- Genomic relatedness describes the genetic similarity between animals estimated from their DNA rather than inferred only from recorded pedigree relationships. It is an important concept in modern animal breeding, quantitative genetics, population genetics, and genomic selection because it provides information about the genetic material that animals actually share across their genomes.
- Traditional pedigree-based relatedness describes the expected relationship between animals based on their common ancestry. Genomic relatedness, in contrast, uses genetic markers such as single nucleotide polymorphisms (SNPs) to estimate the degree of genetic similarity that is actually observed in the genome. This distinction is important because relatives do not inherit exactly the same chromosome segments. Genomic information can therefore reveal differences between the expected relationship from a pedigree and the realized relationship observed from DNA.
- Genomic relatedness is closely connected to genetic relationship, coefficient of relationship, kinship, coancestry, identity by descent, identity by state, inbreeding, genomic inbreeding, runs of homozygosity, and the genomic relationship matrix. Although these concepts are related, they describe different aspects of genetic similarity and should not be treated as interchangeable.
- The basic principle behind genomic relatedness is straightforward. Every animal carries a genome inherited from its parents. Because of segregation and recombination, each offspring receives a unique combination of chromosome segments. Two relatives therefore share some genomic segments because of common ancestry, but the amount and location of those shared segments vary among pairs of relatives.
- For example, two full siblings have an expected additive genetic relationship of approximately 0.50. This does not mean that every pair of full siblings shares exactly 50% of their genome. Instead, 0.50 represents the expected relationship under standard assumptions. Their actual genomic relationship may be higher or lower because of the random inheritance of chromosome segments.
- Genomic relatedness attempts to capture this realized variation.
- One of the most important tools for representing genomic relationships among animals is the genomic relationship matrix, commonly called the G matrix. Each element of the matrix represents an estimate of the genetic relationship between two animals based on genomic marker information.
- A genomic relationship matrix can be represented conceptually as:
- G = [g(i,j)]
- where g(i,j) represents the estimated genomic relationship between animals i and j.
- The exact mathematical calculation of the G matrix depends on the marker coding system, allele-frequency estimates, scaling method, reference population, quality-control procedures, and statistical model used. Therefore, genomic relationship values should always be interpreted according to the specific method used to construct the matrix.
- A common approach uses SNP markers coded according to the number of copies of a reference allele carried by each animal. For a marker, an animal may therefore have a genotype represented as 0, 1, or 2. The marker genotypes are then centered around allele frequencies so that relationships reflect similarity relative to the reference population.
- One commonly used form of genomic relationship estimation can be expressed conceptually as:
- G = ZZ’ / [2Σp(k)(1-p(k))]
- where Z is a matrix of centered genotype values, p(k) is the allele frequency at marker k, and the denominator scales the relationship according to expected genetic variance at the markers.
- Different genomic relationship methods use different scaling and allele-frequency assumptions. Consequently, two analyses can produce somewhat different genomic relationship values even when they use the same animals and markers. This does not necessarily indicate an error; it can reflect differences in methodology and reference population.
- The most important difference between pedigree-based relatedness and genomic relatedness is therefore the source of information. Pedigree relationships are calculated from recorded ancestry, whereas genomic relationships are estimated from observed DNA markers.
- Pedigree-based relationships are expectations based on inheritance rules. Genomic relationships provide information about the genetic similarity actually observed at the markers used in the analysis.
- Consider two full siblings. Pedigree analysis may assign them an expected relationship of approximately 0.50. Genomic analysis may indicate that one sibling pair has a relationship somewhat above this expectation while another pair has a relationship somewhat below it. This occurs because each sibling receives a different random sample of the chromosome segments carried by the parents.
- This is one of the major advantages of genomic relatedness. It captures Mendelian sampling and realized inheritance that cannot be completely predicted from a conventional pedigree.
- Genomic relatedness can also identify animals that appear unrelated from their recorded pedigree but are genetically similar. This can occur when pedigrees are incomplete, when common ancestry occurred before the recorded pedigree began, or when parentage information contains errors.
- For example, two animals may have no known common ancestor within a five-generation pedigree and therefore be treated as unrelated in a pedigree relationship matrix. However, genomic analysis may reveal that they share many genomic segments because they actually descend from common ancestors that are not represented in the available pedigree.
- This is sometimes described as cryptic relatedness.
- Genomic relatedness can therefore be particularly valuable in populations where pedigrees are incomplete or unreliable. It provides an additional source of information that does not depend entirely on recorded ancestry.
- The concept of identity by descent (IBD) is central to understanding genomic relatedness. Two animals share a genomic segment by identity by descent when that segment originated from the same ancestral chromosome segment and was inherited through their respective lineages.
- However, DNA markers do not always directly establish IBD in a simple way. Animals can also share the same allele because it is common in the population without inheriting it from the same ancestral copy. This is known as identity by state (IBS).
- This distinction is important because genomic similarity at individual markers does not automatically mean that the same allele is identical by descent. Statistical methods use information across many markers and, in some analyses, haplotype structure and genomic segments to distinguish patterns of relatedness.
- Kinship and coancestry are also closely related to genomic relatedness. The kinship coefficient describes the probability that an allele randomly selected from one individual and an allele randomly selected from another individual are identical by descent under the relevant definition.
- Under the conventional diploid relationship definition:
- r(i,j) = 2 × φ(i,j)
- where r(i,j) is the coefficient of relationship and φ(i,j) is the kinship coefficient.
- Genomic data can be used to estimate realized versions of these relationships rather than relying only on pedigree expectations.
- The distinction between kinship, relationship, and genomic relationship is therefore important. Kinship is usually expressed as a probability or coefficient associated with identity by descent. The conventional relationship coefficient is commonly twice kinship. Genomic relationship refers to relationship estimated from observed marker data using a particular genomic relationship methodology.
- Genomic relatedness is also closely connected to genomic inbreeding. Inbreeding is a within-individual concept, whereas genomic relatedness generally describes relationships between individuals. However, genomic relationships among prospective parents can be used to estimate the expected genetic similarity between them and therefore help predict the potential inbreeding of their offspring.
- For proposed sire and dam:
- E(F_offspring) ≈ genomic kinship(sire, dam)
- under the corresponding genomic relationship definition and appropriate assumptions.
- If the genomic relationship is expressed using the conventional relationship scale, a corresponding approximation is:
- E(F_offspring) ≈ genomic relationship(sire, dam) / 2
- The exact interpretation depends on the scaling and reference population used to construct the genomic relationship matrix, so these relationships should not be applied mechanically across different genomic methods.
- Another important genomic measure is runs of homozygosity (ROH). ROH are long stretches of the genome in which an animal carries two copies of highly similar or identical haplotypes. They can provide information about historical and recent common ancestry.
- Long ROH often indicate relatively recent shared ancestry, while shorter ROH can reflect more distant ancestral relationships. However, ROH interpretation depends on marker density, population history, genome structure, filtering thresholds, and analytical methods.
- Genomic relatedness and ROH therefore provide complementary information. A genomic relationship matrix summarizes genetic similarity across many markers, while ROH analysis focuses on contiguous homozygous genomic segments and can provide additional insight into the history of autozygosity and inbreeding.
- One of the most important applications of genomic relatedness is genomic selection. Genomic selection uses genome-wide marker information to improve the prediction of breeding values. Instead of relying only on pedigree relationships and phenotypic records, genomic evaluation can use the realized genetic relationships among animals.
- The genomic relationship matrix can be incorporated into statistical models used to estimate genomic estimated breeding values (GEBVs). In many modern breeding programs, genomic information can increase the accuracy of genetic evaluation, particularly for young animals that have little or no own performance or progeny information.
- Genomic relatedness can also improve the identification of relatives. When animals are genotyped, their genetic similarity can be estimated directly from marker information. This can help confirm parentage, identify unexpected relationships, and improve the accuracy of breeding databases.
- Parentage verification is particularly useful when pedigree records are uncertain. Genomic testing can determine whether candidate parents are genetically compatible with an offspring. Correct parentage improves the quality of the pedigree and subsequently improves relationship matrices and genetic evaluations.
- Genomic relatedness is also useful for mate allocation. A breeding program may seek animals with high genetic merit while avoiding mating combinations that would produce excessive relatedness. Genomic relationships can provide more accurate information about the actual genetic similarity of potential mating pairs than pedigree relationships alone.
- This becomes particularly important when pedigrees are incomplete. If two animals are apparently unrelated based on the pedigree but show substantial genomic relatedness, a breeding program can take that information into account before mating them.
- Genomic information can also help manage the rate of inbreeding. Instead of simply avoiding animals that appear closely related in the pedigree, breeding programs can use genomic relationships to identify mating combinations that balance genetic merit and expected genetic diversity.
- This is especially valuable in populations experiencing a popular sire effect, where a small number of highly selected animals contribute disproportionately to future generations. Extensive use of a few genetically successful individuals can increase genomic relatedness throughout the population even when individual pedigree relationships initially appear acceptable.
- Genomic relatedness is also relevant to optimal contribution selection. In this approach, breeding contributions from selected animals are optimized to achieve genetic improvement while controlling the accumulation of inbreeding and preserving genetic diversity.
- Genomic information can make this process more precise because it provides information about realized relationships rather than only expected pedigree relationships.
- Another important application is the management of genetic diversity. Genetic diversity is essential for long-term adaptation, population health, resilience, and continued genetic improvement. A breeding program that focuses exclusively on short-term selection response can unintentionally increase relatedness and reduce diversity.
- Genomic relatedness allows breeders to monitor how genetically similar animals are across the genome and can help identify individuals carrying genetic diversity that is less common in the population.
- This information can be particularly valuable in conservation genetics. Small populations are vulnerable to genetic drift, loss of genetic variation, and accumulation of inbreeding. Genomic relatedness can provide a more detailed picture of population structure and genetic diversity than pedigree information alone.
- For conservation breeding, genomic information can help identify animals that are genetically distinct from the majority of the population and may therefore contribute useful diversity to future generations. However, genetic distinctness should not be considered the only selection criterion. Fitness, health, reproductive ability, adaptation, and population objectives also need to be considered.
- Genomic relatedness is also important for understanding population structure. Animals belonging to different breeds, strains, lines, or geographical populations may show different genomic relationships. Genomic analysis can reveal clusters of genetically similar individuals and can help identify admixture and ancestry patterns.
- This information can be useful when managing crossbreeding programs. Genetic relationships between breeds can help breeders understand the degree of genetic differentiation among populations and plan crosses that combine complementary traits while maintaining appropriate genetic diversity.
- Genomic relatedness can also contribute to the study of heterosis, or hybrid vigor. Crossbred animals often perform differently from their parental populations, particularly for traits related to fitness. Genomic information can help characterize genetic differences among populations and contribute to the design and evaluation of crossbreeding strategies.
- The accuracy of genomic relatedness depends strongly on the quality and characteristics of the genomic data. Factors such as SNP density, marker distribution, genotyping errors, missing genotypes, allele frequencies, population structure, linkage disequilibrium, and quality-control procedures can influence relationship estimates.
- Genotyping quality control is therefore an important part of genomic analysis. Poor-quality markers or incorrect genotype calls can affect genomic relationship estimates and consequently influence genetic evaluations.
- Allele frequency is particularly important because many genomic relationship methods center marker genotypes around allele frequencies. The reference population used to estimate those frequencies can therefore influence the scale and interpretation of genomic relationships.
- Population structure can also influence genomic relationships. If animals come from genetically differentiated populations, genomic similarity may reflect both family-level relatedness and broader population differences.
- For this reason, genomic relationship estimates should always be interpreted in the context of the reference population and statistical method used.
- Pedigree and genomic relationships are not necessarily competing approaches. In modern animal breeding, they are often complementary.
- The pedigree relationship matrix is commonly called the A matrix, while the genomic relationship matrix is commonly called the G matrix. The A matrix represents expected relationships based on pedigree, while the G matrix represents relationships estimated from genomic information.
- Some genetic evaluation systems combine pedigree and genomic information into a single-step genomic evaluation. Single-step methods allow phenotypic, pedigree, and genomic information to be analyzed jointly, making it possible to use genomic information even when only a subset of the population has been genotyped.
- The integration of pedigree and genomic information can be particularly useful because pedigrees provide multigenerational structure while genomic data provide realized relationships. Together, they can improve the accuracy and consistency of genetic evaluation.
- Genomic relatedness also has applications in estimating genetic parameters. Genetic variance, covariance, heritability, and genetic correlations can be estimated using genomic relationships in appropriate statistical models.
- For example, if two animals are genetically similar but experience different environments, their phenotypic similarity can provide information about genetic effects while helping separate those effects from environmental variation. This can be especially valuable for complex traits that are difficult to evaluate using pedigree information alone.
- However, genomic relatedness does not eliminate the need to account for environmental effects. Animals can share genomic similarity while living in very different environments, and genetically unrelated animals can share the same environment.
- The phenotype of an animal can still be represented conceptually as:
- P = G + E
- where P is the observed phenotype, G represents genetic effects, and E represents environmental effects.
- In more complex models, additional terms may be included for maternal effects, common environmental effects, genotype–environment interaction, permanent environmental effects, and other sources of variation.
- Genomic information therefore improves the measurement of genetic relationships but does not replace careful phenotyping and appropriate statistical modeling.
- One of the most important limitations of genomic relatedness is that genomic relationships are not necessarily universal numbers independent of methodology. A genomic relationship of a particular value can have different interpretations depending on how the matrix was constructed, which allele frequencies were used, what population served as the reference, and how genotypes were coded.
- Therefore, genomic relationship values should not automatically be compared across different studies or software packages without checking the underlying definitions and scaling.
- Another limitation is that marker-based genomic relationships represent similarity at the measured markers rather than direct observation of every base pair in the genome. The accuracy with which marker relationships represent genome-wide relationships depends on marker density, linkage disequilibrium, population structure, and the traits or genomic regions being considered.
- Genomic relatedness can also be affected by population stratification. Animals from different breeds may have very different allele frequencies, and a genomic relationship measure can capture breed differences as well as more recent family relationships.
- For this reason, genomic relationship matrices need to be constructed and interpreted carefully in multi-breed populations.
- It is also important not to interpret genomic relatedness as a direct measure of phenotypic similarity. Two animals may be genomically related but perform differently because of environmental conditions, management, nutrition, disease exposure, age, sex, epigenetic effects, and random genetic effects.
- Similarly, animals with low genomic relatedness can have similar phenotypes because of convergent selection or similar environments.
- Genomic relatedness is therefore fundamentally a measure of genetic similarity, not a direct measure of similarity in appearance, productivity, health, or behaviour.
- In practical breeding programs, genomic relatedness can be integrated with estimated breeding values, phenotypic records, pedigree information, reproductive records, health information, and economic weights. This allows breeding decisions to consider both genetic merit and population management.
- For example, a breeder might compare two candidate sires with similar GEBVs. If one sire has high genomic relatedness with most of the breeding females while the other is less related, the second sire may provide a useful opportunity to maintain genetic diversity without sacrificing substantial genetic merit.
- Similarly, if an animal has an exceptionally high breeding value but is closely related to many animals already heavily represented in the population, breeders may limit its reproductive contribution rather than using it without restriction.
- This illustrates an important principle of modern animal breeding: the best breeding animal is not necessarily the animal with the highest individual breeding value. The optimal choice depends on the breeding objective, the genetic merit of the animal, its relationships with the population, expected contribution to future generations, and the need to control inbreeding.
- Genomic relatedness can therefore contribute to a more sustainable balance between genetic gain and genetic diversity.
- The technology is particularly valuable for traits with long generation intervals or traits that are difficult, expensive, or impossible to measure early in life. Genomic information allows relationships and breeding values to be evaluated earlier, potentially reducing the generation interval and increasing the rate of genetic improvement.
- However, rapid genetic gain should not be pursued without considering population health. If genomic selection is focused narrowly on a small number of economically important traits, the population may experience increased relatedness or unfavorable correlated responses.
- A balanced breeding objective should therefore consider production, fertility, health, survival, longevity, welfare, adaptation, resilience, and genetic diversity where appropriate.
- Genomic relatedness also contributes to precision livestock breeding by enabling more detailed characterization of genetic structure. As genotyping becomes more accessible, breeding programs can increasingly combine genomic relationships with large-scale phenotyping and automated data collection.
- Modern technologies such as high-density SNP genotyping, sequencing, automated phenotyping, and genomic prediction are making it possible to characterize genetic relationships at a level that was previously impossible using pedigrees alone.
- Nevertheless, the pedigree remains valuable. It provides information about ancestry that genomic markers may not fully capture, especially when analyzing generations beyond the available genotyping data. Pedigree information can also be essential for defining population structure, breed identity, historical ancestry, and long-term genetic relationships. The most effective approach is therefore often an integrated pedigree-genomic strategy.
- Pedigree-based relatedness answers the question: What genetic relationship is expected from the recorded ancestry?
- Genomic relatedness answers a complementary question: What genetic relationship is observed from the available genomic information?
- Both perspectives are valuable. The difference between expected and realized relationships is especially important in family-based breeding. Parent-offspring, full-sib, half-sib, and other relationships have characteristic expected values, but genomic data reveal the actual variation around those expectations.
- For example, full siblings have an expected relationship of approximately 0.50, but their realized genomic relationship can differ from 0.50. Half-siblings have an expected relationship of approximately 0.25, but again, the realized relationship varies.
- This variation is a natural consequence of Mendelian inheritance and recombination rather than an error in the pedigree.
- Genomic relatedness can therefore be viewed as a bridge between population genetics theory and the actual genomes of individual animals.
- Its importance will continue to increase as breeding programs move toward more integrated systems involving genomic selection, automated phenotyping, precision livestock farming, reproductive technologies, and advanced genetic evaluation.
- Ultimately, genomic relatedness provides a powerful way to understand how animals are genetically connected. It complements pedigree-based relationships by measuring genetic similarity from DNA markers, helps reveal realized inheritance, supports genomic relationship matrices, improves genetic evaluation, assists inbreeding management, and contributes to the conservation of genetic diversity.
- The central principle is that pedigrees describe expected genetic relationships based on ancestry, whereas genomic data provide evidence about realized genetic relationships across the measured genome. Using both sources together allows animal breeders to make more accurate and sustainable decisions about selection, mating, genetic gain, inbreeding, and long-term population management.
