Long-Term Impact of Optimum Contribution Selection Strategies on Local Livestock Breeds with Historical Introgression Using the Example of German Angler Cattle

Simulation of dual-purpose chicken breeding programs implementing gene editing

BACKGROUND

In spite of being controversial and raising ethical concerns, the application of gene editing is more likely to be accepted when it contributes to improving animal welfare. One of the animal welfare and ethical issues in chicken breeding is chick culling, the killing of the male layer chicks after hatching due to the poor fattening performance. Although establishing dual-purpose chicken lines could solve this problem, unfavorable genetic correlations between egg and meat production traits hindered their competitiveness. Although it is also controversial in ethical terms, gene editing may accelerate genetic progress in dual-purpose chicken and alleviate the ethical concerns from chick culling.

RESULTS

The simulation compared the utility improvement in dual-purpose use under two breeding schemes: one consisting in the improvement of the laying hens, and the second in the improvement of a synthetic line obtained from a layer broiler cross. In each breeding scheme, the breeding programs were simulated with and without gene editing. Polygenic breeding values and 500 simulated quantitative trait loci (QTL) with different levels of pleiotropy caused negative correlations between egg production, meat production, and overall health. The results of the simulation demonstrated that genetic gain could be accelerated by at most 81% for several generations if gene editing was used. The actual increase in genetic gain depended on the number of single nucleotide polymorphisms (SNPs) being edited per animal. The rate of genetic improvement became equal in scenarios with and without gene editing after 20 generations. This is because the remaining segregating QTL had small effects and their edition would have negative overall health effects from potential off-target edits. Although gene editing can improve genetic gain in quantitative traits, it can only be recommended as long as QTL with reasonable effect sizes are segregating and detectable.

CONCLUSIONS

This simulation demonstrates the potential of gene editing to accelerate the simultaneous improvement of negatively correlated traits. When the risk of negative consequences from gene editing persists, the number of SNPs to be edited should be chosen carefully to obtain the optimal genetic gain.

Evaluation of Linear Programming and Optimal Contribution Selection Approaches for Long-Term Selection on Beef Cattle Breeding

The optimized selection method can maximize the genetic gain in offspring under the premise of controlling the inbreeding level of the population. At present, genetic gain has been largely improved by using genomic selection in multiple farm animals. However, the design of the optimal selection method and assessment of its effects during long-term selection in beef cattle breeding are yet to be fully explored. In this study, a simulated beef cattle population was constructed, and 15 generations of simulated breeding were carried out using the linear programming breeding strategy (LP) and optimal contribution selection strategy (OCS), respectively. The truncation selection strategy (TS-I and TS-II) was used as the control. During the breeding process, genetic parameters including genetic gain, average kinship coefficient, QTL effect variance, and average observed heterozygosity were calculated and compared across generations. Our results showed that the LP method can significantly improve the genetic gain in the population, especially the genetic performance of the traits with high heritability and the traits with high weight in the breeding process, but the inbreeding level of the population is higher under LP strategy. Although the genetic gain in the population under the OCS strategy is lower than the TS-II strategy, this method can effectively control the inbreeding level of the population. Our findings also suggest that the LP and OCS method can be used as an effective means to improve genetic gain, while the OCS method is a more ideal method to obtain sustainable genetic gain during long-term selection.

Genomic rotational crossbreeding with advanced optimum contribution selection methods applied to simulated German Angler and German Holstein dairy cattle populations

Many local dairy cattle breeds are facing genetic extinction due to a large proportion of foreign genes, which have been introgressed in the past. In addition, the performance gap to popular high-yielding breeds is increasing, resulting in a risk of numeric extinction. In the present simulation study, a genomic rotational crossbreeding scheme with the high-yielding German Holstein breed and the numerically small German Angler breed was analysed with the aim to utilize heterosis effects in the crossbred animals. Simultaneously inbreeding was controlled, and the amount of Holstein introgression observed in the Angler breed was reduced. Different scenarios of implementing OCS methods for Angler individuals were evaluated, which differed in their restrictions regarding kinship, native kinship, as well as the amount of genetic contributions from German Holstein. The results showed that rotational crossbreeding can result in superior crossbred offspring compared to the purebred parental lines, whereby OCS methods can simultaneously restrict the increase in inbreeding and keep the Holstein contributions at their current level. However, reducing the amount of migrant contributions while restricting the increase in the native kinship in Angler turned out to be a costly restriction. The reason was that Angler with low genetic contributions from Holsteins tended to have similar Angler ancestors. Consequently, reducing Holstein contributions would considerably increase the native kinship in Angler if it were not constrained. The constraint on the native kinship made a constraint on the conventional kinship superfluous and caused it to increase at a much lower rate than envisaged. This led to both, a high genetic diversity and a low genetic gain. The high genetic diversity in Angler also resulted in lower and oscillating heterosis effects in the crossbred animals. Thus, the reduction of migrant contribution did not increase heterosis effects in the crossbred offspring, and did not result in superior crossbred offspring in general.

Improving the Accuracy of Multi-Breed Prediction in Admixed Populations by Accounting for the Breed Origin of Haplotype Segments

Numerically small breeds have often been upgraded with mainstream breeds. This historic introgression predisposes the breeds for joint genomic evaluations with mainstream breeds. The linkage disequilibrium structure differs between breeds. The marker effects of a haplotype segment may, therefore, depend on the breed from which the haplotype segment originates. An appropriate method for genomic evaluation would account for this dependency. This study proposes a method for the computation of genomic breeding values for small admixed breeds that incorporate phenotypic and genomic information from large introgressed breeds by considering the breed origin of alleles (BOA) in the evaluation. The proposed BOA model classifies haplotype segments according to their origins and assumes different but correlated SNP effects for the different origins. The BOA model was compared in a simulation study to conventional within-breed genomic best linear unbiased prediction (GBLUP) and conventional multi-breed GBLUP models. The BOA model outperformed within-breed GBLUP as well as multi-breed GBLUP in most cases.

Implementing a genomic rotational crossbreeding scheme to promote local dairy cattle breeds-A simulation study

In dairy cattle breeding, there is a clear trend toward the use of only a few high-yielding breeds. One main reason is that efficient breeding programs require a certain population size. Since some numerically small breeds are well known for their functional traits, they might be an interesting crossing partner for high-yielding breeds with the aim to utilize heterosis. This simulation study investigated the transition period of a small cattle population for the implementation of genomic selection and rotational crossbreeding with a high-yielding breed. Real SNP chip genotype data from the numerically small red dairy breed Angler and the high-yielding breed Holstein Friesian were used to simulate the base generations, from which rotational crossbreeding was conducted for 10 generations. A polygenic trait with many quantitative trait loci with additive and directional dominance effects was simulated. Different selection methods for Angler sires (purebred performance, crossbred performance, and weighted purebred-crossbred performance) and different sizes and structures of the reference population (Angler, crossbred animals, and Angler plus crossbred animals) were considered. The results showed that the implementation of a genomic rotational crossbreeding scheme is an appealing option to promote the numerically small Angler breed. The growing reference population consisting of Angler and crossbred individuals maximized the genetic gain for Angler and the performance level for the crossbred individuals. Selection for purebred performance, crossbred performance, or a weighted combination of both hardly affected the results, and differences between selection scenarios were observed only in the long term with decreasing purebred-crossbred correlations.

Origin Specific Genomic Selection: A Simple Process To Optimize the Favorable Contribution of Parents to Progeny

Modern crop breeding is in constant demand for new genetic diversity as part of the arms race with genetic gain. The elite gene pool has limited genetic variation and breeders are trying to introduce novelty from unadapted germplasm, landraces and wild relatives. For polygenic traits, currently available approaches to introgression are not ideal, as there is a demonstrable bias against exotic alleles during selection. Here, we propose a partitioned form of genomic selection, called Origin Specific Genomic Selection (OSGS), where we identify and target selection on favorable exotic alleles. Briefly, within a population derived from a bi-parental cross, we isolate alleles originating from the elite and exotic parents, which then allows us to separate out the predicted marker effects based on the allele origins. We validated the usefulness of OSGS using two nested association mapping (NAM) datasets: barley NAM (elite-exotic) and maize NAM (elite-elite), as well as by computer simulation. Our results suggest that OSGS works well in its goal to increase the contribution of favorable exotic alleles in bi-parental crosses, and it is possible to extend the approach to broader multi-parental populations.

Implementation of advanced Optimum Contribution Selection in small-scale breeding schemes: prospects and challenges in Vorderwald cattle

Vorderwald cattle are a regional cattle breed from the Black Forest in south western Germany. In recent decades, commercial breeds have been introgressed to upgrade the breed in performance traits. On one hand, native genetic diversity of the breed should be conserved. On the other hand, moderate rates of genetic gain are needed to satisfy breeders to keep the breed. These goals are antagonistic, since the native proportion of the gene pool is negatively correlated to performance traits and the carriers of introgressed alleles are less related to the population. Thus, a standard Optimum Contribution Selection (OCS) approach would lead to reinforced selection on migrant contributions (MC). Our objective was the development of strategies for practical implementation of an OCS approach to manage the MC and native genetic diversity of regional breeds. Additionally, we examined the organisational efforts and the financial impacts on the breeding scheme of Vorderwald cattle. We chose the advanced Optimum Contribution Selection (aOCS) to manage the breed in stochastic simulations based on real pedigree data. In addition to standard OCS approaches, aOCS facilitates the management of the MC and the rate of inbreeding at native alleles. We examined two aOCS strategies. Both strategies maximised genetic gain, while strategy (I) conserved the MC in the breeding population and strategy (II) reduced the MC at a predefined annual rate. These two approaches were combined with one of three flows of replacement of sires (FoR strategies). Additionally, we compared breeding costs to clarify about the financial impact of implementing aOCS in a young sire breeding scheme. According to our results, conserving the MC in the population led to significantly (P < 0.01) higher genetic gain (1.16 ± 0.13 points/year) than reducing the MC (0.88 ± 0.10 points/year). In simulation scenarios that conserved the MC, the final value of MC was 57.6% ± 0.004, while being constraint to 58.2%. However, reducing the MC is only partially feasible based on pedigree data. Additionally, this study proves that the classical rate of inbreeding can be managed by constraining only the rate of inbreeding at native alleles within the aOCS approach. The financial comparison of the different breeding schemes proved the feasibility of implementing aOCS in Vorderwald cattle. Implementing the modelled breeding scheme would reduce costs by 1.1% compared with the actual scheme. Reduced costs were underpinned by additional genetic gain in superior simulation scenarios compared to expected genetic gain in reality (+4.85%).

Inbreeding in a Population of Polish Holstein-Friesian Young Bulls Before and After Genomic Selection

Inbreeding was analysed in a population of 14,144 Polish Black-and-White Holstein-Friesian (PBWHF) young bulls born between 1994 and 2017 and bred under both conventional and genomic breeding programmes. The inbreeding coefficients were computed using a model with genetic groups, according to the algorithm given by VanRaden. It was found that in the analysed population all bulls are inbred (100% of the population), with the mean coefficient of inbreeding ranging from 0.09% to 26.95%. Pedigree analysis also showed a relationship between the changing number of bulls over the years and the dynamics of population inbreeding. These trends are connected with changes in the breeding scheme, related to the implementation of genomic selection in the breeding programme for PBWHF cattle in 2014. The increasing number of weaned young bulls in Poland was paralleled by a fairly consistent increase in the mean inbreeding, but the inbreeding dynamics were relatively small. A reverse trend was observed in the group of young bulls born after 2013. As the number of bulls very rapidly decreased in successive birth years, the mean inbreeding for successive birth-year groups very rapidly increased. As a result, the estimated linear trend was equal to 0.02% inbreeding per year of birth in the group of bulls raised before genomic selection (~20 birth-year) whereas in the group of bulls raised after genomic selection (~4 birth-year) the trend was much higher and amounted to 0.56% inbreeding per year of birth. The high mean inbreeding found in the group of the genomically selected young bulls may translate into higher inbreeding in the whole population of PBWHF cattle, because these bulls are now intensively used as sires. The results of our study also show that the implementation of genomic selection in the breeding programme caused a very rapid increase in the inbreeding rate per birth-year in young bulls.

Runs of Homozygosity and NetView analyses provide new insight into the genome-wide diversity and admixture of three German cattle breeds

Angler (RVA) and Red-and-White dual-purpose (RDN) cattle were in the past decades crossed with influential Red Holstein (RH) sires. However, genome-wide diversity studies in these breeds are lacking. The objective of the present study was to elucidate the genome-wide diversity and population structure of the three German cattle breeds. Using 40,851 single nucleotide polymorphism markers scored in 337 individuals, runs of homozygosity (ROH) were analysed in each breed. Clustering and a high-resolution network visualisation analyses were performed on an extended dataset that included 11 additional (outgroup) breeds. Genetic diversity levels were high with observed heterozygosity above 0.35 in all three breeds. Only RVA had a recent past effective population size (Ne) estimate above 100 at 5 generations ago. ROH length distribution followed a similar pattern across breeds and the majority of ROH were found in the length class of >5 to 10 Mb. Estimates of average inbreeding calculated from ROH (FROH) were 0.021 (RVA), 0.045 (RDN) and 0.053 (RH). Moderate to high positive correlations were found between FROH and pedigree inbreeding (FPED) and between FROH and inbreeding derived from the excess of homozygosity (FHOM), while the intercept of the regression of FROH on FPED was above zero. The population structure analysis showed strong evidence of admixture between RVA and RH. Introgression of RDN with RH genes was minimally detected and for the first time, the study uncovered Norwegian Red Cattle ancestry in RVA. Highly heterogeneous genetic background was found for RVA and RH and as expected, the breeds of the extended dataset effectively differentiated mostly based on geographical origin, validating our findings. The results of this study confirm the impact of RH sires on RVA and RDN populations. Furthermore, a close monitoring is suggested to curb further reduction of Ne in the breeds.

Key Genetic Parameters for Population Management

Population management has the primary task of maximizing the long-term competitiveness of a breed. Breeds compete with each other for being able to supply consumer demands at low costs and also for funds from conservation programs. The competition for consumer preference is won by breeds with high genetic gain for total merit who maintained a sufficiently high genetic diversity, whereas the competition for funds is won by breeds with high conservation value. The conservation value of a breed could be improved by increasing its contribution to the gene pool of the species. This may include the recovery of its original genetic background and the maintenance of a high genetic diversity at native haplotype segments. The primary objective of a breeding program depends on the genetic state of the population and its intended usage. In this paper, we review the key genetic parameters that are relevant for population management, compare the methods for estimating them, derive the formulas for predicting their value at a future time, and clarify their usage in various types of breeding programs that differ in their main objectives. These key parameters are kinships, native kinships, breeding values, Mendelian sampling variances, native contributions, and mutational effects. Population management currently experiences a transition from using pedigree-based estimates to marker-based estimates, which improves the accuracies of these estimates and thereby increases response to selection. In addition, improved measures of the factors that determine the competitiveness of a breed and utilize auxiliary parameters, such as Mendelian sampling variances, mutational effects, and native kinships, enable to improve further upon historic recommendations for genetic population management.

Potential of TLR-gene diversity in Czech indigenous cattle for resistance breeding as revealed by hybrid sequencing

A production herd of Czech Simmental cattle (Czech Red Pied, CRP), the conserved subpopulation of this breed, and the ancient local breed Czech Red cattle (CR) were screened for diversity in the antibacterial toll-like receptors (TLRs), which are members of the innate immune system. Polymerase chain reaction (PCR) amplicons of TLR1, TLR2, TLR4, TLR5, and TLR6 from pooled DNA samples were sequenced with PacBio technology, with 3- 5 ×  coverage per gene per animal. To increase the reliability of variant detection, the gDNA pools were sequenced in parallel with the Illumina X-ten platform at low coverage ( 60 × per gene). The diversity in conserved CRP and CR was similar to the diversity in conserved and modern CRP, representing 76.4 % and 70.9 % of its variants, respectively. Sixty-eight (54.4 %) polymorphisms in the five TLR genes were shared by the two breeds, whereas 38 (30.4 %) were specific to the production herd of CRP; 4 (3.2 %) were specific to the broad CRP population; 7 (5.6 %) were present in both conserved populations; 5 (4.0 %) were present solely for the conserved CRP; and 3 (2.4 %) were restricted to CR. Consequently, gene pool erosion related to intensive breeding did not occur in Czech Simmental cattle. Similarly, no considerable consequences were found from known bottlenecks in the history of Czech Red cattle. On the other hand, the distinctness of the conserved populations and their potential for resistance breeding were only moderate. This relationship might be transferable to other non-abundant historical cattle breeds that are conserved as genetic resources. The estimates of polymorphism impact using Variant Effect Predictor and SIFT software tools allowed for the identification of candidate single-nucleotide polymorphisms (SNPs) for association studies related to infection resistance and targeted breeding. Knowledge of TLR-gene diversity present in Czech Simmental populations may aid in the potential transfer of variant characteristics from other breeds.

Advanced optimum contribution selection as a tool to improve regional cattle breeds: a feasibility study for Vorderwald cattle

In the middle of the 20th century, increasing inbreeding rates were identified as a threat to livestock breeding. Consequences include reduced fertility, fitness and phenotypic expression of lethal alleles. An important step in mitigating this inbreeding was the introduction of optimum contribution selection (OCS). OCS facilitates the simultaneous management of genetic gain and inbreeding rates. However, using a standard OCS methodology for regional breeds with historical introgression for upgrading reasons could lead to reinforced selection on introgressed genetic material since those alleles improve the rate of genetic gain and reduce the average kinship in the population. Consequently, regional breeds may become genetically extinct if a standard OCS approach is used. Thus, the advanced OCS (aOCS) approach takes introgressed genetic material into account. The major goals of this study were to (i) gather key information on the feasibility of aOCS under practical conditions of the actual breeding scheme of Vorderwald cattle, (ii) identify superior strategies for implementing the actual scheme and (iii) examine whether historical breeding decisions to increase genetic gain by introgression from commercial breeds could have been avoided by using aOCS. Stochastic simulations were designed in this study to create populations from the historical gene pool by using aOCS. Simultaneously, all practical constraints of a breeding scheme were met. Thus, the simulated populations were comparable with real data. The annual genetic gain was higher in reality (1.56) than in the simulation scenarios (1.12-1.40). The introgressed genetic material increased to 61.3% in reality but was conserved at a final value of 15.3% (±0.78) across simulations. The classical rate of inbreeding and rate of native inbreeding were constrained to 0.092% on an annual basis. This value is equal to an effective population size of 100. The observed values for rates of inbreeding were 0.082-0.087% and 0.087-0.088% for classical and native kinship, respectively. The corresponding figures in reality were 0.067% and 0.184%, respectively. This study suggests that aOCS is feasible for Vorderwald cattle. Strategies for implementation are identified. Finally, we conclude that historical breeding decisions could have been avoided by using aOCS. The genetic gain would have been reduced by at least 12.2%, but the introgressed genetic material, genetic diversity and native genetic diversity would have been more desirable for a breed under conservation.

Managing genomes of conserved livestock breeds with historical introgression to decrease genetic overlap with other breeds

Recovering the native genetic background of a breed and increasing the founder genome equivalent (FGE) that is contributed by a breed to the gene pool of the species can increase its value for conservation. The suitability of several strategies was compared, whereby a hypothetical multi-breed population, the core set, was used to approximate the genetic diversity of the species. Twenty-five generations of management were simulated based on genotypes of German Angler cattle. The scenarios were compared when the kinship reached 0.10. The native contribution (NC) increased in a population with 400 births per generation from 0.317 to 0.706, whereas 1,000 births enabled to reach 0.894. This scenario maximized the NC, constrained the native kinship, and the kinship of the core set so that its genetic diversity could not decrease. It increased the proportions of mainstream breeds because their genes were removed from the target breed. A substantial increase of the FGE was achieved in some other scenarios, which arose from reduced genetic overlap and from increased diversity within the breed. The latter factor is especially important for breeds with high contributions to the core set.

Optimum contribution selection for animal breeding and conservation: the R package optiSel

Background

Selecting animals for breeding in the optimum way plays an essential role for the management of genetic resources and in selective breeding of livestock species. It requires to compute the optimum genetic contribution of each selection candidate to the next generation. Current software packages for optimum contribution selection (OCS) are not able to handle the main conflicting objectives of animal breeding programs simultaneously, which includes to increase genetic gain, to increase or to maintain genetic diversity, to recover the original genetic background of endangered breeds with historic introgression, and to maintain or increase genetic diversity at native alleles.

Results

The free R package optiSel offers functions for estimating the above mentioned parameters from pedigree and marker data, and for solving OCS problems. One parameter can be optimized, whereas the remaining ones can be constrained. The results reveal the optimum numbers of offspring of all selection candidates, and can subsequently be used for mate allocation. Different solvers can be used. Solver slsqp was superior when the genetic diversity at native alleles was to be maximized, whereas solvers cccp and cccp2 were superior for all other OCS problems.

Conclusion

Optimum contribution selection applied to local breeds requires special attention due to the conflicting objectives of their breeding programs. The free R package optiSel is an easy-to-use software taking these conflicting objectives into account.

Electronic supplementary material

The online version of this article (10.1186/s12859-018-2450-5) contains supplementary material, which is available to authorized users.