Non-random mating for selection with restricted rates of inbreeding and overlapping generations

Minimum coancestry mating with a maximum of one offspring per mating pair (MC1) is compared with random mating schemes for populations with overlapping generations. Optimum contribution selection is used, whereby ΔF is restricted. For schemes with ΔF restricted to 0.25% per year, 256 animals born per year and heritability of 0.25, genetic gain increased with 18% compared with random mating. The effect of MC1 on genetic gain decreased for larger schemes and schemes with a less stringent restriction on inbreeding. Breeding schemes hardly changed when omitting the iteration on the generation interval to find an optimum distribution of parents over age-classes, which saves computer time, but inbreeding and genetic merit fluctuated more before the schemes had reached a steady-state. When bulls were progeny tested, these progeny tested bulls were selected instead of the young bulls, which led to increased generation intervals, increased selection intensity of bulls and increased genetic gain (35% compared to a scheme without progeny testing for random mating). The effect of MC1 decreased for schemes with progeny testing. MC1 mating increased genetic gain from 11–18% for overlapping and 1–4% for discrete generations, when comparing schemes with similar genetic gain and size.     

Mating schemes for optimum contribution selection with constrained rates of inbreeding

The effect of non-random mating on genetic response was compared for populations with discrete generations. Mating followed a selection step where the average coancestry of selected animals was constrained, while genetic response was maximised. Minimum coancestry (MC), Minimum coancestry with a maximum of one offspring per mating pair (MC1) and Minimum variance of the relationships of offspring (MVRO) mating schemes resulted in a delay in inbreeding of about two generations compared with Random, Random factorial and Compensatory mating. In these breeding schemes where selection constrains the rate of inbreeding, ΔF, the improved family structure due to non-random mating increased genetic response. For schemes with ΔF constrained to 1.0% and 100 selection candidates, genetic response was 22% higher for the MC1 and MVRO schemes compared with Random mating schemes. For schemes with a less stringent constraint on ΔF or more selection candidates, the superiority of the MC1 and MVRO schemes was smaller (5–6%). In general, MC1 seemed to be the preferred mating method, since it almost always yielded the highest genetic response. MC1 mainly achieved these high genetic responses by avoiding extreme relationships among the offspring, i.e. fullsib offspring are avoided, and by making the contributions of ancestors to offspring more equal by mating least related animals.     

Optimal mass selection policies for schemes with overlapping generations and restricted inbreeding

Optimum breeding schemes for maximising the rate of genetic progress with a restriction on the rate of inbreeding (per year or per generation) are investigated for populations with overlapping generations undergoing mass selection. The optimisation is for the numbers of males and females to be selected and for their distribution over age classes. Expected rates of genetic progress (ΔG) are combined with expected rates of inbreeding (ΔF) in a linear objective function (Φ = ΔG - λΔF) which is maximised. A simulated annealing algorithm is used to obtain the solutions. The restriction on inbreeding is achieved by increasing the number of parents and, in small schemes with severe restrictions, by increasing the generation interval. In the latter case the optimum strategy for obtaining the maximum genetic gain is far from truncation selection across age classes. In most situations, the optimum mating ratio is one but the differences in genetic gain obtained with different mating ratios are small. Optimisation of schemes when restricting the rate of inbreeding per generation leads to shorter generation intervals than optimisation when restricting the rate of inbreeding per year.     

A combination of walk-back and optimum contribution selection in fish: a simulation study

The aim of this paper was to study the performance of a novel fish breeding scheme, which is a combination of walk-back and optimum contribution selection using stochastic simulation. In this walk-back selection scheme, batches of different sizes (50, 100, 1000, 5000 and 10 000) with the phenotypically superior fish from one tank with mixed families were genotyped to set up the pedigree. BLUP estimated breeding values were calculated. The optimum contribution selection method was used with the rate of inbreeding (ΔF) constrained to 0.005 or 0.01 per generation. If the constraint on ΔF could not be held, a second batch of fish was genotyped etc. Compared with the genotyping of all selection candidates (1000, 5000 or 10 000), the use of batches saves genotyping costs. The results show that two batches of 50 fish were often necessary. With a batch size of 100, genetic level was 76–92% of the genetic level achieved for schemes with all fish being genotyped and thus candidates for the optimum contribution selection step. More parents were selected for schemes with larger batches, resulting in a higher genetic gain, especially when all selection candidates were genotyped. There was little extra genetic gain in genotyping of 1000 fish instead of 100 for the larger schemes of 5000 and 10 000 candidates. The accuracy of breeding values was similar for all batch sizes (~0.30), but higher (~0.5) when all candidates were included. Since only the phenotypically most superior fish were genotyped, BLUP-EBV were biased. Compared with genotyping of all selection candidates, the use of batches saves genotyping costs, while simultaneously maintaining high genetic gains.     

The advantage of factorial mating under selection is uncovered by deterministically predicted rates of inbreeding

Rates of inbreeding (ΔF) in selected populations were predicted using the framework of long-term genetic contributions and validated against stochastic simulations. Deterministic predictions decomposed ΔF into four components due to: finite population size, directional selection, covariance of genetic contribution of mates, and deviation of variance of family size from that expected from a Poisson distribution. Factorial (FM) and hierarchical (HM) mating systems were compared under mass and sib-index selection. Prediction errors were in most cases for ΔF less than 10% and for rate of gain less than 5%. ΔF was higher with index than mass selection. ΔF was lower with FM than HM in all cases except random selection. FM reduced the variance of the average breeding value of the mates of an individual. This reduced the impact of the covariance of contributions of mates on ΔF. Thus, contributions of mates were less correlated with FM than HM, causing smaller deviations of converged contributions from the optimum contributions. With index selection, FM also caused a smaller variance of number of offspring selected from each parent. This reduced variance of family size reduced ΔF further. FM increases the flexibility in breeding schemes for achieving the optimum genetic contributions.     

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.     

Systematic differences in the response of genetic variation to pedigree and genome-based selection methods

Genomic selection (GS) is a DNA-based method of selecting for quantitative traits in animal and plant breeding, and offers a potentially superior alternative to traditional breeding methods that rely on pedigree and phenotype information. Using a 60 K SNP chip with markers spaced throughout the entire chicken genome, we compared the impact of GS and traditional BLUP (best linear unbiased prediction) selection methods applied side-by-side in three different lines of egg-laying chickens. Differences were demonstrated between methods, both at the level and genomic distribution of allele frequency changes. In all three lines, the average allele frequency changes were larger with GS, 0.056 0.064 and 0.066, compared with BLUP, 0.044, 0.045 and 0.036 for lines B1, B2 and W1, respectively. With BLUP, 35 selected regions (empirical P<0.05) were identified across the three lines. With GS, 70 selected regions were identified. Empirical thresholds for local allele frequency changes were determined from gene dropping, and differed considerably between GS (0.167–0.198) and BLUP (0.105–0.126). Between lines, the genomic regions with large changes in allele frequencies showed limited overlap. Our results show that GS applies selection pressure much more locally than BLUP, resulting in larger allele frequency changes. With these results, novel insights into the nature of selection on quantitative traits have been gained and important questions regarding the long-term impact of GS are raised. The rapid changes to a part of the genetic architecture, while another part may not be selected, at least in the short term, require careful consideration, especially when selection occurs before phenotypes are observed.     

The Geographic Spread of the CCR5 Δ32 HIV-Resistance Allele

The Δ32 mutation at the CCR5 locus is a well-studied example of natural selection acting in humans. The mutation is found principally in Europe and western Asia, with higher frequencies generally in the north. Homozygous carriers of the Δ32 mutation are resistant to HIV-1 infection because the mutation prevents functional expression of the CCR5 chemokine receptor normally used by HIV-1 to enter CD4+ T cells. HIV has emerged only recently, but population genetic data strongly suggest Δ32 has been under intense selection for much of its evolutionary history. To understand how selection and dispersal have interacted during the history of the Δ32 allele, we implemented a spatially explicit model of the spread of Δ32. The model includes the effects of sampling, which we show can give rise to local peaks in observed allele frequencies. In addition, we show that with modest gradients in selection intensity, the origin of the Δ32 allele may be relatively far from the current areas of highest allele frequency. The geographic distribution of the Δ32 allele is consistent with previous reports of a strong selective advantage (>10%) for Δ32 carriers and of dispersal over relatively long distances (>100 km/generation). When selection is assumed to be uniform across Europe and western Asia, we find support for a northern European origin and long-range dispersal consistent with the Viking-mediated dispersal of Δ32 proposed by G. Lucotte and G. Mercier. However, when we allow for gradients in selection intensity, we estimate the origin to be outside of northern Europe and selection intensities to be strongest in the northwest. Our results describe the evolutionary history of the Δ32 allele and establish a general methodology for studying the geographic distribution of selected alleles.     

Mutations Affecting Donor Preference during Mating Type Interconversion in Saccharomyces Cerevisiae

Homothallic strains of Saccharomyces cerevisiae can convert mating type from a to α or α to a as often as every generation, by replacing genetic information specifying one mating type at the expressor locus, MAT, with information specifying the opposite mating type. The cryptic mating type information that is copied and inserted at MAT is contained in either of two loci, HML or HMR. The particular locus selected as donor during mating type interconversion is regulated by the allele expressed at MAT. MATa cells usually select HML, and MATα cells usually select HMR, a process referred to as donor preference. To identify factors required for donor preference, we isolated and characterized a number of mutants that frequently selected the nonpreferred donor locus during mating type interconversion. Many of these mutants were found to harbor chromosome rearrangements or mutations at MAT or HML that interfered with the switching process. However, one mutant carried a recessive allele of CHL1, a gene previously shown to be required for efficient chromosome segregation during mitosis. Homothallic strains of yeast containing a null allele of CHL1 exhibited almost random selection of the donor locus in a MATa background but were normal in their ability to select HMR in a MATα background. Our results indicate that Chl1p participates in the process of donor selection and are consistent with a model in which Chl1p helps establish an intrinsic bias in donor preference.     

The Case for Selection at CCR5-Δ32

The C-C chemokine receptor 5, 32 base-pair deletion (CCR5-Δ32) allele confers strong resistance to infection by the AIDS virus HIV. Previous studies have suggested that CCR5-Δ32 arose within the past 1,000 y and rose to its present high frequency (5%–14%) in Europe as a result of strong positive selection, perhaps by such selective agents as the bubonic plague or smallpox during the Middle Ages. This hypothesis was based on several lines of evidence, including the absence of the allele outside of Europe and long-range linkage disequilibrium at the locus. We reevaluated this evidence with the benefit of much denser genetic maps and extensive control data. We find that the pattern of genetic variation at CCR5-Δ32 does not stand out as exceptional relative to other loci across the genome. Moreover using newer genetic maps, we estimated that the CCR5-Δ32 allele is likely to have arisen more than 5,000 y ago. While such results can not rule out the possibility that some selection may have occurred at C-C chemokine receptor 5 (CCR5), they imply that the pattern of genetic variation seen atCCR5-Δ32 is consistent with neutral evolution. More broadly, the results have general implications for the design of future studies to detect the signs of positive selection in the human genome.     

Improving the analysis of low heritability complex traits for enhanced genetic gain in potato

Key message

Best linear unbiased prediction (BLUP), which uses pedigree to estimate breeding values, can result in increased genetic gains for low heritability traits in autotetraploid potato.

Abstract

Conventional potato breeding strategies, based on outcrossing followed by phenotypic recurrent selection over a number of generations, can result in slow but steady improvements of traits with moderate to high heritability. However, faster gains, particularly for low heritability traits, could be made by selection on estimated breeding values (EBVs) calculated using more complete pedigree information in best linear unbiased prediction (BLUP) analysis. One complication in applying BLUP predictions of breeding value to potato breeding programs is the autotetraploid inheritance pattern of this species. Here we have used a large pedigree, dating back to 1908, to estimate heritability for nine key traits for potato breeding, modelling autotetraploid inheritance. We estimate the proportion of double reduction in potatoes from our data, and across traits, to be in the order of 10 %. Estimates of heritability ranged from 0.21 for breeder’s visual preference, 0.58 for tuber yield, to 0.83 for plant maturity. Using the accuracies of the EBVs determined by cross generational validation, we model the genetic gain that could be achieved by selection of genotypes for breeding on BLUP EBVs and demonstrate that gains can be greater than in conventional schemes.     

Designing artificial selection experiments for specific objectives

The observed genetic gain (ΔP) from selection in a finite population is the possible expected genetic gain E(Δ G) minus the difference in inbreeding depression effects in the selected and control lines. The inbreeding depression can be avoided by crossing the control and selected ♂ and ♀ parents to unrelated mates and summing the observed gains. The possible expected gain will be reduced by an amount D from the predicted gain because of the effects of the genetic limit and random genetic drift, the magnitude of which is a function of effective population size, N. The expected value of D is zero in unselected control populations and in the first generation for selected populations. Therefore, this source of bias can be reduced by increasing N in the selected populations and can be avoided by selecting for a single generation. To obtain observed responses which are unbiased estimates of the predicted response from which to estimate the realized heritability (or regression) in the zero generation, or to test genetic theory based on infinite population size, single-generation selection with many replications would be most efficient. To measure the "total" effect or genetic efficiency of a selection criterion or method, including the effect of different selection intensities, effective population sizes, and space requirements, more than one generation of selection is required to estimate the expected response in breeding values. The efficiency, in the sense of minimum variance, of estimating the expected breeding values at any generation t will decline as the number of generations t increases. The variance of either the estimated mean gain or the regression of gain on selection differential can be reduced more by increasing the number of replicates K than by increasing the number of generations t. Also the general pattern of the response over t can be estimated if the N's are known. Therefore, two- or not more than three-generation selection experiments with many replications would be most efficient.     

Mitochondrial membrane potential: a trait involved in organelle inheritance?

Which mitochondria are inherited across generations? Are transmitted mitochondria functionally silenced to preserve the integrity of their genetic information, or rather are those mitochondria with the highest levels of function (as indicated by membrane potential Δψm) preferentially transmitted? Based on observations of the unusual system of doubly uniparental inheritance of mitochondria and of the common strictly maternal inheritance mode, I formulate a general hypothesis to explain which mitochondria reach the primordial germ cells (PGCs), and how this happens. Several studies indicate that mitochondrial movements are driven by microtubules and that mitochondria with high Δψm are preferentially transported. This can be applied also to the mitochondria that eventually populate embryonic PGCs, so I propose that Δψm may be a trait that allows for the preferential transmission of the most active (and healthy) mitochondria. The topics discussed here are fundamental in cell biology and genetics but remain controversial and a subject of heated debate; I propose an explanation for how a Δψm-dependent mechanism can cause the observed differences in mitochondrial transmission.     

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.     

Detecting Selection on Temporal and Spatial Scales: A Genomic Time-Series Assessment of Selective Responses to Devil Facial Tumor Disease

Detecting loci under selection is an important task in evolutionary biology. In conservation genetics detecting selection is key to investigating adaptation to the spread of infectious disease. Loci under selection can be detected on a spatial scale, accounting for differences in demographic history among populations, or on a temporal scale, tracing changes in allele frequencies over time. Here we use these two approaches to investigate selective responses to the spread of an infectious cancer—devil facial tumor disease (DFTD)—that since 1996 has ravaged the Tasmanian devil (Sarcophilus harrisii). Using time-series ‘restriction site associated DNA’ (RAD) markers from populations pre- and post DFTD arrival, and DFTD free populations, we infer loci under selection due to DFTD and investigate signatures of selection that are incongruent among methods, populations, and times. The lack of congruence among populations influenced by DFTD with respect to inferred loci under selection, and the direction of that selection, fail to implicate a consistent selective role for DFTD. Instead genetic drift is more likely driving the observed allele frequency changes over time. Our study illustrates the importance of applying methods with different performance optima e.g. accounting for population structure and background selection, and assessing congruence of the results.     

csi2p modulates microtubule dynamics and organizes the bipolar spindle for chromosome segregation

Proper chromosome segregation is of paramount importance for proper genetic inheritance. Defects in chromosome segregation can lead to aneuploidy, which is a hallmark of cancer cells. Eukaryotic chromosome segregation is accomplished by the bipolar spindle. Additional mechanisms, such as the spindle assembly checkpoint and centromere positioning, further help to ensure complete segregation fidelity. Here we present the fission yeast csi2⁺. csi2p localizes to the spindle poles, where it regulates mitotic microtubule dynamics, bipolar spindle formation, and subsequent chromosome segregation. csi2 deletion (csi2Δ) results in abnormally long mitotic microtubules, high rate of transient monopolar spindles, and subsequent high rate of chromosome segregation defects. Because csi2Δ has multiple phenotypes, it enables estimates of the relative contribution of the different mechanisms to the overall chromosome segregation process. Centromere positioning, microtubule dynamics, and bipolar spindle formation can all contribute to chromosome segregation. However, the major determinant of chromosome segregation defects in fission yeast may be microtubule dynamic defects.     

Selection responses for the number of fertile eggs of the Brown Tsaiya duck (Anas platyrhynchos) after a single artificial insemination with pooled Muscovy (Cairina moschata) semen

A seven-generation selection experiment comprising a selected (S) and a control (C) line was conducted with the objective of increasing the number of fertile eggs (F) of the Brown Tsaiya duck after a single artificial insemination (AI) with pooled Muscovy semen. Both lines consisted of about 20 males and 60 females since parents in each generation and each female duck was tested 3 times, at 26, 29 and 32 weeks of age. The fertile eggs were measured by candling at day 7 of incubation. The selection criterion in the S line was the BLUP animal model value for F. On average, 24.7% of the females and 15% of the males were selected. The direct responses to the selection for F, and correlated responses for the number of eggs set (Ie), the number of total dead embryos (M), the maximum duration of fertility (Dm) and the number of hatched mule ducklings (H) were measured by studying the differences across the generations of selection between the phenotypic value averages in the S and C lines. The predicted genetic responses were calculated by studying the differences between the S and C lines in averaged values of five traits of the BLUP animal model. The selection responses and the predicted responses showed similar trends. There was no genetic change for Ie. After seven generations of selection, the average selection responses per generation were 0.40, 0.33, 0.42, 0.41 genetic standard deviation units for F, M, Dm, and H respectively. Embryo viability was not impaired by this selection. For days 2–8 after AI, the fertility rates (F/Ie) were 89.2% and 63.8%, the hatchability rates (H/F) were 72.5% and 70.6%, and (H/Ie) were 64.7% and 45.1% in the S and C lines respectively. It was concluded that upward selection on the number of fertile eggs after a single AI with pooled Muscovy semen may be effective in ducks to increase the duration of the fertile period and the fertility and hatchability rates with AI once a week instead of twice a week.     

Optimizing Selection on Multiple Identified Quantitative Trait Loci in Population with Overlapping Generations

A method was developed to model and optimize selection on multiple identified quantitative trait loci (QTLs) and polygenic estimated breeding value, in order to maximize a weighted sum of cumulative response to selection over multiple years in a population with overlapping generations. The model allows for a population with multiple sex-age classes, different number of age class between sires and dams, and varied genetic contribution of the age class. The optimization problem was formulated as a multiple-stage optimal control problem and solved by a forward and backward iteration loop. The practical utility of this method was illustrated in an example of pig breeding population with overlapping generations. The selection response of this method was compared with standard QTL selection and conventional best linear unbiased prediction (BLUP) selection. Simulation results show that optimal selection achieved greater selection response than either standard QTL or conventional BLUP selections. The influence of population structure on optimal selection was significant. Optimal QTL selection and standard QTL selection were more favorable in a population with overlapping generations than discrete generations, and obtained more benefits relative to conventional BLUP selection in a population with overlapping generations. Optimal QTL selection relative to conventional BLUP selection is also more favorable following increase of genetic contribution of two-year-old boars and sows in a population with overlapping generations.     

Best linear unbiased prediction and optimum allocation of test resources in maize breeding with doubled haploids

With best linear unbiased prediction (BLUP), information from genetically related candidates is combined to obtain more precise estimates of genotypic values of test candidates and thereby increase progress from selection. We developed and applied theory and Monte Carlo simulations implementing BLUP in 2 two-stage maize breeding schemes and various selection strategies. Our objectives were to (1) derive analytical solutions of the mixed model equations under two breeding schemes, (2) determine the optimum allocation of test resources with BLUP under different assumptions regarding the variance component ratios for grain yield in maize, (3) compare the progress from selection using BLUP and conventional phenotypic selection based on mean performance solely of the candidates, and (4) analyze the potential of BLUP for further improving the progress from selection. The breeding schemes involved selection for testcross performance either of DH lines at both stages (DHTC) or of S₁ families at the first stage and DH lines at the second stage (S₁TC-DHTC). Our analytical solutions allowed much faster calculations of the optimum allocations and superseded matrix inversions to solve the mixed model equations. Compared to conventional phenotypic selection, the progress from selection was slightly higher with BLUP for both optimization criteria, namely the selection gain and the probability to select the best genotypes. The optimum allocation of test resources in S₁TC-DHTC involved ≥10 test locations at both stages, a low number of crosses (≤6) each with 100–300 S₁ families at the first stage, and 500–1,000 DH lines at the second stage. In breeding scheme DHTC, the optimum number of test candidates at the first stage was 5–10 times larger, whereas the number of test locations at the first stage and the number of test candidates at the second stage were strongly reduced compared to S₁TC-DHTC.     

世代重叠群体多个QTL最优化选择

一种扩展的方法能够在一个世代重叠的群体内对多个数量性状位点选择进行最优化,目的是为了在整个计划期内获得最大的累积反应加权和。该模型允许群体有多个性别年龄组、公母畜间有不同的年龄组数、各年龄组有不同的遗传贡献。整个最优化问题被描述成一个多阶段系统优化控制问题,通过一个向前和向后的迭代循环解决。用一个世代重叠的实际育种猪群的参数来评价该方法的选择效果,并和标准QTL选择和常规BLUP选择进行比较。模拟结果表明,优化选择要优于标准QTL选择和常规BLUP选择。群体结构对优化选择的影响比较明显。优化QTL选择和标准QTL选择在世代重叠的群体内比在世代离散的群体内的选择优势更明显,相对于常规BLUP选择,能够获得更大的选择优势。在世代重叠群体内随着2岁公畜遗传贡献的增大,优化选择相对于常规BLUP选择的优势越明显。