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Methane (CH 4 ) 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, CH 4 production from enteric fermentation impacts all three pillars of sustainability: environmental, social, and economic. A variety of factors influence the quantity of CH 4 produced during enteric fermentation, including characteristics of the rumen and feed composition. There are several methodologies available to either quantify or estimate CH 4 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 CH 4 production have been estimated using the different CH 4 quantification methods. Agreement in both the amounts of CH 4 emitted and heritability estimates of CH 4 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 CH 4 production, methods to quantify CH 4 production for genetic evaluation, and genetic parameters of CH 4 production in beef cattle., (© The Author(s) 2024. Published by Oxford University Press on behalf of the American Society of Animal Science.)

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., (Published by Oxford University Press on behalf of the American Society of Animal Science 2023.)

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 (CH4), carbon dioxide (CO2), and oxygen (O2) 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 CH4, CO2, and O2 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 nongrazing (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., (© The Author(s) 2023. Published by Oxford University Press on behalf of the American Society of Animal Science. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

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., (© The Author(s) 2023. Published by Oxford University Press on behalf of the American Society of Animal Science. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background: Cattle production is dependent upon fertility because it results in 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 perform a single-step genome-wide association study (ssGWAS) for beef bull semen attributes. Beef bull fertility phenotypes including volume (VOL), concentration (CONC), number of spermatozoa (NSP), initial motility (IMot), post-thaw motility (PTMot), three-hour post-thaw motility (3HRPTMot), percentage of normal spermatozoa (%NORM), primary abnormalities (PRIM), and secondary abnormalities (SEC) were obtained from two artificial insemination (AI) centers. A total of 1819 Angus bulls with 50,624 collection records were used for ssGWAS. A five-generation pedigree was obtained from the American Angus Association and consisted of 6521 sires and 17,136 dams. Genotypes on 1163 bulls were also obtained from the American Angus Association and utilized in ssGWAS., Results: A multi-trait animal model was used for the estimation of single nucleotide polymorphism (SNP) effects. Significant SNP were those with a -log 10 P-value threshold greater than 4.0. Volume, CONC, NSP, IMot, PTMot, 3HRPTMot, %NORM, PRIM, and SEC have five, three, six, seven, two, six, six, and two genome-wide significant SNP, respectively., Conclusions: Several significant SNP were determined to be near or within quantitative trait loci (QTL) associated with beef bull semen attributes. In addition, genes associated with fertility were found to contain or be near the significant SNP found in the study. The results indicate there are regions of the genome that impact fertility, proving inclusion of genomic information into genetic evaluation should be advantageous for genetic improvement of male fertility traits., (© 2022. The Author(s).)

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., (© The Author(s) 2021. Published by Oxford University Press on behalf of the American Society of Animal Science. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

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., (© The Author(s) 2021. Published by Oxford University Press on behalf of the American Society of Animal Science. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

In the future, water may not be as readily available due to increases in competition from a growing human population, wildlife, and other agricultural sectors, making selection for water efficiency of beef cattle increasingly important. Substantial selection emphasis has recently been placed on feed efficiency in an effort to reduce production costs, but no emphasis has been placed on making cattle more water efficient due to lack of data. Thus, the objective of this study was to calculate water efficiency metrics for cattle and evaluate their relationship to growth, feed intake (FI), and feed efficiency. Individual daily FI and water intake (WI) records were collected on 578 crossbred steers over a 70-d test period. Animals with low water intake ate less feed, had lower gains, and were more water efficient (as defined by water to gain ratio, W/G, and residual water intake, RWI). However, the amount of water consumed by animals had minimal phenotypic relationship with feed efficiency (residual feed intake [RFI], R2 = 0.1050 and feed to gain ratio (F/G) ratio R2 = 0.0726). Cattle that had low DMI consumed less water, had lower gains, had lower RFI, and had higher F/G. The level of feed consumed had minimal relationship with water efficiency. WI, W/G, RWI, and ADG had moderate heritability estimates of 0.39, 0.39, 0.37, and 0.37, respectively. High heritability estimates were observed for DMI and RFI (0.67 and 0.65, respectively). Feed to gain had a low heritability estimate of 0.16. WI had a strong positive genetic correlation with W/G (0.99) and RWI (0.88), thus selecting for decreased WI should also make cattle more water efficient. The genetic correlation between WI and ADG was 0.05; thus, selecting for low WI cattle should have little effect on growth. There is a low to moderate genetic correlation between WI and DMI (0.34). RWI has a positive genetic correlation with W/G ratio (0.89) and F/G ratio (0.42) and is negatively genetically correlated with RFI (-0.57). Water to gain and F/G had a strong positive genetic correlation (0.68). RFI has a positive genetic correlation with W/G ratio (0.37) and F/G (0.88). Minimal antagonisms seem to be present between WI and ADG, although it should be noted that standard errors were large and often not significantly different from zero due to the small sample size. However, care should be taken to ensure that unintended changes do not occur in DMI or other production traits and incorporation of WI into a selection index would likely prove to be the most effective method for selection., (Published by Oxford University Press on behalf of the American Society of Animal Science 2019.)

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., (© The Author(s) 2019. Published by Oxford University Press on behalf of the American Society of Animal Science.)

MicroRNA (miRNA) are abundant in milk, and likely have regulatory activity involving lactation and immunity. The objective of this study was to determine the miRNA profile in colostrum of overconditioned cows compared with cows of more moderate body condition score (BCS) at calving. Multiparous cows with either high (≥4.0 on a scale of 1 to 5; n = 7) or moderate BCS (2.75 to 3.50; n = 9) in the week before parturition were selected from a commercial dairy herd. Blood and colostrum were sampled within 24 h after calving. Blood serum was analyzed for free fatty acid (FFA) concentration. MicroRNA was isolated from colostrum samples after removing milk fat and cells. MicroRNA were sequenced, and reads were mapped to the bovine genome and to the existing database of miRNA at miRBase.org. Two programs, Oasis 2.0 and miRDeep2, were employed in parallel for read alignment, and analysis of miRNA count data was performed using DESeq2. Identification of differentially expressed miRNA from DESeq2 was not affected by the differences in miRNA detected by the 2 mapping programs. Most abundant miRNA included miR-30a, miR-148a, miR-181a, let-7f, miR-26a, miR-21, miR-22, and miR-92a. Large-scale shifts in miRNA profile were not observed; however, colostrum of cows with high BCS contained less miR-486, which has been linked with altered glucose metabolism. Colostrum from cows with elevated serum FFA contained less miR-885, which may be connected to hepatic function during the transition period. Potential functions of abundant miRNA suggest involvement in development and maintenance of cellular function in the mammary gland, with the additional possibility of influencing neonatal tissue and immune system development., (Copyright © 2019 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

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.

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.

The Insentec Roughage Intake Control (RIC) system has been validated for the collection of water intake; however, this system has not been validated for water restriction. The objective of this validation was to evaluate the agreement between direct observations and automated intakes collected by the RIC system under both ad libitum and restricted water conditions. A total of 239 crossbred steers were used in a 3-d validation trial, which assessed intake values generated by the RIC electronic intake monitoring system for both ad libitum water intake ( = 122; BASE) and restricted water intake ( = 117; RES). Direct human observations were collected on 4 Insentec water bins for three 24-h periods and three 12-h periods for BASE and RES, respectively. An intake event was noted by the observer when the electronic identification of the animal was read by the transponder and the gate lowered, and starting and ending bin weights were recorded for each intake event. Data from direct observations across each validation period were compared to automated observations generated from the RIC system. Missing beginning or ending weight values for visual observations occasionally occurred due to the observer being unable to capture the value before the monitor changed when bin activity was high. To estimate the impact of these missing values, analyses denoted as OBS were completed with the incomplete record coded as missing data. These analyses were contrasted with analyses where observations with a single missing beginning or end weight (but not both) were assumed to be identical to that which was recorded by the Insentec system (OBS). Difference in mean total intake across BASE steers was 0.60 ± 2.06 kg OBS (0.54 ± 1.99 kg OBS) greater for system observations than visual observations. The comparison of mean total intake across the 3 RES validation days was 0.53 ± 2.30 kg OBS (0.13 ± 1.83 kg OBS) greater for system observations than direct observations. Day was not a significant source of error in this study ( > 0.05). These results indicate that the system was capable of limiting water of individual animals with reasonable accuracy, although errors are slightly higher during water restriction than during ad libitum access. The Insentec system is a suitable resource for monitoring individual water intake of growing, group-housed steers under ad libitum and restricted water conditions.

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.

The domestication and development of cattle has considerably impacted human societies, but the histories of cattle breeds and populations have been poorly understood especially for African, Asian, and American breeds. Using genotypes from 43,043 autosomal single nucleotide polymorphism markers scored in 1,543 animals, we evaluate the population structure of 134 domesticated bovid breeds. Regardless of the analytical method or sample subset, the three major groups of Asian indicine, Eurasian taurine, and African taurine were consistently observed. Patterns of geographic dispersal resulting from co-migration with humans and exportation are recognizable in phylogenetic networks. All analytical methods reveal patterns of hybridization which occurred after divergence. Using 19 breeds, we map the cline of indicine introgression into Africa. We infer that African taurine possess a large portion of wild African auroch ancestry, causing their divergence from Eurasian taurine. We detect exportation patterns in Asia and identify a cline of Eurasian taurine/indicine hybridization in Asia. We also identify the influence of species other than Bos taurus taurus and B. t. indicus in the formation of Asian breeds. We detect the pronounced influence of Shorthorn cattle in the formation of European breeds. Iberian and Italian cattle possess introgression from African taurine. American Criollo cattle originate from Iberia, and not directly from Africa with African ancestry inherited via Iberian ancestors. Indicine introgression into American cattle occurred in the Americas, and not Europe. We argue that cattle migration, movement and trading followed by admixture have been important forces in shaping modern bovine genomic variation.

Background: The domestication and subsequent selection by humans to create breeds and biological types of cattle undoubtedly altered the patterning of variation within their genomes. Strong selection to fix advantageous large-effect mutations underlying domesticability, breed characteristics or productivity created selective sweeps in which variation was lost in the chromosomal region flanking the selected allele. Selective sweeps have now been identified in the genomes of many animal species including humans, dogs, horses, and chickens. Here, we attempt to identify and characterise regions of the bovine genome that have been subjected to selective sweeps., Results: Two datasets were used for the discovery and validation of selective sweeps via the fixation of alleles at a series of contiguous SNP loci. BovineSNP50 data were used to identify 28 putative sweep regions among 14 diverse cattle breeds. Affymetrix BOS 1 prescreening assay data for five breeds were used to identify 85 regions and validate 5 regions identified using the BovineSNP50 data. Many genes are located within these regions and the lack of sequence data for the analysed breeds precludes the nomination of selected genes or variants and limits the prediction of the selected phenotypes. However, phenotypes that we predict to have historically been under strong selection include horned-polled, coat colour, stature, ear morphology, and behaviour., Conclusions: The bias towards common SNPs in the design of the BovineSNP50 assay led to the identification of recent selective sweeps associated with breed formation and common to only a small number of breeds rather than ancient events associated with domestication which could potentially be common to all European taurines. The limited SNP density, or marker resolution, of the BovineSNP50 assay significantly impacted the rate of false discovery of selective sweeps, however, we found sweeps in common between breeds which were confirmed using an ultra-high-density assay scored in a small number of animals from a subset of the breeds. No sweep regions were shared between indicine and taurine breeds reflecting their divergent selection histories and the very different environmental habitats to which these sub-species have adapted.

Background: In national evaluations, direct genomic breeding values can be considered as correlated traits to those for which phenotypes are available for traditional estimation of breeding values. For this purpose, estimates of the accuracy of direct genomic breeding values expressed as genetic correlations between traits and their respective direct genomic breeding values are required., Methods: We derived direct genomic breeding values for 2239 registered Limousin and 2703 registered Simmental beef cattle genotyped with either the Illumina BovineSNP50 BeadChip or the Illumina BovineHD BeadChip. For the 264 Simmental animals that were genotyped with the BovineHD BeadChip, genotypes for markers present on the BovineSNP50 BeadChip were extracted. Deregressed estimated breeding values were used as observations in weighted analyses that estimated marker effects to derive direct genomic breeding values for each breed. For each breed, genotyped individuals were clustered into five groups using K-means clustering, with the aim of increasing within-group and decreasing between-group pedigree relationships. Cross-validation was performed five times for each breed, using four groups for training and the fifth group for validation. For each trait, we then applied a weighted bivariate analysis of the direct genomic breeding values of genotyped animals from all five validation sets and their corresponding deregressed estimated breeding values to estimate variance and covariance components., Results: After minimizing relationships between training and validation groups, estimated genetic correlations between each trait and its direct genomic breeding values ranged from 0.39 to 0.76 in Limousin and from 0.29 to 0.65 in Simmental. The efficiency of selection based on direct genomic breeding values relative to selection based on parent average information ranged from 0.68 to 1.28 in genotyped Limousin and from 0.51 to 1.44 in genotyped Simmental animals. The efficiencies were higher for 323 non-genotyped young Simmental animals, born after January 2012, and ranged from 0.60 to 2.04., Conclusions: Direct genomic breeding values show promise for routine use by Limousin and Simmental breeders to improve the accuracy of predicted genetic merit of their animals at a young age and increase response to selection. Benefits from selecting on direct genomic breeding values are greater for breeders who use natural mating sires in their herds than for those who use artificial insemination sires. Producers with unregistered commercial Limousin and Simmental cattle could also benefit from being able to identify genetically superior animals in their herds, an opportunity that has in the past been limited to seed stock animals.

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 CAPN1 SNP 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., (© 2012 The Authors, Animal Genetics © 2012 Stichting International Foundation for Animal Genetics.)

Background: Several methods have recently been developed to identify regions of the genome that have been exposed to strong selection. However, recent theoretical and empirical work suggests that polygenic models are required to identify the genomic regions that are more moderately responding to ongoing selection on complex traits. We examine the effects of multi-trait selection on the genome of a population of US registered Angus beef cattle born over a 50-year period representing approximately 10 generations of selection. We present results from the application of a quantitative genetic model, called Birth Date Selection Mapping, to identify signatures of recent ongoing selection., Results: We show that US Angus cattle have been systematically selected to alter their mean additive genetic merit for most of the 16 production traits routinely recorded by breeders. Using Birth Date Selection Mapping, we estimate the time-dependency of allele frequency for 44,817 SNP loci using genomic best linear unbiased prediction, generalized least squares, and BayesCπ analyses. Finally, we reconstruct the primary phenotypes that have historically been exposed to selection from a genome-wide analysis of the 16 production traits and gene ontology enrichment analysis., Conclusions: We demonstrate that Birth Date Selection Mapping utilizing mixed models corrects for time-dependent pedigree sampling effects that lead to spurious SNP associations and reveals genomic signatures of ongoing selection on complex traits. Because multiple traits have historically been selected in concert and most quantitative trait loci have small effects, selection has incrementally altered allele frequencies throughout the genome. Two quantitative trait loci of large effect were not the most strongly selected of the loci due to their antagonistic pleiotropic effects on strongly selected phenotypes. Birth Date Selection Mapping may readily be extended to temporally-stratified human or model organism populations.

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., (© 2011 The Authors, Animal Genetics © 2011 Stichting International Foundation for Animal Genetics.)

Background: Genomic selection is a recently developed technology that is beginning to revolutionize animal breeding. The objective of this study was to estimate marker effects to derive prediction equations for direct genomic values for 16 routinely recorded traits of American Angus beef cattle and quantify corresponding accuracies of prediction., Methods: Deregressed estimated breeding values were used as observations in a weighted analysis to derive direct genomic values for 3570 sires genotyped using the Illumina BovineSNP50 BeadChip. These bulls were clustered into five groups using K-means clustering on pedigree estimates of additive genetic relationships between animals, with the aim of increasing within-group and decreasing between-group relationships. All five combinations of four groups were used for model training, with cross-validation performed in the group not used in training. Bivariate animal models were used for each trait to estimate the genetic correlation between deregressed estimated breeding values and direct genomic values., Results: Accuracies of direct genomic values ranged from 0.22 to 0.69 for the studied traits, with an average of 0.44. Predictions were more accurate when animals within the validation group were more closely related to animals in the training set. When training and validation sets were formed by random allocation, the accuracies of direct genomic values ranged from 0.38 to 0.85, with an average of 0.65, reflecting the greater relationship between animals in training and validation. The accuracies of direct genomic values obtained from training on older animals and validating in younger animals were intermediate to the accuracies obtained from K-means clustering and random clustering for most traits. The genetic correlation between deregressed estimated breeding values and direct genomic values ranged from 0.15 to 0.80 for the traits studied., Conclusions: These results suggest that genomic estimates of genetic merit can be produced in beef cattle at a young age but the recurrent inclusion of genotyped sires in retraining analyses will be necessary to routinely produce for the industry the direct genomic values with the highest accuracy.

To gain insight into the number of loci of large effect that underlie variation in cattle, a quantitative trait locus (QTL) scan for 14 economically important traits was performed in two commercial Angus populations using 390 microsatellites, 11 single nucleotide polymorphisms (SNPs) and one duplication loci. The first population comprised 1769 registered Angus bulls born between 1955 and 2003, with Expected Progeny Differences computed by the American Angus Association. The second comprised 38 half-sib families containing 1622 steers with six post-natal growth and carcass phenotypes. Linkage analysis was performed by half-sib least squares regression with gridqtl or Bayesian Markov chain Monte Carlo analysis of complex pedigrees with loki. Of the 673 detected QTL, only 118 have previously been reported, reflecting both the conservative approach to QTL reporting in the literature, and the more liberal approach taken in this study. From 33 to 71% of the genetic variance and 35 to 56% of the phenotypic variance in each trait was explained by the detected QTL. To analyse the effects of 11 SNPs and one duplication locus within candidate genes on each trait, a single marker analysis was performed by fitting an additive allele substitution model in both mapping populations. There were 53 associations detected between the SNP/duplication loci and traits with -log(10) P(nominal) ≥ 4.0, where each association explained 0.92% to 4.4% of the genetic variance and 0.01% to 1.86% of the phenotypic variance. Of these associations, only six SNP/duplication loci were located within 8 cM of a QTL peak for the trait, with two being located at the QTL peak: SST&#95;DG156121:c.362A>G for ribeye muscle area and TG&#95;X05380:c.422C>T for calving ease. Strong associations between several SNP/duplication loci and trait variation were obtained in the absence of any detected linked QTL. However, we reject the causality of several commercialized DNA tests, including an association between TG&#95;X05380:c.422C>T and marbling in Angus cattle., (© 2010 The Authors, Animal Genetics © 2010 Stichting International Foundation for Animal Genetics.)

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.

Next generation sequencing platforms have democratized genome sequencing. Large genome centers are no longer required to produce genome sequences costing millions. A few lanes of paired-end sequence on an Illumina Genome Analyzer, costing < $10,000, will produce more sequence than generated only a few years ago to produce the human and cow assemblies. The de novo assembly of large numbers of short reads into a high-quality whole-genome sequence is now technically feasible and will allow the whole genome sequencing and assembly of a broad spectrum of ruminant species. Next-generation sequencing instruments are also proving very useful for transcriptome or resequencing projects in which the entire RNA population produced by a tissue, or the entire genomes of individual animals are sequenced, and the produced reads are aligned to a reference assembly. We have used this strategy to examine gene expression differences in tissues from cattle differing in feed efficiency, to perform genome-wide single nucleotide polymorphism discovery for the construction of ultrahigh-density genotyping assays, and in combination with genome-wide association analysis, for the identification of mutations responsible for Mendelian diseases. The new 800K SNP bovine genotyping assays possess the resolution to map trait associations to the locations of individual genes and the 45 million polymorphisms identified in > 180X genome sequence coverage on over 200 animals can be queried to identify the polymorphisms present within positional candidate genes. These new tools should rapidly allow the identification of genes and mutations underlying variation in cattle production and reproductive traits.

The Pecorans (higher ruminants) are believed to have rapidly speciated in the Mid-Eocene, resulting in five distinct extant families: Antilocapridae, Giraffidae, Moschidae, Cervidae, and Bovidae. Due to the rapid radiation, the Pecoran phylogeny has proven difficult to resolve, and 11 of the 15 possible rooted phylogenies describing ancestral relationships among the Antilocapridae, Giraffidae, Cervidae, and Bovidae have each been argued as representations of the true phylogeny. Here we demonstrate that a genome-wide single nucleotide polymorphism (SNP) genotyping platform designed for one species can be used to genotype ancient DNA from an extinct species and DNA from species diverged up to 29 million years ago and that the produced genotypes can be used to resolve the phylogeny for this rapidly radiated infraorder. We used a high-throughput assay with 54,693 SNP loci developed for Bos taurus taurus to rapidly genotype 678 individuals representing 61 Pecoran species. We produced a highly resolved phylogeny for this diverse group based upon 40,843 genome-wide SNP, which is five times as many informative characters as have previously been analyzed. We also establish a method to amplify and screen genomic information from extinct species, and place Bison priscus within the Bovidae. The quality of genotype calls and the placement of samples within a well-supported phylogeny may provide an important test for validating the fidelity and integrity of ancient samples. Finally, we constructed a phylogenomic network to accurately describe the relationships between 48 cattle breeds and facilitate inferences concerning the history of domestication and breed formation.