Use of methane production data for genetic prediction in beef cattle: A review

Methane (CH4) is a greenhouse gas that is produced and emitted from ruminant animals through enteric fermentation. Methane production from cattle has an environmental impact and is an energetic inefficiency. In the beef industry, CH4 production from enteric fermentation impacts all three pillars of sustainability: environmental, social, and economic. A variety of factors influence the quantity of CH4 produced during enteric fermentation, including characteristics of the rumen and feed composition. There are several methodologies available to either quantify or estimate CH4 production from cattle, all with distinct advantages and disadvantages. Methodologies include respiration calorimetry, the sulfur-hexafluoride tracer technique, infrared spectroscopy, prediction models, and the GreenFeed system. Published studies assess the accuracy of the various methodologies and compare estimates from different methods. There are advantages and disadvantages of each technology as they relate to the use of these phenotypes in genetic evaluation systems. Heritability and variance components of CH4 production have been estimated using the different CH4 quantification methods. Agreement in both the amounts of CH4 emitted and heritability estimates of CH4 emissions between various measurement methodologies varies in the literature. Using greenhouse gas traits in selection indices along with relevant output traits could provide producers with a tool to make selection decisions on environmental sustainability while also considering productivity. The objective of this review was to discuss factors that influence CH4 production, methods to quantify CH4 production for genetic evaluation, and genetic parameters of CH4 production in beef cattle.

Variance component estimation and genome-wide association of predicted methane production in crossbred beef steers

Enteric methane is a potent greenhouse gas and represents an escape of energy from the ruminant digestive system. Additive genetic variation in methane production suggests that genetic selection offers an opportunity to diminish enteric methane emissions. Logistic and monetary difficulties in directly measuring methane emissions can make genetic evaluation on an indicator trait such as predicted methane production a more appealing option, and inclusion of genotyping data can result in greater genetic progress. Three predicted methane production traits were calculated for 830 crossbred steers fed in seven groups. The methane prediction equations used included mathematical models from Ellis et al. (2007), Mills et al. (2003), and IPCC (2019). Pearson correlations between the traits were all greater than 0.99, indicating that each prediction equation behaved similarly. Further, the Spearman correlations between the estimated breeding values for each trait were also 0.99, which suggests any of the predicted methane models could be used without substantially changing the ranking of the selection candidates. The heritabilities of Ellis, Mills, and IPCC predicted methane production were 0.60, 0.62, and 0.59, respectively. A genome-wide association study identified one single nucleotide polymorphism (SNP) that reached the threshold for significance for all of the traits on chromosome 7 related to oxidoreductase activity. Additionally, the SNP slightly below the significance threshold indicate genes related to collagen, intracellular microtubules, and DNA transcription may play a role in predicted methane production or its component traits.

Technical Note: Characterization of the number of spot samples required for quantification of gas fluxes and metabolic heat production from grazing beef cows using a GreenFeed

Enteric fermentation from cattle results in greenhouse gas production that is an environmental concern and also an energetic loss. Several methods exist to quantify gas fluxes; however, an open circuit gas quantification system (OCGQS) allows for unencumbered quantification of methane, carbon dioxide, and oxygen from grazing cattle. While previous literature has proven the accuracy of an OCGQS, little work has been done to establish the minimum number of spot samples required to best evaluate an individual grazing animal's gas fluxes and metabolic heat production. A GreenFeed system (C-Lock, Inc) was used to collect at least 100 spot samples each from 17 grazing cows. The mean gas fluxes and metabolic heat production were computed starting from the first 10 visits (forward) and increasing by increments of 10 until an animal had 100 visits. Mean gas fluxes and metabolic heat production were also computed starting from visit 100 (reverse) in increments of 10 using the same approach. Pearson and Spearman correlations were computed between the full 100 visits and each shortened visit interval. A large increase in correlations were seen between 30 and 40 visits. Thus, mean forward and reverse gas fluxes and metabolic heat production were also computed starting at 30 visits and increasing by 2 until 40 visits. The minimum number of spot samples was determined when correlations with the full 100 visits were greater than 0.95. The results indicated that the minimum numbers of spot samples needed for accurate quantification of methane, carbon dioxide, and oxygen gas fluxes are 38, 40, and 40, respectively. Metabolic heat production can be calculated using gas fluxes collected by the OCGQS with 36 spot samples. Practically, calculation of metabolic heat production will require 40 spot samples because the component gases for metabolic heat calculation require up to 40 spot samples. Published literature from non-grazing (confined) environments recommended a similar number of total spot samples. Large variation existed around the average number of spot samples for an animal per day, therefore a wide range of test durations may be needed to meet the same number of spot samples in different populations. For this reason, protocols for the OCGQS should be based on the total number of spot samples, rather than a test duration.

Heritability and variance component estimation for feed and water intake behaviors of feedlot cattle

Feed and water intake are two important aspects of cattle production that greatly impact the profitability, efficiency, and sustainability of producers. Feed and, to a lesser degree, water intake have been studied previously; however, there is little research on their associated animal behaviors and there is a lack of standardized phenotypes for these behaviors. Feed and water intakes obtained with an Insentec system (Hokofarm Group, The Netherlands) from 830 crossbred steers were used to compute five intake behaviors for both feed and water: daily sessions (DS), intake rate (IR), session size (SS), time per session (TS), and session interval (SI). Variance components and heritabilities were estimated for each trait. Heritabilities for feed intake behaviors were 0.50 ± 0.12, 0.63 ± 0.12, 0.40 ± 0.13, 0.35 ± 0.12, and 0.60 ± 0.12 for DS, IR, SS, TS, and SI, respectively. Heritabilities for water intake behaviors were 0.56 ± 0.11, 0.88 ± 0.07, 0.70 ± 0.11, 0.54 ± 0.12, and 0.80 ± 0.10 for NS, IR, SS, TS, and SI, respectively. Daily dry matter intake (DDMI) and daily water intake (DWI) had heritabilities of 0.57 ± 0.11 and 0.44 ± 0.11. Phenotypic correlations varied between pairs of traits (-0.83 to 0.82). Genetic correlations between DDMI and feed intake behaviors were moderate to high, while genetic correlations between DWI and water intake behaviors were low to moderate. Several significant single nucleotide polymorphisms (SNP) were identified for the feed and water intake behaviors. Genes and previously reported quantitative trait loci near significant SNPs were evaluated. The results indicated that feed and water intake behaviors are influenced by genetic factors and are heritable, providing one additional route to evaluate or manipulate feed and water intake.

Stochastic, individual animal systems simulation model of beef cow-calf production: development and validation

A stochastic, individual animal systems simulation model describing U.S. beef cow-calf production was developed and parameterized to match typical U.S. Angus genetics under cow-calf production conditions in the Kansas Flint Hills. Model simulation results were compared to available actual, multivariate U.S. cow-calf production data reported according to beef cow-calf standardized performance analysis (SPA) methodology through North Dakota State University's CHAPS program to assess model validity. Individual animal nutrition, reproduction, growth, and health characteristics, as well as production state are determined on a daily time step. Any number of days can be simulated. These capabilities allow for decision analysis and assessment of long-run outcomes of various genetic, management, and economic scenarios regarding multiple metrics simultaneously. Parameterizing the model to match Kansas Flint Hills production conditions for the years 1995 through 2018, 32 different genetic combinations for mature cow weight and peak lactation potential were simulated with 100 iterations each. Sire mature cow weight genetics ranged from 454 to 771 kg in 45 to 46 kg increments. Sire peak lactation genetics were considered at 6.8, 9, 11.3, and 13.6 kg/d for all eight mature cow weights. Utilizing model results for the years 2000 to 2018, raw model results were assessed against actual historical cow-calf production data. Exploratory factor analysis was applied to interpret the underlying factor scores of model output relative to actual cow-calf production data. Comparing modeled herd output with CHAPS herd data, median average calf weaning age, average cow age, percent pregnant per cow exposed, and percent calf mortality per calf born of model output was 3.4 d greater, 0.2 yr greater, 1 percentage point less, and 1.7 percentage points greater, respectively. Subtracting the median CHAPS pre-weaning average daily gain from the median modeled pre-weaning average daily gain for each of the eight respective mature cow weight genetics categories, and then calculating the median of the eight values, the median difference was -0.21 kg/d. Performing the same calculation for birth weight and adjusted 205 d weaning weight, the modeled data was 4.9 and 48.6 kg lighter than the CHAPS data, respectively. Management and genetic details underlying the CHAPS data were unknown.

Retrospective analysis of cohort risk factors and feeding phase timing associated with noninfectious heart disease deaths in U.S. feedlot cattle

Heart disease, specifically congestive heart failure, has become of increased interest to geneticists and cattle feeders. Data on cohort associations of risk factors related to heart disease and when heart disease deaths occur in U.S. feedlot cattle are limited. The study objectives were to 1) determine potential associations between feedlot cohort demographics and the risk of at least one noninfectious heart disease (NIHD) death occurrence and 2) determine potential association between feedlot cohort demographics and the timing of NIHD deaths during the feeding phase. Data were downloaded from commercial feedyard software and analyzed by constructing a generalized linear mixed model for both analyses. A binomial and Gaussian distributions for risk of NIHD death and timing of NIHD were utilized as link functions for their respective models. Our study population consisted of 28,950 cohorts (representing 4,596,205 cattle) that were placed in 22 U.S. commercial feedlots from January 01, 2016, to January 01, 2019. There were 3,282 cases of NIHD deaths from a population of 75,963 cattle that died during the 3-yr study period. Average cohort arrival weight’s effect on NIHD probability was influenced by arrival quarter and arrival year of placement (P < 0.01). Cohorts with steers were associated with a greater probability of at least one NIHD death (2.38%) compared with heifers (1.95%; P < 0.01). Increasing cohort size was associated with an increased probability of a cohort having at least one NIHD death (P < 0.01). The probability of a cohort having at least one NIHD death increased with increasing DOF categories from 1.51% in cattle fed 100 to 175 d, to 2.12% in cattle fed 176 to 250 d, and 2.87% for cattle fed 251 to 326 d. Cattle > 326 DOF were no different in the probability of a NIHD death compared with the other feeding categories. Timing of a NIHD death had a mean and median occurrence of 110 DOF with an interquartile range of 64 to 153 DOF. The effect of arrival weight on days at death was influenced by year placed with heavier cattle generally decreasing the model adjusted means of DOF at NIHD death. Arrival quarter was influenced by year placed on model adjusted means on the timing of a NIHD death. Steers with NIHD died later compared with heifers (P < 0.01) diagnosed with NIHD. In conclusion, multiple factors are associated with the probability and timing of a NIHD death. Probability of having at least one NIHD death within a cohort was low, and half of the deaths occurred before 110 DOF.

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

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

Evaluation of specific immunoglobulin A in nasal secretions and neutralizing antibodies in serum collected at multiple time points from young beef calves following intranasal or subcutaneous administration of a modified-live bovine respiratory syncytial virus vaccine

OBJECTIVE

To determine anti-bovine respiratory syncytial virus (BRSV) antibody titers for nasal secretions and serum from beef calves following administration of a modified-live (MLV) BRSV vaccine.

ANIMALS

60 healthy newborn purebred beef calves.

PROCEDURES

Calves were randomly assigned to 1 of 3 groups: intranasal (IN)-SC (IN MLV BRSV vaccine within 24 hours of birth and SC MLV BRSV vaccine at 2 months of age), SC-IN (SC MLV BRSV vaccine within 24 hours of birth and IN MLV BRSV vaccine at 2 months of age), or NO-IN (no vaccine within 24 hours of birth and IN MLV BRSV vaccine at 2 months of age). Nasal secretion and serum samples were collected for determination of anti-BRSV antibodies within 24 hours of birth and 2 and 6 months of age.

RESULTS

Titers of anti-BRSV IgA antibodies in nasal secretions and BRSV neutralizing antibodies in serum were similar among groups at each sampling time. Within 24 hours of birth, nasal anti-BRSV IgA titers were negligible. At 2 months, mean nasal anti-BRSV IgA titers for calves in IN-SC, SC-IN, and NO-IN groups were 192.84, 224.49, and 114.71, respectively.

CONCLUSIONS AND CLINICAL RELEVANCE

Concentrations of anti-BRSV IgA antibodies in the nasal secretions and BRSV neutralizing antibodies in the serum of young beef calves following an MLV BRSV vaccine protocol that consisted of IN or SC vaccine within 24 hours of birth and vice versa at 2 months of age were not different from that following only an IN MLV BRSV vaccine at 2 months of age. However, the lack of any differences may have been attributed to other factors.

PSV-5 Effect of Breed and Barn Location on Semen Quality at an Artificial Insemination Facility

A better understanding of the factors that influence collection and semen quality for AI sires is needed. Our objectives were to evaluate the effect of breed and environmental factors on semen characteristics from 49,086 ejaculates analyzed by a single technician at a beef semen collection facility. Bulls were housed in one of 5 barns based on health testing and purpose of semen collection. Multiple ejaculate characteristics were evaluated using regression models; fixed effects included breed, age, and barn. Ejaculate volume differed (P &lt; 0.001) between Angus (8.5 ml) and Horned Hereford (7.5 ml). Concentration of spermatozoa was lower (P &lt; 0.001) for Angus compared with Simmental, Charolais, and Horned Hereford (1009, 1100, 1252, and 1197 x 106/ml, respectively). Horned Hereford had greater (P &lt; 0.01) concentration of spermatozoa compared with Red Angus (1197 and 1046 x 106/ml, respectively). Simmental had greater (P &lt; 0.01) pre-freeze motility when compared with Angus, Red Angus, and Horned Hereford (54, 50, 49 and 49%, respectively). Average production of 0.5 CC frozen straws per collection was greater (P &lt; 0.001) for Simmental (244) when compared with Red Angus (205) and Angus (223). Pre-freeze motility (% motile) varied from 48% to 53% between the five barns (P &lt; 0.001). The average concentration of spermatozoa varied from 1000 (x 106/ml) to 1155 (x 106/ml), with Barn 1 producing the lowest per ejaculate (P &lt; 0.001). Bulls in Barn 1 produced a greater amount (P &lt; 0.001) of primary abnormalities than Barn 4 and more (P &lt; 0.001) secondary abnormalities than Barn 3. Overall, Simmental, when compared with Angus bulls, produced the greatest number of straws per collection, with the highest pre-freeze motility. Recognizing breed differences and the effect of barn location may help improve overall efficiency, and producer expectations of semen collection at this facility.

235 Resource Use for Beef Cattle in the North Central Great Plains

The sustainability of the beef industry has become a point of national interest, particularly the investment of land and water resources. Our objective was to estimate how much land and irrigation water are required to maintain a simulated Angus cow-calf operation in the North Central Great Plains (NCGP) for an average year. A stochastic model was used, which enabled consideration of biological variation. The model computed 100 iterations of a 24-year timeframe (1995–2018). The simulated herd had 100 breeding females with replacement heifers being retained annually. The nutrients required to maintain a body condition score 5 for each individual animal, adjusting for temperature and physiological state, were calculated. A stocking rate of 3.3 hectares (ha) per cow-calf pair and mature cow weight of 600 kg was set, which is representative of the NCGP. Replacement heifers were assumed to be 65% of mature cow weight and allotted 1.22 ha. Bred heifers were assumed to be 85% of mature cow weight and allotted 1.81 ha. The herd was assumed to be grazing from May 1 to October 31. A supplemented ration of 60% alfalfa and 40% corn was provided if an individual’s nutritional needs were not met. Animals were assumed to be delivered a base ration from November 1 to April 30, which consisted of 73% alfalfa, 19% wheat straw, and 8% corn. The amount of irrigation necessary to grow feed was determined by estimating evapotranspiration of each crop then subtracting the amount of precipitation during the growing season. Average crop yield was determined using county level data from the UDSA NASS to estimate how much land would be needed for feed production. Sustaining a 100 head cow-calf herd in the NCGP for an average year requires 103.5 million liters for irrigation, 1288.5 ha for crop production, 357 ha grazing land.

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.

96 Estimation of the genetic parameters of beef bull semen attributes

Fertility is a critical factor in cattle production because it directly relates to producing offspring to offset production costs. A number of semen attributes are believed to affect fertility and are frequently measured as part of routine breeding soundness exams or semen collection procedures. The objective of this study was to estimate the variance components for different semen quantity and quality traits that may influence fertility using phenotypes collected on 369 Simmental bulls. A total of 7,436 bull collection records including volume and concentration were obtained from two bull studs and evaluated utilizing a linear univariate animal model with repeated records. The five-generation pedigree used in the analysis consisted of 3,336 sires and 7,225 dams. Volume is the total amount of ejaculate and measured as milliliters of total ejaculate. Volume measurements ranged from 0.100 to 41.30 milliliters, with an average of 7.599 milliliters. Concentration is a measurement of millions of spermatozoa per milliliter. Concentration measurements ranged from 10 to 3,651 with an average of 1,053 million spermatozoa per milliliter. Fixed effects were included in the model if the effect was significant (P ≤ 0.05) for either backward or forward selection. Fixed effects included bull owner, collection center, location within center, collection day within year as a Julian day, collection year fit as class variables. Fixed effects fit as covariates included age of bull at collection (linear and quadratic), days since previous collection (linear and quadratic), and scrotal circumference (quadratic). Heritability estimates of volume and concentration were 0.43 ± 0.14 and 0.40 ± 0.15. These moderate heritability estimates indicate genetic improvement can be made in beef bull semen quality traits through selection.

PSV-13 Genetic parameters and quantitative trait loci for heat stress related traits in sheep

Greater selection emphasis has been placed on efficiency than on fitness in livestock populations over the last several decades. Heat stress is a concern in production systems due to the negative effects on production, reproduction, and immunity. The objective of the study was to estimate variance components and identify quantitative trait loci (QTL) for heat stress related traits in sheep. A total of 125 Dorper, Katahdin, and St. Croix ewes originating from four regions of the United States were selected for the experiment. Animals were separated into four trials due to facility limitations. Data were collected for each trial over four consecutive two-week periods in an environmentally controlled facility with targeted heat load index (HLI) for daytime/nighttime of 70/70, 85/77, 90/77, and 95/81. Body weight was collected three times per week and rectal temperature was collected weekly. Black globe temperature and humidity were measured every 15 minutes. Animals were genotyped using the Illumina OvineSNP50 BeadChip. After quality control, 49,396 effective single nucleotide polymorphisms were included in the univariate analysis performed with the BLUPF90 suite of programs. Fixed effects in the models included region of origin, breed, trial, and age as a covariate. Traits analyzed included rectal temperature at 95 HLI (RT95), feed intake at 95 HLI (FI95), and average daily gain for the period for HLI between 90 and 95 (ADG). Heritabilities for RT95, FI95, and ADG were 0.35, 0.10, and 0.10, respectively. Largest effect QTL were identified on chromosomes 23, 9, and 6 for RT95, chromosomes 9, 2, and 20 for FI95, and chromosomes 6, 1, and 5 for ADG. Many of the regions identified have also been associated with weight and carcass traits in other studies, but few had obvious connections to the heat stress related response. In conclusion, results suggest selection could improve heat tolerance in sheep.

199 Beef cattle genetic technology utilization - survey of stakeholders 2018

A web-based survey was conducted to understand the utilization of digital and genetic information by beef producers to inform the development of an online beef cattle selection decision support tool allowing creation of customized selection indices. Of 1,656 respondents, responses from U.S. seedstock, commercial cow-calf, stocker and feedlot sectors in 43 states formed a subset (n = 1,065) used in this analysis. Of respondents, 89% were owners, 76% and 47% identified involvement in the commercial cow-calf sector and seedstock sector, respectively (responses were permitted for multiple sectors). Respondents averaged 55 years old with 31 years beef industry experience. Percentages with 100 or fewer females for breeding, 100–500 cows, 500–1,000 cows and more than 1,000 cows were 47, 38, 8, and 6%, respectively. Bull purchases per year were 0 (21%), 1–2 (53%), 3–5 (15%), 6–10 (5%), 11–20 (2%), and &gt;20 (2%). Seedstock producers and industry meetings were most frequently cited as good sources of genetics information. Expected progeny differences were the most commonly reported/used source of genetic information. Nearly 70% (57%) reported keeping very or somewhat detailed animal production/performance (cost of production) records. The majority (90%) have a smart phone while only 45% use a tablet/iPad. Most producers (65%) used the internet as a source of agriculture data/information at least daily. Of all respondents, 44% spend 10 hours or more per week on the internet and 59% had greater than DSL speed. Two-thirds correctly identified the definition of a selection index with 80% indicating that selection indexes provide an efficient, consistent and objective method of ranking selection candidates. Nearly 64% would probably or definitely use an online tool to generate customized indexes. Willingness to pay annually for a tool varied with 36% only using it if free/sponsored, 17% would pay $50–99, 14% would pay $100–249, with 3% would pay $500 or more.

Selection for bull fertility: a review

Fertility is a critically important factor in cattle production because it directly relates to the ability to produce the offspring necessary to offset costs in production systems. Female fertility has received much attention and has been enhanced through assisted reproductive technologies, as well as genetic selection; however, improving bull fertility has been largely ignored. Improvements in bull reproductive performance are necessary to optimize the efficiency of cattle production. Selection and management to improve bull fertility not only have the potential to increase conception rates but also have the capacity to improve other economically relevant production traits. Bull fertility has reportedly been genetically correlated with traits such as average daily gain, heifer pregnancy, and calving interval. Published studies show that bull fertility traits are low to moderately heritable, indicating that improvements in bull fertility can be realized through selection. Although female fertility has continued to progress according to increasing conception rates, the reported correlation between male and female fertility is low, indicating that male fertility cannot be improved by selection for female fertility. Correlations between several bull fertility traits, such as concentration, number of spermatozoa, motility, and number of spermatozoa abnormalities, vary among studies. Using male fertility traits in selection indices would provide producers with more advanced selection tools. The objective of this review was to discuss current beef bull fertility measurements and to discuss the future of genetic evaluation of beef bull fertility and potential genetic improvement strategies.

Effect of vaccination of pregnant beef heifers on the concentrations of serum IgG and specific antibodies to bovine herpesvirus 1, bovine viral diarrhea virus 1, and bovine viral diarrhea virus 2 in heifers and calves

The objective of this study was to evaluate the effect of late-gestation vaccination of beef heifers with 2 doses of a killed-virus (KV) vaccine containing bovine herpesvirus 1 (BoHV-1), bovine viral diarrhea virus 1 (BVDV-1), and bovine viral diarrhea virus 2 (BVDV-2) on the serum concentrations of antibody against BoHV-1, BVDV-1, and BVDV-2 in heifers and their calves and on the IgG concentration in the calves. Of the 47 pregnant beef heifers selected, 26 received 2 doses of the vaccine at 6.5 to 8 mo of gestation (at pregnancy check), and 21 received 2 doses of saline. The mean log₂ serum titers of neutralizing antibody against BoHV-1, BVDV-1, and BVDV-2 before vaccination did not differ significantly between the treatment groups; however, at calving all 3 mean titers were significantly greater (P < 0.05) in the vaccinated heifers than in the control heifers. At 24 h after birth the mean serum IgG levels in the calves did not differ significantly between the 2 groups, at 30.18 and 32.28 g/L, respectively (P < 0.05); however, the mean log₂ serum titers of antibody to all 3 viruses were greater in the calves nursing colostrum from the vaccinated heifers than in the calves nursing colostrum from the nonvaccinated heifers and significantly so for BoHV-1 and BVDV-1 (P < 0.001 and P = 0.009, respectively). Thus, late-gestation vaccination of beef heifers could result in a greater and more consistent deposition of specific antibodies in colostrum, reducing the variability of initial titers in calves and increasing the duration of maternal immunity.

Environmental effects on water intake and water intake prediction in growing beef cattle

Water is an essential nutrient, but there are few recent studies that evaluate how much water individual beef cattle consume and how environmental factors affect an individual's water intake (WI). Most studies have focused on WI of whole pens rather than WI of individual animals. Thus, the objective of this study was to evaluate the impact of environmental parameters on individual-animal WI across different seasons and develop prediction equations to estimate WI, including within different environments and management protocols. Individual daily feed intake and WI records were collected on 579 crossbred steers for a 70-d period following a 21-d acclimation period for feed and water bunk training. Steers were fed in 5 separate groups over a 3-yr period from May 2014 to March 2017. Individual weights were collected every 14 d and weather data were retrieved from the Oklahoma Mesonet's Stillwater station. Differences in WI as a percent of body weight (WI%) were analyzed accounting for average temperature (TAVG), relative humidity (HAVG), solar radiation (SRAD), and wind speed (WSPD). Seasonal (summer vs. winter) and management differences (ad libitum vs. slick bunk) were examined. Regression analysis was utilized to generate 5 WI prediction equations (overall, summer, winter, slick, and ad libitum). There were significant (P < 0.05) differences in WI between all groups when no environmental parameters were included in the model. Although performance was more similar after accounting for all differences in weather variables, significant (P < 0.05) seasonal and feed management differences were still observed for WI%, but were less than 0.75% of steer body weight. The best linear predictors of daily WI (DWI) were dry mater intake (DMI), metabolic body weights (MWTS), TAVG, SRAD, HAVG, and WSPD. Slight differences in the coefficient of determinations for the various models were observed for the summer (0.34), winter (0.39), ad libitum (0.385), slick bunk (0.41), and overall models (0.40). Based on the moderate R2 values for the WI prediction equations, individual DWI can be predicted with reasonable accuracy based on the environmental conditions that are present, MWTS, and DMI consumed, but substantial variation exists in individual animal WI that is not accounted for by these models.

Test duration for water intake, ADG, and DMI in beef cattle

Water is an essential nutrient, but the effect it has on performance generally receives little attention. There are few systems and guidelines for collection of water intake (WI) phenotypes in beef cattle, which makes large-scale research on WI a challenge. The Beef Improvement Federation has established guidelines for feed intake (FI) and ADG tests, but no guidelines exist for WI. The goal of this study was to determine the test duration necessary for collection of accurate WI phenotypes. To facilitate this goal, individual daily WI and FI records were collected on 578 crossbred steers for a total of 70 d using an Insentec system at the Oklahoma State University Willard Sparks Beef Research Unit. Steers were fed in five groups and were individually weighed every 14 d. Within each group, steers were blocked by BW (low and high) and randomly assigned to one of four pens containing approximately 30 steers per pen. Each pen provided 103.0 m2 of shade and included an Insentec system containing six feed bunks and one water bunk. Steers were fed a constant diet across groups and DMI was calculated using the average of weekly percent DM within group. Average FI and WI for each animal were computed for increasingly large test durations (7, 14, 21, 28, 35, 42, 49, 56, 63, and 70 d), and ADG was calculated using a regression formed from BW taken every 14 d (0, 14, 28, 42, 56, and 70 d). Intervals for all traits were computed starting from both the beginning (day 0) and the end of the testing period (day 70). Pearson and Spearman correlations were computed for phenotypes from each shortened test period and for the full 70-d test. Minimum test duration was determined when the Pearson correlations were greater than 0.95 for each trait. Our results indicated that minimum test duration for WI, DMI, and ADG were 35, 42, and 70 d, respectively. No comparable studies exist for WI; however, our results for FI and ADG are consistent with those in the literature. Although further testing in other populations of cattle and areas of the country should take place, our results suggest that WI phenotypes can be collected concurrently with DMI, without extending test duration, even if following procedures for decoupled intake and gain tests.

Decision-making tools: stochastic simulation model accounting for the impacts of biological variation on success of bovine embryo transfer programs

The objective of the project was to create an economic risk analysis tool for user-defined embryo transfer (ET) programs as an aid in decision-making. Distributions defining the biological uncertainty for many reproductive outcomes are estimated through extensive literature review and limited industry sources. Applying the Latin hypercube variation of Monte Carlo simulation, a sample value from the descriptive distribution associated with each stochastic variable is included in each iteration of the simulation. Through large numbers of iterations with dynamic combinations of variable values, the process culminates in a distribution of possible values for the net present value, annuity equivalent net present value, and return on investment associated with the modeled embryo production scenario. Two options for embryo production, multiple ovulation embryo transfer (MOET) and in vitro embryo production (IVP) from aspirated oocytes, are modeled. Within both MOET and IVP, the use of unsorted or sex-sorted semen is considered, as well as the exception or inclusion of follicular synchronization and/or stimulation before ovum pick-up in IVP procedures. Pretransfer embryo selection through embryo biopsy can also be accounted for when considering in vivo derived embryos. Ample opportunity exists for the commercial application of in-depth, alternative ET scenario assessment afforded through stochastic simulation methodology that the ET industry has not yet fully exploited.

Reducing the period of data collection for intake and gain to improve response to selection for feed efficiency in beef cattle

Shortening the period of recording individual feed intake may improve selection response for feed efficiency by increasing the number of cattle that can be recorded given facilities of fixed capacity. Individual DMI and ADG records of 3,462 steers and 2,869 heifers over the entire intake recording period (range 62 to 154 d; mean 83 d; DMI83 and ADG83, respectively), DMI and ADG for the first 42 d of the recording period (DMI42 and ADG42, respectively), and postweaning ADG based on the difference between weaning and yearling weights (PADG) were analyzed. Genetic correlations among DMI42 and DMI83, ADG42 and ADG83, ADG42 and PADG, and ADG83 and PADG were 0.995, 0.962, 0.852, and 0.822, respectively. Four objective functions [feed:gain ratio in steers (FGS) and heifers (FGH); residual gain (RG); and residual feed intake (RFI)] based on DMI83 and ADG83 were considered. Indices using DMI42 and ADG42 (I42); DMI42 and PADG (IPW); and DMI42, ADG42, and PADG (IALL) were developed. Accuracy of the 5 EBV, 4 objectives, and 12 objective × index combinations were computed for all 12,033 animals in the pedigree. Accuracies of indices (IA) were summarized for animals with accuracies for objectives (OA) of 0.25, 0.5, 0.75, and 1. For the RG objective and animals with OA of 0.75, indices I42, IPW, and IALL had IA of 0.63, 0.55, and 0.67, respectively. Differences in IA increased with increased emphasis on ADG83 in the objective. Differences in IA between I42 and IPW usually increased with OA. Relative efficiency (RE) of selection on 42-d tests compared with 83 d was computed based on differences in IA and selection intensities of 5%, 25%, 50%, and 75% under the 83-d scenario, assuming 65% more animals could be tested for 42 d. For 25% selected for the RG objective, and animals with OA of 0.75, indices I42, IPW, and IALL had RE of 1.02, 0.90, and 1.10, respectively. As % selected, OA, and emphasis on DMI increased, RE increased. Relative efficiency varied considerably according to assumptions. One-half of the scenarios considered had RE > 1.15 with a maximum of 2.02 and 77% RE > 1.0. A shorter period of recording DMI can improve selection response for feed efficiency. Selection for the efficiency objectives would not affect PADG. It will be most effective if ADG over the period coinciding with intake recording and ADG over a much longer period of time are simultaneously included in a multiple-trait genetic evaluation with DMI and used in a selection index for efficiency.

Genotype by environment interaction for stayability of Red Angus in the United States

Bulls are used across a wide variety of environments through the use of artificial insemination. However, not all bulls rank the same for genetic merit in all environments. Sire selection could be more accurate via improved methods of characterization. The objective of this study was to evaluate the presence of genotype by environment (GxE) interaction for stayability in Red Angus in the United States. Environments were defined as nine regions within the continental United States with similar temperature-humidity indices. Stayability was defined as having a calf at age 4 given that the cow had a calf at age 2. A probit sire model was used to determine the heritability on the underlying scale. The percentage of females that calved at age 2 that also calved at age 4 ranged from 32.9 to 58.5% across regions and was 55.0% for the national data set. The heritability of stayability ranged from 0.10 to 0.57 across regions and was 0.12 for the national data set. Genetic correlations were estimated for stayability between all pairs of regions. An estimate of less than 0.80 indicates GxE at a level for concern. Genetic correlations between regions ranged from 0.32 to 0.87 and were <0.80 for 29 of 36 region pairs.

Genetic variance and covariance and breed differences for feed intake and average daily gain to improve feed efficiency in growing cattle

Feed costs are a major economic expense in finishing and developing cattle; however, collection of feed intake data is costly. Examining relationships among measures of growth and intake, including breed differences, could facilitate selection for efficient cattle. Objectives of this study were to estimate genetic parameters for growth and intake traits and compare indices for feed efficiency to accelerate selection response. On-test ADFI and on-test ADG (TESTADG) and postweaning ADG (PWADG) records for 5,606 finishing steers and growing heifers were collected at the U.S. Meat Animal Research Center in Clay Center, NE. On-test ADFI and ADG data were recorded over testing periods that ranged from 62 to 148 d. Individual quadratic regressions were fitted for BW on time, and TESTADG was predicted from the resulting equations. We included PWADG in the model to improve estimates of growth and intake parameters; PWADG was derived by dividing gain from weaning weight to yearling weight by the number of days between the weights. Genetic parameters were estimated using multiple-trait REML animal models with TESTADG, ADFI, and PWADG for both sexes as dependent variables. Fixed contemporary groups were cohorts of calves simultaneously tested, and covariates included age on test, age of dam, direct and maternal heterosis, and breed composition. Genetic correlations (SE) between steer TESTADG and ADFI, PWADG and ADFI, and TESTADG and PWADG were 0.33 (0.10), 0.59 (0.06), and 0.50 (0.09), respectively, and corresponding estimates for heifers were 0.66 (0.073), 0.77 (0.05), and 0.88 (0.05), respectively. Indices combining EBV for ADFI with EBV for ADG were developed and evaluated. Greater improvement in feed efficiency can be expected using an unrestricted index versus a restricted index. Heterosis significantly affected each trait contributing to greater ADFI and TESTADG. Breed additive effects were estimated for ADFI, TESTADG, and the efficiency indices.

Genotype by environment interactions for growth in Red Angus

Accuracy of sire selection is limited by how well animals are characterized for their environment. The objective of this study was to evaluate the presence of genotype × environment interactions (G×E) for birth weight (BiW) and weaning weight (WW) for Red Angus in the United States. Adjusted weights were provided by the Red Angus Association of America. Environments were defined as 9 regions within the continental United States with similar temperature-humidity indices. Mean weights of calves were determined for each region and for each sire's progeny within each region. A reaction norm (RN) for each bull was estimated by regressing the sire means on the region means weighted for the number of progeny of each sire. The range for BiW and WW RN was -1.3 to 4.0 and -1.7 to 2.8, respectively. The heritabilities of BiW and WW RN were 0.40 and 0.39, respectively. Phenotypic and genetic correlations between BiW and WW RN were 0.19 and 0.54, respectively. The phenotypic correlation of the progeny mean to the RN was -0.20 ( <0.05) and suggests that sires with higher means are more stable in progeny performance across environments. Weights in different regions were considered separate traits and genetic correlations were estimated between all pairs of regions as another method to determine G×E. Genetic correlations < 0.80 indicate G×E at a level for concern, but existed for only 2 of 36 estimates for BiW and 12 of 36 estimates for WW. Genetic correlations between different regions ranged from 0.74 to 0.96 for BiW and 0.62 to 0.99 for WW and indicate that sires tend to rank similarly across environments for these traits.

Phenotypic relationships between docility and reproduction in Angus heifers

The objective of this study was to elucidate the phenotypic relationships between docility and first-service AI conception rate in heifers. Data ( = 337) collected from 3 cooperator herds in Kansas at the start of synchronization protocol included exit velocity (EV), chute score (CS), fecal cortisol (FC), and blood serum cortisol (BC). Data were analyzed using logistic regression with 30-d pregnancy rate as the dependent variable. The model included the fixed effect of contemporary group and the covariates FC, BC, EV, CS, BW, and age. Correlation coefficients were calculated between all continuous traits. Pregnancy rate ranged from 34% to 60% between herds. Blood cortisol positively correlated with EV ( = 0.22, < 0.01), negatively correlated with age ( = -0.12, < 0.03), and tended to be negatively correlated with BW ( = -0.10, = 0.09). Exit velocity was positively correlated with CS ( = 0.24, < 0.01) and negatively correlated with BW ( = -0.15, < 0.01) and age ( = -0.12, < 0.03). Chute score negatively correlated with age ( = -0.14, < 0.01), and age and BW were moderately positively correlated ( = 0.42, < 0.01), as expected. Older, heavier animals generally had better temperament, as indicated by lower BC, EV, and CS. The power of our test could detect no significant predictors of 30-d pregnancy for the combined data from all ranches. When the data were divided by ranch, CS ( < 0.03) and BW ( < 0.01) were both significant predictors for 30-d pregnancy for ranch 1. The odds ratio estimate for CS has an inverse relationship with pregnancy, meaning that a 1-unit increase in average CS will reduce the probability of pregnancy at ranch 1 by 48.1%. Weight also has a negative impact on pregnancy because a 1-kg increase in BW will decrease the probability of pregnancy by 2.2%. Fertility is a complex trait that depends on many factors; our data suggest that docility is 1 factor that warrants further investigation.

Estimation of genetic parameters for udder traits in Hereford cattle

The objective was to estimate genetic parameters for udder traits in Hereford cattle. American Hereford Association (AHA) members initially recorded an overall score based on all udder characteristics. In 2008, the Beef Improvement Federation established guidelines, which were subsequently adopted by the AHA, for evaluating udder suspension and teat size. Therefore, a female was scored for either overall score or udder suspension and teat size for a single lactation, and females may be evaluated for overall score for a parity and then for udder suspension and teat size at a later parity. In all cases, subjective scores were assigned at parturition and ranged from 1 to 9, with a score of 9 considered ideal. Records on 48,191 animals and a 3-generation pedigree with 126,814 animals were obtained from the AHA, Kansas City, MO. These records contained repeated observations for overall score (n = 73,469), suspension (n = 38,412), and teat size (n = 38,412). Because the distribution of scores for all traits peaked at 7, a linear approximation was used in the analysis. Data were modeled using a multiple-trait animal model with random effects of additive genetic and permanent environment, fixed effect of contemporary group (herd-year-season), and a linear covariate for age in days. Heritability estimates (SE) for overall score, suspension, and teat size were 0.32 (0.01), 0.32 (0.01), and 0.28 (0.01), respectively. Through genetic selection for these traits, beef producers could improve udder traits. Repeatability estimates (SE) for overall score, suspension, and teat size were 0.45 (0.005), 0.47 (0.01), and 0.44 (0.01), respectively. Producers should continue evaluating udder traits repeatedly throughout a cow's lifetime. The phenotypic correlation (SE) between suspension and teat size was 0.64 (0.004) with 57% of records for suspension and teat size having the same score for both traits. The genetic correlations (SE) between teat size and suspension, overall score and teat size, and overall score and suspension were 0.81 (0.01), 0.71 (0.03), and 0.69 (0.03), respectively, and selection for one trait should result in correlated responses in the other traits. In conclusion, traits were moderately repeatable with scores from a parity being informative for subsequent parities. Because overall score, udder suspension, and teat size were moderately heritable with strong, positive genetic correlations, genetic improvement for these traits can be achieved through selection.

Comparison of Bayesian models to estimate direct genomic values in multi-breed commercial beef cattle

Background

While several studies have examined the accuracy of direct genomic breeding values (DGV) within and across purebred cattle populations, the accuracy of DGV in crossbred or multi-breed cattle populations has been less well examined. Interest in the use of genomic tools for both selection and management has increased within the hybrid seedstock and commercial cattle sectors and research is needed to determine their efficacy. We predicted DGV for six traits using training populations of various sizes and alternative Bayesian models for a population of 3240 crossbred animals. Our objective was to compare alternate models with different assumptions regarding the distributions of single nucleotide polymorphism (SNP) effects to determine the optimal model for enhancing feasibility of multi-breed DGV prediction for the commercial beef industry.

Results

Realized accuracies ranged from 0.40 to 0.78. Randomly assigning 60 to 70% of animals to training (n ≈ 2000 records) yielded DGV accuracies with the smallest coefficients of variation. Mixture models (BayesB95, BayesCπ) and models that allow SNP effects to be sampled from distributions with unequal variances (BayesA, BayesB95) were advantageous for traits that appear or are known to be influenced by large-effect genes. For other traits, models differed little in prediction accuracy (~0.3 to 0.6%), suggesting that they are mainly controlled by small-effect loci.

Conclusions

The proportion (60 to 70%) of data allocated to training that optimized DGV accuracy and minimized the coefficient of variation of accuracy was similar to large dairy populations. Larger effects were estimated for some SNPs using BayesA and BayesB95 models because they allow unequal SNP variances. This substantially increased DGV accuracy for Warner-Bratzler Shear Force, for which large-effect quantitative trait loci (QTL) are known, while no loss in accuracy was observed for traits that appear to follow the infinitesimal model. Large decreases in accuracy (up to 0.07) occurred when SNPs that presumably tag large-effect QTL were over-regressed towards the mean in BayesC0 analyses. The DGV accuracies achieved here indicate that genomic selection has predictive utility in the commercial beef industry and that using models that reflect the genomic architecture of the trait can have predictive advantages in multi-breed populations.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-015-0106-8) contains supplementary material, which is available to authorized users.

Bayesian genome-wide association analysis of growth and yearling ultrasound measures of carcass traits in Brangus heifers

Data from developing Brangus heifers (3/8 Brahman-Bos indicus × 5/8 Angus-Bos taurus; n ≈ 802 from 67 sires) registered with International Brangus Breeders Association were analyzed to detect QTL associated with growth traits and ultrasound measures of carcass traits. Genotypes were from BovineSNP50 (Infinium BeadChip, Illumina, San Diego, CA; 53,692 SNP). Phenotypes included BW collected at birth and ∼205 and 365 d of age, and yearling ultrasound assessment of LM area, percent intramuscular fat, and depth of rib fat. Simultaneous association of SNP windows with phenotype were undertaken with Bayes C analyses, using GenSel software. The SNP windows were ≈ 5 SNP in length. Analyses fitted a mixture model that treated SNP effects as random, with an assumed fraction pi = 0.999 having no effect on phenotype. Bootstrap analyses were used to obtain significance values for the SNP windows with the greatest contribution to observed variation. The SNP windows with P < 0.01 were considered as QTL associated with a trait in which case their location was queried from dbSNP and the presence of a previously reported QTL in that location was checked in CattleQTLdb. For 9 traits, QTL were mapped to 139 regions on 25 chromosomes. Forty-one of these QTL were already described in CattleQTLdb, so 98 are new additions. The SNP windows on chromosomes 1, 3, and 6 were associated with multiple traits (i.e., 205- and 365- d BW, and ADG from birth to 205 and 365 d of age). Several chromosomes harbored regions associated with multiple traits; however, the SNP that comprised the window often varied among traits (i.e., chromosomes 1, 3, 4, 5, 6, 7, 9, 10, 11, 13, 14, 15, 16, 20, 21, 22, 24, 28, and 29). Results from whole genome association of SNP with growth and ultrasound carcass traits in developing Brangus heifers confirmed several published QTL and detected several new QTL.

Heritability and Bayesian genome-wide association study of first service conception and pregnancy in Brangus heifers

Brangus [3/8 Brahman (Bos indicus) × 5/8 Angus (Bos taurus); n ≈ 800] heifers from 67 sires were used to estimate heritability and conduct a genome-wide association study (GWAS) for 2 binary fertility traits: first service conception (FSC) and heifer pregnancy (HPG). Genotypes were from 53,692 loci on the BovineSNP50 (Infinium Bead Chips, Illumina, San Diego, CA). Yearling heifers were estrous synchronized, bred by AI, and then exposed to natural service breeding. Reproductive ultrasound and DNA-based parentage testing were used to determine if the heifer conceived by AI or natural service, and code for FSC and HPG traits. Success rates for FSC and HPG were 53.3% and 78.0% ± 0.01%, and corresponding heritability estimates were 0.18 ± 0.07 and 0.10 ± 0.06, respectively. The models used in obtaining these heritability estimates and GWAS included fixed effects of year (i.e., 2005 to 2007), birth location, calving season, age of dam, and contemporary group. In GWAS, simultaneous associations of 1 Mb SNP windows with phenotype were undertaken with Bayes C analyses using GenSel software. The 1 Mb windows contained 21.3 ± 1.1 SNP. Analyses fitted a mixture model that treated SNP effects as random, with an assumed fraction pi = 0.9995 having no effect on phenotype. The windows that accounted for 1.0% of genetic variance were considered as QTL associated with FSC or HPG. Eighteen QTL existed on 15 chromosomes for the 2 traits. On average, each QTL accounted for 2.43% ± 0.2% of the genetic variance. Chromosome 8 harbored 2 QTL for FSC and 1 for HPG; however, these regions did not overlap. Chromosomes 3, 15, 16, 19, 24, 26, 27, 29, and X included QTL only for FSC, whereas chromosomes 2, 4, 10, 13, and 20 contained QTL only for HPG. The multitude of QTL detected for FSC and HPG in this GWAS involving Brangus heifers exemplifies the complex regulation of variation in heifer fertility traits of low heritability.

Genome-wide association analysis for quantitative trait loci influencing Warner-Bratzler shear force in five taurine cattle breeds

We performed a genome-wide association study for Warner–Bratzler shear force (WBSF), a measure of meat tenderness, by genotyping 3360 animals from five breeds with 54 790 BovineSNP50 and 96 putative single-nucleotide polymorphisms (SNPs) within μ-calpain [HUGO nomenclature calpain 1, (mu/I) large subunit; CAPN1] and calpastatin (CAST). Within- and across-breed analyses estimated SNP allele substitution effects (ASEs) by genomic best linear unbiased prediction (GBLUP) and variance components by restricted maximum likelihood under an animal model incorporating a genomic relationship matrix. GBLUP estimates of ASEs from the across-breed analysis were moderately correlated (0.31–0.66) with those from the individual within-breed analyses, indicating that prediction equations for molecular estimates of breeding value developed from across-breed analyses should be effective for genomic selection within breeds. We identified 79 genomic regions associated with WBSF in at least three breeds, but only eight were detected in all five breeds, suggesting that the within-breed analyses were underpowered, that different quantitative trait loci (QTL) underlie variation between breeds or that the BovineSNP50 SNP density is insufficient to detect common QTL among breeds. In the across-breed analysis, CAPN1 was followed by CAST as the most strongly associated WBSF QTL genome-wide, and associations with both were detected in all five breeds. We show that none of the four commercialized CAST and CAPN1SNP diagnostics are causal for associations with WBSF, and we putatively fine-map the CAPN1 causal mutation to a 4581-bp region. We estimate that variation in CAST and CAPN1 explains 1.02 and 1.85% of the phenotypic variation in WBSF respectively.

Genome-wide association analysis for feed efficiency in Angus cattle

Estimated breeding values for average daily feed intake (AFI; kg/day), residual feed intake (RFI; kg/day) and average daily gain (ADG; kg/day) were generated using a mixed linear model incorporating genomic relationships for 698 Angus steers genotyped with the Illumina BovineSNP50 assay. Association analyses of estimated breeding values (EBVs) were performed for 41 028 single nucleotide polymorphisms (SNPs), and permutation analysis was used to empirically establish the genome-wide significance threshold (P < 0.05) for each trait. SNPs significantly associated with each trait were used in a forward selection algorithm to identify genomic regions putatively harbouring genes with effects on each trait. A total of 53, 66 and 68 SNPs explained 54.12% (24.10%), 62.69% (29.85%) and 55.13% (26.54%) of the additive genetic variation (when accounting for the genomic relationships) in steer breeding values for AFI, RFI and ADG, respectively, within this population. Evaluation by pathway analysis revealed that many of these SNPs are in genomic regions that harbour genes with metabolic functions. The presence of genetic correlations between traits resulted in 13.2% of SNPs selected for AFI and 4.5% of SNPs selected for RFI also being selected for ADG in the analysis of breeding values. While our study identifies panels of SNPs significant for efficiency traits in our population, validation of all SNPs in independent populations will be necessary before commercialization.

Determinants of bovine thermal response to heat and solar radiation exposures in a field environment

Continuous exposure of cattle to summer heat in the absence of shade results in significant hyperthermia and impairs growth and general health. Reliable predictors of heat strain are needed to identify this condition. A 12-day study was conducted during a moderate summer heat period using 12 Angus x Simmental (Bos taurus) steers (533 ± 12 kg average body weight) to identify animal and ambient determinations of core body temperature (T(core)) and respiration rate (RR) responses to heat stress. Steers were provided standard diet and water ad libitum, and implanted intraperitoneally with telemetric transmitters to monitor T(core) hourly. Visual count of flank movement at 0800 and 1500 hours was used for RR. Dataloggers recorded air temperature (T(a)), and black globe temperatures (T(bg)) hourly to assess radiant heat load. Analysis was across four periods and 2 consecutive days averaged within each period. Average T(a) and T(bg) increased progressively from 21.7 to 30.3°C and 25.3 to 34.0°C, respectively, from the first to fourth periods. A model utilizing a quadratic function of T(a) explained the most variation in T(core) (R(2) = 0.56). A delay in response from 1 to 3 h did not significantly improve R(2) for this relationship. Measurements at 0800 and 1500 hours alone are sufficient to predict heat strain. Daily minimum core body temperature and initial 2-h rise in T(a) were predictors of maximum core temperature and RR. Further studies using continuous monitoring are needed to expand prediction of heat stress impact under different conditions.

Impact of reduced marker set estimation of genomic relationship matrices on genomic selection for feed efficiency in Angus cattle

BACKGROUND

Molecular estimates of breeding value are expected to increase selection response due to improvements in the accuracy of selection and a reduction in generation interval, particularly for traits that are difficult or expensive to record or are measured late in life. Several statistical methods for incorporating molecular data into breeding value estimation have been proposed, however, most studies have utilized simulated data in which the generated linkage disequilibrium may not represent the targeted livestock population. A genomic relationship matrix was developed for 698 Angus steers and 1,707 Angus sires using 41,028 single nucleotide polymorphisms and breeding values were estimated using feed efficiency phenotypes (average daily feed intake, residual feed intake, and average daily gain) recorded on the steers. The number of SNPs needed to accurately estimate a genomic relationship matrix was evaluated in this population.

RESULTS

Results were compared to estimates produced from pedigree-based mixed model analysis of 862 Angus steers with 34,864 identified paternal relatives but no female ancestors. Estimates of additive genetic variance and breeding value accuracies were similar for AFI and RFI using the numerator and genomic relationship matrices despite fewer animals in the genomic analysis. Bootstrap analyses indicated that 2,500-10,000 markers are required for robust estimation of genomic relationship matrices in cattle.

CONCLUSIONS

This research shows that breeding values and their accuracies may be estimated for commercially important sires for traits recorded in experimental populations without the need for pedigree data to establish identity by descent between members of the commercial and experimental populations when at least 2,500 SNPs are available for the generation of a genomic relationship matrix.

DNA-based paternity analysis and genetic evaluation in a large, commercial cattle ranch setting1

Deoxyribonucleic acid-based tests were used to assign paternity to 625 calves from a multiple-sire breeding pasture. There was a large variability in calf output and a large proportion of young bulls that did not sire any offspring. Five of 27 herd sires produced over 50% of the calves, whereas 10 sires produced no progeny and 9 of these were yearling bulls. A comparison was made between the paternity results obtained when using a DNA marker panel with a high (0.999), cumulative parentage exclusion probability (P(E)) and those obtained when using a marker panel with a lower P(E) (0.956). A large percentage (67%) of the calves had multiple qualifying sires when using the lower resolution panel. Assignment of the most probable sire using a likelihood-based method based on genotypic information resolved this problem in approximately 80% of the cases, resulting in 75% agreement between the 2 marker panels. The correlation between weaning weight, on-farm EPD based on pedigrees inferred from the 2 marker panels was 0.94 for the 24 bulls that sired progeny. Partial progeny assignments inferred from the lower resolution panel resulted in the generation of EPD for bulls that actually sired no progeny according to the high-P(E) panel, although the Beef Improvement Federation accuracies of EPD for these bulls were never greater than 0.14. Simulations were performed to model the effect of loci number, minor allele frequency, and the number of offspring per bull on the accuracy of genetic evaluations based on parentage determinations derived from SNP marker panels. The SNP marker panels of 36 and 40 loci produced EPD with accuracies nearly identical to those EPD resulting from use of the true pedigree. However, in field situations where factors including variable calf output per sire, large sire cohorts, relatedness among sires, low minor allele frequencies, and missing data can occur concurrently, the use of marker panels with a larger number of SNP loci will be required to obtain accurate on-farm EPD.

Genetic and phenotypic relationships of farrowing and weaning survival to birth and placental weights in pigs1

Data obtained during 4 generations of divergent selection for placental efficiency were used to determine factors influencing survival at farrowing and weaning in litters produced by first-parity females. Data were collected from 193 litters and included records on 2,053 individuals. Farrowing survival (FS) and weaning survival (WS) were considered traits of the piglet and were scored 1 if the individual was alive at a time point or 0 if dead. Estimates of (co)variance components for direct and maternal additive genetic effects for FS and WS were obtained using an animal model and computed with the MTDFREML program. Estimates of direct heritability were 0.16 for FS and 0.18 for WS. Estimates of maternal heritability were 0.14 for FS and 0.10 for WS. Genetic correlation estimates between direct and maternal effects were high and negative for both traits. The direct genetic correlation between FS and WS was 0.92. Variables associated with FS and WS were determined using logistic regression procedures. Birth weight (BRW), placental weight, their interaction, and total born can be used as predictors of survival at farrowing in the absence of estimates of genetic merit for survival. The same model, excluding total number born, was the best model for predicting WS. In the presence of BRW information, placental efficiency did not improve the prediction of survival. While it was clearly disadvantageous for a piglet to be below the litter mean in BRW, being above the mean did not provide a substantial advantage in survival. Results from this analysis suggest that it is possible to select for increased survival at farrowing and at weaning. Information on a piglet's BRW, placental weight, litter average BRW, and deviation from litter average BRW can be used to optimize those values at levels resulting in high survival probability.

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.