Changes in genetic trends in US dairy cattle since the implementation of genomic selection

Genomic selection increases accuracy and decreases generation interval, accelerating genetic changes in populations. Assumptions of genetic improvement must be addressed to quantify the magnitude and direction of change. Genetic trends of US dairy cattle breeds were examined to determine the genetic gain since the implementation of genomic evaluations in 2009. Inbreeding levels and generation intervals were also investigated. Breeds included Ayrshire, Brown Swiss, Guernsey, Holstein (HO), and Jersey (JE), which were characterized by the evaluation breed the animal received. Mean genomic predicted breeding values (PBV¯) were analyzed per year to calculate genetic trends for bulls and cows. The data set contained 154,008 bulls and 33,022,242 cows born since 1975. Breakpoints were estimated using linear regression, and nonlinear regression was used to fit the piecewise model for the small sample number in some years. Generation intervals and inbreeding levels were also investigated since 1975. Milk, fat, and protein yields, somatic cell score, productive life, daughter pregnancy rate, and livability PBV¯ were documented. In 2017, 100% of bulls in this data set were genotyped. The percentage of genotyped cows has increased 23 percentage points since 2010. Overall, production traits have increased steadily over time, as expected. The HO and JE breeds have benefited most from genomics, with up to 192% increase in genetic gain since 2009. Due to the low number of observations, trends for Ayrshire, Brown Swiss, and Guernsey are difficult to infer from. Trends in fertility are most substantial; particularly, most breeds are trending downwards and daughter pregnancy rate for JE has been decreasing steadily since 1975 for bulls and cows. Levels of genomic inbreeding are increasing in HO bulls and cows. In 2017, genomic inbreeding levels were 12.7% for bulls and 7.9% for cows. A suggestion to control this is to include the genomic inbreeding coefficient with a negative weight to the selection index of bulls with high future genomic inbreeding levels. For sires of bulls, the current generation intervals are 2.2 yr in HO, 3.2 in JE, 4.4 in Brown Swiss, 5.1 in Ayrshire, and 4.3 in Guernsey. The number of colored breed bulls in the United States is currently at an extremely low level, and this number will only increase with a market incentive or additional breed association involvement. Increased education and extension could be beneficial to increase knowledge about inbreeding levels, use of genomics and genetic improvement, and genetic diversity in the genomic selection era.

Invited review: The future of selection decisions and breeding programs: What are we breeding for, and who decides?

Genetic selection has been a very successful tool for the long-term improvement of livestock populations, and the rapid adoption of genomic selection over the last decade has doubled the rate of gain in some populations. Breeding programs seek to identify genetically superior parents of the next generation, typically as a function of an index that combines information about many economically important traits into a single number. In the United States, the data that drive this system are collected through the national dairy herd improvement program that began more than a century ago. The resulting information about animal performance, pedigree, and genotype is used to compute genomic evaluations for comparing and ranking animals for selection. However, the full expression of genetic potential requires that animals are placed in environments that can support such performance. The Agricultural Research Service of the US Department of Agriculture and the Council on Dairy Cattle Breeding collaborate to deliver state-of-the-art genomic evaluations to the dairy industry. Today, most breeding stock are selected and marketed using the net merit dollars (NM$) selection index, which evolved from 2 traits in 1926 (milk and fat yield) to a combination of 36 individual traits following the last NM$ update in 2018. Updates to NM$ require the estimation of many different values, and it can be difficult to achieve consensus from stakeholders on what should be added to, or removed from, the index at each review, and how those traits should be weighted. Over time, the majority of the emphasis in the index has shifted from yield traits to fertility, health, and fitness traits. Phenotypes for some of these new traits are difficult or expensive to measure, or require changes to on-farm habits that have not been widely adopted. This is driving interest in sensor-based systems that provide continuous measurements of the farm environment, individual animal performance, and detailed milk composition. There is also a need to capture more detailed data about the environment in which animals perform, including information about feeding, housing, milking systems, and infectious and parasitic load. However, many challenges accompany these new technologies, including a lack of standardization or validation, need for high-speed internet connections, increased computational requirements, and interpretations that are often not backed by direct observations of biological phenomena. This work will describe how US selection objectives are developed, as well as discuss opportunities and challenges associated with new technologies for measuring and recording animal performance.

Estimation of the economic value of herd-life length based on simulated changes in survival rate

Functional traits are an important aspect of long‐term breeding strategies for dairy cattle. In this regard, it is necessary to develop simple methods for estimating the economic value of herd life. In this study, the economic daily value of herd life was estimated when survival rate varied between −0.05 and 0.05 from the basal survival rate. The extension days per survival rate were 26.5 days in Hokkaido and 20.3 days in other regions. The increases in values of annual income per day of herd life were 95.18 yen in Hokkaido and 101.80 yen in other regions. The relative economic weights of milk yield to herd life per genetic standard deviation were 0.668 in Hokkaido and 1.03 in other regions. Estimated increments in yearly profits based on young sire selection for herd life were 963 yen in Hokkaido and 1,030 yen in other regions. The estimated increments in annual profits based on young sire selection for milk yield were 1,268 yen in Hokkaido and 2,097 yen in other regions. Given that economic value was linearly correlated with herd‐life length, the linear regression coefficients between these factors could be used to estimate the economic value of herd‐life length.

Review: Applications and benefits of sexed semen in dairy and beef herds

The use of sexed semen in dairy and beef cattle production provides a number of benefits at both farm and industry levels. There is an increasing demand for dairy and beef products across the globe, which will necessitate a greater focus on improving production efficiency. In dairy farming, there is surplus production of unwanted male calves. Male dairy calves increase the risk of dystocia compared with heifer calves, and as an unwanted by-product of breeding with conventional semen, they have a low economic value. Incorporating sexed semen into the breeding programme can minimise the number of unwanted male dairy calves and reduce dystocia. Sexed semen can be used to generate herd replacements and additional heifers for herd expansion at a faster rate from within the herd, thereby minimising biosecurity risks associated with bringing in animals from different herds. Furthermore, the use of sexed semen can increase herd genetic gain compared with use of non-sorted semen. In dairy herds, a sustainable breeding strategy could combine usage of sexed semen to generate replacements only, and usage of beef semen on all dams that are not suitable for generating replacements. This results in increased genetic gain in dairy herd, increased value of beef output from the dairy herd, and reduced greenhouse gas emissions from beef. It is important to note, however, that even a small decrease in fertility of sexed semen relative to conventional semen can negate much of the economic benefit. A high fertility sexed semen product has the potential to accelerate herd expansion, minimise waste production, improve animal welfare and increase profitability compared with non-sorted conventional semen.

The sensitivity of predicted financial and genetic gains in Holsteins to changes in the economic value of traits

The objective of this study was to assess the impact of using different relative economic values (REVs) in selection indices on predicted financial and trait gains from selection of sires of cows and on the choice of leading Holstein bulls available in the UK dairy industry. Breeding objective traits were milk yield, fat yield, protein yield, lifespan, mastitis, non-return rate, calving interval and lameness. Relative importance of a trait, as estimated by a.h(2), was only moderately related to the rate of financial loss or total economic merit (ΔTEM) per percentage under- or overestimation of REV (r = 0.38 and 0.29, respectively) as a result of the variance-covariance structure of traits. The effects on TEM of under- or overestimating trait REVs were non-symmetrical. TEM was most sensitive to incorrect REVs for protein, fat, milk and lifespan and least sensitive to incorrect calving interval, lameness, non-return and mastitis REVs. A guide to deciding which dairy traits require the most rigorous analysis in the calculation of their REVs is given. Varying the REVs within a fairly wide range resulted in different bulls being selected by index and their differing predicted transmitting abilities would result in the herds moving in different directions in the long term (20 years). It is suggested that customized indices, where the farmer creates rankings of bulls tailored to their specific farm circumstances, can be worthwhile.

Triennial Lactation Symposium: Opportunities for improving milk production efficiency in dairy cattle

Increasing feed costs and the desire to improve environmental stewardship have stimulated renewed interest in improving feed efficiency of livestock, including that of US dairy herds. For instance, USDA cost projections for corn and soybean meal suggest a 20% increase over 2010 pricing for a 16% protein mixed dairy cow ration in 2011, which may lead to a reduction in cow numbers to maintain profitability of dairy production. Furthermore, an October 2010 study by The Innovation Center for US Dairy to assess the carbon footprint of fluid milk found that the efficiency of feed conversion is the single greatest factor contributing to variation in the carbon footprint because of its effects on methane release during enteric fermentation and from manure. Thus, we are conducting research in contemporary US Holsteins to identify cows most efficient at converting feed to milk in temperate climates using residual feed intake (RFI), a measure used successfully to identify the beef cattle most efficient at converting feed to gain. Residual feed intake is calculated as the difference between predicted and actual feed intake to support maintenance and production (e.g., growth in beef cattle, or milk in dairy cattle). Heritability estimates for RFI in dairy cattle reported in the literature range from 0.01 to 0.38. Selection for a decreased RFI phenotype can reduce feed intake, methane production, nutrient losses in manure, and visceral organ weights substantially in beef cattle. We have estimated RFI during early lactation (i.e., to 90 d in milk) in the Beltsville Agricultural Research Center Holstein herd and observed a mean difference of 3.7 kg/d (P < 0.0001) in actual DMI between the efficient and inefficient groups (±0.5 SD from the mean RFI of 0), with no evidence of differences (P > 0.20) in mean BW, ADG, or energy-corrected milk exhibited between the 2 groups. These results indicate promise for using RFI in dairy cattle to improve feed conversion to milk. Previous and current research on the use of RFI in lactating dairy cattle are discussed, as well as opportunities to improve production efficiency of dairy cattle using RFI for milk production.