Additive Genetic Random Effects Research Articles

Genetic and genomic evaluation of age at first calving in Italian Holsteins

Age at first calving (AFC) represents the non-productive period of around 2 yr in Holstein cows and thus it has a relevant impact on the cost of rearing replacements in the dairy herd. In the present study we aimed at evaluating genetic and genomic aspects of AFC in the Italian Holstein population. Data of 4,206,218 heifers with first calving between 1996 and 2020 were used. Age at first calving averaged 26.09 ± 3.07 mo and decreased across years. Heritability was estimated using a linear animal model which included the fixed effects of herd-year-season of birth and classes of gestation length, and the random animal additive genetic effect fitted to a pedigree-based relationship matrix. Estimated breeding values (EBV) and genomically enhanced breeding values (GEBV) were obtained, and they were standardized to mean 100 and standard deviation 5, where animals above the mean are those contributing to reduce AFC. Heritability estimates of AFC ranged from 0.031 to 0.045. The trend of sires' GEBV was favorable and indicated a reduced AFC across years. Approximate genetic correlations between GEBV of AFC and GEBV of other economically important traits were calculated on a subset of genotyped females born after 2015. Moderate favorable associations of AFC with production traits (0.39 to 0.51), udder depth (0.40), interval from first to last insemination in heifer (-0.43), and longevity (0.34) were assessed. Overall, the greatest lifetime productive performances and most favorable days open in first lactation were observed when heifers calved at 22-23 mo. On the other hand, progeny of sires with GEBV of AFC above the mean yielded more milk, fat, and protein in first lactation, and had shorter days open than progeny of sires with GEBV of AFC below the mean. Results suggested that breeding strategies to improve AFC should be pursued, also considering genetic correlations between AFC and traits which are already part of the Italian Holstein breeding objective. The inclusion of AFC in an aggregate index is expected to contribute to enhance farm income.

118 Variance Components for Age at First Calving and Yearling Weight When Accounting for Age Differences at Fixed Breeding Dates in a Contemporary Group

Abstract The ability of a heifer to calve earlier in a breeding season has implications on the economic success of heifers in a production system. Heifers that calve earlier in a calving season have increased calf performance, improved subsequent fertility, and a longer productive life in the herd. Production systems typically breed heifers during fixed breeding dates, with heifers of variable ages in the same contemporary group. The objective of this study was to determine if heifer yearling weight (YW) or age differences going into a fixed breeding period influenced the additive genetic variance of age at first calving (AFC) explained in a multi-breed population. Heifer fertility data were obtained from International Genetic Solutions. Females with exposure and calf production records were used to identify individuals calving between 630 and 810 days of age. Females with embryo transfer, multiple birth progeny, and an age differential (DIFF) greater than 100 days were excluded. Age differential was defined as the difference in days between an individual’s birth date and the earliest birth date of an animal in a defined contemporary group. Contemporary group was defined as; breeder, herd, year born, birth and yearling group. After data filtering, there were 149,350 calving records. A 3-generation pedigree file was used containing 365,637 animals, with 37,420 unique sires and 219,533 unique dams. Two bivariate multi-trait animal models for AFC and YW with random additive genetic and residual effects and fixed effects of contemporary group, breed proportion, and % retained hybrid vigor were used. The first model consisted of the aforementioned effects while the second model included DIFF as an additional fixed effect. Analyses were performed using ASReml 3.0. When DIFF was not included as a fixed effect, the additive, residual and phenotypic variances for AFC were 126.1, 456.8, and 582.9 d2, respectively, and the genetic correlation between AFC and YW was 0.36 ± 0.02. When DIFF was included as a fixed effect, the additive, residual, and phenotypic variances for AFC were 10.0, 326.0, and 336.0 d2, respectively. The genetic correlation between AFC and YW was 0.19 ± 0.04. In the absence of DIFF, the heritability estimates for AFC and YW were 0.22 ± 0.01 and 0.44 ± 0.01, respectively but were 0.03 ± 0.003 and 0.44 ± 0.01 respectively, when DIFF was included. Age differential was a significant effect on AFC at –0.86 (P < 0.0001). The low additive variance of AFC when accounting for DIFF suggests that the influence of a female's age going into a fixed breeding date explains much of the variation in AFC. The low heritability estimate for AFC and genetic correlation with YW suggests that selection for improved AFC will be difficult using this method and that producers should instead focus on improved management practices to ensure females calve earlier in a calving season.

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.

16 Genetic Parameter Estimates for Age at First Calving in Simmental and Red Angus Heifers

Abstract The objective of this study was to determine genetic parameter estimates for age at first calving (AFC) in Red Angus and Simmental heifers. The ability for a heifer to calve earlier has implications on calf performance and the heifer's successive re-breeding. Heifer pregnancy data were obtained from International Genetic Solutions, where females with exposure records were included in the population. Females with a subsequent record of calving between 630 and 810 days of age were included in the analysis. Females with embryo transfer or multiple birth progeny were excluded. Records from single-animal and contemporary groups with no variation were eliminated and after data filtering, there were 149,379 Simmental with a mean Simmental breed proportion of 0.58 ± 0.25, and 83,191 Red Angus records with a mean Red Angus breed proportion of 0.80 ± 0.13. A 3-generation pedigree file containing 291,530 Simmental animals with 25,585 unique sires and 161,921 unique dams, and a 3-generation pedigree file containing 174,914 Red Angus animals with 19,733 unique sires and 99,464 unique dams were used for the separate analysis. The mean AFC in Simmental and Red Angus was 724.8 ± 28.64 d, and 724.2 ± 29.93 d, respectively. Data for each breed were modeled separately using a single trait animal model with random additive genetic and residual effects, and the fixed effect of contemporary group using ASReml 3.0. Contemporary group was defined as breeder, herd, year born, birth group and yearling group. The additive, residual, and phenotypic variances for Simmental were 120.08, 520.37, and 640.45 d2, respectively. For Red Angus, 85.67, 543.56, and 629.24 d2 were the additive, residual, and phenotypic variances, respectively. The heritability estimates of AFC for Simmental and Red Angus were 0.19 ± 0.0059 and 0.14 ± 0.0076, respectively. These results demonstrate AFC in days is lowly to moderately heritable. Lower residual and higher additive variance in Simmental compared to Red Angus may suggest the Simmental population has larger variation for underlying fertility influences such as age at puberty. The mean breeding values for AFC in Simmental was 6.1 ± 8.0, with a minimum of -24.4 and maximum of 54.7. Whereas Red Angus breeding values for AFC resulted in a mean of 4.0 ± 5.6 and a minimum and maximum of -16.1, and 37.3, respectively. The comparable heritability estimates, low standard error, and range in breeding values suggest selection for improved AFC can be attained. It is worth further exploring the impact of breed effects and heterosis influences on age at first calving. While this study does not account for heifers that did not calve in their first year, tandem selection for heifer fertility and age at calving should be heavily emphasized due to the economic importance of both traits.

Efecto de dos estrategias de agrupación de padres fantasmas en la evaluación genética de rasgos de crecimiento en el ganado Braunvieh mexicano

The study aimed to compare two grouping strategies for unknown parents or phantom parent groups (PPG) on the genetic evaluation of growth traits for Mexican Braunvieh cattle. Phenotypic data included birth (BW), weaning (WW) and yearling (YW) weights. Pedigree included 57,341 animals. The first strategy involved 12 PPG (G12) based on the birth year of the unknown parent’s progeny and the sex of the unknown parent, while the second involved 24 PPG (G24) based on the birth year of the unknown parent’s progeny and 4-selection pathways. The animal models included fixed effects and the random direct additive genetic effect; WW also included random maternal genetic and maternal permanent environmental effects. Product-moment correlations between EBV from G0 (no PPG) and G12 were 0.96, 0.77 and 0.69 for BW, WW and YW, respectively, and between EBV from G0 and G24 were 0.91, 0.54, and 0.53, respectively. Corresponding rank correlations between G0 and G12 were 0.94, 0.77, and 0.72, and between G0 and G24 were 0.89, 0.61, and 0.60. Genetic trends showed a base deviation from the genetic trend of G0, except for BW of G12. The results did not support the use of the two grouping strategies on the studied population and traits, and further research is required. Introducing PPG to the model, enough phenotype contribution from descendants to PPG, and avoiding collinearity between PPG and fixed effects are important. Genetic groups should reflect changes in the genetic structure of the population to the unknown parents, including different sources of genetic materials, and changes made by selection over time.

Genetic evaluation of lactation persistency in the Gyr breed by using a two-trait random regression model

Context Lactation persistency (LP) is an economically important characteristic to include in the selection objectives of the Gyr breed. Two persistency measures were tested to establish their contribution to the genetic evaluation of milk production in this genotype. The second measure of persistency studied would be the more appropriate measure to use in the genetic evaluation of lactation persistency. Aim The aim of this work was to study LP in Gyr cows by using a random regression model (RRM) in two-trait analysis. Methods Test-day milk yields (TDMY) of the first two lactations of Gyr cows were analysed. RRM was performed by Bayesian inference using the GIBBS3F90 program. Fourth-order Legendre polynomials were used to describe the random additive genetic and permanent environmental effects of the animal. The fixed effects included in the model were contemporary group and, as covariates, age of cow at calving and the regression function according to the TDMY class of lactation as the average trajectories of lactation curve, distinguished by calving order. Two persistency measures (PSi, i.e. PS1 and PS2) were used in the analyses. Rank correlations were calculated between the predicted breeding values for PSi, 305-day lactation milk yield (MY305), and the regression coefficients a0 and a1, to determine the percentage of matching animals between rankings when different selection intensities are applied on the basis of the ranking for MY305. Key results The heritability estimates for PS1, PS2 and for MY305 were 0.19, 0.12 and 0.41 respectively, in the first lactation, and 0.43, 0.27 and 0.38 in the second lactation. The genetic correlation between MY305 and PS1 was negative and of low magnitude. The rank correlation between breeding values for PSi, obtained for bulls with at least five daughters with production records, was higher than 0.80 in the two lactation periods. Conclusions The results indicated that PS2 is the more suitable of the two persistency measures used in this work, for inclusion in genetic evaluations of lactation persistency in Brazilian Gyr cows. Implications PS2 must be included as a selection criteria in a breeding program for the Gyr breed.

Genetic parameter estimates for feet and leg traits in Red Angus cattle.

The objective of this study was to estimate genetic parameters for feet and leg traits, relationships within feet and leg traits, and relationships between feet and leg traits and production traits in Red Angus cattle. Subjective scores for 14 traits including body condition score (BCS), front hoof angle (FHA), front heel depth (FHD), front claw shape (FCS), rear hoof angle (RHA), rear heel depth (RHD), rear claw shape (RCS), size of hoof (SIZE), front side view (FSV), knee orientation (KNEE), front hoof orientation (FHO), rear side view (RSV), rear view (RV), and a composite score (COMP) were collected by trained evaluators on 1,720 Red Angus cattle. All traits except COMP were scored as intermediate optimum traits. Performance data, and EPD were obtained on all animals measured and a three-generation pedigree was obtained from the Red Angus Association of America (RAAA) that contained 13,306 animals. Data were modeled using a linear bivariate animal model with random additive genetic and residual effects, and fixed effects of age and contemporary group (herd-year) implemented in ASREML 4.0. Heritability estimates of BCS, FHA, FHD, FCS, RHA, RHD, RCS, SIZE, FSV, KNEE, FHO, RSV, RV, and COMP were 0.11, 0.20, 0.17, 0.09, 0.19, 0.25, 0.17, 0.36, 0.16, 0.17, 0.17, 0.30, 0.14, and 0.12, respectively. These results demonstrate feet and leg traits are lowly to moderately heritable. Strong, positive genetic correlations were observed between FHA and FHD (0.89), FHA and RHA (0.88), FHD and RHA (0.85), FHA and RHD (0.85), FHD and RHD (0.94), and FHO and KNEE (0.95), indicating these traits were highly related to each other. Strong and negative genetic correlations were observed between KNEE and FSV (-0.59) and FHO and FSV (-0.75). The strongest Pearson correlation between front limb traits (FHA, FHD, FSV, FHO, KNEE, and COMP) and Stayability EPD (STAY) was FSV (r = 0.16) and for rear limb traits (RHA, RHD, RCS, RSV, RV, and COMP) and STAY was RCS (r = -0.12). This suggests cattle with more slope to the angle of the shoulder and cattle with less evidence of hoof curl may stay in the herd longer. Further investigation into the economic viability of feet and leg trait genetic prediction with a larger population of animals is required to help validate these findings.

PSVIII-4 Genetic evaluation of functional heifer longevity in north American angus cattle

Abstract The goals of this study were to develop a genetic evaluation system for a novel trait called functional heifer longevity (FHL), and determine if this novel trait is heritable. The FHL trait was defined as binary, in which the heifers received the code 1 if they had calved by the end of their third year (n = 377,938), or 0 if they were culled/sold during this period (n = 368,308). Analysis were performed using linear animal models and Bayesian inference. The significant systematic effects included in the statistical models are born by embryo transfer, year-season of birth, and age at calving (in months). Three models, differing according to their random effects (i.e., reduced model, which included only herd-year-season and additive genetic random effects; maternal genetic model, which added maternal genetic effects; and complete model, which further added maternal permanent environmental effects), were compared based on the deviance information criterion (DIC) and the estimates of genetic parameters. The reduced model was preferred according to the DIC values. However, high maternal heritabilities were estimated using the maternal genetic (0.51) and complete (0.36) models, indicating that maternal effects can impact the selection of heifers for breeding. Similar additive genetic heritabilities were estimated among the three models (0.24, 0.27, and 0.25 using the reduced, maternal genetic, and complete models, respectively), and no significant re-ranking of selection candidates were observed based on their additive genetic breeding values. Total heritabilities and correlations estimated between additive genetic and maternal genetic effects were 0.37 and -0.28 for the maternal genetic, and 0.31 and -0.27 for the complete model, respectively. This study shows that FHL is heritable, and that including maternal effects in the statistical models might be important. These results contribute to a larger project studying the genetics of female longevity in Angus cattle.

503 Late-Breaking: Using Random Regression Models to Estimate Genetic Parameters for Milk Production Traits under Different Levels of Heat Stress in Canadian Holstein Cattle

Abstract Genetically selecting animals that are heat tolerant can help to maintain production efficiency of the dairy industry under thermal challenges. During the summer months in Canada, dairy cows could be under thermal stress. For instance, in Ontario, cows are expected to be 105 days under thermal stress. The objective of this study was to estimate genetic parameters for milk production traits under heat stress in Canadian Holstein cows. A total of 604,050 test-day records for milk, fat, and protein yields from 78,516 first-lactation Holstein cows were used in this study. The production data was combined with daily maximum temperature-humidity index (THI; ranging from 30 to 83) calculated based on meteorological records from public weather stations. In total, 58 weather stations were located within a maximum distance of 20 km from each of the 1,284 herds included in this study. Single-trait random regressions on THI, fitting linear splines to describe the random additive genetic and permanent environmental effects, were used in the genetic analyses. Based on preliminary analyses, the knots of the spline functions were set to THI = 70, 57, and 58 for milk, fat, and protein yields, respectively. Therefore, the models assumed a linear effect of heat stress beyond the THI threshold, allowing to estimate the additive genetic effect under thermal comfort and at different levels of heat stress. The genetic correlations estimated between thermal comfort and heat stress were -0.09, -0.33, and -0.21 for milk, fat, and protein yields, respectively. This indicates an antagonistic relationship between level of production and heat tolerance. However, small differences in heritability estimates were observed above the THI thresholds (they ranged from 0.20 to 0.22 for milk, 0.18 to 0.15 for fat, and 0.14 to 0.15 for protein yields). This study demonstrates the possibility of genetically selecting for more heat-tolerant animals in Canada.

Genetic associations between growth traits and age at first calving in Guzera cattle using random regression models

The aim of this study was to estimate genetic associations between body weight (BW), scrotal circumference (SC), and age at first calving (AFC) in Guzera cattle using random regression models. The analyses used 159,366 and 23,780 records of BW and SC obtained between 335 and 724 days of age and divided into classes at intervals of 10 days, as well as 63,596 records of AFC. A multitrait animal model via Gibbs sampling was adopted that included random direct additive genetic, permanent environmental (only for BW and SC), and residual effects. The fixed effects considered were the contemporary group, age of cow at calving (linear and quadratic effect), and the fixed curve to model the average trend of the population on the age classes of the animals. For BW and SC, four models were compared using the deviance information criterion, with Legendre polynomials ranging from one to four coefficients (intercept, linear, quadratic, and cubic) for additive genetic and permanent environmental effects. The model with three coefficients (quadratic) was considered the most appropriate to describe the (co)variance structure of the traits analyzed. The mean heritability estimates ranged from 0.17 to 0.31 for BW and from 0.19 to 0.28 for SC across age classes. The mean heritability for AFC was 0.07. The genetic correlations between BW and SC across age classes were always positive and favorable, ranging from 0.33 to 0.39. These findings indicate that selection for higher BW should result in animals with greater SC. The genetic correlations between BW at different ages and AFC ranged from -0.56 to -0.38, while those between SC at different ages and AFC ranged from -0.55 to 0.08. Except for some genetic correlations close to zero and positive between SC close to 365 days of age and AFC, in general the results showed that the selection for either higher BW or greater SC should result in a reduction of AFC in Guzera cattle. Calculation of the relative selection efficiency indicated a greater correlated response in AFC by selection for SC, especially after 634 days of age, compared to direct selection for AFC.

Genetic parameters for performance, feed efficiency, and carcass traits in Senepol heifers

Improving feed efficiency is a key breeding goal in the beef cattle industry. In this study, we estimated the genetic parameters for feed efficiency and carcass traits in Senepol cattle raised in tropical regions. Various indicators of feed efficiency [gain to feed ratio (G:F), feed conversion ratio (FCR), residual weight gain (RG), residual intake and body weight gain (RIG), and residual feed intake (RFI)] as well as growth [final BW, average daily gain (ADG), and DM intake (DMI)], and carcass [rib-eye area (REA), backfat thickness (BF), intramuscular fat score, and carcass conformation score] traits were included in the study. After data editing, records from 1 393 heifers obtained between 2009 and 2018 were used for the analyses. We fitted an animal model that included contemporary group (animals from the same farm that were evaluated in the same test season) as the fixed effect, and a linear effect of animal age at the beginning of the test as a covariate; in addition to random direct additive genetic and residual effects. The (co)variance components were estimated by Bayesian inference in uni- and bivariate analyses. Our results showed that feed efficiency indicators derived from residual variables such as RG, RIG, and RFI can be improved through genetic selection (h2 = 0.14 ± 0.06, 0.13 ± 0.06, and 0.20 ± 0.08, respectively). Variables calculated as ratios such as G:F and FCR were more influenced by environmental factors (h2 = 0.08 ± 0.05 and 0.09 ± 0.05), and were, therefore, less suitable for use in breeding programs. The traits with the greatest and impact on genetic progress in feed efficiency were ADG, REA, and BF. The traits with the greatest and least impact on growth and carcass traits were RG and RFI, respectively. Selection for feed efficiency will result in distinct overall effects on the growth and carcass traits of Senepol heifers. Direct selection for lower RFI may reduce DMI and increase carcass fatness at the finishing stage, but it might also result in reduced growth and muscle deposition. Residual BW gain is associated with the highest weight gain and zero impact on REA and BF, however, it is linked to higher feed consumption. Thus, the most suitable feed efficiency indicator was RIG, as it promoted the greatest decrease in feed intake concomitant with faster growth, with a similar impact on carcass traits when compared to the other feed efficiency indicators.

Assessment of alternative models for genetic analysis of worm and tick infestation in nellore cattle

Worms and ticks are important parasites in beef cattle, especially in tropical areas, causing significant economic and production losses. Understanding animal-to-animal variation on infestation for these parasites might guide genetic selection and improvement of management practices to attenuate its detrimental effects. Statistical models used to analyze such traits usually assume a Gaussian distribution for the observed data. However, this assumption is quite often inappropriate for counting data. Therefore, the objectives of this study were: 1) Estimate genetic parameters for worms and tick infestations in Nellore cattle, and 2) To compare the overall performance of six data analysis approaches for worm and tick infestation in Nellore cattle, using different specifications of generalized linear mixed models (GLMM) and response variables. Data consisted of presence/absence of parasites as well as counting observations for both worms and ticks in a Nellore herd in Brazil. The binary data were analysed with both Gaussian and Threshold models, whereas the counting data were studied using Gaussian models on the original and logarithmic scales, as well as Poisson and Zero-Inflated Poisson (ZIP) models. All models included the systematic effects of contemporary group and age, as well as the random additive genetic and residual effects. Models were compared using four criteria: Deviance Information Criterion (DIC), Spearman's correlation between predicted breeding values from different models, the agreement on the 5 and 50% top-ranked animals across models, and the Mean Squared Error of Prediction (MSEP) assessed via Monte Carlo Cross-Validation (MCCV). The MCCV was performed using parallel computing through the Center for High Throughput Computing (CHTC) at the University of Wisconsin-Madison. The estimates of heritability ranged from 0.15 to 0.40 for worms and from 0.08 to 0.25 for ticks. According to the DIC, non-Gaussian models displayed the best goodness of fit compared to Gaussian models. DIC's results excluded Gaussian models on the logarithmic scale because fairer comparisons involve phenotypes on the same scale. Spearman's correlation and the percentage of agreement on the 5% and 50% top-ranked animals suggested some re-ranking of animals depending upon the model used. Monte Carlos Cross-Validation showed that all models presented similar MSEP with average values of 0.20 (binary data; worms), 0.18 (binary data; ticks), 15.69 (count data; worms), and 14.19 (count data; ticks). Moreover, performing MCCV in parallel had the benefit to deliver results for all models in about 2 days. Heritability estimates indicate that the selection of high merit animals for worms and tick infestation is possible feasible and can potentially contribute to the genetic progress. Furthermore, genetic selection should be performed concomitantly with traditional parasite control approaches. Overall, non-Gaussian models seem to be better suitable for genetic analysis of worm and tick infestation in beef cattle, because such models have lower DIC values with similar predictive performance compared to Gaussian models.

Multi-trait animal model based estimation of direct and correlated responses in Frieswal cattle

The study was undertaken to estimate the genetic parameters, direct and correlated responses for the test day and lactation milk yield in Frieswal cattle. Data on 9,955 daily milk yield records of 973 Frieswal cows calved during 2005 to 2014 at Ambala and Meerut dairy farms were utilized. The variance components, heritability estimates, genetic and phenotypic correlations for all the 11 traits were estimated simultaneously by fitting multi-trait animal model using the Wombat program of Meyer (2006) with contemporary groups as fixed effect, the additive genetic random effects, linear and quadratic regressions of covariate age at first calving and linear regression of covariate first lactation length. The expected genetic gain (DG), correlated response (CR) in cumulative 305-day yield and vice versa and the relative efficiency (RE %) of selection based on different test day yields were estimated. The results revealed lower additive genetic variance and heritability estimates for different test days and cumulative 305-day yield. The genetic correlations between the test days up to 225 and cumulative 305-days were higher which indicated the positive relationship between these traits. The higher correlated responses in cumulative 305- day yield estimated through the selection for TD135, TD165 and TD45, in that order indicated that early selection of sires using test day records would be efficient in genetic improvement for lactational milk yield in Frieswal breed of cattle.

Genetic, farm, and lactation effects on behavior and performance of US Holsteins in automated milking systems

Selecting for favorable behavior and performance could enhance the efficiency of production in automated milking systems (AMS). The objectives of this study were to describe AMS behavior and performance in Holsteins, estimate genetic parameters among AMS traits, and determine genetic relationships of AMS traits with other routinely recorded traits. The edited data included 1,101,651 individual milking records and 394,636 daily records from 2,531 lactations and 1,714 cows that resided on 3 farms; data were obtained from the Dairy Data Warehouse (Assen, Netherlands) cloud. Traits considered were individual milking and daily totals for milk yield, milking time, milk harvest rate (the ratio of milk yield to milking time), milk flow rate, electrical conductivity, machine kickoffs, incomplete milkings, and blood in milk; the number of milkings per day and 305-d mature-equivalent milk yield (305ME) were also evaluated. Individual milkings were evaluated with mixed models that included fixed effects of week of lactation, lactation group (1, 2, ≥3), hour of day, and farm; random effects included cow within lactation, lactation group by week of lactation, and interactions of farm with date, hour, week of lactation, and year-season of calving. Daily records were evaluated with 3-trait animal models that included 305ME and 2 AMS traits with random additive genetic and permanent environment effects. Estimated breeding values were extracted and correlated with yield, conformation, and udder health genetic evaluations. Farm specific robot access policies had notable effects on week of lactation patterns for milk yield and number of milkings. Mature cows had higher milk harvest rates (2.05 kg/min) than first-lactation cows (1.73 kg/min) with larger differences in early lactation. First-lactation cows were more likely to kick off the machine (15.04%) than mature cows (8.62%), particularly in early lactation. Heritability estimates were generally lower for behavior traits (0.03 for incomplete milkings and 0.08 for kickoffs) than for milk harvest rate (0.30) and flow rate (0.55). Udder conformation traits did not have favorable genetic correlations with AMS traits, with the exception that longer teats were correlated with fewer kickoffs (-0.34) and incomplete milkings (-0.49); increased milk harvest rate and flow rate were unfavorably associated with genetic merit for udder health. There is genetic variation for milking efficiency and behavioral traits, suggesting genetic selection to enhance efficiency in AMS systems is possible. Genetic associations with udder conformation indicate that selection for udder morphology is unlikely to substantially improve milking efficiency. This calls for more direct selection of traits related to AMS efficiency.

Bayesian estimation of genetic variance and response to selection on linear or ratio traits of feed efficiency in dairy cattle

This study aimed to estimate genetic parameters of the linear trait genetic residual feed intake (RFI) and the ratio traits feed conversion ratio (FCR) and feed conversion efficiency (FCE) along with dry matter intake (DMI) and energy sink traits such as energy-corrected milk (ECM), body weight (BW), body condition score (BCS), and BW change (BWC) across different weeks in the first lactation of Danish Holstein cows. A second objective was to conduct a Bayesian analysis of direct and correlated superiority of the selected group when selecting on genetic RFI, FCR, or FCE. Feed intake and energy sink traits were recorded during wk 1 to 44 of lactation on 847 primiparous Danish Holstein cows. A Bayesian multivariate random regression animal model was used to analyze DMI, ECM, BW, and BCS in different weeks of lactation. Genetic RFI was obtained by conditioning DMI on ECM, BW, BCS, and BWC using genetic partial regression coefficients. The posterior distribution of the breeding values for FCR and FCE was derived from the posterior distribution of functions of "fixed" environmental effects and random additive genetic effects on DMI and ECM. Genetic superiority of the selected group was defined as the difference in additive genetic mean of the selected top individuals expected to be potential parents, and the total population after integrating genetic trends out of the posterior distribution of selection responses. Posterior means of heritability of genetic RFI ranged from 0.10 to 0.15, genetic variance of FCR and FCE ranged from 2.13 × 10-3 to 3.2 × 10-3 (kg2 DMI/kg2 ECM) and 6.11 × 10-3 to 2.4 × 10-2 (kg2 ECM/kg2 DMI), respectively. Selection against RFI showed a direct response of -1.01 to -2.23 kg/d RFI and correlated responses of -0.031 to -0.056 kg/kg for FCR, 0.104 to 0.160 kg/kg for FCE, and -0.316 to -1.057 kg/d for DMI in different weeks of lactation. Selection against RFI had no significant effect on production traits but selection for ratio traits reduced BW and BCS. Posterior means of genetic correlation between DMI and ratio traits were low. In conclusion, the Bayesian procedure allowed us to estimate genetic RFI without the need for separate multiple regression analysis and considered the non-normal posterior distribution of ratio traits. Selection against genetic RFI might be an effective means to improve feed efficiency compared with ratio traits for feed efficiency in dairy cattle.

Impact of inbreeding on milk fatty acids of a Brazilian Holstein cattle

Context Reproductive technologies may either contribute to the increase of genetic gains or inbreeding levels in dairy cattle breeding programs and herds. In general, studies have evaluated the impacts of inbreeding on traditional traits, such as production and reproduction. However, studies on novel traits, such as milk fatty acids profile, are scarce in the literature. Aim We aimed to evaluate the impact of inbreeding levels on milk fatty acids profile measured in a Brazilian Holstein cattle population. Methods Monthly records of the percentages (%) of palmitic, stearic, oleic, total saturated, unsaturated, monounsaturated and polyunsaturated fatty acids in milk were collected from 2047 Holstein cows between May and December 2012. The pedigree file contained 7963 animals over seven generations. The inbreeding trend was evaluated by linear regression of inbreeding coefficients on generations. The inbreeding impacts on breeding and phenotypic values were evaluated by linear regression of breeding values and phenotypic values on generations respectively. Breeding values were obtained by a Bayesian approach based on an animal model that included the systematic effect of contemporary group, cubic effect of days in milk as a covariate, and the random direct additive genetic and animal permanent environmental effects. Key results The average inbreeding coefficient was 0.28% for all animals, and 1.39% for inbred animals. Inbreeding tended to increase 0.24% per generation (P-value <0.0001). The regression coefficients of phenotypic values on inbreeding were not significant for saturated, unsaturated, monounsaturated, palmitic, stearic and oleic fatty acids (P-values >0.18, 0.10, 0.16, 0.26, 0.51 and 0.09 respectively); whereas for polyunsaturated fatty acids, they were significant (P-value <0.04), with an increase of –0.000978% on phenotypic values for each 1% increase in inbreeding. The regression coefficients of breeding values on inbreeding were not significant for unsaturated, monounsaturated, polyunsaturated, stearic and oleic fatty acids (P-values >0.33, 0.78, 0.48, 0.32 and 0.07 respectively). However, they were significant for saturated and palmitic fatty acids (P-values <0.03 and 0.0001 respectively), presenting an increase of 0.000689% and 0.000283% respectively on breeding values for each 1% increase in inbreeding. Conclusions There was a significant increase in inbreeding coefficients over the studied generations; however, the impacts on both breeding and phenotypic values were small, when significant. Implications Our study may contribute to the understanding of how inbreeding levels may affect the fatty acids profile in a Brazilian Holstein cattle population, as well as encourage future research on this subject.

Estimation of genetic parameters and breeding values for feed intake and energy balance using pedigree relationships or single-step genomic evaluation in Holstein Friesian cows

At the beginning of lactation, high-performing dairy cows often experience a severe energy deficit, which in turn is associated with metabolic stress. Increasing feed intake (FI) or reducing the energy deficit during this period could improve the metabolic stability and thus the health of the animals. Genomic selection for the first time enables the inclusion of this hard-to-measure trait in breeding programs. The objective of the current study was the estimation of genetic parameters and genomic breeding values for FI and energy balance (EB). For this purpose, 1,374 Holstein Friesian (HF) dairy cows from 8 German research farms were phenotyped with standardized FI data protocols. After data editing, phenotypic data of HF comprised a total of 40,012 average weekly FI records with a mean of 21.8 ± 4.3 kg/d. For EB 33,376 average weekly records were available with a mean of 3.20 ± 29.4 MJ of NEL/d. With the Illumina Bovine SNP50 BeadChip (Illumina Inc., San Diego, CA) 1,128 of phenotyped cows were genotyped. Thirty-five female candidates of the HF population were genotyped but not phenotyped. Pedigree information contained sires and dams 4 generations back. The random regression animal model included the fixed effects of herd test week (alternatively, herd group test week), parity, and stage of lactation, modeled by the function according to Ali and Schaeffer (1987). For both the random permanent environmental effect across lactations and the random additive genetic effect, third-order Legendre polynomials were chosen. Additionally, a random permanent environmental cow effect within lactation was included. Analyses for heritabilities, genetic correlations between different lactation stages, and breeding values were estimated using, respectively, pedigree relationships and single-step genomic evaluation, carried out with the DMU software package (Madsen et al., 2013). This allowed for comparison of conventional reliabilities with genomic-assisted reliabilities based on real data, to evaluate the gain of genotyping. Heritability estimates ranged between 0.12 and 0.50 for FI, and 0.15 and 0.48 for EB, and increased toward the end of lactation. Genetic correlations were weak between early and late lactation, with a value of 0.05 for FI and negative with a value of -0.05 for EB. Reliabilities for genomic values of cows for FI and EB ranged between 0.33 and 0.61, and 0.27 and 0.47, respectively. For the genotyped cows without phenotypes, the inclusion of genomic relationship leads to an increase of the average reliability of the breeding value for FI by nearly 9% and for EB by 4%. The results show the possibility of combining pedigree, genotypes, and phenotypes for increasing FI or EB to reduce health and reproductive problems, especially at the beginning of lactation. Nevertheless, the reference population needs to be extended to reach higher breeding value reliabilities.

214 Correlation among host gut microbiome and their relationship with meat quality and carcass composition traits of swine

Abstract Study on correlation among host gut microbiome and their relationship with meat quality and carcass composition traits remains limited. The objectives of this study were 1) to estimate the microbial correlation between meat quality and carcass traits; and 2) to estimate the genetic correlation between microbial alpha diversity, and meat quality and carcass traits in commercial swine population. Data were collected from Duroc sired three-way cross individuals (n = 1,123) genotyped with 60K SNP chips. Fecal 16S microbial sequences for all individuals were obtained at three different stages: weaning (WEAN: 18.64 ± 1.09 days); week 15 (W_15: 118.2 ± 1.18 days); and off test (OT: 196.4 ± 7.80 days). Alpha diversity was measured at each stage [WEAN (alpha_w), W_15 (alpha_15) and OT (alpha_off)] using the Shannon index, which was computed as: ∑ ni=1piln(pi) where pi was the proportional abundance of ith operational taxonomic unit. Microbial correlations were estimated using multi-trait model, which included fixed effects of dam line, contemporary group and sex, as well as random effects of pen, additive genetic and microbiome. Bivariate analyses were conducted between different traits and alpha_w, alpha_15 and alpha_off with the same fixed effects and random pen and additive genetic effect. Analyses were conducted in ASREML v.4. Microbial correlations ranged from -0.93 ± 0.11 between firmness and slice shear force to 0.97 ± 0.02 between carcass average daily gain (CADG) and loin weight. For meat quality traits, correlations were weak, except for alpha_15 with Minolta a* (-0.45±0.19). Alpha_15 showed weak correlations except with CADG (-0.43±0.19). All correlations between alpha_ot and growth, carcass and meat quality traits were weak. These results may establish a newer approach of genetic evaluation process by utilizing gut microbiome information.

216 Contribution of host gut microbiome in prediction of meat quality and carcass composition traits in swine

Abstract The objective of this study was to assess the improvement in predictive ability (PA) for meat quality and carcass composition traits by including the effect of host gut microbiome. Data were collected from Duroc sired three-way crossbred individuals (n = 1,123) genotyped from 60k SNP chips. Fecal 16S microbial sequences for all individuals were obtained at three different stages: weaning (WEAN: 18.64±1.09 days); week 15 (W_15: 118.2±1.18 days); and off test (OT: 196.4±7.80 days). A 4-fold cross validation was used, with animals grouped based on sire relatedness. Analysis was conducted in “BGLR” package in R. The first model included the fixed effect of dam line, contemporary group, and sex, as well as random pen and additive genetic effect (with genomic relationship matrix). The second model included same fixed and random effects with the addition of the microbiome effect (with microbiome relationship matrix). With the inclusion of microbiome, the PA increased for majority of traits. For carcass traits, the increase in PA was greatest for belly weight which changed from 0.22±0.06 to 0.32±0.06 at OT and lowest for loin depth and ham weight which changed from 0.14±0.06 to 0.15 ±0.06 and 0.12±0.02 to 0.13 ±0.03 at WEAN respectively. For meat quality traits, the increase in PA was greatest for subjective firmness score which changed from 0.16±0.04 to 0.19±0.04 at OT and lowest for marbling score and intramuscular fat which changed from 0.27±0.09 to 0.28±0.08 and 0.39±0.05 to 0.40±0.05 at WEAN respectively. Higher predictive ability was observed at OT rather than at WEAN and W_15 microbiome information. The results may lead to a newer approach to the genetic evaluation program of swine.

Genomic Breeding Values for Claw Diseases/Disorders in Czech Holstein Cows

Genomic breeding values (GEBV) were predicted for claw diseases/disorders in Holstein cows. The data sets included 6,498, 6,641 and 16,208 cows for the three groups of analysed disorders. The analysed traits were infectious diseases (ID), including digital and interdigital dermatitis and interdigital phlegmon, and non-infectious diseases (NID), including ulcers, white line disease, horn fissures, and double sole and overall claw disease (OCD), comprising all recorded disorders. Claw diseases/disorders were defined as 0/1 occurrence per lactation. Linear animal models were employed for prediction of conventional breeding values (BV) and genomic breeding values (GEBV), including the random additive genetic effect of animal and the permanent environmental effect of cow and fixed effects of parity, herd, year and month of calving. Both high and intermediate weights (80% and 50%, respectively) of genomic information were employed for GEBV50 and GEBV80 prediction. The estimated heritability for ID was 3.47%, whereas that for NID 4.61% and for OCD was 2.29%. Approximate genetic correlations among claw diseases/disorders traits ranged from 19% (ID x NID) to 81% (NID x OCD). The correlations between predicted BV and GEBV50 (84–99%) were higher than those between BV and GEBV80 (70–98%). Reliability of breeding values was low for each claw disease/disorder (on average, 3.7 to 14.8%) and increased with the weight of genomic information employed.