Short communication: Genetic parameters of production traits in Chinese Holsteins using a random regression test-day model

The objective of this study was to estimate genetic parameters of production traits in the first 3 parities in Chinese Holsteins. Data were a random sample of complete herds (109,005 test-day records of 9,706 cows from 54 herds) extracted from the original data set, which included 362,304 test-day records of 30,942 Holstein cows from 105 herds. A test-day animal model with multiple-trait random regression and the Gibbs sampling method were used for parameter estimation. Regression curves were modeled using Legendre polynomials of order 4. The multiple-trait analysis included milk, fat, and protein yield, and somatic cell score (SCS). Average daily heritabilities ranged between 0.222 and 0.346 for the yield traits and between 0.092 and 0.187 for SCS. Heritabilities were higher in the third lactation for all traits. Within-parity genetic correlations were very high among the yield traits (>0.806) and were close to zero between SCS and yield traits, especially for first-parity cows. Results were similar to previous literature estimates from studies that used the same model as applied to this study. The estimates found in this study will be used to perform breeding value estimation for national genetic evaluations in Chinese Holsteins.     

Changing definition of productive life in US Holsteins: effect on genetic correlations

Data included 392,800 records for cows born between 1995 and 1997. Traits analyzed were milk, fat, and protein yields, somatic cell score, days open (DO), 18 linear type traits, final score, and several measures of longevity. Productive life (PL) was defined as the total number of days in milk up to 84 mo of age with a restriction of 305, 500, or 999 d per lactation (PL(305), PL(500), or PL(999), respectively). Herd life was defined as the total number of days from the first calving date to the last (culling) date. A multiple-trait sire model including the effects of registration status, herd-year, age group, month of calving and stage of lactation, sire, and residual was used for parameter estimation. The average duration of the first lactation was 365 d for survivors and 386 d for culled cows. Lactation lengths for the survivors in the next 3 parities all exceeded 330 d. Heritability estimates of between 0.08 and 0.10 were obtained for all definitions of longevity. As maximum recordable PL was increased from 305 to 999 d per lactation, the genetic correlations with milk production increased (from -0.11 to +0.14) and with DO decreased (-0.62 to -0.27). Formulas for an indirect prediction of PL from correlated traits were developed. As maximum PL per lactation was increased, little change in the weights used to predict the various measures of PL, with the exception of DO was found. As the currently used value of PL(305) does not properly account for the longer lactation lengths that are routinely occurring with today's cows, PL with longer lactations may be preferable in routine evaluation.     

Short communication: Single-step genomic evaluation of milk production traits using multiple-trait random regression model in Chinese Holsteins

The objectives of this study were to evaluate the prediction performance of the single-step genomic BLUP method using a multi-trait random regression model in genomic evaluation for milk production traits of Chinese Holsteins, and investigate how parameters w, τ, and ω used in the construction of the combined relationship matrix (H) affected prediction accuracy and bias. A total of 2.8 million test-day records from 0.2 million cows were available for milk, protein, and fat yields. Pedigree information included 0.3 million animals and 7,577 of them were genotyped with medium-density single nucleotide polymorphism marker panels. Genotypes were imputed into Geneseek Genomic Profiler HD (GeneSeek, Lincoln, NE) including 77K markers. A reduced data set for evaluating models was extracted from the full data set by removing test-day records from the last 4 yr. Bull and cow validation populations were constructed for each trait. We evaluated the prediction performance of the multiple-trait multiple-lactation random regression single-step genomic BLUP (RR-ssGBLUP) models with different values of parameters w, τ, and ω in the H matrix, taking consideration of inbreeding. We compared RR-ssGBLUP with the multiple-trait multiple-lactation random regression model based on pedigree and genomic BLUP. De-regressed proofs for 305-d milk, protein, and fat yields averaged over 3 lactations, which were calculated from the full data set, were used for posteriori validations. The results showed that RR-ssGBLUP was feasible for implementation in breeding practice, and its prediction performance was superior to the other 2 methods in the comparison, including prediction accuracy and unbiasedness. For bulls, RR-ssGBLUP models with $w_{0.05}{\tau }_{2.0}{\omega }_{1.0},w_{0.05}{\tau }_{2.5}{\omega }_{1.0},$ and $w_{0.1}{\tau }_{1.6}{\omega }_{0.4}$ achieved the best performance for milk, protein, and fat yields, respectively. For cows, the RR-ssGBLUP with $w_{0.2}{\tau }_{1.6}{\omega }_{0.4}$ performed the best for all 3 traits. The H matrix constructed with larger τ and smaller ω gave better convergence in solving mixed model equations. Among different RR-ssGBLUP models, the differences in validation accuracy were small. However, the regression coefficient indicating prediction bias varied substantially. The increase of w and τ, and decrease of ω, led to an increase in the regression coefficient. The results demonstrated RR-ssGBLUP is a good alternative to the multi-step approach, but the optimal choice of parameters should be found via preliminary validation study to achieve the best performance.     

Genetic (co-)variation of methane emissions,efficiency, and production traits in Danish Holstein cattle along and across lactations

Methane emissions in ruminant livestock has become a hot topic, given the pressure to reduce greenhouse gas emissions drastically in the European Union over the next 10 to 30 yr. During the 2021 United Nations Climate Change conference, countries also made collective commitments to curb methane emissions by 2050. Genetic selection for low-methane-emitting animals, particularly dairy cows, is one possible strategy for mitigation. However, it is essential to understand how methane emissions in lactating animals vary along lactation and across lactations. This understanding is useful when making decisions for future phenotyping strategies, such as the frequency and duration of phenotyping within and across lactations. Therefore, the objectives of this study were to estimate (1) genetic parameters for 2 methane traits: methane concentration (MeC) and methane production (MeP) at 2 parity levels in Danish Holstein cows across the entire lactation using random regression models; (2) genetic correlations within and between methane traits across the entire lactation; and (3) genetic correlations between the methane traits and economically important traits throughout first lactation. Methane concentration (n = 19,639) records of 575 Danish Holstein cows from a research farm measured between 2013 and 2020 were available. Subsequently, CH₄ production in grams/day (MeP; n = 13,866) was calculated; MeP and MeC for first and second lactation (L1 and L2) were analyzed as separate traits: MeC_L1, MeP_L1, MeC_L2, and MeP_L2. Heritabilities, variance components, and genetic correlations within and between the 4 CH₄ traits were estimated using random regression models with Legendre polynomials. The additive genetic and permanent environmental effects were modeled using second-order Legendre polynomial for lactation weeks. Estimated heritabilities for MeP_L1 ranged between 0.11 and 0.49, for MeC_L1 between 0.10 and 0.28, for MeP_L2 between 0.14 and 0.36, and for MeC_L2 between 0.13 and 0.29. In general, heritability estimates of MeC traits were lower and more stable throughout lactation and were similar between lactations compared with MeP. Genetic correlations (within trait) at different lactation weeks were generally highly positive (0.7) for most of the first lactation, except for the correlation of early lactation (<10 wk) with late lactation (>40 wk) where the correlation was the lowest (<0.5). Genetic correlations between methane traits were moderate to highly correlated during early and mid lactation. Finally, MeP_L1 has stronger genetic correlations with energy-corrected milk and dry matter intake compared with MeC_L1. In conclusion, both traits are different along (and across) lactation(s) and they correlated differently with production, maintenance, and intake traits, which is important to consider when including one of them in a future breeding objective.     

Heritabilities and correlations among body condition score,dairy form and selected linear type traits

The objectives of this study were to estimate the heritability of body condition score (BCS) with data that could be used to generate genetic evaluations for BCS in the US, and to estimate the relationship among BCS, dairy form and selected type traits. Body condition score and linear type trait records were obtained from Holstein Association USA Inc. Because BCS was a new trait for classifiers, scoring distribution and accuracy was not normal. Records from 11 of 29 classifiers were eliminated to generate a data set that should represent BCS data recorded in the future. Edited data included 128,478 records for analysis of first lactation cows and 207,149 records for analysis of all cows. Heritabilities and correlations were estimated with ASREML using sire models. Models included age at calving nested within lactation, 5th order polynomials of DIM, fixed herd-classification visit effects and random sire and error. Genetic correlation estimates were generated between first lactation data that had records from 11 classifiers removed and data with no classifiers removed. Genetic correlation estimates were 0.995 and above between data with and without classifiers removed for scoring distributions, but heritability estimates were higher with the classifiers edited from the data. Heritability estimates for type traits and final score were similar to previously reported estimates. The heritability estimate for BCS was 0.19 for first lactation cows and 0.22 for all cows. The genetic correlation estimate for first lactation cows between BCS and dairy form was -0.73, whereas the genetic correlation estimate between BCS and strength was 0.72. Genetic correlation estimates were nearly identical when cows from all lactations were included in the analyses. Body condition score had a genetic correlation with final score closer to zero (0.08) than correlations of final score with dairy form, stature or strength.     

Genetic analysis of production traits and body size measurements and their relationships with metabolic diseases in German Holstein cattle

This study sheds light on the genetic complexity and interplay of production, body size, and metabolic health in dairy cattle. Phenotypes for body size-related traits from conformation classification (130,166 animals) and production (101,562 animals) of primiparous German Holstein cows were available. Additionally, 21,992, 16,641, and 7,096 animals were from herds with recordings of the metabolic diseases ketosis, displaced abomasum, and milk fever in first, second, and third lactation. Moreover, all animals were genotyped. Heritabilities of traits and genetic correlations between all traits were estimated and GWAS were performed. Heritability was between 0.240 and 0.333 for production and between 0.149 and 0.368 for body size traits. Metabolic diseases were lowly heritable, with estimates ranging from 0.011 to 0.029 in primiparous cows, from 0.008 to 0.031 in second lactation, and from 0.037 to 0.052 in third lactation. Production was found to have negative genetic correlations with body condition score (BCS; ?0.279 to ?0.343) and udder depth (?0.348 to ?0.419). Positive correlations were observed for production and body depth (0.138–0.228), dairy character (DCH) (0.334–0.422), and stature (STAT) (0.084–0.158). In first parity cows, metabolic disease traits were unfavorably correlated with production, with genetic correlations varying from 0.111 to 0.224, implying that higher yielding cows have more metabolic problems. Genetic correlations of disease traits in second and third lactation with production in primiparous cows were low to moderate and in most cases unfavorable. While BCS was negatively correlated with metabolic diseases (?0.255 to ?0.470), positive correlations were found between disease traits and DCH (0.269–0.469) as well as STAT (0.172–0.242). Thus, the results indicate that larger and sharper animals with low BCS are more susceptible to metabolic disorders. Genome-wide association studies revealed several significantly associated SNPs for production and conformation traits, confirming previous findings from literature. Moreover, for production and conformation traits, shared significant signals on Bos taurus autosome (BTA) 5 (88.36 Mb) and BTA 6 (86.40 to 87.27 Mb) were found, implying pleiotropy. Additionally, significant SNPs were observed for metabolic diseases on BTA 3, 10, 14, 17, and 26 in first lactation and on BTA 2, 6, 8, 17, and 23 in third lactation. Overall, this study provides important insights into the genetic basis and interrelations of relevant traits in today's Holstein cattle breeding programs, and findings may help to improve selection decisions.     

Genetic parameters for body condition score and its relationship with type and production traits in Swiss Holsteins

The objectives of this study were to estimate the genetic and environmental parameters between body condition score (BCS) and 27 conformation and 3 production traits in Swiss Holstein cattle. The dataset consisted of 31,500 first-lactation cows, which were daughters of 545 sires in 1867 herds. Bivariate sire models with relationships among sires were used to estimate parameters. Least squares means for BCS by lactation stage show that cows lose BCS up to 5 mo after calving and gain BCS prior to the next calving. Regression models showed that an increase in age and percentage of Holstein genes results in an increase and decrease in BCS, respectively. Heritability (h2) was 0.24 for BCS score, which indicates good potential for selection. Sire estimated breeding values for BCS ranged from -0.46 to +0.51 units. Heritabilities ranged from 0.08 (heel depth) to 0.46 (rump width) for type traits and 0.23 to 0.29 for yield traits. Genetic correlations of BCS with 8 conformation traits were significant; stature (0.28), heart girth (0.21), strength (0.17), loin (-0.39), body capacity (0.19), dairy character (-0.35), udder quality (-0.42), and teat position rear (-0.33). Milk production and body condition have an unfavorable genetic correlation (-0.12 to -0.17). These results show that selection for good body condition, body conformation, and optimal milk production is possible and their genetic associations reported here will be useful for designing Swiss breeding goals.     

Genetic analysis of milk urea concentration and its genetic relationship with selected traits of interest in dairy cows

The aim of this study was to estimate genetic parameters of milk urea concentration (MU) and its genetic correlations with milk production traits, longevity, and functional traits in the first 3 parities in dairy cows. The edited data set consisted in 9,107,349 MU test-day records from the first 3 parities of 560,739 cows in 2,356 herds collected during the years 1994 to 2020. To estimate the genetic parameters of MU, data of 109 randomly selected herds, with a total of 770,016 MU test-day records, were used. Genetic parameters and estimated breeding values were estimated using a multiple-trait (parity) random regression model. Herd-test-day, age-year-season of calving, and days in milk classes (every 5 d as a class) were used as fixed effects, whereas effects of herd-year of calving, permanent environment, and animal were modeled using random regressions and Legendre polynomials of order 2. The average daily heritability and repeatability of MU during days in milk 5 to 365 in the first 3 parities were 0.19, 0.22, 0.20, and 0.48, 0.48, 0.47, respectively. The mean genetic correlation estimated among MU in the first 3 parities ranged from 0.96 to 0.97. The average daily estimated breeding values for MU of the selected bulls (n = 1,900) ranged from −9.09 to 7.37 mg/dL. In the last 10 yr, the genetic trend of MU has gradually increased. The genetic correlation between MU and 11 traits of interest ranged from –0.28 (milk yield) to 0.28 (somatic cell score). The findings of this study can be used as the first step for development of a routine genetic evaluation for MU and its inclusion into the genetic selection program in the Walloon Region of Belgium.     

Genetic correlations of mid-infrared-predicted milk fatty acid groups with milk production traits

The objective of this research was to estimate the genetic correlations between milk mid-infrared-predicted fatty acid groups and production traits in first-parity Canadian Holsteins. Contents of short-chain, medium-chain, long-chain, saturated, and unsaturated fatty acid groupings in milk samples can be predicted using mid-infrared spectral data for cows enrolled in milk recording programs. Predicted fatty acid group contents were obtained for 49,127 test-day milk samples from 10,029 first-parity Holstein cows in 810 herds. Milk yield, fat and protein yield, fat and protein percentage, fat-to-protein ratio, and somatic cell score were also available for these test days. Genetic parameters were estimated for the fatty acid groups and production traits using multiple-trait random regression test day models by Bayesian methods via Gibbs sampling. Three separate 8- or 9-trait analyses were performed, including the 5 fatty acid groups with different combinations of the production traits. Posterior standard deviations ranged from <0.001 to 0.01. Average daily genetic correlations were negative and similar to each other for the fatty acid groups with milk yield (?0.62 to ?0.59) and with protein yield (?0.32 to ?0.25). Weak and positive average daily genetic correlations were found between somatic cell score and the fatty acid groups (from 0.25 to 0.36). Stronger genetic correlations with fat yield, fat and protein percentage, and fat-to-protein ratio were found with medium-chain and saturated fatty acid groups compared with those with long-chain and unsaturated fatty acid groups. Genetic correlations were very strong between the fatty acid groups and fat percentage, ranging between 0.88 for unsaturated and 0.99 for saturated fatty acids. Daily genetic correlations from 5 to 305 d in milk with milk, protein yield and percentage, and somatic cell score traits showed similar patterns for all fatty acid groups. The daily genetic correlations with fat yield at the beginning of lactation were decreasing for long-chain and unsaturated fatty acid groups and increasing for short-chain fatty acids. Genetic correlations between fat percentage and fatty acids were increasing at the beginning of lactation for short- and medium-chain and saturated fatty acids, but slightly decreasing for long-chain and unsaturated fatty acid groups. These results can be used in defining fatty acid traits and breeding objectives.     

Genetic parameters for a multiple-trait multiple-lactation random regression test-day model in Italian Holsteins

The objectives of this study were to estimate variance components for test-day milk, fat, and protein yields and average daily SCS in 3 subsets of Italian Holsteins using a multiple-trait, multiple-lactation random regression test-day animal model and to determine whether a genetic heterogeneous variance adjustment was necessary. Data were test-day yields of milk, fat, and protein and SCS (on a log₂ scale) from the first 3 lactations of Italian Holsteins collected from 1992 to 2002. The 3 subsets of data included 1) a random sample of Holsteins from all herds in Italy, 2) a random sample of Holsteins from herds using a minimum of 75% foreign sires, and 3) a random sample of Holsteins from herds using a maximum of 25% foreign sires. Estimations of variances and covariances for this model were achieved by Bayesian methods using the Gibbs sampler. Estimated 305-d genetic, permanent environmental, and residual variance was higher in herds using a minimum of 75% foreign sires compared with herds using a maximum of 25% foreign sires. Estimated average daily heritability of milk, fat, and protein yields did not differ among subsets. Heritability of SCS in the first lactation differed slightly among subsets and was estimated to be the highest in herds with a maximum of 25% foreign sire use (0.19 ± 0.01). Genetic correlations across lactations for milk, fat, and protein yields were similar among subsets. Genetic correlations across lactations for SCS were 0.03 to 0.08 higher in herds using a minimum of 75% or a maximum of 25% foreign sires, compared with herds randomly sampled from the entire population. Results indicate that adjustment for heterogeneous variance at the genetic level based on the percentage of foreign sire use should not be necessary with a multiple-trait random regression test-day animal model in Italy.     

Genetic and phenotypic relationships among endocrine and traditional fertility traits and production traits in Holstein-Friesian dairy cows

The objective of this study was to estimate the heritability of a number of traditional and endocrine fertility traits in addition to d-56 predicted milk yield (MY56), and the genetic and phenotypic correlations between these traits. Various fixed effects such as season, year, herd, lactation number, diet, percentage Holstein (PCH) of the cow, and occurrence of uterine infection (UI), dystocia (DYS), and retained placenta (RP) were also investigated. Data collected for 1212 lactations of 1080 postpartum (PP) Holstein-Friesian dairy cows in eight commercial farms between 1996 and 1999 included thrice weekly milk progesterone samples, calving and insemination dates, various reproductive health records, monthly/bimonthly production records, three-generation pedigrees, and PCH information. Genetic models were fitted to the data to obtain heritabilitites and correlations using ASREML. Estimates of heritability for interval to commencement of luteal activity PP (lnCLA), length of the first luteal phase PP (lnLutI) and occurrence of persistent CL type I (PCLI) were 0.16, 0.17, and 0.13, respectively. Heritabilities for pregnancy to first service (PFS), interval to first service (IFS), and MY56 were 0.14, 0.13, and 0.50, respectively. Genetic regressions of lnCLA and lnLutI on PTA of the sire for milk, fat, and protein yields, and PIN95 were investigated. Regressions of lnCLA were positive and significant on fat yield, while regressions of lnLutI on both protein yield and PIN95 were negative and significant. Genetic correlations of endocrine fertility traits (lnCLA, lnLutI, and PCLI) with MY56 were high (0.36, P < 0.05; -0.51, P < 0.05; and -0.31, P < 0.1, respectively). Percentage Holstein of the cows had no significant effect on any of the fertility parameters monitored. This work emphasizes the strong genetic correlation of fertility with production traits and, therefore, highlights the urgent requirement for selective breeding for fertility in the United Kingdom. The high heritability of endocrine fertility traits stress their potential value for inclusion in a selection index to improve fertility.     

Phenotypic and genetic variability of production traits and milk fatty acid contents across days in milk for Walloon Holstein first-parity cows

The objective of this study was to assess the phenotypic and genetic variability of production traits and milk fatty acid (FA) contents throughout lactation. Genetic parameters for milk, fat, and protein yields, fat and protein contents, and 19 groups and individual FA contents in milk were estimated for first-parity Holstein cows in the Walloon Region of Belgium using single-trait, test-day animal models and random regressions. Data included 130,285 records from 26,166 cows in 531 herds. Heritabilities indicated that de novo synthesized FA were under stronger genetic control than FA originating from the diet and from body fat mobilization. Estimates for saturated short- and medium-chain individual FA ranged from 0.35 for C4:0 to 0.44 for C8:0, whereas those for monounsaturated long-chain individual FA were lower (around 0.18). Moreover, de novo synthesized FA were more heritable in mid to late lactation. Approximate daily genetic correlations among traits were calculated as correlations between daily breeding values for days in milk between 5 and 305. Averaged daily genetic correlations between milk yield and FA contents did not vary strongly among FA (around −0.35) but they varied strongly across days in milk, especially in early lactation. Results indicate that cows selected for high milk yield in early lactation would have lower de novo synthesized FA contents in milk but a slightly higher content of C18:1 cis-9, indicating that such cows might mobilize body fat reserves. Genetic correlations among FA emphasized the combination of FA according to their origin: contents in milk of de novo FA were highly correlated with each other (from 0.64 to 0.99). Results also showed that genetic correlations between C18:1 cis-9 and other FA varied strongly during the first 100 d in milk and reinforced the statement that the release of long-chain FA inhibits FA synthesis in the mammary gland while the cow is in negative energy balance. Finally, results showed that the FA profile in milk changed during the lactation phenotypically and genetically, emphasizing the relationship between the physiological status of cow and milk composition.     

Estimation of genetic parameters for productive life,reproduction, and milk-production traits in US dairy goats

Heritabilities and correlations for milk yield (MY), fat yield (FY), protein yield (PY), combined fat and protein yield (FPY), fat percentage (F%), protein percentage (P%), age at first kidding (AFK), interval between the first and second kidding (KI), and real and functional productive life at 72 mo (FPL72) of 33,725 US dairy goats, were estimated using animal models. Productive life was defined as the total days in production until 72 mo of age (PL72) for goats having the opportunity to express the trait. Functional productive life was obtained by correcting PL72 for MY, FY, PY, and final type score (FS). Six selection indexes were used, including or excluding PL72, with 6 groups of different economic weights, to estimate the responses to selection considering MY, FY, PY, and PL72 as selection criteria. The main criteria that determined the culling of a goat from the herd were low FS, MY, and FY per lactation. Heritability estimates were 0.22, 0.17, 0.37, 0.37, 0.38, 0.39, 0.54, 0.64, 0.09, and 0.16 for PL72, FPL72, MY, FY, PY, FPY, F%, P%, KI, and AFK, respectively. Most genetic correlations between the evaluated traits and PL72 or FPL72 were positive, except for F% (−0.04 and −0.06, respectively), P% (−0.002 and −0.03, respectively), and AFK (−0.03 and −0.01, respectively). The highest genetic correlations were between FPL72 and MY (0.39) and between PL72 and MY (0.33). Most phenotypic correlations between the traits evaluated and FPL72 and PL72 were positive (>0.23 and >0.26, respectively), except for F% (−0.004 and −0.02, respectively), P% (−0.05 and −0.02), KI (−0.01 and −0.07), and AFK (−0.08 and −0.08). The direct selection for PL72 increased it by 102.28 d per generation. The use of MY, FY, PY, KI, or AFK as selection criteria increased PL72 by 39.21, 27.33, 35.90, −8.28, or 2.77 d per generation, respectively. The inclusion of PL72 as selection criterion increased the expected response per generation from 0.15 to 17.35% in all selection indices studied.     

Analysis of age-specific predicted transmitting abilities for final scores in Holsteins with a random regression model

Conformation final scores obtained by the Holstein Association were used in this study. Five subsets were sampled from the original complete data, which contained about 7 million records, and (co)variance components for additive genetic, permanent environmental, and residual effects were estimated with a multiple-trait (MT) model at different ages of cows and with a random regression model. Transmitting abilities were predicted with the random-regression (RR) model and with the repeatability model for the national evaluation, using the entire data set. The RR model included fixed and random regressions on age at classification for additive genetic and permanent environmental effects. Additive genetic and residual variances estimated with the MT model increased with aging. Genetic correlations between age groups decreased with their distance. Heritability and repeatability estimates with the RR model were 0.27 and 0.88 on average, increasing with cow's age. Correlations between transmitting abilities predicted with the RR model at various ages and with the repeatability model were in the range of 0.89 to 0.99. In the 1980s, predicted transmitting abilities (PTA) of sires increased with their daughters' age, but in 1991 and 1995, the PTA decreased. In general, sires whose daughters were evaluated at mature ages tended to have higher PTA. For sires and cows, genetic trends estimated from the repeatability model and from the RR model were similar. The low genetic trend of cows at 60 mo for recent years was due to many grade cows that had only single records and little pedigree information.     

Genetic line comparisons and genetic parameters for endoparasite infections and test-day milk production traits

Keeping dairy cows in grassland systems relies on detailed analyses of genetic resistance against endoparasite infections, including between- and within-breed genetic evaluations. The objectives of this study were (1) to compare different Black and White dairy cattle selection lines for endoparasite infections and (2) the estimation of genetic (co)variance components for endoparasite and test-day milk production traits within the Black and White cattle population. A total of 2,006 fecal samples were taken during 2 farm visits in summer and autumn 2015 from 1,166 cows kept in 17 small- and medium-scale organic and conventional German grassland farms. Fecal egg counts were determined for gastrointestinal nematodes (FEC-GIN) and flukes (FEC-FLU), and fecal larvae counts for the bovine lungworm Dictyocaulus viviparus (FLC-DV). The lowest values for gastrointestinal nematode infections were identified for genetic lines adopted to pasture-based production systems, especially selection lines from New Zealand. Heritabilities were low for FEC-GIN (0.05–0.06 ± 0.04) and FLC-DV (0.05 ± 0.04), but moderate for FEC-FLU (0.33 ± 0.06). Almost identical heritabilities were estimated for different endoparasite trait transformations (log-transformation, square root). The genetic correlation between FEC-GIN and FLC-DV was 1.00 ± 0.60, slightly negative between FEC-GIN and FEC-FLU (?0.10 ± 0.27), and close to zero between FLC-DV and FEC-FLU (0.03 ± 0.30). Random regression test-day models on a continuous time scale [days in milk (DIM)] were applied to estimate genetic relationships between endoparasite and longitudinal test-day production traits. Genetic correlations were negative between FEC-GIN and milk yield (MY) until DIM 85, and between FEC-FLU and MY until DIM 215. Genetic correlations between FLC-DV and MY were negative throughout lactation, indicating improved disease resistance for high-productivity cows. Genetic relationships between FEC-GIN and FEC-FLU with milk protein content were negative for all DIM. Apart from the very early and very late lactation stage, genetic correlations between FEC-GIN and milk fat content were negative, whereas they were positive for FEC-FLU. Genetic correlations between FEC-GIN and somatic cell score were positive, indicating similar genetic mechanisms for susceptibility to udder and endoparasite infections. The moderate heritabilities for FEC-FLU suggest inclusion of FEC-FLU into overall organic dairy cattle breeding goals to achieve long-term selection response for disease resistance.     

Intercorrelations among milk production traits and body and udder measurements in Holstein heifers

Data from 1341 Holstein heifers of 71 sires were used to study heritabilities of and genetic and phenotypic correlations among milk production traits (308-d milk, front and rear half yields), body measurements (heart girth, withers height, body length, and rump length), udder measurements (front teat length and diameter, rear teat length and diameter, teat distance and udder height), and age at first calving. Genetic and phenotypic parameters were estimated by the multitrait restricted maximum likelihood method. Multitrait estimates of heritability ranged from .37 to .47 for first lactation yield traits, from .19 to .51 for body measurements, and from .08 to .41 for udder measurements. Age at first calving averaged 22.3 mo with a heritability estimate of .11. Milk production traits were all positively correlated with body measurements, suggesting that high producing heifers would be taller, larger, and longer than low producing heifers. Multitrait estimates of genetic and phenotypic correlations between udder height and yield traits were all negative, suggesting that high producing heifers tend to have lower udders. Of four body measurements studied, rump length showed the greatest genetic correlations with yield traits. Among six udder measurements, udder height exhibited the highest degree of associations with yield traits. Thus, rump length and udder height merit greater attention for prediction of lactational performance.     

Estimated genetic parameters for all genetically evaluated traits in Canadian Holsteins

Genetic improvement is a crucial tool to deal with the increasing demand for high quality, sustainably produced dairy. Breeding programs are based on genetic parameters, such as heritability and genetic correlations, for economically important traits in a population. In this study, we estimated population genetic parameters and genetic trends for 67 traits evaluated on heifers and first-lactation Canadian Holstein cows. The data consisted of approximately 500,000 records with pedigree information collected from 1980 to 2019. Genetic parameters were estimated using bivariate linear animal models under a Bayesian approach. Analyses for the 67 traits resulted in 2,211 bivariate combinations, from which the estimated genetic parameters are reported here. The most highly heritable traits were fat percent (0.66) and protein percent (0.69), followed by stature (0.47). Lowest heritabilities (0.01) were observed for disease-related traits, such as lameness and toe ulcer, and calf survival. The genetic correlations between gestation length, calf size, and calving ease measured on both heifer and cows were close to unity. On the other hand, traits such as body condition score and pin width, cystic ovaries and sole ulcer, rear teat placement, and toe ulcer were genetically unrelated. This study reports genetic parameters that have not been previously published for Canadian Holstein cows, and provides updates of those previously estimated. These estimates are useful for building new indexes, updating existing selection indexes, and for predicting correlated responses due to inclusion of novel traits in the breeding programs.     

Genetic and environmental relationships between body condition score and milk production traits in Canadian Holsteins

The objective of this research was to estimate genetic parameters of first-lactation body condition score (BCS), milk yield, fat percentage (Fat%), protein percentage (Prot%), somatic cell score (SCS), milk urea nitrogen (MUN), lactose percentage (Lact%), and fat to protein ratio (F:P) using multiple-trait random regression animal models. Changes in covariances between BCS and milk production traits on a daily basis have not been investigated before and could be useful for determining which BCS estimated breeding values (EBV) might be practical for selection in the future. Field staff from Valacta milk recording agency (Sainte-Anne-de-Bellevue, QC, Canada) collected BCS from Québec herds several times per cow throughout the lactation. Average daily heritabilities and genetic correlations among the various traits were similar to literature values. On an average daily basis, BCS was genetically unfavorably correlated with milk yield (i.e., increased milk yield was associated with lower body condition). The unfavorable genetic correlation between BCS and milk yield became stronger as lactation progressed, but was equivalent to zero for the first month of lactation. Favorable genetic correlations were found between BCS with Prot%, SCS, and Lact% (i.e., greater BCS was associated with greater Prot%, lower SCS, and greater Lact%). These correlations were strongest in early lactation. On an average daily basis, BCS was not genetically correlated with Fat% or MUN, but was negatively correlated with F:P. Furthermore, BCS at 5 and 50 d in milk (DIM) had the most favorable genetic correlations with milk production traits over the lactation (at 5, 50, 150, and 250 DIM). Thus, early lactation BCS EBV shows potential for selection. Regardless, this study showed that the level of association BCS has with milk production traits is not constant over the lactation. Simultaneous selection for both BCS and milk production traits should be considered, mainly due to the unfavorable genetic correlation between BCS with milk yield.     

Genetic variation of Mycobacterium avium ssp. paratuberculosis infection in US Holsteins

The objective of this study was to estimate genetic variability of Mycobacterium avium ssp. paratuberculosis infection in US Holsteins. Blood and fecal samples were collected primarily from daughters of 12 bulls in their second or third lactation. Routine disease testing of the sires documented that they were not infected. Herds without a “suspect” or positive ELISA (sample/positive ratio ≥ 0.10) or positive fecal culture test were deleted from the data set. The remaining 4,603 cows from 238 herds and 46 sires were used to estimate heritability of M. paratuberculosis infection. Heritability was estimated with 3 Johne's disease diagnostic tests: 1) fecal culture alone, 2) serum antibody ELISA alone, and 3) both tests (combined) with a positive animal defined as all animals with either a positive fecal culture or ELISA test. Four statistical models were used to estimate heritability: 1) linear (ELISA), 2) threshold (fecal culture and combined), 3) ordered threshold (ELISA), and 4) bivariate linear-threshold (ELISA-fecal culture). A sire model and Bayesian approach using Markov chain Monte Carlo methods were used in each case. Heritability of infection based on the fecal culture test was 0.153 [posterior standard deviation (PSD) = 0.115]. Heritability with the ELISA was 0.159 (PSD = 0.090) with a linear model and 0.091 (PSD = 0.053) with an ordered threshold model. Heritability of the combined tests was 0.102 (PSD = 0.066). Heritability estimates of fecal culture and ELISA with the bivariate model varied slightly from estimates obtained with the univariate models (0.125 and 0.183, respectively), with a corresponding increase in precision (PSD = 0.096 and 0.082, respectively). This study demonstrates that exploitable genetic variation exists in dairy cattle for M. paratuberculosis infection susceptibility.     

Genetic and environmental parameters for milk production, udder health, and fertility traits in Mexican Holstein cows

Genetic and phenotypic parameters for Mexican Holstein cows were estimated for first- to third-parity cows with records from 1998 to 2003 (n = 2,971-15,927) for 305-d mature equivalent milk production (MEM), fat production (MEF), and protein production (MEP), somatic cell score (SCS), subsequent calving interval (CAI), and age at first calving (AFC). Genetic parameters were obtained by average information matrix-REML methodology using 6-trait (first-parity data) and 5-trait (second- and third-parity data) animal models. Heritability estimates for production traits were between 0.17 ± 0.02 and 0.23 ± 0.02 for first- and second-parity cows and between 0.12 ± 0.03 and 0.13 ± 0.03 for third-parity cows. Heritability estimates for SCS were similar for all parities (0.10 ± 0.02 to 0.11 ± 0.03). For CAI, estimates of heritability were 0.01 ± 0.05 for third-parity cows and 0.02 ± 0.02 for second-parity cows. The heritability for AFC was moderate (0.28 ± 0.03). No unfavorable estimates of correlations were found among MEM, MEF, MEP, CAI, and SCS. Estimates of environmental and phenotypic correlations were large and positive among production traits; favorable between SCS and CAI; slightly favorable between MEM, MEF, and MEP and SCS, between AFC and SCS, and between SCS and CAI; and small but unfavorable between production traits and CAI. Estimates of genetic variation and heritability indicate that selection would result in genetic improvement of production traits, AFC, and SCS. Estimates of both heritability and genetic variation for CAI were small, which indicates that genetic improvement would be difficult.