Repeatability Animal Model Research Articles

Genetic relationships between male and female reproductive traits in Retinta beef cattle

Scrotal circumference (SC) is an indirect measure used to predict the reproductive fitness of beef cattle raised in an extensive regime with limited seasonal breeding. It stands out for having a moderate to high heritability and favorable correlations, with seminal and reproductive quality traits in both the bull and its daughters. In the present study, we analyzed 2,634 SC records of young bulls evaluated in testing stations for future bulls of the Retinta cattle Breed. The data was collected from 828 young bulls which produced 3,616 daughters. Monthly measurements of live weight, average daily gain, feed consumption, and SC were also performed in the bulls during testing. In addition, reproductive controls were performed in the daughters to estimate age at first calving (AFC) and reproductive efficiency (RE). We also estimated genetic parameters for the traits using a classical REML repeatability animal model. Average SC was 34.04 ± 2.43 cm. at 12 months, showing a heritability of 0.282 ± 0.052. Phenotypic (-0.05, 0.11, 0.42) and genetic (0.12, 0.15, -0.09) correlations were obtained between AFC and Reproductive Efficiency (RE) at 3, 6, and last calving and SC. These results suggest a strong environmental influence on the reproductive variables of daughters, probably motivated by the breeding model and the farmer's decision on the date of reproduction of the heifers. However, it can be seen that the AFC, RE3 and RE6 are more favorable for individuals with SC >37 cm, and more unfavorable for SC ≤32 in relation to SC >32 and ≤37. Finally, 85 of the bulls underwent sperm analysis using computer-assisted sperm analysis (C.A.S.A.) technology, using frozen semen samples belonging to the Retinta Breeding Program. Residual phenotypes for SC showed positive correlations with progressivity (0.11 in STR and LIN) and longevity (0.2 in L40 and 0.1 in L50). The highest r2 was obtained using a canonical correlation, suggesting that a higher SC may improve sperm quality in bulls. It can therefore be confirmed that the use of this selection criterion (SC) in the breeding program of this breed will determine a response to positive selection, both for the fertility of the bull and its daughters.

Genetic analysis of daily milk weights in U.S. Holsteins using pen-based contemporary groups

The availability of daily milk weights and pen location information provides an interesting opportunity to capture additional data and review how contemporary groups are defined for dairy cattle genetic evaluations. In the US, dairy cows in larger herds are grouped into pens according to various characteristics like parity, production level, reproductive status, lactation stage, and health status. Our data set included pen location information for each daily milk weight, so instead of using herd-year-season of calving to form contemporary groups, we used herd-pen-milking date to more precisely model the environmental effects cows experience at the pen level on a given day. Our data set included 21,000,951 aggregated daily milk records from 114,243 first parity Holstein cows milked 3 times daily in conventional parlor systems in 157 herds representing 29 US states. Our phenotype of interest was daily milk weight, and alternative repeatability animal models were used to estimate genetic parameters and predict breeding values. Age at first calving (6 levels) and days in milk (10 levels) were included as fixed effects and cow (114,243 levels) was included as a random effect. Contemporary group effects included a fixed or random herd-year-season of calving effect (1,492 levels) and/or a fixed or random herd-pen-milking date effect (285,592 levels). Genetic parameters (kg2; posterior SD) were estimated using GIBBSF90+ software. The additive genetic variance ranged from 10.48 (0.60) to 24.12 (0.66), herd-year-season variance was 10.34 (0.40), herd-pen-milking date variance ranged from 4.91 (0.02) to 4.96 (0.02), permanent environmental variance ranged from 10.65 (0.44) to 16.94 (0.30), and residual variance ranged from 11.81 (0.01) to 14.60 (0.01). Heritability estimates ranged from 0.21 (0.01) to 0.47 (0.01), while repeatability estimates ranged from 0.51 (0.01) to 0.71 (0.01), and mean reliability of sires' breeding value predictions ranged from 0.81 to 0.89. Although caution is needed when disentangling associations between genetic effects, permanent environmental effects, and herd-pen-milking date contemporary groups, our results suggest that using daily milk weights and pen locations may improve the precision of genetic evaluations through increased sire PTA reliabilities for milk production traits in dairy cattle.

Genetic parameters for udder conformation traits derived from Cartesian coordinates generated by robotic milking systems in North American Holstein cattle

Udder conformation is directly related to milk yield, cow health, workability, and welfare. Automatic milking systems (AMS, also known as milking robots) have become popular worldwide, and the number of dairy farms adopting these systems has increased considerably over the past years. In each milking visit, AMS record the location of the 4 teats as Cartesian coordinates in an xyz plan, which can then be used to derive udder conformation traits. Because AMS generate a large amount of data for individual cows per milking visit, they can contribute to an accurate assessment of important traits such as udder conformation without the addition of human classifier errors (in subjective scoring systems). Therefore, the primary objectives of this study were to estimate genomic-based genetic parameters for udder conformation traits derived from AMS records in North American Holstein cattle and to assess the genetic correlation between the derived traits for evaluating the feasibility of multitrait genomic selection for breeding cows that are more suitable for milking in AMS. The Cartesian teat coordinates measured during each milking visit were collected by 36 milking robots in 4,480 Holstein cows from 2017 to 2021, resulting in 5,317,488 records. A total of 4,118 of these Holstein cows were also genotyped for 57,600 SNPs. Five udder conformation traits were derived: udder balance (UB, mm), udder depth (UD, mm), front teat distance (FTD, mm), rear teat distance (RTD, mm), and distance front-rear (DFR, mm). In addition, 2 traits directly related to cow productivity in the system were added to the study: daily milk yield (DY) and milk electroconductivity (EC; as an indicator of mastitis). Variance components and genetic parameters for UB, UD, FTD, RTD, DFR, DY, and EC were estimated based on repeatability animal models. The estimates of heritability (± SE) for UB, UD, FTD, RTD, DFR, DY, and EC were 0.41 ± 0.02, 0.79 ± 0.01, 0.53 ± 0.02, 0.40 ± 0.02, 0.65 ± 0.02, 0.20 ± 0.02, and 0.46 ± 0.02, respectively. The repeatability estimates (± SE) for UB, UD, FTD, RTD, and DFR were 0.82 ± 0.01, 0.93 ± 0.01, 0.87 ± 0.01, 0.83 ± 0.01, and 0.88 ± 0.01, respectively. The strongest genetic correlations were observed between FTD and RTD (0.54 ± 0.03), UD and DFR (-0.47 ± 0.03), DFR and FTD (0.32 ± 0.03), and UD and FTD (-0.31 ± 0.03). These results suggest that udder conformation traits derived from Cartesian coordinates from AMS are moderately to highly heritable. Furthermore, the moderate genetic correlations between these traits should be considered when developing selection subindexes. The most relevant genetic correlations between traits related to cow milk productivity and udder conformation traits were between UD and EC (-0.25 ± 0.03) and between DFR and DY (0.30 ± 0.04), in which both genetic correlations are favorable. These findings will contribute to the design of genomic selection schemes for improving udder conformation in North American Holstein cattle, especially in precision dairy farms.

Evaluation of Genetic and Non-genetic Factors Influencing Semen Production Potential in Sahiwal Bulls

Background: Understanding genetic and non-genetic factors that influence the quality and quantity of semen production plays a crucial role in determining the reproductive efficiency and genetic progress within the Sahiwal breed. The objective of this study was to assess the impact of genetic and non-genetic factors on the semen production potential of Sahiwal bulls. Methods: Semen ejaculate data, including volume (VOL), sperm concentration per milliliter (CONC), total sperm count per ejaculate (TS), initial motility (INIT) and post-thaw motility (PT), as well as semen quality traits such as hypo-osmotic swelling test (HOST) and acrosome integrity of frozen semen (AIFS), were obtained from 52 Sahiwal bulls. The data spanned from January 2011 to December 2018 and were collected at BAIF’s frozen semen station in Jind, Haryana, India. To ensure data reliability, observations beyond the mean±4 standard deviations (S.D.) were identified as outliers and subsequently excluded from the study. Two key factors, namely the season of semen collection (winter, summer and monsoon) and the age of bulls at collection (categorized into 12-month intervals ranging from less than 36 months to 156 months), were considered influential factors affecting semen characteristics. To investigate the correlation between bulls (genetic + permanent environmental correlation) and semen parameters, a repeatability animal model was employed, treating the bull as a random effect. The statistical analysis was conducted using WOMBAT software. Result: The findings revealed that the season of semen collection had a highly significant effect (P less than 0.01) on VOL, CONC, TS and PT. However, INIT, HOST and AIFS were not influenced (P greater than 0.05) by the season of collection. Furthermore, age at semen collection significantly affected all semen characteristics. VOL and TS exhibited an increasing trend until 72 to 84 months, followed by a decline until 96 to 108 months.

Genetic analysis of health traits and their associations with longevity, fertility, production, and conformation traits in Holstein cattle

Health traits have high economic values in dairy cattle breeding, which can cause considerable financial loss through involuntary culling. In this study, fourteen health traits were analysed, including five composite health traits: reproductive disorders, udder health (UH), digestive disorders, metabolic disorders, locomotory diseases (LD), and nine independent health traits: gestation disorders and peripartum disorders, irregular estrus cycle and sterility, metritis (ME), mastitis (MA), abomasal displacement (AD), enteritis (EN), and ketosis, claw diseases (CD), laminitis complex. This study analysed variance components for health traits through both single and bivariate repeatability animal models. All health traits showed low heritability, ranging from 0.001 to 0.025. Most of the health traits in five categories showed negative genetic correlations, ranging from −0.012 (CD and EN) to −0.634 (ME and EN). Strong positive genetic correlations appeared within the same category, ranging from 0.469 (EN and AD) to 0.994 (UH and MA, LD and CD). Furthermore, approximate genetic correlations were evaluated between health traits and routinely collected traits (longevity, fertility, production, and conformation). In general, the low to moderate approximate genetic correlations were estimated between health traits and routinely collected traits. The estimated correlations between health traits and longevity, fertility, production, and conformation traits could provide an indirect reference for disease−resistance breeding in Holstein cattle.

Genetic evaluations and genome-wide association studies for specific digital dermatitis diagnoses in dairy cows considering genotype × housing system interactions

The present study aimed to use detailed phenotyping for the claw disorder digital dermatitis (DD) considering specific DD stages in 2 housing systems (conventional cubicle barns [CON] and compost-bedded pack barns [CBPB]) to infer possible genotype × housing system interactions. The DD stages included 2,980 observations for the 3 traits DD-sick, DD-acute, and DD-chronic from 1,311 Holstein-Friesian and 399 Fleckvieh-Simmental cows. Selection of the 5 CBPB and 5 CON herds was based on a specific protocol to achieve a high level of herd similarity with regard to climate, feeding, milking system, and location, but with pronounced housing-system differences. Five other farms had a "mixed system" with 2 subherds, one representing CBPB and the other one CON. The CBPB system was represented by 899 cows (1,530 observations), and 811 cows (1,450 observations) represented the CON system. The average disease prevalence was 20.47% for DD-sick, 13.88% for DD-acute, and 5.34% for DD-chronic, with a higher prevalence in CON than in CBPB. After quality control of 50K genotypes, 38,495 SNPs from 926 cows remained for the ongoing genomic analyses. Genetic parameters for DD-sick, DD-acute, and DD-chronic were estimated by applying single-step approaches for single-trait repeatability animal models considering the whole dataset, and separately for the CON and CBPB subsets. Genetic correlations between same DD traits from different housing systems, and between DD-sick, DD-chronic, and DD-acute, were estimated via bivariate animal models. Heritabilities based on the whole dataset were 0.16 for DD-sick, 0.14 for DD-acute, and 0.11 for DD-chronic. A slight increase of heritabilities and genetic variances was observed in CON compared with the "well-being" CBPB system, indicating a stronger genetic differentiation of diseases in a more challenging environment. Genetic correlations between same DD traits recorded in CON or CBPB were close to 0.80, disproving obvious genotype × housing system interactions. Genetic correlations among DD-sick, DD-acute and DD-chronic ranged from 0.58 to 0.81. SNP main effects and SNP × housing system interaction effects were estimated simultaneously via GWAS, considering only the phenotypes from genotyped cows. Ongoing annotations of potential candidate genes focused on chromosomal segments 100 kb upstream and downstream from the significantly associated candidate SNP. GWAS for main effects indicated heterogeneous Manhattan plots especially for DD-acute and DD-chronic, indicating particularities in disease pathogenesis. Nevertheless, a few shared annotated potential candidate genes, that is, METTL25, AFF3, PRKG1, and TENM4 for DD-sick and DD-acute, were identified. These genes have direct or indirect effects on disease resistance or immunology. For the SNP × housing system interaction, the annotated genes ASXL1 and NOL4L on BTA 13 were relevant for DD-sick and DD-acute. Overall, the very similar genetic parameters for the same traits in different environments and negligible genotype × housing system interactions indicate only minor effects on genetic evaluations for DD due to housing-system particularities.

Phenotypic and Genetic Analyses of In Vitro Embryo Production Traits in Chinese Holstein Cattle.

Ovum pick up and in vitro embryo production (OPU-IVEP) is an essential technique in the dairy industry. The production efficiency of OPU-IVEP is significantly influenced by various factors, and phenotypic and genetic characteristics are highly variable in different populations. The objectives of this study were (1) to reveal the phenotypic characteristics, including population distribution, and impacts of donor age and month on in vitro embryo production and (2) to estimate genetic parameters for five in vitro embryo production traits in Chinese Holstein cattle. A total of 7311 OPU-IVEP records of 867 Holstein heifers from August 2021 to March 2023 were collected in this study. Five in vitro embryo production traits were defined, including the number of cumulus-oocyte complexes (NCOC), the number of cleaved embryos (NCLV), the number of grade I embryos (NGE), and the proportion of NCLV to NCOC (PCLV) and NGE to NCOC (PGE). A univariate repeatability animal model was employed to estimate heritability and repeatability, and a bivariate repeatability animal model was employed to estimate the genetic correlations among five in vitro embryo production traits. It was found that the in vitro embryo production traits were significantly influenced by season, as the NGE and PGE were significantly decreased from June to August. In addition, the production efficiency of OPU-IVEP was also influenced by donor age. On the observed scale, the estimates of heritability were 0.33 for NCOC, 0.24 for NCLV, 0.16 for NGE, 0.06 for PCLV, and 0.10 for PGE, respectively. On the log-transformed scale, the estimates of heritability of NCOC, NCLV, and NGE were 0.34, 0.18, and 0.13. The genetic correlations among NCOC, NCLV, and NGE ranged from 0.61 (NCLV and NGE) to 0.95 (NCOC and NCLV), considering both scales. However, there were low genetic correlations between NCOC and proportion traits (PCLV and PGE) on both the observed scale and the log-transformed scale. In the end, the variation in Chinese Holstein cattle was found to be considerable. The EBV value and average NCOC, NGE, and PGE for the top 10% donors presented extreme differences to those for the bottom 10% donors for NCOC (24.02 versus 2.60), NGE (3.42 versus 0.36), and PGE (30.54% versus 3.46%). Overall, the results of this study reveal that in vitro embryo production traits are heritable with low to high heritability, and the count traits (NCOC, NCLV, and NGE) and proportion traits (PCLV and PGE) reflect different aspects of in vitro embryo production and should be incorporated into genetic selection for improving the embryo production efficiency of dairy cattle.

Genetic aspects of Wood's lactation curve parameters in Jersey crossbred cattle using Bayesian approach.

The study was undertaken to estimate the genetic parameters of lactation curve parameters of Wood's function in Jersey crossbred cattle using the Bayesian approach. Data on 33,906 fortnightly test day milk yields of 1,718 lactation records of Jersey crossbred cows, maintained at the ICAR-National Dairy Research Institute in West Bengal, were collected over a period of 40 years. The lactation curve parameters including 'a' (initial milk yield after calving), 'b' (ascending slope up to peak yield) and 'c' (descending slope after peak yield) and lactation curve traits, peak yield (ymax), time of peak yield (tmax) and persistency of milk yield (P) of individual cow for each lactation were estimated using the incomplete gamma function (Wood's model) by fitting the Gauss-Newton algorithm as an iteration method using PROC NLIN procedure of SAS 9.3. Variance components and genetic parameters of lactation curve parameters/traits were estimated by a repeatability animal model using the Bayesian approach. Estimates of heritabilities were found to be 0.18 ± 0.05, 0.09 ± 0.03 and 0.11 ± 0.04 for parameters 'a', 'b' and 'c', respectively and 0.24 ± 0.05, 0.12 ± 0.04, and 0.15 ± 0.05 for ymax, tmax and P, respectively. Repeatability estimates were 0.31 ± 0.03, 0.21 ± 0.04 and 0.30 ± 0.04 for parameters 'a', 'b' and 'c' respectively and 0.39 ± 0.03, 0.24 ± 0.03 and 0.37 ± 0.03 for ymax, tmax and p, respectively. Genetic correlations among lactation curve parameters/traits ranged from -0.75 to 0.95. Existence of genetic correlations among lactation curve parameters/traits indicated substantial genetic and physiological relationships among lactation curve parameters/traits of Jersey crossbred cattle.

Genetic parameter estimates for daily predicted gross feed efficiency and its association with energy-corrected milk in South African Holstein cattle

Genetic parameters for daily predicted gross feed efficiency (pGFE) and energy corrected milk (ECM) in the first three parities of South African Holstein cattle were estimated by repeatability animal models. Data comprised of 11,068 test-day milk production records of 1,575 Holstein cows that calved between 2009 and 2019. Heritability estimates for pGFE were 0.12 ± 0.06, 0.09 ± 0.04 and 0.18 ± 0.05 in early, mid and late lactation, respectively. Estimates were moderate for primiparous (0.21 ± 0.05) and low for multiparous (0.10 ± 0.04) cows. Heritability and repeatability across all lactations were 0.14 ± 0.03 and 0.37 ± 0.03, respectively. Genetic correlations between pGFE in different stages of lactation ranged from 0.87 ± 0.24 (early and mid) to 0.97 ± 0.28 (early and late), while a strong genetic correlation (0.90 ± 0.03) was found between pGFE and ECM, across all lactations. The low to moderate heritability estimates for pGFE suggest potential for genetic improvement of the trait through selection, albeit with a modest accuracy of selection. The high genetic correlation of pGFE with ECM may, however, assist to improve accuracy of selection for feed efficiency by including both traits in multi-trait analyses. These genetic parameters may be used to estimate breeding values for pGFE, which will enable the trait to be incorporated in the breeding objective for South African Holstein cattle.

Estimation of genetic parameters for semen traits in Egyptian buffalo bulls

This study was conducted to characterize semen traits (ejaculate volume (VOL), mass motility (MM), sperm livability (LS), percentage of abnormal sperms (AS), and sperm concentration (CONC)) of Egyptian buffalo bulls and evaluate the importance of some nongenetic factors (year (YC) and season (SC) of semen collection and age of bull genetically and environmentally at collection (ABC)) affecting the investigated traits. A total of 7761 normal semen ejaculates were collected from 26 bulls from 2009 to 2019. Single-trait and bivariate repeatability animal models using Bayesian methods were used to estimate variance components, heritability, repeatability, and genetic correlations among the investigated semen traits. YC and ABC exerted significant effects on most semen traits, whereas SC exerted no significant effect on all the investigated semen traits. Heritability estimates were 0.08, 0.52, 0.51, 0.04, and 0.49 for VOL, MM, LS, AS, and CONC, respectively. Repeatability estimates were 0.14, 0.82, 0.79, 0.06, and 0.78 for VOL, MM, LS, AS, and CONC, respectively. The genetic correlations between MM and each of LS and CONC were highly significant (0.99 ± 0.01 and 0.95 ± 0.14, respectively), and that between LS and CONC was also highly significant (0.92 ± 0.20). The high heritability estimates for MM, LS, and CONC combined with the favorable high significant genetic correlations between these traits indicated that direct selection for MM may be an effective method to enhance semen quality in Egyptian buffalo bulls and consequently improve fertility.

Inbreeding depression and its effect on sperm quality traits in Pietrain pigs.

In most cases, inbreeding is expected to have unfavourable effects on traits in livestock. The consequences of inbreeding depression could be substantial, primarily in reproductive and sperm quality traits, and thus lead to decreased fertility. Therefore, the objectives of this study were (i) to compute inbreeding coefficients using pedigree (FPED ) and genomic data based on runs of homozygosity (ROH) in the genome (FROH ) of Austrian Pietrain pigs, and (ii) to assess inbreeding depression on four sperm quality traits. In total, 74,734 ejaculate records from 1034 Pietrain boars were used for inbreeding depression analyses. Traits were regressed on inbreeding coefficients using repeatability animal models. Pedigree-based inbreeding coefficients were lower than ROH-based inbreeding values. The correlations between pedigree and ROH-based inbreeding coefficients ranged from 0.186 to 0.357. Pedigree-based inbreeding affected only sperm motility while ROH-based inbreeding affected semen volume, number of spermatozoa, and motility. For example, a 1% increase in pedigree inbreeding considering 10 ancestor generations (FPED10 ) was significantly (p < 0.05) associated with a 0.231% decrease in sperm motility. Almost all estimated effects of inbreeding on the traits studied were unfavourable. It is advisable to properly manage the level of inbreeding to avoid high inbreeding depression in the future. Further, analysis of effects of inbreeding depression for other traits, including growth and litter size for the Austrian Pietrain population is strongly advised.

Single-Step Genomic Prediction of Superovulatory Response Traits in Japanese Black Donor Cows.

We assessed the performance of single-step genomic prediction of breeding values for superovulatory response traits in Japanese Black donor cows. A total of 25,332 records of the total number of embryos and oocytes (TNE) and the number of good embryos (NGE) per flush for 1874 Japanese Black donor cows were collected during 2008 and 2022. Genotype information on 36,426 autosomal single-nucleotide polymorphisms (SNPs) for 575 out of the 1,874 cows was used. Breeding values were predicted exploiting a two-trait repeatability animal model. Two genetic relationship matrices were used, one based on pedigree information (A matrix) and the other considering both pedigree and SNP marker genotype information (H matrix). Estimated heritabilities of TNE and NGE were 0.18 and 0.11, respectively, when using the H matrix, which were both slightly lower than when using the A matrix (0.26 for TNE and 0.16 for NGE). Estimated genetic correlations between the traits were 0.61 and 0.66 when using H and A matrices, respectively. When the variance components were the same in breeding value prediction, the mean reliability was greater when using the H matrix than when using the A matrix. This advantage seems more prominent for cows with low reliability when using the A matrix. The results imply that introducing single-step genomic prediction could boost the rate of genetic improvement of superovulatory response traits, but efforts should be made to maintain genetic diversity when performing selection.

Genetic analysis of longevity and their associations with fertility traits in Holstein cattle

The increase of longevity is intended to reduce involuntary culling rates, not extend the life span, and it reflects the ability of animals to successfully cope with the environment and disease during production. Sire model, animal model and repeatability animal models were used to estimate the (co) variance components of longevity and fertility traits. Six longevity and thirteen fertility traits were analysed, including herd life (HL), productive life (PL), number of days between first calving and the end of first lactation or culling (L1); number of days between first calving and the end of the second lactation or culling (L2); number of days between first calving and the end of the third lactation or culling (L3); number of days between first calving and the end of the fourth lactation or culling (L4); age at first service, age at first calving (AFC), the interval from first to last inseminations in heifer (IFLh), conception rate of first insemination in heifer, days open (DO), calving interval, gestation length, interval from calving to first insemination (ICF), interval from first to last inseminations in cow (IFLc), conception rate of first insemination in cow, calving ease (CE), birth weight, and calf survival. The estimated heritabilities (±SE) were 0.018 (±0.003), 0.015 (±0.003), 0.049 (±0.004), 0.025 (±0.003), 0.009 (±0.002) and 0.011 (±0.002) for HL, PL, L1, L2, L3 and L4, respectively. Strong correlations were appeared in HL and PL; the genetic and phenotypic correlation coefficients were 0.998 and 0.985, respectively. There were high genetic and phenotypic correlations which were observed in L1 and L2, L2 and L3, L3 and L4, respectively. All fertility traits of heifer showed medium to high heritability, while the cow showed low heritability. All heifer fertility traits had low genetic associations with longevity traits, ranging from −0.018 (L2 and IFLh) to 0.257 (L3 and AFC). Most of the fertility traits showed negative correlations with longevity traits in different parities, and we recommend DO, ICF, IFLc and CE as indirect indicators of longevity traits in dairy cows, but we also need to take into account the differences between parities.

Genetic Analysis of Methane Emission Traits in Holstein Dairy Cattle.

Genetic selection can be a feasible method to help mitigate enteric methane emissions from dairy cattle, as methane emission-related traits are heritable and genetic gains are persistent and cumulative over time. The objective of this study was to estimate heritability of methane emission phenotypes and the genetic and phenotypic correlations between them in Holstein cattle. We used 1765 individual records of methane emission obtained from 330 Holstein cattle from two Canadian herds. Methane emissions were measured using the GreenFeed system, and three methane traits were analyzed: the amount of daily methane produced (g/d), methane yield (g methane/kg dry matter intake), and methane intensity (g methane/kg milk). Genetic parameters were estimated using univariate and bivariate repeatability animal models. Heritability estimates (±SE) of 0.16 (±0.10), 0.27 (±0.12), and 0.21 (±0.14) were obtained for daily methane production, methane yield, and methane intensity, respectively. A high genetic correlation (rg = 0.94 ± 0.23) between daily methane production and methane intensity indicates that selecting for daily methane production would result in lower methane per unit of milk produced. This study provides preliminary estimates of genetic parameters for methane emission traits, suggesting that there is potential to mitigate methane emission in Holstein cattle through genetic selection.

Impact of parity differences on residual feed intake estimation in Holstein cows

Residual feed intake (RFI) has been used as a measure of feed efficiency in farm animals. In lactating dairy cattle, RFI is typically obtained as the difference between dry matter intake observations and predictions from regression on known energy sinks, and effects of parity, days in milk, and cohort. The impact of parity (lactation number) on the estimation of RFI is not well understood, so the objectives of this study were to (1) evaluate alternative RFI models in which the energy sinks (metabolic body weight, body weight change, and secreted milk energy) were nested or not nested within parity, and (2) estimate variance components and genetic correlations for RFI across parities. Data consisted of 72,474 weekly RFI records of 5,813 lactating Holstein cows collected from 2007 to 2022 in 5 research stations across the United States. Estimates of heritability, repeatability, and genetic correlations between weekly RFI for parities 1, 2, and 3 were obtained using bivariate repeatability animal models. The nested RFI model showed better goodness of fit than the nonnested model, and some partial regression coefficients of dry matter intake on energy sinks were heterogeneous between parities. However, the Spearman's rank correlation between RFI values calculated from nested and nonnested models was equal to 0.99. Similarly, Spearman's rank correlation between the RFI breeding values from these 2 models was equal to 0.98. Heritability estimates for RFI were equal to 0.16 for parity 1, 0.19 for parity 2, and 0.22 for parity 3. Repeatability estimates for RFI across weeks within parities were high, ranging from 0.51 to 0.57. Spearman's rank correlations of sires' breeding values were 0.99 between parities 1 and 2, 0.91 between parities 1 and 3, and 0.92 between parities 2 and 3. We conclude that nesting energy sinks within parity when computing RFI improves model goodness of fit, but the impact on the estimated breading values appears to be minimal.

Heritability of the elk hunting traits in the Finnish Jämthund population

ABSTRACT The aim of our study was to estimate the genetic parameters of elk hunting traits in the Finnish Jämthund population. The phenotype data included 40 402 trial observations recorded in Finland between 2012 and 2020 and the pedigree data included information of 34 495 Jämthunds. The genetic parameters of the elk hunting traits were estimated using a repeatability animal model. Season, place, and type of the trial, weather during the trial, and dog sex and age were considered fixed effects in the models, and trial judge and dog litter were treated as random effects. Variance components were estimated with the AI-REML method using the DMU-software. Heritability estimates were generally low (0.01–0.04). The highest estimated heritability was 0.04 for searching. Repeatability estimates for elk hunting traits varied between 0.04 and 0.14. Genetic correlations varied from very weak to very strong (−0.21–1.00) and were particularly strong between the barking traits.

Genetic Parameters of Reproductive Performances in Hungarian Large White, Landrace, and Their Crossbred F1 Pigs from 2010 to 2018

Genetic parameters, breeding values, and aggregate breeding values of number of piglets born alive (NBA), number of weaned piglets (NWE), and litter weight at weaning (LWWE) were predicted in the Hungarian Large White, Hungarian Landrace breeds, and in their cross (F1). Seven repeatability animal models were used. BLUP and REML methodology were used to estimate breeding values and variance–covariance components. PEST and VCE 6 software were used for estimating breeding values and variance components. Heritability for NBA and NWE was the same for all seven models. On the contrary, heritability estimates for LWWE were higher in comparison with NBA and NWE. The permanent environmental variance component was small for all traits. The large White breed had positive and significant genetic trends for all seven models and for all three traits. Landrace breed had significant trends for NBA, which was negative, and for NWE, the results were positive. The constructed indices result in one number (i.e., aggregate genetic merit); thus, the animals can be selected based on their overall performance considering the various aspects.

Defining a nitrogen efficiency index in Holstein cows and assessing its potential effect on the breeding program of bulls.

The purposes of this study were (1) to explore the relationship between 3 milk mid-infrared predicted features including nitrogen intake (NINT), milk true protein N (MTPN), and milk urea-N yield (MUNY); (2) to integrate these 3 features into an N efficiency index (NEI) and analyses approximate genetic correlations between the NEI and 37 traits (indices) of interest; and (3) to assess the potential effect of including the NEI into breeding programs of bulls. The edited data were 1,043,171 test-day records on 342,847 cows in 1,931 herds and 143,595 test-day records on 53,660 cows in 766 herds used for estimating breeding values (EBV) and variance components, respectively. The used records were within 5 to 50 d in milk. The records were grouped into primiparous and multiparous. The genetic parameters for the included mid-infrared features and EBV of the animals included in the pedigree were estimated using a multiple-trait repeatability animal model. Then, the EBV of the NINT, MTPN, MUNY were integrated into the NEI using a selection index assuming weights based on the N partitioning. The approximate genetic correlations between the NEI and 37 traits of interest were estimated using the EBV of the selected bulls. The bulls born from 2011 to 2014 with NEI were selected and the NEI distribution of these bulls having EBV for the 8 selected traits (indices) was checked. The heritability and repeatability estimates for NINT, MTPN, and MUNY ranged from 0.09 to 0.13, and 0.37 to 0.65, respectively. The genetic and phenotypic correlations between NINT, MTPN, and MUNY ranged from -0.31 to 0.87, and -0.02 to 0.42, respectively. The NEI ranged from -13.13 to 12.55 kg/d. In total, 736 bulls with reliability ≥0.50 for all included traits (NEI and 37 traits) and at least 10 daughters distributed in at least 10 herds were selected to investigate genetic aspects of the NEI. The NEI had positive genetic correlations with production yield traits (0.08-0.46), and negative genetic correlations with the investigated functional traits and indices (-0.71 to -0.07), except for the production economic index and functional type economic index. The daughters of bulls with higher NEI had lower NINT and MUNY, and higher MTPN. Furthermore, 26% of the bulls (n = 50) with NEI born between 2011 to 2014 had higher NEI and global economic index than the average in the selected bulls. Finally, the developed NEI has the advantage of large-scale prediction and therefore has the potential for routine application in dairy cattle breeding in the future.

Bayesian estimation of genetic parameters for superovulatory response traits in Japanese Black donor cows using count data models

We estimated genetic parameters for two in vivo embryo production-related superovulatory response traits—total number of embryos and oocytes (TNE) and number of good embryos (NGE)—in Japanese Black donor cows through Bayesian count regression analysis. We used 20,257 records of superovulation treatments from 1546 Japanese Black cows, with 1102 (5.4%) zero-count records for TNE and 3533 (17.4%) for NGE. Two generalized mixed linear models (MLMs; repeatability animal models)—Poisson (POI) and zero-inflated Poisson (ZIP) regression models—were fitted to the untransformed phenotypic records. A Gaussian MLM was also fitted to untransformed phenotypic records (GAU), natural log-transformed records (LOG), and records with Anscombe's variance stabilizing transformation (ANS). The estimated heritabilities and repeatabilities of TNE were 0.30 and 0.43 by POI, 0.35 and 0.47 by ZIP, 0.27 and 0.36 by GAU, 0.21 and 0.31 by LOG, and 0.24 and 0.35 by ANS, respectively. Those of NGE were 0.29 and 0.36 by POI, 0.31 and 0.40 by ZIP, 0.18 and 0.25 by GAU, 0.19 and 0.24 by LOG, and 0.20 and 0.25 by ANS, respectively. Under the ZIP, the estimated heritabilities and repeatabilities of the probability of zero counts were 0.43 and 0.71 for TNE and 0.42 and 0.51 for NGE, respectively, and the rank correlations between estimated breeding values of the 1546 donor cows for superovulation response and those for the probability of zero count were around −0.40 for TNE and −0.50 for NGE.

Genetic parameters, heterosis, and breed effects for body condition score and mature cow weight in beef cattle.

Understanding the genetic relationship between mature cow weight (MWT) and body condition score (BCS) is useful to implement selection programs focused on cow efficiency. The objectives of this study were to estimate genetic parameters, heterosis, and breed effects for MWT and BCS. In total, 25,035 and 24,522 overlapping records were available for MWT and BCS on 6,138 and 6,131 cows, respectively, from the Germplasm Evaluation program, a crossbred beef population at the U.S. Meat Animal Research Center. Pedigree was available for 48,013 individuals. Univariate animal models were used to estimate heritabilities for each trait by parity. Bivariate animal models were used to estimate genetic correlations between parities within a trait and between traits within parities. Bivariate repeatability animal models were used to estimate genetic correlations between traits across parities. Estimates of heritability for different parities ranged from 0.43 ± 0.05 to 0.55 ± 0.07 for MWT and from 0.12 ± 0.03 to 0.25 ± 0.04 for BCS and were lower with the repeatability model at 0.40 ± 0.02 and 0.11 ± 0.01 for MWT and BCS, respectively. Estimates of repeatability were high for MWT (0.67 ± 0.005) and low for BCS (0.22 ± 0.006). Estimates of genetic correlation for MWT and BCS between parities were, in general, high, especially between consecutive parities. Estimates of genetic correlation between MWT and BCS were positive and moderate, ranging from 0.32 ± 0.09 to 0.68 ± 0.14. The direct heterosis estimates were 21.56 ± 3.53kg (P ≤ 0.001) for MWT and 0.095 ± 0.034 (P ≤ 0.001) for BCS. Ordered by decreasing MWT, the breeds ranked Brahman, Charolais, Angus, Simmental, Salers, Hereford, Santa Gertrudis, Chiangus, Brangus, Red Angus, Shorthorn, Maine-Anjou, Gelbvieh, Beefmaster, Limousin, and Braunvieh. Ordered by decreasing BCS, the breeds ranked Brahman, Red Angus, Charolais, Angus, Hereford, Brangus, Beefmaster, Chiangus, Salers, Simmental, Maine-Anjou, Limousin, Santa Gertrudis, Shorthorn, Gelbvieh, and Braunvieh. Estimates of breed differences for MWT were also adjusted for BCS (AMWT), and in general, AMWT depicted smaller differences between breeds with some degree of re-ranking (r = 0.59). These results suggest that MWT and BCS are at least moderately genetically correlated and that they would respond favorably to selection. Estimates of breed differences and heterotic effects could be used to parameterize multibreed genetic evaluations for indicators of cow maintenance energy requirements.