Genetic gains from reciprocal recurrent and within-line selection for egg production in the fowl

Summary Selection for survivors percent egg production from first egg to 40 weeks of age was conducted for six generations. Within-line selection (WLS) on the basis of an index of individual records plus sire family and dam family means was compared with reciprocal recurrent selection (RRS) based on sire family selection among cross progeny. Genetically heterogeneous synthetic populations, the Cornell Control and the Purdue Pool strains were used.The responses to WLS (3.84 °) and RRS (2.57 °) were both significantly greater than zero, but were not significantly different from each other. Nevertheless, the responses were proportional to their predicted values (.363 vs. 340). The advantage of WLS was due to the mechanics of selection resulting in slightly greater selection intensity and an increased correlation between the criterion of selection and the trait being improved. On the contrary, the RRS method had a slightly larger realized heritability as would be expected in the presence of non-additive genetic variance. Four of five pure-lines selected under both methods had statistically significant declines in performance due to inbreeding depression effects. All of the results observed are comparable with known genetic theory.Some problems in comparing genetic gains from different selection methods or selection criteria are discussed.Journal Paper No. 4986 of the Purdue University Agricultural Experiment Station. Conducted in cooperation with the Regional Poultry Breeding Laboratory, Project N. C. 89. Supported in part by N. I. H. Grant No. ES00310.     

Theoretical Modifications of Reciprocal Recurrent Selection

Reciprocal recurrent selection (RRS), which assumes overdominant loci to be important, alters two genetically different populations to improve their crossbred mean. Individual plants from two populations (A and B) are selfed and also crossed with plants from the reciprocal female tester population (B and A, respectively). Selection is based on the mean of crossbred families, and the selected individuals are randomly mated within A and B to form new populations.—We propose two alternatives to RRS. The first (RRS-I) uses, as the tester of population A, a population (LB) that is derived from population B by family selection for low yield. The second (RRS-II) is similar to RRS-I, but also uses, as the tester of B, a population (LA) that is derived from population A by family selection for low yield.—The expected crossbred means of RRS, RRS-I, and RRS-II were compared, assuming equal σP, at several cycles of selection for incomplete and complete dominance, and for several cases of overdominance (depending on the gene frequencies in A and B, and on the equilibrium gene frequency).—The choice of selection method depends on the importance of the effects of overdominant loci compared to loci exhibiting incomplete or complete dominance. If overdominance is unimportant, RRS-II is the best selection method, followed by RRS-I and RRS. If overdominance is important, both RRS and RRS-I are superior to RRS-II; RRS is preferred to RRS-I if the effects of overdominant loci are sufficiently important. If the genetic model is a mixture of levels of dominance at different loci, a combination of selection systems is suggested.     

Maximizing crossbred performance through purebred genomic selection

Background

In livestock production, many animals are crossbred, with two distinct advantages: heterosis and breed complementarity. Genomic selection (GS) can be used to select purebred parental lines for crossbred performance (CP). Dominance being the likely genetic basis of heterosis, explicitly including dominance in the GS model may be an advantage to select purebreds for CP. Estimated breeding values for CP can be calculated from additive and dominance effects of alleles that are estimated using pure line data. The objective of this simulation study was to investigate the benefits of applying GS to select purebred animals for CP, based on purebred phenotypic and genotypic information. A second objective was to compare the use of two separate pure line reference populations to that of a single reference population that combines both pure lines. These objectives were investigated under two conditions, i.e. either a low or a high correlation of linkage disequilibrium (LD) phase between the pure lines.

Results

The results demonstrate that the gain in CP was higher when parental lines were selected for CP, rather than purebred performance, both with a low and a high correlation of LD phase. For a low correlation of LD phase between the pure lines, the use of two separate reference populations yielded a higher gain in CP than use of a single reference population that combines both pure lines. However, for a high correlation of LD phase, marker effects that were estimated using a single combined reference population increased the gain in CP.

Conclusions

Under the hypothesis that performance of crossbred animals differs from that of purebred animals due to dominance, a dominance model can be used for GS of purebred individuals for CP, without using crossbred data. Furthermore, if the correlation of LD phase between pure lines is high, accuracy of selection can be increased by combining the two pure lines into a single reference population to estimate marker effects.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-015-0099-3) contains supplementary material, which is available to authorized users.     

Estimation of additive genetic variance in commercial layer poultry and simulated populations under selection

Changes in genetic parameters over generations for a selected commercial population and simulated populations of poultry with different sizes were studied. The traits analyzed from the commercial population were rate of lay, age at first egg, egg weight, deformation, and body weight. In the simulated population, a trait measured on both sexes and a sex-limited trait, measured only on one sex, each with a heritability of 0.1 and 0.5, were analyzed. In the commercial and simulated populations, males and females were selected on the basis of family selection indexes and data was available only after many generations of selection. Parameters for each generation were estimated by fitting an animal model using derivative free maximum likelihood (DFREML) with different data structures. In structure 1, data included the given (base) generation for which the parameters were to be estimated, and all subsequent generations. In structure 2, only data on birds in the given generation and their progeny were included. In both structures, parents of base-generation birds were assumed unrelated and pedigrees traced back to these parents. With commercial data using structure 1, estimates of _a ² and h² decreased by 14 to 37% across five generations. With structure 2, no trends were observed, though estimates were lower than for structure 1. For simulated data, with a heritability of 0.1, both structures yielded apparently unbiased estimates of the observed additive genetic variances in the (selected) base generation, no matter how many generations of data were utilized, for both sex-limited and normal traits. However, with a heritability of 0.5 the estimated additive genetic variance for both types of trait decreased with a decrease in the number of generations used in the estimation. Estimates based on the first two generations underestimated, while estimates based on five generations of data overestimated, the observed genetic variances in the defined base. The combinations of conditions that lead to varying degrees of bias remain undefined.     

Comparing genomic prediction accuracy from purebred,crossbred and combined purebred and crossbred reference populations in sheep

Background

The accuracy of genomic prediction depends largely on the number of animals with phenotypes and genotypes. In some industries, such as sheep and beef cattle, data are often available from a mixture of breeds, multiple strains within a breed or from crossbred animals. The objective of this study was to compare the accuracy of genomic prediction for several economically important traits in sheep when using data from purebreds, crossbreds or a combination of those in a reference population.

Methods

The reference populations were purebred Merinos, crossbreds of Border Leicester (BL), Poll Dorset (PD) or White Suffolk (WS) with Merinos and combinations of purebred and crossbred animals. Genomic breeding values (GBV) were calculated based on genomic best linear unbiased prediction (GBLUP), using a genomic relationship matrix calculated based on 48 599 Ovine SNP (single nucleotide polymorphisms) genotypes. The accuracy of GBV was assessed in a group of purebred industry sires based on the correlation coefficient between GBV and accurate estimated breeding values based on progeny records.

Results

The accuracy of GBV for Merino sires increased with a larger purebred Merino reference population, but decreased when a large purebred Merino reference population was augmented with records from crossbred animals. The GBV accuracy for BL, PD and WS breeds based on crossbred data was the same or tended to decrease when more purebred Merinos were added to the crossbred reference population. The prediction accuracy for a particular breed was close to zero when the reference population did not contain any haplotypes of the target breed, except for some low accuracies that were obtained when predicting PD from WS and vice versa.

Conclusions

This study demonstrates that crossbred animals can be used for genomic prediction of purebred animals using 50 k SNP marker density and GBLUP, but crossbred data provided lower accuracy than purebred data. Including data from distant breeds in a reference population had a neutral to slightly negative effect on the accuracy of genomic prediction. Accounting for differences in marker allele frequencies between breeds had only a small effect on the accuracy of genomic prediction from crossbred or combined crossbred and purebred reference populations.     

Evidence for genetic control of nematode egg-shedding rates in calves

Differences in nematode fecal egg counts from 167 purebred Angus calves born in 1986 and 133 born in 1987 that had been naturally exposed to infection on pasture were analyzed for sire effects. The calves were sired by 26 different bulls, all of which were related. Differences among fecal egg counts were attributable to sires (P less than 0.0002), to age of the calf (P less than 0.0007), to age of dam (P less than 0.05), and to collection year (P less than 0.0001). No variation in fecal egg count was attributable to calf sex (P greater than 0.23). After accounting for the effects of year, age of calf, and age of dam, heritability was estimated to be 29% (SE = 18%). It was concluded that a paternal contribution to the genome of each calf played an important role in determining average fecal egg output of the sire group. With heritability at 29%, selection against higher fecal egg counts or selection for lower fecal egg counts would be expected to produce measurable genetic change in a population.     

Relations between genetic distance of parental pig breeds and heterozygosity of their F1 crosses measured by genetic markers

The aim of this paper is to examine the extent to which increment of heterozygosity in F₁ crosses can be predicted from genetic distance of parental breeds. For this purpose, 38 polymorphic marker loci (blood groups, allotypes, polymorphic proteins and enzymes) were tested in 1115 purebred animals (Duroc, Hampshire and Czech Meat Pig as sire breeds; Landrace, Large White and Black Pied Přeštice as dam breeds) and in 1428 crossbred animals of the resulting nine crossbred groups. The number of animals in each genetic group ranged from 75 to 230. On the basis of the allele frequencies of the scored loci, three measures of genetic diversity (heterozygosity, standardized heterozygosity, effective number of alleles) were calculated in all 15 genetic groups. Furthermore, two measures of genetic distance (Nei's standard genetic distance and Gregorius' absolute genetic distance) were calculated between the parental populations. High correlations (Pearson product-moment correlation 0.62 to 0.73; Spearman rank correlation 0.58 to 0.85) were found between the increment of heterozygosity in the crosses (in relation to the mean of the heterozygosities of parental populations) and the genetic distance between the parental populations.     

Full-sib and reciprocal recurrent selection in relation to pearl millet improvement

Summary During the years 1973 to 1976 two populations of Pearl millet with wide genetic base, namely, Delhi composite (DC) and Vijay composite (VC) were used to compare the response to selection by the full-sib family method from biparental material and reciprocal recurrent selection (RRS). The results indicated that it was possible to advance grain yield with one cycle of RRS by about 23 percent in the case of population DC and 21 percent in population VC, while for the full-sib selection method, the improvement in grain yield was not so rapid. The studies on the nature of gene action indicated that both additive and dominance gene actions were important for grain yield, ear length and ear girth. The coefficient of variation as a result of RRS was reduced in population DC, while it was comparable to base population in the other population. The correlation studies indicated that the magnitude of favourable correlation of different characters with grain yield were higher in case of RRS compared to the full-sib system. The presence of negative correlation of plant height with grain yield in both the improved populations indicated the possibility of breakage of unfavourable gene combinations through RRS and full-sibs developed from biparental mating.     

Influence of parentage upon growth in Ostrea edulis: evidence for inbreeding depression

Genetic variability for growth was analysed in three populations of Ostrea edulis, selected for resistance to the protozoan parasite Bonamia ostreae. This study was undertaken first to determine the potential for selection for growth in populations that have never been selected for this character, and second to estimate heterosis versus inbreeding depression. Growth was monitored in culture for 10 months. The selected populations (namely S85-G3, S891-G2 and S89W-G2), their crossbred population and a control population were composed of full-sib families whose parents were already genotyped using five microsatellite markers. This genotyping allowed the estimation of genetic relatedness among pairs of parents. The parents' relatedness was then correlated with the growth performance of their offspring within each of the three populations, and inbreeding depression was estimated. The population effect for growth was highly significant, with the crossbred population having the highest growth rate, followed by S891-G2 and S89W-G2, S85-G3 and the control population. The within-populations family effect was also highly significant, indicating, as well as the high value for heritability at the family level (between 0.57 and 0.92), that a potential for a further selection for growth still exists within the three populations. Estimates of inbreeding depression (relative to the mean, for complete inbreeding) were high (1 for S891-G2, 0.44 for S89W-G2 and between 0.02 and 0.43 for S85-G3), which correlates with the apparent heterosis for growth observed in the crossbred population. These results are discussed in the context of the future management of the selected populations.     

Genomic selection of purebreds for crossbred performance

Background

One of the main limitations of many livestock breeding programs is that selection is in pure breeds housed in high-health environments but the aim is to improve crossbred performance under field conditions. Genomic selection (GS) using high-density genotyping could be used to address this. However in crossbred populations, 1) effects of SNPs may be breed specific, and 2) linkage disequilibrium may not be restricted to markers that are tightly linked to the QTL. In this study we apply GS to select for commercial crossbred performance and compare a model with breed-specific effects of SNP alleles (BSAM) to a model where SNP effects are assumed the same across breeds (ASGM). The impact of breed relatedness (generations since separation), size of the population used for training, and marker density were evaluated. Trait phenotype was controlled by 30 QTL and had a heritability of 0.30 for crossbred individuals. A Bayesian method (Bayes-B) was used to estimate the SNP effects in the crossbred training population and the accuracy of resulting GS breeding values for commercial crossbred performance was validated in the purebred population.

Results

Results demonstrate that crossbred data can be used to evaluate purebreds for commercial crossbred performance. Accuracies based on crossbred data were generally not much lower than accuracies based on pure breed data and almost identical when the breeds crossed were closely related breeds. The accuracy of both models (ASGM and BSAM) increased with marker density and size of the training data. Accuracies of both models also tended to decrease with increasing distance between breeds. However the effect of marker density, training data size and distance between breeds differed between the two models. BSAM only performed better than AGSM when the number of markers was small (500), the number of records used for training was large (4000), and when breeds were distantly related or unrelated.

Conclusion

In conclusion, GS can be conducted in crossbred population and models that fit breed-specific effects of SNP alleles may not be necessary, especially with high marker density. This opens great opportunities for genetic improvement of purebreds for performance of their crossbred descendents in the field, without the need to track pedigrees through the system.     

Quantitative genetic studies at the tetraploid and hexaploid levels in alfalfa

Summary Two sets of diallel crosses involving seven tetraploid and five hexaploid alfalfa lines, previously selected for seed and forage yield, are studied. On the basis of combining ability and heritability estimates the following conclusion is drawn. The dominant and epistatic interactions (heterozygosity) are the major components in the expression of variability for yield and characters associated with yield in tetraploid populations. In hexaploid populations, however, there is an appreciable amount of additive variance, and the additive effect of genes along with interaction of various forms may account for the expressed variability for all the characters studied. Better genes and desirable interactions (possibly through heterozygosity) are the two essential genetic components of yield. The selection of better genes is feasible, but by itself will not produce the desired results. Future improvement may therefore depend on the utilization of heterosis and other forms of interactions. There is, in general, a very strong genetic correlation between yield and its components, and therefore, when a direct selection for yield is not feasible, the selection program may rely on a number of closely related characters.     

Imputation of genotypes in Danish purebred and two-way crossbred pigs using low-density panels

Background

Genotype imputation is commonly used as an initial step in genomic selection since the accuracy of genomic selection does not decline if accurately imputed genotypes are used instead of actual genotypes but for a lower cost. Performance of imputation has rarely been investigated in crossbred animals and, in particular, in pigs. The extent and pattern of linkage disequilibrium differ in crossbred versus purebred animals, which may impact the performance of imputation. In this study, first we compared different scenarios of imputation from 5 K to 8 K single nucleotide polymorphisms (SNPs) in genotyped Danish Landrace and Yorkshire and crossbred Landrace-Yorkshire datasets and, second, we compared imputation from 8 K to 60 K SNPs in genotyped purebred and simulated crossbred datasets. All imputations were done using software Beagle version 3.3.2. Then, we investigated the reasons that could explain the differences observed.

Results

Genotype imputation performs as well in crossbred animals as in purebred animals when both parental breeds are included in the reference population. When the size of the reference population is very large, it is not necessary to use a reference population that combines the two breeds to impute the genotypes of purebred animals because a within-breed reference population can provide a very high level of imputation accuracy (correct rate ≥ 0.99, correlation ≥ 0.95). However, to ensure that similar imputation accuracies are obtained for crossbred animals, a reference population that combines both parental purebred animals is required. Imputation accuracies are higher when a larger proportion of haplotypes are shared between the reference population and the validation (imputed) populations.

Conclusions

The results from both real data and pedigree-based simulated data demonstrate that genotype imputation from low-density panels to medium-density panels is highly accurate in both purebred and crossbred pigs. In crossbred pigs, combining the parental purebred animals in the reference population is necessary to obtain high imputation accuracy.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-015-0134-4) contains supplementary material, which is available to authorized users.     

Estimation of quantitative genetic parameters using marker-inferred relatedness in Japanese flounder: a case study of upward bias

Marker-based methods for estimating heritability have been proposed as an effective means to study quantitative traits in long-lived organisms and natural populations. However, practical examinations to evaluate the usefulness and robustness of a regression method are limited. Using several quantitative traits of Japanese flounder Paralichthys olivaceus, the present study examined the influence of relatedness estimator and population structure on the estimation of heritability and genetic correlation under a regression method with 7 microsatellite loci. Significant heritability and genetic correlation were detected for several quantitative traits in 2 laboratory populations but not in a natural population. In the laboratory populations, upward bias in heritability appeared depending on the relatedness estimators and the populations. Upward bias in heritability increased with decreasing the actual variance of relatedness, suggesting that the estimates of heritability under the regression method tend to be overestimated due to the underestimation of the actual variance of relatedness. Therefore, relationship structure and precise estimation of relatedness are critical for applying this method.     

Crossbreeding effects after long-term selection for purebred performance: a model experiment with mice

Summary The influence of purebred selection on the combining abilities of five lines of mice was examined. Two replicated testcross diallels were made after 10 and 20 generations of purebred selection for litter size, weaning weight, weight gain, and feed efficiency. Average direct genetic effects were of major importance, followed by average maternal genetic effects. In all of the replications, between two and four out of ten crosses showed significant heterosis. Heterosis ranged from 0 to 38% in litter size, from 0 to 20% in weaning weight, from -11 to 11% in weight gain, and from -8 to 17% in feed efficiency. For litter size and weaning weight, heterosis estimates increased between 80 and 100% from generation 10 to 20. Weight gain and feed efficiency showed decreasing heterosis with partly negative estimates in the second diallel. Combinations exhibiting significant heterosis varied between replicates and between the two diallels.     

Choice of environments in reciprocal recurrent selection programs

Summary An alternative method of reciprocal recurrent selection (RRS) in which populations A and B are each evaluated in a different environment is proposed. This method is called dual-environment reciprocal recurrent selection (DERRS). Two genetic models are considered in the theoretical study. A comparison of selection methods shows that genetic gain is larger in DERRS than in RRS for the two models. The difference grows greater as the dominance effects operating in the two environments are more divergent and as the number of selection cycles increases. A greater gain is obtained when the genetic covariances between crosses in the two chosen environments are lower.     

Egg shell quality in Japanese quail: characteristics,heritabilities and genetic and phenotypic relationships

The objective of the present study was to estimate heritabilities as well as genetic and phenotypic correlations for egg weight, specific gravity, shape index, shell ratio, egg shell strength, egg length, egg width and shell weight in Japanese quail eggs. External egg quality traits were measured on 5864 eggs of 934 female quails from a dam line selected for two generations. Within the Bayesian framework, using Gibbs Sampling algorithm, a multivariate animal model was applied to estimate heritabilities and genetic correlations for external egg quality traits. The heritability estimates for external egg quality traits were moderate to high and ranged from 0.29 to 0.81. The heritability estimates for egg and shell weight of 0.81 and 0.76 were fairly high. The genetic and phenotypic correlations between egg shell strength with specific gravity, shell ratio and shell weight ranging from 0.55 to 0.79 were relatively high. It can be concluded that it is possible to determine egg shell quality using the egg specific gravity values utilizing its high heritability and fairly high positive correlation with most of the egg shell quality traits. As a result, egg specific gravity may be the choice of selection criterion rather than other external egg traits for genetic improvement of egg shell quality in Japanese quails.     

Effect of genomic prediction on response to selection in forest tree breeding

Through stochastic simulations, estimates of breeding values accuracies and response to selection were assessed under traditional pedigree-based and genomic-based evaluation methods. More specifically, several key parameters such as the trait’s heritability (0.2 and 0.6), the number of QTLs underlying the trait (100 to 200), and the marker density (1 to 10 SNPs/cM) were evaluated. Additionally, impact of two contrasting mating designs (partial diallel vs. single-pair mating) was investigated. Response to selection was then assessed in a seed production population (seed orchard consisting of unrelated selections) for different effective population sizes (N_e?=?5 to 25). The simulated candidate population comprised a fixed size of 2050 individuals with fast linkage disequilibrium decay, generally found in forest tree populations. Following the genetic/genomic evaluation, top-ranked individuals were selected to meeting the predetermined effective population size in target production population. The combination of low h², high N_e, and dense marker coverage resulted at maximum relative genomic prediction efficiency and the most efficient exploitation of the Mendelian sampling term (within-family additive genetic variance). Since genomic prediction of breeding values constitutes the methodological foundation of genomic selection, our results can be used to address important questions when similar scenarios are considered.     

Dissecting total genetic variance into additive and dominance components of purebred and crossbred pig traits

The partition of the total genetic variance into its additive and non-additive components can differ from trait to trait, and between purebred and crossbred populations. A quantification of these genetic variance components will determine the extent to which it would be of interest to account for dominance in genomic evaluations or to establish mate allocation strategies along different populations and traits. This study aims at assessing the contribution of the additive and dominance genomic variances to the phenotype expression of several purebred Piétrain and crossbred (Piétrain × Large White) pig performances. A total of 636 purebred and 720 crossbred male piglets were phenotyped for 22 traits that can be classified into six groups of traits: growth rate and feed efficiency, carcass composition, meat quality, behaviour, boar taint and puberty. Additive and dominance variances estimated in univariate genotypic models, including additive and dominance genotypic effects, and a genomic inbreeding covariate allowed to retrieve the additive and dominance single nucleotide polymorphism variances for purebred and crossbred performances. These estimated variances were used, together with the allelic frequencies of the parental populations, to obtain additive and dominance variances in terms of genetic breeding values and dominance deviations. Estimates of the Piétrain and Large White allelic contributions to the crossbred variance were of about the same magnitude in all the traits. Estimates of additive genetic variances were similar regardless of the inclusion of dominance. Some traits showed relevant amount of dominance genetic variance with respect to phenotypic variance in both populations (i.e. growth rate 8%, feed conversion ratio 9% to 12%, backfat thickness 14% to 12%, purebreds-crossbreds). Other traits showed higher amount in crossbreds (i.e. ham cut 8% to 13%, loin 7% to 16%, pH semimembranosus 13% to 18%, pH longissimus dorsi 9% to 14%, androstenone 5% to 13% and estradiol 6% to 11%, purebreds-crossbreds). It was not encountered a clear common pattern of dominance expression between groups of analysed traits and between populations. These estimates give initial hints regarding which traits could benefit from accounting for dominance for example to improve genomic estimated breeding value accuracy in genetic evaluations or to boost the total genetic value of progeny by means of assortative mating.     

Basal metabolic rate can evolve independently of morphological and behavioural traits

Quantitative genetic analyses of basal metabolic rate (BMR) can inform us about the evolvability of the trait by providing estimates of heritability, and also of genetic correlations with other traits that may constrain the ability of BMR to respond to selection. Here, we studied a captive population of zebra finches (Taeniopygia guttata) in which selection lines for male courtship rate have been established. We measure BMR in these lines to see whether selection on male sexual activity would change BMR as a potentially correlated trait. We find that the genetic correlation between courtship rate and BMR is practically zero, indicating that the two traits can evolve independently of each other. Interestingly, we find that the heritability of BMR in our population (h²=0.45) is markedly higher than was previously reported for a captive zebra finch population from Norway. A comparison of the two studies shows that additive genetic variance in BMR has been largely depleted in the Norwegian population, especially the genetic variance in BMR that is independent of body mass. In our population, the slope of BMR increase with body mass differs not only between the sexes but also between the six selection lines, which we tentatively attribute to genetic drift and/or founder effects being strong in small populations. Our study therefore highlights two things. First, the evolvability of BMR may be less constrained by genetic correlations and lack of independent genetic variation than previously described. Second, genetic drift in small populations can rapidly lead to different evolvabilities across populations.