6 resultados para CROSSOVER

em Cambridge University Engineering Department Publications Database


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Meiosis is a specialized eukaryotic cell division that generates haploid gametes required for sexual reproduction. During meiosis, homologous chromosomes pair and undergo reciprocal genetic exchange, termed crossover (CO). Meiotic CO frequency varies along the physical length of chromosomes and is determined by hierarchical mechanisms, including epigenetic organization, for example methylation of the DNA and histones. Here we investigate the role of DNA methylation in determining patterns of CO frequency along Arabidopsis thaliana chromosomes. In A. thaliana the pericentromeric regions are repetitive, densely DNA methylated, and suppressed for both RNA polymerase-II transcription and CO frequency. DNA hypomethylated methyltransferase1 (met1) mutants show transcriptional reactivation of repetitive sequences in the pericentromeres, which we demonstrate is coupled to extensive remodeling of CO frequency. We observe elevated centromere-proximal COs in met1, coincident with pericentromeric decreases and distal increases. Importantly, total numbers of CO events are similar between wild type and met1, suggesting a role for interference and homeostasis in CO remodeling. To understand recombination distributions at a finer scale we generated CO frequency maps close to the telomere of chromosome 3 in wild type and demonstrate an elevated recombination topology in met1. Using a pollen-typing strategy we have identified an intergenic nucleosome-free CO hotspot 3a, and we demonstrate that it undergoes increased recombination activity in met1. We hypothesize that modulation of 3a activity is caused by CO remodeling driven by elevated centromeric COs. These data demonstrate how regional epigenetic organization can pattern recombination frequency along eukaryotic chromosomes.

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We have investigated single grain boundaries (GBs) isolated in coated conductors produced by Metal-Organic Deposition (MOD). When a magnetic field is swept in the film plane, an angle-dependent crossover from boundary to grain limited critical current density Jc is found. In the force-free orientation, even at fields as high as 8 T, the GBs still limit Jc. We deduce that this effect is a direct consequence of GB meandering. We have employed these single GB results to explain the dependence of Jc of polycrystalline tracks on their width: in-plane measurements become flatter as the tracks are narrowed down. This result is consistent with the stronger GB limitation at field configurations close to force-free found from the isolated boundaries. Our study shows that for certain geometries even at high fields the effect of GBs cannot be neglected.

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Sexual eukaryotes reproduce via the meiotic cell division, where ploidy is halved and homologous chromosomes undergo reciprocal genetic exchange, termed crossover (CO). CO frequency has a profound effect on patterns of genetic variation and species evolution. Relative CO rates vary extensively both within and between plant genomes. Plant genome size varies by over 1000-fold, largely due to differential expansion of repetitive sequences, and increased genome size is associated with reduced CO frequency. Gene versus repeat sequences associate with distinct chromatin modifications, and evidence from plant genomes indicates that this epigenetic information influences CO patterns. This is consistent with data from diverse eukaryotes that demonstrate the importance of chromatin structure for control of meiotic recombination. In this review I will discuss CO frequency patterns in plant genomes and recent advances in understanding recombination distributions.

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Genetic algorithms (GAs) have been used to tackle non-linear multi-objective optimization (MOO) problems successfully, but their success is governed by key parameters which have been shown to be sensitive to the nature of the particular problem, incorporating concerns such as the numbers of objectives and variables, and the size and topology of the search space, making it hard to determine the best settings in advance. This work describes a real-encoded multi-objective optimizing GA (MOGA) that uses self-adaptive mutation and crossover, and which is applied to optimization of an airfoil, for minimization of drag and maximization of lift coefficients. The MOGA is integrated with a Free-Form Deformation tool to manage the section geometry, and XFoil which evaluates each airfoil in terms of its aerodynamic efficiency. The performance is compared with those of the heuristic MOO algorithms, the Multi-Objective Tabu Search (MOTS) and NSGA-II, showing that this GA achieves better convergence.