Estimation of covariance components between one continuous and one binary trait

International audienc

Approximate restricted maximum likelihood and approximate prediction error variance of the Mendelian sampling effect

In an Expectation-Maximization type Restricted Maximum Likelihood (REML) procedure, the estimation of a genetic (co-)variance component involves the trace of the product of the inverse of the coefficient matrix by the inverse of the relationship matrix. Computation of this trace is usually the limiting factor of this procedure. In this paper, a method is presented to approximate this trace in the case of an animal model, by using an equivalent model based on the Mendelian sampling effect and by simplifying its coefficient matrix and its inversion. This approximation appeared very accurate for low heritabilities but was downwards biased when the heritability was high. Implemented in a REML procedure, this approximation reduced dramatically the amount of computation, but provided downwards biased estimates of genetic variances. Several examples are presented to illustrate the method.Dans certaines procédures de Maximum de Vraisemblance Restreint (REML), l’estimation des composantes de (co)variance génétique implique le calcul de la trace du produit de l’inverse de la matrice des coefficients par l’inverse de la matrice de parentés, calcul qui constitue généralement le facteur limitant de ce type de procédure. Nous présentons dans cet article une méthode visant à obtenir une valeur approchée de cette trace dans le cadre d’un modèle animal, en utilisant un modèle équivalent basé sur l’aléa de méiose, en simplifiant sa matrice des coefficients et en en calculant une inverse approchée. Cette approximation est très précise lorsque l’héritabilité du caractère est faible mais elle tend à sous-estimer la trace vraie lorsque l’héritabilité est élevée. Intégrée dans une procédure de REML, cette méthode en réduit considérablement le coût mais fournit en général des valeurs sous-estimées de variance génétique. Divers exemples sont présentés à titre d'illustratio

Estimation of heritability in the base population when only records from later generations are available

International audienc

Comparison of analyses of the QTLMAS XII common dataset. I: Genomic selection

<p>Abstract</p> <p>A dataset was simulated and distributed to participants of the QTLMAS XII workshop who were invited to develop genomic selection models. Each contributing group was asked to describe the model development and validation as well as to submit genomic predictions for three generations of individuals, for which they only knew the genotypes. The organisers used these genomic predictions to perform the final validation by comparison to the true breeding values, which were known only to the organisers. Methods used by the 5 groups fell in 3 classes 1) fixed effects models 2) BLUP models, and 3) Bayesian MCMC based models. The Bayesian analyses gave the highest accuracies, followed by the BLUP models, while the fixed effects models generally had low accuracies and large error variance. The best BLUP models as well as the best Bayesian models gave unbiased predictions. The BLUP models are clearly sensitive to the assumed SNP variance, because they do not estimate SNP variance, but take the specified variance as the true variance. The current comparison suggests that Bayesian analyses on haplotypes or SNPs are the most promising approach for Genomic selection although the BLUP models may provide a computationally attractive alternative with little loss of efficiency. On the other hand fixed effect type models are unlikely to provide any gain over traditional pedigree indexes for selection.</p

Approaches in topical ocular drug delivery and developments in the use of contact lenses as drug-delivery devices

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Drug-delivery approaches have diversified over the last two decades with the emergence of nanotechnologies, smart polymeric systems and multimodal functionalities. The intended target for specific treatment of disease is the key defining developing parameter. One such area which has undergone significant advancements relates to ocular delivery. This has been expedited by the development of material advancement, mechanistic concepts and through the deployment of advanced process technologies. This review will focus on the developments within lens-based drug delivery while touching on conventional and current methods of topical ocular drug delivery. A summary table will provide quick reference to note the key findings in this area. In addition, the review also elucidates current theranostic and diagnostic approaches based on ocular lenses

Impacts of both reference population size and inclusion of a residual polygenic effect on the accuracy of genomic prediction

<p>Abstract</p> <p>Background</p> <p>The purpose of this work was to study the impact of both the size of genomic reference populations and the inclusion of a residual polygenic effect on dairy cattle genetic evaluations enhanced with genomic information.</p> <p>Methods</p> <p>Direct genomic values were estimated for German Holstein cattle with a genomic BLUP model including a residual polygenic effect. A total of 17,429 genotyped Holstein bulls were evaluated using the phenotypes of 44 traits. The Interbull genomic validation test was implemented to investigate how the inclusion of a residual polygenic effect impacted genomic estimated breeding values.</p> <p>Results</p> <p>As the number of reference bulls increased, both the variance of the estimates of single nucleotide polymorphism effects and the reliability of the direct genomic values of selection candidates increased. Fitting a residual polygenic effect in the model resulted in less biased genome-enhanced breeding values and decreased the correlation between direct genomic values and estimated breeding values of sires in the reference population.</p> <p>Conclusions</p> <p>Genetic evaluation of dairy cattle enhanced with genomic information is highly effective in increasing reliability, as well as using large genomic reference populations. We found that fitting a residual polygenic effect reduced the bias in genome-enhanced breeding values, decreased the correlation between direct genomic values and sire's estimated breeding values and made genome-enhanced breeding values more consistent in mean and variance as is the case for pedigree-based estimated breeding values.</p

Statistical modelling of growth using a mixed model with orthogonal polynomials

In statistical modelling, the effects of single-nucleotide polymorphisms (SNPs) are often regarded as time-independent. However, for traits recorded repeatedly, it is very interesting to investigate the behaviour of gene effects over time. In the analysis, simulated data from the 13th QTL-MAS Workshop (Wageningen, The Netherlands, April 2009) was used and the major goal was the modelling of genetic effects as time-dependent. For this purpose, a mixed model which describes each effect using the third-order Legendre orthogonal polynomials, in order to account for the correlation between consecutive measurements, is fitted. In this model, SNPs are modelled as fixed, while the environment is modelled as random effects. The maximum likelihood estimates of model parameters are obtained by the expectation–maximisation (EM) algorithm and the significance of the additive SNP effects is based on the likelihood ratio test, with p-values corrected for multiple testing. For each significant SNP, the percentage of the total variance contributed by this SNP is calculated. Moreover, by using a model which simultaneously incorporates effects of all of the SNPs, the prediction of future yields is conducted. As a result, 179 from the total of 453 SNPs covering 16 out of 18 true quantitative trait loci (QTL) were selected. The correlation between predicted and true breeding values was 0.73 for the data set with all SNPs and 0.84 for the data set with selected SNPs. In conclusion, we showed that a longitudinal approach allows for estimating changes of the variance contributed by each SNP over time and demonstrated that, for prediction, the pre-selection of SNPs plays an important role

2017 HRS/EHRA/ECAS/APHRS/SOLAECE expert consensus statement on catheter and surgical ablation of atrial fibrillation: executive summary.

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