- Breeding value is one of the most important concepts in quantitative genetics and animal breeding because it describes an animal’s genetic merit for transmitting desirable traits to its offspring. While an animal’s observed performance is influenced by both genetics and the environment, the breeding value focuses specifically on the additive genetic component that can be passed predictably from parents to their progeny. Breeding values therefore provide the foundation for genetic selection, estimated breeding values, genomic evaluation, and long-term genetic improvement in livestock and other domesticated animal populations.
- The basic relationship between phenotype, genotype, and environment can be represented as P = G + E, where P is the observed phenotypic value, G represents genetic effects, and E represents environmental effects. Genetic effects can include additive genetic effects, dominance effects, and epistatic interactions. However, breeding value is specifically associated with the additive component of genetic variation because additive effects are transmitted from parents to offspring in a predictable statistical manner. This makes breeding value more useful for selection than simply considering an animal’s total genetic or phenotypic performance.
- The additive genetic value of an animal can be thought of as the sum of the average effects of the alleles it carries for a particular trait. If many genes contribute to a trait such as body weight, milk yield, growth rate, fertility, disease resistance, or feed efficiency, the breeding value represents the cumulative additive contribution of those genes. An animal may have a high phenotypic value because of favourable genetics, favourable environmental conditions, or a combination of both. Breeding value attempts to separate the predictable genetic contribution from environmental influences and non-additive genetic effects.
- A key reason breeding values are important is that an animal does not transmit its entire genotype to each offspring. During reproduction, offspring receive one chromosome set from the sire and one from the dam, and Mendelian sampling creates differences among offspring even when they have the same parents. Consequently, the expected additive genetic value of an offspring is approximately half of the sire’s breeding value plus half of the dam’s breeding value: E(A_offspring) = (A_sire + A_dam) / 2. The actual breeding value of an individual offspring can deviate from this expectation because of Mendelian sampling.
- The distinction between phenotypic value, genotypic value, and breeding value is therefore fundamental. Phenotypic value is what can be observed or measured in an animal, while genotypic value represents the animal’s total genetic contribution, including additive, dominance, and epistatic effects. Breeding value represents the additive genetic component that is expected to be transmitted to the next generation. An animal with an excellent phenotype is not necessarily the animal with the highest breeding value if its performance is strongly influenced by environmental conditions or non-additive genetic effects.
- The amount of additive genetic variation available in a population is central to the usefulness of breeding values. Additive genetic variance is the component of genetic variation that contributes directly to differences in breeding values among animals. When additive genetic variance is present, selection can change the population mean because animals with favourable breeding values can contribute disproportionately to the next generation. If additive genetic variation is very limited, the potential for long-term response to selection is also reduced.
- Heritability is closely related to breeding value because it describes the proportion of phenotypic variance attributable to additive genetic variance. Narrow-sense heritability is expressed as h² = σ²_A / σ²_P, where σ²_A is additive genetic variance and σ²_P is phenotypic variance. Traits with higher heritability generally provide more information about an animal’s breeding value from its own phenotype, although heritability does not determine whether a trait is biologically or economically important. A low-heritability trait can still respond to selection when accurate information from relatives, repeated records, progeny, indicator traits, or genomic data is available.
- An important practical distinction is between the true breeding value and the estimated breeding value (EBV). The true breeding value is a theoretical genetic quantity that is generally unknown because it cannot be observed directly. An EBV is an estimate of that breeding value based on available information. This information may include the animal’s own performance, pedigree relationships, relatives’ records, progeny performance, repeated measurements, correlated traits, and genomic information.
- The accuracy of an EBV depends on the amount and quality of information available. Selection accuracy describes the correlation between the estimated breeding value and the true breeding value. More accurate evaluations allow breeders to distinguish genetically superior animals from animals whose high observed performance is mainly due to environmental advantages. Accuracy can be improved by increasing the number of relevant records, using information from relatives, recording performance under appropriate contemporary groups, incorporating multiple traits, and using genomic information when suitable reference populations are available.
- Contemporary groups are particularly important when estimating breeding values from performance records. Animals should be compared with appropriate peers that have experienced similar management, feeding, housing, climate, health conditions, and other systematic environmental influences. Without appropriate environmental adjustment, an animal raised under unusually favourable conditions could appear genetically superior even when its underlying breeding value is not exceptional. Modern genetic evaluations therefore attempt to separate systematic environmental effects from genetic differences among animals.
- Pedigree information provides another important source of information for estimating breeding values. The pedigree relationship matrix, commonly represented as the A matrix, describes expected genetic relationships among animals based on their known ancestry. An animal’s relatives provide information about its genetic merit because relatives share genes inherited from common ancestors. The usefulness of pedigree information depends on the completeness and accuracy of the pedigree and on the number and quality of performance records available throughout the connected population.
- Family information is particularly valuable when a trait is difficult to measure directly on selection candidates. Family selection, within-family selection, and combined selection can use information from full siblings, half siblings, parents, and other relatives. Family information can be especially useful for traits expressed only in one sex, traits measured after reproductive maturity, expensive traits, carcass traits that require slaughter, or disease-related traits for which direct measurement on elite breeding animals may be undesirable.
- Progeny testing provides another powerful source of information for estimating breeding value. Instead of relying only on the candidate’s own phenotype, breeders evaluate the performance of its offspring and use those records to infer the parent’s genetic merit. Because an individual parent contributes genetic material to many offspring, progeny records can provide substantial information about its breeding value. Traditional progeny testing has therefore been important for traits such as milk production and other sex-limited or difficult-to-measure characteristics, although the long generation interval and high cost have encouraged greater use of genomic selection.
- BLUP, or Best Linear Unbiased Prediction, is one of the most important statistical approaches used for estimating breeding values in modern animal breeding. BLUP can simultaneously account for fixed environmental effects, relationships among animals, repeated records, relatives’ performance, and other sources of information. In an animal model, the general statistical structure can be represented as y = Xb + Za + e, where y is the vector of observations, b represents fixed effects, a represents random additive genetic effects or breeding values, and e represents residual effects. The matrices X and Z connect observations to the relevant effects.
- Modern genetic evaluations increasingly combine pedigree and genomic information. Genomic selection uses large numbers of genetic markers distributed across the genome to improve the prediction of breeding values. Genomic information can be represented through a genomic relationship matrix, commonly called the G matrix. When genomic and pedigree information are combined appropriately, breeders can obtain genomic estimated breeding values (GEBVs) that may be more accurate than pedigree-only evaluations, particularly for young animals that have little or no own-performance or progeny information.
- A major advantage of genomic selection is that it can increase selection accuracy at a young age. Traditionally, breeders may have needed to wait until an animal produced offspring or accumulated performance records before its genetic merit could be evaluated with high confidence. Genomic information can provide useful predictions earlier in life, potentially reducing the generation interval and increasing the rate of genetic improvement. However, genomic prediction depends strongly on the quality and size of the reference population, the relationship between reference and selection populations, marker density, trait architecture, and the quality of phenotypic records.
- The rate of genetic improvement depends not only on breeding value accuracy but also on selection intensity, genetic variation, and generation interval. A commonly used expression is ΔG/year = i × r × σ_A / L, where i is selection intensity, r is the accuracy of selection, σ_A is the additive genetic standard deviation, and L is the generation interval. This relationship illustrates why accurate breeding values are so important. Increasing the accuracy of genetic evaluation can increase genetic gain, while reducing generation interval can also accelerate improvement.
- Breeding values are used for a very wide range of traits in animal breeding. These include growth traits, body weight, mature size, carcass characteristics, milk production, milk composition, meat quality, egg production, egg quality, wool and fibre characteristics, feed intake, feed efficiency, fertility, reproductive performance, semen quality, disease resistance, health, survival, longevity, temperament, welfare-related traits, adaptation, heat tolerance, and resilience. The relative importance of these traits depends on the species, production system, environment, market, and overall breeding objective.
- Breeding values become especially important when selecting for traits that have low heritability. A low heritability means that a relatively small proportion of phenotypic variation is attributable to additive genetic differences, not that the trait is genetically unimportant or impossible to improve. For traits such as fertility, disease resistance, survival, and some welfare-related characteristics, breeders may improve prediction by combining information from relatives, repeated records, indicator traits, progeny, and genomic data.
- For binary or categorical traits, such as disease status, pregnancy outcome, survival, or certain reproductive outcomes, breeding value estimation often uses threshold models or other statistical models designed for non-continuous observations. The underlying genetic liability may be continuous even when the observed phenotype is recorded as categories such as healthy/diseased or pregnant/not pregnant. Appropriate modelling allows genetic differences in such traits to be incorporated into breeding programmes.
- Maternal effects and common environmental effects must also be considered when estimating breeding values for traits influenced by the dam or shared environments. For example, early growth can be affected not only by the offspring’s own genes but also by maternal milk production, maternal behaviour, uterine environment, and other maternal influences. Similarly, littermates may share environmental conditions that make them more similar phenotypically even when their genetic differences are not large. Ignoring these effects can result in biased estimates of genetic merit.
- Repeated records can provide additional information about breeding value for traits expressed multiple times during an animal’s life. Repeatability describes the extent to which repeated measurements on the same animal are consistent because of permanent differences among animals. Traits such as milk production, egg production, body weight, or reproductive records may benefit from repeated observations. Genetic evaluation models can separate permanent environmental effects from additive genetic effects so that repeated performance is not incorrectly interpreted as entirely genetic.
- Genetic correlations are also important when estimating and using breeding values. A genetic correlation exists when the genetic determinants of two traits are related. It can be expressed as r_A = Cov_A(X,Y) / (σ_A,X × σ_A,Y), where Cov_A(X,Y) is additive genetic covariance between traits and σ_A,X and σ_A,Y are their additive genetic standard deviations. A favourable genetic correlation can allow improvement in one trait to contribute to improvement in another, whereas an unfavourable correlation may create an undesirable correlated response.
- For this reason, breeding values are often estimated simultaneously for several traits through multi-trait genetic evaluation. Multi-trait models can use information from genetically correlated traits to improve prediction, particularly when one trait has limited records. For example, an easily measured indicator trait may provide information about the breeding value for a more difficult or expensive trait when the two traits have a sufficiently strong genetic relationship.
- Breeding values can also be incorporated into a selection index when breeders need to select animals for several traits simultaneously. A general selection index can be written as I = b₁x₁ + b₂x₂ + … + bₙxₙ, where x values represent information used for selection and b values are coefficients that determine the contribution of each information source. Selection indexes allow breeding programmes to combine information according to the breeding objective rather than selecting animals based on a single trait.
- A more formal representation of a breeding objective is H = a₁A₁ + a₂A₂ + … + aₙAₙ, where A values represent breeding values for traits and a values represent their relative importance, often derived from economic weights or other defined objective weights. This approach is particularly important in modern breeding programmes because improving a single production trait without considering fertility, health, welfare, survival, feed efficiency, or adaptation can produce undesirable long-term consequences.
- The relationship between breeding value and economic importance should therefore be clearly understood. A trait may have a high heritability but low economic importance, while another trait may have low heritability but major effects on profitability, animal welfare, or sustainability. Breeding programmes should evaluate traits according to their contribution to the overall breeding objective rather than selecting solely according to ease of measurement or heritability.
- Breeding values are also central to the management of genetic diversity. Selection programmes can achieve rapid short-term genetic progress by concentrating reproduction in a small number of genetically superior animals, but excessive concentration can increase relatedness and inbreeding. A particularly influential sire can contribute a large proportion of genes to future generations, creating a popular sire effect and reducing the effective size of the breeding population.
- The effective population size (Ne) is an important indicator of the genetic structure and rate of inbreeding in a population. Under simplified assumptions, the expected increase in inbreeding per generation can be approximated as ΔF ≈ 1 / (2Ne). A small effective population size generally results in faster accumulation of inbreeding and loss of genetic diversity. Therefore, breeding programmes should consider not only the breeding values of candidates but also their relationships and expected contribution to future generations.
- Mate allocation can help manage these competing objectives by choosing mating pairs that combine desirable genetic merit while controlling expected relatedness and inbreeding. The expected inbreeding coefficient of an offspring from a particular sire and dam can be expressed as E(F_offspring) = φ(sire, dam), where φ is the coefficient of coancestry or kinship between the parents. The expected additive genetic relationship between two individuals is approximately twice their kinship coefficient, so r ≈ 2φ under the usual pedigree relationship framework.
- Optimal contribution selection (OCS) provides another approach for balancing genetic gain and genetic diversity. Instead of selecting animals solely according to their estimated breeding values, OCS determines how much each selected animal should contribute to the next generation while considering relationships among candidates. This can help reduce excessive use of highly related animals and manage the rate of inbreeding while still achieving useful genetic improvement.
- Genomic information provides additional opportunities to monitor genetic diversity. Runs of homozygosity (ROH) are long stretches of the genome in which an individual carries homozygous segments that can reflect inheritance from common ancestors. The genomic proportion of the autosomal genome contained in ROH can be summarized as F_ROH = Total length of ROH / Total autosomal genome length. ROH information can complement pedigree-based inbreeding estimates and provide a more direct picture of recent or historical autozygosity.
- Breeding values are also relevant to the management of deleterious genetic variants. Some harmful recessive alleles can remain hidden in heterozygous carriers because they do not produce obvious effects in the carrier itself. If carriers are repeatedly mated with related carriers, homozygous offspring may occur at higher frequency, increasing the risk of genetic disorders and contributing to inbreeding depression. Genomic testing and appropriate mate allocation can help identify and manage such risks while avoiding unnecessary loss of useful genetic diversity.
- The relationship between breeding value and genotype–environment interaction (G×E) is also important. An animal with a high estimated breeding value under one production environment may not necessarily rank equally under another environment. Genetic performance can depend on climate, nutrition, management, disease pressure, housing, and production system. For traits related to heat tolerance, disease resistance, adaptation, and resilience, breeding programmes may therefore need to evaluate animals across relevant environments rather than assuming that genetic rankings are universally stable.
- The quality of breeding values depends heavily on the quality of the underlying data. Accurate phenotypic records, reliable pedigree information, appropriate contemporary groups, consistent trait definitions, sufficient sample sizes, and good data management are essential for reliable genetic evaluation. Poor measurements, systematic recording errors, incomplete pedigrees, or inappropriate environmental adjustment can reduce the accuracy of breeding values and lead to incorrect selection decisions.
- Breeding values should also be interpreted within the population and evaluation system in which they were estimated. EBVs are not necessarily directly comparable across populations or genetic evaluation systems unless appropriate methods are used to establish a common scale or account for differences in genetic base and model definitions. Breeders should therefore understand the evaluation population, reference population, trait definition, genetic base, and reliability associated with published breeding values.
- The reliability of an EBV is related to the accuracy of the estimate and indicates how much confidence can be placed in the prediction of an animal’s genetic merit. Young animals often have lower reliability because less performance and progeny information is available, while older animals with many records or offspring may have substantially higher reliability. Genomic selection can increase the reliability of young animals by adding genome-wide information before extensive performance or progeny data are available.
- Breeding values are not static measurements of an animal’s phenotype. They are statistical predictions that can change as additional information becomes available. When an animal receives new performance records, its relatives are evaluated, its progeny are recorded, or genomic information is incorporated, its EBV may be updated. Consequently, genetic evaluation is an ongoing process rather than a single permanent classification of an animal.
- The use of breeding values has transformed modern animal breeding from selection based primarily on visible performance toward selection based on predicted genetic merit. Traditional phenotypic selection remains useful, particularly for highly heritable traits that can be measured accurately and early, but modern programmes increasingly combine individual performance with pedigree, family, progeny, repeated-record, multi-trait, and genomic information.
- The greatest value of breeding values lies in their ability to support selection decisions that focus on the genetic contribution an animal is expected to make to future generations. An animal should not be selected simply because it looks superior or has a high production record. Instead, breeders seek animals with favourable estimated breeding values, high selection accuracy, appropriate genetic relationships, and a genetic profile that fits the overall breeding objective.
- A successful breeding programme must therefore balance genetic gain, animal health, fertility, survival, welfare, adaptation, economic performance, and genetic diversity. Breeding values provide the quantitative foundation for making these decisions, while tools such as BLUP, genomic selection, selection indexes, progeny testing, multi-trait evaluation, mate allocation, and optimal contribution selection provide practical methods for using that information.
- Ultimately, breeding value is a central concept connecting quantitative genetics with practical animal breeding. It translates genetic variation into a form that can be used for selection and genetic evaluation. By estimating the additive genetic merit of animals and combining that information with accurate phenotypes, pedigree records, relatives, progeny, genomic data, and appropriate statistical models, breeders can increase the accuracy and rate of genetic improvement while managing the risks associated with inbreeding and genetic concentration. The long-term goal is not simply to produce animals with higher production, but to develop populations that are genetically productive, healthy, fertile, resilient, adaptable, welfare-compatible, and genetically diverse.
