BLUP Selection Research Articles

Two-stage selection strategies utilizing marker-quantitative trait locus information and individual performance.

Short- and long-term response to marker-assisted selection in two stages was studied using a stochastic simulation of a closed nucleus herd for beef production. First-stage selection was carried out within families based on information at a fully additive quantitative trait locus (QTL). Second-stage selection strategies were based on 1) individual phenotype, 2) individual phenotype precorrected for QTL, 3) a selection index incorporating phenotype and QTL information, 4) a standard animal model BLUP, and 5) a selection index incorporating marker-QTL information and standard animal model BLUP on records precorrected for QTL. All strategies were efficient in moving the favorable allele at the QTL to fixation, but they differed in the time to reach fixation. Mass selection was less efficient in changing allele frequencies than BLUP. Discounted accumulated response, accounting for the time response was realized and inflation rate, was proposed to rank strategies and to elude the conflict between short- and long-term response in marker-assisted selection. Discounted accumulated response at a time horizon of 20 yr for alternative two-stage selection strategies was compared with conventional BLUP carried out in second stage only. Within-family selection increased discounted accumulated response by more than 11% using Strategy 4 and by up to 12% using Strategy 5 at an inflation rate of 2%. The percentage increase in response was less for highly heritable traits and when the proportion of additive variance explained by the QTL was small. Strategy 5 gave larger response with reduced inbreeding. This strategy also resulted in the lowest cost-benefit ratio, requiring less genotyping per unit of response. Cost-benefit ratio for discounted genotyping and for discounted in vitro production of embryos for traits with low heritability was two to four times that for traits with high heritability. The use of first-stage selection slightly increased the level of inbreeding for both mass (Strategy 1) and BLUP selection (Strategies 4 and 5).

Potential benefit from using an identified major gene in BLUP evaluation with truncation and optimal selection

This study investigates the benefit of including information on an identi- fied major gene in the estimation of breeding values in BLUP selection programmes. Selection for a quantitative trait is controlled by polygenes and a major locus with known effect. The benefit of using the gene information obtained in the short-term was maintained in the long-term by applying a selection tool which makes use of BLUP evaluation and optimisation of genetic contributions for maximising genetic gain while restricting the rate of inbreeding. In the mixed inheritance model the se- lection tool, initially proposed for an infinitesimal model, was able to restrict the rate of inbreeding to the desired value and to give higher rates of response than standard truncation selection both when using and ignoring the information on the major gene. The simple use of BLUP (standard truncation selection) allowed long-term benefits from using the gene in situations where the favourable allele was recessive or additive with large effect. © Inra/Elsevier, Paris

Maximizing the response of selection with a predefined rate of inbreeding: overlapping generations.

In a breeding scheme, the aim is high rates of genetic gain with limited inbreeding. A dynamic selection rule is developed that maximizes selection response in populations with overlapping generations. The rule maximizes the genetic merit of selected animals while limiting the average relationship of the population after the current round of selection. The latter is shown to limit the contribution of the current population to the future inbreeding. The rule accounts for the selection of some candidates during previous selection rounds and for the expected future contributions of the selection candidates. Inputs for the rule are the BLUP breeding values and ages of selection candidates, the relationship matrix of all animals, and contributions of animals during previous selection rounds. Output is the optimal number of offspring for each candidate. Computer simulations of dairy cattle nucleus schemes showed that predefined rates of inbreeding were actually achieved, without compromising long-term selection response, at least up to 20 yr of selection. At the same rates of inbreeding, the dynamic selection rule obtained up to 44% more genetic gain than direct selection for BLUP breeding values. The advantage of the dynamic rule over BLUP selection decreased with increasing population sizes and with greater predefined rates of inbreeding. Consequently, the dynamic rule should be especially useful in small selection schemes in which relatively low rates of inbreeding are desired.

Genetic steady-state under BLUP selection for an infinite and homogeneous population with discrete generations

A matrix derivation is proposed to analytically calculate the asymptotic genetic variance-covariance matrix under BLUP selection according to the initial genetic parameters in a large population with discrete generations. The asymptotic genetic evolution of a homogeneous population with discrete generations is calculated for a selection operating on an index including all information (pedigree and records) from a non-inbred and unselected base population (BLUP selection) or on an index restricted to records of a few ancestral generations. Under the first hypothesis, the prediction error variance of the selection index is independent of selection and is calculated from the genetic parameters of the base population. Under the second hypothesis, the prediction error variance depends on selection. Furthermore, records of several generations of ancestors of the candidates for selection must be used to maintain a constant prediction error variance over time. The number of ancestral generations needed depends on the population structure and on the occurrence of fixed effects. Without fixed effects to estimate, accounting for two generations of ancestors is sufficient to estimate the asymptotic prediction error variance. The amassing of information from an unselected base population proves to be important in order not to overestimate the asymptotic genetic gains and not to underestimate the asymptotic genetic variances.

Genetic steady-state under BLUP selection for an infinite and homogeneous population with discrete generations

Genetic steady-state under BLUP selection for an infinite and homogeneous population with discrete generations

A deterministic model of BLUP selection in two tier open nucleus breeding schemes

A deterministic model is proposed for selection response in two tier open nucleus breeding schemes in which selection is based on breeding value estimates (ebv) calculated using a BLUP animal model. The population structure which maximises the equilibrium rate of genetic gain is determined for various open nucleus schemes selecting on BLUP ebv, and accomodating variance loss due to selection. The percentage improvement over a closed nucleus in the equilibrium rate of genetic gain of an optimised open nucleus scheme is independent of selection accuracy and thus depends solely on selection intensity. Moreover, optimum nucleus size is also independent of selection accuracy. These properties do not hold for mass selection within tiers. In sheep and beef cattle breeding the maximum advantage from opening a closed nucleus is between 8 and 13% for BLUP selection allowing both male and female migration between tiers. For selection on the basis of regressed Within Tier Phenotypic Deviation (rWTPD ), the maximum percentage improvement in the equilibrium genetic gain from opening the closed nucleus decreases as heritability increases and approaches a lower limit determined by BLUP selection.

An alternative to restricted BLUP based on mate selection

A new application of mate selection is presented in this study that maximizes the expected genetic progress of a selected trait while holding a correlated trait unchanged. The proposed method combines the use of BLUP evaluation and linear programming techniques and its properties have been analyzed by Monte Carlo simulation on a numerical example from beef cattle with selection for weaning weight and restriction on birth weight. With respect to restricted index or BLUP selection, this alternative method allows: (a) a similar response for both the selected and restricted traits, (b) lower variances of the responses and (c) greater robustness against errors in the genetic correlation estimate.