted metabolites with lameness in the three following months, rather than the same one. Results showed differences between breeds, Simmentals showing lower correlations than Holsteins or Brown-Swiss. Especially very early values for milk MIR predicted metabolites (first month), and therefore suspected metabolic disorders, were correlated more strongly to later occurring lameness events in Brown Swiss. In Holsteins, higher correlation between metabolites and lameness were observed during later lactation. In general, given the use of classes, the correlations tended to be unstable. Alternative methods, such as covariance functions, might therefore be useful to get a clearer picture. However these first results seem to support the idea of temporal relationships between metabolic disorders and later lameness events during the lactation. [less ▲]

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See detailEarly-programming of dairy cattle, a potential explanation to the adaptation to climate change
Hammami, Hedi ULiege; Colinet, Frédéric ULiege; Bastin, Catherine et al

in Book of Abstracts of the 69th Annual Meeting of the European Federation of Animal Science (2018, August)

Breeding for robustness and considering genotype by environment interaction (G×E) is linked to adaptation. Recently, it has been established that gene expression can be affected by the environment during ... [more ▼]

Breeding for robustness and considering genotype by environment interaction (G×E) is linked to adaptation. Recently, it has been established that gene expression can be affected by the environment during the embryo development. The concept of early programming has been demonstrated in many settings. This study aimed to assess the impact of thermal stress when dairy cows been conceived on their lifetime performances. Studied traits were milk yield and some novel milk-based biomarkers, fertility (days open), health (somatic cell score and ketosis), and heat tolerance. Data used compromised 905,391 test day of 58,297 cows in parity 1 to 3 for production traits, health and ketosis status, 104,635 records of 48,125 cows for days open, and 399,449 test days recorded (linked with temperature humidity index values, THI) of 28,203 cows for heat tolerance trait. Date of conception was estimated using the next calving date of the cow and subtracting 280 d from the calving interval. Cows being conceived in summer (June- August) were considered as influenced by heat stress (environment 1) and those conceived in winter (December- February) as neutral-thermal conditions (environment 2). G×E was analysed by a multi-trait model for days open in which each of the 3 lactations measured in heat stress and thermo-neutral conditions were considered as separate traits. For the rest of the traits, it was analysed using reaction norm models, in which the trait is considered a function of an environmental descriptor (i.e. THI, days in milk) in the two discrete environments. First results showed that genetic correlations across both early-life defined environments and lactations were substantially lower than unity, implying that effects of genes for cows conceived under neutral-thermal conditions may be different of the effects for the same genes for cows conceived under heat stressed conditions. [less ▲]

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See detailTheoretical basis to extend single-step genomic prediction of dominance in a pig population
REIS MOTA, Rodrigo ULiege; Vanderick, Sylvie ULiege; Colinet, Frédéric ULiege et al

in Book of Abstracts of the 69th Annual Meeting of the European Federation of Animal Science (2018, August)

Single-step methods predict implicitly unknown gene content information of non-genotyped from known gene content for genotyped animals. This theory is well derived in an additive setting. There are ... [more ▼]

Single-step methods predict implicitly unknown gene content information of non-genotyped from known gene content for genotyped animals. This theory is well derived in an additive setting. There are reasons not to ignore the dominance context when working with partially genotyped populations. This study addressed several outstanding issues in this context. First, it presented the theoretical basis for dominance single-step genomic best linear unbiased prediction theory. A specific and important issue in all dominance setting is the handling of inbreeding. A total of five dominance single-step inverse matrices were tested and described as C1 to C5 by considering different parameterization (e.g. different ways to account for inbreeding) for pedigree-based and genomic relationships matrices. We simulated genotypes for real crossbred pig population (n=11,943 animals). The SNP effects were assumed to be equal to calculate true dominance values. We added random noise and used them as phenotypes. Accuracy was defined as correlation between true and predicted dominance breeding values. We applied five replicates and estimated accuracies between three situations: all (S1); non-genotyped (S2) and inbred non-genotyped animals (S3). Potential bias of predicted dominance values was assessed by regressing the true dominance values on predicted values. Accuracies of each tested matrix (C1 to C5) were 0.75, 0.33 and 0.35 in average, for S1, S2 and S3, respectively. The matrix C5 better performed and breeding values from C1 and C2 were more biased than those obtained by using C3, C4 and C5. We showed a useful approach to predict dominance gene contents for nongenotyped from genotyped animals. Better matrix compatibility can be obtained by re-scaling the pedigree-based and the genomic relationship matrices to obtain standardized diagonal elements equal to 1 minus the inbreeding coefficient, i.e. the C5 matrix. [less ▲]

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See detailMulti-omics data integration approach for resilience of dairy cattle to heat stress
Hammami, Hedi ULiege; Colinet, Frédéric ULiege; Bastin, Catherine et al

in Book of Abstracts of the 69th Annual Meeting of the European Federation of Animal Science (2018, August)

Breeding for resilience to heat stress (HS) is a topic where associating multiple omics data has the potential to get a better view of the issues and to allow significant advances to overcome undesirable ... [more ▼]

Breeding for resilience to heat stress (HS) is a topic where associating multiple omics data has the potential to get a better view of the issues and to allow significant advances to overcome undesirable consequences of future extreme weather scenarios. An example of omics is here epigenomics (e.g. early programming due to heat-stress) allowing new insights to explain biological mechanisms of resilience to HS and G×E interactions. Even if biological mechanisms are complex and still elusive, this study tried to use a holistic approach integrating milk-based biomarkers, climate conditions, and genomics. Data used included 65,907 third-lactation test-day records for production traits (milk, fat and protein yields), specific fatty acids (FA) and metabolites predicted from mid-infrared spectra (C4:0, C18:1cis9, long chain ‘LCFA’, mono- and unsaturated FA ‘MUFA and UFA’, acetone and BHB) of 9,327 Holstein cows. Phenotypes were merged with a temperature humidity index (THI) from public weather stations. For each trait, the response to THI was estimated via days in milk (DIM) × THI combination, and for each cow by using a random regression model with a common threshold of THI=62. The slope (heat tolerance)-to-intercept (general) genetic variance ratios increased as THI increased. They were higher during mid-lactation (140-245 DIM) for C18:1 cis9, acetone, BHB and for production traits, whereas higher in early lactation (≤125 DIM) for C4:0, LCFA, MUFA, and UFA. At extreme high THI scale, slope-to-intercept ratios for C18:1 cis9, MUFA, UFA, and LCFA were 3.8, 3.4, 3.1, 2.8 fold higher than milk yield. These findings indicate that tolerance to HS and traditional production trait responses to THI are marginally related, and changes in milk-based biomarkers under high THI better elucidate physiological and metabolic pathways in HS dairy cows. Ongoing genomic wide association studies will better explain genetic markers unravelling the biological background of resilience to HS. [less ▲]

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See detailIdeas for continuous genomic evaluation for newly genotyped Walloon Holstein females and males
Naderi Darbaghshahi, Saeid ULiege; REIS MOTA, Rodrigo ULiege; Vanderick, Sylvie ULiege et al

in Book of Abstracts of the 69th Annual Meeting of the European Federation of Animal Science (2018, August)

Crucial for large scale use in dairy cattle of genotyping for females is that any newly genotyped animal (calves, cows and heifers but also bulls) receives very quickly genomic breeding values (GEBV) even ... [more ▼]

Crucial for large scale use in dairy cattle of genotyping for females is that any newly genotyped animal (calves, cows and heifers but also bulls) receives very quickly genomic breeding values (GEBV) even outside the official schedule for routine evaluations. In this study, a system was developed to estimate initial GEBV for newly genotyped animals before their inclusion in the official routine release of genomic evaluations. The system was setup to be run on request, featuring the setup of a ‘continuous’ evaluation, also being quick and simple enough to be used at least on a weekly base. For animals without own records or descendants, official GEBV were approximated using selection-index like method by combining direct genomic values (DGV) of newly genotyped animals and their parent average (PA). DGV for new genotyped animals were calculated based on SNP effects from the previous official routine evaluations (April and August, 2017). Depending on GEBV accessibility from parents of a given animal, PA was calculated based on conventional phenotypic information (cPA), and parent GEBV (gPA). To expand the system for animals with progeny, a subset of genotyped animals was selected, and conventional estimated breeding values (cEBV) and cPA of selected animals were combined with DGV and gPA in order to obtain GEBV for animals with progeny. The weights were calculated based on the covariance between DGV and gPA for animals without progeny, and between DGV, gPA, cEBV and cPA for animals with progeny. Correlations between initial and April official evaluations for 60 new genotyped animals without progeny varied from 0.87 to 0.95 for conformation, fertility and production traits, whereas correlations between initial and August official evaluations varied 0.84 to 0.92 (n=25 new genotyped animals). On the other hand, correlations between initial and August official evaluations for 120 genotyped animals with progeny varied from 0.95 to 0.97 for production traits. Study showed potential to use simple selection index based methods in continuous genomic evaluations, a way to support genotyping of females for genomic selection but also for management and marketing. [less ▲]

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See detailPrediction of milk mid-infrared spectrum using mixed test-day models
Delhez, Pauline ULiege; Vanderick, Sylvie ULiege; Colinet, Frédéric ULiege et al

in Book of Abstracts of the 69th Annual Meeting of the European Federation of Animal Science (2018, August)

Mid-infrared (MIR) analysis of milk currently allows the measurement of many variables of interest for the dairy sector related to milk nutritional quality, milk technological properties, cow’s status or ... [more ▼]

Mid-infrared (MIR) analysis of milk currently allows the measurement of many variables of interest for the dairy sector related to milk nutritional quality, milk technological properties, cow’s status or environmental fingerprint. The aim of this study was to explore the ability of a test-day model to predict milk MIR spectra, and therefore all the resultant variables, for a future test day of a known cow or for a new cow based on easily known characteristics of cows. This is useful for instance for herd management (e.g. detecting problems, predicting potential of heifers) or to predict future environmental impacts of a dairy herd. A total of 467,496 milk MIR spectra from 53,781 Holstein cows in first lactation were used for the calibration data set. First, 323 wavelengths out of the 1,060 wavelengths of the milk spectra were conserved. This spectral information was reduced by using principal component analysis (PCA). A total of 8 principal components (PC) were kept, representing 99% of the spectral information. Then 8 univariate test-day models including the day in milk, herd×year and herd×month as fixed effects and herd×test date, permanent environment and genetics as random effects were applied for each PC. From the solutions of the models and by using a back reversing operation using eigenvectors of the PCA, the predicted 323 wavelengths of the spectra were re-obtained. The calibration correlations between observed and predicted spectral data ranged from 0.76 to 0.93. Correlations between observed and predicted milk fat and protein contents obtained from the modelled spectra were 0.83 and 0.89, respectively. These findings demonstrate the moderate ability of a test-day model to predict milk MIR spectra. [less ▲]

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See detailEffect of milk yield and milk content curve shapes on first lactation survival in large herds
Grayaa, Marwa ULiege; Ben Gara, A.; Grayaa, S. et al

in Book of Abstracts of the 69th Annual Meeting of the European Federation of Animal Science (2018, August)

Genetic parameters of first lactation survival and curve shape traits of milk yield, fat and protein percentages were estimated using information of 25,981 primiparous Tunisian Holsteins belonging to ... [more ▼]

Genetic parameters of first lactation survival and curve shape traits of milk yield, fat and protein percentages were estimated using information of 25,981 primiparous Tunisian Holsteins belonging to large herds. For each trait lactation peak, apparent persistency, real persistency and level of production adjusted to 305 days in milk were defined. Variance components were estimated under three bivariate animal models with a linear random regression model. Milk yield as well as fat and protein percentages were modelled by fixed herd × test day interaction effects, fixed classes of 25 days in milk × age of calving × season of calving interaction effects, random environment effects, and random additive genetic effects. Survival was modelled by fixed herd × year of calving interaction effects, age of calving × season of calving interaction effects, random environment permanent effects, and random additive genetic effects. Heritability estimates were 0.03 for survival, 0.23, 0.29 and 0.30 for average milk yield, fat and protein percentages adjusted to 305 days in milk, respectively. Genetic correlations between survival and average milk yield, fat and protein percentages adjusted to 305 days in milk were 0.33, -0.33 and -0.14, respectively. Genetic correlations between survival and real persistency for fat and protein percentages were -0.24 and -0.15, respectively. Cows that had higher persistencies for fat and protein percentages, and therefore flatter fat and protein percentages curves, were more likely not to survive. This was due to higher fat percentages at the end of the lactation leading to the hypothesis that cows producing higher fat percentage dispose of less energy available for gestation and were therefore less likely to be or remain pregnant and, therefore, to survive. [less ▲]

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See detailGenetic parameters of novel mid-infrared predicted milk traits in three dual-purpose cattle breeds
Vanderick, Sylvie ULiege; Colinet, Frédéric ULiege; Mineur, Axelle ULiege et al

in Book of Abstracts of the 69th Annual Meeting of the European Federation of Animal Science (2018, August)

The objective of this study was to estimate genetic parameters of 39 novel mid-infrared predicted milk traits (e.g. nutritional quality, technological properties, metabolic status, environmental ... [more ▼]

The objective of this study was to estimate genetic parameters of 39 novel mid-infrared predicted milk traits (e.g. nutritional quality, technological properties, metabolic status, environmental fingerprint) for three dual purpose cattle breeds (i.e. Dual-Purpose Belgian Blue (dpBB), Montbéliarde (MON) and Normande (NOR)), which are also used in organic farming in the Walloon Region of Belgium, as part of the 2-Org-Cows project. Edited data included 21,287, 10,062 and 4,637 first-lactation test-day records collected in the Walloon region of Belgium from 2,988, 1,330 and 621 dpBB, MON and NOR cows, respectively. Genetic parameters were estimated using REML applied to single-trait random regression test-day models for six conventional traits (yields, contents and somatic cell score) and the 39 novel mid-infrared predicted milk traits. Results for conventional traits allowed comparison to literature showing values that were close to the expected ones. For novel traits, comparison with available literature values for Holstein breed showed generally similar estimated heritabilities. Reported average daily heritabilities estimated for the 39 novel traits tended to be higher for dpBB (0.13-0.64) than MON and NOR (0.03-0.60) breeds. Few novel traits showed large differences between breeds except between dpBB and NOR for milk composition traits. However, results for NOR breed have to be taken very carefully given the low number of animals. Even if the used methane prediction equation was not yet validated for these breeds, estimated average daily heritability was moderately high for dpBB (0.41) and MON (0.36) and moderate for NOR (0.23) indicating that this prediction might also be useful in these dual purpose breeds. [less ▲]

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See detailFirst study into the temporal relationship between metabolic disorders and lameness events over the course of a lactation
Mineur, Axelle ULiege; Egger-Danner, Christa; Sölkner, Johann et al

Conference (2018, June 25)

Lameness in dairy cows is an issue that can vary greatly in severity, and is of concern for both producers and consumers. Metabolic disorders are a major problem in themselves, and, next to this, can ... [more ▼]

Lameness in dairy cows is an issue that can vary greatly in severity, and is of concern for both producers and consumers. Metabolic disorders are a major problem in themselves, and, next to this, can cause lameness. Indeed, lameness is an often occurring consequence of various metabolic disorders, such as sub acute ruminal acidosis (SARA), ketosis or milk fever. The caused lameness event can occur weeks to months after the metabolic disorder making the detection of causality difficult. Moreover, detection of many metabolic disorders is very challenging and not straightforward. Mid-infrared (MIR) technology is already used for the prediction of major milk components, such as fat or protein, during routine milk recording and for milk payment. It was recently shown that this technology can also be used to predict novel components, linked to metabolic disorders of cows, such as ketone bodies, citrate and minerals. In the context of limiting the occurrence and severity of lameness, early prediction of lameness could help indicate the need to adapt the management and the environment of a cow at risk of lameness. Therefore, the aim of this study was to analyze the temporal link between metabolic disorders and lameness events, using locomotion scores of the cow and MIR based milk biomarkers for different metabolic disorders of her milk from previous test days. Data recorded between, July 2014 and December 2014, consisted of 9324 records, from 3895 cows and 122 farms. Correct definition of the response variable is an important aspect as extremes in lameness severity, expressed on lameness scales, were more easily predictable. First results were obtained using covariance functions on correlations computed between averaged metabolites and lameness scores, per animal, across the lactation stage classes. Correlations tended to be higher when comparing predicted metabolites with lameness in the three following months, rather than the same one, hinting at a temporal relationship. [less ▲]

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See detailSingle-step genomic analysis of dominance in a crossbred pig population
REIS MOTA, Rodrigo ULiege; Vanderick, Sylvie ULiege; Colinet, Frédéric ULiege et al

in Proceedings of the World Congress on Genetics Applied to Livestock Production (2018, February)

When all animals are genotyped, developments focused on dominance are well derived. However, this is rare in practice and adaptations are required. The dominant pedigree-based and genomic matrices should ... [more ▼]

When all animals are genotyped, developments focused on dominance are well derived. However, this is rare in practice and adaptations are required. The dominant pedigree-based and genomic matrices should be compatible in scale to be combined. We aimed to show how gene content flows from genotyped to non-genotyped animals. Scenarios where 0% (D), 20% (C20), 40% (C40) 60% (C60), 80% (C80), and 100% (G) of animals were genotyped were assumed in a crossbred pig population. Dominance variances were more sensitive by choosing G rather than D. D and C60 presented the highest dominance variances whereas G showed the lowest. The prediction accuracies increased as the number of genotyped animals increased. C40 provided less inflated dominance breeding values (1.01), and 55% of accuracy. Dominance relationships flew from genotyped to non-genotyped animals but single-step extension might worked because we used an approximation of D where inbreeding is ignored and due to simple family structure in our dataset. Thus, our approach might be useful but is not general as the original derivations of single-step. Genotyping strategies can be optimized based on the proportion of genotyped animals where 40% seemed to be optimal. [less ▲]

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See detailDefining and using novel milk composition based heat stress resilience traits in the context of genomic selection for more robust dairy cows in Wallonia
Mineur, Axelle ULiege; REIS MOTA, Rodrigo ULiege; Gengler, Nicolas ULiege et al

in Proceedings ICAR 2018 (2018)

Recent research showed the usefulness of using estimated breeding values (EBV) for mid-infrared (MIR) based biomarkers in genetic improvement. A novel class of biomarkers was defined based on modelling ... [more ▼]

Recent research showed the usefulness of using estimated breeding values (EBV) for mid-infrared (MIR) based biomarkers in genetic improvement. A novel class of biomarkers was defined based on modelling responses of milk composition (e.g., mid-infrared (MIR) based) to stress expressed on continuous scales using reaction norm models. Heat stress is an important aspect of dairy production even in temperate climates as shown in recent studies. Implementation of genomic selection for tolerance to heat stress is therefore not only an issue for Australian dairy cattle, a country that introduced recently such an evaluation. The question remains open if using milk composition based heat stress resilience genomically enhanced EBV (GEBV) is not a viable option. Genetic parameters were estimated for production and milk composition traits. Data included 155,977 test-day records for milk, fat, and protein yields, fat and protein percentages, 9 individual milk fatty acids (FA), 7 FA groups, 5 minerals, and 3 ketone bodies) predicted by mid-infrared spectrometry., and 7 FA groups. Data were from 21,375 first-lactation Holstein cows in 473 herds in the Walloon region of Belgium and were collected between 2008 and 2014. Test-day records were merged with daily temperature-humidity index (THI) values based on meteorological records from public weather stations. The maximum distance between each farm and its corresponding weather station was 13 km. Linear reaction norm models were used to estimate the intercept and slope responses of 23 traits to increasing THI values. Most yield and FA traits had phenotypic and genetic declines as THI increased, whereas C18:0, C18:1 cis-9, and 4 FA groups (unsaturated FA, monounsaturated FA, polyunsaturated FA, and long-chain FA) increased with THI. Moreover, the latter traits had the largest slope-to-intercept genetic variance ratios, which indicate that they are more affected by heat stress at high THI levels and therefore good candidate traits. Among all traits, C18:1 cis-9 was the most sensitive to heat stress. As this trait is known to reflect body reserve mobilization, using its response to THI could be a very affordable milk biomarker of heat stress for dairy cattle expressing the equilibrium between intake and mobilization, and therefore adaptation, under warm conditions. By including novel milk based composition traits to traditional production traits, correlations between EBVs and also GEBVs of those milk based traits and udder health, fertility and longevity increased considerably. This study demonstrated that milk composition resilience heat stress traits could be used as early indicators of robustness traits. Our results also suggest that marker information tend to lead to higher accuracies of prediction. Therefore, new options to improve robustness through genomic selection in Walloon Holsteins are now presented. [less ▲]

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See detailMilk mid-infrared spectra based biomarkers contributing to genetic improvement for udder health, fertility and longevity
Gengler, Nicolas ULiege; Mineur, Axelle ULiege; Vanderick, Sylvie ULiege et al

in Proceedings ICAR 2018 (2018)

Recent research showed the usefulness of using estimated breeding values (EBV) for midinfrared (MIR) based biomarkers in genetic improvement. Similarly, research has also shown that genetic variation is ... [more ▼]

Recent research showed the usefulness of using estimated breeding values (EBV) for midinfrared (MIR) based biomarkers in genetic improvement. Similarly, research has also shown that genetic variation is contained in the absorbance traits along the MIR band of wavelengths. Targeted extraction of the useful genetic variance can be achieved by the combination of EBV. Direct estimation of EBV for absorbance traits was demonstrated. Our first objective was to show that the reduction of the rank of the (co)variance structure among spectral traits is possible by imposing linear functions, even if these functions represent lower accuracy MIR biomarkers. MIR based biomarkers traits were derived from ongoing research in the FP7 GplusE project. In this study, the pathway from MIR spectra to the use in genetic improvement will be described. First, blood reference phenotypic data was collected on Holstein cows, at early lactation for IGF-1, glucose, urea, cholesterol, fructosamine, β- hydroxybutyric (BHB) acid and non-esterified fatty acids (NEFA). These traits were calibrated against corresponding MIR spectral data. Calibration 2 cv R ranged from 0.21 to 0.51, very low from a chemometrical point of view, but potentially sufficient to extract useful spectral variation. This was validated, using EBV that were based on these MIR predictions for 144,623 records (closest to days in milk 25), from 73,378 cows, in the Walloon region of Belgium. Single-trait, but multi-lactation (1, 2, 3+) models yielded h2 estimates ranging from 0.07 to 0.27. At least 20 daughters with novel traits and official EBV for udder health, fertility and longevity with minimum reliabilities of 70% were required; a total of 124 bulls met this criteria. Standard selection index theory would usually rely on prediction error variance minimisation and estimated population (co)variances. Alternatively in this study, Partial Least Squares were applied to EBV for the milk MIR based biomarkers to develop novel genetic predictors, for udder health, fertility and longevity, by extracting genetic variation along the wave band after rank reduction. Using all bulls, correlations between best predictors and EBV for udder health, fertility and longevity were at least 0.63, 0.67 and 0.62. Using selection index theory and based on significant increases of prediction abilities of longevity (0.76 compared to 0.68 from udder health or fertility alone) using also milk MIR based blood biomarkers, their potential contribution to genetic improvement of udder health, fertility and longevity will be demonstrated. [less ▲]

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See detailBayesian single-step genomic evaluations combining local and foreign information in Walloon Holsteins
Colinet, Frédéric ULiege; Vandenplas, J.; Vanderick, Sylvie ULiege et al

in Animal (2017)

Most dairy cattle populations found in different countries around the world are small to medium sized and use many artificial insemination bulls imported from different foreign countries. The Walloon ... [more ▼]

Most dairy cattle populations found in different countries around the world are small to medium sized and use many artificial insemination bulls imported from different foreign countries. The Walloon population in the southern part of Belgium is a good example for such a small-scale population. Wallonia has also a very active community of Holstein breeders requesting high level genetic evaluation services. Single-step Genomic BLUP (ssGBLUP) methods allow the simultaneous use of genomic, pedigree and phenotypic information and could reduce potential biases in the estimation of genomically enhanced breeding values (GEBV). Therefore, in the context of implementing a Walloon genomic evaluation system for Holsteins, it was considered as the best option. However, in contrast to multi-step genomic predictions, natively ssGBLUP will only use local phenotypic information and is unable to use directly important other sources of information coming from abroad, for example Multiple Across Country Evaluation (MACE) results as provided by the Interbull Center (Uppsala, Sweden). Therefore, we developed and implemented single-step Genomic Bayesian Prediction (ssGBayes), as an alternative method for the Walloon genomic evaluations. The ssGBayes method approximated the correct system of equations directly using estimated breeding values (EBV) and associated reliabilities (REL) without any explicit deregression step. In the Walloon genomic evaluation, local information refers to Walloon EBV and REL and foreign information refers to MACE EBV and associated REL. Combining simultaneously all available genotypes, pedigree, local and foreign information in an evaluation can be achieved but adding contributions to left-hand and right-hand sides subtracting double-counted contributions. Correct propagation of external information avoiding double counting of contributions due to relationships and due to records can be achieved. This ssGBayes method computed more accurate predictions for all types of animals. For example, for genotyped animals with low Walloon REL (<0.25) without MACE results but sired by genotyped bulls with MACE results, the average increase of REL for the studied traits was 0.38 points of which 0.08 points could be traced to the inclusion of MACE information. For other categories of genotyped animals, the contribution by MACE information was also high. The Walloon genomic evaluation system passed for the first time the Interbull GEBV tests for several traits in July 2013. Recent experiences reported here refer to its use in April 2016 for the routine genomic evaluations of milk production, udder health and type traits. Results showed that the proposed methodology should also be of interest for other, similar, populations. [less ▲]

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See detailGenetic evaluation for birth and conformation traits in dual-purpose Belgian Blue cattle using a mixed inheritance model
REIS MOTA, Rodrigo ULiege; Mayeres, P.; Bastin, Catherine et al

in Journal of Animal Science (2017)

The segregation of the causal mutation (mh) in the muscular hypertrophy gene in dual-purpose Belgian Blue (dpBB) cattle is considered to result in greater calving difficulty (dystocia). Establishing ... [more ▼]

The segregation of the causal mutation (mh) in the muscular hypertrophy gene in dual-purpose Belgian Blue (dpBB) cattle is considered to result in greater calving difficulty (dystocia). Establishing adapted genetic evaluations might overcome this situation through efficient selection. However, the heterogeneity of dpBB populations at the mh locus implies separating the major gene and other polygenic effects in complex modeling. The use of mixed inheritance models may be an interesting option because they simultaneously assume both influences. A genetic evaluation in dpBB based on a mixed inheritance model was developed for birth and conformation traits: gestation length (GL), calving difficulty (CD), birth weight (BiW), and body conformation score (BC). A total of 27,362 animals having records were used for analyses. The total number of animals in the pedigree used to build the numerator relationship matrix was 62,617. Genotypes at the mh locus were available for 2,671 animals. Missing records at this locus were replaced with genotype probabilities. A total of 13,221 (48.3%) were registered as dpBB, 1,287 (4.7%) as beef Belgian Blue, and 12,854 (47.0%) were unknown. From those 13,221dpBB animals, 650, 849, and 534 had double or single copies or no copy, respectively, of the causal mutation (mh) in the muscular hypertrophy gene, whereas 11,188 had missing genotypes. This heterogeneity at the mh locus may be the reason for high variability in the studied traits, that is, high heritability estimates of 0.33, 0.30, 0.38, and 0.43 for GL, CD, BiW, and BC, respectively. In general, additive (P < 0.05) and dominance (P < 0.001) allele substitution for calves and dams had significant impact for all traits. The moderate coefficient of genetic variation (27.80%) and high direct heritability (0.28) for CD suggested genetic variability in dpBB and possible genetic improvement through selection. This variability has allowed dpBB breeders to successfully apply mass selection in the past. Genetic trend means from 1988 to 2016 showed that sire selection for CD within genotype was progressively applied by breeders. The selection intensity was more important for CD in double-muscled lines than in segregated lines. Our study illustrated the possible confusion caused by the use of major genes in selection and the importance of fitting appropriate models such as mixed inheritance models that combine polygenic and gene content information. [less ▲]

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See detailConsequences of genetic selection for environmental impact traits on economically important traits in dairy cows
Kandel, Purna ULiege; Vanderick, Sylvie ULiege; Vanrobays, Marie-Laure ULiege et al

in Animal Production Science (2017)

Methane (CH4) emission is an important environmental trait in dairy cows. Breeding aiming to mitigate CH4 emissions require the estimation of genetic correlations with other economically important traits ... [more ▼]

Methane (CH4) emission is an important environmental trait in dairy cows. Breeding aiming to mitigate CH4 emissions require the estimation of genetic correlations with other economically important traits and the prediction of their selection response. In this study, test-day CH4 emissions were predicted from milk mid-infrared spectra of Holstein cows. Predicted CH4 emissions (PME) and log-transformed CH4 intensity (LMI) computed as the natural logarithm of PME divided by milk yield (MY). Genetic correlations of PME and LMI with traits used currently were approximated from correlations between estimated breeding values of sires. Values were for PME with MY 0.06, fat yield (FY) 0.09, protein yield (PY) 0.13, fertility 0.17; body condition score (BCS) –0.02; udder health (UDH) 0.22; and longevity 0.22. As expected by its definition, values were negative for LMI with production traits (MY –0.61; FY –0.15 and PY –0.40) and positive with fertility (0.36); BCS (0.20); UDH (0.08) and longevity (0.06). The genetic correlations of 33 type traits with PME ranged from –0.12 to 0.25 and for LMI ranged from –0.22 to 0.18. Without selecting PME and LMI (status quo) the relative genetic change through correlated responses of other traits were in PME by 2% and in LMI by –15%, but only due to the correlated response to MY. Results showed for PME that direct selection of this environmental trait would reduce milk carbon foot print but would also affect negatively fertility. Therefore, more profound changes in current indexes will be required than simply adding environmental traits as these traits also affect the expected progress of other traits. [less ▲]

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See detailImprovement of genetic evaluation systems for maternally influenced traits and multi-breed livestock populations
Vanderick, Sylvie ULiege

Doctoral thesis (2017)

Animal breeding programs are designed to genetically improve livestock populations over many generations to enhance farm sustainability and competitiveness. Genetic improvement is achieved by selecting ... [more ▼]

Animal breeding programs are designed to genetically improve livestock populations over many generations to enhance farm sustainability and competitiveness. Genetic improvement is achieved by selecting genetically superior animals, based on estimated breeding values, to be the parents of the next generation. These estimated breeding values are calculated by solving mixed model equations characterizing appropriate statistical genetic evaluation models. To guarantee effective genetic selection, genetic evaluation models must be tailored to the specific characteristics of the traits and population under evaluation. This PhD thesis focused on the development of genetic evaluation models suitable for categorical maternally influenced traits and for multi-breed populations. Appropriate genetic animal models were developed and assessed: (1) for two categorical maternally influenced traits based on calving ease scores from Walloon Holstein dairy cattle and on lamb survival data from a New Zealand sheep population; (2) for two multi-breed populations based on milk yield records of New Zealand purebred and crossbred dairy cattle, and on purebred and crossbred calving ease scores from Walloon Belgian Blue and Holstein cattle. Results showed that (1) fitting maternal effects was required to avoid biasing the estimated breeding values, and there was no clear advantage in using non-linear mixed models instead of linear mixed models for the genetic analysis of the two categorical maternal traits studied; (2) breed-dependent breeding values could be estimated using the proposed multi-breed models, and that combining purebred and crossbred data had a positive influence on the accuracy of the breeding values of purebred animals. Finally, part of the research presented in this thesis contributed to the development of the genetic evaluation systems currently used in Walloon Region of Belgium and in New Zealand. [less ▲]

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See detailUsefulness of multi-breed models in genetic evaluation of direct and maternal calving ease in Holstein and Belgian Blue Walloon purebreds and crossbreds
Vanderick, Sylvie ULiege; Gillon, Alain; Glorieux, Géry et al

in Livestock Science (2017), 198

The objective of this study was to verify the feasibility of a joint genetic evaluation system for calving ease trait of Belgian Blue (BBB) and Holstein (HOL) Walloon cattle based on data of purebred and ... [more ▼]

The objective of this study was to verify the feasibility of a joint genetic evaluation system for calving ease trait of Belgian Blue (BBB) and Holstein (HOL) Walloon cattle based on data of purebred and crossbred animals. Variance components and derived genetic parameters for purebred BBB and HOL animals were estimated by using single-breed linear animal models. This analysis showed clear genetic differences between breeds. Estimates of direct and maternal heritabilities (± standard error) were 0.34 (±0.02) and 0.09 (±0.01) for BBB, respectively, but only 0.09 (±0.01) and 0.04 (±0.01) for HOL, respectively. Moreover, a significant negative genetic correlation between direct and maternal effects was obtained in both breeds: −0.46 (±0.04) for BBB and −0.29 (±0.11) for HOL. Variance components and derived genetic parameters for purebred BBB and HOL and crossbred BBB ×× HOL cattle were then estimated by using two multi-breed linear animal models: a multi-breed model based on a random regression test-day model (Model MBV), and a multi-breed model based on the random regression multi-breed model (Model MBSM). Both multi-breed models use different functions of breed proportions as random regressions, thereby enabling modelling different additive effects according to animal's breed composition. The main difference between these models is the way in which relationships between breeds are accounted for in the genetic (co)variance structure. Genetic parameters differed between single-breed and multi-breed analysis, but are similar to the literature. For BBB, estimates of direct and maternal heritabilities (±SE) were 0.45 (±0.07) and 0.08 (±0.01) by using Model MBV, and 0.45 (±0.08) and 0.09 (±0.02) for Model MBSM, respectively. For HOL, these estimates were 0.18 (±0.04) and 0.05 (±0.01) using Model MBV, and 0.16 (±0.04) and 0.05 (±0.01) for Model MBSM, respectively. Reliability gains (up to 25%) indicated that the use of crossbred data in the multi-breed models had a positive influence on the estimation of genetic merit of purebred animals. A slight re-ranking of purebred sires and maternal grandsires was observed between single-breed and multi-breed models. Moreover, both multi-breed models can be considered as quasi-equivalent models because they performed almost equally well with respect to MSE and correlations, for purebred and crossbred animals. [less ▲]

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See detailCapitalizing on fine milk composition for breeding and management of dairy cows
Gengler, Nicolas ULiege; Soyeurt, Hélène ULiege; Dehareng, Fréderic et al

in Journal of Dairy Science (2016), 99(5), 4071-4079

The challenge of managing and breeding dairy cows is permanently adapting to changing production circumstances under socio-economic constraints. If managing and breeding address different timeframes of ... [more ▼]

The challenge of managing and breeding dairy cows is permanently adapting to changing production circumstances under socio-economic constraints. If managing and breeding address different timeframes of action, both need relevant phenotypes that allow for precise monitoring of the status of the cows, and their health, behavior, and well-being as well as their environmental impact and the quality of their products (i.e., milk and subsequently dairy products). Milk composition has been identified as an important source of information because it could reflect, at least partially, all these elements. Major conventional milk components such as fat, protein, urea, and lactose contents are routinely predicted by mid-infrared (MIR) spectrometry and have been widely used for these purposes. But, milk composition is much more complex and other nonconventional milk components, potentially predicted by MIR, might be informative. Such new milk-based phenotypes should be considered given that they are cheap, rapidly obtained, usable on a large scale, robust, and reliable. In a first approach, new phenotypes can be predicted from MIR spectra using techniques based on classical prediction equations. This method was used successfully for many novel traits (e.g., fatty acids, lactoferrin, minerals, milk technological properties, citrate) that can be then useful for management and breeding purposes. An innovation was to consider the longitudinal nature of the relationship between the trait of interest and the MIR spectra (e.g., to predict methane from MIR). By avoiding intermediate steps, prediction errors can be minimized when traits of interest (e.g., methane, energy balance, ketosis) are predicted directly from MIR spectra. In a second approach, research is ongoing to detect and exploit patterns in an innovative manner, by comparing observed with expected MIR spectra directly (e.g., pregnancy). All of these traits can then be used to define best practices, adjust feeding and health management, improve animal welfare, improve milk quality, and mitigate environmental impact. Under the condition that MIR data are available on a large scale, phenotypes for these traits will allow genetic and genomic evaluations. Introduction of novel traits into the breeding objectives will need additional research to clarify socio-economic weights and genetic correlations with other traits of interest. [less ▲]

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