Marker assisted selection with optimised contributions of the candidates to selection

The benefits of marker assisted selection (MAS) are evaluated under realistic assumptions in schemes where the genetic contributions of the candidates to selection are optimised for maximising the rate of genetic progress while restricting the accumulation of inbreeding. MAS schemes were compared with schemes where selection is directly on the QTL (GAS or gene assisted selection) and with schemes where genotype information is not considered (PHE or phenotypic selection). A methodology for including prior information on the QTL effect in the genetic evaluation is presented and the benefits from MAS were investigated when prior information was used. The optimisation of the genetic contributions has a great impact on genetic response but the use of markers leads to only moderate extra short-term gains. Optimised PHE did as well as standard truncation GAS (i.e. with fixed contributions) in the short-term and better in the long-term. The maximum accumulated benefit from MAS over PHE was, at the most, half of the maximum benefit achieved from GAS, even with very low recombination rates between the markers and the QTL. However, the use of prior information about the QTL effects can substantially increase genetic gain, and, when the accuracy of the priors is high enough, the responses from MAS are practically as high as those obtained with direct selection on the QTL.     

Dynamics of long-term genomic selection

Background

Simulation and empirical studies of genomic selection (GS) show accuracies sufficient to generate rapid gains in early selection cycles. Beyond those cycles, allele frequency changes, recombination, and inbreeding make analytical prediction of gain impossible. The impacts of GS on long-term gain should be studied prior to its implementation.

Methods

A simulation case-study of this issue was done for barley, an inbred crop. On the basis of marker data on 192 breeding lines from an elite six-row spring barley program, stochastic simulation was used to explore the effects of large or small initial training populations with heritabilities of 0.2 or 0.5, applying GS before or after phenotyping, and applying additional weight on low-frequency favorable marker alleles. Genomic predictions were from ridge regression or a Bayesian analysis.

Results

Assuming that applying GS prior to phenotyping shortened breeding cycle time by 50%, this practice strongly increased early selection gains but also caused the loss of many favorable QTL alleles, leading to loss of genetic variance, loss of GS accuracy, and a low selection plateau. Placing additional weight on low-frequency favorable marker alleles, however, allowed GS to increase their frequency earlier on, causing an initial increase in genetic variance. This dynamic led to higher long-term gain while mitigating losses in short-term gain. Weighted GS also increased the maintenance of marker polymorphism, ensuring that QTL-marker linkage disequilibrium was higher than in unweighted GS.

Conclusions

Losing favorable alleles that are in weak linkage disequilibrium with markers is perhaps inevitable when using GS. Placing additional weight on low-frequency favorable alleles, however, may reduce the rate of loss of such alleles to below that of phenotypic selection. Applying such weights at the beginning of GS implementation is important.     

Optimization of a crossing system using mate selection

A simple model based on one single identified quantitative trait locus (QTL) in a two-way crossing system was used to demonstrate the power of mate selection algorithms as a natural means of opportunistic line development for optimization of crossbreeding programs over multiple generations. Mate selection automatically invokes divergent selection in two parental lines for an over-dominant QTL and increased frequency of the favorable allele toward fixation in the sire-line for a fully-dominant QTL. It was concluded that an optimal strategy of line development could be found by mate selection algorithms for a given set of parameters such as genetic model of QTL, breeding objective and initial frequency of the favorable allele in the base populations, etc. The same framework could be used in other scenarios, such as programs involving crossing to exploit breed effects and heterosis. In contrast to classical index selection, this approach to mate selection can optimize long-term responses.     

Upweighting rare favourable alleles increases long-term genetic gain in genomic selection programs

Background

The short-term impact of using different genomic prediction (GP) models in genomic selection has been intensively studied, but their long-term impact is poorly understood. Furthermore, long-term genetic gain of genomic selection is expected to improve by using Jannink’s weighting (JW) method, in which rare favourable marker alleles are upweighted in the selection criterion. In this paper, we extend the JW method by including an additional parameter to decrease the emphasis on rare favourable alleles over the time horizon, with the purpose of further improving the long-term genetic gain. We call this new method dynamic weighting (DW). The paper explores the long-term impact of different GP models with or without weighting methods.

Methods

Different selection criteria were tested by simulating a population of 500 animals with truncation selection of five males and 50 females. Selection criteria included unweighted and weighted genomic estimated breeding values using the JW or DW methods, for which ridge regression (RR) and Bayesian lasso (BL) were used to estimate marker effects. The impacts of these selection criteria were compared under three genetic architectures, i.e. varying numbers of QTL for the trait and for two time horizons of 15 (TH15) or 40 (TH40) generations.

Results

For unweighted GP, BL resulted in up to 21.4% higher long-term genetic gain and 23.5% lower rate of inbreeding under TH40 than RR. For weighted GP, DW resulted in 1.3 to 5.5% higher long-term gain compared to unweighted GP. JW, however, showed a 6.8% lower long-term genetic gain relative to unweighted GP when BL was used to estimate the marker effects. Under TH40, both DW and JW obtained significantly higher genetic gain than unweighted GP. With DW, the long-term genetic gain was increased by up to 30.8% relative to unweighted GP, and also increased by 8% relative to JW, although at the expense of a lower short-term gain.

Conclusions

Irrespective of the number of QTL simulated, BL is superior to RR in maintaining genetic variance and therefore results in higher long-term genetic gain. Moreover, DW is a promising method with which high long-term genetic gain can be expected within a fixed time frame.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-015-0101-0) contains supplementary material, which is available to authorized users.     

The impact of recombination on short-term selection gain in plant breeding experiments

Recombination is a requirement for response to selection, but researchers still debate whether increasing recombination beyond normal levels will result in significant gains in short-term selection. We tested this hypothesis, in the context of plant breeding, through a series of simulation experiments comparing short-term selection response (≤20 cycles) between populations with normal levels of recombination and similar populations with unconstrained recombination (i.e., free recombination). We considered additive and epistatic models and examined a wide range of values for key design variables: selection cycles, QTL number, heritability, linkage phase, selection intensity and population size. With few exceptions, going from normal to unconstrained levels of recombination produced only modest gains in response to selection (≈11 % on average). We then asked how breeders might capture some of this theoretical gain by increasing recombination through either (1) extra rounds of mating or (2) selection of highly recombinant individuals via use of molecular markers/maps. All methods tested captured less than half of the potential gain, but our analysis indicates that the most effective method is to select for increased recombination and the trait simultaneously. This recommendation is based on evidence of a favorable interaction between trait selection and the impact of recombination on selection gains. Finally, we examined the relative contributions of the two components of meiotic recombination, chromosome assortment and crossing over, to short-term selection gain. Depending primarily on the presence of trait selection pressure, chromosome assortment alone accounted for 40–75 % of gain in response to short-term selection.     

Within-family marker-assisted selection for aquaculture species

A within-family marker-assisted selection scheme was designed for typical aquaculture breeding schemes, where most traits are recorded on sibs of the candidates. Here, sibs of candidates were tested for the trait and genotyped to establish genetic marker effects on the trait. BLUP breeding values were calculated, including information of the markers (MAS) or not (NONMAS). These breeding values were identical for all family members in the NONMAS schemes, but differed between family members in the MAS schemes, making within-family selection possible. MAS had up to twice the total genetic gain of the corresponding NONMAS scheme. MAS was somewhat less effective when heritability increased from 0.06 to 0.12 or when the frequency of the positive allele was < 0.5. The relative efficiency of MAS was higher for schemes with more candidates, because of larger fullsib family sizes. MAS was also more efficient when male:female mating ratio changed from 1:1 to 1:5 or when the QTL explained more of the total genetic variation. Four instead of two markers linked to the QTL increased genetic gain somewhat. There was no significant difference in polygenic genetic gain between MAS and NONMAS for most schemes. The rates of inbreeding were lower for MAS than NON-MAS schemes, because fewer full-sibs were selected by MAS.     

Temporal changes in allele frequencies in two European F2 flint maize populations under modified recurrent full-sib selection

Selection and random genetic drift are the two main forces affecting the selection response of recurrent selection (RS) programs by changes in allele frequencies. Therefore, detailed knowledge on allele frequency changes attributable to these forces is of fundamental importance for assessing RS programs. The objectives of our study were to (1) estimate the number, position, and genetic effect of quantitative trait loci (QTL) for selection index and its components in the base populations, (2) determine changes in allele frequencies of QTL regions due to the effects of random genetic drift and selection, and (3) predict allele frequency changes by using QTL results and compare these predictions with observed values. We performed QTL analyses, based on restriction fragment length polymorphisms (RFLPs) and simple sequence repeats (SSRs), in 274 F_2:3 lines of cross KW1265 × D146 (A × B) and 133 F_3:4 lines of cross D145 × KW1292 (C × D) originating from two European flint maize populations. Four (A × B) and seven (C × D) cycles of RS were analyzed with SSRs for significant allele frequency changes due to selection. Several QTL regions for selection index were detected with simple and composite interval mapping. In some of them, flanking markers showed a significant allele frequency change after the first and the final selection cycles. The correlation between observed and predicted allele frequencies was significant only in A × B. We attribute these observations mainly to (1) the high dependence of the power of QTL detection on the population size and (2) the occurrence of undetectable QTL in repulsion phase. Assessment of allele frequency changes in RS programs can be used to detect marker alleles linked to QTL regions under selection pressure. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Introgression of a major QTL from an inferior into a superior population using genomic selection

Background

Selection schemes aiming at introgressing genetic material from a donor into a recipient line may be performed by backcross-breeding programs combined with selection to preserve the favourable characteristics of the donor population. This stochastic simulation study investigated whether genomic selection can be effective in preserving a major quantitative trait locus (QTL) allele from a donor line during the backcrossing phase.

Methods

In a simulation study, two fish populations were generated: a recipient line selected for a production trait and a donor line characterized by an enhanced level of disease resistance. Both traits were polygenic, but one major QTL affecting disease resistance was segregating only within the donor line. Backcrossing was combined with three types of selection (for total merit index) among the crossbred individuals: classical selection, genomic selection using genome-wide dense marker maps, and gene-assisted genomic selection. It was assumed that production could be observed directly on the selection candidates, while disease resistance had to be inferred from tested sibs of the selection candidates.

Results

Classical selection was inefficient in preserving the target QTL through the backcrossing phase. In contrast, genomic selection (without specific knowledge of the target QTL) was usually effective in preserving the target QTL, and had higher genetic response to selection, especially for disease resistance. Compared with pure genomic selection, gene-assisted selection had an advantage with respect to disease resistance (28–40% increase in genetic gain) and acted as an extra precaution against loss of the target QTL. However, for total merit index the advantage of gene-assisted genomic selection over genomic selection was lower (4–5% increase in genetic gain).

Conclusion

Substantial differences between introgression programs using classical and genomic selection were observed, and the former was generally inferior with respect to both genetic gain and the ability to preserve the target QTL. Combining genomic selection with gene-assisted selection for the target QTL acted as an extra precaution against loss of the target QTL and gave additional genetic gain for disease resistance. However, the effect on total merit index was limited.     

Optimum contribution selection in large general tree breeding populations with an application to Scots pine

Development of selection methods that optimises selection differential subject to a constraint on the increase of inbreeding (or coancestry) in a population is an important part of breeding programmes. One such method that has received much attention in animal breeding is the optimum contribution (OC) dynamic selection method. We implemented the OC algorithm and applied it to a diallel progeny trial of Pinus sylvestris L. (Scots pine) focussing on two traits (total tree height and stem diameter). The OC method resulted in a higher increase in genetic gain (8–30%) compared to the genetic gain achieved using standard restricted selection method at the same level of coancestry constraint. Genetic merit obtained at two different levels of restriction on coancestry showed that the benefit of OC was highest when restriction was strict. At the same level of genetic merit, OC decreased coancestry with 56 and 39% for diameter and height, respectively, compared to the level of coancestry obtained using unrestricted truncation selection. Inclusion of a dominance term in the statistical model resulted in changes in contribution rank of trees with 7 and 13% for diameter and height, respectively, compared to results achieved by using a pure additive model. However, the genetic gain was higher for the pure additive model than for the model including dominance for both traits.     

不同QTL增效基因初始频率下标记辅助选择的效果

采用随机模拟方法模拟了在一个闭锁群体内连续对单个性状选择10个世代的情形。在假定选择性状受一个位于常染色体上的QTL和多基因共同控制的情况下,采用动物模型标记辅助最佳线性无偏预测方法估计个体育种值并据此进行种畜的选留,并在此基础上系统地比较了QTL增效基因初始频率对标记辅助选择效果的影响。结果表明：当群体中QTL增效基因的初始频率较低时,选择所获得的QTL基因型值的进展会更大,标记辅助选择在单位时间内可获得较大的遗传进展;此时,尽管QTL增效基因在群体中固定所需的世代数会更长一些,但其频率上升的速度却更快。而QTL增效基因初始频率的高低对群体近交增量的影响不是很大。     

Evaluation of marker-assisted selection through computer simulation

Computer simulation was used to evaluate responses to marker-assisted selection (MAS) and to compare MAS responses with those typical of phenotypic recurrent selection (PRS) in an allogamous annual crop species such as maize (Zea mays L.). Relative to PRS, MAS produced rapid responses early in the selection process; however, the rate of these responses diminished greatly within three to five cycles. The gains from MAS ranged from 44.7 to 99.5% of the maximum potential, depending on the genetic model considered. Linkage distance between markers and quantitative trait loci (QTLs) was the factor which most limited the responses from MAS. When averaged across all models considered, flanking QTLs within two marker loci produced 38% more gain than did selection based on single markers if markers were loosely-linked to a QTL (20% recombination). Flanking markers were much less advantageous when markers were closely-linked to a QTL (5% recombination), producing an advantage over single markers of only 11%. Markers were most effective in fully exploiting the genetic potential when fewer QTLs controlled the trait. Large QTL numbers exacerbated the problem of marker-QTL recombination by requiring more generations for fixation. In annual crop species, MAS may offer a primary advantage of enabling two selection cycles per year versus the 2 years per cycle required by most PRS schemes for the evaluation of testcross progeny. MAS thus appears to allow very rapid gains for the first 2–3 years of recurrent selection, after which time conventional methods might replace MAS to achieve further responses.Publication number 19, 330 of the Minnesota Agricultural Experiment Station     

Genetic architecture of a selection response in Arabidopsis thaliana

Quantitative trait locus (QTL) mapping has become an established and effective method for studying the genetic architecture of complex traits. In this report, we use a QTL mapping approach in combination with data from a large selection experiment in Arabidopsis thaliana to explore a response to selection of experimental populations with differentiated genetic backgrounds. Experimental populations with genetic backgrounds derived from ecotypes Landsberg and Niederzenz were exposed to multiple generations of fertility and viability selection. This selection resulted in phenotypic shifts in a number of life-history and fitness-related characters including early development time, flowering time, dry biomass, longevity, and fruit production. Quantitative trait loci were mapped for these traits and their positions were compared to previously characterized allele frequency changes in the experimental populations (Ungerer et al. 2003). Quantitative trait locus positions largely colocalized with genomic regions under strong and consistent selection in populations with differentiated genetic backgrounds, suggesting that alleles for these traits were selected similarly in differentiated genetic backgrounds. However, one QTL region exhibited a more variable response; being positively selected on one genetic background but apparently neutral in another. This study demonstrates how QTL mapping approaches can be combined with map-based population genetic data to study how selection acts on standing genetic variation in populations.     

性状遗传力与QTL方差对标记辅助选择效果的影响

在采用动物模型标记辅助最佳线性无偏预测方法对个体育种值进行估计的基础上,模拟了在一个闭锁群体内连续对单个性状选择10个世代的情形,并系统地比较了性状遗传力和QTL方差对标记辅助选择所获得的遗传进展、QTL增效基因频率和群体近交系数变化的影响。结果表明：在对高遗传力和QTL方差较小的性状实施标记辅助选择时,可望获得更大的遗传进展;遗传力越高,QTL方差越大,则QTL增效基因频率的上升速度越快;遗传力较高时,群体近交系数上升的速度较为缓慢,而QTL方差对群体近交系数上升速度的影响则不甚明显。结合前人关于标记辅助选择相对效率的研究结果,可以认为：当选择性状的遗传力和QTL方差为中等水平时,标记辅助选择可望获得理想的效果。     

Genomic selection for marker-assisted improvement in line crosses

Efficiency of genomic selection with low-cost genotyping in a composite line from a cross between inbred lines was evaluated for a trait with heritability 0.10 or 0.25 using a low-density marker map. With genomic selection, selection was on the sum of estimates of effects of all marker intervals across the genome, fitted either as fixed (fixed GS) or random (random GS) effects. Reponses to selection over 10 generations, starting from the F₂, were compared with standard BLUP selection. Estimates of variance for each interval were assumed independent and equal. Both GS strategies outperformed BLUP selection, especially in initial generations. Random GS outperformed fixed GS in early generations and performed slightly better than fixed GS in later generations. Random GS gave higher genetic gain when the number of marker intervals was greater (180 or 10 cM intervals), whereas fixed GS gave higher genetic gain when the number of marker intervals was low (90 or 20 cM). Including interactions between generation and marker scores in the model resulted in lower genetic gains than models without interactions. When phenotypes were available only in the F₂ for GS, treating marker scores as fixed effects led to considerably lower genetic gain than random GS. Benefits of GS over standard BLUP were lower with high heritability. Genomic selection resulted in greater response than MAS based on only significant marker intervals (standard MAS) by increasing the frequency of QTL with both large and small effects. The efficiency of genomic selection over standard MAS depends on stringency of the threshold used for QTL detection. In conclusion, genomic selection can be effective in composite lines using a sparse marker map.     

Trait-specific long-term consequences of genomic selection in beef cattle

Simulation studies allow addressing consequences of selection schemes, helping to identify effective strategies to enable genetic gain and maintain genetic diversity. The aim of this study was to evaluate the long-term impact of genomic selection (GS) in genetic progress and genetic diversity of beef cattle. Forward-in-time simulation generated a population with pattern of linkage disequilibrium close to that previously reported for real beef cattle populations. Different scenarios of GS and traditional pedigree-based BLUP (PBLUP) selection were simulated for 15 generations, mimicking selection for female reproduction and meat quality. For GS scenarios, an alternative selection criterion was simulated (wGBLUP), intended to enhance long-term gains by attributing more weight to favorable alleles with low frequency. GS allowed genetic progress up to 40% greater than PBLUP, for female reproduction and meat quality. The alternative criterion wGBLUP did not increase long-term response, although allowed reducing inbreeding rates and loss of favorable alleles. The results suggest that GS outperforms PBLUP when the selected trait is under less polygenic background and that attributing more weight to low-frequency favorable alleles can reduce inbreeding rates and loss of favorable alleles in GS.     

Allele frequency changes due to hitch-hiking in genomic selection programs

Background

Genomic selection makes it possible to reduce pedigree-based inbreeding over best linear unbiased prediction (BLUP) by increasing emphasis on own rather than family information. However, pedigree inbreeding might not accurately reflect loss of genetic variation and the true level of inbreeding due to changes in allele frequencies and hitch-hiking. This study aimed at understanding the impact of using long-term genomic selection on changes in allele frequencies, genetic variation and level of inbreeding.

Methods

Selection was performed in simulated scenarios with a population of 400 animals for 25 consecutive generations. Six genetic models were considered with different heritabilities and numbers of QTL (quantitative trait loci) affecting the trait. Four selection criteria were used, including selection on own phenotype and on estimated breeding values (EBV) derived using phenotype-BLUP, genomic BLUP and Bayesian Lasso. Changes in allele frequencies at QTL, markers and linked neutral loci were investigated for the different selection criteria and different scenarios, along with the loss of favourable alleles and the rate of inbreeding measured by pedigree and runs of homozygosity.

Results

For each selection criterion, hitch-hiking in the vicinity of the QTL appeared more extensive when accuracy of selection was higher and the number of QTL was lower. When inbreeding was measured by pedigree information, selection on genomic BLUP EBV resulted in lower levels of inbreeding than selection on phenotype BLUP EBV, but this did not always apply when inbreeding was measured by runs of homozygosity. Compared to genomic BLUP, selection on EBV from Bayesian Lasso led to less genetic drift, reduced loss of favourable alleles and more effectively controlled the rate of both pedigree and genomic inbreeding in all simulated scenarios. In addition, selection on EBV from Bayesian Lasso showed a higher selection differential for mendelian sampling terms than selection on genomic BLUP EBV.

Conclusions

Neutral variation can be shaped to a great extent by the hitch-hiking effects associated with selection, rather than just by genetic drift. When implementing long-term genomic selection, strategies for genomic control of inbreeding are essential, due to a considerable hitch-hiking effect, regardless of the method that is used for prediction of EBV.     

The effect of index selection on allele frequencies and future genetic gains when traits are correlated

The application of the selection index in the case of an additive two-trait model in which the genetic effect on each trait is determined by a finite number of loci is examined. Simulation results indicate that the direction of change in the frequency of favourable alleles is not necessarily in the positive direction at all loci when index selection is used as the basis for truncation selection. When the genetic correlation was positive (or favourable with respect to the economic weights), there was little difference (<5%) in genetic gain over 20 generations and no difference in the direction of change in allele frequencies or genetic correlation whether or not updated values for the genetic (co)variances were used in constructing the selection index. However, when the genetic correlation was negative or unfavourable, the effect of using genetic parameters which were not updated had unexpected effects on the allele frequencies and genetic correlation and reduced the genetic gain by a greater amount (< 12%).     

Two-trait selection response with marker-based assortative mating

 Marker-based assortative mating (MAM) – the mating of individuals that have similar genotypes at random marker loci – can increase selection response for a single trait by 3–8% over random mating (RM). Genetic gain is usually desired for multiple traits rather than for a single trait. My objectives in this study were to (1) compare MAM, phenotypic assortative mating (PAM), and RM of selected individuals for improving two traits and (2) determine when MAM will be most useful for improving two traits. I simulated 20 generations of selecting 32 out of 200 individuals in an F₂ population. The individuals were selected based on an index (SI) of two traits and were intermated by MAM, PAM, or RM. I studied eight genetic models that differed in three contrasts: (1) weight, number of quantitative trait loci (QTL), and heritability (h ²) for each trait; (2) linkage of QTL for each trait; and (3) trait means of the inbred parents of the F₂. For SI and the two component traits, MAM increased short-term selection response by 5–8% in six out of the eight genetic models. The MAM procedure was least effective in two genetic models, wherein the QTL for one trait were unlinked to the QTL for the other trait and the parents of the F₂ had divergent means for each trait. The loss of QTL heterozygosity was much greater with MAM than with PAM or RM. Consequently, the advantage of MAM over RM dissipated after 5–7 generations. Differences were small between selection responses with PAM and RM. The MAM procedure can enhance short-term selection response for two traits when selection is not stringent, h ² is low, and the means of the parents of the F₂ are equal for each trait. Received: 10 June 1998 / Accepted: 5 August 1998     

Most of the long-term genetic gain from optimum-contribution selection can be realised with restrictions imposed during optimisation

Background

We tested the hypothesis that optimum-contribution selection (OCS) with restrictions imposed during optimisation realises most of the long-term genetic gain realised by OCS without restrictions.

Methods

We used stochastic simulation to estimate long-term rates of genetic gain realised by breeding schemes that applied OCS without and with restrictions imposed during optimisation, where long-term refers to generations 23 to 25 (approximately). Six restrictions were imposed. Five of these removed solutions from the solution space. The sixth removed records of selection decisions made at earlier selection times. We also simulated a conventional breeding scheme with truncation selection as a reference point. Generations overlapped, selection was for a single trait, and the trait was observed for all selection candidates prior to selection.

Results

OCS with restrictions realised 67 to 99% of the additional gain realised by OCS without restrictions, where additional gain was the difference in the long-term rates of genetic gain realised by OCS without restrictions and our reference point with truncation selection. The only exceptions were those restrictions that removed all solutions near the optimum solution from the solution space and the restriction that removed records of selection decisions made at earlier selection times. Imposing these restrictions realised only −12 to 46% of the additional gain.

Conclusions

Most of the long-term genetic gain realised by OCS without restrictions can be realised by OCS with restrictions imposed during optimisation, provided the restrictions do not remove all solutions near the optimum from the solution space and do not remove records of earlier selection decisions. In breeding schemes where OCS cannot be applied optimally because of biological and logistical restrictions, OCS with restrictions provides a useful alternative. Not only does it realise most of the long-term genetic gain, OCS with restrictions enables OCS to be tailored to individual breeding schemes.     

Marker assisted selection for the improvement of two antagonistic traits under mixed inheritance

A Monte Carlo simulation was used to investigate the potential of Marker Assisted Selection (MAS) in a multiple-trait situation. Only additive effects were considered. The base population was assumed to be in linkage equilibrium and, next, the population was managed over 15 discrete generations, 10 males and 50 females were chosen out of the 100 candidates of each sex. Performance for two traits was simulated with an overall heritability of a given trait equal to 0.25 or 0.10 and the overall genetic correlation between traits was generally equal to -0.4 except in one case where it was equal to 0. The model involved one biallelic QTL, accounting for 10 or 20% of the genetic variance of a given trait, plus polygenes. Initial allelic frequencies at the QTL were generally equal to 0.5 but in one case were equal to 0.1 and 0.9. A marker with 120 different alleles in the 60 founder parents was simulated in the vicinity of the QTL. Two values of the recombination rate between these two loci were considered, 0.10 and 0.02. The genetic evaluation was based on a multiple-trait BLUP animal model, accounting (MAS) or not (conventional BLUP) for marker information. Two sets of simulations were run: (1) a "missing data"case, with males having no record for one of the traits, and (2) a "secondary trait"case, with one trait having a weight in the aggregate genotype 4 times less than the other trait and the QTL acting only on this secondary trait. In the first set, evaluation methods were found to mainly affect the accuracy of overall genetic values prediction for the trait with missing data. In comparison with BLUP, MAS led to an extra overall genetic response for the trait with missing data, which was strongly penalised under the conventional BLUP, and to a deficit in response for the other trait. This more balanced evolution of the two traits was obtained, however, at the expense of the long-term overall cumulated response for the aggregate genotype, which was 1 to 2.5% lower than the one obtained under the conventional BLUP. In the second set of simulation, in the case of low initial frequency (0.1) of the QTL allele favourable to the secondary trait, MAS was found to be substantially more efficient to avoid losing this allele than BLUP only when the QTL had a large effect and the marker was close. More benefits should be expected from MAS with more specific applications, such as early selection of animals, or by applying dynamic procedures i.e. letting the respective weights to QTL and polygenic values in the selection criterion vary across generation.