From the Cover: PNAS Plus: Changes in genetic selection differentials and generation intervals in US Holstein dairy cattle as a result of genomic selection

Seven years after the introduction of genomic selection in the United States, it is now possible to evaluate the impact of this technology on the population. Selection differential(s) (SD) and generation interval(s) (GI) were characterized in a four-path selection model that included sire(s) of bulls (SB), sire(s) of cows (SC), dam(s) of bulls (DB), and dam(s) of cows (DC). Changes in SD over time were estimated for milk, fat, and protein yield; somatic cell score (SCS); productive life (PL); and daughter pregnancy rate (DPR) for the Holstein breed. In the period following implementation of genomic selection, dramatic reductions were seen in GI, especially the SB and SC paths. The SB GI reduced from ∼7 y to less than 2.5 y, and the DB GI fell from about 4 y to nearly 2.5 y. SD were relatively stable for yield traits, although modest gains were noted in recent years. The most dramatic response to genomic selection was observed for the lowly heritable traits DPR, PL, and SCS. Genetic trends changed from close to zero to large and favorable, resulting in rapid genetic improvement in fertility, lifespan, and health in a breed where these traits eroded over time. These results clearly demonstrate the positive impact of genomic selection in US dairy cattle, even though this technology has only been in use for a short time. Based on the four-path selection model, rates of genetic gain per year increased from ∼50–100% for yield traits and from threefold to fourfold for lowly heritable traits.Genetic improvement of livestock during the second half of the 20th century using pedigree and performance data has been very successful, particularly in dairy cattle populations (e.g., ref. 1). The improvement of dairy cattle has depended heavily on the use of artificial insemination (AI) to maximize the impact of elite bulls globally. Historically, progeny testing (2), or the characterization of these AI bulls by measuring and comparing performance of daughters, has been a critical step in identifying the very best bulls for widespread use. However, traditional genetic improvement schemes in dairy cattle have been limited by time required and expense of the progeny test paradigm. This process remained relatively slow because of the substantial time needed to accumulate sufficient daughter phenotypes to compute genetic evaluations with high accuracy. The recent development of genomic selection (3) programs based on single-nucleotide polymorphism genotypes was expected to increase rates of genetic gain (3, 4) in several ways, including shortened generation interval(s) (GI) (5, 6) and increased reliability of predicted breeding value(s) (PBV) (7). A doubling of rates of genetic gain was predicted when comparing genomic evaluations and traditional progeny testing schemes (5, 6, 8, 9). These advantages have been demonstrated in simulations (10, 11), and increased accuracies have been documented in the US Holstein population (12), but response to the incorporation of genomic data into dairy cattle evaluations has not been characterized.In April 2008, the United States released its first unofficial genomic PBV, and official evaluations for Holsteins and Jerseys were published in January 2009 (9). Genomic selection was rapidly adopted by the industry, and more than half of all AI matings in the United States are now made to genomically tested young bulls (13). Genomic breeding values have been available for 6 y, so a characterization was conducted of the dynamic changes in rates of genetic gain associated with alterations in GI and selection differential(s) (SD). Rendel and Robertson (14) described a four-path model of genetic improvement in which genetic progress occurs with differing selection dynamics, partitioned into improvement due to genetic changes in sire(s) of bulls (SB), sire(s) of cows (SC), dam(s) of bulls (DB), and dam(s) of cows (DC). The objective of this study was to measure the impact of genomic selection on SD and GI in US Holstein cattle using this four-path model, and to compare these observed results with those results predicted by theory.