Impact of QTL properties on the accuracy of multi-breed genomic prediction

Background

Although simulation studies show that combining multiple breeds in one reference population increases accuracy of genomic prediction, this is not always confirmed in empirical studies. This discrepancy might be due to the assumptions on quantitative trait loci (QTL) properties applied in simulation studies, including number of QTL, spectrum of QTL allele frequencies across breeds, and distribution of allele substitution effects. We investigated the effects of QTL properties and of including a random across- and within-breed animal effect in a genomic best linear unbiased prediction (GBLUP) model on accuracy of multi-breed genomic prediction using genotypes of Holstein-Friesian and Jersey cows.

Methods

Genotypes of three classes of variants obtained from whole-genome sequence data, with moderately low, very low or extremely low average minor allele frequencies (MAF), were imputed in 3000 Holstein-Friesian and 3000 Jersey cows that had real high-density genotypes. Phenotypes of traits controlled by QTL with different properties were simulated by sampling 100 or 1000 QTL from one class of variants and their allele substitution effects either randomly from a gamma distribution, or computed such that each QTL explained the same variance, i.e. rare alleles had a large effect. Genomic breeding values for 1000 selection candidates per breed were estimated using GBLUP modelsincluding a random across- and a within-breed animal effect.

Results

For all three classes of QTL allele frequency spectra, accuracies of genomic prediction were not affected by the addition of 2000 individuals of the other breed to a reference population of the same breed as the selection candidates. Accuracies of both single- and multi-breed genomic prediction decreased as MAF of QTL decreased, especially when rare alleles had a large effect. Accuracies of genomic prediction were similar for the models with and without a random within-breed animal effect, probably because of insufficient power to separate across- and within-breed animal effects.

Conclusions

Accuracy of both single- and multi-breed genomic prediction depends on the properties of the QTL that underlie the trait. As QTL MAF decreased, accuracy decreased, especially when rare alleles had a large effect. This demonstrates that QTL properties are key parameters that determine the accuracy of genomic prediction.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-015-0124-6) contains supplementary material, which is available to authorized users.     

Intravenous Immunoglobulin with Enhanced Polyspecificity Improves Survival in Experimental Sepsis and Aseptic Systemic Inflammatory Response Syndromes

Sepsis is a major cause for death worldwide. Numerous interventional trials with agents neutralizing single proinflammatory mediators have failed to improve survival in sepsis and aseptic systemic inflammatory response syndromes. This failure could be explained by the widespread gene expression dysregulation known as “genomic storm” in these patients. A multifunctional polyspecific therapeutic agent might be needed to thwart the effects of this storm. Licensed pooled intravenous immunoglobulin preparations seemed to be a promising candidate, but they have also failed in their present form to prevent sepsis-related death. We report here the protective effect of a single dose of intravenous immunoglobulin preparations with additionally enhanced polyspecificity in three models of sepsis and aseptic systemic inflammation. The modification of the pooled immunoglobulin G molecules by exposure to ferrous ions resulted in their newly acquired ability to bind some proinflammatory molecules, complement components and endogenous “danger” signals. The improved survival in endotoxemia was associated with serum levels of proinflammatory cytokines, diminished complement consumption and normalization of the coagulation time. We suggest that intravenous immunoglobulin preparations with additionally enhanced polyspecificity have a clinical potential in sepsis and related systemic inflammatory syndromes.     

The human gutome: nutrigenomics of the host-microbiome interactions

Demonstrating the importance of the gut microbiota in human health and well-being represents a major transformational task in both medical and nutritional research. Owing to the high-throughput -omics methodologies, the complexity, evolution with age, and individual nature of the gut microflora have been more thoroughly investigated. The balance between this complex community of gut bacteria, food nutrients, and intestinal genomic and physiological milieu is increasingly recognized as a major contributor to human health and disease. This article discusses the "gutome," that is, nutritional systems biology of gut microbiome and host-microbiome interactions. We examine the novel ways in which the study of the human gutome, and nutrigenomics more generally, can have translational and transformational impacts in 21st century practice of biomedicine. We describe the clinical context in which experimental methodologies, as well as data-driven and process-driven approaches are being utilized in nutrigenomics and microbiome research. We underscore the pivotal importance of the gutome as a common platform for sharing data in the emerging field of the integrated metagenomics of gut pathophysiology. This vision needs to be articulated in a manner that recognizes both the omics biotechnology nuances and the ways in which nutrigenomics science can effectively inform population health and public policy, and vice versa.     

Temporal encoding in a nervous system

We examined the extent to which temporal encoding may be implemented by single neurons in the cercal sensory system of the house cricket Acheta domesticus. We found that these neurons exhibit a greater-than-expected coding capacity, due in part to an increased precision in brief patterns of action potentials. We developed linear and non-linear models for decoding the activity of these neurons. We found that the stimuli associated with short-interval patterns of spikes (ISIs of 8 ms or less) could be predicted better by second-order models as compared to linear models. Finally, we characterized the difference between these linear and second-order models in a low-dimensional subspace, and showed that modification of the linear models along only a few dimensions improved their predictive power to parity with the second order models. Together these results show that single neurons are capable of using temporal patterns of spikes as fundamental symbols in their neural code, and that they communicate specific stimulus distributions to subsequent neural structures.     

Estimate of M-wave changes in human biceps brachii during continuous stimulation.

The purpose of the present study was to validate the capability of new fatigue indexes (in the time and frequency domain) applied to experimental recordings and thus, to test some assumptions made in previous simulations. The indexes were applied to M-waves detected non-invasively from human m.biceps brachii during repetitive slightly above threshold stimulations. It was found that distance between the motor point and middle of the end-plate region could be relatively large. Under identical conditions (signals detected by monopolar electrodes and high-pass filtered at 1 Hz), the relative changes of the indexes obtained in electrophysiological experiments and simulations were similar. Changes of the intracellular action potential profile during fatigue used in the simulations were consequently supposed to be close to the actual ones for the muscle analyzed. When the high-pass cut-off frequency was higher than 1 Hz, the sensitivity of the index in the time domain was higher, while that in the frequency domain was lower. If the normalizing spectral moment was of higher order, the sensitivity of the spectral index could be even 150-times greater than that of the fatigue indexes traditionally used. Thus, the spectral index promises high capability to assess fatigue during functional electrical stimulation.     

Internodal sodium channels ensure active processes under myelin manifesting in depolarizing afterpotentials

The current opinion about processes in myelinated axon is that action potential saltatorially propagates between nodes of Ranvier and passively charges internodal axolemma thus causing depolarizing afterpotentials (DAP). Demyelination blocks the conduction that gives additional argument in favor of hypothesis that internode is not able to be activated by the existing internodal sodium channels. The results of our modeling study shows that, when periaxonal space is sufficiently narrow, saltatorial action potential is able to activate internodes. Low density of internodal sodium channels is sufficient to generate active internodal waves that slowly propagate from nodes towards corresponding midinternodes where they collide. The periaxonal width that stops internodal wave propagation (about 400 nm) is significantly larger than the highest value of the physiological range for this parameter (30 nm). Internodal activation is directly manifested as transmembrane internodal potential or as a full-sized action potential in periaxonal space where it can hardly be detected, and only as a small deflection in intracellular space. However, changes in the periaxonal potential cause transmyelin currents that lead to significant DAP. The shape and amplitude of DAP depends on myelin parameters and densities of internodal channels. Several technical parameters affect the results of calculations. Internodal spatial segmentation has to be sufficiently fine (at most 20 microm) for the model to be able to simulate internodal activation. We employ 338 internodal segments as compared with up to 21 used in previous models. Ionic accumulation together with related diffusive and electrical processes alter the calculated DAP amplitude. Inclusion of these processes in calculations demands such increase in the total number of segments that the numerical methods used up to now become unapplicable. To overcome the problem, an iterative implicit approach is proposed. It reduces a matrix of general type in multi-cable models to tridiagonal one and accelerates calculations considerably.     

Immobilization of cells with nitrilase activity from a thermophilic bacterial strain

Cells of the moderately thermophilic Bacillus sp. UG-5B strain, producing nitrilase (EC3.5.5.1), which converts nitriles directly to the corresponding acid and ammonia, were immobilized using different types of matrices and techniques. A variety of sol-gel silica hybrids were tested for entrapment and adsorption of bacterial cells as well as chemical binding on polysulphone membranes. Activation of the matrix surface with formaldehyde led to an increase in immobilization efficiency and operational stability of the biocatalysts. Among the supports screened, membranes gave the best results for enzyme activity and especially operational stability, with retention of 100% activity after eight reaction cycles.