Genetic correlations among body condition score, yield, and fertility in first-parity cows estimated by random regression models

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.

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.

The effects of genotype-by-environment interactions on body condition score across three winter supplemental feed environments in a composite beef cattle breed in Montana

Cattle operations in the Northern Great Plains region of the United States face extreme cold weather conditions and require nutritional supplementation over the winter season in order for animals to maintain body condition. In cow-calf operations, body condition scores (BCS) measured at calving and breeding have been shown to be associated with several economically important health and fertility traits, so maintenance of BCS is both an animal welfare and economic concern. A low-to-medium heritability has been found for BCS when measured across various production stages, indicating a large environmental influence but sufficient genetic basis for selection. The present study evaluated BCS measured prior to calving (late winter) and breeding (early summer) under three winter supplementation environments in a multitrait linear mixed model. Traits were discretized by winter supplementation and genetic correlations between environments were considered a reflection of evidence for genotype-by-environment interactions between BCS and diet. Winter supplementation treatments were fed October through April and varied by range access and protein content: 1) feedlot environment with approximately 15% crude protein (CP) corn/silage diet, 2) native rangeland access with 1.8 kg of an 18% CP pellet supplement, and 3) native rangeland access with a self-fed 50% CP and mineral supplement. A total of 2,988 and 2,353 records were collected across multiple parities on 1,010 and 800 individuals for prebreeding and precalving BCS, respectively. Heifers and cows came from a composite beef cattle breed developed and maintained by the USDA Fort Keogh Livestock and Range Research Laboratory near Miles City, Montana. Genetic correlations between treatments 1 and 2, 1 and 3, and 2 and 3 were 0.98, 0.78, and 0.65 and 1.00, 0.98, and 0.99 for precalving and prebreeding BCS, respectively. This provides moderate evidence of genotype-by-environment interactions for precalving BCS under treatment 3 relative to treatments 1 and 2, but no evidence for genotype-by-environment interactions for prebreeding BCS. Treatment 3 differed substantially in CP content relative to treatments 1 and 2, indicating that some animals differ in their ability to maintain BCS up to spring calving across a protein gradient. These results indicate the potential for selection of animals with increased resilience under cold weather conditions and high protein, restricted energy diets to maintain BCS.

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.

Usefulness of mid-infrared spectroscopy as a tool to estimate body condition score change from milk samples in intensively fed dairy cows

Directly measuring individual cow energy balance is not trivial. Other traits such as body condition score (BCS) and BCS change (ΔBCS) can, however, be used as an indicator of cow energy status. Body condition score is a metric used worldwide to estimate cow body reserves, but the estimation of ΔBCS was, until now, conditional on the availability of multiple BCS assessments. The aim of the present study was to estimate ΔBCS from milk mid-infrared (MIR) spectra and days in milk (DIM) in intensively fed dairy cows using statistical prediction methods. Daily BCS was interpolated from cubic splines fitted through the BCS records and daily ΔBCS was calculated from these splines. The ΔBCS records were merged with milk MIR spectra recorded on the same week. The dataset comprised 37,077 ΔBCS phenotypes across 9,403 lactations from 6,988 cows in 151 herds based in Quebec, Canada. Partial least squares regression (PLSR) and a neural network (NN) were then used to estimate ΔBCS from (1) MIR spectra only, (2) DIM only, or (3) MIR spectra and DIM together. The ΔBCS data in both the first 120 and 305 DIM of lactation were used to develop the estimates. Daily ΔBCS had a standard deviation of 4.40 × 10-3 BCS units in the 120-d dataset and of 3.63 × 10-3 BCS units in the 305-d dataset. A 4-fold cross-validation was used to calibrate and test the prediction equations. External validation was also conducted using more recent years of data. Irrespective of whether based on the first 120 or 305 DIM, or when MIR spectra only, DIM only or MIR spectra and DIM were jointly used as prediction variables, NN produced the lowest root mean square error (RMSE) of cross-validation (1.81 × 10-3 BCS units and 1.51 × 10-3 BCS units, respectively, using the 120-d and 305-d dataset). Relative to predictions for the entire 305 DIM, the RMSE of cross-validation was 15.4% and 1.5% lower in the first 120 DIM when using PLSR and NN, respectively. Predictions from DIM only were more accurate than those using just MIR spectra data but, irrespective of the dataset and of the prediction model used, combining DIM information with MIR spectral data as prediction variables reduced the RMSE compared with the inclusion of DIM alone, albeit the benefit was small (the RMSE from cross-validation reduced by up to 5.5% when DIM and spectral data were jointly used as model features instead of DIM only). However, when predicting extreme ΔBCS records, the MIR spectral data were more informative than DIM. Model performance when predicting ΔBCS records in future years was similar to that from cross-validation demonstrating the ability of MIR spectra of milk and DIM combined to estimate ΔBCS, particularly in early lactation. This can be used to routinely generate estimates of ΔBCS to aid in day-to-day individual cow management.

Visually assessed body condition shows high heritability in a pedigreed great ape population

Body condition, a measure for relative fat mass, is associated with primate health, fitness, and overall welfare. Body condition is often influenced by dietary factors, age, and/or sex, but several body condition measures (body weight, weight-to-height ratios, and so on) also show high heritability across primate species, indicating a role of genetic effects. Although different measures for body condition exist, many require direct handling of animals, which is invasive, time-consuming, and expensive, making them impractical in wild and captive settings. Therefore, noninvasive visual body condition score (BCS) systems were developed for various animal species, including macaques and chimpanzees, to visually assess relative fat mass. Here we evaluate the utility of a visual BCS system in bonobos by assessing (1) inter-rater reliability, (2) links with body mass, a traditional hands-on measure of condition, and (3) the factors driving individual variation in BCS. We adapted the chimpanzee BCS system to rate 76 bonobos in 11 European zoos (92% of the adult population). Inter-rater reliability was high (s* = 0.948), BCSs were positively associated with body mass (β = 0.075) and not predicted by diet, sex, or age, nor were they associated with a higher abundance of obesity-related diseases. Instead, BCSs showed high levels of heritability (h2  = 0.637), indicating that a majority of body condition variation in bonobos is attributable to genetic similarity of the individuals. This is in line with reported h2 -values for traditional body condition measures in primates and provides support for the reliability of visual BCS systems in great apes. The results of this study emphasize an often unanticipated role of genetics in determining primate body fat and health that has implications for the management of captive primates. Application of this tool in wild populations would aid to unravel environmental from genetic drivers of body condition variation in primates.

Genetic relationships between weight loss in early lactation and daily milk production throughout the lactation in Holstein cows

After calving, high-yielding dairy cows mobilize body reserves for energy, sometimes to the detriment of health and fertility. This study aimed to estimate the genetic correlation between body weight loss until nadir and daily milk production (MY24) in first- (L1) and second-lactation (L2) Holstein cows. The data set included 859,020 MY24 records and 570,651 daily raw body weight (BWr) phenotypes from 3,989 L1 cows, and 665,361 MY24 records and 449,449 BWr phenotypes from 3,060 L2 cows, recorded on 36 French commercial farms equipped with milking robots that included an automatic weighing platform. To avoid any bias due to change in digestive content, BWr was adjusted for variations in feed intake, estimated from milk production and BWr. Adjusted body weight was denoted BW. The genetic parameters of BW and MY24 in L1 and L2 cows were estimated using a 4-trait random regression model. In this model, the random effects were fitted by second-order Legendre polynomials on a weekly basis from wk 1 to 44. Nadir of BW was found to be earlier than reported in the literature, at 29 d in milk, and BW loss from calving to nadir was also lower than generally assumed, close to 29 kg. To estimate genetic correlations between body weight loss and production, we defined BWL5 as the loss of weight between wk 1 and 5 after calving. Genetic correlations between BWL5 and MY24 ranged from -0.26 to 0.05 in L1 and from -0.11 to 0.10 in L2, according to days in milk. These moderate to low values suggest that it may be possible to select for milk production without increasing early body mobilization.

Genetic relationships of body condition score and locomotion with production, type and fertility traits in Holstein-Friesian cows

New traits are sought to add in breeding goals to prevent worsening health and fertility of Polish Holstein-Friesian cows. The objectives of this study were to estimate genetic parameters for body condition score (BCS) and locomotion (LOC) and their relationship with other type traits, milk and fertility traits, and to show genetic trends for BCS and LOC in Polish Holstein-Friesian population. Data on 317 028 Holstein-Friesian cows, born from 2010 through 2015 in 11 792 herds, were collected. All cows were scored for BCS and 43% of them for LOC. All records comprised lactational yields of milk, fat and protein, content of fat and protein and somatic cell count from the first three lactations, stature, five composite and 16 linear conformation traits, and four fertility traits. Genetic parameters were estimated using a Bayesian method with Gibbs Sampling, generating 100 000 samples in each of four steps: BCS and LOC with five composite conformation traits, BCS and LOC with 16 linear conformation traits, BCS and LOC with production traits, and BCS and LOC with four fertility traits. The linear model for BCS and LOC contained fixed effects of herd-year-season-classifier and lactation stage, fixed linear and quadratic regressions on age at calving, fixed linear regression on the percentage of Holstein-Friesian genes, and random additive genetic effect. Breeding values for BCS and LOC were calculated using the same model as used for estimation of genetic parameters. Genetic trends for BCS and LOC, defined as regression coefficients of mean breeding value on birth year, were examined. BCS was a moderately heritable trait (0.19) and was genetically correlated with non-return rate until 56 days after first insemination for cows (-0.32) and with days open (-0.22), so selection for BCS might have a favourable correlated effect on fertility. LOC, lowly heritable (0.06), was relatively strongly genetically correlated with feet-and-legs traits (from 0.48 to 0.93, ignoring sign) and could be included in a selection subindex for feet-and-legs. The positive trend for LOC indicated substantial progress towards the highest genetic value (optimum at the end of the scale), while the small trend for BCS showed a tendency to stabilise the average value in the middle of the scale (optimum for BCS). The estimates of the genetic parameters for BCS and LOC indicate that both traits could contribute to more effective selection to improve fertility (BCS) and legs health (LOC) in the Polish dairy cattle population.

The response to genetic merit for milk production in dairy cows differs by cow body weight

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Heavier cows yield more milk, fat, and protein.

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The association between genetic merit for milk yield and actual yield differs by BW.

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The association between genetic merit for milk composition and actual composition does not differ by BW.

Attention is increasing on both cow size and body weight (BW) as energy sinks and thus as contributors to differences in production efficiency among cows. What is not currently clear, however, is how cow BW affects the increase in yield per cow per unit increase in genetic merit for milk production. This void in knowledge was filled in the present study using BW data from 20,470 lactations on 16,980 Holstein-Friesian dairy cows stratified into 4 groups on BW adjusted for differences in parity, days in milk, and body condition score. Using linear mixed models that adjusted for nuisance factors, cow phenotypic milk production variables were regressed on estimates of parental average genetic merit for the respective trait within each stratum of BW defined within contemporary group; estimates of genetic merit were from the national genetic evaluations. Both the intercept and linear regression coefficients on genetic merit were compared across BW strata. The intercepts representing the mean phenotypic yield at a genetic merit of zero differed among BW strata; irrespective of yield trait, the least squares means yield per BW stratum increased numerically as cows got heavier, although not every stepwise increase in BW stratum was associated with significantly greater yield compared with the previous (lighter) stratum. Nonetheless, the yield of the cows in the lightest of the 4 strata was always less than that of the heaviest 2 strata; relative to the lightest stratum, cows in the heaviest BW stratum produced only 3 to 4% more yield. Furthermore, the association between phenotypic yield and its respective measures of genetic merit differed by BW stratum; the response to selection for each of the yield traits was 15 to 23% greater for the heaviest stratum of cows compared with their contemporaries in the lightest stratum. Although BW stratum was associated with mean fat and protein concentration after adjusting for differences in genetic merit for fat and protein concentration, the association did not differ by BW stratum for either fat or protein concentration. The effect of BW on efficiency should consider the association between BW and not only mean phenotypic yield at a given genetic merit, but also how the differences in yield diverge as genetic merit increases.

Contribution of genetic variability to phenotypic differences in on-farm efficiency metrics of dairy cows based on body weight and milk solids yield

Milk solids per kilogram of body weight (BW) is growing in popularity as a measure of dairy cow lactation efficiency. Little is known on the extent of genetic variability that exist in this trait but also the direction and strength of genetic correlations with other performance traits. Such genetic correlations are important to know if producers are to consider actively selecting cows excelling in milk solids per kilogram of BW. The objective of the present study was to use a large data set of commercial Irish dairy cows to quantify the extent of genetic variability in milk solids per kilogram of BW and related traits but also their genetic and phenotypic inter-relationships. Mid-lactation BW and body condition score (BCS), along with 305-d milk solids yield (i.e., fat plus protein yield) were available on 12,413 lactations from 11,062 cows in 85 different commercial dairy herds. (Co)variance components were estimated using repeatability animal linear mixed models. The genetic correlation between milk solids and body weight was only 0.05, which when coupled with the observed large genetic variability in both traits, indicate massive potential to select for both traits in opposite directions. The genetic correlations between both milk solids and BW with BCS; however, need to be considered in any breeding strategy. The genetic standard deviation, heritability, and repeatability of milk solids per kilogram of BW was 0.08, 0.37, and 0.57, respectively. The genetic correlation between milk solids per kilogram of BW with milk solids, BW, and BCS was 0.62, -0.75, and -0.41, respectively. Therefore, based on genetic regression, each increase of 0.10 units in genetic merit for milk solids per kilogram of BW is expected to result in, on average, an increase in 16.1 kg 305-d milk solids yield, a reduction of 25.6 kg of BW and a reduction of 0.05 BCS units (scale of 1-5 where 1 is emaciated). The genetic standard deviation (heritability) for 305-d milk solids yield adjusted phenotypically to a common BW was 27.3 kg (0.22). The genetic correlation between this adjusted milk solids trait with milk solids, BW, and BCS was 0.91, -0.12, and -0.26, respectively. Once also adjusted phenotypically to a common BCS, the genetic standard deviation (heritability) for milk solids adjusted phenotypically to a common BW was 26.8 kg (0.22) where the genetic correlation with milk solids, BW and BCS was 0.91, -0.21, and -0.07, respectively. The genetic standard deviation (heritability) of BW adjusted phenotypically for differences in milk solids was 35.3 kg (0.61), which reduced to 33.2 kg when also phenotypically adjusted for differences in BCS. Results suggest considerable opportunity exists to change milk solids yield independent of BW, and vice versa. The opportunity is reduced slightly once also corrected for differences in BCS. Inter-animal BCS differences should be considered if selection on such metrics is contemplated.

A Review of Beef Production Systems for the Sustainable Use of Surplus Male Dairy-Origin Calves Within the UK

The UK dairy herd is predominantly of the Holstein-Friesian (HF) breed, with a major emphasis placed on milk yield. Subsequently, following years of continued single-trait selection, the beef production potential of dairy bred calves has declined. Thus, male HF calves are commonly seen as a by-product of the dairy industry. Limited markets, perceived low economic value and high rearing costs mean that these surplus calves are often euthanised shortly after birth or exported to the EU for further production. Welfare concerns have been raised regarding both euthanasia and long distance transportation of these calves. Furthermore, total UK beef consumption increased by 8.5% from 2009 to 2019. Thus, in light of this growing demand, beef from the dairy herd could be better utilized within the UK. Therefore, the potential for these calves to be used in a sustainable, cost-effective beef production system with high welfare standards within the UK requires investigation. Thus, the aim of this review was to evaluate both steer and bull beef production systems, examining the impact on performance, health, welfare, and economic potential to enable a sustainable farming practice, while meeting UK market requirements. The principal conclusions from this review indicate that there is the potential for these calves to be used in UK based production systems and meet market requirements. Of the steer production systems, a 24 month system appears to achieve a balance between input costs, growth from pasture and carcass output, albeit the literature is undecided on the optimum system. The situation is similar for bull beef production systems, high input systems do achieve the greatest gain in the shortest period of time, however, these systems are not sustainable in volatile markets with fluctuating concentrate prices. Thus, again the inclusion of a grazing period, may increase the resilience of these systems. Furthermore, production systems incorporating a period at pasture are seen to have animal welfare benefits. The main welfare concern for surplus dairy bred calves is often poor colostrum management at birth. While in steer systems, consideration needs to be given to welfare regarding castration, with the negative impacts being minimized by completing this procedure soon after birth.

Relationships between energy balance during early lactation and cow performance, blood metabolites, and fertility: A meta-analysis of individual cow data

This study was designed to contribute to the understanding of the relationships between energy balance (EB) in early lactation [4 to 21 d in milk (DIM)] and fertility traits [interval to start of luteal activity (SLA), interval to first observed heat (FOH), and conception to first artificial insemination (AI)], and their associated relationships with cow performance and blood metabolites between 4 to 150 DIM. Individual cow data (488 primiparous and 1,020 multiparous lactations) from 27 experiments was analyzed. Data on cow performance, EB (on a metabolizable energy basis), and fertility traits were available for all cows, whereas milk progesterone data (to determine SLA) and periodic blood metabolite data were available for 1,042 and 1,055 lactations, respectively. Data from primiparous and multiparous cows were analyzed separately, with the data sets for the 2 parity groups divided into quartiles (Q1-Q4) according to the average EB during 4 to 21 DIM (EB range for Q1 to Q4: primiparous, -120 to -49, -49 to -24, -24 to -3, and -3 to 92 MJ/d, respectively: multiparous, -191 to -79, -79 to -48, -48 to -22, and -22 to 93 MJ/d, respectively). Differences between EB quartiles for production and fertility traits were compared. In early lactation (4 to 21 DIM), moving from Q1 to Q4 mean DMI and metabolizable energy intake increased whereas mean ECM decreased. During the same period, moving from Q1 to Q4 milk fat content, milk fat-to-protein ratio, and plasma nonesterified fatty acid and β-hydroxybutyrate concentrations decreased, whereas milk protein content and plasma glucose concentrations increased in both primiparous and multiparous cows. When examined over the entire experimental period (4 to 150 DIM), many of the trends in intakes and milk production remained, although the magnitude of the difference between quartiles was much reduced, whereas milk fat content did not differ between quartiles in primiparous cows. The percentage of cows with FOH before 42 DIM increased from Q1 to Q4 (from 46 to 72% in primiparous cows, and from 41 to 58% in multiparous cows). Interval from calving to SLA and to FOH decreased with increasing EB during 4 to 21 DIM, with these occurring 9.8 and 10.2 d earlier, respectively, in Q4 compared with Q1 (primiparous cows), and 7.4 and 5.9 d earlier, respectively, in Q4 compared with Q1 (multiparous cows). For each 10 MJ/d decrease in mean EB during 4 to 21 DIM, FOH was delayed by 1.2 and 0.8 d in primiparous and multiparous cows, respectively. However, neither days to first AI nor the percentage of cows that conceived to first AI were affected by daily EB during 4 to 21 DIM in either primiparous or multiparous cows, and this is likely to reflect a return to a less metabolically stressed status at the time of AI. These results demonstrate that interval from calving to SLA and to FOH were reduced with increasing EB in early lactation, whereas early lactation EB had no effect on conception to the first service.

Genome-wide association study for age at puberty and resumption of cyclicity in a crossbred dairy cattle population

Fertility is of primary economic importance in dairy cattle and the most common reason for involuntary culling. However, standard fertility traits have very low heritability that renders genetic selection slow and difficult. In this study, we explored fertility from an endocrine standpoint. A total of 1,163 crossbred Holstein-Normande females in a 3-generation familial design were studied for progesterone level measured every 10 d to determine age at puberty (PUB) and commencement of postpartum luteal activity (CPLA). Genetic parameters were estimated using REML with WOMBAT software. The heritability estimates were 0.38 ± 0.10 and 0.16 ± 0.07 for PUB and CPLA, respectively. Moreover, the 2 traits were genetically correlated (0.45 ± 0.23), suggesting a partially common determinism. Because of the family structure, a linkage disequilibrium and linkage analysis approach was preferred over standard genome-wide association study to map genomic regions associated with these traits. Ten quantitative trait loci (QTL) were detected for PUB on chromosomes 1, 3, 11, 13, 14, 21, and 29, whereas 3 QTL were associated with CPLA on chromosomes 21 and 26. Only the QTL on chromosome 21 was common to both traits. Four functional candidate genes (NCOA2, GAS2, OVOL1, and FOSL1) were identified in the detected regions. These findings will contribute to a clearer understanding of fertility determinism and enhance the value of introducing endocrinological data in fertility studies.

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.

Fourier transform infrared spectroscopy of milk samples as a tool to estimate energy balance, energy- and dry matter intake in lactating dairy cows

The objective of the study was to evaluate the potential of Fourier transform infrared spectroscopy (FTIR) analysis of milk samples to predict body energy status and related traits (energy balance (EB), dry matter intake (DMI) and efficient energy intake (EEI)) in lactating dairy cows. The data included 2371 milk samples from 63 Norwegian Red dairy cows collected during the first 105 days in milk (DIM). To predict the body energy status traits, calibration models were developed using Partial Least Squares Regression (PLSR). Calibration models were established using split-sample (leave-one cow-out) cross-validation approach and validated using an external test set. The PLSR method was implemented using just the FTIR spectra or using the FTIR together with milk yield (MY) or concentrate intake (CONCTR) as predictors of traits. Analyses were conducted for the entire first 105 DIM and separately for the two lactation periods: 5 ≤ DIM ≤ 55 and 55 < DIM ≤ 105. To test the models, an external validation using an independent test set was performed. Predictions depending on the parity (1st, 2nd and 3rd-to 6th parities) in early lactation were also investigated. Accuracy of prediction (r) for both cross-validation and external test set was defined as the correlation between the predicted and observed values for body energy status traits. Analyzing FTIR in combination with MY by PLSR, resulted in relatively high r-values to estimate EB (r = 0.63), DMI (r = 0.83), EEI (r = 0.84) using an external validation. Only moderate correlations between FTIR spectra and traits like EB, EEI and dry matter intake (DMI) have so far been published. Our hypothesis was that improvements in the FTIR predictions of EB, EEI and DMI can be obtained by (1) stratification into different stages of lactations and different parities, or (2) by adding additional information on milking and feeding traits. Stratification of the lactation stages improved predictions compared with the analyses including all data 5 ≤ DIM ≤105. The accuracy was improved if additional data (MY or CONCTR) were included in the prediction model. Furthermore, stratification into parity groups, improved the predictions of body energy status. Our results show that FTIR spectral data combined with MY or CONCTR can be used to obtain improved estimation of body energy status compared to only using the FTIR spectra in Norwegian Red dairy cattle. The best prediction results were achieved using FTIR spectra together with MY for early lactation. The results obtained in the study suggest that the modeling approach used in this paper can be considered as a viable method for predicting an individual cow's energy status.

Comprehensive analyses of 723 transcriptomes enhance genetic and biological interpretations for complex traits in cattle

By uniformly analyzing 723 RNA-seq data from 91 tissues and cell types, we built a comprehensive gene atlas and studied tissue specificity of genes in cattle. We demonstrated that tissue-specific genes significantly reflected the tissue-relevant biology, showing distinct promoter methylation and evolution patterns (e.g., brain-specific genes evolve slowest, whereas testis-specific genes evolve fastest). Through integrative analyses of those tissue-specific genes with large-scale genome-wide association studies, we detected relevant tissues/cell types and candidate genes for 45 economically important traits in cattle, including blood/immune system (e.g., CCDC88C) for male fertility, brain (e.g., TRIM46 and RAB6A) for milk production, and multiple growth-related tissues (e.g., FGF6 and CCND2) for body conformation. We validated these findings by using epigenomic data across major somatic tissues and sperm. Collectively, our findings provided novel insights into the genetic and biological mechanisms underlying complex traits in cattle, and our transcriptome atlas can serve as a primary source for biological interpretation, functional validation, studies of adaptive evolution, and genomic improvement in livestock.

Reproductive efficiency and survival of Holstein-Friesian cows of divergent Economic Breeding Index, evaluated under seasonal calving pasture-based management

The objective of the current study was to examine phenotypic fertility performance and survival, and to gain insight into underlying factors that may contribute to greater fertility performance in 2 divergent genetic groups (GG) of Holstein-Friesian, selected using the Irish Economic Breeding Index (EBI). The GG were evaluated across 3 spring calving pasture-based feeding treatments (FT) over 4 yr. The 2 divergent GG were (1) high EBI; representative of the top 5% nationally (elite), and (2) EBI representative of the national average (NA). In each year, 90 elite and 45 NA cows were randomly allocated to 1 of 3 FT: control, lower grass allowance, and high concentrate. No interaction between GG and FT was observed for any of the measures of fertility investigated. The elite cows achieved significantly greater pregnancy rate to first service (+14.9 percentage points), and significantly greater pregnancy rates after 21, 42, and 84 d of breeding (+17.3, +15.2, and +9.6 percentage points, respectively) compared with NA. The number of services per cow was fewer for elite (1.57) compared with NA (1.80). The interval from mating start date to pregnancy was significantly shorter for elite cows compared with NA. The elite cows maintained greater mean body condition score than NA throughout the study (2.91 vs. 2.72), and had greater body condition score at calving, artificial insemination, and drying off compared with NA. The elite cows had greater mean circulating concentrations of insulin-like growth factor-1 compared with NA. No significant effect was observed of GG on commencement of luteal activity, or progesterone profile variables. Greater survival to the start of fifth lactation was observed for elite cows. The elite cows were 43% less likely to be culled than NA by the beginning of the fifth lactation. The results highlight the success of the Economic Breeding Index to deliver reproductive performance and longevity consistent with industry targets across a range of seasonal pasture-based FT. The results also clearly demonstrate the potential of appropriate genetic selection to reverse negative fertility trends incurred during previous decades of selection for milk production alone.

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.

Identification of loci associated with conception rate in primiparous Holstein cows

BACKGROUND

Subfertility is a major issue facing the dairy industry as the average US Holstein cow conception rate (CCR) is approximately 35%. The genetics underlying the physiological processes responsible for CCR, the proportion of cows able to conceive and maintain a pregnancy at each breeding, are not well characterized. The objectives of this study were to identify loci, positional candidate genes, and transcription factor binding sites (TFBS) associated with CCR and determine if there was a genetic correlation between CCR and milk production in primiparous Holstein cows. Cows were bred via artificial insemination (AI) at either observed estrus or timed AI and pregnancy status was determined at day 35 post-insemination. Additive, dominant, and recessive efficient mixed model association expedited (EMMAX) models were used in two genome-wide association analyses (GWAA). One GWAA focused on CCR at first service (CCR1) comparing cows that conceived and maintained pregnancy to day 35 after the first AI (n = 494) to those that were open after the first AI (n = 538). The second GWAA investigated loci associated with the number of times bred (TBRD) required for conception in cows that either conceived after the first AI (n = 494) or repeated services (n = 472).

RESULTS

The CCR1 GWAA identified 123, 198, and 76 loci associated (P < 5 × 10- 08) in additive, dominant, and recessive models, respectively. The TBRD GWAA identified 66, 95, and 33 loci associated (P < 5 × 10- 08) in additive, dominant, and recessive models, respectively. Four of the top five loci were shared in CCR1 and TBRD for each GWAA model. Many of the associated loci harbored positional candidate genes and TFBS with putative functional relevance to fertility. Thirty-six of the loci were validated in previous GWAA studies across multiple breeds. None of the CCR1 or TBRD associated loci were associated with milk production, nor was their significance with phenotypic and genetic correlations to 305-day milk production.

CONCLUSIONS

The identification and validation of loci, positional candidate genes, and TFBS associated with CCR1 and TBRD can be utilized to improve, and further characterize the processes involved in cattle fertility.

Symposium review: The choice and collection of new relevant phenotypes for fertility selection

In dairy production, high fertility contributes to herd profitability by achieving greater production and maintaining short calving intervals. Improved management practices and genetic selection have contributed to reversing negative trends in dairy cow fertility, but further progress is still required. Phenotypes included in current genetic evaluations are largely interval and binary traits calculated from insemination and calving date records. Several indicator traits such as calving, health, variation in body condition score, and longevity traits also apply to genetic improvement of fertility. Several fertility traits are included in the selection indices of many countries, but for improved selection, the development of novel phenotypes that more closely describe the physiology of reproduction and limit management bias could be more effective. Progesterone-based phenotypes can be determined from milk samples to describe the heritable interval from calving to corpus luteum activity, as well as additional measures of cow cyclicity. A fundamental component of artificial insemination practices is the observation of estrus. Novel phenotypes collected on estrous activity could be used to select for cows clearly displaying heat, as those cows are more likely to be inseminated at the right time and therefore have greater fertility performance. On-farm technologies, including in-line milk testing and activity monitors, may allow for phenotyping novel traits on large numbers of animals. Additionally, selection for improved fertility using traditional traits could benefit from refined and accurate recording and implementation of parameters such as pregnancy confirmation and reproductive management strategy, to differentiate embryonic or fetal loss, and to ensure selection for reproductive capability without producer intervention. Opportunities exist to achieve genetic improvement of reproductive efficiency in cattle using novel phenotypes, which is required for long-term sustainability of the dairy cattle population and industry.

Gene co-expression networks from RNA sequencing of dairy cattle identifies genes and pathways affecting feed efficiency

Background

Selection for feed efficiency is crucial for overall profitability and sustainability in dairy cattle production. Key regulator genes and genetic markers derived from co-expression networks underlying feed efficiency could be included in the genomic selection of the best cows. The present study identified co-expression networks associated with high and low feed efficiency and their regulator genes in Danish Holstein and Jersey cows.

RNA-sequencing data from Holstein and Jersey cows with high and low residual feed intake (RFI) and treated with two diets (low and high concentrate) were used. Approximately 26 million and 25 million pair reads were mapped to bovine reference genome for Jersey and Holstein breed, respectively. Subsequently, the gene count expressions data were analysed using a Weighted Gene Co-expression Network Analysis (WGCNA) approach. Functional enrichment analysis from Ingenuity® Pathway Analysis (IPA®), ClueGO application and STRING of these modules was performed to identify relevant biological pathways and regulatory genes.

Results

WGCNA identified two groups of co-expressed genes (modules) significantly associated with RFI and one module significantly associated with diet. In Holstein cows, the salmon module with module trait relationship (MTR) = 0.7 and the top upstream regulators ATP7B were involved in cholesterol biosynthesis, steroid biosynthesis, lipid biosynthesis and fatty acid metabolism. The magenta module has been significantly associated (MTR = 0.51) with the treatment diet involved in the triglyceride homeostasis. In Jersey cows, the lightsteelblue1 (MTR = − 0.57) module controlled by IFNG and IL10RA was involved in the positive regulation of interferon-gamma production, lymphocyte differentiation, natural killer cell-mediated cytotoxicity and primary immunodeficiency.

Conclusion

The present study provides new information on the biological functions in liver that are potentially involved in controlling feed efficiency. The hub genes and upstream regulators (ATP7b, IFNG and IL10RA) involved in these functions are potential candidate genes for the development of new biomarkers. However, the hub genes, upstream regulators and pathways involved in the co-expressed networks were different in both breeds. Hence, additional studies are required to investigate and confirm these findings prior to their use as candidate genes.

Electronic supplementary material

The online version of this article (10.1186/s12859-018-2553-z) contains supplementary material, which is available to authorized users.

A 100-Year Review: Identification and genetic selection of economically important traits in dairy cattle

Over the past 100 yr, the range of traits considered for genetic selection in dairy cattle populations has progressed to meet the demands of both industry and society. At the turn of the 20th century, dairy farmers were interested in increasing milk production; however, a systematic strategy for selection was not available. Organized milk performance recording took shape, followed quickly by conformation scoring. Methodological advances in both genetic theory and statistics around the middle of the century, together with technological innovations in computing, paved the way for powerful multitrait analyses. As more sophisticated analytical techniques for traits were developed and incorporated into selection programs, production began to increase rapidly, and the wheels of genetic progress began to turn. By the end of the century, the focus of selection had moved away from being purely production oriented toward a more balanced breeding goal. This shift occurred partly due to increasing health and fertility issues and partly due to societal pressure and welfare concerns. Traits encompassing longevity, fertility, calving, health, and workability have now been integrated into selection indices. Current research focuses on fitness, health, welfare, milk quality, and environmental sustainability, underlying the concentrated emphasis on a more comprehensive breeding goal. In the future, on-farm sensors, data loggers, precision measurement techniques, and other technological aids will provide even more data for use in selection, and the difficulty will lie not in measuring phenotypes but rather in choosing which traits to select for.

Genetic parameters for body weight from birth to calving and associations between weights with test-day, health, and female fertility traits

A data set including 57,868 records for calf birth weight (CABW) and 9,462 records for weight at first insemination (IBW) were used for the estimation of direct and maternal genetic effects in Holstein Friesian dairy cattle. Furthermore, CABW and IBW were correlated with test-day production records and health traits in first-lactation cows, and with nonreturn rates in heifers. Health traits considered overall disease categories from the International Committee for Animal Recording diagnosis key, including the general disease status, diarrhea, respiratory diseases, mastitis, claw disorders, female fertility disorders, and metabolic disorders. For single-trait measurements of CABW and IBW, animal models with maternal genetic effects were applied. The direct heritability was 0.47 for CABW and 0.20 for IBW, and the direct genetic correlation between CABW and IBW was 0.31. A moderate maternal heritability (0.19) was identified for CABW, but the maternal genetic effect was close to zero for IBW. The correlation between direct and maternal genetic effects was antagonistic for CABW (-0.39) and for IBW (-0.24). In bivariate animal models, only weak genetic and phenotypic correlations were identified between CABW and IBW with either test-day production or health traits in early lactation. Apart from metabolic disorders, there was a general tendency for increasing disease susceptibilities with increasing CABW. The genetic correlation between IBW and nonreturn rates in heifers after 56 d and after 90 d was slightly positive (0.18), but close to zero when correlating nonreturn rates with CABW. For the longitudinal BW structure from birth to the age of 24 mo, random regression models with the time-dependent covariate "age in months" were applied. Evaluation criteria (Bayesian information criterion and residual variances) suggested Legendre polynomials of order 3 to modeling the longitudinal body weight (BW) structure. Direct heritabilities around birth and insemination dates were slightly larger than estimates for CABW and IBW from the single-trait models, but maternal heritabilities were exactly the same from both models. Genetic correlations between BW were close to 1 for neighboring age classes, but decreased with increasing time spans. The genetic correlation between BW at d 0 (birth date) and at 24 mo was even negative (-0.20). Random regression model estimates confirmed the antagonistic relationship between direct and maternal genetic effects, especially during calfhood. This study based on a large data set in dairy cattle confirmed genetic parameters and (co)variance components for BW as identified in beef cattle populations. However, BW records from an early stage of life were inappropriate early predictors for dairy cow health and productivity.

Effect of selection for residual feed intake during the grow/finish phase of production on sow reproductive performance and lactation efficiency

As feed costs continue to rise and efficiency during finishing is emphasized, the impact of selecting for more efficient grow/finish pigs on reproductive performance and feed efficiency of sows must be evaluated. Therefore, the objectives of this study were to evaluate correlated responses for sow reproductive performance and lactation feed efficiency to selection for residual feed intake (RFI) during the grow/finish phase of production (RFI) in 2 selection lines of pigs developed at Iowa State University (Ames, IA) and to estimate heritabilities of these traits. One line was selected over 7 generations for decreased RFIG/F (low RFI [LRFI] line) and the other line was randomly selected for 5 generations and then selected for increased RFIG/F (high RFI [HRFI] line). After 7 generations of selection, LRFI sows had 1.0 more piglets farrowed ( = 0.11) compared with HRFI sows, 1.3 more pigs born alive ( < 0.05), similar farrowing survival, 0.4 fewer mummies ( < 0.01), and more piglets weaned, both by litter (1.6 more; < 0.01) and by sow (1.1 more; < 0.01). Low RFI sows consumed 25 kg less feed and lost 9.8 kg more BW, 7.0 kg more fat mass, and 3.1 mm more backfat than HRFI sows ( < 0.001) during lactation. Although LRFI sows had a greater negative energy balance (-19.8 vs. -8.0 MJ ME/d; < 0.001), they had better RFI during lactation (-28.6 vs. 8.2 kg; < 0.0001), and the trend was for LRFI sows to have better lactation efficiency (61.3 vs. 57.8%; = 0.47) than HRFI sows. Heritabilities for sow weights, sow body composition, sow maintenance requirements (estimated from BW), and piglet birth weight were high ( > 0.4, SE < 0.07). Traits pertaining to piglet growth during lactation and mobilization of body tissue of the sow were moderately heritable (0.2 < < 0.4, SE < 0.07). In conclusion, selection for decreased RFI has favorably affected piglet performance and lactation efficiency but has unfavorably affected sow body condition loss and energy balance during lactation. These results indicate that pigs selected for increased efficiency during grow-finish are better able to direct resources where needed during other life history phases, that is, reproduction and lactation.

Effect of energy balance profiles on metabolic and reproductive response in Holstein and Swedish Red cows

This study examined the effect of two feeding levels during the antepartum and postpartum period on reproductive performance and blood metabolites (glucose, non-esterified fatty acids (NEFA), insulin) in primiparous Holstein and Swedish Red (SRB) cows, in order to identify possible differences in the way these breeds respond to negative energy balance after calving. A total of 44 cows (22 Holstein, 22 SRB) kept in a loose housing system were included in the study. The control group (HE, n = 23) was fed a diet for high-producing cows (target 35 kg/d energycorrected milk, ECM). A lower feeding intensity (LE, n = 21) was achieved by giving -50% concentrate to target 25 kg/d ECM. Diets were implemented 30 days before expected calving and the cows were monitored for 120 days postpartum. Milk yield and composition, dry matter intake (DMI), live body weight and body condition score (BCS) were assessed to calculate the weekly energy balance (residual feed intake). Blood sampling started before diet implementation and was repeated every 2 weeks until Day 60 postpartum and then once monthly until Day 120. Plasma was kept at -20 °C until analysis for glucose, insulin and NEFA concentrations. Mixed linear models were used to analyse data (SAS 9.3; PROC MIXED). Holstein cows had lower mean energy balance than SRB cows (-4.7 ± 1.4 and -0.9 ± 1.4 MJ, respectively; p = 0.05). SRB cows had higher (p<0.001) BCS (3.3 ± 0.1) than Holstein cows (2.7 ± 0.1) and also higher plasma glucose concentrations from Day -30 to Day 120 relative to parturition (4.1 ± 0.1 and 4.2 ± 0.1 log ; mg/100 ml, respectively; p < 0.05). Overall, breed or diet had no effect on NEFA blood plasma concentrations. However, plasma NEFA concentration levels tended to be higher (p = 0.09) in SRB cows than in Holsteins at Day -14 before calving, indicating higher mobilisation of lipid from adipose tissue already before calving. In contrast, Holstein cows had higher NEFA at Day 14 postpartum than SRB cows (p < 0.05). There were no significant effects of diet or breed on reproductive performance (% pregnant at first AI, days open). However, commencement of luteal activity within 21d postpartum was affected (p < 0.05) by the interaction of breed and diet. These results suggest that Holstein cows prioritise milk production to a larger extent than SRB cows, resulting in a less balanced metabolic profile.

Genetic and phenotypic associations of type traits and body condition score with dry matter intake, milk yield, and number of breedings in first lactation Canadian Holstein cows

The objective of the present study was to estimate genetic parameters of milk yield (MY), intake traits, type traits, body condition score (BCS), and number of breedings (NOB) in first lactation Canadian Holsteins with a focus on the possibility of using type traits as an indicator of feed intake. Data were obtained from the Canadian Dairy Network and Valacta. A mixed linear model was fitted under REML for the statistical analysis. The multivariate (five traits) model included the fixed effects of age at calving, stage of lactation, and herd-round-classifier for type traits; age at calving, stage of lactation, and herd–year–season of calving (HYS) for BCS; age at calving and HYS for MY, feed intake, and NOB. Animal and residual effects were fitted as random effects for all traits. Estimates of heritabilities for MY, dry matter intake (DMI), angularity, body depth, stature, dairy strength, final score, BCS, and NOB were 0.41, 0.13, 0.24, 0.30, 0.50, 0.30, 0.22, 0.20, and 0.02, respectively. Genetic correlations between type traits and DMI ranged from 0.16 to 0.60. Results indicate that type traits appear to have the potential to predict DMI as a combination/index of two or more traits.

Variance component estimates for alternative litter size traits in swine

Litter size at d 5 (LS5) has been shown to be an effective trait to increase total number born (TNB) while simultaneously decreasing preweaning mortality. The objective of this study was to determine the optimal litter size day for selection (i.e., other than d 5). Traits included TNB, number born alive (NBA), litter size at d 2, 5, 10, 30 (LS2, LS5, LS10, LS30, respectively), litter size at weaning (LSW), number weaned (NW), piglet mortality at d 30 (MortD30), and average piglet birth weight (BirthWt). Litter size traits were assigned to biological litters and treated as a trait of the sow. In contrast, NW was the number of piglets weaned by the nurse dam. Bivariate animal models included farm, year-season, and parity as fixed effects. Number born alive was fit as a covariate for BirthWt. Random effects included additive genetics and the permanent environment of the sow. Variance components were plotted for TNB, NBA, and LS2 to LS30 using univariate animal models to determine how variances changed over time. Additive genetic variance was minimized at d 7 in Large White and at d 14 in Landrace pigs. Total phenotypic variance for litter size traits decreased over the first 10 d and then stabilized. Heritability estimates increased between TNB and LS30. Genetic correlations between TNB, NBA, and LS2 to LS29 with LS30 plateaued within the first 10 d. A genetic correlation with LS30 of 0.95 was reached at d 4 for Large White and at d 8 for Landrace pigs. Heritability estimates ranged from 0.07 to 0.13 for litter size traits and MortD30. Birth weight had an h of 0.24 and 0.26 for Large White and Landrace pigs, respectively. Genetic correlations among LS30, LSW, and NW ranged from 0.97 to 1.00. In the Large White breed, genetic correlations between MortD30 with TNB and LS30 were 0.23 and -0.64, respectively. These correlations were 0.10 and -0.61 in the Landrace breed. A high genetic correlation of 0.98 and 0.97 was observed between LS10 and NW for Large White and Landrace breeds, respectively. This would indicate that NW could possibly be used as an effective maternal trait, given a low level of cross-fostering, to avoid back calculating litter size traits from piglet records. Litter size at d 10 would be a compromise between gain in litter size at weaning and minimizing the potentially negative effects of the nurse dam and direct additive genetics of the piglets, as they are expected to increase throughout lactation.

The effect of strain of Holstein-Friesian cow and feeding system on reproductive performance in seasonal-calving milk production systems

Three strains of Holstein-Friesian (HF) cows: high production North American (HP), high durability North American (HD) and New Zealand (NZ) were assigned, within strain, to one of three pasture-based feeding systems: Moorepark (MP), high concentrate (HC), and high stocking rate (HS). The effects of strain of HF, feeding system and parity on milk production, body condition score (BCS), live weight, energy balance and reproductive performance were studied using a repeated measures model with a factorial arrangement of strain ofHF and feeding systems. Associations between these variables and conception to first service (CONCEPT1), conception to first and second service (CONCEPTl_2), pregnancy rate at 6 weeks (PREG6) and overall pregnancy rate (PREG) were assessed using logistic regressions. When treatment means were compared, the NZ strain had a shorter gestation length and a higher CONCEPT1J2 than both the HP and HD strains. Similarly, the NZ strain had a higher PREG6 and PREG than the HP strain. Feeding system had no significant effect on reproductive performance. The HP strain had the highest milk yield at first AI and peak milk yield, the NZ strain had the lowest milk yield while the HD strain was intermediate. The energy balance of the NZ strain was higher than that of the HP and HD strains. The NZ strain had the lowest live weight and highest BCS; the HD strain had the highest live weight and the HP strain had the lowest BCS. The results show that dairy cows with superior genetic merit for fertility traits have better reproductive performance.

Genetic parameters for growth, reproductive performance, calving ease and suckling performance in beef cattle heifers

There is considerable concern about the consequences on fitness-related traits of using narrow breeding objectives for production traits. The aim of this study was to assess the potential consequences of selection for growth in French beef cattle breeds by estimating genetic correlations between growth, reproduction, calving and suckling traits of Charolais, Limousin and Blonde d’Aquitaine heifers. Data consisted of the records collected from 1985 to 2002 in progeny test stations that were used in the genetic evaluation of 284 Charolais, 125 Limousin and 118 Blonde d’Aquitaine AI sires. Seven traits were considered simultaneously in the analysis: weights at 18 months and after calving (for measuring heifer growth), sexual precocity and fertility (for measuring heifer reproductive performance), calving difficulty score and pelvic opening (for measuring calving ease) and milk yield (for measuring the suckling ability of the primiparous cow). REML (co)variance estimates were derived using linear multitrait sire models. Estimates of heritability were in the range of values given in the literature. They were very similar in the Charolais and Blonde d’Aquitaine breeds, and rather different for reproductive and suckling performance in the Limousin breed. Estimates were about 0·35 for heifer growth traits and about 0·15 for calving difficulty score in the three breeds. In the Charolais and Blonde d’Aquitaine breeds, estimates of heritability were 0·15 for sexual precocity and 0·05 for heifer fertility. These estimates were close to zero in the Limousin breed. Heritabilities of pelvic opening and milk yield were, respectively, 0·2 and 0·6 in the Limousin breed and around 0·3 in the other two breeds. Genetic correlations between traits concerning the same ability (as, for instance, weight at 18 months and weight at calving) were high and, in general, similar among breeds. Genetic correlations between heifer growth, reproductive traits, calving ease and suckling performance were nil or slightly favourable in the three breeds. Consequently, past selection mainly directed towards increasing growth seems not to have adversely affected the efficiency of female reproduction and the maternal abilities of French specialized beef cattle breeds.

Genetic correlations among body condition score, somatic cell score, milk production, fertility and conformation traits in dairy cows

Genetic and phenotypic parameters for body condition score (BCS), days to first service (DFS), non-return rate (NRR), somatic cell score (SCS), and 305-day milk, fat and protein yields were estimated, using 38930 multiple lactation records of cows across 1830 herds. The cows were daughters of '243 different sires. Single- and multi-trait repeatability animal models were used to estimate parameters based on restricted maximum likelihood methodology. Fixed effects in the model varied depending on the individual trait. Further, genetic relationships between 27 (linear and descriptive) type traits and functional traits (fertility and SCS) were estimated by regressing daughter type records on their sire's estimated breeding values for functional traits, using the same data set. Estimated regression coefficients were then subsequently used to derive approximate genetic correlations between type and functional traits (DFS, NRR and SCS). Body condition score had a moderate heritability (h2) of 0-26 and fertility traits had a low h2 (0-12 for DFS and 0-06 for NRR). Heritability of SCS and milk production traits was 0-14 and around 0-30, respectively. Ratio of permanent environmental variance to phenotypic variance was higher than h2 for all traits considered and ranged from 0-09 for NRR to 0-45 for milk yield. Body condition score had a favourable genetic correlation (rg) with SCS, but it was not strong (-0-08). Milk production was genetically antagonistic with fertility (rg: range 0-12 to 0-27 with DFS and -0-12 to -0-24 with NRR), with BCS (-0-39 to -0-50), and with SCS (0-10 to 0-15) showing that selecting for milk production alone would lead to decline in genetic merit for these functional traits. Body condition score had favourable genetic correlations with fertility traits (-0-35 with DFS and 0-04 with NRR) suggesting that BCS could be considered in a fertility index. Several type traits (especially 'udder' traits) had a favourable genetic relationship with fertility traits and SCS whereas dairy character had an unfavourable genetic relationship. Results of this study on genetic and phenotypic correlations among several functional, type and production traits could be used to design improved selection indexes for dairy producers.

The influence of cow genetic merit for milk production on response to level of concentrate supplementation in a grass-based system

The objective of this study was to investigate if there is a genotype ✕ feeding system interaction for milk production in Holstein-Friesian dairy cows. For this purpose, 48 high genetic merit (HM) and 48 medium genetic merit (MM) dairy cows, were used in a two (genotypes) ✕ three (levels of concentrate feeding) randomized-block design experiment in three consecutive years. In year 1, all animals were in their first lactation, while in year 2 and year 3, 18 and 12 first lactation cows replaced animals culled at the end of the previous lactation. A total of 66 cows remained in the study in the same feeding system for the 3-year duration of the study. Concentrate feeding levels were 376, 810 and 1540 kg per cow per lactation; these were identified as the LC, MC and HC feeding systems respectively. There was a separate farmlet for each feeding system; farmlets were managed so that pre-grazing and post-grazing herbage height were similar for all three feeding systems. When compared on treatment means there was a significant genotype ✕ feeding system interaction for fat yield, while for mean solid-corrected milk yield the interaction was close to statistical significance (P = 0·07). However, regression coefficients of both milk and protein yield on pedigree index for milk and protein yield were significantly different between the LC and the HC. The interaction between feeding system and the regression of both on pre-experimental milk and protein yield were close to statistical significance (P = 0·08 and P = 0·09 respectively). Outputs of milk, fat, protein and lactose were greater for the HM than the MM cows. Feeding system had a significant effect on milk, fat, protein and lactose yields. There was a significant genotype ✕ feeding system interaction for body condition score (BCS) at the end of lactation; the MM cows had a higher rate of body tissue repletion than the HM cows especially in the HC system. The results suggest that there is a genotype ✕ concentrate feeding level interaction and that feeding systems developed in the past for animals of lower genetic merit may require adaptation if they are to be optimal for higher genetic merit animals.

Periparturient immunosuppression and strategies to improve dairy cow health during the periparturient period

Common health problems observed during peripartum include milk fever, mastitis, fatty liver disease, ketosis, dystocia, retained placenta, metritis, hypomagnesaemia and abomasal displacements. The increased incidence of health problems observed during the periparturient period can be partly attributed to suboptimal immune responses. Factors contributing to decreased periparturient immunity include the act of parturition itself, impaired leukocytic activity, effects of colostrogenesis and lactogenesis, and associated hypocalcemia and negative energy balance. Nutritional and other management strategies represent a relevant short-term strategy aimed at improving the health and welfare of the transitioning cow. Additionally, it is important to consider improving the health of dairy herds through the genetic selection of animals with enhanced robustness by identifying those with superior disease resistance or resilience in the face of infection. As a consequence these animals are better able to cope with the production and environmental stresses. These may provide long-term selection strategies for improving the health and welfare of the transitioning cow particularly when combined with sound management practices, allowing dairy cattle to reach their full genetic potential.

Improving the reliability of female fertility breeding values using type and milk yield traits that predict energy status in Australian Holstein cattle

The objectives of this study were (1) to propose changing the selection criteria trait for evaluating fertility in Australia from calving interval to conception rate at d 42 after the beginning of the mating season and (2) to use type traits as early fertility predictors, to increase the reliability of estimated breeding values for fertility. The breeding goal in Australia is conception within 6 wk of the start of the mating season. Currently, the Australian model to predict fertility breeding values (expressed as a linear transformation of calving interval) is a multitrait model that includes calving interval (CVI), lactation length (LL), calving to first service (CFS), first nonreturn rate (FNRR), and conception rate. However, CVI has a lower genetic correlation with the breeding goal (conception within 6 wk of the start of the mating season) than conception rate. Milk yield, type, and fertility data from 164,318 cow sired by 4,766 bulls were used. Principal component analysis and genetic correlation estimates between type and fertility traits were used to select type traits that could subsequently be used in a multitrait analysis. Angularity, foot angle, and pin set were chosen as type traits to include in an index with the traits that are included in the multitrait fertility model: CVI, LL, CFS, FNRR, and conception rate at d 42 (CR42). An index with these 8 traits is expected to achieve an average bull first proof reliability of 0.60 on the breeding objective (conception within 6 wk of the start of the mating season) compared with reliabilities of 0.39 and 0.45 for CR42 only or the current 5-trait Australian model. Subsequently, we used the first eigenvector of a principal component analysis with udder texture, bone quality, angularity, and body condition score to calculate an energy status indicator trait. The inclusion of the energy status indicator trait composite in a multitrait index with CVI, LL, CFS, FNRR, and CR42 achieved a 12-point increase in fertility breeding value reliability (i.e., increased by 30%; up to 0.72 points of reliability), whereas a lower increase in reliability (4 points, i.e., increased by 10%) was obtained by including angularity, foot angle, and pin set in the index. In situations when a limited number of daughters have been phenotyped for CR42, including type data for sires increased reliabilities compared with when type data were omitted. However, sires with more than 80 daughters with CR42 records achieved reliability estimates close to 80% on average, and there did not appear to be a benefit from having daughters with type records. The cost of phenotyping to obtain such reliabilities (assuming a cost of AU$14 per cow with type data and AU$5 per cow with pregnancy diagnosed) is lower if more pregnancy data are collected in preference to type data. That is, efforts to increase the reliability of fertility EBV are most cost effective when directed at obtaining a larger number of pregnancy tests.

Biological efficiency profiles over the lactation period in multiparous high-producing dairy cows under divergent production systems

Abstract. The study examined variation in energetic-efficiency profiles among production systems and cow parities. Further, the correlation between cows' body condition score (BCS) and energetic efficiency over the lactation period was determined. Biological efficiency was defined using four measures of production efficiency and two measures of energetic efficiency. The following were measures of energetic efficiency: the net energy intake required to produce 1 kg milk solids (NEin / MS) and the proportion of net energy utilized for milk production after accounting for maintenance (NElact / (NEin- NEm)). Seven years of data were gathered from a total of 595 Holstein-Friesian cows in a long-term genetics × feeding–management interaction project. Two feeding regimes – High forage (HF) and Low forage (LF) – were applied to each of two genetic lines (Control (C) and Select (S)), giving four dairy production systems: Low Forage Control (LFC), Low Forage Select (LFS), High Forage Control (HFC) and High Forage Select (HFS). LFS was the most efficient system using all measures. Variation in the rate and scale of change at which the cows' energetic efficiency declined over lactation was significantly different (P < 0.001) amongst different dairy production systems and parities. Loss of efficiency over the lactation period was lower in Select cows than in Control cows and increased with parity. The trajectory of energetic-efficiency profiles was influenced by cow genetic line, and yet the level of the efficiency profile was influenced by the feeding regime. There was a strong relationship between BCS and energetic efficiency. Continued in situ monitoring of cows' biological efficiency may enable optimal management of dairy systems.

Estimation of genetic parameters of fertility traits in Chinese Holstein cattle

Guo, G., Guo, X., Wang, Y., Zhang, X., Zhang, S., Li, X., Liu, L., Shi, W., Usman, T., Wang, X., Du, L. and Zhang, Q. 2014. Estimation of genetic parameters of fertility traits in Chinese Holstein cattle. Can. J. Anim. Sci. 94: 281–285. The objective of this study was to estimate genetic parameters for fertility traits in Chinese Holstein heifers and cows. Data of 20169 animals with 42106 records over a period of 10 yr (2001–2010) were collected from Sanyuan Lvhe Dairy Cattle Center in Beijing, China. Traits included age at first service (AFS), number of services (NS), days from calving to first service (CTFS), days open (DO), and calving interval (CI). Genetic parameters were estimated with multiple-trait animal model using the DMU software. Heritability estimates for AFS, NS, CTFS, DO and CI were 0.100±0.012, 0.040±0.017, 0.034±0.011, 0.053±0.019 and 0.056±0.014, respectively. Genetic correlations between traits observed ranged from −0.13 to 0.99. Genetic correlations between AFS with NS, CTFS, DO and CI were −0.31, 0.15, −0.13 and −0.15, respectively. Calving interval was strongly correlated with NS, CTFS and DO (0.49–0.99), and DO showed strong correlation with NS and CTFS (0.49 and 0.58, respectively). The genetic correlation between CTFS and NS was negative moderate (−0.25). Results were in range with previous literature estimates and can be used in Chinese Holstein genetic evaluation for fertility traits.

Genetics and genomics of reproductive performance in dairy and beef cattle

Excellent reproductive performance in both males and females is fundamental to profitable dairy and beef production systems. In this review we undertook a meta-analysis of genetic parameters for female reproductive performance across 55 dairy studies or populations and 12 beef studies or populations as well as across 28 different studies or populations for male reproductive performance. A plethora of reproductive phenotypes exist in dairy and beef cattle and a meta-analysis of the literature suggests that most of the female reproductive traits in dairy and beef cattle tend to be lowly heritable (0.02 to 0.04). Reproductive-related phenotypes in male animals (e.g. semen quality) tend to be more heritable than female reproductive phenotypes with mean heritability estimates of between 0.05 and 0.22 for semen-related traits with the exception of scrotal circumference (0.42) and field non-return rate (0.001). The low heritability of reproductive traits, in females in particular, does not however imply that genetic selection cannot alter phenotypic performance as evidenced by the decline until recently in dairy cow reproductive performance attributable in part to aggressive selection for increased milk production. Moreover, the antagonistic genetic correlations among reproductive traits and both milk (dairy cattle) and meat (beef cattle) yield is not unity thereby implying that simultaneous genetic selection for both increased (milk and meat) yield and reproductive performance is indeed possible. The required emphasis on reproductive traits within a breeding goal to halt deterioration will vary based on the underlying assumptions and is discussed using examples for Ireland, the United Kingdom and Australia as well as quantifying the impact on genetic gain for milk production. Advancements in genomic technologies can aid in increasing the accuracy of selection for especially reproductive traits and thus genetic gain. Elucidation of the underlying genomic mechanisms for reproduction could also aid in resolving genetic antagonisms. Past breeding programmes have contributed to the deterioration in reproductive performance of dairy and beef cattle. The tools now exist, however, to reverse the genetic trends in reproductive performance underlying the observed phenotypic trends.