Genetic analysis of protein yield,udder health,and female fertility in first-parity Danish Holstein cows

Abstract

Genetic parameters for protein yield, clinical mastitis, SCS, number of inseminations (NI), and days from first to last insemination (FLI) were estimated for first-parity Danish Holstein cows. The objective was to estimate genetic correlations between the five traits mentioned above and to study whether NI and FLI are measures of the same trait. Records containing information on approximately 200 000 cows were analysed using tri-variate animal models. The genetic correlations between the udder health traits and the fertility traits were favourable and in the range from 0.17 to 0.42, whereas the genetic correlations between protein yield and the fertility traits were unfavourable and ranged from 0.43 to 0.52. These results highlight the importance of continuing to emphasize functional traits in future breeding programmes. The genetic correlation between the fertility traits was 0.82. Based on this result, it cannot be concluded that NI and FLI are measures of the same trait.     

Genetic parameters for fertility traits in Nellore bulls

Nellore is the main cattle breed used in Brazil, being the largest commercial herd in the world. Beyond the importance of male reproductive efficiency for farm profit, the use of reproductive techniques, mainly artificial insemination, turns the evaluation of male reproductive traits even more important. Estimation of genetic parameters increases the knowledge on traits variances and allows envisaging the possibility of the inclusion of new traits as selection criterion. Genetic parameters for fifteen traits that can be classified as testicular biometry or physical and morphological semen traits were estimated for a Nellore bull population ranging from 18 to 36 months. Single-trait and bi-trait animal models were used for (co)variance components estimation. The contemporary group was considered as fixed effect and age at measurement as covariable. Scrotal circumference presented heritability of 0.47 ± 0.12. This value is similar to the heritabilities found for all testicular biometry traits (0.34–0.48). Sperm progressive motility, which has a direct effect on bull fertility, presented low heritability (0.07 ± 0.08). Major and total sperm defects presented moderate to high heritabilities (0.49 ± 0.18 and 0.39 ± 0.15, respectively), indicating that great genetic gain can be obtained through selection against sperm defects. High and positive genetic correlations were observed among testicular biometry traits, which also presented favourable genetic correlations with physical and morphological traits of the semen with magnitude ranging from high to low. Scrotal circumference presented moderate to high and favourable genetic correlations with sperm progressive motility, sperm turbulence, major sperm defects and total sperm defects. Thus, the selection for scrotal circumference results in favourable correlated genetic response for semen quality. The results show that the use of scrotal circumference as reference trait for bull fertility is appropriate, since it presents high heritability and favourable genetic correlation with semen quality.     

宁夏地区荷斯坦牛青年牛繁殖性状遗传参数估计

旨在探究青年牛繁殖性状遗传能力群体遗传参数,评估不同配种季节间青年牛繁殖性状基因型与环境的互作效应(G×E).本研究利用宁夏地区12个牧场2007-2019年荷斯坦牛繁殖事件信息记录,计算青年牛繁殖性状包括:首配日龄(AFS)、初产日龄(AFC)、首次配种后56天不返情率(NRR56)、首末次配种间隔(IFL)、妊娠期...     

三河牛繁殖性状遗传参数的评估

本研究以1986年中国自主培育兼用牛新品种--三河牛,在内蒙古海拉尔谢尔塔拉种牛场核心群5 257头1998-2012年20 949条繁殖记录为研究材料,以青年牛首次妊娠日龄、青年牛首次产犊日龄、成母牛妊娠期、成母牛空怀期、产犊间隔为研究对象,用SAS 9.13、DMU软件对数据进行处理,采用AI-REML结合EM算法并配合多性状动物模型对各性状影响因素方差组分进行估计,估算出各性状遗传力,并利用各性状育种值分析其遗传趋势.结果显示,青年牛首次妊娠日龄、青年牛首次产犊日龄、成母牛妊娠期、成母牛空怀期、产犊间隔遗传力分别为0.0552、0.0638、0.0527、0.1096、0.0844,繁殖性状除成母牛空怀期遗传力为0.1096外,其余均小于0.1,属于低遗传力性状.青年牛首次妊娠日龄、青年牛首次产犊日龄、成母牛妊娠期、成母牛空怀期、产犊间隔育种值遗传趋势总体上无明显下降趋势,三河牛繁殖性能保持良好.该试验结果为三河牛优化育种方案、提高选种准确性提供重要理论依据.     

Genetic Evaluation of Reproductive Traits in Sanhe Cattle

This study was conducted on 20 949 reproductive records from 1998 to 2012 of 5 257 Sanhe cattle in Xiertala cattle farm,Inner Mongolia,which was a synthetic breed formed in China in 1986.Age at first pregnancy in heifer (AFPH),age at first calving in heifer (AFCH),gestation length in cow (GLC),days open in cow (DOC),and calving interval in cow (CIC) were considered for genetic evaluation.SAS 9.13 and DMU software were used for data processing,and AI-REML combined EM algorithm based on multiple traits animal model was employed for estimating variance components.The heritability for each trait were then calculated,and breeding value was used to analyze the genetic trends.The results showed that the estimated heritabilities of age at first pregnancy in heifer,age at first calving in heifer,gestation length in cow,days open in cow,calving interval in cow were 0.0552,0.0638,0.0527,0.1096 and 0.0844,respectively.The heritabilities were all less than 0.1 except days open (0.1096),indicating these were low inheritable traits.In general,trends of EBVs for each trait didn't show any defined progresses and indicating good reproductive performance maintained in Sanhe cattle.These results lay a theoretical foundation for optimizing breeding programs and improving the accuracy of selection in Sanhe cattle.     

Variance components due to direct genetic, maternal genetic and permanent environmental effect for growth and feed-efficiency traits in young male Japanese Black cattle

Variance components and genetic parameters were estimated using data recorded on 740 young male Japanese Black cattle during the period from 1971 to 2003. Traits studied were feed intake (FI), feed‐conversion ratio (FCR), residual feed intake (RFI), average daily gain (ADG), metabolic body weight (MWT) at the mid‐point of the test period and body weight (BWT) at the finish of the test (345 days). Data were analysed using three alternative animal models (direct, direct + maternal environmental, and direct + maternal genetic effects). Comparison of the log likelihood values has shown that the direct genetic effect was significant (p < 0.05) for all traits and that the maternal environmental effects were significant (p < 0.05) for MWT and BWT. The heritability estimates were 0.20 ± 0.12 for FI, 0.14 ± 0.10 for FCR, 0.33 ± 0.14 for RFI, 0.19 ± 0.12 for ADG, 0.30 ± 0.14 for MWT and 0.30 ± 0.13 for BWT. The maternal effects (maternal genetic and maternal environmental) were not important in feed‐efficiency traits. The genetic correlation between RFI and ADG was stronger than the corresponding correlation between FCR and ADG. These results provide evidence that RFI should be included for genetic improvement in feed efficiency in Japanese Black breeding programmes.     

Additive genetic relationships between heifer pregnancy and scrotal circumference in Hereford cattle.

The objective of this study was to determine an appropriate method for using yearling scrotal circumference observations and heifer pregnancy observations to produce EPD for heifer pregnancy. We determined the additive genetic effects of and relationship between scrotal circumference and heifer pregnancy for a herd of Hereford cattle in Solano, New Mexico. The binary trait of heifer pregnancy was defined as the probability of a heifer conceiving and remaining pregnant to 120 d, given that she was exposed at breeding. Estimates of heritability for heifer pregnancy and scrotal circumference were .138+/-.08 and .714+/-.132, respectively. Estimates of fixed effects for age of dam and age were significant for heifer pregnancy and bull scrotal circumference. The estimate of the additive genetic correlation between yearling heifer pregnancy and yearling bull scrotal circumference was .002+/-.45. Additional analyses included models with additive genetic groups for scrotal circumference EPD for heifer pregnancy or heifer pregnancy EPD for scrotal circumference to account for a potential nonlinear relationship between scrotal circumference and heifer pregnancy. Results support the development of a heifer pregnancy EPD because of a higher estimated heritability than previously reported. The development of a heifer pregnancy EPD would be an additional method for improving genetic merit for heifer fertility.     

Genetic parameters for total lactation yields of milk,fat, protein,and somatic cell score in New Zealand dairy goats

The aim of this study was to estimate genetic parameters for lactation yields of milk (MY), fat (FY), protein (PY), and somatic cell score (SCS) of New Zealand dairy goats. The analysis used 64,604 lactation records from 23,583 does, kidding between 2004 and 2017, distributed in 21 flocks and representing 915 bucks. Estimates of genetic and residual (co) variances, heritabilities, and repeatabilities were obtained using a multiple‐trait repeatability animal model. The model included the fixed effects of contemporary group (does kidding in the same flock and year), age of the doe (in years), and as covariates, kidding day, proportion of Alpine, Nubian, Toggenburg, and “unknown” breeds (Saanen was used as the base breed), and heterosis. Random effects included additive animal genetic and doe permanent environmental effects. Estimates of heritabilities were 0.25 for MY, 0.24 for FY, 0.24 for PY, and 0.21 for SCS. The phenotypic correlations between MY, FY, and PY ranged from 0.90 to 0.96, and the genetic correlations ranged from 0.81 to 0.93. These results indicate lactation yield traits exhibit useful heritable variation and that multiple trait selection for these traits could improve milk revenue produced from successive generations of New Zealand dairy goats.     

Genetic analysis of liability to clinical mastitis, with somatic cell score and production traits using bivariate threshold–linear and linear–linear models

Inferences about genetic and residual correlation estimates and sire evaluations involving a categorical trait with linear model are ambiguous and mostly based on data simulations. In this study, estimates of variance components and prediction of breeding values in a model with a categorical and a continuous trait were compared between threshold–linear (TLM) and linear–linear models (LLM) in analysis of large clinical mastitis (CM) field data. Data on CM, somatic cell score (SCS), 305-day milk (MY), protein (PY) and fat yield (FY) from first-lactation Finnish Ayrshire cows were used. Four bivariate analyses were made using a TLM in Bayesian analysis. Each analysis fitted CM and one continuous trait at a time. Corresponding bivariate analyses were made using a Gaussian linear model. Estimates of heritabilities for CM were 0.06 and 0.02 from TLM and LLM, respectively whilst heritability estimates of the continuous traits were similar from both models. Genetic correlations between CM–SCS, CM–MY, CM–PY, and CM–FY from TLM and LLM were 0.63 and 0.63; 0.36 and 0.36; 0.32 and 0.32; 0.30 and 0.29, respectively. Estimates of residual correlations were 0.11 and 0.06; − 0.04 and − 0.02; − 0.03 and − 0.02; − 0.05 and − 0.03 between CM–SCS, CM–MY, CM–PY, and CM–FY, respectively. Comparison between the models indicates similar estimates of genetic correlations with no underestimation with the linear model analysis. In CM evaluation, the comparison of model's predictive ability showed greater improvements in accuracy with the bivariate than with the univariate models. There was, however no clear advantage of univariate threshold model over univariate linear model, except for less accuracy sires.     

Genetic relationships between length of productive life and lifetime production efficiency in a commercial swine herd in Northern Thailand

Genetic parameters and trends for length of productive life (LPL), lifetime number of piglets born alive per year (LBAY), lifetime number of piglets weaned per year (LPWY), lifetime litter birth weight per year (LBWY) and lifetime litter weaning weight per year (LWWY) were estimated using phenotypic records of 3085 sows collected from 1989 to 2013 in a commercial swine farm in Northern Thailand. The five‐trait animal model included the fixed effects of first farrowing year‐season, breed group and age at first farrowing. Random effects were animal and residual. Heritability estimates ranged from 0.04 ± 0.02 for LBWY to 0.17 ± 0.04 for LPL. Genetic correlations ranged from 0.66 ± 0.14 between LPL and LBAY to 0.95 ± 0.02 between LPWY and LWWY. Spearman rank correlations among estimated breeding values for LPL and lifetime production efficiency traits tended to be higher for boars than for sows. Sire genetic trends were negative and significant for all traits, except for LPWY. Dam genetic trends were positive and significant for all traits. Sow genetic trends were mostly positive and significant only for LPWY and LBWY. Improvement of LPL and lifetime production efficiency traits will require these traits to be included in the selection indexes used to choose replacement boars and gilts in this population.     

Genetic relationships among female fertility disorders,female fertility traits and productivity of Holstein dairy cows in the early lactation period

Fertility health disorders from the early lactation period including retained placenta (REPLA), metritis (MET), corpus luteum persistence (CLP), anoestria/acyclia (AOEAC) and ovarial cysts (OC), as well as overall disease categories (disorders during the postpartal period (DPP), ovary infertility (OINF), overall trait definition “fertility disorders” (FD)), were used to estimate genetic (co)variance components with female fertility and test‐day traits. The disease data set comprised 25,142 Holstein cows from parities 1, 2 and 3 resulting in 43,584 lactations. For disease traits, we used the binary trait definition (sick or healthy) and disease count data reflecting the sum of treatments for the same disease within lactation or within lactation periods. Statistical modelling included single and multiple trait repeatability animal models for all trait combinations within a Bayesian framework. Heritabilities for binary disease traits ranged from 0.04 (OC) to 0.10 (REPLA) and were slightly lower for the corresponding sum trait definitions. Correlations between both trait definitions were almost one, for genetic as well as for permanent environmental effects. Moderate to high genetic correlations were found among puerperal disorders DPP, REPLA and MET (0.45–0.98) and among the ovarian disorders OINF, AOEAC, CLP and OC (0.59–0.99). Genetic correlations between puerperal and ovarian disorders were close to zero, apart from the REPLA–OC association (0.55). With regard to fertility disorders and productivity in early lactation, a pronounced genetic antagonistic relationship was only identified between OC and protein yield. Genetic correlations between fertility disorders and test‐day SCS were close to zero. OINF and all diseases contributing to OINF were strongly correlated with the female fertility traits “interval from calving to first service,” “interval from service to pregnancy” and “interval from calving to pregnancy.” The strong correlations imply that fertility disorders could be included in genetic evaluations of economic fertility traits as correlated predictors. Vice versa, a breeding focus on female fertility traits will reduce genetic susceptibility to OC, CLP and AOEAC.     

Economic weights of production and functional traits for Holstein‐Friesian cattle in Hungary

A bio‐economic model was used to estimate economic values of 15 milk production, functional, growth and carcass traits for Hungarian Holstein‐Friesian cattle. The calculations were carried out for the situation in Hungary from 2000 to 2007, assuming no production quotas. The marginal economic values were defined as partial derivatives of the profit function with respect to each trait in a production system with dairy cow herds and with sales of surplus male calves. The economic weights for maternal and direct components of traits were calculated multiplying the marginal economic values by the number of discounted expression summed over a 25‐year investment period for 2‐year‐old bulls (candidates for selection). The standardized economic weight (economic weight × genetic standard deviation) of the trait or trait component expressed as percentage of the sum of the standardized economic weights for all traits and trait components represented the relative economic importance of this trait or trait component. The highest relative economic importance was obtained for milk yield (25%), followed by productive lifetime of cows (23%), protein yield and the direct component of a cow’s total conception rate (9% each), the maternal effect of the total conception rate of cows and the somatic cell score (approximately 7% each), fat yield (5%) and mature weight of cows and daily gain in rearing of calves (approximately 4% each). Other functional traits (clinical mastitis incidence, calving difficulty score, total conception rate of heifers and calf mortality) reached a relative economic importance between 0.5% and 2%. Birth weight and dressing percentage were least important (<0.5%). Based on these results, the inclusion of productive lifetime and cow fertility in the breeding programme for Holstein‐Friesian cattle in Hungary is advisable.     

Genetic variability of maternal effect on body measurements and its intra‐ and inter‐genetic relationship with direct effect in Japanese Black calves

This study was conducted to evaluate the importance of maternal effect on body measurement traits at an early stage of growth, and to estimate the genetic relationships between direct and maternal effects and among body measurement traits at 0 month (0‐mo) and 4 months (4‐mo) of age in a population of Japanese Black calves. Body measurements and body weight of 889 Japanese Black calves were estimated with the use of an animal model by the Residual Maximum Likelihood procedure. Direct heritabilities were low to moderate, ranging between 0.17 ± 0.09 and 0.48 ± 0.13 at 0‐mo, and slightly lower, ranging between 0.15 ± 0.07 and 0.33 ± 0.13 at 4‐mo. Estimated maternal heritabilities were low to moderate, ranging between 0.08 ± 0.07 and 0.33 ± 0.07 at 0‐mo and 0.13 ± 0.06 to 0.33 ± 0.06 at 4‐mo. The direct genetic correlations between 0‐mo and 4‐mo were moderate to highly positive, ranging from 0.53 ± 0.23 to 0.96 ± 0.09. The estimated direct genetic correlation of chest width with other width traits was low and positive at both ages, whereas with hip width it was high and positive (0.80 ± 0.09) at 0‐mo, suggesting that simultaneous improvement of body width of the front and back parts is possible. Maternal genetic effects were relatively independent of direct genetic effects for body measurement traits and can be considered in genetic evaluation.     

Genetic parameter estimates for semen production traits and growth rate of a paternal rabbit line

Variance components of sperm production traits (volume in ml, V; concentration in ×10⁶ sperm/ml, CN; sperm production in ×10⁶ sperm, PROD) were estimated in a paternal line of rabbit selected for 25 generations based on daily weight gain (DG, g/day) between 28 and 63 days of age. Features of the marginal posterior distributions for ratios of genetic variance, variance owing to non‐additive plus environmental permanent male effects and variance owing to common litter of birth effects with respect to phenotypic variance are reported. The correlations between sperm production traits and the selection criteria were also estimated. Three sets of two‐trait analyses were performed, involving 12908 records of DG, 2329 ejaculates corresponding to 412 bucks and 14700 animals in pedigree file. The heritabilities (h²) of the semen traits were 0.13 ± 0.05, 0.08 ± 0.04 and 0.07 ± 0.03 for V, CN and PROD, respectively. The permanent environmental effects were lower than the corresponding values of h² and varied between 0.06 and 0.11. A favourable and moderate genetic correlation was observed between V and DG (0.36 ± 0.34; p > 0: 0.83), together with a non‐favourable and moderate correlation between permanent environmental effects owing to common litter of birth for both traits (?0.35 ± 0.35; p < 0: 0.85). On the other hand, the correlation between male permanent environmental effects for semen traits and DG was moderate and non‐favourable (?0.51 ± 0.29 with p < 0: 0.95 for DG‐CN, and ?0.31 ± 0.37 with p < 0: 0.79 for DG‐PROD).     

Genetic variation and covariation in beef cow and bull fertility

Single-sire natural mating data from a beef cattle herd in tropical Australia were used to estimate heritabilities of cow fertility (hc2), heritabilities of bull fertility (hb2) and genetic correlations between cow and bull fertility (rg) within each of six genotypes. Estimates of hc2 and hb2 were low, averaging .11 and .08, respectively. The pooled estimate of rg was 0.16, indicating that cow and bull fertility are favorably genetically correlated and therefore that cow fertility could be genetically improved by indirect selection on bull fertility, or some more heritable component of bull fertility.     

Genetic associations of visual scores with subsequent rebreeding and days to first calving in Nellore cattle

Records of Nellore animals born from 1990 to 2006 were used to estimate genetic correlations of visual scores at yearling (conformation, C; finishing precocity, P; and muscling, M) with primiparous subsequent rebreeding (SR) and days to first calving (DC), because the magnitude of these associations is still unknown. Genetic parameters were estimated by multiple‐traits Bayesian analysis, using a nonlinear (threshold) animal models for visual scores and SR and a linear animal models for weaning weight (WW) and DC. WW was included in the analysis to account for the effects of sequential selection. The posterior means of heritabilities estimated for C, P, M, SR and DC were 0.24 ± 0.01, 0.31 ± 0.01, 0.30 ± 0.01, 0.18 ± 0.02 and 0.06 ± 0.02, respectively. The posterior means of genetic correlations estimated between SR and visual scores were low and positive, with values of 0.09 ± 0.02 (C), 0.19 ± 0.03 (P) and 0.18 ± 0.05 (M). On the other hand, negative genetic correlations were found between DC and C (?0.11 ± 0.09), P (?0.19 ± 0.09) and M (?0.16 ± 0.09). The primiparous rebreeding trait has genetic variability in Nellore cattle. The genetic correlations between visual scores, and SR and DC were low and favourable. The genetic changes in C, P and M were 0.02, 0.03 and 0.03/year, respectively. For SR and DC, genetic trends were 0.01/year and ?0.01 days/year, respectively, indicating that the increase in genetic merit for reproductive traits was small over time. Direct selection for visual scores together with female reproductive traits is recommended to increase the fertility of beef cows.     

Estimation of genetic parameters for milk and fertility traits within and between low,medium and high dairy production systems in Kenya to account for genotype-by-environment interaction

Dairy records from the Dairy Recording Service of Kenya were classified into low, medium and high production systems based on mean 305-day milk yield using the K-means clustering method. Milk and fertility records were then analysed to develop genetic evaluation systems accounting for genotype-by-environment interaction between the production systems. Data comprised 26,638 lactation yield, 3,505 fat yield, 9,235 age at first calving and 17,870 calving interval records from 12,631 cows which were descendants of 2,554 sires and 8,433 dams. An animal model was used to estimate variance components, genetic correlations and breeding values for the production systems. Variance components increased with production means, apart from genetic group variances, which decreased from the low to the high production system. Moderate heritabilities were estimated for milk traits (0.21–0.27) and fat traits (0.11–0.38). Low heritabilities were estimated for lactation length (0.04–0.10) and calving interval (0.03–0.06). Moderate heritabilities (0.25–0.26) were estimated for age at first calving, except under the high production system (0.05). Within production systems, lactation milk yield, 305-day milk yield and lactation length had high positive genetic correlations (0.52–0.96), while lactation milk yield and lactation length with age at first calving had negative genetic correlations. Milk yield and calving interval were positively correlated except under the low production system. The genetic correlations for lactation milk yield and 305-day milk yield between low and medium (0.48 ± 0.20 and 0.46 ± 0.21) and low and high production systems’ (0.74 ± 0.15 and 0.62 ± 0.17) were significantly lower than one. Milk yield in the low production system is, therefore, a genetically different trait. The low genetic correlations between the three production systems for most milk production and fertility traits suggested that sires should be selected based on progeny performance in the targeted production system.     

Genetic parameter estimation for beef bull semen attributes

Improvements in bull reproductive performance are necessary to optimize the efficiency of cattle production. Female fertility has been enhanced through assisted reproductive technologies as well as genetic selection; however, improving beef bull fertility has been largely ignored. Phenotypes routinely collected at bull semen collection facilities are believed to affect fertility and provide the phenotypes necessary for a genetic evaluation. The first objective of this study was to determine the significant fixed effects for modeling beef bull fertility using data from bull semen collection facilities. The second objective was to estimate variance components, heritabilities, repeatabilities, and correlations between beef bull semen attributes. Beef bull fertility phenotypes including volume (VOL), concentration (CONC), number of spermatozoa (NSP), initial motility (IMot), post-thaw motility (PTMot), 3-h post-thaw motility (3HRPTMot), percentage of normal spermatozoa (%NORM), primary abnormalities (PRIM), and secondary abnormalities (SEC) were obtained from two bull semen collection facilities. A total of 1,819 Angus bulls with 50,624 collection records were analyzed. Of the fixed class and covariate effects tested, the significant class effects were collection location and collection day within year and the significant covariate effects included age at collection, days since previous collection, and cumulative comprehensive climate index (CCI). For this study, the CCI was calculated for a 75-d period including the 61-d spermatogenesis cycle and 14-d epididymal transit time. The 75 d prior to collection accounted for the environmental stress a bull may have experienced over the course of development of the spermatozoa, which was more significant than the CCI calculated for collection day or spermatogenesis start date. Pre-thaw beef bull semen traits had low heritability estimates of 0.11 ± 0.02 (VOL), 0.09 ± 0.02 (CONC), 0.08 ± 0.02 (NSP), and 0.12 ± 0.03 (IMot). Heritabilities of post-thaw beef bull semen attributes were more variable at 0.10 ± 0.02 (PTMot), 0.05 ± 0.04 (3HRPTMot), 0.10 ± 0.04 (%NORM), 0.03 ± 0.03 (PRIM), and 0.18 ± 0.04 (SEC). Correlations of breeding values for these traits with scrotal circumference (SC) expected progeny difference (EPD) are low. The low to moderate heritability estimates indicate that genetic improvement can be made in beef bull semen quality traits if new tools are developed to augment the scrotal circumference EPD that are currently available within the industry.     

Genetic parameters for carcass traits and their live animal indicators in Simmental cattle

The objective of this study was to estimate parameters required for genetic evaluation of Simmental carcass merit using carcass and live animal data. Carcass weight, fat thickness, longissimus muscle area, and marbling score were available from 5,750 steers and 1,504 heifers sired by Simmental bulls. Additionally, yearling ultrasound measurements of fat thickness, longissimus muscle area, and estimated percentage of intramuscular fat were available on Simmental bulls (n = 3,409) and heifers (n = 1,503). An extended pedigree was used to construct the relationship matrix (n = 23,968) linking bulls and heifers with ultrasound data to steers and heifers with carcass data. All data were obtained from the American Simmental Association. No animal had both ultrasound and carcass data. Using an animal model and treating corresponding ultrasound and carcass traits separately, genetic parameters were estimated using restricted maximum likelihood. Heritability estimates for carcass traits were 0.48 +/- 0.06, 0.35 +/- 0.05, 0.46 +/- 0.05, and 0.54 +/- 0.05 for carcass weight, fat thickness, longissimus muscle area, and marbling score, respectively. Heritability estimates for bull (heifer) ultrasound traits were 0.53 +/- 0.07 (0.69 +/- 0.09), 0.37 +/- 0.06 (0.51 +/- 0.09), and 0.47 +/- 0.06 (0.52 +/- 0.09) for fat thickness, longissimus muscle area, and intramuscular fat percentage, respectively. Heritability of weight at scan was 0.47 +/- 0.05. Using a bivariate weight model including scan weight of bulls and heifers with carcass weight of slaughter animals, a genetic correlation of 0.77 +/- 0.10 was obtained. Models for fat thickness, longissimus muscle area, and marbling score were each trivariate, including ultrasound measurements on yearling bulls and heifers, and corresponding carcass traits of slaughter animals. Genetic correlations of carcass fat thickness with bull and heifer ultrasound fat were 0.79 +/- 0.13 and 0.83 +/- 0.12, respectively. Genetic correlations of carcass longissimus muscle area with bull and heifer ultrasound longissimus muscle area were 0.80 +/- 0.11 and 0.54 +/- 0.12, respectively. Genetic correlations of carcass marbling score with bull and heifer ultrasound intramuscular fat percentage were 0.74 +/- 0.11 and 0.69 +/- 0.13, respectively. These results provide the parameter estimates necessary for genetic evaluation of Simmental carcass merit using both data from steer and heifer carcasses, and their ultrasound indicators on yearling bulls and heifers.