Genetic Differentiation and Delimitation between Ecologically Diverged Populus euphratica and P. pruinosa

The fixed genetic differences between ecologically divergent species were found to change greatly depending on the markers examined. With such species it is difficult to differentiate between shared ancestral polymorphisms and past introgressions between the diverging species. In order to disentangle these possibilities and provide a further case for DNA barcoding of plants, we examine genetic differentiation between two ecologically divergent poplar species, Populus euphratica Oliver and P. pruinosa Schrenk using three different types of genetic marker.We genotyped 290 individuals from 29 allopatric and sympatric populations, using chloroplast (cp) DNA, nuclear (nr) ITS sequences and eight simple sequence repeat (SSR) loci. Three major cpDNA haplotypes were widely shared between the two species and between-species cpDNA differentiation (F(CT)) was very low, even lower than among single species populations. The average SSR F(CT) values were higher. Bayesian clustering analysis of all loci allowed a clear delineation of the two species. Gene flow, determined by examining all SSR loci, was obvious but only slightly asymmetrical. However, the two species were almost fixed for two different nrITS genotypes that had the highest F(CT), although a few introgressed individuals were detected both in allopatric and sympatric populations.The two species shared numerous ancestral polymorphisms at cpDNA and a few SSR loci. Both ITS and a combination of nuclear SSR data could be used to differentiate between the two species. Introgressions and gene flow were obvious between the two species either during or after their divergence. Our findings underscore the complex genetic differentiations between ecologically diverged species and highlight the importance of nuclear DNA (especially ITS) differentiation for delimiting closely related plant species

Tailoring evolutionary algorithms to solve the multi-objective location-routing problem for biomass waste collection

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Location-routing problems widely exist in logistics activities. For the biomass waste collection, there is a recognized need for novel models to locate the collection facilities and plan the vehicle routes. So far most location-routing models fall into the cost-driven-only category. However, comprehensive objectives are required in the specific context, such as time-dependent pollution and speed-and load-related emission. Furthermore, location-routing problems are hierarchical by nature, containing the facility location problems (strategic level) and the vehicle routing problems (tactical level). Existing studies in this field usually adopt computational intelligence methods directly without decomposing the problem. This can be inefficient especially when multiple objectives are applied. Motivated by these, we develop a novel multi-objective optimization model for the location-routing problem for biomass waste collection. To solve this model, we explore the way to tailor evolutionary algorithms to the hierarchical structure. We develop adapted versions of two commonly used evolutionary algorithms: the genetic algorithm and the ant colony optimization algorithm. For the genetic algorithm, we divide the population by the strategic level decisions, so that each subpopulation has a fixed location plan, breaking the location-routing problem down into many multi-depot vehicle routing problems. For the ant colony optimization, we use an additional pheromone vector to track the good decisions on the location level, and segregate the pheromones related to different satellite depots to avoid misleading information. Thus, the problem degenerates into vehicle routing problem. Experimental results show that our proposed methods have better performances on the location routing problem for biomass waste collection

An integrated genetic linkage map for silkworms with three parental combinations and its application to the mapping of single genes and QTL

<p>Abstract</p> <p>Background</p> <p><it>Bombyx mori</it>, the domesticated silkworm, is a well-studied model insect with great economic and scientific significance. Although more than 400 mutations have been described in silkworms, most have not been identified, especially those affecting economically-important traits. Simple sequence repeats (SSRs) are effective and economical tools for mapping traits and genetic improvement. The current SSR linkage map is of low density and contains few polymorphisms. The purpose of this work was to develop a dense and informative linkage map that would assist in the preliminary mapping and dissection of quantitative trait loci (QTL) in a variety of silkworm strains.</p> <p>Results</p> <p>Through an analysis of > 50,000 genotypes across new mapping populations, we constructed two new linkage maps covering 27 assigned chromosomes and merged the data with previously reported data sets. The integrated consensus map contains 692 unique SSR sites, improving the density from 6.3 cM in the previous map to 4.8 cM. We also developed 497 confirmed neighboring markers for corresponding low-polymorphism sites, with 244 having polymorphisms. Large-scale statistics on the SSR type were suggestive of highly efficient markers, based upon which we searched 16,462 available genomic scaffolds for SSR loci. With the newly constructed map, we mapped single-gene traits, the QTL of filaments, and a number of ribosomal protein genes.</p> <p>Conclusion</p> <p>The integrated map produced in this study is a highly efficient genetic tool for the high-throughput mapping of single genes and QTL. Compared to previous maps, the current map offers a greater number of markers and polymorphisms; thus, it may be used as a resource for marker-assisted breeding.</p

Approaches to enhance electroluminescent efficiency of light-emitting diodes based on quasi-two-dimensional perovskite

Quasi-two-dimensional (quasi-2D) perovskites with (Ai)2(A2)n-iPbnX3n+i multi-quantum well structures are considered as the potential electroluminescence (EL) materials due to their controllable quantum confine effect which would lead a high EL efficiency. However, the quasi-2D perovskite films fabricated with solution processing technologies consist of different n phases and orientated layers, which limits the performance of quasi-2D perovskite light- emitting diodes (PeLEDs). To improve the performance of PeLEDs, it is essential to obtain perovskite thin films with both large exciton binding energy, complete surface coverage and suitable morphology. Here some approaches are developed to improve the performance of quasi-2D PeLEDs