Associations between a range of enteric methane emission traits and performance traits in indoor-fed growing cattle.

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.

Exploring definitions of daily enteric methane emission phenotypes for genetic evaluations using a population of indoor-fed multi-breed growing cattle with feed intake data.

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.

Adenylate kinase 9 is essential for sperm function and male fertility in mammals.

Despite passing routine laboratory tests for semen quality, bulls used in artificial insemination exhibit significant variation in fertility. Routine analysis of fertility data identified a dairy bull with extreme subfertility (10% pregnancy rate). To characterize the subfertility phenotype, a range of in vitro, in vivo, and molecular assays were carried out.

Accelerated matrix-vector multiplications for matrices involving genotype covariates with applications in genomic prediction.

In the last decade, a number of methods have been suggested to deal with large amounts of genetic data in genomic predictions. Yet, steadily growing population sizes and the suboptimal use of computational resources are pushing the practical application of these approaches to their limits. As an extension to the C/CUDA library , we have developed tailored solutions for the computation of genotype matrix multiplications which is a critical bottleneck in the empirical evaluation of many statistical models.

Efficient large-scale single-step evaluations and indirect genomic prediction of genotyped selection candidates.

Background: Single-step genomic best linear unbiased prediction (ssGBLUP) models allow the combination of genomic, pedigree, and phenotypic data into a single model, which is computationally challenging for large genotyped populations. In practice, genotypes of animals without their own phenotype and progeny, so-called genotyped selection candidates, can become available after genomic breeding values have been estimated by ssGBLUP. In some breeding programmes, genomic estimated breeding values (GEBV) for these animals should be known shortly after obtaining genotype information but recomputing GEBV using the full ssGBLUP takes too much time.

A breed-of-origin of alleles model that includes crossbred data improves predictive ability for crossbred animals in a multi-breed population.

Background: Recently, crossbred animals have begun to be used as parents in the next generations of dairy and beef cattle systems, which has increased the interest in predicting the genetic merit of those animals. The primary objective of this study was to investigate three available methods for genomic prediction of crossbred animals. In the first two methods, SNP effects from within-breed evaluations are used by weighting them by the average breed proportions across the genome (BPM method) or by their breed-of-origin (BOM method).

Phenotypic relationship and repeatability of methane emissions and performance traits in beef cattle using a GreenFeed system.

Rumen methanogenesis results in the loss of 6% to 10% of gross energy intake in cattle and globally is the single most significant source of anthropogenic methane (CH4) emissions. The purpose of this study was to analyze greenhouse gas traits recorded in a commercial feedlot unit to gain an understanding into the relationships between greenhouse gas traits and production traits. Methane and carbon dioxide (CO2) data recorded via multiple GreenFeed Emission Monitoring (GEM), systems as well as feed intake, live weight, ultrasound scanning data, and slaughter data were available on 1,099 animals destined for beef production, of which 648 were steers, 361 were heifers, and 90 were bulls.

Detection of Genomic Imprinting for Carcass Traits in Cattle Using Imputed High-Density Genotype Data.

Genomic imprinting is an epigenetic phenomenon defined as the silencing of an allele, at least partially, at a given locus based on the sex of the transmitting parent. The objective of the present study was to detect the presence of SNP-phenotype imprinting associations for carcass weight (), carcass conformation () and carcass fat () in cattle. The data used comprised carcass data, along with imputed, high-density genotype data on 618,837 single nucleotide polymorphisms () from 23,687 cattle; all animal genotypes were phased with respect to parent of origin.

The Association Between Genomic Heterozygosity and Carcass Merit in Cattle.

The objective of the present study was to quantify the association between both pedigree and genome-based measures of global heterozygosity and carcass traits, and to identify single nucleotide polymorphisms () exhibiting non-additive associations with these traits. The carcass traits of interest were carcass weight (), carcass conformation () and carcass fat (). To define the genome-based measures of heterozygosity, and to quantify the non-additive associations between SNPs and the carcass traits, imputed, high-density genotype data, comprising of 619,158 SNPs, from 27,213 cattle were used.

Predicting carcass cut yields in cattle from digital images using artificial intelligence.

Deep Learning (DL) has proven to be a successful tool for many image classification problems but has yet to be applied to carcass images. The aim of this study was to train DL models to predict carcass cut yields and compare predictions to more standard machine learning (ML) methods. Three approaches were undertaken to predict the grouped carcass cut yields of Grilling cuts and Roasting cuts from a large dataset of 54,598 and 69,246 animals respectively.

Contribution of herd characteristics to best linear unbiased estimates of slaughter traits in beef cattle.

Genetic evaluations separate phenotypes into their contributing additive genetic effects and non-(additive) genetic effects, with the former termed best linear unbiased predictions, and the latter termed best linear unbiased estimates (BLUEs). For the purpose of the present study, genetic evaluations, along with phenotypic data from 4 137 376 animals, were used to generate herd, year of slaughter and sex contemporary group BLUEs for various slaughter-related traits. These slaughter traits included carcass weight (CW), carcass conformation (CC) and carcass fat (CF).

Herd solutions from genetic evaluations can be used as a tool to rescale the expected expression of genetic potential in cattle.

The objective of this study was to determine whether response to selection for carcass weight (CW), conformation (CC) and fat (CF), and the association between heterosis and carcass performance varied by herd environment in cattle. Following edits, carcass information was available for 4,616,761 cattle, of which the majority were some crossbred combination of the following breeds: Angus, Aubrac, Belgian Blue, Blonde d'Aquitaine, Charolais, Hereford, Holstein-Friesian, Jersey, Limousin, Saler, Shorthorn and Simmental. Herd environment was defined separately for each carcass trait using herd solutions outputted from carcass trait genetic evaluations.

Identification of genomic regions that exhibit sexual dimorphism for size and muscularity in cattle.

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.

An index framework founded on the future profit potential of female beef cattle to aid the identification of candidates for culling.

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 achievement of a given carcass specification is under moderate genetic control in cattle.

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.

Breed- and trait-specific associations define the genetic architecture of calving performance traits in cattle.

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.

Genomic Regions Associated With Skeletal Type Traits in Beef and Dairy Cattle Are Common to Regions Associated With Carcass Traits, Feed Intake and Calving Difficulty.

Linear type traits describing the skeletal characteristics of an animal are moderately to strongly genetically correlated with a range of other performance traits in cattle including feed intake, reproduction traits and carcass merit; thus, type traits could also provide useful insights into the morphological differences among animals underpinning phenotypic differences in these complex traits. The objective of the present study was to identify genomic regions associated with five subjectively scored skeletal linear traits, to determine if these associated regions are common in multiple beef and dairy breeds, and also to determine if these regions overlap with those proposed elsewhere to be associated with correlated performance traits. Analyses were carried out using linear mixed models on imputed whole genome sequence data separately in 1,444 Angus, 1,129 Hereford, 6,433 Charolais, 8,745 Limousin, 1,698 Simmental, and 4,494 Holstein-Friesian cattle, all scored for the linear type traits.

Genomic regions associated with muscularity in beef cattle differ in five contrasting cattle breeds.

Background: Linear type traits, which reflect the muscular characteristics of an animal, could provide insight into how, in some cases, morphologically very different animals can yield the same carcass weight. Such variability may contribute to differences in the overall value of the carcass since primal cuts vary greatly in price; such variability may also hinder successful genome-based association studies. Therefore, the objective of our study was to identify genomic regions that are associated with five muscularity linear type traits and to determine if these significant regions are common across five different breeds.

Genomic Regions Associated With Gestation Length Detected Using Whole-Genome Sequence Data Differ Between Dairy and Beef Cattle.

While many association studies exist that have attempted to relate genomic markers to phenotypic performance in cattle, very few have considered gestation length as a phenotype, and of those that did, none used whole genome sequence data from multiple breeds. The objective of the present study was therefore to relate imputed whole genome sequence data to estimated breeding values for gestation length using 22,566 sires (representing 2,262,706 progeny) of multiple breeds [Angus (AA), Charolais (CH), Holstein-Friesian (HF), and Limousin (LM)]. The associations were undertaken within breed using linear mixed models that accounted for genomic relatedness among sires; a separate association analysis was undertaken with all breeds analysed together but with breed included as a fixed effect in the model.

Using the difference in actual and expected calf liveweight relative to its dam liveweight as a statistic for interherd and intraherd benchmarking and genetic evaluations1.

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.

Linear classification scores in beef cattle as predictors of genetic merit for individual carcass primal cut yields1.

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.

Genome-wide association study of endo-parasite phenotypes using imputed whole-genome sequence data in dairy and beef cattle.

Background: Quantitative genetic studies suggest the existence of variation at the genome level that affects the ability of cattle to resist to parasitic diseases. The objective of the current study was to identify regions of the bovine genome that are associated with resistance to endo-parasites.

Methods: Individual cattle records were available for Fasciola hepatica-damaged liver from 18 abattoirs.

Dressing percentage and the differential between live weight and carcass weight in cattle are influenced by both genetic and non-genetic factors1.

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.

Myristate-induced endoplasmic reticulum stress requires ceramide synthases 5/6 and generation of C14-ceramide in intestinal epithelial cells.

Saturated fatty acids (SFAs) have been shown to induce endoplasmic reticulum (ER) stress and chronic inflammatory responses, as well as alter sphingolipid metabolism. Disruptions in ER stress and sphingolipid metabolism have also been implicated in intestinal inflammation. Therefore, to elucidate the roles of SFAs in ER stress and inflammation in intestinal epithelial cells, we examined myristate (C14:0) and palmitate (C16:0).