Symposium review: Building a better cow—The Australian experience and future perspectives

Self Cite

Dairying in Australia is practiced in highly diverse climatic conditions and production systems, which means that re-ranking of genotypes could occur across environments that vary in temperature and humiditythat is, genotype-by-environment interactions (G × E) may exist. The objective of this study was to investigate G × E for heat tolerance with respect to milk production traits in Australian Holsteins. A total of 6.7 million test-day milk yield records for first, second, and third lactations from 491,562 cows and 6,410 sires that had progeny in different climatic environments were included in the analysis. The environmental gradient used was the temperature-humidity index (THI) calculated from climate data from 163 Australian public weather stations between 2003 and 2017. Data were analyzed using univariate reaction norm (RM) sire model, and the results were compared with multitrait model (MT). The MT analysis treated test-day yields at 5th percentile (THI = 61; i.e., thermoneutral conditions), 50th percentile (THI = 67; i.e., moderate heat stress conditions), and 95th percentile (THI = 73; i.e., high heat stress conditions) of the trajectory of THI as correlated traits. A THI series of 61, 67, and 73, for example, is equivalent to average temperature and relative humidity of approximately 20°C and 45%, 25°C and 45%, and 31°C and 50%, respectively. We observed some degree of heterogeneity of additive (AG) and permanent environmental (PE) variance over the trajectory THI from RM analysis, with estimates decreasing at higher THI values more steeply for PE than for AG variance. The genetic correlations of the tests between the 5th and 95th percentiles of THI for milk, protein, and fat yield from RM were 0.88 ± 0.01 (standard error), 0.79 ± 0.01, and 0.86 ± 0.01, respectively , whereas the corresponding estimates from MT were 0.86 ± 0.02, 0.84 ± 0.03, and 0.87 ± 0.03. We observed lower genetic correlations between the 5th and 95th percentiles of THI for milk tests from recent years (i.e., 2009 and 2017) compared with earlier years (i.e., 2003 and 2008), which suggests that the level of G × E is increasing in the studied population and should be monitored especially in anticipation of future expected increase in daily average temperature and frequency of heat events. Overall, our results indicate presence of G × E at the upper extreme of the trajectory of THI, but the current extent of sire re-ranking may not justify providing separate genetic evaluations for different levels of heat stress. However, variations observed in the sire sensitivity to heat stress suggest that dairy herds in high heat load conditions could benefit more from using heat-tolerant or resilient sires.

Section: Discussionmentioning

confidence: 77%

Section: Introductionmentioning

confidence: 99%

Genotype-by-environment (temperature-humidity) interaction of milk production traits in Australian Holstein cattle

Cheruiyot

Nguyen

Haile‐Mariam

et al. 2020

Self Cite

“…Milk yield may temporarily decline at a later lactational stage but can recover as soon as energy and nutrient supply meet the requirements of the mammary gland. Today, animal breeding and genetics have the tools to identify the genetic basis of phenotypic traits that can be annotated to defined genomic regions (Berry, 2018;Pryce et al, 2018). The disciplines of Figure 1.…”

Section: Introductionmentioning

confidence: 99%

Invited review: Metabolic challenges and adaptation during different functional stages of the mammary gland in dairy cows: Perspectives for sustainable milk production

Gross

Bruckmaier

2019

Milk production of dairy cows has increased markedly during recent decades and continues to increase further. The evolutionarily conserved direction of nutrients to the mammary gland immediately after calving provided the basis for successful selective breeding toward higher performance. Considerable variation in adaptive responses toward energy and nutrient shortages exists; however, this variation in adaptability recently gained interest for identifying more metabolically robust dairy cows. Metabolic challenges during periods of high milk production considerably affect the immune system, reproductive performance, and product quality as well as animal welfare. Moreover, growing consumer concerns need to be taken into consideration because the public perception of industrialized dairy cow farming, the high dependency on feed sources suitable for human nutrition, and the apparently abundant use of antibiotics may affect the sales of dairy products. Breeding for high yield continues, but the metabolic challenges increasingly come close to the adaptational limits of meeting the mammary gland's requirements. The aim of the present review is to elucidate metabolic challenges and adaptational limitations at different functional stages of the mammary gland in dairy cows. From the challenges and adaptational limitations, we derive perspectives for sustainable milk production. Based on previous research, we highlight the importance of metabolic plasticity in adaptation mechanisms at different functional stages of the mammary gland. Metabolic adaptation and plasticity change among developing, nonlactating, remodeling, and lactational stages of the mammary gland. A higher metabolic plasticity in early-lactating dairy cows could be indicative of resilience, and a high performance level without an extraordinary occurrence of health disorders can be achieved.

“…Today, none of the modern selection indices used globally are based solely on milk fat and protein production; milk production traits typically comprise approximately 50% of the total index (Cole and VanRaden, 2018). In addition to milk production traits, modern indices incorporate functional traits, including those that are specifically designed to improve reproductive performance (Miglior et al, 2017;Cole and VanRaden, 2018;Pryce et al, 2018). This change in dairy selection indices has reversed the decline in reproductive traits as well as other important functional traits in dairy cattle (Carvalho et al, 2018;Cole and VanRaden, 2018).…”

Section: Introductionmentioning

confidence: 99%

Symposium review: Selection for fertility in the modern dairy cow—Current status and future direction for genetic selection

Lucy

2019

The establishment of pregnancy following insemination is the primary definition of fertility in most dairy systems. Highly fertile cows establish pregnancy sooner after calving and require fewer inseminations than lower-fertility cows. Pregnancy occurs through a series of individual events in sequence. In postpartum cows, for example, the uterus involutes, estrous cycles are re-established, estrus is expressed and detected, sperm are deposited in the reproductive tract and capacitate, ovulation occurs and is followed by fertilization, and the corpus luteum forms and produces sufficient progesterone to maintain pregnancy. The oviduct supports early cleavage and the uterus establishes a receptive environment for the developing pregnancy. Each individual event is theoretically heritable and these events collectively contribute to the phenotype of pregnancy after insemination. Across most dairy systems, genetic selection for fertility in cows is primarily based on reduced days from calving to pregnancy (i.e., days open). Dairy systems differ with respect to reproductive management applied to cows, which may affect the relative importance of individual components to the overall fertility of the cow. In some systems, cows are inseminated after detected estrus with minimal intervention. In these systems, days open effectively captures the summation of the individual components of fertility. More intensive systems use hormonal treatments (e.g., PGF 2α , GnRH) followed by timed artificial insemination (AI). Timed AI does not invalidate days open but the individual components that contribute to days open may be more or less important. Selection of cows for days open within populations that are managed differently may place different pressures on the individual components of fertility. Ensuring uniform performance of future cows across a variety of reproductive management systems may require a greater understanding of the underlying genetics of the individual components of fertility.