1,287 research outputs found

    Use of maternal information for QTL detection in a (grand)daughter design

    Get PDF
    In a (grand)daughter design, maternal information is often neglected because the number of progeny per dam is limited. The number of dams per maternal grandsire (MGS), however, could be large enough to contribute to QTL detection. But dams and MGS usually are not genotyped, there are two recombination opportunities between the MGS and the progeny, and at a given location, only half the progeny receive a MGS chromosomal segment. A 3-step procedure was developed to estimate: (1) the marker phenotypes probabilities of the MGS; (2) the probability of each possible MGS haplotype; (3) the probabilities that the progeny receives either the first, or second MGS segment, or a maternal grandam segment. These probabilities were used for QTL detection in a linear model including the effects of sire, MGS, paternal QTL, MGS QTL and maternal grandam QTL. Including the grandam QTL effect makes it possible to detect QTL in the grandam population, even when MGS are not informative. The detection power, studied by simulation, was rather high, provided that MGS family size was greater than 50. Using maternal information in the French dairy cattle granddaughter design made it possible to detect 23 additional QTL genomewise significant

    Connectedness in the French Holstein cattle population

    Get PDF

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

    Get PDF
    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 procĂ©dures de Maximum de Vraisemblance Restreint (REML), l’estimation des composantes de (co)variance gĂ©nĂ©tique implique le calcul de la trace du produit de l’inverse de la matrice des coefficients par l’inverse de la matrice de parentĂ©s, calcul qui constitue gĂ©nĂ©ralement le facteur limitant de ce type de procĂ©dure. Nous prĂ©sentons dans cet article une mĂ©thode visant Ă  obtenir une valeur approchĂ©e de cette trace dans le cadre d’un modĂšle animal, en utilisant un modĂšle Ă©quivalent basĂ© sur l’alĂ©a de mĂ©iose, en simplifiant sa matrice des coefficients et en en calculant une inverse approchĂ©e. Cette approximation est trĂšs prĂ©cise lorsque l’hĂ©ritabilitĂ© du caractĂšre est faible mais elle tend Ă  sous-estimer la trace vraie lorsque l’hĂ©ritabilitĂ© est Ă©levĂ©e. IntĂ©grĂ©e dans une procĂ©dure de REML, cette mĂ©thode en rĂ©duit considĂ©rablement le coĂ»t mais fournit en gĂ©nĂ©ral des valeurs sous-estimĂ©es de variance gĂ©nĂ©tique. Divers exemples sont prĂ©sentĂ©s Ă  titre d'illustratio
    • 

    corecore