Linear and threshold model genetic parameters for disease, fertility and milk production in dairy cattle

Genetic parameters for milk yield and reproductive traits in Honduran Holstein cattle

The aim of this study was to estimate the (co)variance components and genetic parameters for milk yield adjusted to 305d (MY305), calving-to-conception interval (CCI), number of services per conception (NSC) and calving interval (CI) of Honduran Holstein cows, by fitting a bivariate animal model using Maximum Restricted Likelihood procedures. Model included the fixed effects of calving number, the contemporary calving group (farm-season-year of calving and the cow age as covariate). The estimated means and standard deviations for MY, CCI, NSC and CI were, 5098.60 ± 1564.32 kg, 168.27 ± 104.71 days, 2.46 ± 1.69 services, and 448.73 ± 109.16 days, respectively; and their estimated heritabilities were 0.21 ± 0.05, 0.03 ± 0.028, 0.02 ± 0.024 and 0.06 ± 0.04, respectively. The genetic correlations between MY305 and CCI, NSC and CI were positive and antagonist, with values of 0.64 ± 0.52, 0.99 ± 0.56, and 0.32 ± 0.24 respectively. Even though moderate to low heritability was estimated for MY305, systematic selection for milk yield, with a reduction in reproductive efficiency, if considered as the only selection criterion is important to be considered. By including reproductive traits and considering permanent environment effects into the breeding program, might yield a slow, but constant and permanent improvement over time.

A comprehensive meta-analysis of genetic parameters for resilience and productivity indicator traits in Holstein cattle

Selection for resilience indicator (RIND) traits in Holstein cattle is becoming an important breeding objective as the worldwide population is expected to be exposed to increased environmental stressors due to both climate change and changing industry standards. However, genetic correlations between RIND and productivity indicator (PIND) traits, which are already being selected for and have the most economic value, are often unfavorable. As a result, it is necessary to fully understand these genetic relationships when incorporating novel traits into selection indices, so that informed decisions can be made to fully optimize selection for both groups of traits. In the past 2 decades, there have been many estimates of RIND traits published in the literature, albeit in small populations. To provide valuable pooled summary estimates, a random-effects meta-analysis was conducted for heritability and genetic correlation estimates for PIND and RIND traits in worldwide Holstein cattle. In total, 926 heritability estimates for 9 PIND and 27 RIND traits, along with 362 estimates of genetic correlation (PIND × RIND traits) were collected. Resilience indicator traits were grouped into the following subgroups: Metabolic Diseases, Hoof Health, Udder Health, Fertility, Heat Tolerance, Longevity, and Other. Pooled estimates of heritability for PIND traits ranged from 0.201 ± 0.05 (energy-corrected milk) to 0.377 ± 0.06 (protein content), while pooled estimates of heritability for RIND traits ranged from 0.032 ± 0.02 (incidence of lameness, incidence of milk fever) to 0.497 ± 0.05 (measures of body weight). Pooled estimates of genetic correlations ranged from -0.360 ± 0.25 (protein content vs. milk acetone concentration) to 0.535 ± 0.72 (measures of fat-to-protein ratio vs. milk acetone concentration). Additionally, out of 243 potential genetic correlations between PIND and RIND traits that could have been reported, only 40 had enough published estimates to implement the meta-analysis model. Our results confirmed that the interactions between PIND and RIND traits are complex, and all relationships should be evaluated when incorporating novel traits into selection indices. This study provides a valuable reference for breeders looking to incorporate RIND traits for Holstein cattle into selection indices.

Effect of temperature-humidity index on the evolution of trade-offs between fertility and production in dairy cattle

BACKGROUND

In the current context of climate change, livestock production faces many challenges to improve the sustainability of systems. Dairy farming, in particular, must find ways to select animals that will be able to achieve sufficient overall production while maintaining their reproductive ability in environments with increasing temperatures. With future forecasted climate conditions in mind, this study used data from Holstein and Montbeliarde dairy cattle to: (1) estimate the genetic-by-temperature-humidity index (THI) interactions for female fertility, and (2) evaluate the production-fertility trade-off with increasing values of THI.

RESULTS

Two-trait random regression models were fitted for conception rate (fertility) and test-day protein yield (production). For fertility, genetic correlations between different THI values were generally above 0.75, suggesting weak genotype-by-THI interactions for conception rate in both breeds. However, the genetic correlations between the conception rate breeding values at the current average THI (THI = 50, corresponding to a 24-h average temperature of 8 °C at 50% relative humidity) and their slopes (i.e., potential reranking) for heat stress scenarios (THI > 70), were different for each breed. For Montbeliarde, this correlation tended to be positive (i.e., overall the best reproducers are less affected by heat stress), whereas for Holstein it was approximately zero. Finally, our results indicated a weak antagonism between production and fertility, although for Montbeliarde this antagonism intensified with increasing THI.

CONCLUSIONS

Within the range of weather conditions studied, increasing temperatures are not expected to exacerbate the fertility-production trade-off. However, our results indicated that the animals with the best breeding values for production today will be the most affected by temperature increases, both in terms of fertility and production. Nonetheless, these animals should remain among the most productive ones during heat waves. For Montbeliarde, the current selection program for fertility seems to be adequate for ensuring the adaptation of fertility traits to temperature increases, without adverse effects on production. Such a conclusion cannot be drawn for Holstein. In the future, the incorporation of a heat tolerance index into dairy cattle breeding programs would be valuable to promote the selection of animals adapted to future climate conditions.

Genetic relationships between reproductive and production traits in Jersey crossbred cattle

The study aimed to estimate the genetic parameters of different reproductive traits namely age at first calving (AFC), calving interval (CI), days open (DO) and number of service per conception (NSPC) and their associations with productive traits including 305-day milk yield (305DMY), total lactation milk yield (TLMY) and lactation length (LL) of Jersey crossbred cattle maintained at Kalyani, Nadia, West Bengal, India. Genetic parameters of reproductive traits and their correlations with productive traits were estimated by Restricted Maximum Likelihood method and Bayesian approach. Using both analytical approaches, the estimates of heritability for AFC, CI, DO and NSPC ranged from 0.12 -0.15, 0.05-0.08, 0.08-0.09 and 0.04-0.06, respectively. Low proportion of variances associated with permanent environmental effect of animals (c2 effect) were detected for CI (0.08-0.10), DO (0.09-0.11) and NSPC (0.05-0.06) in both the methods. Repeatability measures for all the reproductive traits considered in this study were low to moderate in nature, which ranged from 0.09 to 0.17. Genetic correlations between different reproductive traits were positive and low (0.05) to high (0.98) in magnitude except AFC-NSPC. Low and negative genetic correlations of AFC with 305DMY and TLMY were favourable and indicated animals with high milk yield had early age of maturity. Positive genetic correlations between CI, DO and NSPC with all production traits implied the antagonism relationships among these traits, therefore in any breeding program for improvement of production traits via selection, the reproductive traits should be taken into account as well.

Estimation of genetic parameters for fertility traits in Chinese Holstein of south China

Introduction: Chinese Holstein in South China suffer heat stress for a long period, which leads to evolutionary differences from Chinese Holstein in North China. The aim of this study was to estimate the genetic parameters of fertility traits for Chinese Holstein in South China. Methods: A total of 167,840 Chinese Holstein heifers and cows from Guangming Animal Husbandry Co., LTD farms were used in this study. The fertility traits analyzed were calving interval (CI), days open (DO), age of first service (AFS), age of first calving (AFC), calving to first insemination (CTFS), first insemination to conception (FSTC), gestation length (GL), non-return rate to 56 days (NRR), and number of services (NS). Results: The descriptive statistics revealed that the same trait in heifers performed better than in cows, which was consistent with the other studies. The heritabilities of fertility traits in this study ranged from close to 0 (for NS of cows) to 0.2474 (for AFC of heifers). The genetic correlation of NRR between heifers and cows was 0.9993, which indicates that the NRR for heifers and cows could be treated as one trait in this population. Conclusion: The heritabilities of fertility traits in Chinese Holstein in south China were quite different from the heritabilities of fertility traits in North China. NRR56, NS, AFC, and CI were suggested to be included into the selection index to improve fertility performance of Chinsese Holstein of south China. The results of this study could provide genetic parameters for the animal breeding program of Chinese Holstein in the south of China.

Genetic parameters for health traits and their association with fertility and milk production in Chinese Holsteins

Herd health is one of the key problems influencing the efficiency of the dairy industry. Genetic selection, with a focus on animal health, is important for herd improvement. This study aimed to estimate genetic parameters for health traits and their correlations with fertility and milk production traits in dairy cattle. Based on records from 58,549 lactating cows calved between 2015 and 2021, a total of 24 health traits (six composite health traits and 18 independent health traits), four fertility traits and five milk production traits were analysed. First, linear and threshold animal models were used to estimate the variance components and heritabilities of the health traits. Second, a bivariate linear animal model was used to estimate genetic correlations among all 24 health traits. Finally, a bivariate linear animal model based on records from the first lactation was used to estimate the correlations between health traits and fertility or milk production traits. The results showed that all health traits had low heritabilities, ranging from 0.002 (0.001) to 0.048 (0.004) in the linear model and from <0.001 (0.021) to 0.226 (0.035) in the threshold model. Genetic correlations between health traits across categories were generally low, whereas the relatively high genetic correlations were found between health traits within the same category. In this study, only a few significant and moderate genetic correlations were observed between health traits and fertility or milk production traits. Clinical mastitis showed relatively moderate correlations with fertility traits, ranging from 0.277 (0.113) (interval from first to last insemination) to 0.401 (0.104) (calving interval). Moreover, there were moderate genetic correlations between hoof health and milk production traits. The results from the current study will support balanced dairy breeding to genetically improve disease resistance in dairy cows.

Profitability Optimization of Dairy Farms: The Effect of Pregnancy Rate and Culling Decision

One of the most important decisions in dairy cattle production today is the correct choice of culling time for cows. In the culling decision process, the farmer has to take into account a number of factors, the complexity of which makes the decision-making task difficult. A crucial factor is the evolution of reproductive indicators. The aim of the research was to develop a microsimulation method that can be used to easily investigate the impact on profitability of increasing pregnancy rates and when the culling decision is made. In the microsimulation, the stock was examined without changing any other conditions. A microsimulation method has been developed to determine with high accuracy the effect of the pregnancy rate and the increase in culling days on the economic indicators of individual dairy farms. By microsimulation, the effect of changing these two parameters on the expected milk production of cows, the most important economic indicator for cattle farms, was investigated. The other parameters of economic importance were simulated using a cattle farm database. The purpose of microsimulation is to assist in producing certain managerial decisions in order to achieve better profitability and economic efficiency. In summary, the results showed that increasing the pregnancy rate can successfully reduce the length of the calving interval, but the improved pregnancy rate did not show a significant increase in milk production. In order to obtain results that can be used by farms, the authors intend to further develop the model in the future, adapting it to farms and taking into account their specificities.

Genetical analysis of mastitis and reproductive traits in first-parity Holstein cows using standard and structural equation modelling

The present study aimed to investigate the causal relationships between clinical mastitis and some reproductive traits, including success at first insemination (SFI), the number of inseminations to pregnancy (INS), the interval from calving to first service (CTFS), first and last service interval (IFL), and open days (OD) in first-parity Holstein cows. For this purpose, the records of 58 281 first parity Holstein cows were analysed. These data sets were collected from 17 large dairy herds from 2008 to 2017. Recursive Mixed Models (RMMs) were applied and compared with the estimations under Standard Mixed Models. Then, one trivariate and three bivariate Gaussian-threshold models were used for the analyses. Recursive models were applied, considering that clinical mastitis can influence fertility traits. Mastitis is considered a covariate for the reproductive traits to determine their causal relationship. The results of this study indicated that causal effects of mastitis on SFI (on the observed scale, %), CTFS, IFL, OD, and INS were -5.7%, 3.3 days, 12.27 days, seven days, and 0.26 services, respectively. The estimated structural coefficients of the recursive models in the first parity imply that mastitis significantly lengthened the fertility interval and decreased the conception rate. In addition, genetic, residual, and phenotypic correlations between mastitis and the reproductive traits under both models were statistically significant. Results of genetic correlations between mastitis and fertility traits suggest that more incidence of mastitis during lactation is related to the delays in the heat show and pregnancy rate after insemination. In summary, considering the causal effects under RMMs may be advantageous to comprehend complicated relationships between complex traits better.

Birth weight and stillbirth genetic parameter estimation in a river buffalo simulated population

Stillbirth (SB) is a threshold character that has been detected as the most important factor affecting the future reproductive life of an animal. In buffaloes, stillbirth accounts for approximately 42% of all reproductive disorders being considered as the main reproductive disorder in buffalo calves. The present study aimed to estimate the heritability values and to determine the genetic and phenotypic correlation between stillbirth rate and birth weight (BW) using a Bayesian approach via Gibbs sampling method in a river buffalo population. A stochastic simulation was used to create a population in which random mating was used for 15 discrete generations. A bivariate animal model including maternal effects was used. Maternal effects were significant (p < .05) for both BW and SB. The results showed that when the SB rate increased from 1% to 50%, the estimated direct heritability of SB increased. Yet, by increasing the SB rate from 50% to 99%, a decrease of the SB estimated direct heritability was observed. The genetic correlation between BW and SB was decreased by increasing the level of occurrence of SB in the population from 1% to 99%. The root mean square error (RMSE) of heritability was increased from 40% to 70% level of occurrence of SB. Based on findings, it can be concluded that to reduce stillbirth rate in the population, it is possible to use genetic improvement program and birth weight could be one of the main components of a selection goal.

Estimation of Genetic Parameters for Heifer and Cow Fertility Traits Derived from On-Farm AI Service Records of South African Holstein Cattle

This study aimed to derive additional fertility traits from service data and estimate their genetic parameters for their possible inclusion in the South African Holstein cattle breeding programs. Service records (n = 64,464) were collected from 18 South African Holstein herds using on-farm automated milk recording systems. Using a multivariate model, the data were used to estimate heritabilities and correlations among several fertility traits. The pedigree data consisted of information on 18,592 animals born between 1981 and 2013. Heritability estimates observed were low to moderate (0.02 ± 0.00 to 0.24 ± 0.00), indicating that there is some genetic basis for the explored fertility traits to warrant selection. The genetic correlations observed between fertility traits were generally favorable, with some high correlations between age at first service (AFS) and services per conception for heifers (SPCh) (0.73 ± 0.00) and between days from calving to first service (CFS) and services per conception for cows (SPC) (0.90 ± 0.01). Positive genetic correlations indicate that improvement in one trait is coupled with a correlated genetic increase in another trait. The studied fertility traits could be used in addition to AFC and CI to serve as a basis for the selection of reproduction in dairy cattle to minimize selection bias.

Repeatability of Health and Welfare Traits and Correlation with Performance Traits in Dairy Goats Reared under Low-Input Farming Systems

The objectives of the study were to estimate the repeatability of health and welfare traits and investigate their association with performance in three breeds of dairy goats reared under low-input farming systems in Greece. A total of 1210 goats of Eghoria (n = 418), Skopelos (n = 429), and Damascus (n = 363) breeds were assessed. Udder health, parasitic resistance, welfare, milk yield and quality, and body condition score were recorded monthly for two milking periods. Udder health records included somatic cell count (SCC) and total viable count (TVC). Based on combinations of SCC and TVC and thresholds set at >106 cells/mL and >2 × 104 cfu/mL, respectively, additional udder health phenotypes were defined. Parasitism included myiasis, tick infestation, gastrointestinal nematode (GIN) and cestode faecal egg count (FEC), and lungworm faecal larval count (FLC). Infection with each of the endoparasites was defined based on FEC/FLC. Welfare assessment parameters included the presence of ear and horn injuries, ocular and nasal discharge, body and udder abscesses, injury and lesions on the skin of different regions, diarrhoea, hernias, overgrown hooves, arthritis, lameness, and udder asymmetry. Trait repeatability and animal correlations were estimated. Significant (p < 0.05) repeatability was reported for all udder health and most welfare traits in all breeds, GIN and cestode FEC, and GIN and lungworm infection in Eghoria, and myiasis in Skopelos. Correlations of health and most of welfare traits with performance were non-significant or favourable. Overall, results demonstrate potential to improve health and welfare of the studied breeds without compromising performance.

Robustness scores in fattening pigs based on routinely collected phenotypes: determination and genetic parameters

The objective was to determine operational proxies for robustness based on data collected routinely on farm that allow phenotyping of these traits in fattening pigs, and to estimate their genetic parameters. A total of 7,256 pigs, from two Piétrain paternal lines (Pie and Pie NN), were tested at the AXIOM boar testing station (Azay-sur-Indre, France) from 2019 to 2021. During the fattening period (from 75 to 150 d of age), individual performance indicators were recorded (growth, backfat, loin depth, feed intake, and feed conversion ratio [FCR]) together with indicators such as insufficient growth, observable defect, symptoms of diseases, and antibiotic and anti-inflammatory injections. These indicators were combined into three categorical robustness scores: R1, R2, and R3. Genetic parameters were estimated using an animal linear model. The robustness score R2 (selectable or not selectable animal) that combined information from status at testing and mortality had the highest heritability estimates of 0.08 ± 0.03 for Pie NN line and a value of 0.09 ± 0.02 for Pie line, compared with traits R1 and R3. The score R3 that combines information from the score R2 with antibiotic and anti-inflammatory injections presented slightly lower heritability estimates (0.05 ± 0.02 to 0.07 ± 0.03). Genetic correlations between R2 and R3 were high and favorable (0.93 ± 0.04 to 0.95 ± 0.03) and R2 and R3 can be considered identical with regard to the confidence interval. These two robustness scores were also highly and favorably genetically correlated with initial body weight and average daily gain, and unfavorably correlated with daily feed intake (ranging from 0.73 ± 0.06 to 0.90 ± 0.08). Estimates of genetic correlations of R2 and R3 with backfat depth and raw FCR (not standardized between starting and finishing weights) were moderate and unfavorable (0.20 ± 0.13 to 0.46 ± 0.20). A part of these genetic correlations, that are of low precision due to the number of data available, have to be confirmed on larger datasets. The results showed the interest of using routine phenotypes collected on farm to build simple robustness indicators that can be applied in breeding.

Genetic analyses of blood β-hydroxybutyrate predicted from milk infrared spectra and its association with longevity and female reproductive traits in Holstein cattle

Ketosis is one of the most prevalent and complex metabolic disorders in high-producing dairy cows and usually detected through analyses of β-hydroxybutyrate (BHB) concentration in blood. Our main objectives were to evaluate genetic parameters for blood BHB predicted based on Fourier-transform mid-infrared spectra from 5 to 305 d in milk, and estimate the genetic relationships of blood BHB with 7 reproduction traits and 6 longevity traits in Holstein cattle. Predicted blood BHB records of 11,609 Holstein cows (after quality control) were collected from 2016 to 2019 and used to derive 4 traits based on parity number, including predicted blood BHB in all parities (BHBp), parity 1 (BHB1), parity 2 (BHB2), and parity 3+ (BHB3). Single- and multitrait repeatability models were used for estimating genetic parameters for the 4 BHB traits. Random regression test-day models implemented via Bayesian inference were used to evaluate the daily genetic feature of BHB variability. In addition, genetic correlations were calculated for the 4 BHB traits with reproduction and longevity traits. The heritability estimates of BHBp, BHB1, BHB2, and BHB3 ranged from 0.100 ± 0.026 (± standard error) to 0.131 ± 0.023. The BHB in parities 1 to 3+ were highly genetically correlated and ranged from 0.788 (BHB1 and BHB2) to 0.911 (BHB1 and BHB3). The daily heritability of BHBp ranged from 0.069 to 0.195, higher for the early and lower for the later lactation periods. A similar trend was observed for BHB1, BHB2, and BHB3. There are low direct genetic correlations between BHBp and selected reproductive performance and longevity traits, which ranged from -0.168 ± 0.019 (BHBp and production life) to 0.157 ± 0.019 (BHBp and age at first calving) for the early lactation stage (5 to 65 d). These direct genetic correlations indicate that cows with higher BHBp (greater likelihood of having ketosis) in blood usually have shorter production life (-0.168 ± 0.019). Cows with higher fertility and postpartum recovery, such as younger age at first calving (0.157 ± 0.019) and shorter interval from calving to first insemination in heifer (0.111 ± 0.006), usually have lower BHB concentration in the blood. Furthermore, the direct genetic correlations change across parity and lactation stage. In general, our results suggest that selection for lower predicted BHB in early lactation could be an efficient strategy for reducing the incidence of ketosis as well as indirectly improving reproductive and longevity performance in Holstein cattle.

Genetic parameters and genetic trend of some yield traits of Holstein Friesian cattle population in Tropical Region (Teke)

This study was conducted to determine the milk yield and reproduction characteristics, genetic trend, and breeding values of Holstein cattle reared in Teke region (Antalya, Burdur, Denizli, and Isparta provinces) of Turkey. In this study, 9844 lactation and reproductive records of Holstein Friesian dairy cattle for the period of 2010 to 2017 were used. For this purpose, variance components and the heritability were calculated based on calving interval (CI) and number of inseminations per conception (NIC) from fertility characteristics and lactation length (LL), 305-day milk yield (305 DMY), and dry period (DP). It was determined that CI, NIC, LL, 305 DMY, and DP were 0.11, 0.10, 0.11, 0.33, and 0.01, respectively. The genetic trend of 305 DMY was 111.5 kg/year. The average breeding value was negative between 2005 and 2009 and positive between 2010 and 2015. In conclusion, the fact that especially 305 DMY heritability was generally higher in this study than the values reported by other studies conducted in Turkey and the genetic trend for 305 DMY was positive and high indicates that breeding value of Holstein cattle in the Teke region is high. Therefore, it can be recommended to continue the pedigree breeding of Holstein cattle in this region, keep pedigree and yield records meticulously, estimate breeding values for selecting animals with superior yield characteristics and using them in future generations, and include current biotechnological methods in breeding program to increase the efficiency in selection.

Genome Wide Prediction, Mapping and Development of Genomic Resources of Mastitis Associated Genes in Water Buffalo

Water buffalo (Bubalus bubalis) are an important animal resource that contributes milk, meat, leather, dairy products, and power for plowing and transport. However, mastitis, a bacterial disease affecting milk production and reproduction efficiency, is most prevalent in populations having intensive selection for higher milk yield, especially where the inbreeding level is also high. Climate change and poor hygiene management practices further complicate the issue. The management of this disease faces major challenges, like antibiotic resistance, maximum residue level, horizontal gene transfer, and limited success in resistance breeding. Bovine mastitis genome wide association studies have had limited success due to breed differences, sample sizes, and minor allele frequency, lowering the power to detect the diseases associated with SNPs. In this work, we focused on the application of targeted gene panels (TGPs) in screening for candidate gene association analysis, and how this approach overcomes the limitation of genome wide association studies. This work will facilitate the targeted sequencing of buffalo genomic regions with high depth coverage required to mine the extremely rare variants potentially associated with buffalo mastitis. Although the whole genome assembly of water buffalo is available, neither mastitis genes are predicted nor TGP in the form of web-genomic resources are available for future variant mining and association studies. Out of the 129 mastitis associated genes of cattle, 101 were completely mapped on the buffalo genome to make TGP. This further helped in identifying rare variants in water buffalo. Eighty-five genes were validated in the buffalo gene expression atlas, with the RNA-Seq data of 50 tissues. The functions of 97 genes were predicted, revealing 225 pathways. The mastitis proteins were used for protein-protein interaction network analysis to obtain additional cross-talking proteins. A total of 1,306 SNPs and 152 indels were identified from 101 genes. Water Buffalo-MSTdb was developed with 3-tier architecture to retrieve mastitis associated genes having genomic coordinates with chromosomal details for TGP sequencing for mining of minor alleles for further association studies. Lastly, a web-genomic resource was made available to mine variants of targeted gene panels in buffalo for mastitis resistance breeding in an endeavor to ensure improved productivity and the reproductive efficiency of water buffalo.

Likelihood of pregnancy in cows identified with different amounts of anechoic intrauterine fluid at the time of insemination

Effects of amount of anechoic intrauterine fluid (IUF) and size of largest follicle at insemination on proportion of cows pregnant as a result of AI (P/AI percentage), as well as factors associated with amount of IUF and size of the follicle were investigated. Follicle size was determined, and amount of IUF in the largest uterine segment was categorized as containing no fluid, ≤10, >10-20, and >20 mm using the ultrasonic monitor grid in 735 cows at time of insemination. Multivariable regression models were constructed to evaluate effects of different variables on P/AI percentage, and variables associated with the IUF score and follicle size. On day 30 post-insemination, the P/AI percentage was greater in cows that had >10 to 20 mm IUF than cows with no IUF (OR = 1.9, P = 0.01), but on day 70 post-insemination, the P/AI percentage was similar in cows with different amounts of IUF. Follicle size was not associated with P/AI percentage on days 30 and 70 post-insemination. Cows in spontaneous estrus, multiparous cows, cows with a cystic structure and a typically functional follicle, and Holstein cows had a greater likelihood for a larger IUF value. Primiparous cows, cows on which there was imposing of a hormonal-ovulation-synchronization regimen, and crossbred cows were more likely to have smaller follicles. In conclusion, amount of IUF at the time of insemination and size of the follicle were not associated with P/AI percentage, and several variables were associated with amount of IUF or follicle size.

Realized genetic selection differentials in Canadian Ayrshire, Jersey, and Brown Swiss dairy cattle populations

Estimated breeding values of a selection index, production, durability, health, and fertility traits from Canadian Ayrshire, Jersey, and Brown Swiss bulls and cows were used to study genetic selection differentials (GSD). The bulls and cows were born from 1950 and 1960, respectively. The GSD for the 3 Canadian dairy populations were studied along the 4-path selection model: sire-to-bull (SB), dam-to-bull (DB), sire-to-cow (SC), and dam-to-cow (DC) pathways. We also determined the variations in realized GSD due to herd and herd × year of conception in addition to the effects of some environmental factors on realized GSD of the SC and DC paths. The mean realized GSD of the DB were higher than those of other paths and were increasing for lifetime performance index, 305-d milk yield, 305-d fat yield, and 305-d protein yield in all 3 dairy cattle populations. We observed no clear trends in realized GSD for type traits in all 3 dairy cattle breeds except for the apparent increasing trends in realized GSD of mammary system, dairy strength, and feet and legs in the DB and SC paths of the Ayrshire breed. No clear patterns were observed in the realized GSD of daughter fertility in the SB, DB, and SC paths of all dairy cattle breeds. Realized GSD for somatic cell score showed increasing and favorable trends in the 3 most influential selection paths (SB, DB, and SC). Year of conception influenced realized GSD of artificial insemination bulls in Ayrshire, Jersey, and Brown Swiss dairy populations. Selection emphases for the SC path generally increased with time. There was considerable variation among herds in selection pressures applied in the SC and DC pathways but no clear association with housing system or region. This study demonstrates that variations exist among herds of minor dairy cattle breeds in their selection for economically important traits. These variations offer opportunities for further improvements in these populations.

Liability to diseases and their relation to dry matter intake and energy balance in German Holstein and Fleckvieh dairy cows

Dairy cow efficiency is increasingly important for future breeding decisions. The efficiency is determined mostly by dry matter intake (DMI). Reducing DMI seems to increase efficiency if milk yield remains the same, but resulting negative energy balance (EB) may cause health problems, especially in early lactation. Objectives of this study were to examine relationships between DMI and liability to diseases. Therefore, cow effects for DMI and EB were correlated with cow effects for 4 disease categories throughout lactation. Disease categories were mastitis, claw and leg diseases, metabolic diseases, and all diseases. In addition, this study presents relative percentages of diseased cows per days in milk (DIM), repeatability, and cow effect correlations for disease categories across DIM. A total of 1,370 German Holstein (GH) and 287 Fleckvieh (FV) primiparous and multiparous dairy cows from 12 dairy research farms in Germany were observed over a period of 2 yr. Farm staff and veterinarians recorded health data. We modeled health and production data with threshold random regression models and linear random regression models. From DIM 2 to 305 average daily DMI was 22.1 kg/d in GH and 20.2 kg/d in FV. Average weekly EB was 2.8 MJ of NE_L/d in GH and 0.6 MJ of NE_L/d in FV. Most diseases occurred in the first 20 DIM. Multiparous cows were more susceptible to diseases than primiparous cows. Relative percentages of diseased cows were highest for claw and leg diseases, followed by metabolic diseases and mastitis. Repeatability of disease categories and production traits was moderate to high. Cow effect correlations for disease categories were higher for adjacent lactation stages than for more distant lactation stages. Pearson correlation coefficients between cow effects for DMI, as well as EB, and disease categories were estimated from DIM 2 to 305. Almost all correlations were negative in GH, especially in early lactation. In FV, the course of correlations was similar to GH, but correlations were mostly more negative in early lactation. For the first 20 DIM, correlations ranged from -0.31 to 0.00 in GH and from -0.42 to -0.01 in FV. The results illustrate that future breeding for dairy cow efficiency should focus on DMI and EB in early lactation to avoid health problems.

Genome-Wide Association Study and Pathway Analysis for Female Fertility Traits in Iranian Holstein Cattle

Female fertility is an important trait that contributes to cow’s profitability and it can be improved by genomic information. The objective of this study was to detect genomic regions and variants affecting fertility traits in Iranian Holstein cattle. A data set comprised of female fertility records and 3,452,730 pedigree information from Iranian Holstein cattle were used to predict the breeding values, which were then employed to estimate the de-regressed proofs (DRP) of genotyped animals. A total of 878 animals with DRP records and 54k SNP markers were utilized in the genome-wide association study (GWAS). The GWAS was performed using a linear regression model with SNP genotype as a linear covariate. The results showed that an SNP on BTA19, ARS-BFGL-NGS-33473, was the most significant SNP associated with days from calving to first service. In total, [69] significant SNPs were located within 27 candidate genes. Novel potential candidate genes include OSTN, DPP6, EphA5, CADPS2, Rfc1, ADGRB3, Myo3a, C10H14orf93, KIAA1217, RBPJL, SLC18A2, GARNL3, NCALD, ASPH, ASIC2, OR3A1, CHRNB4, CACNA2D2, DLGAP1, GRIN2A and ME3. These genes are involved in different pathways relevant to female fertility and other characteristics in mammals. Gene set enrichment analysis showed that thirteen GO terms had significant overrepresentation of genes statistically associated with female fertility traits. The results of network analysis identified CCNB1 gene as a hub gene in the progesterone-mediated oocyte maturation pathway, significantly associated with age at first calving. The candidate genes identified in this study can be utilized in genomic tests to improve reproductive performance in Holstein cattle.

Integrating RNA-Seq with GWAS reveals novel insights into the molecular mechanism underpinning ketosis in cattle

Background

Ketosis is a common metabolic disease during the transition period in dairy cattle, resulting in long-term economic loss to the dairy industry worldwide. While genetic selection of resistance to ketosis has been adopted by many countries, the genetic and biological basis underlying ketosis is poorly understood.

Results

We collected a total of 24 blood samples from 12 Holstein cows, including 4 healthy and 8 ketosis-diagnosed ones, before (2 weeks) and after (5 days) calving, respectively. We then generated RNA-Sequencing (RNA-Seq) data and seven blood biochemical indicators (bio-indicators) from leukocytes and plasma in each of these samples, respectively. By employing a weighted gene co-expression network analysis (WGCNA), we detected that 4 out of 16 gene-modules, which were significantly engaged in lipid metabolism and immune responses, were transcriptionally (FDR < 0.05) correlated with postpartum ketosis and several bio-indicators (e.g., high-density lipoprotein and low-density lipoprotein). By conducting genome-wide association signal (GWAS) enrichment analysis among six common health traits (ketosis, mastitis, displaced abomasum, metritis, hypocalcemia and livability), we found that 4 out of 16 modules were genetically (FDR < 0.05) associated with ketosis, among which three were correlated with postpartum ketosis based on WGCNA. We further identified five candidate genes for ketosis, including GRINA, MAF1, MAFA, C14H8orf82 and RECQL4. Our phenome-wide association analysis (Phe-WAS) demonstrated that human orthologues of these candidate genes were also significantly associated with many metabolic, endocrine, and immune traits in humans. For instance, MAFA, which is involved in insulin secretion, glucose response, and transcriptional regulation, showed a significantly higher association with metabolic and endocrine traits compared to other types of traits in humans.

Conclusions

In summary, our study provides novel insights into the molecular mechanism underlying ketosis in cattle, and highlights that an integrative analysis of omics data and cross-species mapping are promising for illustrating the genetic architecture underpinning complex traits.

Hyperketonemia GWAS and parity-dependent SNP associations in Holstein dairy cows intensively sampled for blood β-hydroxybutyrate concentration

Hyperketonemia (HYK) is a metabolic disorder that affects early postpartum dairy cows; however, there has been limited success in identifying genomic variants contributing to HYK susceptibility. We conducted a genome-wide association study (GWAS) using HYK phenotypes based on an intensive screening protocol, interrogated genotype interactions with parity group (GWIS), and evaluated the enrichment of annotated metabolic pathways. Holstein cows were enrolled into the experiment after parturition, and blood samples were collected at four timepoints between 5 and 18 days postpartum. Concentration of blood β-hydroxybutyrate (BHB) was quantified cow-side via a handheld BHB meter. Cows were labeled as a HYK case when at least one blood sample had BHB ≥ 1.2 mmol/L, and all other cows were considered non-HYK controls. After quality control procedures, 1,710 cows and 58,699 genotypes were available for further analysis. The GWAS and GWIS were performed using the forward feature select linear mixed model method. There was evidence for an association between ARS-BFGL-NGS-91238 and HYK susceptibility, as well as parity-dependent associations to HYK for BovineHD0600024247 and BovineHD1400023753. Candidate genes annotated to these single nuclear polymorphism associations have been previously associated with obesity, diabetes, insulin resistance, and fatty liver in humans and rodent models. Enrichment analysis revealed focal adhesion and axon guidance as metabolic pathways contributing to HYK etiology, while genetic variation in pathways related to insulin secretion and sensitivity may affect HYK susceptibility in a parity-dependent matter. In conclusion, the present work proposes several novel marker associations and metabolic pathways contributing to genetic risk for HYK susceptibility.

Somatic cell counts, reproduction indicators, and technical efficiency in milk production: A stochastic frontier analysis for Spanish dairy farms

Health and reproductive conditions affect milk yields in dairy cows and may lead to differences in technical efficiency across farms. To investigate this, we created a novel panel data set of 197 dairy farms in northern Spain observed over the period 2006-2014 by combining information from 2 different sources and including data on production variables, somatic cell count, and reproduction indicators, as well as a genetic index. We used these data to estimate a stochastic production frontier where the somatic cell count, age at first calving, and calving interval are included as determinants of technical efficiency. Higher somatic cell count, greater age at first calving, and longer calving intervals were found to decrease technical efficiency, translating into significant losses in profits which we quantify through a simulation exercise. We also quantified the effect of genetic selection on profits, taking into account not only its direct effect on productivity but also its indirect effect through reduced technical efficiency due to the effect of genetic selection on the health and reproduction variables.

Possibilities for a specific breeding program for organic dairy production

Organic dairy production differs from conventional dairy production in many aspects. However, breeding programs for the 2 production systems are the same in most countries. Breeding goals (BG) might be different for the 2 production systems and genotype × environment interaction may exist between organic and conventional dairy production, both of which have an effect on genetic gain in different breeding strategies. Other aspects also need to be considered, such as the application of multiple ovulation and embryo transfer (MOET), which is not allowed in organic dairy production. The general aim of this research was to assess different environment-specific breeding strategies for organic dairy production. The specific aim was to study differences in BG weights and include the effect of genotype × environment interaction, MOET, and the selection of breeding bulls from the conventional environment. Different scenarios were simulated. In the current scenario, the present-day situation for dairy production in Denmark was emulated as much as possible. The BG was based on a conventional dairy production system, MOET was applied in both environments, and conventional bulls could be selected as breeding bulls in the organic environment. Four alternative scenarios were simulated, all with a specific organic BG in the organic breeding program but differences in the usage of MOET and the selection of conventional bulls as breeding bulls. Implementation of a specific BG in organic dairy production slightly increased genetic gain in the aggregate genotype compared with the breeding program that is currently implemented in organic dairy production. Not using embryo transfer or only selecting breeding bulls from the organic environment decreased genetic gain in the aggregate genotype by as much as 24%. However, the use of embryo transfer is debatable because this is not allowed according to current regulations for organic dairy production. Assessing genetic gain on trait levels showed that a significant increase for functional traits was possible compared with the current breeding program in the organic environment without a decrease in genetic gain in the aggregate genotype. This difference on trait level was even more present when selection of conventional bulls as breeding bulls in the organic environment was not possible. This finding is very relevant when breeding for the desired cow in organic dairy production.

Symposium review: Big data, big predictions: Utilizing milk Fourier-transform infrared and genomics to improve hyperketonemia management

Negative animal health and performance outcomes are associated with disease incidences that can be labor-intensive, costly, and cumbersome for many farms. Amelioration of unfavorable outcomes through early detection and treatment of disease has emphasized the value of improving health monitoring. Although the value is recognized, detecting hyperketonemia (HYK) is still difficult for many farms to do practically and efficiently. Increasing data streams available to farms presents opportunities to use data to better monitor cow and herd health; however, challenges remain with regard to validating, integrating, and interpreting data. During the transition to lactation period, useful data are presented in the form of milk production and composition, milk Fourier-transform infrared (FTIR) wavelength absorbance, cow management records, and genomics, which have been employed to monitor postpartum onset of HYK. Attempts to predict postpartum HYK from test-day milk and performance variables incorporated into multiple linear regression models have demonstrated sufficient accuracy to monitor monthly herd prevalence; however, they lacked the sensitivity and specificity for individual cow diagnostics. Subsequent artificial neural network prediction models employing FTIR data and milk composition variables achieved 83 and 81% sensitivity and specificity for individual cow diagnostics. Although these results fail to reach the diagnostic goals of 90%, they are achieved without individual cow blood samples, which may justify acceptance of lower performance. The caveat is that these models depend on milk analysis, which is traditionally done every 4 weeks. This infrequent sampling allows for a single diagnostic sample for about half of the fresh cows. Benefits to farms are greatly improved if postpartum cows can be milk-tested weekly. Additionally, this allows for close monitoring of somatic cell count and may open the door for use of other herd health monitoring tools. Future improvements in these models may be achievable by maximizing sensitivity at the expense of specificity and may be most economical in disorders for which the cost of treatment is less than that of mistreating (e.g., HYK). Genomic predictions for HYK may be improved by incorporating genome-wide associated SNP and further utilized for precision management of HYK risk groups. Development and validation of HYK prediction models may provide producers with individual cow and herd-level management tools.

Genomic evaluation for wellness traits in US Jersey cattle

The number of Jersey cows in the United States has been steadily increasing in recent years according to Council on Dairy Cattle Breeding statistics. To help producers reduce the risk of health disorders in their Jersey animals, Zoetis has developed genomic predictions for wellness traits in Jersey cattle using producer-recorded data. The traits included mastitis (MAST), metritis, retained placenta, displaced abomasum (DA), ketosis, lameness, and milk fever in cows and respiratory disease, scours, and calf livability (DEAD) in calves. Phenotypic data on health events, pedigree, and genotypes were collected directly from producers upon obtaining their permission. Each trait was defined as a binary event, having a value of 1 if an animal has been recorded with a disorder and 0 otherwise. The number of phenotypic records ranged from 216,166 for DA to 628,958 for MAST for cow traits and from 186,505 for scours to 380,429 for DEAD for calf traits. The number of genotyped animals was 41,271. All traits were analyzed using a univariate threshold animal model. The model for cow wellness traits included the fixed effect of parity and random effects of herd × year × season of calving, animal, and permanent environment. The model for calf wellness traits included the fixed effect of year of birth × calving season × region and random effects of herd × year of birth and animal. A total of 45,163 SNP were used in genomic analyses. Animals genotyped with low-density chips were imputed to the required number of markers. All analyses were based on the single-step genomic BLUP. Heritabilities ranged from 0.061 for DA to 0.120 for lameness. Predicted transmitting abilities were expressed in percentage points as deviations from the average estimated probability of a disorder in the base population. Reliabilities of genomic predicted transmitting abilities had average values between 32% (DA) and 51% (MAST and DEAD). The results indicate that a direct evaluation of cow and calf wellness traits under a genomic threshold model is feasible and offers predictions with average reliabilities comparable with other lowly heritable traits for Jersey cattle.

Genetic correlations among selected traits in Canadian Holsteins

In the Canadian dairy industry, there are currently over 80 traits routinely evaluated, and more are considered for potential selection. Particularly, in the last few years, recording has commenced for several new phenotypes required to introduce novel traits with high economic importance into the selection program. However, without a systematic estimation of the genetic correlations that exist among traits, the potential results of indirect selection are unknown. Therefore, 29 traits representative of the trait diversity for first lactation Canadian animals were selected. Their two-by-two genetic correlations were estimated from a dataset of 62 498 first lactation Holstein cows, using a Markov Chain Monte Carlo Gibbs sampling approach. The general tendencies among the groups of traits confirm that production traits are negatively correlated with fertility traits and that functional traits are positively correlated with one another. The association of udder depth with fertility and disease resistance has also been highlighted. This contribution offers a comprehensive overview of current estimates across traits and includes correlations with novel traits that constitute an original addition to the literature. These new estimates can be used for newly developed genomic evaluation models and possibly lead to more accurate estimations of the dairy cows’ overall genetic merit.

Modelling for the inheritance of multiple births and fertility in endangered equids: Determining risk factors and genetic parameters in donkeys (Equus asinus)

Multiple births or twinning in equids are dangerous, undesirable situations that compromise the life of the dam and resulting offspring. However, embryo vitrification and freezing techniques take advantage of individuals whose multiple ovulations allow flushing more fertilised embryos from the oviduct to be collected, increasing the productivity and profitability of reproductive techniques. Embryo preservation is especially important in highly endangered populations such as certain donkey (Equus asinus) breeds; for which conventional reproductive techniques have previously been deemed inefficient. For instance, becoming an effective alternative to artificial insemination with frozen semen to preserve the individuals' genetic material. The objective of this study was to examine the historical foaling records of Andalusian donkeys to estimate prevalence, risk factors, phenotypic and genetic parameters for multiple births, assessing the cumulative foal number born per animal, maximum foal number per birth and multiple birth number per animal. We designed a Bayesian General Animal Mixed Model with single records considering the 'fixed' effects of birth year, birth season, birth month, sex, farm, location, and husbandry system. Age was considered and included as a linear and quadratic covariate. Gibbs sampling reported heritability estimates ranging from 0.18 ± 0.101 to 0.24 ± 0.078. Genetic and phenotypic correlations ranged from 0.496 ± 0.298 to 0.846 ± 0.152 and 0.206 ± 0.063 to 0.607 ± 0.054, respectively. Predicted breeding values obtained enable the potential selection against/for these traits, offering a new perspective for donkey breeding and conservation.

"Arte et Labore"-A Blackburn Rovers fan's legacy in human complex trait genetics

Through his own research contributions on the modelling and genetic analysis of quantitative traits and through his former students and postdocs, Robin Thompson has indirectly left a major legacy in human genetics. In this short note, we highlight examples of the long-lasting relevance and impact of Robin's work in human genetics. A lone early study of marker-assisted selection developed many of the tools and approaches later exploited (often after reinvention) by the human genetics community in GWAS studies and for prediction. Furthermore, a particularly clear example of the pervasive impact of Robin's work is that REML has become the default method to estimate variance components and that genetic predictions exploiting linkage disequilibrium in the population are starting to become used in precision medicine applications.

Genetics of heifer reproductive traits in Japanese Black cattle

Objective

The objective of this study was to identify environmental factors strongly associated with and to estimate genetic parameters of reproductive traits in Japanese Black heifers.

Methods

Data included reproduction records of Japanese Black heifers born between 2004 and 2014. First service non-return rate (NRR) to 56 days from first to successful insemination (FS), number of services per conception (IN), age at first calving (AFC) and gestation length were analyzed with the use of the general linear model. Genetic parameters were estimated with the use of the univariate animal model of the residual maximum likelihood.

Results

Averages of reproductive traits over eleven years were assessed, and the effects of farm, year, month, artificial insemination technician and interaction of farm×year on the traits were determined. Estimated heritability of FS was very low and that of AFC was higher than that of the other traits. A close genetic relation was observed among NRR, IN, and FS; however, their heritabilities were very low. AFC shows favorable genetic correlation with IN and FS.

Conclusion

Low heritabilities of most reproductive traits in Japanese Black heifers are strongly influenced by farm management practices, and that large residual variances make genetic evaluation difficult. Among the reproductive traits, AFC is potentially more useful for genetic improvement of heifer reproductive traits because it has high heritability and favorable genetic correlations with IN and FS.

Genetic aspects of some reproductive, udder health and energy status traits in Holstein cows

The objective of this study was to estimate heritability as well as genetic and environmental relationships between days to first heat (DFH), days to first service (DFS), interval from calving to conception (ICC), calving interval (CI) and number of inseminations per conception (NIS) with mastitis (Mast), number of mastitis occurrence (NumMast), different measures of somatic cell count (SCC) and fat to protein ratio (F:P) in the first lactation of Holstein cows in Iran using linear and threshold animal and sire models. The 33851 first lactation records of Holstein cows from five large dairy herds with calving dates from March 2002 to September 2014 were analyzed with univariate and bivariate linear and threshold animal and sire models using Gibbs sampling methodology. Data from parity one to nine comprising 62483 records were used to conduct repeatability model analysis for reproductive traits. Heritabilities of the reproduction traits varied from 0.067 (for ICC) to 0.105 (for DFH) using linear animal models. Also, the heritabilities of udder health traits varied from 0.005 to 0.102 using different models. The repeatabilities of reproductive traits ranged from 0.110 to 0.307. In general, the genetic correlations (r_g) between reproduction traits were positive and high (with the exception of r_g between DFH-NIS). The r_g between reproduction traits with udder health traits ranged from -0.029 to 0.359 and 0.151 to 0.584 using linear-linear and threshold-linear animal models, respectively. Generally, there was favorable r_g between reproduction traits with udder health traits; therefore, selection for one set of these traits would improve the correlated traits. However, due to different (co)variance components and economic weights in each country/region, it can be recommended to investigate inclusion of both sets of these traits in breeding objectives.

Genetic correlation estimates between milk production traits, mastitis and different measures of somatic cells in Holstein cows

The objective of this study was to estimate genetic parameters including repeatability, heritability as well as genetic and environmental relationships between 305-day milk yield, milk fat and protein yield (Fat and Pro), milk fat and protein percentages (Fat% and Pro%), mastitis (Mast), number of mastitis occurrence and different measurements of somatic cell counts using linear and threshold animal as well as linear and threshold sire models in Holstein cows of Iran. Records of 33851 first lactation Holstein cows from five large dairy herds with calving dates from March 2002 to September 2014 were analysed, using Gibbs sampling methodology. Heritabilities of production traits estimated by linear animal model ranged from 0.14 (Fat%) to 0.29 (Pro%). Generally, udder health traits had low heritability (ranged from 0.005 to 0.10). Estimates of heritability for Mast using linear models were higher than those obtained with threshold models. However, in general estimates of heritabilities using threshold models were higher than those from linear models. There were unfavourable genetic correlations between production traits and Mast, which implies that breeding programs with emphasis on 305-day milk yield will experience deterioration in udder health. Despite low heritability of udder health traits, genetic variability exists for these traits that allow selecting superior animals and increasing resistance to Mast and animal welfare. Considering relatively high ratio of permanent environmental variance for Mast, culling decisions can be made with higher accuracy in order to reduce Mast incidence phenotypically over time.

Additive genetic and heterosis effects for milk fever in a population of Jersey, Holstein × Jersey, and Holstein cattle under grazing conditions

The aim of this study was to estimate additive genetic and heterosis effects for milk fever (MF) in Costa Rican dairy cattle. A farm-based management information software was used to collect 223,783 parity records between years 1989 and 2016, from 64,008 cows, 2 breeds (Jersey, Holstein × Jersey crosses, and Holstein), and 134 herds. The pedigree file comprised 73,653 animals distributed across 10 generations. A total of 4,355 (1.95%) clinical cases of MF were reported within this population, affecting 3,469 (5.42%) cows. Data were analyzed using 2 animal models, both accounting for repeatability and assuming different distributions for MF event: normal (linear model) or binomial (threshold model). The models included parity as fixed effect, breed and heterosis as fixed regressions, and herd-year-season, additive genetic, and permanent environment as random effects. The models were fit using a generalized linear mixed model approach, as implemented in ASReml 4.0 software. We noted significant regression on the percentage of Holstein breed, depicting a -0.0086% [standard error (SE) = 0.0012] decrease in MF incidence for each 1-unit increase in percentage of Holstein breed. A favorable heterosis of 5.9% for MF was found, although this was not statistically significant. Heritability and repeatability were, respectively, 0.03 (SE = 0.002) and 0.05 (SE = 0.002) for the linear model, and 0.07 (SE = 0.007) and 0.07 (SE = 0.007) for the threshold model. The correlation between BLUP (all animals in pedigree) for linear and threshold models, was 0.89. The average accuracy of the estimated BLUP for all animals were 0.44 (standard deviation = 0.13) for the linear model and 0.29 (standard deviation = 0.14) for the threshold model. Heritability and repeatability for MF within this population was low, though significant.

Symposium review: Novel strategies to genetically improve mastitis resistance in dairy cattle

Mastitis is a disease of major economic importance to the dairy cattle sector because of the high incidence of clinical mastitis and prevalence of subclinical mastitis and, consequently, the costs associated with treatment, production losses, and reduced animal welfare. Disease-recording systems compiling data from a large number of farms are still not widely implemented around the world; thus, selection for mastitis resistance is often based on genetically correlated indicator traits such as somatic cell count (SCC), udder depth, and fore udder attachment. However, in the past years, several countries have initiated collection systems of clinical mastitis, based on producers recording data in most cases. The large data sets generated have enabled researchers to assess incidence of this disease and to investigate the genetic background of clinical mastitis itself, as well as its relationships with other traits of interest to the dairy industry. The genetic correlations between clinical mastitis and its previous proxies were estimated more accurately and confirmed the strong relationship of clinical mastitis with SCC and udder depth. New traits deriving from SCC were also studied, with the most relevant findings being associated with mean somatic cell score (SCS) in early lactation, standard deviation of SCS, and excessive test-day SCC pattern. Genetic correlations between clinical mastitis and other economically important traits indicated that selection for mastitis resistance would also improve resistance against other diseases and enhance both fertility and longevity. However, milk yield remains negatively correlated with clinical mastitis, emphasizing the importance of including health traits in the breeding objectives to achieve genetic progress for all important traits. These studies enabled the establishment of new genetic and genomic evaluation models, which are more efficient for selection to mastitis resistance. Further studies that are potential keys for future improvement of mastitis resistance are deep investigation of the bacteriology of mastitis, identification of novel indicator traits and tools for selection, and development of a larger female reference population to improve reliability of genomic evaluations. These cutting-edge studies will result in a better understanding of the genetic background of mastitis resistance and enable a more accurate phenotyping and genetic selection to improve mastitis resistance, and consequently, animal welfare and industry profitability.

Genetic analysis of docility score of Australian Angus and Limousin cattle

The temperament of cattle is believed to affect the profitability of the herd through impacting production costs, meat quality, reproduction, maternal behaviour and the welfare of the animals and their handlers. As part of the national beef cattle genetic evaluation in Australia by BREEDPLAN, 50 935 Angus and 50 930 Limousin calves were scored by seedstock producers for temperament using docility score. Docility score is a subjective score of the animal’s response to being restrained and isolated within a crush, at weaning, and is scored on a scale from 1 to 5 with 1 representing the quiet and 5 the extremely nervous or anxious calves. Genetic parameters for docility score were estimated using a threshold animal model with four thresholds (five categories) from a Bayesian analysis carried out using Gibbs sampling in THRGIBBS1F90 with post-Gibbs analysis in POSTGIBBSF90. The heritability of docility score on the observed scale was 0.21 and 0.39 in Angus and Limousin, respectively. Since the release of the docility breeding value to the Australian Limousin population there has been a favourable trend within the national herd towards more docile cattle. Weak but favourable genetic correlations between docility score and the production traits indicates that docility score is largely independent of these traits and that selection to improve temperament can occur without having an adverse effect on growth, fat, muscle and reproduction.

Estimation of genetic parameters of the productive and reproductive traits in Ethiopian Holstein using multi-trait models

Objective

This study estimated the genetic parameters for productive and reproductive traits.

Methods

The data included production and reproduction records of animals that have calved between 1979 and 2013. The genetic parameters were estimated using multivariate mixed models (DMU) package, fitting univariate and multivariate mixed models with average information restricted maximum likelihood algorithm.

Results

The estimates of heritability for milk production traits from the first three lactation records were 0.03±0.03 for lactation length (LL), 0.17±0.04 for lactation milk yield (LMY), and 0.15±0.04 for 305 days milk yield (305-d MY). For reproductive traits the heritability estimates were, 0.09±0.03 for days open (DO), 0.11±0.04 for calving interval (CI), and 0.47±0.06 for age at first calving (AFC). The repeatability estimates for production traits were 0.12±0.02, for LL, 0.39±0.02 for LMY, and 0.25±0.02 for 305-d MY. For reproductive traits the estimates of repeatability were 0.19±0.02 for DO, and to 0.23±0.02 for CI. The phenotypic correlations between production and reproduction traits ranged from 0.08±0.04 for LL and AFC to 0.42±0.02 for LL and DO. The genetic correlation among production traits were generally high (>0.7) and between reproductive traits the estimates ranged from 0.06±0.13 for AFC and DO to 0.99±0.01 between CI and DO. Genetic correlations of productive traits with reproductive traits were ranged from −0.02 to 0.99.

Conclusion

The high heritability estimates observed for AFC indicated that reasonable genetic improvement for this trait might be possible through selection. The h² and r estimates for reproductive traits were slightly different from single versus multi-trait analyses of reproductive traits with production traits. As single-trait method is biased due to selection on milk yield, a multi-trait evaluation of fertility with milk yield is recommended.