Estimating backfat depth, loin depth, and intramuscular fat percentage from ultrasound images in swine.

Fast, accurate, and reliable estimates of backfat depth, loin depth, and intramuscular fat percentage in swine breeding stock are used to increase genetic improvement and farm profitability. The objective of this study was to develop an equation-based model for the estimation of swine backfat depth, loin depth, and intramuscular fat percentage estimates obtained from longitudinal ultrasound images. Images were collected from purebred Duroc (n = 230), purebred Large White (n = 154), and commercial (n = 190) pigs born in January 2021 at three farms located in North Carolina. An Exapad ultrasound machine captured longitudinal images across the 10th to 13th ribs at 182 (±12.8 SD) days of pig age. The total number of images processed for Duroc, Large White, and commercial pigs was 1 385, 928, and 1 168 images, respectively. To establish a standard measurement for model comparison, trained personnel following standard company procedures using the BioSoft Toolbox (v4.0.1.2; Biotronics Inc., Ames, IA) obtained backfat and loin depth measurements from the images. Longissimus muscle intramuscular fat percentage was predicted using near-infrared spectroscopy at approximately 22 h postmortem. Backfat and loin depth estimation were conducted only for commercial pigs (n = 190) while intramuscular fat estimation was conducted on all pigs (n = 574). Average backfat depth, loin depth, and intramuscular fat percentage were 14.6 (±2.6 SD) mm, 63.7 (±5.5 SD) mm, and 2.21 (±0.82 SD) %. Image analysis and estimation model development were conducted in MATLAB R2021a. Edge detection via the image gradient was applied to segment ultrasound images into backfat, loin, and rib regions. Segmented images were used to estimate backfat depth, loin depth, and loin intramuscular fat percentage. After image quality control and filtering, the image inclusion rate for each breed-trait combination ranged from 76 to 97%. All Duroc and commercial pigs and 97% of Large White pigs were represented by at least one image for trait estimation. Coefficient of determination of models for the estimation of backfat depth, loin depth, and intramuscular fat percentage were 0.58, 0.57, and 0.56, respectively. Root mean square error of backfat depth, loin depth, and intramuscular fat estimation were 1.65 mm, 3.58 mm, and 0.54%, respectively. Results demonstrate the feasibility of using ultrasound image gradient and an equation-based approach to estimate swine backfat and loin depth, and intramuscular fat percentage. This equation-based approach to estimate carcass traits in live swine can enhance genetic improvement.

A heuristic method to identify runs of homozygosity associated with reduced performance in livestock.

Although, for the most part, genome-wide metrics are currently used in managing livestock inbreeding, genomic data offer, in principle, the ability to identify functional inbreeding. Here, we present a heuristic method to identify haplotypes contained within a run of homozygosity (ROH) associated with reduced performance. Results are presented for simulated and swine data. The algorithm comprises 3 steps. Step 1 scans the genome based on marker windows of decreasing size and identifies ROH genotypes associated with an unfavorable phenotype. Within this stage, multiple aggregation steps reduce the haplotype to the smallest possible length. In step 2, the resulting regions are formally tested for significance with the use of a linear mixed model. Lastly, step 3 removes nested windows. The effect of the unfavorable haplotypes identified and their associated haplotype probabilities for a progeny of a given mating pair or an individual can be used to generate an inbreeding load matrix (ILM). Diagonals of ILM characterize the functional individual inbreeding load (IIL). We estimated the accuracy of predicting the phenotype based on IIL. We further compared the significance of the regression coefficient for IIL on phenotypes with genome-wide inbreeding metrics. We tested the algorithm using simulated scenarios (12 scenarios), combining different levels of linkage disequilibrium (LD) and number of loci impacting a quantitative trait. Additionally, we investigated 9 traits from 2 maternal purebred swine lines. In simulated data, as the LD in the population increased, the algorithm identified a greater proportion of the true unfavorable ROH effects. For example, the proportion of highly unfavorable true ROH effects identified rose from 32 to 41% for the low- to the high-LD scenario. In both simulated and real data, the haplotypes identified were contained within a much larger ROH (9.12-12.1 Mb). The IIL prediction accuracy was greater than 0 across all scenarios for simulated data (mean of 0.49 [95% confidence interval 0.47-0.52] for the high-LD scenario) and for nearly all swine traits (mean of 0.17 [SD 0.10]). On average, across simulated and swine data sets, the IIL regression coefficient was more closely related to progeny performance than any genome-wide inbreeding metric. A heuristic method was developed that identified ROH genotypes with reduced performance and characterized the combined effects of ROH genotypes within and across individuals.

Geno-Diver: A combined coalescence and forward-in-time simulator for populations undergoing selection for complex traits.

Geno-Diver is a combined coalescence and forward-in-time simulator designed to simulate complex traits with a quantitative and/or fitness component and implement multiple selection and mating strategies utilizing pedigree or genomic information. The simulation is carried out in two steps. The first step generates whole-genome sequence data for founder individuals. A variety of trait architectures can be generated for quantitative and fitness traits along with their covariance. The second step generates new individuals forward-in-time based on a variety of selection and mating scenarios. Genetic values are predicted for individuals utilizing pedigree or genomic information. Relationship matrices and their associated inverses are generated using computationally efficient routines. We benchmarked Geno-Diver with a previous simulation program and described how to simulate a traditional quantitative trait along with a quantitative and fitness trait. A user manual with examples, source code in C++11 and executable versions of Geno-Diver for Linux are freely available at https://github.com/jeremyhoward/Geno-Diver.

The effect of breed and sex on sulfamethazine, enrofloxacin, fenbendazole and flunixin meglumine pharmacokinetic parameters in swine.

Drug use in livestock has received increased attention due to welfare concerns and food safety. Characterizing heterogeneity in the way swine populations respond to drugs could allow for group-specific dose or drug recommendations. Our objective was to determine whether drug clearance differs across genetic backgrounds and sex for sulfamethazine, enrofloxacin, fenbendazole and flunixin meglumine. Two sires from each of four breeds were mated to a common sow population. The nursery pigs generated (n = 114) were utilized in a random crossover design. Drugs were administered intravenously and blood collected a minimum of 10 times over 48 h. A non-compartmental analysis of drug and metabolite plasma concentration vs. time profiles was performed. Within-drug and metabolite analysis of pharmacokinetic parameters included fixed effects of drug administration date, sex and breed of sire. Breed differences existed for flunixin meglumine (P-value<0.05; Cl, Vdss ) and oxfendazole (P-value<0.05, AUC0→∞ ). Sex differences existed for oxfendazole (P-value < 0.05; Tmax ) and sulfamethazine (P-value < 0.05, Cl). Differences in drug clearance were seen, and future work will determine the degree of additive genetic variation utilizing a larger population.

The effect of myostatin genotype on body temperature during extreme temperature events.

Extreme heat and cold events can create deleterious physiological changes in cattle as they attempt to cope. The genetic background of animals can influence their response to these events. The objective of the current study was to determine the impact of myostatin genotype (MG) on body temperature during periods of heat and cold stress. Two groups of crossbred steers and heifers of unknown pedigree and breed fraction with varying percentages of Angus, Simmental, and Piedmontese were placed in a feedlot over 2 summers and 2 winters. Before arrival, animals were genotyped for the Piedmontese-derived myostatin mutation (C313Y) to determine their MG as either homozygous normal (0 copy; n = 84), heterozygous (1 copy; n = 96), or homozygous for inactive myostatin (2 copy; n = 59). Hourly tympanic and vaginal temperature measurements were collected for steers and heifers, respectively, for 5 d during times of anticipated heat and cold stress. Mean (±SD) ambient temperature for summer and winter stress events were 24.4 (±4.64) and -1.80 (±11.71), respectively. A trigonometric function (sine + cosine) with periods of 12 and 24 h was used to describe the diurnal cyclical pattern. Hourly body temperature was analyzed within a season, and fixed effects included MG, group, trigonometric functions nested within group, and interaction of MG with trigonometric functions nested within group; random effects were animal and residual (Model [I]). A combined analysis of season and group was also investigated with the inclusion of season as a main effect and the nesting of effects within both group and season (Model [C]). In both models, the residual was fitted using an autoregressive covariance structure. A 3-way interaction of MG, season, and trigonometric function periodicities of 24 h (P < 0.001) and 12 h (P < 0.02) for Model [C] indicate that a genotype × environment interaction exists for MG. For MG during summer stress events the additive estimate was 0.10°C (P < 0.01) and dominance estimate was -0.12°C (P < 0.001). During winter stress events the additive estimate was 0.10°C (P < 0.001) and dominance estimate was 0.054°C (P > 0.05). The current study illustrated that a genotype × environment interaction exists for MG and 1-copy animals were more robust to environmental extremes in comparison with 0- or 2-copy animals.

Perspectives on the etiology of Alzheimer's disease.

There is a lack of consensus among investigators concerning the etiology of Alzheimer's disease. Clues are not lacking, however, and we have assessed them in a broad biologic context. This inquiry has led us to regard Alzheimer's disease as a multifactorial disorder in which a putative infective agent is an essential element. Despite seeming competition among current hypotheses, there is overall unity. The concept that Down's syndrome is a congenital form of Alzheimer's disease and that both conditions are the result of a ubiquitous infective pathogen that affects genetically susceptible individuals offers the broadest unification. In both conditions slow infection develops against the background of aging. Indirect evidence involving immunologic and other biologic phenomena supports the postulated infectious origin. Overlapping pathologic and clinical features of Alzheimer's disease and the known transmissible encephalopathies suggest a similar pathogenesis.