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Despite the multiple definitions currently used to express enteric methane emissions from ruminants, no consensus has been reached on the most appropriate definition. The objective of the present study was to explore alternative trait definitions reflecting animal level differences in enteric methane emissions in growing cattle. It is likely that no single methane trait definition will be best suited to all intended use cases, but at least, knowing the relationships between the different traits may help inform the selection process. The research aimed to understand the complex interrelationships between traditional and novel methane traits and their association with performance traits across multiple breeds and sexes of cattle; also of interest was the extent of variability in daily enteric methane emissions independent of performance traits like feed intake, growth and live-weight. Methane and carbon dioxide data were collected using the Greenfeed system on 939 growing crossbred cattle from a commercial feedlot. Performance traits including feed intake, feeding behavior, liveweight, live animal ultrasound, subjectively scored skeletal and muscular traits, and slaughter data were also available. A total of 13 different methane traits were generated, including (average) daily methane production, five ratio traits and seven residual methane (RMP) traits. The RMP traits were defined as methane production adjusted statistically for different combinations of the performance traits of energy intake, liveweight, average daily gain and carcass weight; terms reflecting systematic effects were also included in the fixed effects linear models. Of the performance traits investigated, liveweight and energy intake individually explained more of the variability in methane production than growth rate or fat. All definitions of RMP were strongly phenotypically correlated with each other (>0.90) as well as with methane production itself (>0.86); the RMP traits were also moderately correlated with the methane ratio traits (>0.57). The dataset included heifers, steers and bulls; bulls were either fed a total mixed ration or ad lib concentrates. When all sexes fed total mixed ration were compared, bulls, on average, emitted the most enteric methane per day of 269.53g, while heifers and steers produced 237.54g and 253.26g, respectively. Breed differences in the methane traits existed, with Limousins, on average, producing the least amount of methane of the breeds investigated. Herefords and Montbéliardes produced 124.50g and 130.77g more methane per day, respectively, than Limousins. The most efficient 10% of test-day records, as defined by daily methane independent of both energy intake and liveweight emitted, on average, 54.60 g/d less methane than animals that were average for daily methane independent of both energy intake and liveweight. This equates to 6.5kg less methane production per animal over a 120-day finishing period for the same feed intake and liveweight., (© The Author(s) 2024. Published by Oxford University Press on behalf of the American Society of Animal Science.)

Genetic selection has been identified as a promising approach for reducing enteric methane (CH4) emissions; a prerequisite for genetic evaluations; however, these are estimates of the necessary genetic parameters based on a population representative of where the genetic evaluations will be used. The objective of this study was, therefore, to derive genetic parameters for a series of definitions of CH4, carbon dioxide (CO2), and dry matter intake (DMI) as well as genetic correlations between CH4, CO2, and DMI in a bid to address the paucity of studies involving methane emissions measured in beef cattle using GreenFeed systems. Lastly, estimated breeding values (EBV) were generated for nine alternative definitions of CH4 using the derived genetic parameters; the EBV were validated against both phenotypic performance (adjusted for non-genetic effects) and the Legarra and Reverter method comparing EBV generated for a subset of the dataset compared to EBV generated from the entire dataset. Individual animal CH4 and CO2 records were available from a population of 1,508 multi-breed growing beef cattle using 10 GreenFeed Emission Monitoring systems. Nine trait definitions for CH4 and CO2 were derived: individual spot measures, the average of all spot measures within a 3-h, 6-h, 12-h, 1-d, 5-d, 10-d, and 15-d period and the average of all spot measures across the full test period (20 to 114 d on test). Heritability estimates from 1,155 animals, for CH4, increased as the length of the averaging period increased and ranged from 0.09 ± 0.03 for the individual spot measures trait to 0.43 ± 0.11 for the full test average trait; a similar trend existed for CO2 with the estimated heritability ranging from 0.17 ± 0.04 to 0.50 ± 0.11. Enteric CH4 was moderately to strongly genetically correlated with DMI with a genetic correlation of 0.72 ± 0.02 between the spot measures of CH4 and a 1-d average DMI. Correlations, adjusted for heritability, between the adjusted phenotype and (parental average) EBV ranged from 0.56 to 1.14 across CH4 definitions and the slope between the adjusted phenotype and EBV ranged from 0.92 to 1.16 (expectation = 1). Validation results from the Legarra and Reverter regression method revealed a level bias of between -0.81 and -0.45, a dispersion bias of between 0.93 and 1.17, and ratio accuracy (ratio of the partial evaluation accuracies on whole evaluation accuracies) from 0.28 to 0.38. While EBV validation results yielded no consensus, CH4 is a moderately heritable trait, and selection for reduced CH4 is achievable., (© The Author(s) 2024. Published by Oxford University Press on behalf of the American Society of Animal Science.)

A fully functional myostatin gene inhibits muscle fiber growth. The objective of the present study was to quantify the association between 21 known myostatin mutations with both calving and carcass traits in 12 cattle breeds. The myostatin genotypes of 32,770 dam-progeny combinations were used in the association analysis of calving dystocia, with the genotypes of 129,803 animals used in the mixed model association analyses of carcass weight, conformation, and fat score. The mixed model included additive genetic, maternal, and permanent environmental effects where appropriate. The mutant genotypes of nt821, Q204X, and F94L were all associated (P < 0.01) with more calving difficulty when present in either the dam or the progeny. The nt821 deletion had the greatest association with calving difficulty when the homozygous deletion was present in either the calf (0.37 points greater calving difficulty score relative to calves carrying no copies of the deletion based on a one to four scale) or the dam (1.30 points greater calving difficulty score relative to dams carrying no copies of the deletion), although the association between the calf's nt821 genotype and calving difficulty differed depending on the nt821 genotype of the dam. With the exception of nt748&#95;78, nt414, and nt374&#95;51, all other seven segregating myostatin variants were associated (range of allele substitution effect size relative to animals with no copies of the mutant allele) with carcass weight (2.36 kg lighter to 15.56 kg heavier), all 10 segregating variants with conformation (0.15 units less conformed to 2.24 units more conformed assessed on a scale of 1 to 15), and all segregating variants other than E226X with carcass fat (0.23 units less carcass fat cover to 3.85 units more carcass fat cover assessed on a scale of 1 to 15). Of these, the F94L, Q204X, and nt821 mutations generally had the greatest association with all three carcass traits, giving rise to heavier and more conformed carcasses. Despite the antagonistic genetic relationship between calving difficulty and carcass traits, the nt374&#95;51, F94L, and E226X mutations were all associated with improved carcass merit while having minimal expected consequences on calving difficulty. Thus, animals carrying these mutation(s) may have favorable genetic merit for calving difficulty and carcass merit. Furthermore, depending on the dam genotype, a bull with two copies of the nt821 mutation can produce progeny with improved carcass merit while minimizing calving problems., (© 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.)

The identification of different meat cuts for labeling and quality control on production lines is still largely a manual process. As a result, it is a labor-intensive exercise with the potential for not only error but also bacterial cross-contamination. Artificial intelligence is used in many disciplines to identify objects within images, but these approaches usually require a considerable volume of images for training and validation. The objective of this study was to identify five different meat cuts from images and weights collected by a trained operator within the working environment of a commercial Irish beef plant. Individual cut images and weights from 7,987 meats cuts extracted from semimembranosus muscles (i.e., Topside muscle), post editing, were available. A variety of classical neural networks and a novel Ensemble machine learning approaches were then tasked with identifying each individual meat cut; performance of the approaches was dictated by accuracy (the percentage of correct predictions), precision (the ratio of correctly predicted objects relative to the number of objects identified as positive), and recall (also known as true positive rate or sensitivity). A novel Ensemble approach outperformed a selection of the classical neural networks including convolutional neural network and residual network. The accuracy, precision, and recall for the novel Ensemble method were 99.13%, 99.00%, and 98.00%, respectively, while that of the next best method were 98.00%, 98.00%, and 95.00%, respectively. The Ensemble approach, which requires relatively few gold-standard measures, can readily be deployed under normal abattoir conditions; the strategy could also be evaluated in the cuts from other primals or indeed other species., (© 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 growing cattle, the phenotypic and genetic relationships between feeding behavior and both live animal ultrasound measures and subsequent carcass merit are generally poorly characterized. The objective of the current study was to quantify the phenotypic and genetic associations between a plethora of feeding behavior traits with both pre-slaughter ultrasound traits and post-slaughter carcass credentials in crossbred Bos taurus cattle. Carcass data were available on 3,146 young bulls, steers, and heifers, of which 2,795 and 2,445 also had records for pre-slaughter ultrasound muscle depth and intramuscular fat percentage, respectively; a total of 1,548 steers and heifers had information on all of the feeding behavior, ultrasound, and carcass traits. Young bulls were fed concentrates, while steers and heifers were fed a total mixed ration. Feeding behavior traits were defined based on individual feed events or meal events (i.e., individual feed events grouped into meals). Animal linear mixed models were used to estimate (co)variance components. Phenotypic correlations between feeding behavior and both ultrasound and carcass traits were generally weak and not different from zero, although there were phenotypic correlations of 0.40, 0.26, and 0.37 between carcass weight and feeding rate, energy intake per feed event, and energy intake per meal, respectively. Genetically, cattle that had heavier carcass weights, better carcass conformation, or a higher dressing percentage fed for a shorter time per day (genetic correlations [±SE] of -0.46 ± 0.12, -0.39 ± 0.11, and -0.50 ± 0.10, respectively). Genetic correlations of 0.43 ± 0.12 and 0.68 ± 0.13 were estimated between dressing difference (i.e., differential between live weight pre-slaughter and carcass weight) and energy intake per feed event and energy intake per meal, respectively. Neither intramuscular fat percentage measured on live animals nor carcass fat score (i.e., a measure of subcutaneous fat cover of the carcass) was genetically associated with any of the feeding behavior traits. The genetic associations between some feeding behavior traits and both ultrasound and carcass traits herein suggested that indirect responses in the feeding behavior of growing cattle from selection for improved carcass merit would be expected. Such changes in feeding behavior patterns in cattle may be reduced by measuring and including feeding behavior in a multiple-trait selection index alongside carcass traits., (© 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.)

The objectives of the present study were to estimate genetic parameters for several feeding behavior traits in growing cattle, as well as the genetic associations among and between feeding behavior and both performance and feed efficiency traits. An additional objective was to investigate the use of feeding behavior traits as predictors of genetic merit for feed intake. Feed intake and live-weight data on 6,088 growing cattle were used of which 4,672 had ultrasound data and 1,548 had feeding behavior data. Feeding behavior traits were defined based on individual feed events or meal events (where individual feed events were grouped into meals). Univariate and bivariate animal linear mixed models were used to estimate (co)variance components. Heritability estimates (± SE) for the feeding behavior traits ranged from 0.19 ± 0.08 for meals per day to 0.61 ± 0.10 for feeding time per day. The coefficient of genetic variation per trait varied from 5% for meals per day to 22% for the duration of each feed event. Genetically heavier cattle, those with a higher daily energy intake (MEI), or those that grew faster had a faster feeding rate, as well as a greater energy intake per feed event and per meal. Better daily feed efficiency (i.e., lower residual energy intake) was genetically associated with both a shorter feeding time per day and shorter meal time per day. In a validation population of 321 steers and heifers, the ability of estimated breeding values (EBV) for MEI to predict (adjusted) phenotypic MEI was demonstrated; EBVs for MEI were estimated using multi-trait models with different sets of predictor traits such as liveweight and/or feeding behaviors. The correlation (± SE) between phenotypic MEI and EBV for MEI marginally improved (P < 0.001) from 0.64 ± 0.03 to 0.68 ± 0.03 when feeding behavior phenotypes from the validation population were included in a genetic evaluation that already included phenotypic mid-test metabolic live-weight from the validation population. This is one of the largest studies demonstrating that significant exploitable genetic variation exists in the feeding behavior of young crossbred growing cattle; such feeding behavior traits are also genetically correlated with several performance and feed efficiency metrics. Nonetheless, there was only a marginal benefit to the inclusion of time-related feeding behavior phenotypes in a genetic evaluation for MEI to improve the precision of the EBVs for this trait., (© The Author(s) 2021. Published by Oxford University Press on behalf of the American Society of Animal Science.)

A major obstacle in applying genomic selection (GS) to uniquely adapted local breeds in less-developed countries has been the cost of genotyping at high densities of single-nucleotide polymorphisms (SNP). Cost reduction can be achieved by imputing genotypes from lower to higher densities. Locally adapted breeds tend to be admixed and exhibit a high degree of genomic heterogeneity thus necessitating the optimization of SNP selection for downstream imputation. The aim of this study was to quantify the achievable imputation accuracy for a sample of 1,135 South African (SA) Drakensberger cattle using several custom-derived lower-density panels varying in both SNP density and how the SNP were selected. From a pool of 120,608 genotyped SNP, subsets of SNP were chosen (1) at random, (2) with even genomic dispersion, (3) by maximizing the mean minor allele frequency (MAF), (4) using a combined score of MAF and linkage disequilibrium (LD), (5) using a partitioning-around-medoids (PAM) algorithm, and finally (6) using a hierarchical LD-based clustering algorithm. Imputation accuracy to higher density improved as SNP density increased; animal-wise imputation accuracy defined as the within-animal correlation between the imputed and actual alleles ranged from 0.625 to 0.990 when 2,500 randomly selected SNP were chosen vs. a range of 0.918 to 0.999 when 50,000 randomly selected SNP were used. At a panel density of 10,000 SNP, the mean (standard deviation) animal-wise allele concordance rate was 0.976 (0.018) vs. 0.982 (0.014) when the worst (i.e., random) as opposed to the best (i.e., combination of MAF and LD) SNP selection strategy was employed. A difference of 0.071 units was observed between the mean correlation-based accuracy of imputed SNP categorized as low (0.01 < MAF ≤ 0.1) vs. high MAF (0.4 < MAF ≤ 0.5). Greater mean imputation accuracy was achieved for SNP located on autosomal extremes when these regions were populated with more SNP. The presented results suggested that genotype imputation can be a practical cost-saving strategy for indigenous breeds such as the SA Drakensberger. Based on the results, a genotyping panel consisting of ~10,000 SNP selected based on a combination of MAF and LD would suffice in achieving a <3% imputation error rate for a breed characterized by genomic admixture on the condition that these SNP are selected based on breed-specific selection criteria., (© 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.)

Awareness and interest in calf health and wellbeing is intensifying, prompting change in the management and breeding decisions of producers and associated policy-makers. The objectives of the present study were to 1) quantify the risk factors associated with subjectively measured scores of vigor and birth size as well as diagnoses of scour and pneumonia in a large national dataset of beef calves, and 2) to estimate the contribution of genetic variance to such phenotypic measures. After edits, the data consisted of health and birth size data subjectively scored by producers on 88,207 calves born in 6,126 Irish beef herds. Vigor was recorded on a scale of 1 (very poor) to 5 (very good). Birth size was also scored on a scale of 1 (very small) to 5 (very large). Scour and pneumonia were both scored independently based on the suspected number of occurrence of each (0 = no occurrence, 1 = one occurrence, or 2 = more than one occurrence). On average, 14.7% of calves were recorded as having had at least one occurrence of scour within the first 5 mo of life, whereas 6.4% of calves were recorded as having had at least one occurrence of pneumonia within the first 5 mo of life. Relative to female calves, male calves had a worse vigor score and a suspected greater incidence of both scour and pneumonia. Relative to singletons, twins were, on average, smaller at birth, they had a worse vigor score, and they were more prone to scour. Calves born in the later periods of the calving season (i.e., late and very late) had a greater incidence of scour relative to calves in the herd born earlier in the calving season. Heritability estimates for vigor, birth size, and pneumonia were 0.12 (0.02), 0.33 (0.03), and 0.08 (0.02), respectively; no genetic variance was detected for scour. Breeding for vigorous calves that are less susceptible to pneumonia could provide producers with an additional strategy to ensure consumer concerns regarding food quality, safety, and calf wellbeing are being met., (© 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.)

Sexual dimorphism, the phenomenon whereby males and females of the same species are distinctive in some aspect of appearance or size, has previously been documented in cattle for traits such as growth rate and carcass merit using a quantitative genetics approach. No previous study in cattle has attempted to document sexual dimorphism at a genome level; therefore, the objective of the present study was to determine whether genomic regions associated with size and muscularity in cattle exhibited signs of sexual dimorphism. Analyses were undertaken on 10 linear-type traits that describe the muscular and skeletal characteristics of both males and females of five beef cattle breeds: 1,444 Angus (AA), 6,433 Charolais (CH), 1,129 Hereford, 8,745 Limousin (LM), and 1,698 Simmental. Genome-wide association analyses were undertaken using imputed whole-genome sequence data for each sex separately by breed. For each single-nucleotide polymorphism (SNP) that was segregating in both sexes, the difference between the allele substitution effect sizes for each sex, in each breed separately, was calculated. Suggestively (P ≤ 1 × 10-5) sexually dimorphic SNPs that were segregating in both males and females were detected for all traits in all breeds, although the location of these SNPs differed by both trait and breed. Significantly (P ≤ 1 × 10-8) dimorphic SNPs were detected in just three traits in the AA, seven traits in the CH, and three traits in the LM. The vast majority of all segregating autosomal SNPs (86% in AA to 94% in LM) had the same minor allele in both males and females. Differences (P ≤ 0.05) in allele frequencies between the sexes were observed for between 36% (LM) and 66% (AA) of the total autosomal SNPs that were segregating in both sexes. Dimorphic SNPs were located within a number of genes related to muscularity and/or size including the NAB1, COL5A2, and IWS1 genes on BTA2 that are located close to, and thought to be co-inherited with, the MSTN gene. Overall, sexual dimorphism exists in cattle at the genome level, but it is not consistent by either trait or breed., (© 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.)

Meticulous culling decisions, coupled with careful breeding decisions, are fundamental to shifting a population distribution in the favorable direction and improving profit per cow. Nevertheless, there is a paucity of easy-to-use dynamic tools to aid in culling decisions in beef cattle. The motivation for the present study was to develop a monetary-based culling tool, here referred to as the Beef Female's Profit Potential (BFPP), to identify females for culling. The BFPP reflects the expected lifetime profitability of an individual female in a herd for the expected remainder of her lifetime; this profit included that of the beef female herself as well as her progeny. The BFPP index framework was composed of 4 subindexes reflecting the value of an animal: (1) as a nulliparae (this was voided if the cow had already calved), (2) for the remainder of her current parity, (3) summed across each of her expected remaining parities, and (4) when she is retained within the herd and not voluntarily culled. Each subindex was comprised of different components reflecting both genetic and non-genetic effects associated with each female. Transition matrices predicting the expected longevity of each female and their expected month of calving were also utilized in calculating the expected remaining lifetime profitability of each female. The BFPP index was validated on 21,102 beef cows as well as their harvested progeny from 875 herds by stratifying the cows, within herd, into 4 strata based on their BFPP. The mean of the within-herd correlation between the BFPP and the Irish national replacement (i.e., breeding) index was, on average, 0.45 indicating the shortcomings of the breeding index as a culling tool. Cows within the top BFPP stratum had a genetic expectation of accruing almost an additional €36 profit per calving, relative to cows within the worst stratum; when validated on the cow's own calving interval and survival performance as well as their progeny's carcass performance, the actual phenotypic value was estimated to be an additional €32 profit per calving. A proportion of this additional profit was due to the harvested progeny of the high BFPP cows having, on average, heavier, more conformed carcasses with less fat cover relative to their poor BFPP contemporaries. This BFPP framework is a useful and easy-to-use tool to aid in producer decision making on the choice of females to voluntarily cull but also on which replacement heifers to graduate into the mature herd., (© The Author(s) 2020. 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.)

Despite the importance of validating any technology prior to recommendation for use, few studies exist in the scientific literature which have demonstrated the superior performance of high-ranking animals in a given total merit index; this is especially true for maternal cattle selection indexes. The objective of the present study was to demonstrate the impact of the Irish total merit maternal-based index and provide the benefits of using the Irish total merit maternal-based beef index as part of a breeding policy. The validation exercise was undertaken using 269,407 records (which included the cow's own records and her progeny records) from 92,300 females differing in a total merit index for maternal value; a comparison was also made with the Irish terminal index. Association analyses were undertaken within the framework of linear and threshold mixed models; the traits analyzed were fertility (e.g., calving interval), slaughter (e.g., harvest weight), live weight (e.g., weaning weight), and producer-recorded traits (e.g., docility). All traits were analyzed with the maternal index and terminal index fitted as covariate(s) separately. Depending on the independent variable analyzed, the other fixed effects included: parity of cow, heterosis and recombination loss of cow and/or progeny, gender of progeny, and the estimated breeding value of the sire; contemporary group was included as a random effect. The results demonstrate the effectiveness of using total merit indexes to improve performance in a whole range of different traits, despite the often antagonistic genetic correlations among traits that underpin the index. Cows excelling on the maternal index had less calving difficulty, superior fertility performance, lighter carcasses, and live weight, as well as being more easily managed. Additionally, progeny of higher maternal index cows were lighter at birth and more docile albeit with a small impact on slaughter traits. In contrast, higher terminal index cows had more calving difficulty, compromised fertility and had heavier carcasses themselves as well as their progeny. While the differences in phenotypic performance between groups on maternal index was, in most instances, relatively small, the benefits are: (1) expected to be greater when more genetically extreme groups of animals are evaluated and (2) expected to accumulate over time given the cumulative and permanent properties of breeding schemes., (© The Author(s) 2020. 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.)

Beef originates from the progeny of either dairy or beef dams. The objective of the present study was to identify contributing factors to the differences in the carcass merit of progeny from both dam types. This goal was achieved using slaughter records from 16,414 bucket-reared dairy animals (DXD), 5,407 bucket-reared dairy-beef animals (BXD), 42,102 suckle-reared animals from a beef × dairy F1 cross dam (BXF1), and 93,737 suckle-reared animals from a beef × beef cow (BXB). Linear mixed models were used to quantify the least squares means for carcass characteristics in the various progeny genotypes. Nuisance fixed effects adjusted for in the models were: animal heterosis and recombination loss, dam parity, age at slaughter, and contemporary group; age at slaughter was replaced as an independent variable with both carcass weight and carcass fat score where the dependent variable was age at slaughter. In a follow-up analysis, models were re-analyzed where the genetic merit of the sire was adjusted for; a further analysis set the genetic merit of the dam for the dependent variable to be identical for both the dairy and beef dams. The final analysis adjusted to a common sire and dam genetic merit facilitating the estimation of just differences in early-life rearing strategies. Irrespective of the genetic merit of the sire and dam, animals originating from beef herds had heavier and more conformed carcasses. BXB animals had a 67 kg heavier carcass, with a conformation score (scale 1 [poor] to 15 [excellent]) of 5 units greater compared with DXD animals. When the genetic merit of all dams was set to be equal, BXB animals were heavier and better conformed than BXD animals. When the genetic merit for both the sire and dam were set to be equal, carcasses of the BXB animals were 15 kg heavier, with a 0.69 unit superior conformation score compared with the DXD animals; this difference is due to early life experiences. In conclusion, the majority of the inferiority in carcass metrics of calves from dairy herds compared with beef herds is due to differences in the genetic merit of the parents. Nevertheless, even after adjusting the parents to the same genetic merit, progeny from dairy herds were still inferior to their contemporaries born in beef herds, due most likely to the persistence of early life experiences., (© The Author(s) 2020. 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.)

Beef carcasses in Europe are classified on measures of carcass weight, conformation, and fat cover. These measurements provide the basis for payment to producers, with financial penalties for carcasses that do not conform to desirable characteristics. The objective of the present study was to identify animal-level factors associated with the achievement of a desirable carcass weight, conformation score, fat score, and age at harvest, as stipulated by Irish beef processors in accordance with the EUROP carcass classification system. The stipulated specifications were a EUROP conformation score ≥O=, a carcass weight between 270 and 380 kg, a EUROP fat score between 2+ and 4=, and an age at harvest ≤ 30 mo. In the present study, 59% of cattle failed to achieve at least one of these desired specifications. The logit of the probability of achieving the desired specifications was estimated using multivariable logistic regression and carcass data from 4,717,989 cattle finished and harvested in Ireland between the years 2003 and 2017. In comparison to beef-origin carcasses and after accounting for breed differences, the likelihood of dairy-origin carcasses achieving the desired age, conformation, fat, and weight specifications was 0.97, 0.88, 1.14, and 1.05, respectively. In comparison to heifer carcasses, the odds ratio (OR) of bull and steer carcasses simultaneously achieving all of the desired specifications (i.e. the overall specification) was 0.35 and 0.95, respectively. Additionally, after accounting for breed differences, heifers from the dairy herd were half as likely as heifers from the beef herd to achieve the overall specification, whereas the odds of dairy-origin bulls (OR = 3.46) and steers (OR = 2.41) achieving the overall specification was greater than that of their respective beef-origin counterparts. Finally, cattle with a greater breed proportion of Angus were most likely to achieve the overall specification. Results from the present study could provide a deeper understanding as to why animals fail to achieve desirable carcass specifications and could be implemented into the management decisions made on farm to ensure that the supply of beef carcasses that achieve the desired metrics is maximized., (© The Author(s) 2020. 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.)

The purpose of this study was to define an extensive suite of feeding behavior traits in growing crossbred cattle and to investigate their phenotypic inter-relationships as well as relationships with other performance and efficiency traits. Time-series feeding behavior data, as well as feed intake and liveweight records, were available for 624 growing crossbred cattle, of which 445 were steers and 179 were heifers. Feeding behavior repeatability estimates were calculated using linear mixed models. Additionally, partial Spearman correlations were estimated among 14 feeding behavior traits, as well as between feeding behavior with both performance and feed efficiency traits, using residuals retained from linear mixed models. The marginal contribution of several feeding behavior traits to the variability in metabolizable energy intake (MEI) was also determined. Repeatability estimates of 0.57, 0.36, and 0.48 were calculated for the number of feed events per day, the total time spent feeding per day, and the feeding rate, respectively. Cattle that ate more frequently each day, ate at a faster rate and consumed less energy in each visit to the feed bunk. More efficient cattle fed less often per day and fed for a shorter duration per day; they also had a slower feeding rate and fed for longer in each visit to the feed bunk. Moreover, heavier cattle fed for a longer duration per day had a faster feeding rate, but fed less often per day; heavier animals also fed first in the pen after the fresh feed was offered. The number of feed events per day and feeding time per day together explained an additional 13.4 percentage points of the variability in MEI above that already explained by all of growth rate, liveweight, and backfat depth. The results from the present study suggest that several repeatable time-series-related feeding behavior traits, that are less resource intensive to measure, may have a role as useful predictor traits of important but relatively difficult to record traits, such as feed intake and efficiency., (© The Author(s) 2020. Published by Oxford University Press on behalf of the American Society of Animal Science.)

The objective of the present study was to estimate the genetic parameters associated with the achievement of desirable weight, conformation, and fat specifications, represented by a series of binary traits. The desired specifications were those stipulated by Irish beef processors, in accordance with the EUROP carcass grading system, and were represented by a carcass weight between 270 and 380 kg, a fat score between 2+ and 4= (between 6 and 11 on a 15-point scale), and a conformation score of O= or better (≥5 on a 15-point scale). Using data from 58,868 beef carcasses, variance components were estimated using linear mixed models for these binary traits, as well as their underlying continuous measures. Heritability estimates for the continuous traits ranged from 0.63 to 0.73; heritability estimates for the binary traits ranged from 0.05 to 0.19. An additional trait was defined to reflect if all desired carcass specifications were met. All genetic correlations between this trait and the individual contributing binary traits were positive (0.38 to 0.87), while all genetic correlations between this trait and the continuous carcass measures were negative (-0.87 to -0.07). The genetic parameters estimated in the present study signify that potential exists to breed cattle that more consistently achieve desirable carcass metrics at harvest., (© The Author(s) 2020. 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.)

Reducing the incidence of both the degree of assistance required at calving, as well as the extent of perinatal mortality (PM) has both economic and societal benefits. The existence of heritable genetic variability in both traits signifies the presence of underlying genomic variability. The objective of the present study was to locate regions of the genome, and by extension putative genes and mutations, that are likely to be underpinning the genetic variability in direct calving difficulty (DCD), maternal calving difficulty (MCD), and PM. Imputed whole-genome single-nucleotide polymorphism (SNP) data on up to 8,304 Angus (AA), 17,175 Charolais (CH), 16,794 Limousin (LM), and 18,474 Holstein-Friesian (HF) sires representing 5,866,712 calving events from descendants were used. Several putative quantitative trait loci (QTL) regions associated with calving performance both within and across dairy and beef breeds were identified, although the majority were both breed- and trait-specific. QTL surrounding and encompassing the myostatin (MSTN) gene were associated (P < 5 × 10-8) with DCD and PM in both the CH and LM populations. The well-known Q204X mutation was the fifth strongest association with DCD in the CH population and accounted for 5.09% of the genetic variance in DCD. In contrast, none of the 259 segregating variants in MSTN were associated (P > × 10-6) with DCD in the LM population but a genomic region 617 kb downstream of MSTN was associated (P < 5 × 10-8). The genetic architecture for DCD differed in the HF population relative to the CH and LM, where two QTL encompassing ZNF613 on Bos taurus autosome (BTA)18 and PLAG1 on BTA14 were identified in the former. Pleiotropic SNP associated with all three calving performance traits were also identified in the three beef breeds; 5 SNP were pleiotropic in AA, 116 in LM, and 882 in CH but no SNP was associated with more than one trait within the HF population. The majority of these pleiotropic SNP were on BTA2 surrounding MSTN and were associated with both DCD and PM. Multiple previously reported, but also novel QTL, associated with calving performance were detected in this large study. These also included QTL regions harboring SNP with the same direction of allele substitution effect for both DCD and MCD thus contributing to a more effective simultaneous selection for both traits., (© The Author(s) 2020. Published by Oxford University Press on behalf of the American Society of Animal Science.)

The importance of improving the efficiency of beef production systems using both genetic and management strategies has long been discussed. Despite the contribution of the mature beef herd to the overall cost of production in the sector as a whole, most strategies for improving (feed) efficiency have focused on the growing animal. The objective of the present study was to quantify the phenotypic and genetic variability in several novel measures that relate the weight of a calf to that of its dam and vice versa. Two novel residual traits, representing the deviation in calf weight relative to its expectation from the population based on its dam's weight (DIFFcalf) or the deviation in the weight of the dam relative to its expectation from the population based on its calf's weight (DIFFdam), were calculated while simultaneously accounting for some nuisance factors in a multiple regression model. Four supplementary traits were also calculated, namely, 1) the deviation in calf weight from its expectation expressed relative to the weight of the dam (DIFFcalf&#95;ratio), 2) the deviation in dam weight from its expectation relative to the weight of the dam (DIFFdam&#95;ratio), 3) DIFFcalf-DIFFdam, and 4) the simple ratio of calf weight to its dam's weight (RATIOcalfdam). Genetic and residual variance components for each of the 6 traits were estimated using animal-dam linear mixed models. The phenotypic SD for DIFFcalf was 42 kg and, when expressed relative to the weight of the dam (i.e., DIFFcalf&#95;ratio), was 0.07. The genetic SD for DIFFcalf and DIFFcalf&#95;ratio was 16.66 kg and 0.02, respectively. The direct and maternal heritability estimated for DIFFcalf was 0.28 (SE = 0.04) and 0.11 (SE = 0.02), respectively, and for DIFFcalf&#95;ratio was 0.24 (SE = 0.04) and 0.17 (SE = 0.03), respectively. The genetic SD for DIFFdam was 47.09 kg; the direct heritability was 0.50 (SE = 0.03), and the dam repeatability was 0.75 (SE = 0.01). The genetic SD for RATIOcalfdam was 0.03; the direct and maternal heritability was 0.24 (SE = 0.04) and 0.24 (SE = 0.03), respectively. The suggested traits outlined in the present study provide useful metrics for benchmarking dam-calf efficiency; in addition, the genetic variability detected in these traits suggest genetic progress for more efficient dam-calf pairs is indeed possible., (© The Author(s) 2019. 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.)

Some definitions of feed efficiency such as residual energy intake (REI) and residual gain (RG) may not truly reflect production efficiency. The energy sinks used in the derivation of the traits include metabolic live-weight; producers finishing cattle for slaughter are, however, paid on the basis of carcass weight, as opposed to live-weight. The objective of the present study was to explore alternative definitions of REI and RG which are more reflective of production efficiency, and quantify their relationship with performance, ultrasound, and carcass traits across multiple breeds and sexes of cattle. Feed intake and live-weight records were available on 5,172 growing animals, 2,187 of which also had information relating to carcass traits; all animals were fed a concentrate-based diet representative of a feedlot diet. Animal linear mixed models were used to estimate (co)variance components. Heritability estimates for all derived REI traits varied from 0.36 (REICWF; REI using carcass weight and carcass fat as energy sinks) to 0.50 (traditional REI derived with the energy sinks of both live-weight and ADG). The heritability for the RG traits varied from 0.24 to 0.34. Phenotypic correlations among all definitions of the REI traits ranged from 0.90 (REI with REICWF) to 0.99 (traditional REI with REI using metabolic preslaughter live-weight and ADG). All were different (P < 0.001) from one suggesting reranking of animals when using different definitions of REI to identify efficient cattle. The derived RG traits were either weakly or not correlated (P > 0.05) with the ultrasound and carcass traits. Genetic correlations between the REI traits with carcass weight, dressing difference (i.e., live-weight immediately preslaughter minus carcass weight) and dressing percentage (i.e., carcass weight divided by live-weight immediately preslaughter) implies that selection on any of the REI traits will increase carcass weight, lower the dressing difference and increase dressing percentage. Selection on REICW (REI using carcass weight as an energy sink), as opposed to traditional REI, should increase the carcass weight 2.2 times slower but reduce the dressing difference 4.3 times faster. While traditionally defined REI is informative from a research perspective, the ability to convert energy into live-weight gain does not necessarily equate to carcass gain, and as such, traits such as REICW and REICWF provide a better description of production efficiency for feedlot cattle., (© The Author(s) 2019. 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.)

The ability to alter the morphology of cattle towards greater yields of higher value primal cuts has the potential to increase the value of animals at slaughter. Using weight records of 14 primal cuts from 31,827 cattle, the objective of the present study was to quantify the extent of genetic variability in these primal cuts; also of interest was the degree of genetic variability in the primal cuts adjusted to a common carcass weight. Variance components were estimated for each primal cut using animal linear mixed models. The coefficient of genetic variation in the different primal cuts ranged from 0.05 (bavette) to 0.10 (eye of round) with a mean coefficient of genetic variation of 0.07. When phenotypically adjusted to a common carcass weight, the coefficient of genetic variation of the primal cuts was lesser ranging from 0.02 to 0.07 with a mean of 0.04. The heritability of the 14 primal cuts ranged from 0.14 (bavette) to 0.75 (topside) with a mean heritability across all cuts of 0.48; the heritability estimates reduced, and ranged from 0.12 (bavette) to 0.56 (topside), when differences in carcass weight were accounted for in the statistical model. Genetic correlations between each primal cut and carcass weight were all ≥0.77; genetic correlations between each primal cut and carcass conformation score were, on average, 0.59 but when adjusted to a common carcass weight, the correlations weakened to, on average, 0.27. The genetic correlations among all 14 primal cut weights was, on average, strong (mean correlation of 0.72 with all correlations being ≥0.37); when adjusted to a common carcass weight, the mean of the genetic correlations among all primal cuts was 0.10. The ability of estimated breeding values for a selection of primal cuts to stratify animals phenotypically on the respective cut weight was demonstrated; the weight of the rump, striploin, and fillet of animals estimated to be in the top 25% genetically for the respective cut, were 10 to 24%, 12 to 24%, and 7 to 17% heavier than the weight of cuts from animals predicted to be in the worst 25% genetically for that cut. Significant exploitable genetic variability in primal carcass cuts was clearly evident even when adjusted to a common carcass weight. The high heritability of many of the primal cuts infers that large datasets are not actually required to achieve high accuracy of selection once the structure of the data and the number of progeny per sire is adequate., (© The Author(s) 2019. 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.)

Having access to early predictions of both the genetic merit and expected phenotypic performance of an individual or its progeny can contribute to more informed decision-making. The objective here was to evaluate the usefulness of routinely available subjectively scored linear conformation information on live animals to predict genetic merit for primal carcass cut yields of their relatives. Data on 6 muscular and 6 skeletal traits on 43,078 live animals were used; the weights of up to 14 primal cuts plus 3 groups of primal cuts of 31,827 cattle were also used. Genetic correlations between the linear scores and the primal cut weights were estimated using sire linear mixed models; correlations were estimated with or without phenotypic adjustment of the primal cut weights to a constant carcass weight. The genetic correlations between each of the muscular and skeletal linear type traits with each of the primal cut weights (not adjusted for carcass weight) were all positive with the exception of the correlations between both chest width and pelvic length with cuberoll. On average, the muscular type traits were more strongly correlated (on average 0.42) with the primal cut weights than the skeletal traits (on average 0.35). Moreover, the average of the genetic correlations between each of the 6 muscular traits with all 8 hindquarter traits was, on average, 10% to 18% stronger than the average of the genetic correlations between the same muscular traits with all 5 forequarter primal cuts. When adjusted for differences in carcass weight, the correlations between all linear scores and the carcass traits regressed to zero or became negative. The skeletal traits were, in general, weakly genetically correlated with the primal cuts adjusted to a common carcass weight. The average of the genetic correlation between the muscular type traits and the primal cuts adjusted for differences in carcass weight was only 0.09 with only 13 of the 84 pairwise correlations being stronger than 0.30; the genetic correlation between silverside with the muscular traits was all stronger than 0.30, whereas the majority of the muscular traits had a correlation stronger than 0.30 with the topside primal cut. In fact, the average of the genetic correlations between the topside and silverside cuts with all the muscular traits was 0.50 and 0.42, respectively, with none of the correlations being negative., (© The Author(s) 2019. 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.)

The objective of the present study was to quantify the genetic and non-genetic contributors to variability in both carcass dressing percentage and dressing difference (i.e., the difference between carcass weight and live weight immediately prior to slaughter) in young animals and cows. The datasets contained 18,479 young animals from 653 herds, and 2,887 cows from 665 herds. Live weight records within 7 d of slaughter and associated carcass weight were available for all animals. Association analyses were undertaken using linear mixed models with fixed effects for the model of young animals consisting of animal breed, days between the date of last recorded live weight and slaughter date, heterosis and recombination loss coefficients, dam parity, a 3-way interaction between whether the animal originated in a dairy or beef herd, animal sex, and age at slaughter, as well as a 2-way interaction between calendar year of slaughter and month of slaughter; contemporary group was included as a random effect. Fixed effects in the cow model were cow breed, the number of days between the date of last recorded live weight and slaughter date, heterosis and recombination loss coefficients, the number of days postcalving, parity of the cow, and a 2-way interaction between calendar year of slaughter and month of slaughter; contemporary group was included as a random effect. The mean dressing percentage (phenotypic standard deviation in parentheses) and dressing difference in young animals were 55.86% (3.21%) and 280.03 kg (41.44 kg), respectively. Steers had the heaviest dressing difference at 34.18 and 60.44 kg heavier than a 16-mo old bull and 22-mo old heifer, respectively. Dressing difference for 30-mo old Simmental steers (breed with heaviest dressing difference) was 41.66 kg heavier than 30-mo old Belgian Blue steers (breed with lightest dressing difference). The heritability of dressing percentage (0.48) and dressing difference (0.35) in young animals was relatively similar to each other, in contrast to dressing percentage (0.08) in cows which was considerably lower than dressing difference (0.28). Considerable genetic variability existed in dressing difference amongst young animals (genetic standard deviation of 15.03 kg), despite the near unity genetic correlation (0.93) between carcass weight and live weight. This therefore indicates that genetic selection for increased saleable product can be achieved by selecting for increased carcass weight while concurrently selecting for lighter animals although the opportunity is limited by the strong part-whole relationships that exists between carcass weight, live weight, and dressing difference., (© The Author(s) 2019. 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.)

The objective of the present study was to quantify the accuracy of imputing medium-density single nucleotide polymorphism (SNP) genotypes from lower-density panels (384 to 12,000 SNPs) derived using alternative selection methods to select the most informative SNPs. Four different selection methods were used to select SNPs based on genomic characteristics (i.e., minor allele frequency (MAF) and linkage disequilibrium (LD)) within five sheep breeds (642 Belclare, 645 Charollais, 715 Suffolk, 440 Texel, and 620 Vendeen) separately. Selection methods evaluated included (i) random, (ii) splitting the genome into blocks of equal length and selecting SNPs within block based on MAF and LD patterns, (iii) equidistant location while optimizing MAF, (iv) a combination of MAF, distance from already selected SNPs, and weak LD with the SNP(s) already selected. All animals were genotyped on the Illumina OvineSNP50 Beadchip containing 51,135 SNPs of which 44,040 remained after edits. Within each breed separately, the youngest 100 animals were assumed to represent the validation population; the remaining animals represented the reference population. Imputation was undertaken under three different conditions: (i) SNPs were selected within a given breed and imputed for all breeds individually, (ii) all breeds were collectively used to select SNPs and were included as the reference population, and (iii) the SNPs were selected for each breed separately and imputation was undertaken for all breeds but excluding from the reference population, the breed from which the SNPs were selected. Regardless of SNP selection method, mean animal allele concordance rate improved at a diminishing rate while the variability in mean animal allele concordance rate reduced as the panel density increased. The SNP selection method impacted the accuracy of imputation although the effect reduced as the density of the panel increased. Overall, the most accurate SNP selection method for panels with <9,000 SNPs was that based on MAF and LD pattern within genomic blocks. The mean animal allele concordance rate varied from 0.89 in Texel to 0.97 in Vendeen. Greater imputation accuracy was achieved when SNPs were selected and imputed within each breed individually compared with when SNPs were selected across all breeds and imputed using a multi-breed reference population. In all, results indicate that accurate genotype imputation to medium density is achievable with low-density genotype panels with at least 6,000 SNPs., (© The Author(s) 2019. 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.)

Genetic selection is an inexpensive and complementary strategy to traditional methods of improving animal health and welfare. Nonetheless, endeavors to incorporate animal health and welfare traits in international breeding programs have been hampered by the availability of informative phenotypes. The recent eradication program for bovine viral diarrhea (BVD) in the Republic of Ireland has provided an opportunity to quantify the potential benefits that genetic selection could offer BVD eradication programs elsewhere, as well as inform possible eradication programs for other diseases in the Republic of Ireland. Using a dataset of 188,085 Irish calves, the estimated direct and maternal heritability estimates for the birth of persistently infected calves following likely in utero exposure to BVD virus ranged from not different from zero (linear model) to 0.29 (SE = 0.075; threshold model) and from essentially zero (linear model) to 0.04 (SE = 0.033; threshold model), respectively. The corresponding genetic SD for the direct and maternal effect of the binary trait (0, 1) ranged from 0.005 (linear model) to 0.56 (threshold model) units and ranged from 0.00008 (linear model) to 0.20 (threshold model) units, respectively. The coefficient of direct genetic variation based on the linear model was 2.56% indicating considerable genetic variation could be exploited. Based on results from the linear model in the present study, there is the potential to reduce the incidence of persistent infection in cattle by on average 0.11 percentage units per year which is cumulative and permanent. Therefore, genetic selection can contribute to reducing the incidence of persistent infection in cattle. Moreover, where populations are free from persistent infection, inclusion of the estimated genetic merit for BVD in national breeding indexes could contribute to a preservation of a BVD-free status. Results from the present study can be used to inform breeding programs of the potential genetic gains achievable. Moreover, the approaches used in the present study can be applied to other diseases when data become available.

Copy number variants (CNVs) are a form of genomic variation that changes the structure of the genome through deletion or duplication of stretches of DNA. The objective of the present study was to characterize CNVs in a large multibreed population of beef and dairy bulls. The CNVs were called on the autosomes of 5,551 cattle from 22 different beef and dairy breeds, using 2 freely available software suites, QuantiSNP and PennCNV. All CNVs were classified into either deletions or duplications. The median concordance between PennCNV and QuantiSNP, per animal, was 18.5% for deletions and 0% for duplications. The low concordance rate between PennCNV and QuantiSNP indicated that neither algorithm, by itself, could identify all CNVs in the population. In total, PennCNV and QuantiSNP collectively identified 747,129 deletions and 432,523 duplications; 80.2% of all duplications and 69.1% of all deletions were present only once in the population. Only 0.154% of all CNVs identified were present in more than 50 animals in the population. The distribution of the percentage of the autosomes that were composed of deletions, per animal, was positively skewed, as was the distribution for the percentage of the autosomes that were composed of duplications, per animal. The first quartile, median, and third quartile of the distribution of the percentage of the autosomes that were composed of deletions were 0.019%, 0.037%, and 0.201%, respectively. The first quartile, median, and third quartile of the distribution of the percentage of the autosomes that were composed of duplications were 0.013%, 0.028%, and 0.076%, respectively. The distributions of the number of deletions and duplications per animal were both positively skewed. The interquartile range for the number of deletions per animal in the population was between 16 and 117, whereas for duplications it was between 8 and 23. Per animal, there tended to be twice as many deletions as duplications. The distribution of the length of deletions was positively skewed, as was the distribution of the length of duplications. The interquartile range for the length of deletions in the population was between 25 and 101 kb, and for duplications the interquartile range was between 46 and 235 kb. Per animal, duplications tended to be twice as long as deletions. This study provides a description of the characteristics and distribution of CNVs in a large multibreed population of beef and dairy cattle.

The objective of the present study was to quantify the relationship between udder skin surface temperature (USST) and somatic cell count (SCC) in lactating dairy cows. Data were recorded on the same 14 Holstein-Friesian cows, at evening (15:00 to 16:00) milking every day over a 2-mo period. Surface temperature measurements of all udders were extracted from thermal images. After imaging, milk was extracted from each quarter and analyzed for SCC. Environmental and cow-related factors (i.e., ambient temperature, humidity, rainfall, wind speed, distance walked to the parlor, number of days since the udder was shaved, parity, and stage of lactation) were recorded on each day of the experiment. A large array of descriptive temperature parameters (DTP) were extracted from every udder image including temperature-based (e.g., maximum, average and minimum USST), pixel count-based, and textural-based DTPs. Several different analytical methods were tested in an attempt to relate any given DTP to SCC; this included investigating the relationship between USST and the log transform of SCC (i.e., somatic cell score; SCS). The temperature range within each udder was also compared with the natural log of the range in SCC of the respective quarters. In a separate analysis, the temperature difference between each DTP and its respective daily baseline (i.e., average of the 5 lowest values of that DTP across the herd) was compared with SCS. Finally, the association between environmental and cow-related factors with each DTP was investigated to create prediction models for each DTP, the residuals of which were compared with SCC. Results from the present study indicate that the correlation between any DTP and SCS was weak (range of -0.16 to 0.19) and so could not be used to identify quarters with high SCC. Although some alternative measures had a significant relationship with SCS, again, the correlation was too weak for practical use on its own. Maximum and average USST could be predicted with a root mean square error of 0.23 and 0.35 °C, respectively, although the residuals from the prediction model could not be used to identify animals with high SCC. This suggests that infrared thermography alone could not be used as a real-time automated tool to detect high SCC for dairy cows in a pasture-based system.

Ewe efficiency has traditionally been defined as the ratio of litter weight to ewe weight; given the statistical properties of ratio traits, an alternative strategy is proposed in the present study. The concept of using the deviation in performance of an animal from the population norm has grown in popularity as a measure of animal-level efficiency. The objective of the present study was to define novel measures of efficiency for sheep, which considers the combined weight of a litter of lambs relative to the weight of their dam, and vice versa. Two novel traits, representing the deviation in total litter weight at 40 d (DEV40L) or weaning (DEVweanL), were calculated as the residuals of a statistical model, with litter weight as the dependent variable and with the fixed effects of litter rearing size, contemporary group, and ewe weight. The deviation in ewe weight at 40-d postlambing (DEV40E) or weaning (DEVweanE) was derived using a similar approach but with ewe weight and litter weight interchanged as the dependent variable. Variance components for each trait were estimated by first deriving the litter or ewe weight deviation phenotype and subsequently estimating the variance components. The phenotypic SD in DEV40L and DEVweanL was 8.46 and 15.37 kg, respectively; the mean litter weight at 40 d and weaning was 30.97 and 47.68 kg, respectively. The genetic SD and heritability for DEV40L was 2.65 kg and 0.12, respectively. For DEVweanL, the genetic SD and heritability was 4.94 kg and 0.13, respectively. The average ewe weight at 40-d postlambing and at weaning was 66.43 and 66.87 kg, respectively. The genetic SD and heritability for DEV40E was 4.33 kg and 0.24, respectively. The heritability estimated for DEVweanE was 0.31. The traits derived in the present study may be useful not only for phenotypic benchmarking of ewes within flock on performance but also for benchmarking flocks against each other; furthermore, the extent of genetic variability in all traits, coupled with the fact that the data required to generate these novel phenotypes are usually readily available, signals huge potential within sheep breeding programs.

It is anticipated that in the future, livestock will be exposed to a greater risk of infection from parasitic diseases. Therefore, future breeding strategies for livestock, which are generally long-term strategies for change, should target animals adaptable to environments with a high parasitic load. Covariance components were estimated in the present study for a selection of dairy and beef performance traits over herd-years differing in Fasciola hepatica load using random regression sire models. Herd-year prevalence of F. hepatica was determined by using F. hepatica-damaged liver phenotypes which were recorded in abattoirs nationally. The data analyzed consisted up to 83,821 lactation records from dairy cows for a range of milk production and fertility traits, as well as 105,054 young animals with carcass-related information obtained at slaughter. Reaction norms for individual sires were derived from the random regression coefficients. The heritability and additive genetic standard deviations for all traits analyzed remained relatively constant as herd-year F. hepatica prevalence gradient increased up to a prevalence level of 0.7; although there was a large increase in heritability and additive genetic standard deviation for milk and fertility traits in the observed F. hepatica prevalence levels >0.7, only 5% of the data existed in herd-year prevalence levels >0.7. Very little rescaling, therefore, exists across differing herd-year F. hepatica prevalence levels. Within-trait genetic correlations among the performance traits across different herd-year F. hepatica prevalence levels were less than unity for all traits. Nevertheless, within-trait genetic correlations for milk production and carcass traits were all >0.8 for F. hepatica prevalence levels between 0.2 and 0.8. The lowest estimate of within-trait genetic correlations for the different fertility traits ranged from -0.03 (SE = 1.09) in age of first calving to 0.54 (SE = 0.22) for calving to first service interval. Therefore, there was reranking of sires for fertility traits across different F. hepatica prevalence levels. In conclusion, there was little or no genetic variability in sensitivity to F. hepatica prevalence levels among cattle for milk production and carcass traits. But, some genetic variability in sensitivity among dairy cows did exist for fertility traits measured across herds differing in F. hepatica prevalence.

Linear type traits describing the skeletal, muscular, and functional characteristics of an animal are routinely scored on live animals in both the dairy and beef cattle industries. Previous studies have demonstrated that genetic parameters for certain performance traits may differ between breeds; no study, however, has attempted to determine if differences exist in genetic parameters of linear type traits among breeds or sexes. Therefore, the objective of the present study was to determine if genetic covariance components for linear type traits differed among five contrasting cattle breeds, and to also investigate if these components differed by sex. A total of 18 linear type traits scored on 3,356 Angus (AA), 31,049 Charolais (CH), 3,004 Hereford (HE), 35,159 Limousin (LM), and 8,632 Simmental (SI) were used in the analysis. Data were analyzed using animal linear mixed models which included the fixed effects of sex of the animal (except in the investigation into the presence of sexual dimorphism), age at scoring, parity of the dam, and contemporary group of herd-date of scoring. Differences (P < 0.05) in heritability estimates, between at least two breeds, existed for 13 out of 18 linear type traits. Differences (P < 0.05) also existed between the pairwise within-breed genetic correlations among the linear type traits. Overall, the linear type traits in the continental breeds (i.e., CH, LM, SI) tended to have similar heritability estimates to each other as well as similar genetic correlations among the same pairwise traits, as did the traits in the British breeds (i.e., AA, HE). The correlation between a linear function of breeding values computed conditional on covariance parameters estimated from the CH breed with a linear function of breeding values computed conditional on covariance parameters estimated from the other breeds was estimated. Replacing the genetic covariance components estimated in the CH breed with those of the LM had least effect but the impact was considerable when the genetic covariance components of the AA were used. Genetic correlations between the same linear type traits in the two sexes were all close to unity (≥0.90) suggesting little advantage in considering these as separate traits for males and females. Results for the present study indicate the potential increase in accuracy of estimated breeding value prediction from considering, at least, the British breed traits separate to continental breed traits.

Parasitic diseases have economic consequences in cattle production systems. Although breeding for parasite resistance can complement current control practices to reduce the prevalence globally, there is little knowledge of the implications of such a strategy on other performance traits. Records on individual animal antibody responses to Fasciola hepatica, Ostertagia ostertagi, and Neospora caninum were available from cows in 68 dairy herds (study herds); national abattoir data on F. hepatica-damaged livers were also available from dairy and beef cattle. After data edits, 9,271 dairy cows remained in the study herd dataset, whereas 19,542 dairy cows and 68,048 young dairy and beef animals had a record for the presence or absence of F. hepatica-damaged liver in the national dataset. Milk, reproductive, and carcass phenotypes were also available for a proportion of these animals as well as their contemporaries. Linear mixed models were used to estimate variance components of antibody responses to the three parasites; covariance components were estimated between the parasite phenotypes and economically important traits. Heritability of antibody responses to the different parasites, when treated as a continuous trait, ranged from 0.07 (O. ostertagi) to 0.13 (F. hepatica), whereas the coefficient of genetic variation ranged from 4% (O. ostertagi) to 20% (F. hepatica). The antibody response to N. caninum was genetically correlated with the antibody response to both F. hepatica (-0.29) and O. ostertagi (-0.67); a moderately positive genetic correlation existed between the antibody response to F. hepatica and O. ostertagi (0.66). Genetic correlations between the parasite phenotypes and the milk production traits were all close to zero (-0.14 to 0.10), as were the genetic correlations between F. hepatica-damaged livers and the carcass traits of carcass weight, conformation, and fat score evaluated in cows and young animals (0.00 to 0.16). The genetic correlation between F. hepatica-damaged livers in cows and milk somatic cell score was 0.32 (SE = 0.20). Antibody responses to F. hepatica and O. ostertagi had favorable genetic correlations with fertility traits, but conversely, antibody response to N. caninum and F. hepatica-damaged livers were unfavorably genetically correlated with fertility. This study provides the necessary information to undertake national multitrait genetic evaluations for parasite phenotypes.

Animal mortality is indicative of animal health and welfare standards, which are of growing concern to the agricultural industry. The objective of the present study was to ascertain risk factors associated with mortality at multiple life stages in pasture-based, seasonal-calving dairy and beef herds. Males and females were stratified into seven life stages based on age (0 to 2 d, 3 to 7 d, 8 to 30 d, 31 to 182 d, 183 to 365 d, 366 to 730 d, and 731 to 1,095 d) whereas females with ≥1 calving event were further stratified into five life stages based on cow parity number (1, 2, 3, 4, and 5). Mortality was defined as whether an animal died during each life stage; only animals that either survived the entire duration or died during a life stage were considered. The data, following edits, consisted of 4,404,122 records from 1,358,712 animals. Multivariable logistic regression was used to estimate the logit of the probability of mortality in each life stage separately. The odds of a young animal (i.e., aged ≤ 1,095 d) dying was generally greater if veterinary assistance was required at their birth relative to no assistance (odds ratio [OR]: 3.10 to 31.85), if the animal was a twin relative to a singleton (OR: 1.46 to 2.31) or if the animal was male relative to female (OR: 1.14 to 6.15). Moreover, the odds of a cow (i.e., females with ≥1 calving event) dying were greater when she required veterinary assistance at calving (OR: 2.69 to 7.55) compared with a cow that did not require any assistance, if she produced twin relative to singleton progeny (OR: 1.59 to 2.03) or male relative to female progeny (OR: 1.09 to 1.20). Additionally, the odds of a first or second parity cow dying when she herself had received veterinary assistance at birth were only 0.63 to 0.66 times that of a cow that was provided no assistance at birth. For both young animals and cows, the odds of dying generally increased with herd size, whereas animals residing in expanding herds had lower odds of dying. Results from the present study indicate that the risk factors associated with mortality in pasture-based, seasonal-calving herds are similar to those reported in literature in confinement, nonseasonal-calving herds. Moreover, the present study identifies that these risk factors are similar in both dairy and beef herds, yet the magnitude of the association often differs and also changes with life stage.

Apprehension among consumers is mounting on the efficiency by which cattle convert feedstuffs into human edible protein and energy as well as the consequential effects on the environment. Most (genetic) studies that attempt to address these issues have generally focused on efficiency metrics defined over a certain time period of an animal's life cycle, predominantly the period representing the linear phase of growth. The age at which an animal reaches the carcass specifications for slaughter, however, is also known to vary between breeds; less is known on the extent of the within-breed variability in age at slaughter. Therefore, the objective of the present study was to quantify the phenotypic and genetic variability in the age at which cattle reach a predefined carcass weight and subcutaneous fat cover. A novel trait, labeled here as the deviation in age at slaughter (DAGE), was represented by the unexplained variability from a statistical model, with age at slaughter as the dependent variable and with the fixed effects, among others, of carcass weight and fat score (scale 1 to 15 scored by video image analysis of the carcass at slaughter). Variance components for DAGE were estimated using either a 2-step approach (i.e., the DAGE phenotype derived first and then variance components estimated) or a 1-step approach (i.e., variance components for age at slaughter estimated directly in a mixed model that included the fixed effects of, among others, carcass weight and carcass fat score as well as a random direct additive genetic effect). The raw phenotypic SD in DAGE was 44.2 d. The genetic SD and heritability for DAGE estimated using the 1-step or 2-step models varied from 14.2 to 15.1 d and from 0.23 to 0.26 (SE 0.02), respectively. Assuming the (genetic) variability in the number of days from birth to reaching a desired carcass specifications can be exploited without any associated unfavorable repercussions, considerable potential exists to improve not only the (feed) efficiency of the animal and farm system but also the environmental footprint of the system. The beauty of the approach proposed, relative to strategies that select directly for the feed intake complex and enteric methane emissions, is that data on age at slaughter are generally readily available. Of course, faster gains may potentially be achieved if a dual objective of improving animal efficiency per day coupled with reduced days to slaughter was embarked on.

The objective of the present study was to estimate genetic co-variance parameters pertaining to live weight, feed intake, and 2 efficiency traits (i.e., residual feed intake and residual daily gain) in a population of pigs over a defined growing phase using Legendre polynomial equations. The data set used consisted of 51,893 live weight records and 903,436 feed intake, residual feed intake (defined as the difference between an animal's actual feed intake and its expected feed intake), and residual daily gain (defined as the difference between an animal's actual growth rate and its expected growth rate) records from 10,201 growing pigs. Genetic co-variance parameters for all traits were estimated using random regression Legendre polynomials. Daily heritability estimates for live weight ranged from 0.25 ± 0.04 (d 73) to 0.50 ± 0.03 (d 122). Low to moderate heritability estimates were evident for feed intake, ranging from 0.07 ± 0.03 (d 66) to 0.25 ± 0.02 (d 170). The estimated heritability for residual feed intake was generally lower than those of both live weight and feed intake and ranged from 0.04 ± 0.01 (d 96) to 0.17 ± 0.02 (d 159). The heritability for feed intake and residual feed intake increased in the early stages of the test period and subsequently sharply declined, coinciding with older ages. Heritability estimates for residual daily gain ranged from 0.26 ± 0.03 (d 188) to 0.42 ± 0.03 (d 101). Genetic correlations within trait were strongest between adjacent ages but weakened as the interval between ages increased; however, the genetic correlations within all traits tended to strengthen between the extremes of the trajectory. Moderate to strong genetic correlations were evident among live weight, feed intake, and the efficiency traits, particularly in the early stage of the trial period (d 66 to 86), but weakened with age. Results from this study could be implemented into the national genetic evaluation for pigs, providing comprehensive information on the profile of growth and efficiency throughout the growing period of the animal's life, thus helping producers identify genetically superior animals.

The objective of the present study was to quantify the interrelationships between different feed efficiency measures in growing pigs and characterize pigs divergent for a selection of these measures. The data set included data from 311 growing pigs between 42 and 91 d of age from 3 separate batches. Growth-related metrics available included midtest metabolic BW (BW), energy intake (EI), and ADG. Ratio efficiency traits included energy conversion ratio (ECR), Kleiber ratio (ADG/BW), relative growth rate (RGR), residual EI (REI), and residual daily gain (RDG). Residual intake and gain (RIG; i.e., a dual index of both REI and RDG) and residual midtest metabolic weight (RMW) were also calculated. Simple Pearson correlations were estimated between the growth and feed efficiency metrics. In litters with at least 3 pigs of each sex, pigs were separately stratified on each residual trait as high, medium, and low rank. Considerable interanimal variability existed in all metrics evaluated. Male pigs were superior to females for all metrics ( < 0.001) except for both BW and EI, where no sex differences were evident. Feed efficiency metrics improved as birth BW increased ( < 0.05) except for RGR, where the contrary was observed. Correlations between most growth and feed efficiency metrics were strong to moderate ( < 0.05). Low-REI pigs (i.e., more efficient) had lower EI and ECR and were superior for RIG ( < 0.001) compared with high- and medium-REI pigs. High-RDG pigs (i.e., more efficient) had greater BW gain and better ECR ( < 0.001) compared with medium- and low-RDG pigs. Residual EI and RIG were both superior ( < 0.001) in high-RDG pigs compared with medium- and low-RDG pigs. Energy conversion ratio, REI, and RIG were superior ( < 0.05) in high-RMW pigs (i.e., more efficient) compared with medium-RMW pigs. High-RIG pigs (i.e., more efficient) had lower EI ( < 0.01) and superior ECR for RDG and REI compared with medium- and low-RIG pigs. In general, most of the correlations among the feed efficiency traits investigated in this study were different from unity, indicating that each trait is depicting a different aspect of efficiency in pigs, although the moderate to strong correlations suggest that improvement in one trait would, on average, lead to improvements in the others. Pigs ranked as more efficient on residual traits such as REI consumed less energy for a similar BW gain, which would translate into an economic benefit for pig producers.

The objective of this study was to quantify the impact of alternative contemporary group definitions for lambing traits on genetic evaluations in the Irish multibreed sheep population. Three lambing traits were considered for analysis: lambing difficulty, birth weight, and survival. Eight alternative contemporary group definitions were investigated for each lambing trait; all contemporary groups were formed within flock of lambing and included (flock by) week of lambing, week of lambing by litter size (i.e., singles vs. multiples), 2-wk interval (i.e., fortnight) of lambing, fortnight of lambing by litter size, month of lambing, and month of lambing by litter size or were based on an optimized algorithm that creates contemporary groups based on animals from the same flock that are born in close proximity of date. Three alternative scenarios were modeled for each of the lambing traits using the contemporary group definitions: the first scenario (termed Current Scenario) represented the editing criteria currently employed in the Irish national genetic evaluations; the second scenario (No Restriction Scenario) removed any restriction on number of records per contemporary group, and the final scenario (Variation Scenario) included only data from contemporary groups with some variability in the dependent variable. Variance components and EBV for each of the 3 lambing traits were estimated using linear mixed models. The direct heritability estimates ranged from 0.09 ± 0.02 to 0.29 ± 0.02 for lambing difficulty, 0.11 ± 0.01 to 0.24 ± 0.01 for birth weight, and 0.05 ± 0.02 to 0.10 ± 0.02 for lamb survival. Irrespective of lambing trait, greater estimated accuracy of the sire EBV was achieved with the No Restriction Scenario. Results for the ability to predict future lambing characteristics, based on only the direct and maternal EBV, revealed that the area under the receiver operator characteristic curve for the dichotomized lambing assistance phenotype varied from 0.56 to 0.66; a lambing event predicted to be in the worst 10% risk category of a difficult lambing on the basis of genetic merit alone was 5.48 times (95% CI: 3.94 to 7.61; < 0.001) more likely to require assistance at lambing compared to a lambing event in the best 10%. Results show that the use of contemporary groups formed over short time periods, coupled with moderate editing of the data, yielded superior predictions for all lambing traits.

The objective of the present study was to quantify, using simulations, the impact of successive generations of genotype imputation on genomic predictions. The impact of using a small reference population of true genotypes versus a larger reference population of imputed genotypes on the accuracy of genomic predictions was also investigated. After construction of a founder population, high-density (HD) genotypes ( = 43,500 single nucleotide polymorphisms, SNP) were simulated across 25 generations ( = 46,800 per generation); a low-density genotype panel ( = 3,000 SNP) was developed from these HD genotypes, which was then used to impute genotypes using 7 alternative imputation strategies. Both low (0.03) and moderately (0.35) heritable phenotypes were simulated. Direct genomic values (DGV) were estimated using imputed genotypes from the investigated scenarios and the accuracy of predicting the simulated true breeding values (TBV) were expressed relative to the accuracy when the true genotypes were used. Mean allele concordance rate and the rate of change in mean allele concordance per generation differed between the imputation strategies investigated. Imputation was most accurate when the true HD genotypes of sires and 50% of the dams of the generation being imputed were included in the reference population; the average allele concordance rate for this scenario across generations was 0.9707. The strongest correlation between the TBV and DGV of the last generation was when the reference population included sequentially imputed HD genotypes of all previous generations, plus the true HD genotypes of all sires of the previous generations (0.987 as efficient as when the true genotypes were used in the reference population). With a moderate heritability, the correlation between the TBV and the DGV using a small reference population of accurate genotypes were, on average, 0.07 units stronger compared to DGV generated using a larger population of imputed genotypes. When the heritability was low, the accuracy of genomic predictions benefited from a larger reference population, even if SNP were imputed. The impact on the accuracy of genomic predictions from the accumulation of imputation errors across generations indicates the need to routinely generate HD genotypes on influential animals to reduce the accumulation of imputation errors over generations.

Evidence exists from a range of species on the impact of karyotype abnormalities on reproductive performance. Despite this, cytogenetic analyses of cattle, especially females, are not routinely undertaken. Genome-wide single nucleotide polymorphism (SNP) genotype data are now, however, routinely being generated in many species globally at a relatively low cost. The objective of the present study was to evaluate the potential of routinely available SNP genotype data to identify sex-chromosome aberrations using X chromosome monosomy 59,X0 as a case study for illustration. A single 2.5-yr old Holstein-Friesian heifer was detected with a mean allelic intensity of SNP on the X chromosome almost 17 standard deviations less than the mean of other genotyped females ( = 103,326). Following cytogenetic analysis (10 replicates by karyotyping and a further 140 by FISH), the female was deduced to be a non-mosaic 59,X0. The female had never produced a calf and, although gross examination revealed no physical abnormalities, she was smaller in size than expected based on her breed and age. Given the age of the animal at slaughter, the uterus and uterine tubes appeared immature and inactive. The oviduct appeared normal while the single ovary present contained a markedly reduced number of follicles. There was, however, some evidence of prior ovulation and formation of corpora lutea. The approach proposed in the present study to identify allosome aneuploidy from routinely available genotype data can be used to screen for such abnormalities at no additional cost to the breeder or producer.

The objective of the present study was to quantify the within- and between-cow, operator, and day variances of various descriptive temperature parameters from different anatomical areas captured using thermal images on Holstein-Friesian cows. Three experiments were undertaken. In Exp. 1, 30 images were captured by a single operator of each of the eye, hoof, and udder from each of 45 cows; in Exp. 2, three different operators captured eye and hoof images from 12 cows; and in Exp. 3, eye and hoof images were captured by a single operator from 8 cows over a 5-d period. Maximum, minimum, and average descriptive temperature parameters were manually extracted from all thermal images within the study. The repeatability of thermal imaging and the number of replicates required to obtain a certain level of precision was evaluated. Precision was defined as the 95% CI range within which the (average of the) measured temperature(s) was expected to lie relative to the gold standard; the gold standard temperature of an entity in this study was the average of 30 temperature measurements. The partitioning of the variance into error, cow, operator, and day variances was undertaken using mixed models. Results show that the most repeatable anatomical area was the hoof, with the total proportion of variation attributed to the cow ranging from 91.37 to 99.28%. The descriptive temperature parameter with the lowest error variance was the maximum temperature for the eye (0.11°C) and udder (0.03°C) images, whereas the average temperature was the most precise descriptive temperature parameter for hoof (0.08°C) images. Additionally, no significant between-day variance was detected for maximum hoof temperatures. Results from the present study indicate that when the most precise descriptive temperature parameter is used, measurements made using infrared thermography can achieve a high level of precision in an agricultural environment if at least 3 replicate images of the eye, udder, or hooves of cows are captured and averaged. Additionally, when multiple operators capture thermal images in an agricultural environment, a standard operating procedure should be put in place to minimize the variance between operators.

Data quality of SNP arrays impacts the accuracy and precision of downstream data analyses. One such quality control measure often imposed is a threshold on individual animal call rate. Different call rate thresholds have been applied across studies; little is known, however, about the impact of these thresholds on the quality of the genotype data. The objective of the present study was to investigate the effect of different call rate thresholds on the integrity of the genotypes but also to quantify the contribution of different factors to the variability in animal call rate. Data included 142,342 samples genotyped on a custom Illumina genotype panel from 141,591 dairy and beef cattle; the number of Illumina SNP on the panel was 14,371. The mean animal call rate across all samples was 99.09%; 487 animals had both a low call rate (<99%) and a subsequent high call rate (≥99%) after resampling and regenotyping. Several factors were associated ( < 0.001) with individual call rate including animal sex, the sampling herd, the date of genotyping, the genotyping plate, and the plate well. The genotype and allele concordance between the genotypes of the 487 low- and high-call rate individuals improved at a diminishing rate as mean animal call rate increased. Mean genotype and allele concordance rates of 0.987 and 0.997, respectively, existed when animal call rate was between 85 and 90%, increasing to 0.998 and 0.999, respectively, when animal call rate was between 95 and <99%. The mean within-animal allele concordance rate of rare variants (i.e., minor allele frequency < 0.05) between low and high genotype call rate animals increased when animal call rate improved; an allele concordance rate of 1.00 was achieved when animal call rate was between 85 and <99%. The accuracy of imputation of the nonobserved genotypes in the low-call rate animals improved as animal call rate increased; the mean genotype concordance rate of the imputed nonobserved SNP was 0.41 when animal call rate was <40% but increased to 0.95 when animal call rate was between 95 and <99%. Parentage validation, determined by the count of opposing homozygotes in a parent-progeny pair, was unreliable when animal call rate was <85%. Therefore, to ensure the provision of high-quality genotypes while also considering the cost and inconvenience of resampling and regenotyping, we suggest a minimum animal call rate threshold of 85%.

is a helminth parasite of economic importance to the global cattle industry, with documented high international herd prevalence. The objective of the present study was to generate the first published genetic parameter estimates for liver damage caused by as well as antibody response to in cattle. Abattoir data on the presence of live , or -damaged livers, were available between the years 2012 and 2015, inclusive. A second data set was available on cows from 68 selected dairy herds with a blood ELISA test for antibody response to in autumn 2015. Animals were identified as exposed by using herd mate phenotype, and only exposed animals were retained for analysis. The abattoir data set consisted of 20,481 dairy cows and 75,041 young dairy and beef animals, whereas the study herd data set consisted of 6,912 dairy cows. (Co)variance components for phenotypes in both data sets were estimated using animal linear mixed models. Fixed effects included in the model for both data sets were contemporary group, heterosis coefficient, recombination loss coefficient, parity, age relative to parity/age group, and stage of lactation. An additional fixed effect of abattoir by date of slaughter was included in the model for the analysis of the abattoir data. Direct additive genetic effects and a residual effect were included as random effects for all analyses. After data edits, the prevalence of liver damage caused by in cows and young cattle was 47% and 20%, respectively. The prevalence of a positive antibody response to in cows from the study herd data was 36% after data edits. The heritability of as a binary trait for dairy cows in abattoir data and study herd data was 0.03 ± 0.01 and 0.09 ± 0.02, respectively; heritability in young cattle was 0.01 ± 0.005. The additive genetic SD of as a binary trait was 0.069 and 0.050 for cows and young cattle from the abattoir data, respectively, and 0.112 from the study herd cows. The genetic correlation between liver damage caused by in young cattle and cows from the abattoir data was 0.94 ± 0.312 and the genetic correlation between liver damage caused by in cows and positive antibody response to in cows in the study herd data was 0.37 ± 0.283.

Livestock mature at different rates depending, in part, on their genetic merit; therefore, the optimal age at slaughter for progeny of certain sires may differ. The objective of the present study was to examine sire-level genetic profiles for carcass weight, carcass conformation, and carcass fat in cattle of multiple beef and dairy breeds, including crossbreeds. Slaughter records from 126,214 heifers and 124,641 steers aged between 360 and 1,200 d and from 86,089 young bulls aged between 360 and 720 d were used in the analysis; animals were from 15,127 sires. Variance components for each trait across age at slaughter were generated using sire random regression models that included quadratic polynomials for fixed and random effects; heterogeneous residual variances were assumed across ages. Heritability estimates across genders ranged from 0.08 (±0.02) to 0.34 (±0.02) for carcass weight, from 0.24 (±0.02) to 0.42 (±0.01) for conformation, and from 0.16 (±0.03) to 0.40 (±0.02) for fat score. Genetic correlations within each trait across ages weakened as the interval between ages compared lengthened but were all >0.64, suggesting a similar genetic background for each trait across different ages. Eigenvalues and eigenfunctions of the additive genetic covariance matrix revealed genetic variability among animals in their growth profiles for carcass traits, although most of the genetic variability was associated with the height of the growth profile. At the same age, a positive genetic correlation (0.60 to 0.78; SE ranged from 0.01 to 0.04) existed between carcass weight and conformation, whereas negative genetic correlations existed between fatness and both conformation (-0.46 to 0.08; SE ranged from 0.02 to 0.09) and carcass weight (-0.48 to -0.16; SE ranged from 0.02 to 0.14) at the same age. The estimated genetic parameters in the present study indicate genetic variability in the growth trajectory in cattle, which can be exploited through breeding programs and used in decision support tools.

The objective of this study was to develop, using alternative algorithms, low-density SNP genotyping panels (384 to 12,000 SNP), which can be accurately imputed to higher-density panels across independent cattle populations. Single nucleotide polymorphisms were selected based on genomic characteristics (i.e., linkage disequilibrium [LD], minor allele frequency [MAF], and genomic distance) in a population of 1,267 Holstein-Friesian animals genotyped on the Illumina Bovine50 Beadchip (54,001 SNP). Single nucleotide polymorphism selection methods included 1) random; 2) equidistant location; 3) combination of SNP MAF and LD structure while maintaining relatively equal genomic distance between adjacent SNP; 4) a combination of high MAF, genomic distance between selected and candidate SNP, and correlation between genotypes of selected and candidate SNP; and 5) a machine learning algorithm. The panels were validated separately in 1) a population of 750 Holstein-Friesian animals with masked genotypes to reflect the lower-density SNP densities under investigation (1,249 animals with complete genotypes included in reference population) and 2) a population of 359 Limousin and Charolais cattle with high (777,962 SNP)-density genotypes (1,918 animals with complete genotypes included in the reference population). Irrespective of SNP selection method, imputation accuracy in both populations improved at a diminishing rate as the number of SNP included in the lower-density genotype panel increased. Additionally, the variability in mean imputation accuracy per individual decreased as the panel density increased. The SNP selection method had a major impact on the mean allele concordance rate, although its impact diminished as the panel density increased. Imputation accuracy for SNP selected using a combination of high SNP MAF, LD structure, and relatively equal genomic distance between SNP outperformed all other selection methods in densities < 12,000 SNP. Using this method of SNP selection, the correlation between the imputed and actual genotypes for the 3,000 SNP panel was 0.90 and 0.96 when applied to the beef and dairy populations, respectively; the respective correlations for the 6,000 SNP panel were 0.95 and 0.98. It is necessary to include between 3,000 and 6,000 SNP in a low-density panel to achieve adequate imputation accuracy to either medium density (approximately 50,000 SNP in the dairy population) or high density (approximately 700,000 SNP in the beef population) across diverse and independent populations.

Due primarily to a lack of phenotypic data, little research has been undertaken on the genetics of reproductive performance in beef cattle. The objective of this study was to quantify, using data from the Irish national cattle herd, the contribution of additive genetics to phenotypic differences in reproductive performance in beef cattle and to investigate whether routinely available early predictors of genetic merit for reproductive performance exist. Up to 218,718 parity records from 156,506 animals were used to estimate variance components for a range of reproductive traits using repeatability animal linear mixed models. Covariances with performance traits were estimated using bivariate sire linear mixed models. The reproductive traits were age at first calving, calving in the first 42 d of the calving seasons (defined separately in heifers and cows), calving interval between consecutive calving events, and survival to the next lactation. Performance traits included calving dystocia, linear type traits describing the skeletal, muscular, and functional characteristics of an animal, live weight and price, carcass traits, and producer subjectively scored traits of weanling quality and docility. Heritability for age at first calving was 0.31 while the heritability of the remaining reproductive traits ranged from 0.01 to 0.06; repeatability estimates varied from 0.02 to 0.06. Increased muscularity, measured either by trained assessors or producers on live animals, or by mechanical grading machines on slaughtered animals (i.e., carcass conformation), was genetically correlated with reduced reproductive performance for some of the reproductive variables assessed. This is one of the largest studies undertaken on the genetics of reproduction in beef herds and clearly shows that genetic selection for improved reproductive performance in beef herds is feasible. However, breeding goals that select for muscularity and live weight or growth rate should be cognizant of indirect response to selection that may cause any deterioration in reproductive performance.

Genetic evaluations provide information to aid in breeding decisions that increase long-term performance of animals and herds. However, to date no study has been undertaken to investigate the accuracy of the Irish maternal genetic evaluations in beef cattle. The objective, therefore, of this study was to quantify the relationship between phenotypic performance and measures of genetic merit for predominantly maternal-related traits in Irish beef cattle. The association between animal EBV for calving interval, age at first calving, and both direct and maternal weaning weight with the respective phenotypic performance was quantified using a fixed effects model; the expectation for the regression coefficient of phenotypic performance on EBV was one. The association between genetic merit for cow survival, perinatal mortality, calving assistance, and calving dystocia with the log of the odds of the respective trait was quantified using logistic regression. The association analyses were conducted using field data on up to 38,619 records from 5,236 herds. Age at first calving increased linearly by 0.32 ± 0.15 (P = 0.03) days per day increase in EBV for age at first calving. Calving interval increased by, on average, 0.58 ± 0.16 (P = 0.002) days per day increase in EBV for calving interval although the association differed by parity with a greater association in pluriparae. Weaning weight increased linearly by 1.74 ± 0.09 and 0.84 ± 0.16 kg (P < 0.001) per kilogram increase in EBV for direct and maternal weaning weight, respectively. The log of the odds of a cow surviving to next lactation increased linearly by 0.16 ± 0.03 (P < 0.001) per unit increase in EBV for cow survival. The log of the odds of an assisted calving or dystocia both increased linearly by 0.21 ± 0.01 and 0.24 ± 0.01, respectively, per unit increase in EBV for direct calving difficulty (P < 0.001). The log of the odds of a dead calf at birth increased linearly by 0.93 ± 0.13 (P < 0.001) per unit increase in EBV for calf mortality. Results from this study show that selection of breeding animals for favorable maternal genetic attributes will result in favorable improvements in performance and profitability.

The objective of this study was to quantify the phenotypic and genetic risk factors associated with multiple ovulations and twin births in cattle. Prevalence and cow- and herd-level risk factors associated with ovulation rate were determined using 40,617 ultrasonographic records of the reproductive tract from 27,907 dairy and beef cows from 738 commercial herds. Prevalence of twin births was estimated from the Irish national database containing 23,658,351 calving events from 8,546,695 cows from 125,251 dairy and beef herds; factors associated with twin births were determined using a random subsample of 505,200 calving events from 280,638 cows in 81,329 herds. The mean prevalence of multiple ovulations was 6.83% while the prevalence of twin births was 1.74%. Occurrence of both multiple ovulations and twin births was associated with the month of scan (P < 0.0001) and month of calving (P < 0.0001), respectively, and peaked in November for multiple ovulations and October for twin births. The likelihood of multiple ovulations increased with interval postpartum and peaked between 45 to 185 d postcalving, after which the likelihood declined. The likelihood of both multiple ovulations (P < 0.0001) and twin births (P < 0.0001) increased with increasing cow parity. A greater proportion of Holstein, Friesian, Simmental, Hereford, and Charolais breed fractions were associated with a greater likelihood of multiple ovulations. There was no difference between breed proportion of the cow and incidence of twin births, where all breed proportions examined, litter difference existed among breeds in their association with risk of twin births. Although multiple ovulations were lowly heritable (0.028 ± 0.003), their occurrence was repeatable (0.326 ± 0.342) while twin birth rate in cattle was lowly heritable (0.017 ± 0.004) and repeatable (0.018 ± 0.011). The genetic SD of the presence of multiple ovulations and twin births was 0.04 and 0.02, respectively, indicating considerable genetic variation, especially for multiple ovulations. A moderate genetic correlation (0.66 ± 0.16) existed between multiple ovulations and twin births.

Residual feed intake (RFI) is the difference between observed and predicted feed intake. It is calculated as the residuals from a multiple regression model of DMI on the various energy expenditures (e.g., maintenance, growth, activity). Residual feed intake is often cited to be indicative of feed efficiency differences among animals. However, explaining a large proportion of the (phenotypic and genetic) interanimal variation in RFI remains difficult. Here we first describe a biological framework for RFI dwelling on similarities between RFI and energy balance. Alternative phenotypic and genetic statistical models are subsequently applied to a dataset of 1,963 growing bulls of 2 British and 3 Continental breeds. The novel aspect of this study was the use of a mixed model framework to quantify the heritable interanimal variation in the partial regression coefficients on the energy expenditure traits within the RFI equation. Heritable genetic variation in individual animal regression coefficients for metabolic live weight existed. No significant genetic variation in animal-level regression coefficients for growth or body fat level, however, existed in the study population. The presence of genetic variation in the partial regression coefficient of maintenance suggests the existence of interanimal variation in maintenance efficiency. However, it could also simply reflect interanimal genetic variation in correlated energy expenditure traits not included in the statistical model. Estimated breeding values for the random regression coefficient could be useful phenotypes in themselves for studies wishing to elucidate the underlying mechanisms governing differences among animals in RFI.

Increasing food production for the growing human population off a constraining land base will require greater efficiency of production. Genetic improvement of feed efficiency in cattle, which is cumulative and permanent, is one likely vehicle to achieving efficiency gains. The objective of this review is to summarize genetic parameters for feed efficiency traits in dairy and beef cattle and also to address some of the misconceptions associated with feed efficiency in these sectors, as well as discuss the potential use of feed efficiency in breeding programs. A meta-analysis of up to 39 scientific publications in growing cattle clearly showed that genetic variation in feed efficiency exists with a pooled heritability for residual feed intake (RFI) and feed conversion efficiency of 0.33 ± 0.01 (range of 0.07 to 0.62) and 0.23 ± 0.01 (range of 0.06 to 0.46), respectively. Heritability estimates for feed efficiency in cows were lower; a meta-analysis of up to 11 estimates revealed heritability estimates for gross feed efficiency and RFI of 0.06 ± 0.010 and 0.04 ± 0.008, respectively. Meta-analysis of genetic correlations between feed intake, feed efficiency and other performance traits are presented, and selection index theory is used to calculate the proportion of genetic variation in feed intake that can be explained by easy to measure, and often already collected, data. A large proportion of the genetic variation in feed intake could be explained in both growing animals and lactating animals using up to 5 predictor traits, including BW, growth rate, milk yield, body composition, and linear type traits reflecting body size and muscularity. Knowledge of genetic merit for feed intake can be used, along with estimates of genetic merit for energy sinks, to calculate genetic merit for feed efficiency. Therefore, the marginal benefit of collecting actual feed intake data, using the genetic parameters used in this study, appears to be low. There is now sufficient information available to develop a road map on how best to direct research to ensure long-term food security for a growing human population. Gaps in knowledge are identified here, and possibilities to address these gaps are discussed.

Interest in improving feed efficiency in cattle is intensifying. Residual feed intake (RFI), which is the difference between expected intake and that predicted based on energy demands, is now the most commonly used measure of feed efficiency over a given time period. However, RFI, as commonly defined, is independent of growth rate, which may affect its acceptance by industry. Residual BW gain (RG) has also been proposed as a measure of feed efficiency and is represented as the residuals from a multiple regression model regressing ADG on both DMI and BW. In this study, we propose a new trait, residual intake and BW gain (RIG), which retains the favorable characteristic of both RFI and RG being independent of BW, but animals superior for RIG have, on average, both greater ADG and reduced DMI. Phenotypic and genetic analyses were undertaken on up to 2,605 purebred performance-tested bulls. Clear phenotypic differences in DMI and ADG existed between animals divergent for RIG. The heritability of RIG was 0.36 ± 0.06, which is consistent with the heritability estimates of RFI and other feed efficiency traits measured in the study. The RIG trait was both phenotypically and genetically negatively correlated with DMI and positively correlated with ADG; no correlation existed between RIG and BW. The advantages of both reduced daily DMI and greater ADG in animals superior for RIG are demonstrated compared with animals superior for either RFI or RG.

Interest in selection for improved feed efficiency is increasing, but before any steps are taken toward selecting for feed efficiency, correlations with other economically important traits must first be quantified. The objective of this study was to quantify the genetic associations between feed efficiency measured during performance testing and linear type traits, BW, live animal value, and carcass traits recorded in commercial herds. Feed efficiency data were available on 2,605 bulls from 1 performance test station. There were between 10,384 and 93,442 performance records on type traits, BW, animal value, or carcass traits from 17,225 commercial herds. (Co)variance components were estimated using linear mixed animal models. Genetic correlations between the muscular type traits in commercial animals and feed conversion ratio (-0.33 to -0.25), residual feed intake (RFI; -0.33 to -0.22), and residual BW gain (RG; 0.24 to 0.27) suggest that selection for improved feed efficiency should increase muscling. This is further evidenced by the genetic correlations between carcass conformation of commercial animals and feed conversion ratio (-0.46), RFI (-0.37), and residual BW gain (0.35) measured in performance-tested animals. Furthermore, the genetic correlations between RFI and both ultrasonic fat depth and carcass fat score (0.39 and 0.33, respectively) indicated that selection for improved RFI will result in leaner animals. It can be concluded from the genetic correlations estimated in this study that selection for feed efficiency will have no unfavorable effects on the performance traits measured in this study and will actually lead to an improvement in performance for some traits, such as muscularity, animal price, and carcass conformation. Conversely, this suggests that genetic selection for traits such as carcass quality, muscling traits, and animal value might also be indirectly selecting for more efficient animals.

Most studies on feed efficiency in beef cattle have focused on performance in young animals despite the contribution of the cow herd to overall profitability of beef production systems. The objective of this study was to quantify, using a large data set, the genetic covariances between feed efficiency in growing animals measured in a performance-test station, and beef cow performance including fertility, survival, calving traits, BW, maternal weaning weight, cow price, and cull cow carcass characteristics in commercial herds. Feed efficiency data were available on 2,605 purebred bulls from 1 test station. Records on cow performance were available on up to 94,936 crossbred beef cows. Genetic covariances were estimated using animal and animal-dam linear mixed models. Results showed that selection for feed efficiency, defined as feed conversion ratio (FCR) or residual BW gain (RG), improved maternal weaning weight as evidenced by the respective genetic correlations of -0.61 and 0.57. Despite residual feed intake (RFI) being phenotypically independent of BW, a negative genetic correlation existed between RFI and cow BW (-0.23; although the SE of 0.31 was large). None of the feed efficiency traits were correlated with fertility, calving difficulty, or perinatal mortality. However, genetic correlations estimated between age at first calving and FCR (-0.55 ± 0.14), Kleiber ratio (0.33 ± 0.15), RFI (-0.29 ± 0.14), residual BW gain (0.36 ± 0.15), and relative growth rate (0.37 ± 0.15) all suggest that selection for improved efficiency may delay the age at first calving, and we speculate, using information from other studies, that this may be due to a delay in the onset of puberty. Results from this study, based on the estimated genetic correlations, suggest that selection for improved feed efficiency will have no deleterious effect on cow performance traits with the exception of delaying the age at first calving.

Beef outputs from dairy farms make an important contribution to overall profitability in Irish dairy herds and are the sole source of revenue in many beef herds. The aim of this study was to estimate genetic parameters for animal BW and price across different stages of maturity. Data originated from 2 main sources: price and BW from livestock auctions and BW from on-farm weighings between 2000 and 2008. The data were divided into 4 distinct maturity categories: calves (n = 24,513), weanlings (n = 27,877), postweanlings (n = 23,279), and cows (n = 4,894). A univariate animal model used to estimate variance components was progressively built up to include a maternal genetic effect and a permanent environmental maternal effect. Bivariate analyses were used to estimate genetic covariances between BW and price per animal within and across maturity category. Direct heritability estimates for price per animal were 0.34 ± 0.03, 0.31 ± 0.05, 0.19 ± 0.04, and 0.10 ± 0.04 for calves, weanling, postweanlings, and cows, respectively. Direct heritability estimates for BW were 0.26 ± 0.03 for weanlings, 0.25 ± 0.04 for postweanlings, and 0.24 ± 0.06 for cows; no BW data were available on calves. Significant maternal genetic and maternal permanent environmental effects were observed for weanling BW only. The genetic correlation between price per animal and BW within each maturity group varied from 0.55 ± 0.06 (postweanling price and BW) to 0.91 ± 0.04 (cow price and BW). The availability of routinely collected data, along with the existence of ample genetic variation for animal BW and price per animal, facilitates their inclusion in Irish dairy and beef breeding objectives to better reflect the profitability of both enterprises.