Genomic selection for maternal traits in pigs

The aim of this study was to compare alternative designs for implementation of genomic selection to improve maternal traits in pigs, with a conventional breeding scheme and a progeny testing scheme. The comparison was done through stochastic simulation of a pig population. It was assumed that selection was performed based on a trait that could be measured on females after the first litter, with a heritability of 0.1. Genomic selection increased genetic gain and reduced the rate of inbreeding, compared with conventional selection without progeny testing. Progeny testing could also increase genetic gain and decrease the rate of inbreeding, but because of the increased generation interval, the increase in annual genetic gain was only 7%. When genomic selection was applied, genetic gain was increased by 23 to 91%, depending on which and how many animals were genotyped. Genotyping dams in addition to the male selection candidates gave increased accuracy of the genomic breeding values, increased genetic gain, and decreased rate of inbreeding. To genotype 2 or 3 males from each litter, in order to perform within-litter selection, increased genetic gain 8 to 12%, compared with schemes with the same number of genotyped females but only 1 male candidate per litter. Comparing schemes with the same total number of genotyped animals revealed that genotyping more females caused a greater increase in genetic gain than genotyping more males because greater accuracy of selection was more advantageous than increasing the number of male selection candidates. When more than 1 male per litter was genotyped, and thereby included as selection candidates, rate of inbreeding increased because of coselection of full sibs. The conclusion is that genomic selection can increase genetic gain for traits that are measured on females, which includes several traits with economic importance in maternal pig breeds. Genotyping females is essential to obtain a high accuracy of selection.     

Selection strategies for dairy buffaloes: economic and genetic consequences

Buffaloes are generally raised in Brazil without milk‐recording programs, and thus without genetic evaluations of any of their traits. This study evaluated the economic impacts of three different selection strategies on buffalo populations and the evolution of genetic trends, genetic variances and inbreeding coefficients resulting from each of them. The selection strategies used were as follows: (i) random selection; (ii) phenotypic selection; and (iii) progeny testing (PT). As the numbers of herds enrolled in milk‐recording programs increased, phenotypic selection and PT strategies increased both monetary benefits and genetic trends. The extra costs of implementing milk recording (MR) and PT procedures were exceeded by the income resulting from better buffalo performance. Progeny testing is known to result in beneficial genetic trends and the use of artificial insemination promoted better distributions of genetic material into herds that were not enrolled in milk‐recording programs. Phenotypic selection and PT increased mean milk production ‐ a key factor in profitability. Inbreeding levels remained stable with phenotypic selection, even as the numbers of MR herds increased. Increases in the numbers of sires that were evaluated reduced the mean inbreeding coefficient in PT. Increasing the number of herds enrolled in milk‐recording programs resulted in increased numbers of sires needed for PT, but this did not increase the inbreeding coefficient. In summary, phenotypic selection and PT strategies appear to be economically viable for buffalo husbandry in south‐eastern Brazil under current (2007–2008) economic conditions and should be encouraged.     

Gametic gene flow method accounts for genomic imprinting

Findings within the last 15 years emphasize the possible role of genomic imprinting for trait expression in livestock species. In genetic evaluation, genomically imprinted traits can be treated by models with two different breeding values per animal; one accounts for the paternal and the other for the maternal expression pattern. Relative weighting factors for these breeding values were derived by a generalized version of the discounted gene flow method, which was extended to a gametic level to account for parent‐of‐origin effects. The gametic approach proved also useful for calculating the expected increase in inbreeding induced by one round of selection and its dynamics over time. The gametic gene flow method was applied to a hypothetical pig breeding programme. Relative weighting factors were higher for the paternally inherited genetic effect even in female selection paths, but depend on the breeding scheme heavily. The maximum medium‐term increase in inbreeding due to selection exceeded the long‐term increase in a range of 20–100%.     

Reducing inbreeding rates with a breeding circle: Theory and practice in Veluws Heideschaap

Breeding circles allow genetic management in closed populations without pedigrees. In a breeding circle, breeding is split over sub‐populations. Each sub‐population receives breeding males from a single sub‐population and supplies breeding males to one other sub‐population. Donor‐recipient combinations of sub‐populations remain the same over time. Here, we derive inbreeding levels both mathematically and by computer simulation and compare them to actual inbreeding rates derived from DNA information in a real sheep population. In Veluws Heideschaap, a breeding circle has been in operation for over 30 years. Mathematically, starting with inbreeding levels and kinships set to zero, inbreeding rates per generation (ΔF) initially were 0.29%–0.47% within flocks but later converged to 0.18% in all flocks. When, more realistically, inbreeding levels at the start were high and kinship between flocks low, inbreeding levels immediately dropped to the kinship levels between flocks and rates more gradually converged to 0.18%. In computer simulations with overlapping generations, inbreeding levels and rates followed the same pattern, but converged to a lower ΔF of 0.12%. ΔF was determined in the real population with a 12 K SNP chip in recent generations. ΔF in the real population was 0.29%, based on markers to 0.41% per generation based on heterozygosity levels. This is two to three times the theoretically derived values. These increased rates in the real population are probably due to selection and/or the presence of dominant rams siring a disproportionate number of offspring. When these were simulated, ΔF agreed better: 0.35% for selection, 0.38% for dominant rams and 0.67% for both together. The realized inbreeding rates are a warning that in a real population inbreeding rates in a breeding circle can be higher than theoretically expected due to selection and dominant rams. Without a breeding circle, however, inbreeding rates would have been even higher.     

Genotyping strategies of selection candidates in livestock breeding programmes

Benefits of genomic selection (GS) in livestock breeding operations are well known particularly where traits are sex‐limited, hard to measure, have a low heritability and/or measured later in life. Sheep and beef breeders have a higher cost:benefit ratio for GS compared to dairy. Therefore, strategies for genotyping selection candidates should be explored to maximize the economic benefit of GS. The aim of the paper was to investigate, via simulation, the additional genetic gain achieved by selecting proportions of male selection candidates to be genotyped via truncation selection. A two‐trait selection index was used that contained an easy and early‐in‐life measurement (such as post‐weaning weight) as well as a hard‐to‐measure trait (such as intra‐muscular fat). We also evaluated the optimal proportion of female selection candidates to be genotyped in breeding programmes using natural mating and/or artificial insemination (NatAI), multiple ovulation and embryo transfer (MOET) or juvenile in vitro fertilization and embryo transfer (JIVET). The final aim of the project was to investigate the total dollars spent to increase the genetic merit by one genetic standard deviation (SD) using GS and/or reproductive technologies. For NatAI and MOET breeding programmes, females were selected to have progeny by 2 years of age, while 1‐month‐old females were required for JIVET. Genomic testing the top 20% of male selection candidates achieved 80% of the maximum benefit from GS when selection of male candidates prior to genomic testing had an accuracy of 0.36, while 54% needed to be tested to get the same benefit when the prior selection accuracy was 0.11. To achieve 80% of the maximum benefit in female, selection required 66%, 47% and 56% of female selection candidates to be genotyped in NatAI, MOET and JIVET breeding programmes, respectively. While JIVET and MOET breeding programmes achieved the highest annual genetic gain, genotyping male selection candidates provides the most economical way to increase rates of genetic gain facilitated by genomic testing.     

Prediction of response to marker-assisted and genomic selection using selection index theory

Selection index methods can be used for deterministic assessment of the potential benefit of including marker information in genetic improvement programmes using marker-assisted selection (MAS). By specifying estimates of breeding values derived from marker information (M-EBV) as a correlated trait with heritability equal to 1, it was demonstrated that marker information can be incorporated in standard software for selection index predictions of response and rates of inbreeding, which requires specifying phenotypic traits and their genetic parameters. Path coefficient methods were used to derive genetic and phenotypic correlations between M-EBV and the phenotypic data. Methods were extended to multi-trait selection and to the case when M-EBV are based on high-density marker genotype data, as in genomic selection. Methods were applied to several example scenarios, which confirmed previous results that MAS substantially increases response to selection but also demonstrated that MAS can result in substantial reductions in the rates of inbreeding. Although further validation by stochastic simulation is required, the developed methodology provides an easy means of deterministically evaluating the potential benefits of MAS and to optimize selection strategies with availability of marker data.     

Selection for scrapie resistance and simultaneous restriction of inbreeding in the rare sheep breed "Mergellander"

Scrapie is a fatal infectious neurodegenerative disease for which susceptibility is associated with polymorphisms in the ovine prion protein (PrP) gene. Scrapie-eradication programmes are based on eliminating the susceptible VRQ allele and/or breeding for the resistant ARR allele. In rare breeds or breeds with a low frequency of the ARR allele this can lead to unacceptably high inbreeding rates with associated increased risk of genetic defects and inbreeding depression. The conservation status of populations with inbreeding rates (DeltaF) above 1% is considered critical. In the Dutch rare sheep breed the Mergellander animals carrying ARR alleles are closely related to one another, and could reach 1.53% when only ARR/ARR animals are used as parents. Inbreeding rates can be reduced by selecting the set of parents according to their average co-ancestry. We minimised inbreeding rates by calculating the optimal contribution of each ram and selection of ewes. This resulted in inbreeding rates of -0.17% with exclusive use of homozygous ARR rams, and -0.38% if use of heterozygous rams was allowed as well. Thus sophisticated breeding programs can prevent unacceptably high inbreeding rates when breeding for scrapie resistance.     

Optimum contribution selection using traditional best linear unbiased prediction and genomic breeding values in aquaculture breeding schemes

The aim of this study was to compare genetic gain for a traditional aquaculture sib breeding scheme with breeding values based on phenotypic data (TBLUP) with a breeding scheme with genome-wide (GW) breeding values. Both breeding schemes were closed nuclei with discrete generations modeled by stochastic simulation. Optimum contribution selection was applied to restrict pedigree-based inbreeding to either 0.5 or 1% per generation. There were 1,000 selection candidates and a sib test group of either 4,000 or 8,000 fish. The number of selected dams and sires to create full sib families in each generation was determined from the optimum contribution selection method. True breeding values for a trait were simulated by summing the number of each QTL allele and the true effect of each of the 1,000 simulated QTL. Breeding values in TBLUP were predicted from phenotypic and pedigree information, whereas genomic breeding values were computed from genetic markers whose effects were estimated using a genomic BLUP model. In generation 5, genetic gain was 70 and 74% greater for the GW scheme than for the TBLUP scheme for inbreeding rates of 0.5 and 1%. The reduction in genetic variance was, however, greater for the GW scheme than for the TBLUP scheme due to fixation of some QTL. As expected, accuracy of selection increased with increasing heritability (e.g., from 0.77 with a heritability of 0.2 to 0.87 with a heritability of 0.6 for GW, and from 0.53 and 0.58 for TBLUP in generation 5 with sib information only). When the trait was measured on the selection candidate compared with only on sibs and the heritability was 0.4, accuracy increased from 0.55 to 0.69 for TBLUP and from 0.83 to 0.86 for GW. The number of selected sires to get the desired rate of inbreeding was in general less in GW than in TBLUP and was 33 for GW and 83 for TBLUP (rate of inbreeding 1% and heritability 0.4). With truncation selection, genetic gain for the scheme with GW breeding values was nearly twice as large as a scheme with traditional BLUP breeding values. The results indicate that the benefits of applying GW breeding values compared with TBLUP are reduced when contributions are optimized. In conclusion, genetic gain in aquaculture breeding schemes with optimized contributions can increase by as much as 81% by applying genome-wide breeding values compared with traditional BLUP breeding values.     

动物模型BLUP选择效果的计算机模拟研究

在采用动物模型最佳线性无偏预测(BLUP) 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, 并系统地比较了群体规模、公母比例和性状遗传力对选择所获得的遗传进展和群体近交系数变化的影响。结果表明, 扩大育种群规模不仅可以获得更大的持续进展, 同时还可有效缓解近交系数的过快上升; 育种群中公畜比例过低时, 不仅会降低遗传进展, 群体近交系数的上升速度也会加快, 实际中应保证育种群具有一定的规模和适宜的公母比例。对高遗传力性状进行选择时, 可望获得更大的遗传进展, 同时近交系数的上升速度也会快一些。     

Correlated responses to selection for yearling or18-month weight in Angus and Hereford cattle

Correlated responses to selection for yearling (AS1 herd) or 18-month weight (AS2 herd) wereevaluated against a control (AC0 herd) in a progeny test herd using 2294 calves born in 1975–1988. A sample of privately-owned Angus bulls, available by artificial insemination (AI), were compared with them for eight liveweight or gain traits up to 18 months, with four carcass traits on steers. Cows of known pedigree in the progeny test herd were also evaluated for seven maternal traits. Other correlated responses were evaluated directly in the ACO and selection herds (three puberty traits, daily food intake, cow weight, and survival and reproduction traits).Realised genetic correlations to selection for yearling weight (AS1 herd) averaged 6% higher (forgrowth and carcass traits) than published paternal half-sib estimates, whilst those with 18-month weight (AS2 herd) were about 10% lower than with yearling weight. The sign of maternal genetic effects for live weights up to weaning varied among selection herds. Realised genetic correlations with selection weight averaged 0.51 (carcass fat depth), 0.93 (food intake), 0.16 (scrotal circumference in bulls), 0. 18 (age at puberty) and 0.37 (weight at puberty in heifers), 0.38 (cow weight, AS I herd) and 0.92 (cow weight, AS2 herd). The selection herd differences from control were not significant for cow or calf mortality or reproductive traits (6501 mating records), but tended to be negative for cow and calf death rates, and variable for overall reproductive rate.     

Stochastic simulation of Manchega sheep breed selection scheme. Impact of artificial insemination, progeny testing system and nucleus size on genetic progress and inbreeding

Manchega is a local Spanish sheep breed located in the region of Castilla la Mancha, Actually there are 0.8 million of milked ewes. The selection scheme of Manchega breed (ESROM) started in 1988, involving a selection nucleus composed by 103,887 ewes distributed in 106 flocks. Results obtained from the ESROM has been moderate in comparison with other similar European schemes. By this and other reasons, to develop a specific tool to study the ESROM system seems to be necessary.

The objectives of this work were to develop a genetic simulation model based on the ESROM real system and to study the effects on genetic progress and inbreeding level achieved from different rates of AI used, the progeny test system and the selection nucleus size.

An additive infinitesimal model was assumed for the trait 120 days Total Milk Yield (TMY). Five alternatives selection criteria (two per each group of animals to be selected), differentiated on their selection intensities, were associated to the selection of lambs for future artificial insemination rams, natural mating rams and ewes. All selection decisions were based on periodical genetic evaluations (BLUP), using an animal model with repeated measures. 60 specific cases were studied, each one with 20 replicates.

An average true genetic progress per year ranging from 1.04% to 2.10% in AI rams and 0.59% to 2.11% in ewes were observed. Results of phenotypic progress varied from 0.44% to 1.83% per year. True inbreeding levels of ewes at year 17 were between 0.218% and 1.879%.

The model used had the expected behavior. In general, the studied selection scheme had its better results (maximum genetic progress), when AI rate was equal or greater than 50%, a greater number of new rams were tested per year (75 and 44) and a selection nucleus size equal or greater than 9000 ewes (30 flocks). Selection intensity of natural mating rams had a great impact on the genetic progress, especially when the use of AI was low. The greater the nucleus size, the higher the genetic progress, but an operative scheme from around 9000 initial ewes could be established.

Results observed demonstrate the existence of some critical areas, which could be verified on the real system in order to improve their effectiveness. In this framework, the ESROM could develop two complementary strategies: to improve the selection system of Natural Mating Rams (selecting only sons of AI rams) and/or to increase the levels of AI until 50%.     

Effect of sire mating patterns on future genetic merit and inbreeding in a closed beef cattle population

Summary Alternative breeding strategies were simulated based on the population structure of the Tajima strain of Japanese Black cattle. An analysis of the population structure revealed that some sires up to 20 years of age have been used in Tajima. In addition, 95% of newborn calves were the progeny of only 20 sires, and their mating frequencies were significantly skewed. The current average inbreeding coefficient and founder genome equivalents of the strain were estimated to be 0.199 and 2.25, respectively. Average inbreeding coefficient is expected to reach 0.394 within 27 years. Thus, different breeding strategies were assessed for their effect on the level of inbreeding and average genetic merit. We compared strategies that (1) halve the sire service period, (2) double the number of mating sires and (3) lower the skewed sire mating frequency and optimize the frequency for weighted genetic merit and diversity. Reducing the service period yielded a 7.0–12.0% reduction in the rate of inbreeding while maintaining almost the same genetic gain. Increasing the number of sires resulted in a 19.3–21.3% reduction in inbreeding with a corresponding 1.6–8.4% reduction in gain. The rates of inbreeding from the optimized strategies decreased as the weight on genetic diversity increased. However, a strategy that emphasized only genetic gain yielded lower gain than other strategies because the strategy allowed only one sire to mate, resulting in reduced genetic variance and low accuracy of genetic evaluation. In contrast, a strategy with no emphasis on genetic gain when determining mating frequency resulted in reductions of 16.0% and 63.2% in genetic gain and inbreeding, respectively. The strategies examined here are easily applicable and can be expected to reduce immediate loss of genetic diversity.     

Assessing genetic gain, inbreeding, and bias attributable to different flock genetic means in alternative sheep sire referencing schemes

Flocks participating in sire referencing schemes can achieve greater genetic gains than those achievable by within-flock selection. However, requirements for joining these schemes can be prohibitive to some producers. The objectives of this study were to determine whether less restrictive schemes or schemes of shorter duration could achieve rates of gain and reduce inbreeding as efficiently as continuous sire referencing schemes (SRS) and to investigate whether bias from different genetic means could be reduced by these alternative schemes. Pedigree and performance data for a single trait with a within-flock heritability of 0.25 were simulated (50 replications) for 15 flocks with 40 to 140 ewes per flock. Founder genetic means for each flock were sampled from a normal distribution with mean 0 and SD equal to the trait's genetic SD. After 10 yr of random mating, flocks had the opportunity to join an SRS and begin selection for the simulated trait. Yearling rams were chosen as reference sires randomly from the top one-sixth of the population ranked on BLUP EBV. Every year, in each flock, 3 reference sires were mated to 10 ewes. Six sire referencing scenarios were considered, in which all flocks participated in a SRS for 1) 15 yr; 2) 5 yr before discontinuing the scheme; 3) 10 yr before discontinuing the scheme; 4) 2 out of every 3 yr; 5) 15 yr with reference sire mating by natural service; and 6) no years (no use of SRS). Ewes not mated to reference sires were mated either to their own home-bred sires exclusively or to a mixture of homebred and unrelated purchased rams of unknown merit. Genetic gain was equivalent whether the SRS used AI or natural service matings, although inbreeding was lower with natural service. Across all scenarios, genetic gain and inbreeding were greater when excess ewes were mated exclusively to homebred sires. Genetic gains without SRS were 80 to 82% lower than when the scheme operated for 15 yr, whereas inbreeding was considerably greater. Other scenarios were intermediate in both gain and inbreeding levels. In all SRS scenarios, bias in EBV attributable to differing flock genetic means rapidly decreased in the first 5 yr of sire referencing. Levels of bias did not substantially increase when flocks discontinued SRS after 5 or 10 yr, suggesting that further participation in an SRS may not be necessary to manage risk. Natural service and noncontinuous SRS are viable options to continuous AI SRS in terms of genetic gain, inbreeding, and bias reduction.     

Investigating maternal effects on production traits in Duroc pigs using animal and sire models

Variance components for production traits were estimated using different models to evaluate maternal effects. Data analysed were records from the South African pig performance testing scheme on 22 224 pigs from 18 herds, tested between 1990 and 2008. The traits analysed were backfat thickness (BFAT), test period weight gain (TPG), lifetime weight gain (LTG), test period feed conversion ratio (FCR) and age at slaughter (AGES). Data analyses were performed by REML procedures in ASREML, where random effects were successively fitted into animal and sire models to produce different models. The first animal model had one random effect, the direct genetic effects, while the additional random effects were maternal genetic and maternal permanent environmental effects. In the sire model, the random effects fitted were sire and maternal grand sire effects. The best model considered the covariance between direct and maternal genetic effects or between sire and maternal grand sire effects. Fitting maternal genetic effects into the animal model reduced total additive variance, while the total additive variance increased when maternal grand sire effects were fitted into the sire model. The correlations between direct and maternal genetic effects were all negative, indicating antagonism between these effects, hence the need to consider both effects in selection programmes. Direct genetic correlations were higher than other correlations, except for maternal genetic correlations of FCR with TPG, LTG and AGES. There has been direct genetic improvement and almost constant maternal ability in production traits as shown by trends for estimated (EBVs) and maternal breeding values (MBVs), while phenotypic trends were similar to those for EBVs. These results suggest that maternal genetic effects should be included in selection programmes for these production traits. Therefore, the animal–maternal model may be the most appropriate model to use when estimating genetic parameters for production traits in this population.     

Genomic selection strategies in dairy cattle: Strong positive interaction between use of genotypic information and intensive use of young bulls on genetic gain

We tested the following hypotheses: (i) breeding schemes with genomic selection are superior to breeding schemes without genomic selection regarding annual genetic gain of the aggregate genotype (ΔG(AG) ), annual genetic gain of the functional traits and rate of inbreeding per generation (ΔF), (ii) a positive interaction exists between the use of genotypic information and a short generation interval on ΔG(AG) and (iii) the inclusion of an indicator trait in the selection index will only result in a negligible increase in ΔG(AG) if genotypic information about the breeding goal trait is known. We examined four breeding schemes with or without genomic selection and with or without intensive use of young bulls using pseudo-genomic stochastic simulations. The breeding goal consisted of a milk production trait and a functional trait. The two breeding schemes with genomic selection resulted in higher ΔG(AG) , greater contributions of the functional trait to ΔG(AG) and lower ΔF than the two breeding schemes without genomic selection. Thus, the use of genotypic information may lead to more sustainable breeding schemes. In addition, a short generation interval increases the effect of using genotypic information on ΔG(AG) . Hence, a breeding scheme with genomic selection and with intensive use of young bulls (a turbo scheme) seems to offer the greatest potential. The third hypothesis was disproved as inclusion of genomically enhanced breeding values (GEBV) for an indicator trait in the selection index increased ΔG(AG) in the turbo scheme. Moreover, it increased the contribution of the functional trait to ΔG(AG) , and it decreased ΔF. Thus, indicator traits may still be profitable to use even when GEBV for the breeding goal traits are available.     

Effect of selection for scrapie resistance on genetic diversity in a rare and locally adapted sheep breed: The case of Sambucana

In Italy, since 2005 a breeding plan to increase scrapie resistance has been adopted. The impact of this selection on genetic diversity was assessed on Sambucana, an autochtonous sheep breed reared in southern Piedmont, by analysing the evolution of allele frequencies at different levels: PRNP (prion protein) gene, microsatellite loci on OAR13 (where PRNR maps), and microsatellite loci on other chromosomes, not subjected to selection for scrapie resistance. A total of 147 young rams, 80 born in 2004 and 67 in 2008–2009 were analysed. Evidence of diversity loss was observed for PRNP gene as a consequence of the directional selection. Diversity was affected in the immediate vicinity of PRNP but the effect on more distant loci on the same chromosome was trivial. With regard to neutral markers, lack of heterozygosis with no changeover of allele frequencies was observed suggesting an increase of inbreeding. Mating policies would be sufficient to solve these problems. A selection scheme based on genotyping rams and eliminating carriers of both susceptible and high susceptible alleles is the best way to improve natural resistance to scrapie with low costs and minimal problems in the current conservation programmes targeting rare breeds.     

Expected increases in genetic merit from using optimized contributions in two livestock populations of beef cattle and sheep

The expected benefits from optimized selection in real livestock populations were evaluated by applying dynamic selection algorithms to two livestock populations of sheep (Meatlinc) and beef cattle (Aberdeen Angus). In addition, the effects of introducing BLUP evaluations on the population structure, genetic gain, and inbreeding were investigated. The use of BLUP-EBV accelerated the rates of gain in the Meatlinc, but the effects of BLUP evaluations on Aberdeen Angus are not as evident. Although steady increases in the average coefficient of inbreeding (F) were observed, the inbreeding rates (deltaF) before and after the introduction of BLUP evaluations were not significantly different. The observed deltaF in the last generation was 1.0% for Meatlinc and 0.2% for Aberdeen Angus. The application of the dynamic selection algorithms for maximizing genetic gain at a fixed deltaF led to important expected increases in the rate of genetic gain (deltaG). When deltaF was restricted to the value observed in both populations, increments per year in deltaG of 4.6 (i.e., 17%) index units for Meatlinc and 3.5 (i.e., 30%) index units for Aberdeen Angus were found in comparison to the deltaG expected from conventional truncation BLUP selection. More relaxed constraints on deltaF allowed even higher expected increases in deltaG in both populations. This study demonstrates that the optimization tools constitute a potentially highly effective way of managing gain and inbreeding under a broad range of schemes in terms of scale and inbreeding level. No losses in genetic gain were associated with the use of dynamic optimization selection when schemes were compared at the same deltaF.     

基于基因组和系谱信息的不同选配方案效果模拟研究

基因组选配（genomic mating,GM）是利用基因组信息进行优化的选种选配,可以有效控制群体近交水平的同时实现最大化的遗传进展。但基因组选配是对群体中所有个体进行选配,这与实际的育种工作有点相悖。本研究模拟了遗传力为0.5的9 000头个体的基础群数据,每个世代根据GEBV选择30头公畜、900头母畜作为种用个体,而后使用基因组选配、同质选配、异质选配、随机交配4种不同的选配方案。其中基因组选配中分别选取遗传进展最大的解、家系间方差最大的解、近交最小的解所对应的交配方案进行选育。每种方案选育5个世代,比较其后代群体的平均GEBV、每世代的遗传进展、近交系数、遗传方差,并重复5次取平均值。结果表明,3种基因组选配方案的ΔG均显著高于随机交配和异质选配（P<0.01）,而且,选取遗传进展最大的基因组选配方案的ΔG比同质选配还高出4.3%。3种基因组选配的方案的ΔF比同质选配低22.2%~94.1%,而且选取近交最小的基因组选配方案ΔF比异质选配低11.8%。同质选配的遗传方差迅速降低,在第5世代显著低于除基因组选配中选择遗传进展最大的方案以外的所有方案（P<0.05）,3种基因组选配方案的遗传方差比同质选配高10.8%~32.2%。这表明基因组选配不仅可以获得比同质选配更高的遗传进展,同时有效的降低了近交水平,并且减缓了遗传方差降低速度,保证了一定的遗传变异。基因组选配作为一种有效的可持续育种方法,在畜禽育种中开展十分有必要。     

Optimizing female allocation to reproductive technologies considering merit,inbreeding and cost in nucleus breeding programmes with genomic selection

Female reproductive technologies such as multiple ovulation and embryo transfer (MOET) and juvenile in vitro fertilization and embryo transfer (JIVET) have been shown to accelerate genetic gain by increasing selection intensity and decreasing generation interval. Genomic selection (GS) increases the accuracy of selection of young candidates which can further accelerate genetic gain. Optimal contribution selection (OCS) is an effective method of keeping the rate of inbreeding at a sustainable level while increasing genetic merit. OCS could also be used to selectively and optimally allocate reproductive technologies in mate selection while accounting for their cost. This study uses stochastic simulation to simulate breeding programmes that use a combination of artificial insemination (AI) or natural mating (N), MOET and JIVET with GS. OCS was used to restrict inbreeding to 1.0% increase per generation and also to optimize use of reproductive technologies, considering their effect on genetic gain as well as their cost. Two Australian sheep breeding objectives were used as an example to illustrate the methodology—a terminal sire breeding objective (A) and a dual‐purpose self‐replacing breeding objective (B). The objective function used for optimization considered genetic merit, constrained inbreeding and cost of technologies where costs were offset by a premium paid to the seedstock breeder investing in female reproductive technologies. The premium was based on the cumulative discounted expression of genetic merit in the progeny of a commercial tier in the breeding programme multiplied by the proportion of that benefit received by the breeder. With breeding objective B, the highest premium of 64% paid to the breeder resulted in the highest allocation of reproductive technologies (4%–10% for MOET and 19%–54% for JIVET) and hence the highest annual genetic gain. Conversely, breeding objective A, which had a lower dollar value of the breeding objective and a maximum of 5% mating types for JIVET and zero for MOET were optimal, even when highest premiums were paid. This study highlights that the level of investment in breeding technologies to accelerate genetic gain depends on the investment of genetic improvement returned to the breeder per index point gain achieved. It also demonstrates that breeding programmes can be optimized including allocation of reproductive technologies at the individual animal level. Accounting for revenue to the breeder and cost of the technologies can facilitate more practical decision support for beef and sheep breeders.     

Marker-assisted selection for commercial crossbred performance

Several studies have shown that selection of purebreds for increased performance of their crossbred descendants under field conditions is hampered by low genetic correlations between purebred and commercial crossbred (CC) performance. Although this can be addressed by including phenotypic data from CC relatives for selection of purebreds through combined crossbred and purebred selection (CCPS), this also increases rates of inbreeding and requires comprehensive systems for collection of phenotypic data and pedigrees at the CC level. This study shows that both these limitations can be overcome with marker-assisted selection (MAS) by using estimates of the effects of markers on CC performance. To evaluate the potential benefits of CC-MAS, a model to incorporate marker information in selection strategies was developed based on selection index theory, which allows prediction of responses and rates of inbreeding by using standard deterministic selection theory. Assuming a genetic correlation between purebred and CC performance of 0.7 for a breeding program representing a terminal sire line in pigs, CC-MAS was shown to substantially increase rates of response and reduce rates of inbreeding compared with purebred selection and CCPS, with 60 CC half sibs available for each purebred selection candidate. When the accuracy of marker-based EBV was 0.6, CC-MAS resulted in 34 and 10% greater responses in CC performance than purebred selection and CCPS. Corresponding rates of inbreeding were 1.4% per generation for CC-MAS, compared with 2.1% for purebred selection and 3.0% for CCPS. For marker-based EBV with an accuracy of 0.9, CC-MAS resulted in 75 and 43% greater responses than purebred selection and CCPS, and further reduced rates of inbreeding to 1.0% per generation. Selection on marker-based EBV derived from purebred phenotypes resulted in substantially less response in CC performance than in CC-MAS. In conclusion, effective use of MAS requires estimates of the effect on CC performance, and MAS based on such estimates enables more effective selection for CC performance without the need for extensive pedigree recording and while reducing rates of inbreeding.