Genetic evaluation with finite locus models

The availability of genotypic data in recent years has resulted in increased interest in the use of marker assisted genetic evaluation (MAGE) in livestock species. Under additive inheritance, Henderson\u27s mixed model equations (HMME) provide an efficient approach to obtain genetic evaluations by marker assisted best linear unbiased prediction (MABLUP) given pedigree relationships, trait, and marker data. For large pedigrees with many missing markers, however, it is not feasible to calculate the exact gametic variance covariance matrix required to construct HMME, and thus, approximations are used. By computer simulation we observed that the use of exact matrices would increase response to selection by 2.2% up to 11.7%. Marker assisted selection (MAS) is efficient especially for traits that have low heritability and non-additive gene action. BLUP methodology under non-additive gene action is not feasible for large inbred or crossbred pedigrees. It is easy to incorporate non-additive gene action in a finite locus model. Under such a model, the unobservable genotypic values can be predicted using the conditional mean of the genotypic values given the available data, which is also known as the best predictor (BP). The potential of alternative methods to compute BP under finite locus models was studied, and it was shown that Markov chain Monte Carlo (MCMC) methods that sample blocks of genotypes jointly hold most promise for such computations. The efficiency of MCMC methods for genetic evaluation by BP under finite locus models, depends on the number of loci considered in the model. Thus, the effect of the number of loci used in the finite locus model used for genetic evaluation by BP was studied by computer simulation. In our study, models with two to six loci yielded accurate BP evaluations for traits determined by 100 loci. Finally, we proposed a strategy to improve the computational efficiency of MAGE under finite locus models

The potential of computationally rendered images for the evaluation of lighting quality in interior spaces

Lighting designers have the ability to show, and help everyone visualize the outcome of the lighting design by using tools such as calculations, mock-ups, and renderings. In recent years, the use of digital renderings instead of mock-up installations has become increasingly popular.;Even though the rendering methods that exist today offer the possibility to accurately simulate a scene, this does not guarantee that the images will be interpreted and perceived correctly. Increased applications of computer graphics which demand high levels of realism has made it necessary to examine the manner in which these images are evaluated and validated.;The objective of our research is to determine if classic lighting studies can be explored in a contemporary setting by using computationally rendered images, and to identify to what extent the subjective evaluation of the lighting conditions of an interior space can be reproduced using these images

Hierarchical Segmentation of Polarimetric SAR Images Using Heterogeneous Clutter Models

International audienceIn this paper, heterogeneous clutter models are used to describe polarimetric synthetic aperture radar (PolSAR) data. The KummerU distribution is introduced to model the PolSAR clutter. Then, a detailed analysis is carried out to evaluate the potential of this new multivariate distribution. It is implemented in a hierarchical maximum likelihood segmentation algorithm. The segmentation results are shown on both synthetic and high-resolution PolSAR data at the X- and L-bands. Finally, some methods are examined to determine automatically the "optimal" number of segments in the final partition

An efficient algorithm to compute marginal posterior genotype probabilities for every member of a pedigree with loops

<p>Abstract</p> <p>Background</p> <p>Marginal posterior genotype probabilities need to be computed for genetic analyses such as geneticcounseling in humans and selective breeding in animal and plant species.</p> <p>Methods</p> <p>In this paper, we describe a peeling based, deterministic, exact algorithm to compute efficiently genotype probabilities for every member of a pedigree with loops without recourse to junction-tree methods from graph theory. The efficiency in computing the likelihood by peeling comes from storing intermediate results in multidimensional tables called cutsets. Computing marginal genotype probabilities for individual <it>i </it>requires recomputing the likelihood for each of the possible genotypes of individual <it>i</it>. This can be done efficiently by storing intermediate results in two types of cutsets called anterior and posterior cutsets and reusing these intermediate results to compute the likelihood.</p> <p>Examples</p> <p>A small example is used to illustrate the theoretical concepts discussed in this paper, and marginal genotype probabilities are computed at a monogenic disease locus for every member in a real cattle pedigree.</p

Improved techniques for sampling complex pedigrees with the Gibbs sampler

Markov chain Monte Carlo (MCMC) methods have been widely used to overcome computational problems in linkage and segregation analyses. Many variants of this approach exist and are practiced; among the most popular is the Gibbs sampler. The Gibbs sampler is simple to implement but has (in its simplest form) mixing and reducibility problems; furthermore in order to initiate a Gibbs sampling chain we need a starting genotypic or allelic configuration which is consistent with the marker data in the pedigree and which has suitable weight in the joint distribution. We outline a procedure for finding such a configuration in pedigrees which have too many loci to allow for exact peeling. We also explain how this technique could be used to implement a blocking Gibbs sampler

Seed transmission and control of Sclerotinia sclerotiorum in soybean seeds

In this study, we addressed issues related to the importance of internal infection of soybean seeds infected with Sclerotinia sclerotiorum, the cause of Sclerotinia stem rot. The first objective of this study was to determine the extent of contamination of soybean seed lots grown in Mid-West of the USA with seeds infected with Sclerotinia sclerotiorum. Fifty seed lots from the Mid-West of USA in each of the years 1997, 1998, and 1999 of soybean seed crops, were analyzed for internally infected seeds with S. sclerotiorum. The pathogen Sclerotinia sclerotiorum was present in 1997 in three seed lots. In the next two years, 1998 and 1999, the pathogen was not present in any of the seed lots analyzed. The second objective was to determine the mechanism of transmission of the disease from infected plants to seeds. Seeds from diseased and healthy plants were analyzed for seed infection. Infected seeds came from infected tissues of infected plants, and not from healthy tissues of infected plants. Infected plants that showed visible symptoms were actually the plants that produced internally infected seeds. The third objective was to determine the significance of soybean seeds infected with Sclerotinia sclerotiorum as a means of infesting fields with sclerotia or transmitting the disease to plants grown from the infected seeds. The development of the fungus was analyzed at different levels of temperatures (15C, 20C,and 25C) and moisture in soil (28% and 35%). Even though the best environmental conditions for disease development are prolonged periods of moist and cool weather, temperature and moisture were not environmental factors that had a significant influence in sclerotia formation. The fourth objective was the seed conditioning as a part of disease management. The fungus was analyzed in relation to the seed size. Seeds that pass through a 10/64 sieve represent the fraction of seeds with the highest incidence of infection. The seed conditioning process (particularly the air screen cleaner) can be very effective in eliminating sclerotia, which represents an important source of inoculum for Sclerotinia sclerotiorum, The fifth objective was to investigate the effectiveness of seed treatment fungicides in eradicating seedborne infection of soybeans with Sclerotinia sclerotiorum. The best results were obtained using carboxim + thiram which reduced the fungus expression by 99% for inoculated seeds, and captan + PCNB + thiabendazole, which reduced the fungus expression by 89% for inoculated seeds

Advanced Sea Clutter Models and their Usefulness for Target Detection

International audienceRobust naval target detection is of significant importance to national security, to navigation safety, and to environmental monitoring. Here we consider the particular case of high resolution coastal radars, working at low grazing angles. The robustness of detection heavily relies on the appropriate knowledge of two classes of backscattered signals: the target echo, and the sea echo. The latter, usually regarded as a noise, is known as the sea clutter. This particular combination, of high resolution and low grazing angles, raises considerable challenges to radar processing algorithms. Specifically, the probability density function governing the sea clutter amplitude is no more Gaussian and a lot of effort has been aimed at characterizing it. Three approaches are reviewed here: the stochastic, texture and chaotic models. While the stochastic models represent an essay to extend classical detection theory to radars operating in marine environment, the other two models represent entirely new paradigms. Since each model has its strengths and weaknesses and more testing on real data is required to credibly validate any of the proposed models, a definitive conclusion is far from reach. However, critical comments, as well as experimentally supported conclusions are presented in the paper

Electrochemical preparation and characterisation of bilayer films composed by Prussian Blue and conducting polymer

Preparation and electrochemical behaviour of bilayer films consisting of iron(Ill) hexacyanoferrate, well known as Prussian Blue, and of poly[4,4´-bis(butylsulphanyl)-2,2´-bithiophene], on a platinum electrode, are reported. The electrochemical features of the Prussian Blue/conducting polymer bilayer system are examined in aqueous and acetonitrile solutions. Cyclic voltammetric studies show that, in acetonitrile solvent, the inner layer Prussian Blue is electroactive to some extent, though the electrochemical response of the system is mainly accounted for by poly[4,4´-bis(butylsulphanyl)-2,2´-bithiophene] outer layer. On the other hand, in aqueous solution Prussian Blue exhibits good electroactivity. Under specific experimental conditions, the individual redox behaviour of each constituent of the bilayer is evidenced in the two solvents separately, i.e., that of PB and that of poly[4,4´-bis(butylsulphanyl)-2,2´bithiophene] in aqueous and in organic solvent, respectively. However, interesting reciprocal influences are evident in the current/potential curves recorded under conditions which are discussed

Polydactyl Pigs: There’s More to the Story Than Just Extra Toes

Several pigs expressing a polydactyl (extra toes) phenotype were identified in the ISU purebred Yorkshire herd. Sires, dams, and littermate sibs to the polydactyl pigs were retained in the herd and planned matings were designed to enlarge the population. In addition to creating 12 pigs with either extra toes or dewclaws, the population also had an extremely high number of stillborn and mummified pigs. Furthermore, this population also showed differences in growth and reproduction. Multiple genes have been implicated in causing extra digits in several other species. Using comparative genomics as a guide many of these genes were expected to map on pig chromosome 18. Pig chromosome 18 is the smallest pig autosome on which there has been limited research. Candidate genes on pig chromosome 18 were mapped to ensure their location using Iowa State University’s Berkshire by Yorkshire resource population. Once chromosomal locations were confirmed for each candidate gene, genotypes were obtained for each gene on all pigs in the polydactyl population and were used by a complex statistical method (Elston-Stewart algorithm) to calculate the likelihood that the gene caused the polydactyl phenotype