Using New Selection Tools

The goal of most beef production systems is to increase or at least maintain profitability. Producers can attempt to increase profitability in a variety of ways that might include reducing feed costs, changing their marketing program, or perhaps by changing the performance of their herd through genetic improvement. Focusing on this latter option, there are two primary genetic tools available: selection and mating where selection refers to the selection of breeding animals and mating includes which females are mated to which bulls, for example, crossbreeding systems. This paper focuses on the former, the selection of the appropriate animals for a production system with the goal to improve profitability. The best tool available for making selection decisions is expected progeny differences (EPD). Over the years the number of EPD available to guide producers in making selection decisions has grown from 5 to over 15 in most cases. Simply put, the amount of information that the breeder must sift through to try to make a good selection decision has become overwhelming. The producer must determine which EPD have the greatest influence on their income and their expenses, and by how much—a daunting task. Historically this task has depended on the “intuition” and experience of the breeder. For instance, they know that selection for heavier weaning weight will increase the weight of calves sold at weaning, but that blind selection for weaning weight will also increase calving difficulty and if replacements are kept, likely increase cow size and feed costs. Breeders have been performing a balancing act with little concrete information on how important each of those traits is to their profitability. Fortunately, there are several tools that have recently become available to ease the process of combining the costs and the revenues of beef production with EPD to make selection decisions that will produce progeny which are more profitable

REVIEW: Life-cycle, total-industry genetic improvement of feed efficiency in beef cattle: Blueprint for the Beef Improvement Federation

On a life-cycle basis, beef animals are able to consume large amounts of low-cost, low-quality forages relative to higher-cost concentrates compared with pigs and chickens. However, of the 3, beef is still more expensive to produce on a cost–per–edible pound basis. Accordingly, there is need for genetic programs and management changes that will improve efficiency, sustainability, and profitability of beef production. Options include improving reproductive rate, reducing feed used for maintenance, or both, while not reducing output. A goal for improving efficiency of feed utilization is to reduce the amount or proportion of feed used for maintenance. Such reduction is a target for genetic improvement, but such a goal does not include defining a single measure of efficiency. A single efficiency measure would likely lead to single-trait selection and not account for any potentially antagonistic effects on other production characteristics. Because we are not able to explain all variation in individual-animal intake from only knowledge of BW maintained and level of production, measuring feed intake is necessary. Therefore, our recommendation is that national cattle evaluation systems analyze feed intake as an economically relevant trait with incorporation of appropriate indicator traits for an EPD for feed intake requirements that could then be used in a multiple-trait setting such as in a selection index. With improvements in technology for measurement of feed intake, individual measures of feed intake should continually be collected to facilitate development of genetic predictors that enhance accuracy of prediction of progeny differences in national cattle evaluations

Use of robust multivariate linear mixed models for estimation of genetic parameters for carcass traits in beef cattle

Assumptions of normality of residuals for carcass evaluation may make inferences vulnerable to the presence of outliers, but heavy-tail densities are viable alternatives to normal distributions and provide robustness against unusual or outlying observations when used to model the densities of residual effects. We compare estimates of genetic parameters by fitting multivariate Normal (MN) or heavy-tail distributions (multivariate Student’s t and multivariate Slash, MSt and MS) for residuals in data of hot carcass weight (HCW), longissimus muscle area (REA) and 12th to 13th rib fat (FAT) traits in beef cattle using 2475 records from 2007 to 2008 from a large commercial operation in Nebraska. Model comparisons using deviance information criteria (DIC) favoured MSt over MS and MN models, respectively. The posterior means (and 95% posterior probability intervals, PPI) of v for the MSt and MS models were 5.89±0.90 (4.35, 7.86) and 2.04±0.18 (1.70, 2.41), respectively. Smaller values of posterior densities of v for MSt and MS models confirm that the assumption of normally distributed residuals is not adequate for the analysis of the data set. Posterior mean (PM) and posterior median (PD) estimates of direct genetic variances were variable with MSt having the highest mean value followed by MS and MN, respectively. Posterior inferences on genetic variance were, however, comparable among the models for FAT. Posterior inference on additive heritabilities for HCW, REA and FAT using MN, MSt and MS models indicated similar and moderate heritability comparable with the literature. Posterior means of genetic correlations for carcass traits were variable but positive except for between REA and FAT, which showed an antagonistic relationship. We have demonstrated that genetic evaluation and selection strategies will be sensitive to the assumed model for residuals

Use of robust multivariate linear mixed models for estimation of genetic parameters for carcass traits in beef cattle

Assumptions of normality of residuals for carcass evaluation may make inferences vulnerable to the presence of outliers, but heavy-tail densities are viable alternatives to normal distributions and provide robustness against unusual or outlying observations when used to model the densities of residual effects. We compare estimates of genetic parameters by fitting multivariate Normal (MN) or heavy-tail distributions (multivariate Student’s t and multivariate Slash, MSt and MS) for residuals in data of hot carcass weight (HCW), longissimus muscle area (REA) and 12th to 13th rib fat (FAT) traits in beef cattle using 2475 records from 2007 to 2008 from a large commercial operation in Nebraska. Model comparisons using deviance information criteria (DIC) favoured MSt over MS and MN models, respectively. The posterior means (and 95% posterior probability intervals, PPI) of v for the MSt and MS models were 5.89±0.90 (4.35, 7.86) and 2.04±0.18 (1.70, 2.41), respectively. Smaller values of posterior densities of v for MSt and MS models confirm that the assumption of normally distributed residuals is not adequate for the analysis of the data set. Posterior mean (PM) and posterior median (PD) estimates of direct genetic variances were variable with MSt having the highest mean value followed by MS and MN, respectively. Posterior inferences on genetic variance were, however, comparable among the models for FAT. Posterior inference on additive heritabilities for HCW, REA and FAT using MN, MSt and MS models indicated similar and moderate heritability comparable with the literature. Posterior means of genetic correlations for carcass traits were variable but positive except for between REA and FAT, which showed an antagonistic relationship. We have demonstrated that genetic evaluation and selection strategies will be sensitive to the assumed model for residuals

Polymorphisms associated with the number of live-born piglets in sows infected with the PRRS virus in southern Sonora Mexico

The porcine reproductive and respiratory syndrome (PRRS) is a viral disease that decreases the reproductive performance in breeding sows and leads to economic losses to the swine industry. The objective of the present study was to identify single nucleotide polymorphisms (SNP) associated to the number of live-born piglets in the first (LBP1) and second birth (LBP2) in breeding sows exposed to PRRS virus. The study included 100 pregnant females of the Landrace(¾)/ Yorkshire(¼) line, 75 of which were infected with the PRRS virus and 25 were free of PRRS. Individual blood samples (6-8 drops) were obtained and spotted onto FTA cards and subsequently processed for DNA extraction, which was genotyped using a 10,000 SNP chip for genomic profile. Resulting genotypes were analyzed using a multi-locus mixed model that detected three SNP associated to LBP1 and five SNP associated to LBP2 (P<0.001). These eight SNP were validated using an associative mixed effects model which included the terms genotype and age of dam as fixed effects, and sire as random effect. Allele substitution effects were estimated using the same model including the term genotype as covariate. The SNP rs81276080, rs81334603 and rs80947173 were associated to LBP1 (P<0.001), whereas the SNP rs81364943, rs80859829, rs80895640, rs80893794 and rs81245908 were associated to LBP2 (P<0.001). Only two SNP were in functional chromosomal regions and the remainder SNP were within an intergenic position. In conclusion, these results suggest the existence of gene variants associated with the reproductive performance of sows infected with the PRRS virus.The porcine reproductive and respiratory syndrome (PRRS) is a viral disease that decreases the reproductive performance in breeding sows and leads to economic losses to the swine industry. The objective of the present study was to identify single nucleotide polymorphisms (SNP) associated to the number of live-born piglets in the first (LBP1) and second birth (LBP2) in breeding sows exposed to PRRS virus. The study included 100 pregnant females of the Landrace(¾)/ Yorkshire(¼) line, 75 of which were infected with the PRRS virus and 25 were free of PRRS. Individual blood samples (6-8 drops) were obtained and spotted onto FTA cards and subsequently processed for DNA extraction, which was genotyped using a 10,000 SNP chip for genomic profile. Resulting genotypes were analyzed using a multi-locus mixed model that detected three SNP associated to LBP1 and five SNP associated to LBP2 (P<0.001). These eight SNP were validated using an associative mixed effects model which included the terms genotype and age of dam as fixed effects, and sire as random effect. Allele substitution effects were estimated using the same model including the term genotype as covariate. The SNP rs81276080, rs81334603 and rs80947173 were associated to LBP1 (P<0.001), whereas the SNP rs81364943, rs80859829, rs80895640, rs80893794 and rs81245908 were associated to LBP2 (P<0.001). Only two SNP were in functional chromosomal regions and the remainder SNP were within an intergenic position. In conclusion, these results suggest the existence of gene variants associated with the reproductive performance of sows infected with the PRRS virus

Event-Related Potentials Reveal Rapid Verification of Predicted Visual Input

Human information processing depends critically on continuous predictions about upcoming events, but the temporal convergence of expectancy-based top-down and input-driven bottom-up streams is poorly understood. We show that, during reading, event-related potentials differ between exposure to highly predictable and unpredictable words no later than 90 ms after visual input. This result suggests an extremely rapid comparison of expected and incoming visual information and gives an upper temporal bound for theories of top-down and bottom-up interactions in object recognition

Error bounds in the gap metric for dissipative balanced approximations

We derive an error bound in the gap metric for positive real balanced truncation and positive real singular perturbation approximation. We prove these results by working in the context of dissipative driving-variable systems, as in behavioral and state/signal systems theory. In such a framework no prior distinction is made between inputs and outputs. Dissipativity preserving balanced truncation of dissipative driving-variable systems is addressed and a gap metric error bound is obtained. Bounded real and positive real input-state-output systems are manifestations of a dissipative driving-variable system through particular decompositions of the signal space. Under such decompositions the existing bounded real and positive real balanced truncation schemes can be seen as special cases of dissipative balanced truncation and the new positive real error bounds follow

Eccentric Exercise Activates Novel Transcriptional Regulation of Hypertrophic Signaling Pathways Not Affected by Hormone Changes

Unaccustomed eccentric exercise damages skeletal muscle tissue, activating mechanisms of recovery and remodeling that may be influenced by the female sex hormone 17β-estradiol (E2). Using high density oligonucleotide based microarrays, we screened for differences in mRNA expression caused by E2 and eccentric exercise. After random assignment to 8 days of either placebo (CON) or E2 (EXP), eighteen men performed 150 single-leg eccentric contractions. Muscle biopsies were collected at baseline (BL), following supplementation (PS), +3 hours (3H) and +48 hours (48H) after exercise. Serum E2 concentrations increased significantly with supplementation (P<0.001) but did not affect microarray results. Exercise led to early transcriptional changes in striated muscle activator of Rho signaling (STARS), Rho family GTPase 3 (RND3), mitogen activated protein kinase (MAPK) regulation and the downstream transcription factor FOS. Targeted RT-PCR analysis identified concurrent induction of negative regulators of calcineurin signaling RCAN (P<0.001) and HMOX1 (P = 0.009). Protein contents were elevated for RND3 at 3H (P = 0.02) and FOS at 48H (P<0.05). These findings indicate that early RhoA and NFAT signaling and regulation are altered following exercise for muscle remodeling and repair, but are not affected by E2

Mitochondrial dysfunction in autism spectrum disorders: a systematic review and meta-analysis

A comprehensive literature search was performed to collate evidence of mitochondrial dysfunction in autism spectrum disorders (ASDs) with two primary objectives. First, features of mitochondrial dysfunction in the general population of children with ASD were identified. Second, characteristics of mitochondrial dysfunction in children with ASD and concomitant mitochondrial disease (MD) were compared with published literature of two general populations: ASD children without MD, and non-ASD children with MD. The prevalence of MD in the general population of ASD was 5.0% (95% confidence interval 3.2, 6.9%), much higher than found in the general population (∼0.01%). The prevalence of abnormal biomarker values of mitochondrial dysfunction was high in ASD, much higher than the prevalence of MD. Variances and mean values of many mitochondrial biomarkers (lactate, pyruvate, carnitine and ubiquinone) were significantly different between ASD and controls. Some markers correlated with ASD severity. Neuroimaging, in vitro and post-mortem brain studies were consistent with an elevated prevalence of mitochondrial dysfunction in ASD. Taken together, these findings suggest children with ASD have a spectrum of mitochondrial dysfunction of differing severity. Eighteen publications representing a total of 112 children with ASD and MD (ASD/MD) were identified. The prevalence of developmental regression (52%), seizures (41%), motor delay (51%), gastrointestinal abnormalities (74%), female gender (39%), and elevated lactate (78%) and pyruvate (45%) was significantly higher in ASD/MD compared with the general ASD population. The prevalence of many of these abnormalities was similar to the general population of children with MD, suggesting that ASD/MD represents a distinct subgroup of children with MD. Most ASD/MD cases (79%) were not associated with genetic abnormalities, raising the possibility of secondary mitochondrial dysfunction. Treatment studies for ASD/MD were limited, although improvements were noted in some studies with carnitine, co-enzyme Q10 and B-vitamins. Many studies suffered from limitations, including small sample sizes, referral or publication biases, and variability in protocols for selecting children for MD workup, collecting mitochondrial biomarkers and defining MD. Overall, this evidence supports the notion that mitochondrial dysfunction is associated with ASD. Additional studies are needed to further define the role of mitochondrial dysfunction in ASD

2013 WSES guidelines for management of intra-abdominal infections

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