What is genetic quality?

Mate choice is favored by indirect selection if choosy females mate with males of high genetic quality. We believe, however, that testing hypotheses about indirect selection has been constrained by how we conceptualize and therefore empirically measure male genetic quality. Here, we argue that genetic quality is the breeding value of an individual for total fitness. We can therefore learn little about genetic quality from measures of only a few fitness components. We explain breeding value for total fitness, drawing on concepts from life-history theory and quantitative genetics, and suggest how approaches incorporating these insights might result in empirical progress.     

Accelerating the domestication of trees using genomic selection: accuracy of prediction models across ages and environments

? Genomic selection is increasingly considered vital to accelerate genetic improvement. However, it is unknown how accurate genomic selection prediction models remain when used across environments and ages. This knowledge is critical for breeders to apply this strategy in genetic improvement. ? Here, we evaluated the utility of genomic selection in a Pinus taeda population of c. 800 individuals clonally replicated and grown on four sites, and genotyped for 4825 single-nucleotide polymorphism (SNP) markers. Prediction models were estimated for diameter and height at multiple ages using genomic random regression best linear unbiased predictor (BLUP). ? Accuracies of prediction models ranged from 0.65 to 0.75 for diameter, and 0.63 to 0.74 for height. The selection efficiency per unit time was estimated as 53-112% higher using genomic selection compared with phenotypic selection, assuming a reduction of 50% in the breeding cycle. Accuracies remained high across environments as long as they were used within the same breeding zone. However, models generated at early ages did not perform well to predict phenotypes at age 6 yr. ? These results demonstrate the feasibility and remarkable gain that can be achieved by incorporating genomic selection in breeding programs, as long as models are used at the relevant selection age and within the breeding zone in which they were estimated.     

Total cost estimation for implementing genome-enabled selection in a multi-level swine production system

Background

Determining an animal’s genetic merit using genomic information can improve estimated breeding value (EBV) accuracy; however, the magnitude of the accuracy improvement must be large enough to recover the costs associated with implementing genome-enabled selection. One way to reduce costs is to genotype nucleus herd selection candidates using a low-density chip and to use high-density chip genotyping for animals that are used as parents in the nucleus breeding herd. The objective of this study was to develop a tool to estimate the cost structure associated with incorporating genome-enabled selection into multi-level commercial breeding programs.

Results

For the purpose of this deterministic study, it was assumed that a commercial pig is created from a terminal line sire and a dam that is a cross between two maternal lines. It was also assumed that all male and female selection candidates from the 1000 sow maternal line nucleus herds were genotyped at low density and all animals used for breeding at high density. With the assumptions used in this analysis, it was estimated that genome-enabled selection costs for a maternal line would be approximately US$0.082 per weaned pig in the commercial production system. A total of US$0.164 per weaned pig is needed to incorporate genome-enabled selection into the two maternal lines. Similarly, for a 600 sow terminal line nucleus herd and genotyping only male selection candidates with the low-density panel, the cost per weaned pig in the commercial herd was estimated to be US$0.044. This means that US$0.21 per weaned pig produced at the commercial level and sired by boars obtained from the nucleus herd breeding program needs to be added to the genetic merit value in order to break even on the additional cost required when genome-enabled selection is used in both maternal lines and the terminal line.

Conclusions

By modifying the input values, such as herd size and genotyping strategy, a flexible spreadsheet tool developed from this work can be used to estimate the additional costs associated with genome-enabled selection. This tool will aid breeders in estimating the economic viability of incorporating genome-enabled selection into their specific breeding program.     

Integration of genomic information into sport horse breeding programs for optimization of accuracy of selection

Reliable selection criteria are required for young riding horses to increase genetic gain by increasing accuracy of selection and decreasing generation intervals. In this study, selection strategies incorporating genomic breeding values (GEBVs) were evaluated. Relevant stages of selection in sport horse breeding programs were analyzed by applying selection index theory. Results in terms of accuracies of indices (r_TI) and relative selection response indicated that information on single nucleotide polymorphism (SNP) genotypes considerably increases the accuracy of breeding values estimated for young horses without own or progeny performance. In a first scenario, the correlation between the breeding value estimated from the SNP genotype and the true breeding value (= accuracy of GEBV) was fixed to a relatively low value of r_mg = 0.5. For a low heritability trait (h² = 0.15), and an index for a young horse based only on information from both parents, additional genomic information doubles r_TI from 0.27 to 0.54. Including the conventional information source ‘own performance’ into the before mentioned index, additional SNP information increases r_TI by 40%. Thus, particularly with regard to traits of low heritability, genomic information can provide a tool for well-founded selection decisions early in life. In a further approach, different sources of breeding values (e.g. GEBV and estimated breeding values (EBVs) from different countries) were combined into an overall index when altering accuracies of EBVs and correlations between traits. In summary, we showed that genomic selection strategies have the potential to contribute to a substantial reduction in generation intervals in horse breeding programs.     

Accuracy of genomic selection for age at puberty in a multi‐breed population of tropically adapted beef cattle

Genomic selection is becoming a standard tool in livestock breeding programs, particularly for traits that are hard to measure. Accuracy of genomic selection can be improved by increasing the quantity and quality of data and potentially by improving analytical methods. Adding genotypes and phenotypes from additional breeds or crosses often improves the accuracy of genomic predictions but requires specific methodology. A model was developed to incorporate breed composition estimated from genotypes into genomic selection models. This method was applied to age at puberty data in female beef cattle (as estimated from age at first observation of a corpus luteum) from a mix of Brahman and Tropical Composite beef cattle. In this dataset, the new model incorporating breed composition did not increase the accuracy of genomic selection. However, the breeding values exhibited slightly less bias (as assessed by deviation of regression of phenotype on genomic breeding values from the expected value of 1). Adding additional Brahman animals to the Tropical Composite analysis increased the accuracy of genomic predictions and did not affect the accuracy of the Brahman predictions.     

Prediction of genetic values of quantitative traits with epistatic effects in plant breeding populations

Though epistasis has long been postulated to have a critical role in genetic regulation of important pathways as well as provide a major source of variation in the process of speciation, the importance of epistasis for genomic selection in the context of plant breeding is still being debated. In this paper, we report the results on the prediction of genetic values with epistatic effects for 280 accessions in the Nebraska Wheat Breeding Program using adaptive mixed least absolute shrinkage and selection operator (LASSO). The development of adaptive mixed LASSO, originally designed for association mapping, for the context of genomic selection is reported. The results show that adaptive mixed LASSO can be successfully applied to the prediction of genetic values while incorporating both marker main effects and epistatic effects. Especially, the prediction accuracy is substantially improved by the inclusion of two-locus epistatic effects (more than onefold in some cases as measured by cross-validation correlation coefficient), which is observed for multiple traits and planting locations. This points to significant potential in using non-additive genetic effects for genomic selection in crop breeding practices.     

Genomic prediction of cotton fibre quality and yield traits using Bayesian regression methods

Genomic selection or genomic prediction (GP) has increasingly become an important molecular breeding technology for crop improvement. GP aims to utilise genome-wide marker data to predict genomic breeding value for traits of economic importance. Though GP studies have been widely conducted in various crop species such as wheat and maize, its application in cotton, an essential renewable textile fibre crop, is still significantly underdeveloped. We aim to develop a new GP-based breeding system that can improve the efficiency of our cotton breeding program. This article presents a GP study on cotton fibre quality and yield traits using 1385 breeding lines from the Commonwealth Scientific and Industrial Research Organisation (CSIRO, Australia) cotton breeding program which were genotyped using a high-density SNP chip that generated 12,296 informative SNPs. The aim of this study was twofold: (1) to identify the models and data sources (i.e. genomic and pedigree) that produce the highest prediction accuracies; and (2) to assess the effectiveness of GP as a selection tool in the CSIRO cotton breeding program. The prediction analyses were conducted under various scenarios using different Bayesian predictive models. Results highlighted that the model combining genomic and pedigree information resulted in the best cross validated prediction accuracies: 0.76 for fibre length, 0.65 for fibre strength, and 0.64 for lint yield. Overall, this work represents the largest scale genomic selection studies based on cotton breeding trial data. Prediction accuracies reported in our study indicate the potential of GP as a breeding tool for cotton. The study highlighted the importance of incorporating pedigree and environmental factors in GP models to optimise the prediction performance.Subject terms: Plant breeding, Genome     

Indirect genetic effects in a sex‐limited trait: the case of breeding time in red‐billed gulls

Female reproductive performance can be strongly affected by male care, so that breeding time, a trait expressed only by females, can be seen as one trait determined by both male and female genotypes. Animal model analyses of a 46‐year study of red‐billed gulls (Larus novaehollandiae scopulinus) revealed that laying date was not heritable in females (h² = 0.001 ± 0.030), but significantly so in males (h² = 0.134 ± 0.029). Heritability of breeding time in males probably reflects genetic variability in some other trait such as courtship feeding ability. In line with predictions of evolutionary models incorporating indirect genetic effects, the strong and consistent directional selection for advanced breeding time has not resulted in detectable selection response in males. Our results demonstrate that a female trait is largely determined by genetic characteristics of its mate, and hence, any evolutionary change in red‐billed gull breeding time depends critically on genetic variation in males.     

INFLUENCE OF POLLINATION SPECIALIZATION AND BREEDING SYSTEM ON FLORAL INTEGRATION AND PHENOTYPIC VARIATION IN IPOMOEA

Natural selection should reduce phenotypic variation and increase integration of floral traits involved in placement of pollen grains on stigmas. In this study, we examine the role of pollinators and breeding system on the evolution of floral traits by comparing the patterns of floral phenotypic variances and covariances in 20 Ipomoea species that differ in their level of pollination specialization and pollinator dependence incorporating phylogenetic relatedness. Plants with specialized pollination (i.e., those pollinated by one functional group or by few morphospecies) displayed less phenotypic variation and greater floral integration than generalist plants. Self‐compatible species also displayed greater floral integration than self‐incompatible species. Floral traits involved in pollen placement and pick up showed less variation and greater integration than floral traits involved in pollinator attraction. Analytical models indicate that both breeding system and the number of morphospecies had significant effects on floral integration patterns although only differences in the former were significant after accounting for phylogeny. These results suggest that specialist/self‐compatible plants experience more consistent selection on floral traits than generalist/self‐incompatible plants. Furthermore, pollinators and breeding system promote integration of floral traits involved in pollen placement and pick up rather than integration of the whole flower.     

Successes and failures of small ruminant breeding programmes in the tropics: a review

Despite the large numbers and importance of adapted indigenous sheep and goats in the tropics, information on sustainable conventional breeding programmes for them is scarce and often unavailable. This paper reviews within-breed selection strategies for indigenous small ruminants in the tropics, highlighting aspects determining their success or failure. The aim is to better understand opportunities for genetic improvement of small ruminants by the resource-poor farmers in traditional smallholder and pastoral farming systems. Dismal performance of programmes involving breed substitution of exotics for indigenous breeds and crossbreeding with temperate breeds have stimulated a recent re-orientation of breeding programmes in tropical countries to utilize indigenous breeds, and most programmes are incipient. The success rate of some breeding programmes involving native breeds is encouraging. Definition of comprehensive breeding objectives incorporating the specific, immediate, and long-term social and economic circumstances of the target group as well as ecological constraints was found lacking in some projects that failed. To achieve success, it is necessary to look at the production system holistically, and involve the producer at every stage in the planning and operation of the breeding programme, integrating traditional behaviour and values.     

Quantitative trait loci mapping for canine hip dysplasia and its related traits in UK Labrador Retrievers

Background

Canine hip dysplasia (CHD) is characterised by a malformation of the hip joint, leading to osteoarthritis and lameness. Current breeding schemes against CHD have resulted in measurable but moderate responses. The application of marker-assisted selection, incorporating specific markers associated with the disease, or genomic selection, incorporating genome-wide markers, has the potential to dramatically improve results of breeding schemes. Our aims were to identify regions associated with hip dysplasia or its related traits using genome and chromosome-wide analysis, study the linkage disequilibrium (LD) in these regions and provide plausible gene candidates. This study is focused on the UK Labrador Retriever population, which has a high prevalence of the disease and participates in a recording program led by the British Veterinary Association (BVA) and The Kennel Club (KC).

Results

Two genome-wide and several chromosome-wide QTLs affecting CHD and its related traits were identified, indicating regions related to hip dysplasia.

Conclusion

Consistent with previous studies, the genetic architecture of CHD appears to be based on many genes with small or moderate effect, suggesting that genomic selection rather than marker-assisted selection may be an appropriate strategy for reducing this disease.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-833) contains supplementary material, which is available to authorized users.     

The impacts of inbreeding,drift and selection on genetic diversity in captive breeding populations

The goal of captive breeding programmes is often to maintain genetic diversity until re‐introductions can occur. However, due in part to changes that occur in captive populations, approximately one‐third of re‐introductions fail. We evaluated genetic changes in captive populations using microsatellites and mtDNA. We analysed six populations of white‐footed mice that were propagated for 20 generations using two replicates of three protocols: random mating (RAN), minimizing mean kinship (MK) and selection for docility (DOC). We found that MK resulted in the slowest loss of microsatellite genetic diversity compared to RAN and DOC. However, the loss of mtDNA haplotypes was not consistent among replicate lines. We compared our empirical data to simulated data and found no evidence of selection. Our results suggest that although the effects of drift may not be fully mitigated, MK reduces the loss of alleles due to inbreeding more effectively than random mating or docility selection. Therefore, MK should be preferred for captive breeding. Furthermore, our simulations show that incorporating microsatellite data into the MK framework reduced the magnitude of drift, which may have applications in long‐term or extremely genetically depauperate captive populations.     

Congruence between selection on breeding values and farmers' selection criteria in sheep breeding under conventional nucleus breeding schemes

Designing breeding schemes suitable for smallholder livestock production systems in developing regions has hitherto been a challenge. The suggested schemes either do not address farmers' breeding goals (centralized station-based nucleus schemes) or yield slow genetic progress (village-based schemes). A new breeding scheme that integrates the merits of previously suggested schemes has been designed for Menz sheep improvement in Ethiopia. It involves selection based on breeding values in nucleus flocks to produce elite rams, a one-time only provision of improved rams to villagers and a follow-up village-based selection to sustain genetic progress in village flocks. Here, we assessed whether conventional selection of breeding rams based on breeding values for production traits, which is the practice in station-based nucleus flocks, meets farmers' breeding objectives. We also elicited determinants of farmers' ram choice. Low but significant correlations were found between rankings of rams based on farmers' selection criteria, estimated breeding values (EBV) and body weight (BW). Appearance traits (such as color and horn) and meat production traits (BW and linear size traits) significantly determined farmers' breeding ram choice. The results imply that conventional selection criteria based solely on EBV for production traits do not address farmers' trait preferences fully, but only partially. Thus, a two-stage selection procedure involving selection on breeding values in nucleus centers followed by farmers' selection among top- ranking candidate rams is recommended. This approach accommodates farmers' preferences and speeds up genetic progress in village-based selection. The Menz sheep scheme could be applied elsewhere with similar situations to transform conventional station-based nucleus breeding activities into participatory breeding programs.     

Why breeding time has not responded to selection for earlier breeding in a songbird population

A crucial assumption underlying the breeders' equation is that selection acts directly on the trait of interest, and not on an unmeasured environmental factor which affects both fitness and the trait. Such an environmentally induced covariance between a trait and fitness has been repeatedly proposed as an explanation for the lack of response to selection on avian breeding time. We tested this hypothesis using a long-term dataset from a Dutch great tit (Parus major) population. Although there was strong selection for earlier breeding in this population, egg-laying dates have changed only marginally over the last decades. Using a so-called animal model, we quantified the additive genetic variance in breeding time and predicted breeding values for females. Subsequently, we compared selection at the phenotypic and genetic levels for two fitness components, fecundity and adult survival. We found no evidence for an environmentally caused covariance between breeding time and fitness or counteracting selection on the different fitness components. Consequently, breeding time should respond to selection but the expected response to selection was too small to be detected.     

Prediction of effects of beef selection indexes on greenhouse gas emissions

Genetic improvement in production efficiency traits can also drive reduction in greenhouse gas emissions. This study used international ‘best-practice’ methodology to quantify the improvements in system-wide CO₂ equivalent emissions per unit of genetic progress in the Irish Maternal Replacement (MR) and Terminal (T) beef cattle indexes. Effects of each index trait on system gross emissions (GE) and system emissions intensity (EI) were modelled by estimating effects of trait changes on per-animal feed consumption and associated methane production, per-animal meat production and numbers of animals in the system. Trait responses to index selection were predicted from linear regression of individual bull estimated breeding values for each index trait on their MR or T index value, and the resulting regression coefficients were used to calculate trait-wise responses in GE and EI from index selection. Summed over all trait responses, the MR index was predicted to reduce system GE by 0.810 kg CO₂e/breeding cow per year per € index and system EI by 0.009 kg CO₂e/kg meat per breeding cow per year per € index. These reductions were mainly driven by improvements in cow survival, reduced mature cow maintenance feed requirements, shorter calving interval and reduced offspring mortality. The T index was predicted to reduce system EI by 0.021 kg CO₂e/kg meat per breeding cow per year per € index, driven by increased meat production from improvements in carcass weight, conformation and fat. Implications for incorporating an EI reduction index to the current production indexes and long-term projections for national breeding programs are discussed.     

Fitness Consequences of Timing of Migration and Breeding in Cormorants

In most bird species timing of breeding affects reproductive success whereby early breeding is favoured. In migratory species migration time, especially arrival at the breeding grounds, and breeding time are expected to be correlated. Consequently, migration time should also have fitness consequences. However, in contrast to breeding time, evidence for fitness consequences of migration time is much more limited. Climate change has been shown to negatively affect the synchrony between trophic levels thereby leading to directional selection on timing but again direct evidence in avian migration time is scarce. We here analysed fitness consequences of migration and breeding time in great cormorants and tested whether climate change has led to increased selection on timing using a long-term data set from a breeding colony on the island of Vorsø (Denmark). Reproductive success, measured as number of fledglings, correlated with breeding time and arrival time at the colony and declined during the season. This seasonal decline became steeper during the study period for both migration and breeding time and was positively correlated to winter/spring climate, i.e. selection was stronger after warmer winters/springs. However, the increasing selection pressure on timing seems to be unrelated to climate change as the climatic variables that were related to selection strength did not increase during the study period. There is indirect evidence that phenology or abundances of preferred prey species have changed which could have altered selection on timing of migration and breeding.     

Genomic selection using beef commercial carcass phenotypes

In this study, an industry terminal breeding goal was used in a deterministic simulation, using selection index methodology, to predict genetic gain in a beef population modelled on the UK pedigree Limousin, when using genomic selection (GS) and incorporating phenotype information from novel commercial carcass traits. The effect of genotype–environment interaction was investigated by including the model variations of the genetic correlation between purebred and commercial cross-bred performance (ρ_X). Three genomic scenarios were considered: (1) genomic breeding values (GBV)+estimated breeding values (EBV) for existing selection traits; (2) GBV for three novel commercial carcass traits+EBV in existing traits; and (3) GBV for novel and existing traits plus EBV for existing traits. Each of the three scenarios was simulated for a range of training population (TP) sizes and with three values of ρ_X. Scenarios 2 and 3 predicted substantially higher percentage increases over current selection than Scenario 1. A TP of 2000 sires, each with 20 commercial progeny with carcass phenotypes, and assuming a ρ_X of 0.7, is predicted to increase gain by 40% over current selection in Scenario 3. The percentage increase in gain over current selection increased with decreasing ρ_X; however, the effect of varying ρ_X was reduced at high TP sizes for Scenarios 2 and 3. A further non-genomic scenario (4) was considered simulating a conventional population-wide progeny test using EBV only. With 20 commercial cross-bred progenies per sire, similar gain was predicted to Scenario 3 with TP=5000 and ρ_X=1.0. The range of increases in genetic gain predicted for terminal traits when using GS are of similar magnitude to those observed after the implementation of BLUP technology in the United Kingdom. It is concluded that implementation of GS in a terminal sire breeding goal, using purebred phenotypes alone, will be sub-optimal compared with the inclusion of novel commercial carcass phenotypes in genomic evaluations.     

Goals and hurdles for a successful implementation of genomic selection in breeding programme for selected annual and perennial crops

Genomic Selection is an important topic in quantitative genetics and breeding. Not only does it allow the full use of current molecular genetic technologies, it stimulates also the development of new methods and models. Genomic selection, if fully implemented in commercial farming, should have a major impact on the productivity of various agricultural systems. But suggested approaches need to be applicable in commercial breeding populations. Many of the published research studies focus on methodologies. We conclude from the reviewed publications, that a stronger focus on strategies for the implementation of genomic selection in advanced breeding lines, introduction of new varieties, hybrids or multi-line crosses is needed. Efforts to find solutions for a better prediction and integration of environmental influences need to continue within applied breeding schemes. Goals of the implementation of genomic selection into crop breeding should be carefully defined and crop breeders in the private sector will play a substantial part in the decision-making process. However, the lack of published results from studies within, or in collaboration with, private companies diminishes the knowledge on the status of genomic selection within applied breeding programmes. Studies on the implementation of genomic selection in plant breeding need to evaluate models and methods with an enhanced emphasis on population-specific requirements and production environments. Adaptation of methods to breeding schemes or changes to breeding programmes for a better integration of genomic selection strategies are needed across species. More openness with a continuous exchange will contribute to successes.     

Quantitative Genetics in the Genomics Era

The genetic analysis of quantitative or complex traits has been based mainly on statistical quantities such as genetic variances and heritability. These analyses continue to be developed, for example in studies of natural populations. Genomic methods are having an impact on progress and prospects. Actual relationships of individuals can be estimated enabling novel quantitative analyses. Increasing precision of linkage mapping is feasible with dense marker panels and designed stocks allowing multiple generations of recombination, and large SNP panels enable the use of genome wide association analysis utilising historical recombination. Whilst such analyses are identifying many loci for disease genes and traits such as height, typically each individually contributes a small amount of the variation. Only by fitting all SNPs without regard to significance can a high proportion be accounted for, so a classical polygenic model with near infinitesimally small effects remains a useful one. Theory indicates that a high proportion of variants will have low minor allele frequency, making detection difficult. Genomic selection, based on simultaneously fitting very dense markers and incorporating these with phenotypic data in breeding value prediction is revolutionising breeding programmes in agriculture and has a major potential role in human disease prediction.