- Maternal models are important statistical tools in animal breeding and quantitative genetics used to understand how a mother influences the performance of her offspring. In livestock populations, traits such as birth weight, weaning weight, growth rate, survival, and early development can be influenced not only by the genes an offspring inherits directly but also by the maternal environment provided by its dam. Maternal models help researchers separate these different sources of variation, allowing more accurate genetic evaluations and better-informed breeding decisions. They are particularly useful in beef cattle, sheep, goats, pigs, and other species in which maternal care and early-life conditions play an important role in animal performance.
- The maternal influence on offspring performance can arise through several pathways. A dam contributes half of an offspring’s nuclear genetic material, but she also affects its development through pregnancy, uterine conditions, milk production, maternal behavior, and the environment she provides after birth. These influences may affect the offspring’s birth weight, growth, health, and survival. For example, a calf born to a cow with high milk production may grow faster before weaning than a calf whose mother produces less milk, even if the calves have similar genetic potential for growth. Maternal models help distinguish the genetic effects expressed directly by the offspring from genetic effects expressed through the mother.
- A maternal model is a statistical model that includes maternal effects as part of the explanation for variation in a trait. In animal breeding, these models often distinguish between direct additive genetic effects and maternal genetic effects. The direct genetic effect represents the influence of an animal’s own genes on its phenotype. The maternal genetic effect represents the influence of the dam’s genes on the environment or maternal characteristics she provides to her offspring. Depending on the trait and available information, a model may also include maternal permanent environmental effects, which represent lasting non-genetic differences among dams that affect their offspring.
- A simplified maternal animal model can be written as y=Xb+Zaa+Zmm+Wc+e, where y represents observed records, Xb represents fixed effects, a represents direct additive genetic effects, m represents maternal genetic effects, c represents maternal permanent environmental effects, and e represents residual errors. The matrices Za, Zm, and W connect the observations to the corresponding effects. Fixed effects may include herd, year, season, sex, age of dam, litter size, and management group. The exact model depends on the species, trait, breeding system, and structure of the data.
- Direct additive genetic effects are important because they determine the inherited contribution an animal can pass to its offspring. Maternal genetic effects are different because they influence the performance of offspring through the dam’s genetically influenced maternal characteristics. For example, genes affecting milk production in a cow can influence the growth of her calf during the suckling period. Similarly, genes affecting maternal behavior may influence the survival and development of young animals. These maternal effects are genetically relevant, but they do not represent the same biological pathway as the genes directly expressed by the offspring.
- Maternal permanent environmental effects must also be distinguished from maternal genetic effects. Some dams consistently provide more favorable environments to their offspring because of lasting non-genetic characteristics, such as differences in udder condition, previous management, or persistent health-related factors. These differences may influence multiple offspring produced by the same dam. A maternal permanent environmental effect accounts for this repeated influence without treating it as an inherited genetic effect. Separating maternal genetic and permanent environmental effects is important because only the genetic component can be used directly to predict inherited maternal merit in a breeding program.
- One of the most common applications of maternal models is the analysis of birth weight and weaning weight in beef cattle. Birth weight is influenced by the calf’s direct genes, the dam’s uterine environment, gestation length, and other environmental factors. Weaning weight is influenced by the calf’s own growth potential as well as the dam’s milk production, maternal ability, and the conditions experienced during early life. A model that includes only direct genetic effects may incorrectly attribute some maternal influences to the calf’s own genetic merit. By including maternal effects, researchers can estimate these contributions separately, provided that the available data contain enough information to distinguish them.
- For example, consider a beef cattle population in which calves from some cows consistently have higher weaning weights than calves from other cows. The difference may result from the calves’ inherited growth potential, the milk production and maternal ability of their dams, or differences in management. A maternal model can account for direct genetic effects, maternal genetic effects, relevant environmental factors, and maternal permanent environmental influences. This produces a more detailed understanding of why calves differ in weaning weight and helps breeders select animals for both direct growth performance and desirable maternal characteristics.
- Maternal models are especially important in sheep and goats, where litter size and milk production can strongly influence early growth and survival. In sheep, lamb birth weight, weaning weight, and pre-weaning survival may be affected by the ewe’s maternal characteristics, the number of lambs born, and the quality of the rearing environment. Twins and triplets often experience different nutritional conditions from single-born lambs because they share the dam’s milk supply. In goats, maternal milk production and mothering ability may affect kid growth and survival. Suitable maternal models can account for these influences and help breeders improve both offspring performance and maternal productivity.
- In pig breeding, maternal effects are particularly relevant to litter traits, piglet survival, and early growth. Sow characteristics such as milk production, mothering ability, and the uterine environment can influence the number of piglets that survive and grow successfully. Genetic evaluation may therefore need to distinguish direct genetic effects affecting piglet performance from maternal genetic effects affecting the sow’s ability to support the litter. Depending on the breeding objective, additional effects related to litter, parity, farrowing environment, and permanent sow characteristics may also be included. Because reproductive traits have complex genetic and environmental influences, careful model design is essential.
- Maternal models can also be used to investigate survival and early development. Young animals are often vulnerable to disease, poor nutrition, adverse weather, and inadequate maternal care. The dam’s genetic characteristics may influence the protection and resources available to her offspring. However, survival data are not always best analyzed using a simple linear model. When the outcome is binary, such as whether an animal survives to weaning, a generalized linear mixed model may be more suitable. For time-to-event traits, specialized survival models may be appropriate. The general principle remains the same: distinguish direct animal effects from relevant maternal and environmental influences using a statistical model suited to the data.
- An important part of maternal modeling is the relationship between direct and maternal genetic effects. These effects may be positively or negatively genetically correlated. A genetic correlation describes the association between genetic effects for two traits or between two different genetic pathways affecting the same trait. For example, direct genetic effects for growth and maternal genetic effects for weaning weight may be related, but they need not be. A negative correlation can make selection more complicated because improvement in one component may be associated with an unfavorable change in the other. Estimating this relationship can help breeders design balanced selection strategies.
- The estimation of variance components is central to maternal models. Researchers often estimate direct additive genetic variance, maternal genetic variance, the covariance between direct and maternal genetic effects, maternal permanent environmental variance, and residual variance. These components help explain the different sources of variation in a trait. They can also be used to estimate direct heritability and maternal heritability, depending on the model and definitions applied. Direct heritability describes the proportion of phenotypic variance attributable to direct additive genetic variance, while maternal heritability relates to the maternal genetic component under the specified model. Because direct and maternal effects may be correlated, these estimates must be interpreted carefully rather than treated as completely independent quantities.
- Maternal models are often implemented as extensions of animal models and mixed linear models. The animal model includes the additive genetic effect of each animal and uses pedigree relationships to represent genetic similarities among animals. A maternal animal model extends this framework by including a maternal genetic effect associated with the dam of each record. This allows genetic information from relatives to contribute to the evaluation of direct and maternal effects. For example, the maternal performance of a young female may be predicted using information from her dam, sisters, daughters, and other relatives, depending on the pedigree structure and available records.
- Best Linear Unbiased Prediction, or BLUP, is commonly used to predict direct and maternal genetic effects within mixed-model frameworks. BLUP combines performance records, pedigree information, and fixed environmental effects to produce predictions of genetic merit. The reliability of these predictions depends on the quantity and quality of records, the heritability of the trait, the genetic relationships among animals, and the suitability of the model. Maternal traits may require particularly careful evaluation because the same record can reflect the genetics of the offspring, the genetics of the dam, and environmental conditions shared by animals in the same litter or management group.
- Accurate identification of dams and offspring is essential for maternal model analysis. Incorrect parentage information can lead to genetic effects being assigned to the wrong animals, reducing the reliability of the estimates. Consistent recording of birth weight, weaning weight, litter size, dam age, parity, management conditions, and other relevant factors is also important. If key environmental influences are omitted, the model may attribute environmental differences to genetic effects. Researchers should therefore check pedigree completeness, data quality, model assumptions, and the precision of estimated variance components before applying the results to selection decisions.
- Maternal models have important implications for breeding objectives. In some production systems, breeders want to improve an animal’s own growth potential, while in others they also need females that produce healthy, fast-growing offspring. Selecting solely for direct growth may not provide the best long-term outcome if maternal ability is also economically important. A balanced breeding program may therefore consider direct growth, maternal performance, fertility, survival, and other relevant traits. Selection indexes can combine these traits according to their economic value and biological importance, helping breeders improve overall production efficiency rather than maximizing a single characteristic.
- Maternal effects can also vary with environmental conditions. The influence of a dam’s milk production or maternal behavior may differ depending on nutrition, climate, disease exposure, and management. Under challenging conditions, maternal ability may be particularly important for offspring survival and growth. Researchers can investigate these patterns using models that account for relevant environmental factors or, when supported by sufficient data, genotype-by-environment interactions. This can help breeding programs identify animals suited to different production systems and improve resilience in changing environments.
- Although maternal models provide valuable information, they can be difficult to estimate accurately. Direct genetic and maternal genetic effects may be strongly correlated, and the data may not contain enough information to distinguish them reliably. The results can be sensitive to the choice of model, the inclusion of maternal permanent environmental effects, and the treatment of litter or common environmental influences. Overly complex models may produce imprecise estimates, while models that omit important effects may give misleading results. Researchers must therefore use biological knowledge and statistical diagnostics to determine which effects should be included.
- It is also important to remember that a maternal genetic effect is not the same as an individual animal’s own breeding value for direct performance. A female may have average direct genetic merit for growth but favorable maternal genetic merit because her offspring benefit from her maternal characteristics. Conversely, an animal may have high direct growth potential but less favorable maternal ability. Keeping these components separate helps breeders make more informed decisions about which animals to use as sires and dams. The appropriate emphasis depends on the breeding objective, production system, and economic importance of the traits involved.
- Modern animal breeding software allows researchers to fit maternal models, estimate variance components, and predict direct and maternal breeding values from large livestock datasets. These methods can be combined with pedigree information and, in more advanced systems, genomic data. Genomic information may help improve the prediction of genetic merit, particularly for young animals with limited performance records. However, successful genomic maternal evaluation requires suitable reference populations, reliable phenotypes, and models that accurately represent the genetic and environmental structure of the population.
- Maternal models have become an important part of quantitative genetics because they recognize that offspring performance can reflect both the animal’s own genetic potential and the characteristics of its mother. By separating direct genetic effects, maternal genetic effects, and persistent maternal environmental influences, these models provide a more complete understanding of traits such as growth, survival, and early development. Their use supports more accurate breeding value estimation, better selection strategies, and improvements in livestock productivity and maternal performance. As animal breeding increasingly focuses on health, welfare, reproductive efficiency, and adaptability, maternal models will continue to help researchers and breeders make balanced and sustainable genetic improvement decisions.
