Bayes factor for testing between different structures of random genetic groups: A case study using weaning weight in Bruna dels Pirineus beef cattle

The implementation of genetic groups in BLUP evaluations accounts for different expectations of breeding values in base animals. Notwithstanding, many feasible structures of genetic groups exist and there are no analytical tools described to compare them easily. In this sense, the recent development of a simple and stable procedure to calculate the Bayes factor between nested competing models allowed us to develop a new approach of that method focused on compared models with different structures of random genetic groups. The procedure is based on a reparameterization of the model in terms of intraclass correlation of genetic groups. The Bayes factor can be easily calculated from the output of a Markov chain Monte Carlo sampling by averaging conditional densities at the null intraclass correlation. It compares two nested models, a model with a given structure of genetic groups against a model without genetic groups. The calculation of the Bayes factor between different structures of genetic groups can be quickly and easily obtained from the Bayes factor between the nested models. We applied this approach to a weaning weight data set of the Bruna dels Pirineus beef cattle, comparing several structures of genetic groups, and the final results showed that the preferable structure was an only group for unknown dams and different groups for unknown sires for each year of calving.     

Pig melatonin receptor 1a (MTNR1A) genotype is associated with seasonal variation of sow litter size

The duration of nocturnal melatonin secretion reaches its minimum in summer, a physiological event that is likely related with the diminished sow fertility and delayed puberty typically observed in this season. Melatonin exerts its function by binding two different receptors named as MTNR1A and MTNR1B. Interestingly, the MTNR1A gene is located on a chromosome SSC17 region where QTL for prolificacy traits have been detected in previous studies. In this work, we have found a synonymous T162C polymorphism at exon 2 of the pig MTNR1A gene. An association analysis between this polymorphism and sow prolificacy in an Iberian ×  Meishan intercross was performed. The utilization of four statistical models of increasing complexity demonstrated that the MTNR1A gene has both additive and dominant effects on total number of born piglets (TNB) and number of piglets born alive (NBA). Additive effects were significant in summer (TNB, P < 0.01; NBA, P < 0.001), whereas dominant effects reached significance both in fall (TNB, P < 0.01; NBA, P < 0.05) and in winter (TNB, P < 0.001; NBA, P < 0.05). The seasonal variation observed for MTNR1A additive and dominant effects might be produced by the influence of photoperiod on the pattern and duration of melatonin secretion. These results illustrate that the complex interaction between genotype and environment can be an important source of phenotypic variation of reproductive traits.     

Hypothesis testing for the genetic background of quantitative traits

The testing of Bayesian point null hypotheses on variance component models have resulted in a tough assignment for which no clear and generally accepted method exists. In this work we present what we believe is a succeeding approach to such a task. It is based on a simple reparameterization of the model in terms of the total variance and the proportion of the additive genetic variance with respect to it, as well as on the explicit inclusion on the prior probability of a discrete component at origin. The reparameterization was used to bypass an arbitrariness related to the impropriety of uninformative priors onto unbounded variables while the discrete component was necessary to overcome the zero probability assigned to sets of null measure by the usual continuous variable models. The method was tested against computer simulations with appealing results.     

Mutants of Saccharomyces cerevisiae cell division cycle defective in cytokinesis. Biosynthesis of the cell wall and morphology

The four temperature-sensitive mutants of Saccharomyces cerevisiae in the cell division cycle defective in cytokinesis (cdc, 3, 10, 11 and 12), have been analyzed with respect to the biosynthesis of the cell wall polymers. After 3 hours of incubation at the non-permissive temperature (37°C) these strains stop growing. The synthesis of glucan, mannan and chitin (wall polymers) level off in a similar time, but glucan, mannan and chitin synthases remained active for at least 4 hours.If the mutants are analyzed by transmission and scanning electron microscopy different pictures emerge. Two of the mutants cdc 10 and cdc 12, after 3 hours of incubation at 37°C present apparently normal cytoplasms and cell wall surfaces with multiple elongated buds. The other two mutants, cdc 3 and cdc 11, present a completely disarranged cytoplasmic content and damage at the level of the plasma membrane is evident.These and other observations, suggest that between the execution points of cdc 3 (0.27) and cdc 10 (0.58), essential processes in the assembly of cell membrane occur.This work was supported in part by a grant from la Comisión de Investigación Científica y Técnica of the Spanish Ministerio de Educación y Ciencia (Project no. 4593-1980).     

History-dependent excitability as a single-cell substrate of transient memory for information discrimination

Neurons react differently to incoming stimuli depending upon their previous history of stimulation. This property can be considered as a single-cell substrate for transient memory, or context-dependent information processing: depending upon the current context that the neuron "sees" through the subset of the network impinging on it in the immediate past, the same synaptic event can evoke a postsynaptic spike or just a subthreshold depolarization. We propose a formal definition of History-Dependent Excitability (HDE) as a measure of the propensity to firing in any moment in time, linking the subthreshold history-dependent dynamics with spike generation. This definition allows the quantitative assessment of the intrinsic memory for different single-neuron dynamics and input statistics. We illustrate the concept of HDE by considering two general dynamical mechanisms: the passive behavior of an Integrate and Fire (IF) neuron, and the inductive behavior of a Generalized Integrate and Fire (GIF) neuron with subthreshold damped oscillations. This framework allows us to characterize the sensitivity of different model neurons to the detailed temporal structure of incoming stimuli. While a neuron with intrinsic oscillations discriminates equally well between input trains with the same or different frequency, a passive neuron discriminates better between inputs with different frequencies. This suggests that passive neurons are better suited to rate-based computation, while neurons with subthreshold oscillations are advantageous in a temporal coding scheme. We also address the influence of intrinsic properties in single-cell processing as a function of input statistics, and show that intrinsic oscillations enhance discrimination sensitivity at high input rates. Finally, we discuss how the recognition of these cell-specific discrimination properties might further our understanding of neuronal network computations and their relationships to the distribution and functional connectivity of different neuronal types.     

Genome scans for transmission ratio distortion regions in mice

Transmission ratio distortion (TRD) is the departure from the expected genotypic frequencies under Mendelian inheritance. This departure can be due to multiple physiological mechanisms during gametogenesis, fertilization, fetal and embryonic development, and early neonatal life. Although a few TRD loci have been reported in mouse, inheritance patterns have never been evaluated for TRD. In this article, we developed a Bayesian binomial model accounting for additive and dominant deviation TRD mechanisms. Moreover, this model was used to perform genome-wide scans for TRD quantitative trait loci (QTL) on six F2 mouse crosses involving between 296 and 541 mice and between 72 and 1854 genetic markers. Statistical significance of each model was checked at each genetic marker with Bayes factors. Genome scans revealed overdominance TRD QTL located in mouse chromosomes 1, 2, 12, 13, and 14 and additive TRD QTL in mouse chromosomes 2, 3, and 15, although these results did not replicate across mouse crosses. This research contributes new statistical tools for the analysis of specific genetic patterns involved in TRD in F2 populations, our results suggesting a relevant incidence of TRD phenomena in mouse with important implications for both statistical analyses and biological research.     

Effects of changes in hydromineral balance on rat brain aspartyl, arginyl, and alanyl aminopeptidase activities.

In order to examine the possible relationship between the processing and inactivation roles of aminopeptidases and the disruption of water-electrolyte balance, we measured the activities of aspartyl aminopeptidase (Asp-Ap), arginyl aminopeptidase (Arg-Ap) and alanyl aminopeptidase (Ala-Ap) in certain brain areas (hypothalamus, hippocampus, thalamus and brain cortices) and in the pituitary gland in several models of hydrosaline change. The activity of hypothalamic membrane-bound Asp-Ap significantly decreased (more than 50%) following treatments which induced a hypovolemic state. Aminopeptidase M activity (membrane-bound Ala-Ap activity with low sensitivity to puromycin) was also significantly decreased by 53 % in the thalamus of rats under conditions of hypovolemia plus hyperosmolality in comparison to the control group. These results indicate that aminopeptidases in the central nervous system may be involved in the physiological regulation of hydromineral balance.     

Effects of hydrosaline treatments on prolyl endopeptidase activity in rat tissues

Enzymatic cleavage of some peptide hormones, neurotransmitters and neuromodulators could be implicated in the regulation of extra- and intracellular fluid volume and osmolality. Prolyl endopeptidase is known to hydrolyze several peptides, which act on hydromineral balance, such as angiotensins, bradykinin, vasopressin, oxytocin, thyrotropin-releasing hormone, neurotensin and opioids. In this work, we analyzed the effects of certain volume and/or osmotic changes in the activity of the soluble and membrane-bound prolyl endopeptidase in several brain areas, heart, lungs, kidney and adrenal and pituitary glands of the rat. Soluble prolyl endopeptidase activity was higher in the renal cortex of the chronic salt-loaded rats than in the control rats. In the water-deprived and polyethylene glycol-treated rats, heart particulate prolyl endopeptidase was lower than in the control rats. Particulate prolyl endopeptidase was also lower in the adrenal gland of the acute salt-loaded rats and in the brain cortex of the water-loaded rats than in the control rats. Data suggest that tissue-dependent peptide hydrolysis evoked by prolyl endopeptidase activity is involved in the water-electrolyte homeostasis.     

Analysis of litter size and average litter weight in pigs using a recursive model

An analysis of litter size and average piglet weight at birth in Landrace and Yorkshire using a standard two-trait mixed model (SMM) and a recursive mixed model (RMM) is presented. The RMM establishes a one-way link from litter size to average piglet weight. It is shown that there is a one-to-one correspondence between the parameters of SMM and RMM and that they generate equivalent likelihoods. As parameterized in this work, the RMM tests for the presence of a recursive relationship between additive genetic values, permanent environmental effects, and specific environmental effects of litter size, on average piglet weight. The equivalent standard mixed model tests whether or not the covariance matrices of the random effects have a diagonal structure. In Landrace, posterior predictive model checking supports a model without any form of recursion or, alternatively, a SMM with diagonal covariance matrices of the three random effects. In Yorkshire, the same criterion favors a model with recursion at the level of specific environmental effects only, or, in terms of the SMM, the association between traits is shown to be exclusively due to an environmental (negative) correlation. It is argued that the choice between a SMM or a RMM should be guided by the availability of software, by ease of interpretation, or by the need to test a particular theory or hypothesis that may best be formulated under one parameterization and not the other.