# Dairy Cow Genetics: Selection for Production, Health, and Longevity ## Key Takeaways - Dairy cow genetic improvement focuses on balancing production traits (milk, fat, protein yield) with health (mastitis resistance via Somatic Cell Score, metabolic disorders), fertility (daughter pregnancy rate), and longevity (productive life PTAs). - Predicted Transmitting Ability (PTA) and Estimated Breeding Values (EBVs) are foundational genetic evaluation tools, representing an animal's expected genetic merit transmitted to offspring, with reliability increasing with progeny and genomic data. - Genomic selection leverages DNA marker information (SNPs) to predict genetic merit in young animals before performance data is available, significantly reducing the generation interval and accelerating genetic gain. - Selection indices, such as Lifetime Net Merit (LNM) and Total Performance Index (TPI), integrate multiple trait PTAs based on economic importance, enabling balanced genetic progress across diverse breeding goals. - Practical implementation involves defining herd breeding goals, evaluating current genetic levels, selecting sires using indices and individual traits, and utilizing genomic testing for replacement heifers to identify superior animals early. - Common pitfalls in genetic selection include overemphasizing production at the expense of health/fertility, ignoring inbreeding, using low-reliability sires, and failing to update breeding goals to reflect evolving herd needs and market conditions. --- Dairy cow genetics is the application of quantitative and molecular genetic principles to improve herd performance through selective breeding. For dairy farmers and herd managers, genetic selection decisions directly influence milk production efficiency, animal health, reproductive performance, and the longevity of cows in the milking herd. This article explains the genetic evaluation tools available, how to select for multiple traits, and the role of genomic testing in modern dairy breeding programs. ## At a Glance: Genetic Selection Priorities for Dairy Herds The table below summarizes the main categories of traits that dairy farmers can select for, the typical genetic evaluation tools used, and the practical herd outcomes associated with each category. | Trait Category | Genetic Evaluation Tool | Herd Outcome | |---|---|---| | Milk production (milk yield, fat, protein) | Predicted Transmitting Ability (PTA) or Estimated Breeding Value (EBV) from national genetic evaluations | Increased saleable milk solids per cow per lactation | | Health and disease resistance (mastitis, lameness, metabolic disorders) | Genetic evaluations for health traits, including [Somatic Cell](/blog/guides/somatic-cell) Score (SCS) as an indicator of mastitis resistance | Reduced veterinary costs, lower culling rates, improved animal welfare | | Fertility and reproduction (daughter pregnancy rate, calving interval) | Fertility PTAs from national evaluations and genomic predictions | Shorter calving intervals, higher conception rates, reduced reliance on reproductive interventions | | Longevity and functional type (udder depth, feet and legs, body condition score) | Linear type trait evaluations and productive life PTAs | Cows that remain productive for more lactations, reducing replacement heifer costs | | Feed efficiency (residual feed intake, [feed conversion ratio](/knowledge/animal-farming/poultry/feed-conversion-ratio-measuring-improving-poultry-efficiency)) | Genomic predictions and research indices from breed associations | Lower feed costs per unit of milk produced, improved environmental footprint | ## Genetic Evaluation Tools and Their Practical Use ### Predicted Transmitting Ability and Estimated Breeding Values National genetic evaluations produce PTAs or EBVs for individual animals. These values represent the genetic merit an animal is expected to transmit to its offspring for a specific trait. PTAs are expressed in the units of the trait, such as kilograms of milk or percentage of fat. Dairy farmers use these values to compare bulls and cows within a breed and to select mating sires that will improve the herd's genetic level over time. The reliability of a PTA increases with the amount of data available from the animal itself, its progeny, and its genomic profile. ### Genomic Predictions Genomic selection uses DNA marker information to predict the genetic merit of young animals before they have performance records. A reference population of animals with both genotypes and phenotypes is used to estimate the effect of thousands of DNA markers across the genome. Young animals are genotyped, and their genomic PTAs are calculated from the marker effects. This approach reduces the generation interval because bulls can be selected for breeding at a younger age, accelerating genetic gain. Research on cow genotyping strategies for genomic selection in a small dairy cattle population has shown that genotyping more cows can increase genetic gain and reduce the rate of true inbreeding in a dairy cattle breeding scheme using female reproductive technologies (Journal of Dairy Science, 2020, https://doi.org/10.3168/jds.2019-16974). ### Selection Indices Most breed associations and AI companies combine PTAs for multiple traits into a single selection index. Examples include the Lifetime Net Merit (LNM) in the United States, the Profitable Lifetime Index (PLI) in the United Kingdom, and the Total Performance Index (TPI). These indices weight traits according to their economic importance and the breeding goal of the population. Farmers who use a selection index can make balanced genetic progress across production, health, fertility, and longevity traits without having to manually balance multiple individual PTAs. ## Trait Selection for Production, Health, and Longevity ### Milk Production Traits Milk yield, fat yield, protein yield, and fat and protein percentages are the traditional production traits in dairy genetic evaluations. Selection for higher milk yield has been successful over decades, but it has also been associated with negative genetic correlations with health and fertility traits. Modern selection indices place less emphasis on production alone and include health and fertility traits to counteract these negative correlations. Research on harnessing the genetics of the modern dairy cow to continue improvements in feed efficiency has highlighted the importance of including feed efficiency in breeding goals (Journal of Dairy Science, 2016, https://pubmed.ncbi.nlm.nih.gov/27085407). ### Health and Disease Resistance Genetic selection for mastitis resistance is possible through direct genetic evaluations for clinical mastitis and through indicator traits such as [Somatic Cell](/blog/guides/somatic-cell) Score. A review of genetic selection for mastitis resistance in The Veterinary Clinics of North America. Food Animal Practice (2018, https://pubmed.ncbi.nlm.nih.gov/30316503) discusses the heritability of mastitis and the availability of genomic predictions for this trait. Selecting for lower SCS reduces the incidence of clinical and subclinical mastitis, lowering treatment costs and improving milk quality. Other health traits that can be selected for include resistance to ketosis, displaced abomasum, metritis, and lameness. Some national genetic evaluations now include these traits directly, while others use indicator traits such as body condition score and feet and leg conformation scores. ### Fertility and Reproductive Performance Female fertility traits in genetic evaluations include daughter pregnancy rate, heifer conception rate, cow conception rate, and calving interval. Male fertility can also be evaluated through sire conception rate and genomic predictions for bull fertility. A review of genomics of bull fertility in Animal: An International Journal of Animal Bioscience (2018, https://pubmed.ncbi.nlm.nih.gov/29618393) discusses the genetic architecture of male reproductive traits. Selecting for improved fertility reduces the number of services per conception, shortens calving intervals, and lowers the cost of reproductive management. ### Longevity and Functional Type Traits Productive life or longevity PTAs estimate the genetic ability of a cow to remain in the herd. Functional type traits such as udder depth, teat placement, foot angle, and leg conformation are genetically correlated with longevity. A genome-wide association study as an efficacious approach to discover candidate genes associated with body linear type traits in dairy cattle (Animals, 2024, https://doi.org/10.3390/ani14152181) demonstrates the genetic basis of these conformation traits. Selecting for improved type traits that are associated with durability helps cows stay productive for more lactations. ### Feed Efficiency Feed efficiency is an increasingly important trait in dairy breeding. Residual feed intake (RFI) is a measure of feed efficiency that is independent of production level. Cows with low RFI eat less than expected for their size and production, reducing feed costs. Genomic predictions for RFI are available from some breed associations and research programs. Including feed efficiency in the breeding goal improves the profitability and environmental sustainability of the dairy operation. ## Genomic Testing in Dairy Herds ### How Genomic Testing Works Genomic testing involves collecting a DNA sample from an animal, typically from a hair root, blood, or ear tissue. The sample is sent to a laboratory that genotypes the animal for thousands of DNA markers called single nucleotide polymorphisms (SNPs). The genotype data is then compared to a reference population to calculate genomic PTAs for all traits in the evaluation system. ### Practical Implementation on the Farm Farmers can use genomic testing for several purposes. Testing replacement heifers allows early identification of the best animals to keep as herd replacements and which to cull or breed to beef bulls. Testing young bulls before they enter AI service accelerates the selection process. Testing cows in the milking herd can improve the accuracy of genetic evaluations for the herd and help identify the best dams for embryo transfer programs. Research on cow genotyping strategies for genomic selection in a small dairy cattle population (Journal of Dairy Science, 2017, https://pubmed.ncbi.nlm.nih.gov/27837974) provides insights into how many cows need to be genotyped to achieve reliable genomic predictions in smaller herds. Genotyping more cows increases genetic gain and reduces the rate of true inbreeding in a dairy cattle breeding scheme using female reproductive technologies (Journal of Dairy Science, 2020, https://doi.org/10.3168/jds.2019-16974). ### Costs and Benefits The cost of genomic testing has decreased over time, making it accessible to more dairy farmers. The benefits include higher accuracy of selection for young animals, reduced generation interval, and the ability to select for traits that are difficult or expensive to measure, such as feed efficiency and disease resistance. Farmers should compare the cost of testing to the expected genetic gain and the value of that gain in their specific herd situation. ## Practical Steps for Implementing a Genetic Selection Program ### Step 1: Define Herd Breeding Goals Identify the traits that are most limiting in your herd. Review herd records for culling reasons, disease incidence, reproductive performance, and milk production. Prioritize traits that have the greatest economic impact on your operation. For example, if mastitis is a major cause of culling, prioritize SCS and mastitis resistance in your selection decisions. ### Step 2: Evaluate Current Genetic Level Obtain genetic evaluations for all animals in the herd. Many breed associations and dairy record processing centers provide genetic reports. Calculate the average PTAs for your herd for the traits you have prioritized. This baseline allows you to measure genetic progress over time. ### Step 3: Select Sires Based on Index and Individual Traits Use selection indices to identify bulls that will improve the overall genetic merit of the herd. For specific problem areas, you may also select bulls with high PTAs for individual traits. For example, if your herd has poor fertility, select bulls with high daughter pregnancy rate PTAs. Use the reliability of the bull's PTAs to assess the risk of the prediction. ### Step 4: Implement Genomic Testing for Replacement Heifers Test all replacement heifers at birth or weaning. Use the genomic results to rank heifers for retention, sale, or breeding to beef bulls. This practice reduces the number of heifers that need to be raised and accelerates genetic progress by selecting the best animals earlier. ### Step 5: Monitor Genetic Progress Track the average PTAs of the herd over time. Compare the genetic trend to the herd's phenotypic performance for production, health, and fertility traits. Adjust the breeding goal if the herd's performance in certain areas is not improving as expected. ## Records and Measurements for Genetic Selection ### Pedigree Records Accurate pedigree records are essential for genetic evaluation. Each animal must have a known sire and dam. Errors in parentage reduce the accuracy of genetic evaluations and can lead to incorrect selection decisions. Use DNA parentage verification if there is any doubt about pedigree accuracy. ### Performance Records Milk production records from official milk recording programs provide the data needed for genetic evaluations of production traits. Health and fertility records from herd management software are used for genetic evaluations of health and reproductive traits. The quality of genetic evaluations depends on the completeness and accuracy of these records. ### Genotype Records When animals are genotyped, the laboratory provides a genotype file that is submitted to the breed association or genetic evaluation center. Keep a record of which animals have been genotyped and the date of testing. This information is useful for tracking the adoption of genomic testing in the herd. ### Culling and Disposal Records Records of why animals leave the herd are valuable for identifying traits that need improvement. If many cows are culled for lameness, for example, selecting for better feet and leg conformation should be a priority. Culling records also contribute to genetic evaluations for longevity and productive life. ## Common Failure Patterns in Genetic Selection ### Overemphasis on Production Traits Selecting solely for milk yield without considering health and fertility traits leads to cows that produce well but have poor reproductive performance and high disease incidence. This pattern increases culling rates and reduces the average number of lactations per cow. Use a balanced selection index that includes health and fertility traits to avoid this problem. ### Ignoring Inbreeding Using a small number of popular sires across multiple generations increases inbreeding in the herd. Inbreeding depression reduces fertility, calf survival, and milk production. Monitor the average inbreeding coefficient of the herd and avoid mating closely related animals. Genomic testing can help identify animals that are less related to the current herd. ### Using Low Reliability Sires Selecting young bulls with low reliability PTAs carries more risk than using proven bulls with high reliability. The actual genetic merit of a low reliability bull may be significantly different from its predicted value. Use a combination of proven bulls for consistency and young genomic bulls for accelerated genetic gain, but limit the use of low reliability bulls to a small percentage of matings. ### Failing to Update Breeding Goals Herd needs change over time. A breeding goal that was appropriate five years ago may not address current problems. Review the breeding goal annually and adjust it based on changes in herd performance, market conditions, and available genetic evaluations. ## Limitations of Genetic Selection ### Genetic Correlations Between Traits Some traits are genetically correlated in a favorable direction, while others are correlated unfavorably. For example, milk yield is genetically correlated with higher feed intake and lower fertility. Selection for one trait will cause correlated responses in other traits. Understanding these correlations is important for setting realistic breeding goals. ### Heritability of Traits Heritability estimates the proportion of phenotypic variation that is due to additive genetic effects. Traits with higher heritability, such as milk yield and type traits, respond more quickly to selection than traits with lower heritability, such as fertility and disease resistance. Genomic selection can improve the accuracy of selection for low heritability traits, but progress will still be slower than for high heritability traits. ### Environmental Interactions Genotype by environment interactions occur when the genetic merit of an animal depends on the environment in which it is kept. A bull that is proven in a high input system may not perform as well in a pasture based system. Use genetic evaluations from populations that are similar to your management system when possible. ## Welfare and Safety Context ### Animal Welfare Benefits of Genetic Selection Selecting for health traits such as mastitis resistance, lameness resistance, and metabolic disease resistance directly improves animal welfare. Cows that are healthier experience less pain and stress and have a better quality of life. Selecting for longevity means that cows are more likely to remain productive and healthy for more lactations, reducing the number of animals that need to be culled and replaced. ### Worker Safety Considerations Cows with better temperament and easier handling characteristics are safer for farm workers. Some genetic evaluations include temperament or milking speed traits. Selecting for these traits can reduce the risk of injury to workers during milking and handling. ### [Food Safety](/knowledge/bacteria/livestock-bacteria/cooking-chicken-bacteria-prevention) Implications Genetic selection for mastitis resistance reduces the use of antibiotics for mastitis treatment, which supports food safety by lowering the risk of antibiotic residues in milk. Selecting for lower SCS improves milk quality and reduces the risk of high somatic cell count penalties. ## Professional Escalation Criteria ### When to Consult a Geneticist or Breed Association Specialist Consider consulting a professional geneticist or breed association specialist in the following situations: - The herd is not making genetic progress despite using high index sires. - Inbreeding levels are increasing and you need guidance on mate selection. - You are considering implementing genomic testing and need help interpreting the results. - You want to develop a customized selection index for your specific herd goals. - You are planning to use advanced reproductive technologies such as embryo transfer or ovum pickup and need to integrate them with genetic selection. ### When to Seek Veterinary Advice Veterinary input is needed when genetic selection is being used to address health problems. A veterinarian can help identify the specific diseases that are most prevalent in the herd and advise on whether genetic selection is an appropriate tool. For example, if mastitis is a problem, the veterinarian can help interpret SCS data and recommend whether genetic selection for mastitis resistance should be combined with management changes. ## Frequently Asked Questions ### What is the difference between PTA and EBV in dairy cattle genetics? PTA (Predicted Transmitting Ability) and EBV (Estimated Breeding Value) are both measures of genetic merit. PTA is half of the EBV because it represents the genetic value that an animal transmits to its offspring, while EBV represents the total genetic value of the animal itself. Different countries and breed associations use either PTA or EBV in their genetic evaluations. ### How many heifers should I genotype in my dairy herd? The number of heifers to genotype depends on herd size, replacement rate, and budget. Genotyping all replacement heifers provides the most information for selection decisions. Research on cow genotyping strategies for genomic selection in a small dairy cattle population (Journal of Dairy Science, 2017, https://pubmed.ncbi.nlm.nih.gov/27837974) suggests that genotyping more cows increases genetic gain. Farmers should compare the cost of testing to the expected value of improved selection. ### Can I select for both high milk production and good fertility at the same time? Yes, but progress will be slower than selecting for either trait alone because milk yield and fertility are genetically correlated in an unfavorable direction. Using a selection index that includes both production and fertility traits allows balanced progress. Genomic selection can improve the accuracy of fertility predictions and help identify animals that combine high production with acceptable fertility. ### What is the heritability of mastitis resistance in dairy cows? Mastitis resistance has low to moderate heritability, typically in the range of 0.02 to 0.12 depending on the population and how mastitis is measured. Despite the low heritability, genetic selection for mastitis resistance is possible and effective when combined with genomic information. A review of genetic selection for mastitis resistance in The Veterinary Clinics of North America. Food Animal Practice (2018, https://pubmed.ncbi.nlm.nih.gov/30316503) discusses the genetic parameters for this trait. ### How does genomic testing reduce inbreeding in dairy herds? Genomic testing allows breeders to identify animals that are less related to the current herd population. By selecting sires and dams with lower genomic relationships, the rate of inbreeding can be reduced. Research on genotyping more cows increases genetic gain and reduces rate of true inbreeding in a dairy cattle breeding scheme using female reproductive technologies (Journal of Dairy Science, 2020, https://doi.org/10.3168/jds.2019-16974) demonstrates this effect. ### What traits are included in the Lifetime Net Merit index? The Lifetime Net Merit index includes traits for milk production, health, fertility, longevity, and type. The specific traits and their weights are updated periodically by the Council on Dairy Cattle Breeding. Farmers should check the current index formula from their breed association or genetic evaluation provider. ### Can I use beef on dairy crossbreeding and still make genetic progress in my dairy herd? Yes, beef on dairy crossbreeding can be used for heifers and low genetic merit cows while maintaining genetic progress in the dairy herd through selective breeding of the best females. An invited review on beef on dairy the generation of crossbred beef dairy cattle in the Journal of Dairy Science (2021, https://pubmed.ncbi.nlm.nih.gov/33663845) discusses the opportunities and challenges of this approach. The dairy females that are kept as replacements should be bred to high genetic merit dairy sires. ### How often should I update my herd's breeding goal? The breeding goal should be reviewed at least annually. Changes in herd performance, market conditions, disease prevalence, and available genetic evaluations may warrant adjustments to the goal. Some farmers review the breeding goal after each genetic evaluation release from the breed association. ## Related Farming Guides - [Dairy Cattle Farming Nutrition Housing Health Signals And Herd Management](/knowledge/animal-farming/dairy-cattle/dairy-cattle-farming-nutrition-housing-health-signals-and-herd-management) - [Dairy Cow Cooling System Management](/knowledge/animal-farming/dairy-cattle/dairy-cow-cooling-system-management) - [Beef Cattle Water Quality Testing](/knowledge/animal-farming/beef-cattle/beef-cattle-water-quality-testing) - [Dairy Cow Culling Decisions And Records](/knowledge/animal-farming/dairy-cattle/dairy-cow-culling-decisions-and-records) - [How To Design A Comfortable Dairy Cow Barn](/knowledge/animal-farming/dairy-cattle/how-to-design-a-comfortable-dairy-cow-barn) ## Related Clinical & Scientific Guides * [Evaluating Feed Additives for Dairy Cow Performance](/knowledge/animal-farming/dairy-cattle/evaluating-feed-additives-for-dairy-cow-performance) * [Dairy Barn Fire Safety: Design and Prevention Measures](/knowledge/animal-farming/dairy-cattle/dairy-barn-fire-safety-design-prevention) * [Dairy Cow Pregnancy Loss Records and Review](/knowledge/animal-farming/dairy-cattle/dairy-cow-pregnancy-loss-records-and-review) ## References and Further Reading - [www.nrcs.usda.gov](https://www.nrcs.usda.gov/) - [www.merckvetmanual.com](https://www.merckvetmanual.com/management-and-nutrition) - [FAO Animal Production and Health](https://www.fao.org/animal-production/en). Food and Agriculture Organization of the United Nations. - [Animal Health and Welfare](https://www.nal.usda.gov/animal-health-and-welfare). USDA National Agricultural Library. - [Genetics and genomics of reproductive performance in dairy and beef cattle.](https://pubmed.ncbi.nlm.nih.gov/24703258). Animal : an international journal of animal bioscience, 2014. - [Invited review: Beef-on-dairy-The generation of crossbred beef × dairy cattle.](https://pubmed.ncbi.nlm.nih.gov/33663845). Journal of dairy science, 2021. - [Cow genotyping strategies for genomic selection in a small dairy cattle population.](https://pubmed.ncbi.nlm.nih.gov/27837974). Journal of dairy science, 2017. - [Genetic Selection for Mastitis Resistance.](https://pubmed.ncbi.nlm.nih.gov/30316503). The Veterinary clinics of North America. Food animal practice, 2018. - [Review: Genomics of bull fertility.](https://pubmed.ncbi.nlm.nih.gov/29618393). Animal : an international journal of animal bioscience, 2018. - [Harnessing the genetics of the modern dairy cow to continue improvements in feed efficiency.](https://pubmed.ncbi.nlm.nih.gov/27085407). Journal of dairy science, 2016. - [Twinning in Dairy Cattle](https://doi.org/10.15232/S1080-7446%2815%2931599-0). Professional Animal Scientist, 2001. - [Genotyping more cows increases genetic gain and reduces rate of true inbreeding in a dairy cattle breeding scheme using female reproductive technologies](https://doi.org/10.3168/jds.2019-16974). Journal of Dairy Science, 2020. - [A Review of Research on Genetic Variation in Physiological Characteristics Related to Performance in Dairy Cattle](https://doi.org/10.3168/jds.S0022-0302%2879%2983333-0). Journal of Dairy Science, 1979. - [Genetics and genomics of dairy cattle](https://doi.org/10.1016/B978-0-12-817052-6.00006-9). Animal Agriculture Sustainability Challenges and Innovations, 2019. - [Genome-Wide Association Study as an Efficacious Approach to Discover Candidate Genes Associated with Body Linear Type Traits in Dairy Cattle](https://doi.org/10.3390/ani14152181). Animals, 2024. > This article is educational and is not a substitute for veterinary diagnosis, treatment, public-health guidance, or regulatory reporting.