Estimation of genetic variance for macro- and micro-environmental sensitivity using double hierarchical generalized linear models

Background: Genetic variation for environmental sensitivity indicates that animals are genetically different in their response to environmental factors. Environmental factors are either identifiable (e.g. temperature) and called macro-environmental or unknown and called micro-environmental. The objectives of this study were to develop a statistical method to estimate genetic parameters for macro- and micro-environmental sensitivities simultaneously, to investigate bias and precision of resulting estimates of genetic parameters and to develop and evaluate use of Akaike’s information criterion using h-likelihood to select the best fitting model. Methods: We assumed that genetic variation in macro- and micro-environmental sensitivities is expressed as genetic variance in the slope of a linear reaction norm and environmental variance, respectively. A reaction norm model to estimate genetic variance for macro-environmental sensitivity was combined with a structural model for residual variance to estimate genetic variance for micro-environmental sensitivity using a double hierarchical generalized linear model in ASReml. Akaike’s information criterion was constructed as model selection criterion using approximated h-likelihood. Populations of sires with large half-sib offspring groups were simulated to investigate bias and precision of estimated genetic parameters. Results: Designs with 100 sires, each with at least 100 offspring, are required to have standard deviations of estimated variances lower than 50% of the true value. When the number of offspring increased, standard deviations of estimates across replicates decreased substantially, especially for genetic variances of macro- and micro-environmental sensitivities. Standard deviations of estimated genetic correlations across replicates were quite large (between 0.1 and 0.4), especially when sires had few offspring. Practically, no bias was observed for estimates of any of the parameters. Using Akaike’s information criterion the true genetic model was selected as the best statistical model in at least 90% of 100 replicates when the number of offspring per sire was 100. Application of the model to lactation milk yield in dairy cattle showed that genetic variance for micro- and macro-environmental sensitivities existed. Conclusion: The algorithm and model selection criterion presented here can contribute to better understand genetic control of macro- and micro-environmental sensitivities. Designs or datasets should have at least 100 sires each with 100 offspring.

Variance component estimates applying random regression models for test-day milk yield in Caracu heifers (Bos taurus Artiodactyla, Bovidae)

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Partial urethral obstruction of rabbit urinary bladder: stereological evidence that the increase in muscle content is mostly driven by changes in number, rather than size, of smooth muscle cells

The effects of partial urethral obstruction on the detrusor muscle of rabbit urinary bladder were investigated using stereological sampling and estimation tools. Twelve female Norfolk rabbits (2.5-3.0 kg body weight) were divided into four groups: 3, 7 and 12 weeks after surgical intervention to produce a standard partial obstruction and unobstructed controls. Following removal, bladder axes (craniocaudal, dorsoventral and laterolateral) and organ weights were recorded. Bladders were prepared for light microscopy by multistage random sampling procedures. Stereological methods were used to estimate the volume of muscle and the packing density and total number of myocyte nuclei in each bladder. We also estimated mean myocyte volume and the mean cross-sectional area and length of myocytes. Group comparisons were made by one-way analysis of variance. Changes in bladder axes were mainly laterolateral and craniocaudal. Mean bladder weight increased roughly six-fold by 3 weeks and 17-fold by 12 weeks and was accompanied, on average, by 12- and 33-fold increases in total muscle volume. These variables did not differ at 3 and 7 weeks post-obstruction. Increases in muscle content were not accompanied by changes in packing densities but were associated with increases in the total numbers of myocyte nuclei (13-fold by 3 weeks, 28-fold by 12 weeks). Mean myocyte volume did not vary significantly between groups but cells in obstructed groups were shorter and wider. These findings support the notion that partial outflow obstruction leads to an increase in the number, but not mean volume, of myocytes. If due solely to myocyte mitosis, the total of 43 x 10(8) cells found at 12 weeks could be generated by the original complement of 15 x 10(7) cells if an average of only 2.1 x 10(6) new cells was produced every hour. In reality, even this modest proliferation rate is unlikely to be achieved because myocyte proliferation rates are very low and it is possible that new myocytes can arise by differentiation of mesenchymal or other precursor cells.

Synthetic control chart for monitoring the pprocess mean and variance

In this article, we consider the synthetic control chart with two-stage sampling (SyTS chart) to control the process mean and variance. During the first stage, one item of the sample is inspected; if its value X, is close to the target value of the process mean, then the sampling is interrupted. Otherwise, the sampling goes on to the second stage, where the remaining items are inspected and the statistic T = Sigma [x(i) - mu(0) + xi sigma(0)](2) is computed taking into account all items of the sample. The design parameter is function of X-1. When the statistic T is larger than a specified value, the sample is classified as nonconforming. According to the synthetic procedure, the signal is based on Conforming Run Length (CRL). The CRL is the number of samples taken from the process since the previous nonconforming sample until the occurrence of the next nonconforming sample. If the CRL is sufficiently small, then a signal is generated. A comparative study shows that the SyTS chart and the joint X and S charts with double sampling are very similar in performance. However, from the practical viewpoint, the SyTS chart is more convenient to administer than the joint charts.

Difference variance dispersion graphs for comparing response surface designs with applications in food technology

Variance dispersion graphs have become a popular tool in aiding the choice of a response surface design. Often differences in response from some particular point, such as the expected position of the optimum or standard operating conditions, are more important than the response itself. We describe two examples from food technology. In the first, an experiment was conducted to find the levels of three factors which optimized the yield of valuable products enzymatically synthesized from sugars and to discover how the yield changed as the levels of the factors were changed from the optimum. In the second example, an experiment was conducted on a mixing process for pastry dough to discover how three factors affected a number of properties of the pastry, with a view to using these factors to control the process. We introduce the difference variance dispersion graph (DVDG) to help in the choice of a design in these circumstances. The DVDG for blocked designs is developed and the examples are used to show how the DVDG can be used in practice. In both examples a design was chosen by using the DVDG, as well as other properties, and the experiments were conducted and produced results that were useful to the experimenters. In both cases the conclusions were drawn partly by comparing responses at different points on the response surface.

The variance of the index (R) of aggregation of Clark and Evans

The exact formula for the variance of the Index (R) of aggregation of Clark and Evans is derived. Due to the fact that R is a dimensionless number, its variance is independent of population density, being only a function of the sample size and so can be manipulated. © 1985 Springer-Verlag.

Is the number of antennal plate organs (sensilla placodea) greater in hygienic than in non-hygienic Africanized honey bees?

Hygienic behavior is a desirable trait in honey bees (Apis mellifera L.), as hygienic bees quickly remove diseased brood, intermpting the infectious cycle. Hygienic lines of honey bees appear to be more sensitive to the odors of dead and diseased honey bee brood, and Africanized honey bees are generally more hygienic than are European honey bees. We compared the number of sensilla placodea, antennal sensory structures involved in the perception of odor, in 10 bees from each of six hygienic and four non-hygienic colonies of Africanized honey bees. The sensilla placodea of three of the terminal segments (flagellomeres) of the right antenna of each bee were counted with a scanning electron microscope. There were no significant differences in the mean numbers of sensilla placodea between the hygienic and non-hygienic bees, though the variance was higher in the hygienic group. Flagellomere 4 had significantly more sensilla placodea than flagellomeres 6 and 8. However, there was no significant difference between the other two flagellomeres. As hygienic bees are capable of identifying dead, injured, or infested brood inside a capped brood cell, sensilla placodea probably have an important role in enabling worker bees to sense sick brood. However, we did not find greater numbers of this sensory structure in the antennae of hygienic, compared to non-hygienic Africanized honey bees.

Estimation of variance components and prediction of breeding values in rubber tree breeding using the REML/BLUP procedure

The present paper deals with estimation of variance components, prediction of breeding values and selection in a population of rubber tree [Hevea brasiliensis (Willd. ex Adr. de Juss.) Müell.-Arg.] from Rio Branco, State of Acre, Brazil. The REML/BLUP (restricted maximum likelihood/best linear unbiased prediction) procedure was applied. For this purpose, 37 rubber tree families were obtained and assessed in a randomized complete block design, with three unbalanced replications. The field trial was carried out at the Experimental Station of UNESP, located in Selvíria, State of Mato Grosso do Sul, Brazil. The quantitative traits evaluated were: girth (G), bark thickness (BT), number of latex vessel rings (NR), and plant height (PH). Given the unbalanced condition of the progeny test, the REML/BLUP procedure was used for estimation. The narrow-sense individual heritability estimates were 0.43 for G, 0.18 for BT, 0.01 for NR, and 0.51 for PH. Two selection strategies were adopted: one short-term (ST - selection intensity of 8.85%) and the other long-term (LT - selection intensity of 26.56%). For G, the estimated genetic gains in relation to the population average were 26.80% and 17.94%, respectively, according to the ST and LT strategies. The effective population sizes were 22.35 and 46.03, respectively. The LT and ST strategies maintained 45.80% and 28.24%, respectively, of the original genetic diversity represented in the progeny test. So, it can be inferred that this population has potential for both breeding and ex situ genetic conservation as a supplier of genetic material for advanced rubber tree breeding programs. Copyright by the Brazilian Society of Genetics.

Influence of the number of load cycles to obtain the stiffness properties of angico preto (Anadenanthera macrocarpa) wood specie

The tests used to obtain the stiffness properties of wood are made with two loading cycles, as defined by the Brazilian standard ABNT NBR 7190 (Design of Timber Structures). However, the possibility of reducing the number of cycles allows decrease the operating time of the machine, resulting in reduced spending on electricity used during the tests. This research aimed to investigate, with the aid of the analysis of variance (ANOVA), the influence of the use of three load cycles to obtain the modulus of elasticity in compression parallel to grain (Ec0), in tensile parallel to the grain (Et0), in bending (Em) and in compression perpendicular to the grain (Ec90) of Angico Preto (Anadenanthera macrocarpa) wood specie. For the number of cycles and stiffness were manufactured 12 samples, totaling 144 specimens. The results of the ANOVA revealed statistical equivalence between the stiffness properties for both load cycle numbers evaluated, indicating that it is possible to carry out the tests with a single charge cycle, allowing savings in time and energy in the operation of the equipment.

Variance Effective Population Size for Dioecious Species

The concept of effective population size (N(e)) is an important measure of representativeness in many areas. In this research, we consider the statistical properties of the number of contributed gametes under practical situations by adapting Crow and Denninston's (1988) N(e) formulas for dioecious species. Three sampling procedures were considered. In all circumstances, results show that as the offspring sex ratio (r) deviates from 0.5, N(e) values become smaller, and the efficiency of gametic control for increasing N(e) is reduced. For finite populations, where all individuals are potentially functional parents, the reduction in N(e) due to an unequal sex ratio can be compensated for through female gametic control when 0.28 <= r <= 0.72. This outcome is important when r is unknown. When only a fraction of the individuals in a population is taken for reproduction, N(e) is meaningful only if the size of the reference population is clearly defined. Gametic control is a compensating factor in accession regeneration when the viability of the accession is around 70 or 75%. For germ-plasm collection, when parents are a very small fraction of the population, maximum N(e) will be approximately 47 and 57% of the total number of offspring sampled, with female gametic control, r varying between 0.3 and 0.5, and being constant over generations.

MODIFIED TEST STATISTICS BY INTER-VOXEL VARIANCE SHRINKAGE WITH AN APPLICATION TO fMRI

Functional Magnetic Resonance Imaging (fMRI) is a non-invasive technique which is commonly used to quantify changes in blood oxygenation and flow coupled to neuronal activation. One of the primary goals of fMRI studies is to identify localized brain regions where neuronal activation levels vary between groups. Single voxel t-tests have been commonly used to determine whether activation related to the protocol differs across groups. Due to the generally limited number of subjects within each study, accurate estimation of variance at each voxel is difficult. Thus, combining information across voxels in the statistical analysis of fMRI data is desirable in order to improve efficiency. Here we construct a hierarchical model and apply an Empirical Bayes framework on the analysis of group fMRI data, employing techniques used in high throughput genomic studies. The key idea is to shrink residual variances by combining information across voxels, and subsequently to construct an improved test statistic in lieu of the classical t-statistic. This hierarchical model results in a shrinkage of voxel-wise residual sample variances towards a common value. The shrunken estimator for voxelspecific variance components on the group analyses outperforms the classical residual error estimator in terms of mean squared error. Moreover, the shrunken test-statistic decreases false positive rate when testing differences in brain contrast maps across a wide range of simulation studies. This methodology was also applied to experimental data regarding a cognitive activation task.

Detection of nonrandom association of alleles from the distribution of the number of heterozygous loci in a sample.

The distribution of the number of heterozygous loci in two randomly chosen gametes or in a random diploid zygote provides information regarding the nonrandom association of alleles among different genetic loci. Two alternative statistics may be employed for detection of nonrandom association of genes of different loci when observations are made on these distributions: observed variance of the number of heterozygous loci (s2k) and a goodness-of-fit criterion (X2) to contrast the observed distribution with that expected under the hypothesis of random association of genes. It is shown, by simulation, that s2k is statistically more efficient than X2 to detect a given extent of nonrandom association. Asymptotic normality of s2k is justified, and X2 is shown to follow a chi-square (chi 2) distribution with partial loss of degrees of freedom arising because of estimation of parameters from the marginal gene frequency data. Whenever direct evaluations of linkage disequilibrium values are possible, tests based on maximum likelihood estimators of linkage disequilibria require a smaller sample size (number of zygotes or gametes) to detect a given level of nonrandom association in comparison with that required if such tests are conducted on the basis of s2k. Summarization of multilocus genotype (or haplotype) data, into the different number of heterozygous loci classes, thus, amounts to appreciable loss of information.

Evaluating statistical methods used to estimate the number of postsynaptic receptors.

Calcium levels in spines play a significant role in determining the sign and magnitude of synaptic plasticity. The magnitude of calcium influx into spines is highly dependent on influx through N-methyl D-aspartate (NMDA) receptors, and therefore depends on the number of postsynaptic NMDA receptors in each spine. We have calculated previously how the number of postsynaptic NMDA receptors determines the mean and variance of calcium transients in the postsynaptic density, and how this alters the shape of plasticity curves. However, the number of postsynaptic NMDA receptors in the postsynaptic density is not well known. Anatomical methods for estimating the number of NMDA receptors produce estimates that are very different than those produced by physiological techniques. The physiological techniques are based on the statistics of synaptic transmission and it is difficult to experimentally estimate their precision. In this paper we use stochastic simulations in order to test the validity of a physiological estimation technique based on failure analysis. We find that the method is likely to underestimate the number of postsynaptic NMDA receptors, explain the source of the error, and re-derive a more precise estimation technique. We also show that the original failure analysis as well as our improved formulas are not robust to small estimation errors in key parameters.

Acclimatization to high-variance habitats does not enhance physiological tolerance of two key Caribbean corals to future temperature and pH

Corals are acclimatized to populate dynamic habitats that neighbour coral reefs. Habitats such as seagrass beds exhibit broad diel changes in temperature and pH that routinely expose corals to conditions predicted for reefs over the next 50-100 years. However, whether such acclimatization effectively enhances physiological tolerance to, and hence provides refuge against, future climate scenarios remains unknown. Also, whether corals living in low-variance habitats can tolerate present-day high-variance conditions remains untested. We experimentally examined how pH and temperature predicted for the year 2100 affects the growth and physiology of two dominant Caribbean corals (Acropora palmata and Porites astreoides) native to habitats with intrinsically low (outer-reef terrace, LV) and/or high (neighbouring seagrass, HV) environmental variance. Under present-day temperature and pH, growth and metabolic rates (calcification, respiration and photosynthesis) were unchanged for HV versus LV populations. Superimposing future climate scenarios onto the HV and LV conditions did not result in any enhanced tolerance to colonies native to HV. Calcification rates were always lower for elevated temperature and/or reduced pH. Together, these results suggest that seagrass habitats may not serve as refugia against climate change if the magnitude of future temperature and pH changes is equivalent to neighbouring reef habitats.

Human TOP3: a single-copy gene encoding DNA topoisomerase III.

A human cDNA encoding a protein homologous to the Escherichia coli DNA topoisomerase I subfamily of enzymes has been identified through cloning and sequencing. Expressing the cloned human cDNA in yeast (delta)top1 cells lacking endogenous DNA topoisomerase I yielded an activity in cell extracts that specifically reduces the number of supercoils in a highly negatively supercoiled DNA. On the basis of these results, the human gene containing the cDNA sequence has been denoted TOP3, and the protein it encodes has been denoted DNA topoisomerase III. Screening of a panel of human-rodent somatic hybrids and fluorescence in situ hybridization of cloned TOP3 genomic DNA to metaphase chromosomes indicate that human TOP3 is a single-copy gene located at chromosome 17p11.2-12.