New genetic evaluations will be available on Tuesday, August 13, for all dairy cattle in the U.S. database. Several updates were implemented in this proof run so that the evaluations are as accurate as possible. Then, farmers worldwide can make breeding and culling decisions based on the most current, credible predictions of genetic merit.

These updated genetic evaluations for 50 individual traits and four selection indexes will be published by the Council on Dairy Cattle Breeding (CDCB) for more than 86 million individual animals. Review the traits and indexes by reading “Making sense of dairy sire summaries.”

What changes were made and why?

First, 305-Average Age (305-AA) is now the new standardized yield measurement, replacing 305-Mature Equivalent (305-ME) in the calculation of CDCB genetic evaluations. This measure allows us to fairly compare cows of different ages, parities, climates, seasons of calving, and lactation lengths. The new 305-AA estimates a cow’s production for a given lactation, adjusted to 36 months of age and utilizing partial yield measurements captured by milk testing.

This evolution from 305-ME to 305-AA is designed to better align with today’s management practices and environmental impacts on production. The 305-ME adjustments were last updated in 1994. Now 30 years later, both herd management and the biology of the cow have changed. Producers need current tools for making accurate, fair comparisons among cows. This transition and the new 305-AA are based on a 2023 study by USDA’s Animal Genomics and Improvement Laboratory and the CDCB, which analyzed more than 100 million milk yield records in the national cooperator database managed by CDCB.

The 305-AA adjustments will impact the genetic evaluations for each breed differently, and test runs suggest a small reranking of bulls will take place with this change. Yield traits will experience the most variation, resulting in additional impacts to Net Merit $ and other indices that rely heavily on yield traits. CDCB’s Katie Schmitt further described this change in “Moving from ME to average age.”

Second, we’ve now completed the implementation of constructed IDs across the entire national cooperator database. Constructed IDs use parentage identification via genomics to build more complete pedigrees for animals that previously had no link to their maternal ancestors, improving evaluation accuracy.

Knowing an animal’s ancestry several generations back is certainly the goal for many producers; however, there are instances where animals have a gap in their pedigree. When animals have an unknown sire or dam, their assessment of genetic merit is incomplete. As animal breeders, that creates a dead end. We’re not able to accurately factor ancestors’ contributions to the animal’s genetic merit. With genomics, we can fill in these pedigree gaps. CDCB was the first in the world to introduce this new method, coined constructed ID. As a result, the genetic evaluations for affected animals are more accurate and reliable, and the U.S. genetic evaluations improve in accuracy overall.

For Brown Swiss breeders, rear teat placement (RTP) is a new trait available in August 2024 traditional and genomic evaluations. Traditional evaluations – those produced from only performance data – include RTP as a single trait, currently uncorrelated to other traits. These values then provide an RTP evaluation to all 72,000-plus genotyped Brown Swiss animals.

Last but not least, the haplotypes Holstein HH6 and Jersey neuropathy with splayed forelimbs (JNS) will now include direct gene test information in their haplotype calculation.

What is a haplotype?

The benefits of haplotypes to understand and identify genetic variation is a fairly new phenomenon in cattle breeding, resulting from the expanded use of genomics and genotyping over the past 15 years.

A haplotype for a genomically-tested animal is a short section of DNA inherited together from its sire or dam. In genotyping, we read genetic markers — most often single-nucleotide polymorphisms (SNPs) — scattered across an animal’s genome.

Haplotype matching has allowed us to discover ancestors in cases where animals’ parentage was unknown or questionable. Haplotype analysis is also used to identify genetic factors that impact expression of specific phenotypic features. Sometimes this is a desired expression, like polled (hornless) or coat color. In other cases, those factors are detrimental or even lethal. In the past decade, several haplotype calls that affect fertility, embryo death, and stillbirth, for example, have been discovered and reported.

Typically, results from a gene test are used to identify the carrier status of high-profile animals. We cannot always obtain actual gene tests to identify carrier status on all animals in a population. Sometimes the causal variant is unknown or not on a commercial genotyping chip. In these cases, haplotype calls are made available to identify animals’ carrier status in a cost-effective, efficient way through the normal genomic evaluation process.

Driving the U.S. genetic evaluations

The triannual evaluations – on April 2, August 13, and December 3, 2024 – incorporate genomic data along with updated performance, or phenotypic, data to assess the genetic merit of dairy animals. The engine of the U.S. dairy evaluations is the national cooperator database managed by CDCB.

A new milestone was achieved on May 3, 2024, when the 9 millionth animal genotype was recorded in the CDCB database.

The first U.S. Holstein sires were genotyped in 2008, and it took seven years to reach 1 million genotypes. Since then, the database has grown exponentially. Now, a million genotypes are added every eight to nine months. That rapid increase is driven by the widespread adoption of genomic testing of females to make mating, culling, and other herd management decisions.

The national cooperator database of both genotypes and phenotypes is the world’s largest animal database. A sophisticated process is in place to assure high data quality comes into the database from farms across the U.S. and around the world through strategic international partnerships.

This combination of data quantity and quality provides increasingly accurate genetic evaluations used by dairy herds worldwide.