Accuracy of genomic breeding values in multi-breed dairy cattle populations

Background

Two key findings from genomic selection experiments are 1) the reference population used must be very large to subsequently predict accurate genomic estimated breeding values (GEBV), and 2) prediction equations derived in one breed do not predict accurate GEBV when applied to other breeds. Both findings are a problem for breeds where the number of individuals in the reference population is limited. A multi-breed reference population is a potential solution, and here we investigate the accuracies of GEBV in Holstein dairy cattle and Jersey dairy cattle when the reference population is single breed or multi-breed. The accuracies were obtained both as a function of elements of the inverse coefficient matrix and from the realised accuracies of GEBV.

Methods

Best linear unbiased prediction with a multi-breed genomic relationship matrix (GBLUP) and two Bayesian methods (BAYESA and BAYES_SSVS) which estimate individual SNP effects were used to predict GEBV for 400 and 77 young Holstein and Jersey bulls respectively, from a reference population of 781 and 287 Holstein and Jersey bulls, respectively. Genotypes of 39,048 SNP markers were used. Phenotypes in the reference population were de-regressed breeding values for production traits. For the GBLUP method, expected accuracies calculated from the diagonal of the inverse of coefficient matrix were compared to realised accuracies.

Results

When GBLUP was used, expected accuracies from a function of elements of the inverse coefficient matrix agreed reasonably well with realised accuracies calculated from the correlation between GEBV and EBV in single breed populations, but not in multi-breed populations. When the Bayesian methods were used, realised accuracies of GEBV were up to 13% higher when the multi-breed reference population was used than when a pure breed reference was used. However no consistent increase in accuracy across traits was obtained.

Conclusion

Predicting genomic breeding values using a genomic relationship matrix is an attractive approach to implement genomic selection as expected accuracies of GEBV can be readily derived. However in multi-breed populations, Bayesian approaches give higher accuracies for some traits. Finally, multi-breed reference populations will be a valuable resource to fine map QTL.     

Potential uses of cloning in breeding schemes: dairy cattle

Cloning by nuclear transfer has many potential applications in a dairy cattle breeding program. It can be used to increase the accuracy of selection and therefore the rate of genetic progress, to speed up the dissemination of the genes from animals of exceptionally high genetic merit to the commercial population, and to reproduce transgenic animals. Today, however, the main limitation of the use of cloning besides governmental regulations is its low success rate and consequently the high cost to produce an animal ready for reproduction. As a result cloning is mostly limited to the reproduction of animals of very high genetic merit or that carry genes of specific interest. Examples of this are top-ranked bulls which do not produce enough semen for the demand due to various reasons. A strategy that could be used by artificial insemination (AI) centers would be to create a bank of somatic cells for every bull entering AI facilities long before they are placed on the young sire proving program. The other use of cloning is to assist in the selection and reproduction of bull dams. Marker assisted selection (MAS) can substantially enhance the accuracy of selection for embryos or young animals without comprehensive performance records, and therefore can greatly increase the value of cloning such embryos or young animals.     

Expected early genetic gain from selection for milk yield in dairy cattle

Summary A matrix program to predict short term genetic gain from single trait selection for milk yield was developed. Rate of genetic gain was calculated as the annual change in the mean breeding value of all producing females. Several parameters sets representing various selection policies were used to examine situations pertinent to dairy populations of the United States. Approach to the asymptotic rates of genetic gain within the model varied with the choice of parameters, but even with consistent selection policies, predicted total genetic gain in the first 10 years was only half of the expected from classical theory. Considerable year to year variation in the rate of gain occurred. Early gains were more dependent on female selection decisions than gains during the steady state. In a two-phase model, the approach to the linear rate of gain in the second phase was accelerated by starting with an ongoing improvement program, but considerable delays still existed. Selection for sex- limited traits such as milk yield, which require pedigree selection and a waiting time for progeny test results reached asymptotic rates more slowly than previously assumed.     

Relationship of declines in grain consumption and milk yield to estrus in dairy cattle

A retrospective study was done to determine if a reduction in daily grain consumption or decline in daily milk yield were accurate indicators of estrus in 25 Holstein cows. A computer automatically identified all cows that left more than 10% of their daily grain allocation in the feed stall or that gave less than 85% of their most current 7-d daily average milk yeild. By retrospectively analyzing breeding records, grain refusal and milk declines were identified as either occurring in conjunction with estrus or nonestrus. Declines in grain consumption and milk yield were frequently associated with estrus, but many cows in estrus did not exhibit such declines. While such declines hold promise as estrous detection aids, it was concluded that refusals of daily grain allocation or declines in daily milk yield were not sufficiently accurate to supplant other methods of estrous detection in dairy cattle.     

Practical application of genomic selection in a doubled-haploid winter wheat breeding program

Crop improvement is a long-term, expensive institutional endeavor. Genomic selection (GS), which uses single nucleotide polymorphism (SNP) information to estimate genomic breeding values, has proven efficient to increasing genetic gain by accelerating the breeding process in animal breeding programs. As for crop improvement, with few exceptions, GS applicability remains in the evaluation of algorithm performance. In this study, we examined factors related to GS applicability in line development stage for grain yield using a hard red winter wheat (Triticum aestivum L.) doubled-haploid population. The performance of GS was evaluated in two consecutive years to predict grain yield. In general, the semi-parametric reproducing kernel Hilbert space prediction algorithm outperformed parametric genomic best linear unbiased prediction. For both parametric and semi-parametric algorithms, an upward bias in predictability was apparent in within-year cross-validation, suggesting the prerequisite of cross-year validation for a more reliable prediction. Adjusting the training population’s phenotype for genotype by environment effect had a positive impact on GS model’s predictive ability. Possibly due to marker redundancy, a selected subset of SNPs at an absolute pairwise correlation coefficient threshold value of 0.4 produced comparable results and reduced the computational burden of considering the full SNP set. Finally, in the context of an ongoing breeding and selection effort, the present study has provided a measure of confidence based on the deviation of line selection from GS results, supporting the implementation of GS in wheat variety development.     

Postpartum anestrus in dairy cattle

Fertility of the postpartum period is negatively influenced by the incidence of anestrus. The latter condition is characterized by the absence of estrous behavior, which may be an indication of suboptimal conditions (e.g., inadequate peripartum nutrition) or pathologic conditions (e.g., chronic debilitating diseases or uterine and ovarian diseases). Although initiation of ovarian follicular growth in the postpartum period is generally not affected, subsequent development (deviation) and the fate of the dominant follicle are the primary factors that affect reestablishment of ovarian cyclicity. Anestrus can be classified based on the three functional states of follicular development; that is, follicle emergence, deviation, and ovulation. Prevention of anestrus is preferable to treatment and can be achieved in part by maintaining a healthy periparturient period. To better understand the etiology of anestrus and its prevention, research is urgently needed in the following three areas: the role of peripartum disease conditions that influence reproduction, genes involved in ovulation, and the influence of proteins (e.g., leptin) that appear to be important links between metabolic signals and the neuroendocrine axis.     

Social dominance in dairy cattle

The meaning of “social dominance” and the problems associated with its use are discussed. Most problems disappear if dominance is restricted to the phenomenon that in every pair of animals one member can inhibit the behaviour of the other. The dominance order of the group is the sum of all such inhibitory relationships. Dominant animals probably have been aggressive in the past to obtain their dominant positions, but a dominant animal need not be aggressive now. Measures of the dominance position of animals in a herd should be based on observations in the particular herd, contain sufficient observations to be reliable, reflect the actual magnitude of differences between animals, and be normally distributed. The method of Beilharz and Mylrea (1963) meets these requirements. The application of this method is discussed.The dominance structure of three dairy herds near Freiburg in South West Germany were studied. None of the herds had an individual cow who was dominant over all others in the herd. Parameters of social structure varied from herd to herd. The findings are discussed in relation to differences in space per animal, manner of recruitment of young stock to the herds, presence of horns and other features. It is concluded that the dominance relationship of any pair of animals is a result of learning, with many different factors, including trivial ones, being involved in the initial serious formation of the relationship. Once learnt, dominance relationships for each pair of animals persist for a long time. While bidirectional dominance relationships are found in young animals, where none has yet accepted dominance of others, mature animals of all species of domestic livestock generally have clear unidirectional dominance relationships. The dominance order of the group may be no more than the sum of the individual relationships. Dominant animals are freer than others in attending to stimuli from outside the herd.     

Optimising multistage dairy cattle breeding schemes including genomic selection using decorrelated or optimum selection indices

Background

The prediction of the outcomes from multistage breeding schemes is especially important for the introduction of genomic selection in dairy cattle. Decorrelated selection indices can be used for the optimisation of such breeding schemes. However, they decrease the accuracy of estimated breeding values and, therefore, the genetic gain to an unforeseeable extent and have not been applied to breeding schemes with different generation intervals and selection intensities in each selection path.

Methods

A grid search was applied in order to identify optimum breeding plans to maximise the genetic gain per year in a multistage, multipath dairy cattle breeding program. In this program, different values of the accuracy of estimated genomic breeding values and of their costs per individual were applied, whereby the total breeding costs were restricted. Both decorrelated indices and optimum selection indices were used together with fast multidimensional integration algorithms to produce results.

Results

In comparison to optimum indices, the genetic gain with decorrelated indices was up to 40% less and the proportion of individuals undergoing genomic selection was different. Additionally, the interaction between selection paths was counter-intuitive and difficult to interpret. Independent of using decorrelated or optimum selection indices, genomic selection replaced traditional progeny testing when maximising the genetic gain per year, as long as the accuracy of estimated genomic breeding values was ≥ 0.45. Overall breeding costs were mainly generated in the path "dam-sire". Selecting males was still the main source of genetic gain per year.

Conclusion

Decorrelated selection indices should not be used because of misleading results and the availability of accurate and fast algorithms for exact multidimensional integration. Genomic selection is the method of choice when maximising the genetic gain per year but genotyping females may not allow for a reduction in overall breeding costs. Furthermore, the economic justification of genotyping females remains questionable.     

Simulation study on the efficiencies of MOET nucleus breeding schemes applying marker assisted selection in dairy cattle

Advantages of breeding schemes using genetic marker information and/or multiple ovulation and embryo transfer (MOET) technology over the traditional approach were extensively evaluated through simulation. Milk yield was the trait of interest and QTL was the genetic marker utilized. Eight dairy cattle breeding scenarios were considered, i.e., traditional progeny testing breeding scheme (denoted as STANPT), GASPT scheme including a pre-selection of young bulls entering progeny testing based on their own QTL information, MOETPT scheme using MOET technology to generate young bulls and a selection of young bulls limited within the full-sib family, GAMOPT scheme adopting both QTL pre-selection and MOET technology, COMBPT scheme using a mixed linear model which considered QTL genotype instead of the BLUP model in GAMOPT, and three non-progeny testing schemes, i.e. the MOET, GAMO and COMB schemes, corresponding to MOETPT, GAMOPT and COMBPT with progeny testing being part of the system. Animals were selected based on their breeding value which was estimated under an animal model framework. Sequential selection over 17 years was performed in the simulations and 30 replicates were designed for each scenario. The influences of using QTL information and MOET technology on favorable QTL allele frequency, true breeding values, polygenetic breeding values and the accumulated genetic superiority were extensively evaluated, for five different populations including active sires, lactating cows, bull dams, bull sires, and young bulls. The results showed that the combined schemes significantly outperformed other approaches wherein accumulated true breeding value progressed. The difference between schemes exclusively using QTL information or MOET technology was not significant. The STANPT scheme was the least efficient among the 8 schemes. The schemes using MOET technology had a higher polygenetic response than others in the 17th year. The increases of frequency of the favorable QTL allele varied more greatly across the 3 male groups than in the lactating cows group. The accumulated genetic superiorities of the GASPT scheme, MOETPT scheme, GAMOPT scheme, COMBPT scheme, MOET scheme, GAMO scheme and COMB scheme over the STANPT scheme were 8.42%, 3.59%, 14.58%, 18.54%, 4.12%, 14.12%, 16.50% in active sires and 2.70%, 5.00%, 11.05%, 12.78%, 7.51%, 17.12%, 25.38% in lactating cows. Supported by Key Project for Introducing Advanced International Agriculture Science & Technologies (Grant No. 2006-G48), the National Key Basic Research and Development Program of China (Grant No. 2006CB102107) and National Key Technology Research and Development Program of China (Grant No. 2006BAD04A01).     

Hoof overgrowth in Holstein--Friesian dairy cattle

The genetic etiology of hoof overgrowth, a widespread problem in Holstein-Friesian cattle, was examined. Although all four feet are affected, the hind feet usually have a greater degree of overgrowth. There is a distinct age tendency for the trait; the younger cows' hooves grow faster than those of the older cows, but the overgrowth in older cows reaches greater proportions. Analysis of variance of chi-square frequency tests showed that there is a component of heritability involved in the expression of the trait, but that it follows a more complex model than a simple autosomal recessive gene would show.     

Inheritance of UMP synthase in dairy cattle

The inheritance of uridine-5'-monophosphate (UMP) synthase in dairy cattle was consistent with a two-allele, single-autosomal-locus model. Two phenotypes were associated with different levels of the enzyme in bovine erythrocytes. The predominant phenotype (assumed normal) had twice the concentration of UMP synthase as the second phenotype (deficient). A one-to-one correspondence between enzyme level and genotype identified one homozygote as normal, the heterozygote as deficient, and the other homozygote as unobserved. Three alternative hypotheses were rejected. The deficiency as homozygous recessive was rejected because 20 matings between assumed normal males and deficient females resulted in 10 normal and 10 deficient offspring. The hypothesis that the deficiency was homozygous dominant was rejected because the 95 percent confidence interval about the observed gene frequency, 0.0024 to 0.0146, did not contain the estimated gene frequency for equilibrium between an average 10(-5) mutation rate and selection against the deficiency as homozygous dominant. Analyses of female relatives implicated one bull as deficient (96 percent probability), as he had, independently, 2 deficient daughters, 5 deficient granddaughters from untested dams, and 3 deficient great-granddaughters from untested ancestors. The hypothesis that the deficiency was sex-linked was rejected because 3 of 9 tested sons of the putative deficient bull were deficient. Calf mortality is expected in 25 percent of matings between deficient animals.     

Serum post-albumins and fertility in dairy cattle

Blood samples from 180 Guernsey cows and 599 Holstein cows were typed for post-albumins (Poa). The genotypes were compared for breeding efficiency, mean return interval, anestrus interval, service interval, gestation length and lactation length. Poa SF cows had a significantly shorter (P < 0.01) mean return interval than SS cows. The effect is associated with order of insemination, but is independent of lactation number. None of the other parameters showed genotypic differences.     

Factors affecting gestation length in dairy cattle

Data were collected through a special record keeping system for 2,254 herds that used artificial insemination, 37% of which were enrolled in Dairy Herd Improvement Associations. Information was available on a total of 35,162 gestations, consisting of 24,367 Holstein, 5,849 Guernsey, 2,872 Jersey, 1,667 Ayrshire and 407 Brown Swiss pregnancies resulting in single births plus 930 multiple births. Breeds, twinning, sex of calf, parity of the cow and time of day on which estrus occurred were associated with differences in gestation length. Month of insemination had no effect. Mates and sires of the cows both affected gestation length slightly, but significantly. Selection of sires for high milk production of their daughters over a 23-year period appears to have had little, if any, effect on gestation length, as the mean gestation length has increased only one day, from 278 to 279 days for Holsteins during that time.