Changes in genetic selection differentials and generation intervals in US Holstein dairy cattle as a result of genomic selection

Abstract

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.

Accelerating genetic gains in legumes for the development of prosperous smallholder agriculture: integrating genomics, phenotyping, systems modelling and agronomy

“…The use of GS for accelerating genetic gains, based on genomic-estimated breeding values predicted using genome-wide dense markers, has been deployed extensively in dairy cattle (Van Raden et al, 2009). García-Ruiz et al (2016) reported a positive impact of GS on cattle breeding through drastic reduction of generation interval and increased selection intensity for low heritable traits. Initially, computer simulations and parametric and non-parametric statistical models were used on maize and wheat datasets to study the prediction accuracies in real plant breeding scenarios (Bernardo and Yu, 2007;de los Campos et al, 2009;Crossa et al, 2010Crossa et al, , 2011.…”

“…The impact of GS and generation intervals in cattle breeding was first systematically studied by de Roos et al (2010). Recently, García-Ruiz et al (2016) reported that decreased generation interval and increased selection intensity for low heritable traits is as a result of the positive impact of GS on the US cattle industry. Genomic selection in combination with a reduced generation interval may double the rate of genetic gain while keeping the rate of inbreeding per generation constant.…”

Evaluating Sequence-Based Genomic Prediction with an Efficient New Simulator

“…This was the first species where GS was applied due to its peculiar population structure, since GS can be quite effective in reducing the long generation interval in dairy cattle (García-Ruiz et al 2016). Currently, GS is being extended to other species.…”

Eigenvector index for two female fertility traits based in random regression coefficients matrix in Holstein cows

“…Nowadays, fertility is included in national selection index of many countries (Miglior et al, 2005) and improvement on daughter pregnancy rates has been found from the use of genomic selection (García-Ruiz et al, 2016). However, selection for improved fertility is a complex task.…”