Genomic selection in dairy cattle breeding instead of progeny testing

Replaces: progeny testing of AI bulls · Scope: dairy and livestock breeding · Evidence: high

The old process#

• Until about 2009, an AI bull was proven by progeny testing: hundreds of daughters had to calve and complete a lactation before his breeding value was known — five years or more and a large cost per bull, with only a few bulls selected each year.
• Slow cycles made it hard to select for low-heritability traits such as fertility, health and disease resistance.

Product overview#

Genomic selection predicts an animal’s breeding value from tens of thousands of DNA markers (SNP chips) using a reference population of genotyped, phenotyped animals (Meuwissen, Hayes and Goddard, 2001). US genomic evaluations for Holsteins became official in 2009. Breeding companies now market young genomic bulls directly, and farms genotype heifers to choose replacements.

Active ingredient / Composition#

• SNP genotyping arrays (and increasingly sequence data), central reference databases (in the US run by CDCB with USDA), statistical prediction models (GBLUP, single-step GBLUP).
• Delivered through AI companies, breed associations and genotyping labs.

Key facts#

Advantages#

• Selection years earlier, faster genetic progress per year.
• Health, fertility and disease-resistance traits can be selected effectively — fewer treatments over time (links to SG03, V04).
• Lower cost per proven bull; genotyping heifers improves herd decisions.

Mode of action#

Markers across the genome capture the combined effect of many small-effect genes; a prediction equation trained on animals with both genotypes and performance records estimates the breeding value of a young animal from its genotype alone.

Application#

Limitations#

• Accuracy depends on a large reference population — smaller breeds and countries need collaboration (Interbull).
• Faster selection can raise inbreeding; it must be managed.
• Benefits depend on recording infrastructure (milk recording, health data).

Evidence of displacement — D3: proven displacement at scale#

Assessment (hand-reviewed): National (USA): 79% of Holstein bulls on the market were young genomic-tested bulls in 2016 (peer-reviewed extension journal); young genomic sires got ~70% of AI breedings (CDCB/Interbull) — progeny testing displaced within about seven years.

Verified figures (the number is in the quoted sentence and the sentence is on the source page):

• displacement — Genomic selection has displaced progeny testing as the primary method for selecting service sires in the US dairy industry, with the majority of bulls marketed being young genomic-tested bulls rather than progeny-tested bulls. (United States, 2016; peer-reviewed: journals.flvc.org)
• displacement — In 2016, 67% of breedings through AI were to bulls with no milking progeny. (United States, 2016; weak: interbull.org)
• displacement — In 2018, 69% of AI breedings were to genomic bulls. (United States, 2018; weak: uscdcb.com)
• displacement — By 2021, young genomic sires accounted for 71% of the inseminations in U.S. herds that record through Dairy Herd Information (DHI). (United States, 2021; weak: usacattlegenetics.com)

Suppliers — real products and services (from the vendor index)#

Companies below are active vendors in the vendor index whose own card (profile / official website) shows this product or service — matched 2026-10-06 by keyword and checked by hand against the card text. Being listed is not an endorsement; open each card for evidence, contacts and status.

Government funding signals#

Scanned 2026-10-06.

China, Brazil, India — national research grants acknowledged in publications#

Papers since 2015 whose title matches “genomic selection dairy” and that acknowledge national government funders (Crossref funder metadata; conservative lower bounds). Signal bands: Strong ≥30 · Moderate 5–29 · Weak 1–4 · None 0.

Scientific evidence#

• Meuwissen THE, Hayes BJ, Goddard ME (2001). Prediction of total genetic value using genome-wide dense marker maps. Genetics 157: 1819–1829.
• García-Ruiz A, Cole JB, VanRaden PM, Wiggans GR, Ruiz-López FJ, Van Tassell CP (2016). Changes in genetic selection differentials and generation intervals in US Holstein dairy cattle as a result of genomic selection. Proceedings of the National Academy of Sciences 113: E3995–E4004.
• Note: journal references are checked against Crossref.

Bioeconomy value#

The clearest case of bioinformatics disrupting an old process: within about seven years of the first official genomic evaluations, young genomic bulls made up most of the US Holstein market — the decades-old progeny-testing system was displaced by DNA data and statistics.

First article of digital robotics (added 2026-10-06, evidence-first: grade D3).