References of "Genetics, Selection, Evolution"
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See detailUnified method to integrate and blend several, potentially related, sources of information for genetic evaluation
Vandenplas, Jérémie ULg; Colinet, Frédéric ULg; Gengler, Nicolas ULg

in Genetics, Selection, Evolution (2014), 46

Background A condition to predict unbiased estimated breeding values by best linear unbiased prediction is to use simultaneously all available data. However, this condition is not often fully met. For ... [more ▼]

Background A condition to predict unbiased estimated breeding values by best linear unbiased prediction is to use simultaneously all available data. However, this condition is not often fully met. For example, in dairy cattle, internal (i.e. local) populations lead to evaluations based only on internal records while widely used foreign sires have been selected using internally unavailable external records. In such cases, internal genetic evaluations may be less accurate and biased. Because external records are unavailable, methods were developed to combine external information that summarizes these records, i.e. external estimated breeding values and associated reliabilities, with internal records to improve accuracy of internal genetic evaluations. Two issues of these methods concern double-counting of contributions due to relationships and due to records. These issues could be worse if external information came from several evaluations, at least partially based on the same records, and combined into a single internal evaluation. Based on a Bayesian approach, the aim of this research was to develop a unified method to integrate and blend simultaneously several sources of information into an internal genetic evaluation by avoiding double-counting of contributions due to relationships and due to records. Results This research resulted in equations that integrate and blend simultaneously several sources of information and avoid double-counting of contributions due to relationships and due to records. The performance of the developed equations was evaluated using simulated and real datasets. The results showed that the developed equations integrated and blended several sources of information well into a genetic evaluation. The developed equations also avoided double-counting of contributions due to relationships and due to records. Furthermore, because all available external sources of information were correctly propagated, relatives of external animals benefited from the integrated information and, therefore, more reliable estimated breeding values were obtained. Conclusions The proposed unified method integrated and blended several sources of information well into a genetic evaluation by avoiding double-counting of contributions due to relationships and due to records. The unified method can also be extended to other types of situations such as single-step genomic or multi-trait evaluations, combining information across different traits. [less ▲]

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See detailError rate for imputation from the Illumina BovineSNP50 chip to the Illumina BovineHD chip.
Schrooten, Chris; Dassonneville, Romain; Ducrocq, Vincent et al

in Genetics, Selection, Evolution (2014), 46(1), 10

BACKGROUND: Imputation of genotypes from low-density to higher density chips is a cost-effective method to obtain high-density genotypes for many animals, based on genotypes of only a relatively small ... [more ▼]

BACKGROUND: Imputation of genotypes from low-density to higher density chips is a cost-effective method to obtain high-density genotypes for many animals, based on genotypes of only a relatively small subset of animals (reference population) on the high-density chip. Several factors influence the accuracy of imputation and our objective was to investigate the effects of the size of the reference population used for imputation and of the imputation method used and its parameters. Imputation of genotypes was carried out from 50 000 (moderate-density) to 777 000 (high-density) SNPs (single nucleotide polymorphisms). METHODS: The effect of reference population size was studied in two datasets: one with 548 and one with 1289 Holstein animals, genotyped with the Illumina BovineHD chip (777 k SNPs). A third dataset included the 548 animals genotyped with the 777 k SNP chip and 2200 animals genotyped with the Illumina BovineSNP50 chip. In each dataset, 60 animals were chosen as validation animals, for which all high-density genotypes were masked, except for the Illumina BovineSNP50 markers. Imputation was studied in a subset of six chromosomes, using the imputation software programs Beagle and DAGPHASE. RESULTS: Imputation with DAGPHASE and Beagle resulted in 1.91% and 0.87% allelic imputation error rates in the dataset with 548 high-density genotypes, when scale and shift parameters were 2.0 and 0.1, and 1.0 and 0.0, respectively. When Beagle was used alone, the imputation error rate was 0.67%. If the information obtained by Beagle was subsequently used in DAGPHASE, imputation error rates were slightly higher (0.71%). When 2200 moderate-density genotypes were added and Beagle was used alone, imputation error rates were slightly lower (0.64%). The least imputation errors were obtained with Beagle in the reference set with 1289 high-density genotypes (0.41%). CONCLUSIONS: For imputation of genotypes from the 50 k to the 777 k SNP chip, Beagle gave the lowest allelic imputation error rates. Imputation error rates decreased with increasing size of the reference population. For applications for which computing time is limiting, DAGPHASE using information from Beagle can be considered as an alternative, since it reduces computation time and increases imputation error rates only slightly. [less ▲]

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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 ▲]

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See detailStructural esuation models to estimate risk infection and tolerance to bovine mastitis
Detilleux, Johann ULg; Theron, Léonard ULg; Duprez, Jean-Noël ULg et al

in Genetics, Selection, Evolution (2013), 45

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See detailEffectiveness analysis of resistance and tolerance to infection
Detilleux, Johann ULg

in Genetics, Selection, Evolution (2011)

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See detailA common reference population from four European Holstein populations increases reliability of genomic predictions.
Lund, M. S.; de Ross, S. P.; de Vries, A. G. et al

in Genetics, Selection, Evolution (2011), 43(1), 43

ABSTRACT: BACKGROUND: Size of the reference population and reliability of phenotypes are crucial factors influencing the reliability of genomic predictions. It is therefore useful to combine closely ... [more ▼]

ABSTRACT: BACKGROUND: Size of the reference population and reliability of phenotypes are crucial factors influencing the reliability of genomic predictions. It is therefore useful to combine closely related populations. Increased accuracies of genomic predictions depend on the number of individuals added to the reference population, the reliability of their phenotypes, and the relatedness of the populations that are combined. METHODS: This paper assesses the increase in reliability achieved when combining four Holstein reference populations of 4000 bulls each, from European breeding organizations, i.e. UNCEIA (France), VikingGenetics (Denmark, Sweden, Finland), DHV-VIT (Germany) and CRV (The Netherlands, Flanders). Each partner validated its own bulls using their national reference data and the combined data, respectively. RESULTS: Combining the data significantly increased the reliability of genomic predictions for bulls in all four populations. Reliabilities increased by 10%, compared to reliabilities obtained with national reference populations alone, when they were averaged over countries and the traits evaluated. For different traits and countries, the increase in reliability ranged from 2% to 19%. CONCLUSIONS: Genomic selection programs benefit greatly from combining data from several closely related populations into a single large reference population. [less ▲]

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See detailDoes probabilistic modelling of linkage disequilibrium evolution improve the accuracy of QTL location in animal pedigree?
Cierco-Ayrolles, C.; Dejean, S.; Legarra, A. et al

in Genetics, Selection, Evolution (2010), 42

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See detailThe analysis of disease biomarker data using a mixed hidden Markov model
Detilleux, Johann ULg

in Genetics, Selection, Evolution (2008), 40(5), 491-509

A mixed hidden Markov model (HMM) was developed for predicting breeding values of a biomarker (here, somatic cell score) and the individual probabilities of health and disease (here, mastitis) based upon ... [more ▼]

A mixed hidden Markov model (HMM) was developed for predicting breeding values of a biomarker (here, somatic cell score) and the individual probabilities of health and disease (here, mastitis) based upon the measurements of the biomarker. At a first level, the unobserved disease process (Markov model) was introduced and at a second level, the measurement process was modeled, making the link between the unobserved disease states and the observed biomarker values. This hierarchical formulation allows joint estimation of the parameters of both processes. The flexibility of this approach is illustrated on the simulated data. Firstly, lactation curves for the biomarker were generated based upon published parameters (mean, variance, and probabilities of infection) for cows with known clinical conditions (health or mastitis due to Escherichia coli or Staphylococcus aureus). Next, estimation of the parameters was performed via Gibbs sampling, assuming the health status was unknown. Results from the simulations and mathematics show that the mixed HMM is appropriate to estimate the quantities of interest although the accuracy of the estimates is moderate when the prevalence of the disease is low. The paper ends with some indications for further developments of the methodology. [less ▲]

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See detailDetection of quantitative trait loci for reproduction and production traits in Large White and French Landrace pig populations.
Tribout, Thierry; Iannuccelli, Nathalie; Druet, Tom ULg et al

in Genetics, Selection, Evolution (2008), 40(1), 61-78

A genome-wide scan was performed in Large White and French Landrace pig populations in order to identify QTL affecting reproduction and production traits. The experiment was based on a granddaughter ... [more ▼]

A genome-wide scan was performed in Large White and French Landrace pig populations in order to identify QTL affecting reproduction and production traits. The experiment was based on a granddaughter design, including five Large White and three French Landrace half-sib families identified in the French porcine national database. A total of 239 animals (166 sons and 73 daughters of the eight male founders) distributed in eight families were genotyped for 144 microsatellite markers. The design included 51 262 animals recorded for production traits, and 53 205 litter size records were considered. Three production and three reproduction traits were analysed: average backfat thickness (US_M) and live weight (LWGT) at the end of the on-farm test, age of candidates adjusted at 100 kg live weight, total number of piglets born per litter, and numbers of stillborn (STILLp) and born alive (LIVp) piglets per litter. Ten QTL with medium to large effects were detected at a chromosome-wide significance level of 5% affecting traits US_M (on SSC2, SSC3 and SSC17), LWGT (on SSC4), STILLp (on SSC6, SSC11 and SSC14) and LIVp (on SSC7, SSC16 and SSC18). The number of heterozygous male founders varied from 1 to 3 depending on the QTL. [less ▲]

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See detailEstimation by simulation of the efficiency of the French marker-assisted selection program in dairy cattle.
Guillaume, François; Fritz, Sébastien; Boichard, Didier et al

in Genetics, Selection, Evolution (2008), 40(1), 91-102

The efficiency of the French marker-assisted selection (MAS) was estimated by a simulation study. The data files of two different time periods were used: April 2004 and 2006. The simulation method used ... [more ▼]

The efficiency of the French marker-assisted selection (MAS) was estimated by a simulation study. The data files of two different time periods were used: April 2004 and 2006. The simulation method used the structure of the existing French MAS: same pedigree, same marker genotypes and same animals with records.The program simulated breeding values and new records based on this existing structure and knowledge on the QTL used in MAS (variance and frequency). Reliabilities of genetic values of young animals (less than one year old) obtained with and without marker information were compared to assess the efficiency of MAS for evaluation of milk, fat and protein yields and fat and protein contents. Mean gains of reliability ranged from 0.015 to 0.094 and from 0.038 to 0.114 in 2004 and 2006, respectively. The larger number of animals genotyped and the use of a new set of genetic markers can explain the improvement of MAS reliability from 2004 to 2006. This improvement was also observed by analysis of information content for young candidates. The gain of MAS reliability with respect to classical selection was larger for sons of sires with genotyped progeny daughters with records. Finally, it was shown that when superiority of MAS over classical selection was estimated with daughter yield deviations obtained after progeny test instead of true breeding values, the gain was underestimated. [less ▲]

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See detailEstimation of genetic parameters for test day records of dairy traits in the first three lactations.
Druet, Tom ULg; Jaffrezic, Florence; Ducrocq, Vincent

in Genetics, Selection, Evolution (2005), 37(3), 257-71

Application of test-day models for the genetic evaluation of dairy populations requires the solution of large mixed model equations. The size of the (co)variance matrices required with such models can be ... [more ▼]

Application of test-day models for the genetic evaluation of dairy populations requires the solution of large mixed model equations. The size of the (co)variance matrices required with such models can be reduced through the use of its first eigenvectors. Here, the first two eigenvectors of (co)variance matrices estimated for dairy traits in first lactation were used as covariables to jointly estimate genetic parameters of the first three lactations. These eigenvectors appear to be similar across traits and have a biological interpretation, one being related to the level of production and the other to persistency. Furthermore, they explain more than 95% of the total genetic variation. Variances and heritabilities obtained with this model were consistent with previous studies. High correlations were found among production levels in different lactations. Persistency measures were less correlated. Genetic correlations between second and third lactations were close to one, indicating that these can be considered as the same trait. Genetic correlations within lactation were high except between extreme parts of the lactation. This study shows that the use of eigenvectors can reduce the rank of (co)variance matrices for the test-day model and can provide consistent genetic parameters. [less ▲]

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See detailGenetic management of infectious diseases: An heterogeneous epidemio-genetic model illustrated with S. aureus mastitis
Detilleux, Johann ULg

in Genetics, Selection, Evolution (2005), 37(4), 437-453

Given that individuals are genetically heterogeneous in their degree of resistance to infection, a model is proposed to formulate appropriate choices that will limit the spread of an infectious disease ... [more ▼]

Given that individuals are genetically heterogeneous in their degree of resistance to infection, a model is proposed to formulate appropriate choices that will limit the spread of an infectious disease. The model is illustrated with data on S. aureus mastitis and is based on parameters characterizing the spread of the disease (contact rate, probability of infection after contact, and rate of recovery after infection), the demography (replacement and culling rates) and the genetic composition (degree of relationship and heritability of the disease trait) of the animal population. To decrease infection pressure, it is possible to apply non-genetic procedures that increase the culling (e.g., culling of chronically infected cows) and recovery (e.g., antibiotic therapy) rates of infected cows. But the contribution of the paper is to show that genetic management of infectious disease is also theoretically possible as a control measure complementary to non-genetic actions. Indeed, the probability for an uninfected individual to become infected after contact with an infected one is partially related to their degree of kinship: the more closely they are related, the more likely they are to share identical genes like those associated to the non-resistance to infection. Different prospective genetic management procedures are proposed to decrease the contact rate between infected and uninfected relatives and keep the number of secondary cases generated by one infected animal below 1. [less ▲]

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See detailThe callipyge mutation and other genes that affect muscle hypertrophy in sheep.
Cockett, Noelle E; Smit, Maria A; Bidwell, Christopher A et al

in Genetics, Selection, Evolution (2005), 37 Suppl 1

Genetic strategies to improve the profitability of sheep operations have generally focused on traits for reproduction. However, natural mutations exist in sheep that affect muscle growth and development ... [more ▼]

Genetic strategies to improve the profitability of sheep operations have generally focused on traits for reproduction. However, natural mutations exist in sheep that affect muscle growth and development, and the exploitation of these mutations in breeding strategies has the potential to significantly improve lamb-meat quality. The best-documented mutation for muscle development in sheep is callipyge (CLPG), which causes a postnatal muscle hypertrophy that is localized to the pelvic limbs and loin. Enhanced skeletal muscle growth is also observed in animals with the Carwell (or rib-eye muscling) mutation, and a double-muscling phenotype has been documented for animals of the Texel sheep breed. However, the actual mutations responsible for these muscular hypertrophy phenotypes in sheep have yet to be identified, and further characterization of the genetic basis for these phenotypes will provide insight into the biological control of muscle growth and body composition. [less ▲]

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See detailMixture model for inferring susceptibility to mastitis in dairy cattle: a procedure for likelihood-based inference
Gianola, D.; Odegard, J.; Heringstad, B. et al

in Genetics, Selection, Evolution (2004), 36(1, JAN-FEB), 3-27

A Gaussian mixture model with a finite number of components and correlated random effects is described. The ultimate objective is to model somatic cell count information in dairy cattle and to develop ... [more ▼]

A Gaussian mixture model with a finite number of components and correlated random effects is described. The ultimate objective is to model somatic cell count information in dairy cattle and to develop criteria for genetic selection against mastitis, an important udder disease. Parameter estimation is by maximum likelihood or by an extension of restricted maximum likelihood. A Monte Carlo expectation- maximization algorithm is used for this purpose. The expectation step is carried out using Gibbs sampling, whereas the maximization step is deterministic. Ranking rules based on the conditional probability of membership in a putative group of uninfected animals, given the somatic cell information, are discussed. Several extensions of the model are suggested. [less ▲]

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See detailHaplotype diversity of the myostatin gene among beef cattle breeds
Dunner, S.; Miranda, M. E.; Amigues, Y. et al

in Genetics, Selection, Evolution (2003), 35(1, JAN-FEB), 103-118

A total of 678 individuals from 28 European bovine breeds were both phenotyped and analysed at the myostatin locus by the Single Strand Conformation Polymorphism (SSCP) method. Seven new mutations were ... [more ▼]

A total of 678 individuals from 28 European bovine breeds were both phenotyped and analysed at the myostatin locus by the Single Strand Conformation Polymorphism (SSCP) method. Seven new mutations were identified which contribute to the high polymorphism (1 SNP every 100 bp) present in this small gene; twenty haplotypes were described and a genotyping method was set up using the Oligonucleotide Ligation Assay (OLA) method. Some haplotypes appeared to be exclusive to a particular breed; this was the case for 5 in the Charolaise (involving mutation Q204X) and 7 in the Maine-Anjou (involving mutation E226X). The relationships between the different haplotypes were studied, thus allowing to test the earlier hypothesis on the origin of muscular hypertrophy in Europe: muscular hypertrophy (namely m821 (del11)) was mainly spread in different waves from northern Europe milk purpose populations in most breeds; however, other mutations (mostly disruptive) arose in a single breed, were highly selected and have since scarcely evolved to other populations. [less ▲]

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See detailResults of a whole genome scan targeting QTL for growth and carcass traits in a Pietrain x Large White intercross
Nezer, C.; Moreau, L.; Wagenaar, D. et al

in Genetics, Selection, Evolution (2002), 34(3, May-Jun), 371-387

We herein report the results of a whole genome scan performed in a Pietrain x Large White intercross counting 525 offspring to map QTL influencing economically important growth and carcass traits. We ... [more ▼]

We herein report the results of a whole genome scan performed in a Pietrain x Large White intercross counting 525 offspring to map QTL influencing economically important growth and carcass traits. We report experiment-wide significant lod scores (> 4.6) for meatiness and fat deposition on chromosome SSC2, and for average daily gain and carcass length on chromosome SSC7. Additional suggestive lod scores (> 3.3) for fat deposition are reported on chromosomes SSC1, SSC7 and SSC13. A significant dominance deviation was found for the QTL on SSC1, while the hypothesis of an additive QTL could not be rejected for the QTL on SSC7 and SSC13. No evidence for imprinted QTL could be found for QTL other than the one previously reported on SSC2. [less ▲]

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See detailRelationships among estimates of inbreeding depression, dominance and additive variance for linear traits in Holsteins
Misztal, I.; Lawlor, T. J.; Gengler, Nicolas ULg

in Genetics, Selection, Evolution (1997), 29(4), 319-326

Estimates of dominance and additive variances were obtained for 14 linear traits. The data included 600 678 first parity records on 14 linear traits in Holsteins. The model included management groups, age ... [more ▼]

Estimates of dominance and additive variances were obtained for 14 linear traits. The data included 600 678 first parity records on 14 linear traits in Holsteins. The model included management groups, age at calving, additive and dominance effects, and regression on inbreeding percentage. The estimate of the dominance variance was 9.8% of the phenotypic variance for body depth: 8.0% for strength, 6.9% for stature, and was less than 5% for the remaining traits. The additive variance ranged from 12.2% for foot angle to 45.3% for stature. No clear relationship was found between the estimates of dominance and additive variance. larger negative estimates of the inbreeding depression were associated with higher estimates of the dominance variance. [less ▲]

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See detailAbsence probable de la translocation Robertsonienne 1/29 en race bovine Blanc Bleu Belge
Nicolas, N.; Hidas, A.; Renaville, Robert ULg et al

in Genetics, Selection, Evolution (1995), 27(4), 377-380

The 1/29 translocation, a structural chromosomal abnormality, is often associated with infertility. For this reason, we wished to know its frequency in the Belgian Blue breed. In this study, none of the ... [more ▼]

The 1/29 translocation, a structural chromosomal abnormality, is often associated with infertility. For this reason, we wished to know its frequency in the Belgian Blue breed. In this study, none of the 138 Belgian Blue bulls karyotyped carried the 1/29 translocation. We calculated that the 1/29 translocation frequency in the Belgian Blue breed must be lower than 0.69% at the 5% level. This result can be explained by the origins of the breed. The Belgian Blue breed is descended from focal dairy breeds and from the Shorthorn breed, which can all be considered to be free of the 1/29 translocation. [less ▲]

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