Genome-Enabled Hitchhiking Mapping Identifies QTLs for Stress Resistance in Natural \u3ci\u3eDrosophila\u3c/i\u3e

Identification of genes underlying complex traits is an important problem. Quantitative trait loci (QTL) are mapped using marker-trait co-segregation in large panels of recombinant genotypes. Most frequently, recombinant inbred lines derived from two isogenic parents are used. Segregation pat-terns are also studied in pedigrees from multiple families. Great advances have been made through creative use of these techniques, but narrow sampling and inadequate power represent strong limi-tations. Here, we propose an approach combining the strengths of both techniques. We established a mapping population from a sample of natural genotypes and applied artificial selection for a com-plex character. Selection changed the frequencies of alleles in QTLs contributing to the selection re-sponse. We infer QTLs with dense genotyping microarrays by identifying blocks of linked markers undergoing selective changes in allele frequency. We demonstrated this approach with an experi-mental population composed from 20 isogenic strains. Selection for starvation survival was executed in three replicated populations with three control non-selected populations. Three individuals per population were genotyped using Affymetrix GeneChips. Two regions of the genome, one each on the left arms of the second and third chromosomes, showed significant divergence between control and selected populations. For the former region, we inferred allele frequencies in selected and control populations by pyrosequencing. We conclude that the allele frequency difference, averaging approx-imately 40% between selected and control lines, contributed to selection response. Our approach can contribute to the fine scale decomposition of the genetics of direct and indirect selection responses and genotype by environment interactions

Genome-Enabled Hitchhiking Mapping Identifies QTLs for Stress Resistance in Natural \u3ci\u3eDrosophila\u3c/i\u3e

Identification of genes underlying complex traits is an important problem. Quantitative trait loci (QTL) are mapped using marker-trait co-segregation in large panels of recombinant genotypes. Most frequently, recombinant inbred lines derived from two isogenic parents are used. Segregation pat-terns are also studied in pedigrees from multiple families. Great advances have been made through creative use of these techniques, but narrow sampling and inadequate power represent strong limi-tations. Here, we propose an approach combining the strengths of both techniques. We established a mapping population from a sample of natural genotypes and applied artificial selection for a com-plex character. Selection changed the frequencies of alleles in QTLs contributing to the selection re-sponse. We infer QTLs with dense genotyping microarrays by identifying blocks of linked markers undergoing selective changes in allele frequency. We demonstrated this approach with an experi-mental population composed from 20 isogenic strains. Selection for starvation survival was executed in three replicated populations with three control non-selected populations. Three individuals per population were genotyped using Affymetrix GeneChips. Two regions of the genome, one each on the left arms of the second and third chromosomes, showed significant divergence between control and selected populations. For the former region, we inferred allele frequencies in selected and control populations by pyrosequencing. We conclude that the allele frequency difference, averaging approx-imately 40% between selected and control lines, contributed to selection response. Our approach can contribute to the fine scale decomposition of the genetics of direct and indirect selection responses and genotype by environment interactions

An efficient and general approach for implementing thermodynamic phase equilibria information in geophysical and geodynamic studies

We present a flexible, general, and efficient approach for implementing thermodynamic phase equilibria information (in the form of sets of physical parameters) into geophysical and geodynamic studies. The approach is based on Tensor Rank Decomposition methods, which transform the original multidimensional discrete information into a separated representation that contains significantly fewer terms, thus drastically reducing the amount of information to be stored in memory during a numerical simulation or geophysical inversion. Accordingly, the amount and resolution of the thermodynamic information that can be used in a simulation or inversion increases substantially. In addition, the method is independent of the actual software used to obtain the primary thermodynamic information, and therefore, it can be used in conjunction with any thermodynamic modeling program and/or database. Also, the errors associated with the decomposition procedure are readily controlled by the user, depending on her/his actual needs (e.g., preliminary runs versus full resolution runs). We illustrate the benefits, generality, and applicability of our approach with several examples of practical interest for both geodynamic modeling and geophysical inversion/modeling. Our results demonstrate that the proposed method is a competitive and attractive candidate for implementing thermodynamic constraints into a broad range of geophysical and geodynamic studies. MATLAB implementations of the method and examples are provided as supporting information and can be downloaded from the journal's website.Peer ReviewedPostprint (author's final draft

Theory of High-Tc Superconductivity: Accurate Predictions of Tc

The superconducting transition temperatures of high-Tc compounds based on copper, iron, ruthenium and certain organic molecules are discovered to be dependent on bond lengths, ionic valences, and Coulomb coupling between electronic bands in adjacent, spatially separated layers [1]. Optimal transition temperature, denoted as T_c0, is given by the universal expression $k_BT_c0 = e^2 \Lambda / \ell\zeta$; $\ell$ is the spacing between interacting charges within the layers, \zeta is the distance between interacting layers and \Lambda is a universal constant, equal to about twice the reduced electron Compton wavelength (suggesting that Compton scattering plays a role in pairing). Non-optimum compounds in which sample degradation is evident typically exhibit Tc < T_c0. For the 31+ optimum compounds tested, the theoretical and experimental T_c0 agree statistically to within +/- 1.4 K. The elemental high Tc building block comprises two adjacent and spatially separated charge layers; the factor e^2/\zeta arises from Coulomb forces between them. The theoretical charge structure representing a room-temperature superconductor is also presented.Comment: 7 pages 5 references, 6 figures 1 tabl

The impact of prior platinum therapy on survival in patients with metastatic urothelial cancer receiving vinflunine

Background: A phase III trial demonstrated an overall survival advantage with the addition of vinflunine to best supportive care (BSC) in platinum-refractory advanced urothelial cancer. We subsequently examined the impact of an additional 2 years of survival follow-up and evaluated the influence of first-line platinum therapy on survival. Methods: The 357 eligible patients from the phase III study were categorised into two cohorts depending on prior cisplatin treatment: cisplatin or non-cisplatin. Survival was calculated using the Kaplan–Meier method. Results: The majority had received prior cisplatin (70.3%). Survival was higher in the cisplatin group (HR: 0.76; CI 95% 0.58–0.99; P=0.04) irrespective of treatment arm. Multivariate analysis including known prognostic factors (liver involvement, haemoglobin, performance status) and prior platinum administration did not show an independent effect of cisplatin. Vinflunine reduced the risk of death by 24% in the cisplatin-group (HR: 0.76; CI 95% 0.58–0.99; P=0.04) and by 35% in non-cisplatin patients (HR: 0.65; CI 95% 0.41–1.04; P=0.07). Interpretation: Differences in prognostic factors between patients who can receive prior cisplatin and those who cannot may explain the survival differences in patients who undergo second line therapy. Prior cisplatin administration did not diminish the subsequent benefit of vinflunine over BSC

Poincare Semigroup Symmetry as an Emergent Property of Unstable Systems

The notion that elementary systems correspond to irreducible representations of the Poincare group is the starting point for this paper, which then goes on to discuss how a semigroup for the time evolution of unstable states and resonances could emerge from the underlying Poincare symmetry. Important tools in this analysis are the Clebsch-Gordan coefficients for the Poincare group.Comment: 17 pages, 1 figur