Artificial insemination businesses provide top genetics for dairy cow genetic improvement projects, with the most marketable bulls having the most genetic value. This extensive within-family selection results in higher degrees of connection, which leads to increased inbreeding. Reducing or even restricting inbreeding often results in the selection of lower-index bulls. As improved reproductive methods become more widely used and long-term technologies like as in vitro breeding evolve, selection intensities on bull and cow dams may skyrocket, worsening the situation even further.
The dairy genetics community must now decide who is prepared to decrease the pace of genetic gain in order to effectively regulate inbreeding. The literature has several instances of the negative impacts of inbreeding, however it is not true that all inbreeding is equal, and a distinct boundary exists between safe and risky. There is likely to be a tipping point beyond which we do not want to go, but its position is uncertain. Lush (1945) proposed that generations of high-intensity selection may necessarily result in large percentages of homozygosity.
To analyze the present situation, we may compare changes in phenotypic performance during inbreeding to rates of genetic gain. In all but one situation, annual genetic benefits outweigh inbreeding depression: the daughter pregnancy rate, which decreases by 0.02 PTA units each year. This is not to say that there is nothing to be worried about; it just means that we are not yet losing ground. As the phrase goes, “When you’re in a hole, stop digging,” but we need to act first.
The desire for elite genetics contributes to the continual loss of genetic variety in dairy cow herds, making it harder to preserve heterozygosity. Elite bulls are no longer enough; they must also have good breeding values for milk, components, fertility, and other attributes. Most marketed bulls cannot hit all of these criteria, but it is often assumed that they will.
Some measures may be used to reduce inbreeding rates in dairy cow herds. Refine PTA Adjustments: Genetic assessments in the United States are altered to account for the potential implications of future inbreeding. Predicted transmitting abilities (PTA) for bulls closely related to the population are reduced to account for inbreeding depression, while PTA for bulls less related to the population than average are increased to account for advantageous heterosis. However, the problem with this strategy is that the top AI bulls causing genetic change in the population are often severe outliers, and post-hoc modifications lack theoretical support.
Use the Right Metric: Genomic inbreeding assesses both identity-in-state and identity-by-descent, while pedigree inbreeding solely considers the latter. One technique to lower apparent inbreeding rates is to use pedigree inbreeding instead of genomic inbreeding. A more tempting strategy is to shift away from crude measurements of inbreeding and toward more accurate measures of diversity, such as runs of homozygosity (ROH) or direct measures of identity-by-descent (IBD). Timing is important, and older inbreeding is less concerning than current inbreeding since older haplotypes have been cleared of possible recessive genes.
Trim Pedigrees: Pedigree information is simple and inexpensive to record, but it has numerous limitations, including incompleteness, greater than expected genuine inbreeding, and underestimation of real ties among people. Trimming pedigrees to just a specific number of generations is a simple technique to minimize inbreeding. A similar alternative is to use a changing base year for inbreeding rather than a set reference year (the US uses 1960 as its base population).
Trimming pedigrees does not directly address rates of inbreeding in the population, either pedigree or genomic, but it is proposed because it may drive selection decisions away from families with the highest rates of recent inbreeding, which are the lineages most likely to contain genetic load that has not yet been purged.
The area of genetic selection has various obstacles, including the issue of bulls with the highest PTA being in high demand, independent culling levels, and implementing optimum contribution selection. To remedy this, it is proposed that instead of publicizing PTA for specific qualities, bulls be randomly assigned to the cow population. Bulls might also be given red, yellow, or green badges for each characteristic to signify their PTA, although this may not be desirable.
Homomorphic encryption may be used to hide the PTA provided to software from end users, although this is not a usual practice, and implementation is difficult. Hiding PTA would be a significant departure from existing methods, and most consumers or salesmen may not find this approach desirable.
Additional measures of genetic variety might be added to selection indices as a trait, exerting direct selection pressure on heterozygosity. This implies that choosing high-index bulls would entail some selection for increased heterozygosity, rather than trusting that inbreeding is taken into account during the mating process. However, this is a less efficient method of achieving optimum contribution selection, and it has been largely neglected in the United States since its inception.
Varona et al. (2019) recommended that an artificial purging system be built around a selection index that includes both breeding values and inbreeding burdens. This is a more attractive approach than include an ad hoc measure of variety in the index, and there is a strong theoretical underpinning to support its usage.
The implementation of optimum contribution selection in certain places, such as the United States, is not especially contentious owing to its complexity and the impression that the advantages do not outweigh the increased complexity. Many genetics end users are unwilling to accept the trade-off between genetic trend and heterozygosity preservation, and in a competitive market, they may just buy their sperm and embryos from another provider.
Finally, genetic protection procedures that limit germplasm interchange are allowing breeding projects run by several AI corporations to develop into distinct subpopulations within breeds. While it is unclear if these groupings are distinct enough to result in widespread outbreeding, current study indicates that bigger variances between families within a breed may exist than previously thought.
Genetics corporations may concentrate on selling embryos that represent perfect terminal dairy cows, necessitating a large increase in the scope of dairy embryo transfer. This would result in a system that is more like modern swine production than ancient dairy cow rearing. Some genetics businesses may begin selling embryos into smaller-scale specialist markets, such as those seeking high-genetic-merit polled animals.
Gene editing technologies have advanced, leading in increased efficiency and the capacity to stack numerous alterations. This might be a technique to sustain rates of genetic gain without experiencing negative repercussions or relying on natural purging. However, this strategy has several obstacles, including a lack of understanding about editing targets, an inability to edit dozens or hundreds of targets at the same time, and an ever-changing regulatory environment.
To effectively address the challenges posed by inbreeding, a collaboration between AI companies and the scientific community must persuade farmers that there is a real problem to be solved, that our proposed solutions will work, and that they are not being asked to jeopardize their livelihoods by participating in this process. The size of the issue is important, since many farmers are worried about the long-term impacts of inbreeding but do not necessarily agree that vigorous action must be done now. There is also common belief that the individuals who created the issue cannot be trusted to repair it, and that things function differently in the actual world than they do on paper.
Inbreeding is expected to attract greater attention in the future because of its impact on social license rather than production economics. Most laypeople are unaware of the fundamental distinction between inbreeding with stringent performance selection, as is used in animal breeding programs, and inbreeding with no performance selection. Increased genetic load also impairs an animal’s capacity to adapt to changes, which is concerning as the environment shifts.
Dairy cow breeding is a loosely connected method that allows for efficient management across the production chain. Effective population control will be challenging and will need adjustments on the side of AI businesses and farmers.
