Surface features in the taxonomy of Pratylenchus species

RESP-872

Different models of genetic variation and their effect on genomic evaluation

<p>Abstract</p> <p>Background</p> <p>The theory of genomic selection is based on the prediction of the effects of quantitative trait loci (QTL) in linkage disequilibrium (LD) with markers. However, there is increasing evidence that genomic selection also relies on "relationships" between individuals to accurately predict genetic values. Therefore, a better understanding of what genomic selection actually predicts is relevant so that appropriate methods of analysis are used in genomic evaluations.</p> <p>Methods</p> <p>Simulation was used to compare the performance of estimates of breeding values based on pedigree relationships (Best Linear Unbiased Prediction, BLUP), genomic relationships (gBLUP), and based on a Bayesian variable selection model (Bayes B) to estimate breeding values under a range of different underlying models of genetic variation. The effects of different marker densities and varying animal relationships were also examined.</p> <p>Results</p> <p>This study shows that genomic selection methods can predict a proportion of the additive genetic value when genetic variation is controlled by common quantitative trait loci (QTL model), rare loci (rare variant model), all loci (infinitesimal model) and a random association (a polygenic model). The Bayes B method was able to estimate breeding values more accurately than gBLUP under the QTL and rare variant models, for the alternative marker densities and reference populations. The Bayes B and gBLUP methods had similar accuracies under the infinitesimal model.</p> <p>Conclusions</p> <p>Our results suggest that Bayes B is superior to gBLUP to estimate breeding values from genomic data. The underlying model of genetic variation greatly affects the predictive ability of genomic selection methods, and the superiority of Bayes B over gBLUP is highly dependent on the presence of large QTL effects. The use of SNP sequence data will outperform the less dense marker panels. However, the size and distribution of QTL effects and the size of reference populations still greatly influence the effectiveness of using sequence data for genomic prediction.</p

The importance of information on relatives for the prediction of genomic breeding values and the implications for the makeup of reference data sets in livestock breeding schemes.

<p>Abstract</p> <p>Background</p> <p>The theory of genomic selection is based on the prediction of the effects of genetic markers in linkage disequilibrium with quantitative trait loci. However, genomic selection also relies on relationships between individuals to accurately predict genetic value. This study aimed to examine the importance of information on relatives versus that of unrelated or more distantly related individuals on the estimation of genomic breeding values.</p> <p>Methods</p> <p>Simulated and real data were used to examine the effects of various degrees of relationship on the accuracy of genomic selection. Genomic Best Linear Unbiased Prediction (gBLUP) was compared to two pedigree based BLUP methods, one with a shallow one generation pedigree and the other with a deep ten generation pedigree. The accuracy of estimated breeding values for different groups of selection candidates that had varying degrees of relationships to a reference data set of 1750 animals was investigated.</p> <p>Results</p> <p>The gBLUP method predicted breeding values more accurately than BLUP. The most accurate breeding values were estimated using gBLUP for closely related animals. Similarly, the pedigree based BLUP methods were also accurate for closely related animals, however when the pedigree based BLUP methods were used to predict unrelated animals, the accuracy was close to zero. In contrast, gBLUP breeding values, for animals that had no pedigree relationship with animals in the reference data set, allowed substantial accuracy.</p> <p>Conclusions</p> <p>An animal's relationship to the reference data set is an important factor for the accuracy of genomic predictions. Animals that share a close relationship to the reference data set had the highest accuracy from genomic predictions. However a baseline accuracy that is driven by the reference data set size and the overall population effective population size enables gBLUP to estimate a breeding value for unrelated animals within a population (breed), using information previously ignored by pedigree based BLUP methods.</p

Relativistic many-body calculations of electric-dipole matrix elements, lifetimes and polarizabilities in rubidium

Electric-dipole matrix elements for ns-n'p, nd-n'p, and 6d-4f transitions in Rb are calculated using a relativistic all-order method. A third-order calculation is also carried out for these matrix elements to evaluate the importance of the high-order many-body perturbation theory contributions. The all-order matrix elements are used to evaluate lifetimes of ns and np levels with n=6, 7, 8 and nd levels with n=4, 5, 6 for comparison with experiment and to provide benchmark values for these lifetimes. The dynamic polarizabilities are calculated for ns states of rubidium. The resulting lifetime and polarizability values are compared with available theory and experiment.Comment: 8 pages, 2 figure

A qualitative investigation of decision making during help-seeking for adult hearing loss

Objective: The Any Qualified Provider framework in the National Health Service has changed the way adult audiology services are offered in England. Under the new rules, patients are being offered a choice in geographical location and audiology provider. This study aimed to explore how choices in treatment are presented and to identify what information patients need when they are seeking help with hearing loss. Design: This study adopted qualitative methods of ethnographic observations and focus group interviews to identify information needed prior to, and during, help-seeking. Observational data and focus group data were analysed using the constant comparison method of grounded theory. Study sample: Participants were recruited from a community Health and Social Care Trust in the west of England. This service incorporates both an Audiology and a Hearing Therapy service. Twenty seven participants were involved in focus groups or interviews. Results: Participants receive little information beyond the detail of hearing aids. Participants report little information that was not directly related to uptake of hearing aids. Conclusions: Participant preferences were not explored and limited information resulted in decisions that were clinician-led. The gaps in information reflect previous data on clinician communication and highlight the need for consistent information on a range of interventions to manage hearing loss

The frequency of transforming growth factor-TGF-B gene polymorphisms in a normal southern Iranian population

Several single nucleotide polymorphisms (SNPs) of the transforming growth factor-β1 gene (TGFB1) have been reported. Determination of TGFB1 SNPs allele frequencies in different ethnic groups is useful for both population genetic analyses and association studies with immunological diseases. In this study, five SNPs of TGFB1 were determined in 325 individuals from a normal southern Iranian population using polymerase chain reaction-restriction fragment length polymorphism method. This population was in Hardy-Weinberg equilibrium for these SNPs. Of the 12 constructed haplotypes, GTCGC and GCTGC were the most frequent in the normal southern Iranian population. Comparison of genotype and allele frequencies of TGFB SNPs between Iranian and other populations (meta-analysis) showed significant differences, and in this case the southern Iranian population seems genetically similar to Caucasoid populations. However, neighbour-joining tree using Nei's genetic distances based on TGF-β1 allele frequencies showed that southern Iranians are genetically far from people from the USA, Germany, UK, Denmark and the Czech Republic. In conclusion, this is the first report of the distribution of TGFB1 SNPs in an Iranian population and the results of this investigation may provide useful information for both population genetic and disease studies. © 2008 The Authors