Rapid decline of fitness in panmictic populations of Drosophila melanogaster maintained under relaxed natural selection

The parameters of the spontaneous deleterious mutation process remain poorly known, despite their importance. Here, we report the results of a mutation accumulation experiment performed on panmictic populations of Drosophila melanogaster without any genetic manipulations. Two experimental populations were kept for 30 generations under relaxed natural selection. Each generation, 100 pairs were formed randomly, and every fecund pair contributed a son and a daughter to the next generation. Comparison with two controls, one cryopreserved and the other kept as the experimental populations but with long generation time, showed that the number of surviving offspring per female declined by 0.2% and 2.0% per generation under benign and harsh, competitive conditions, respectively. Thus, the mutational pressure on fitness may be strong and depends critically on the conditions under which fitness is assayed.

Adult fitness consequences of sexual selection in Drosophila melanogaster

Few experiments have demonstrated a genetic correlation between the process of sexual selection and fitness benefits in offspring, either through female choice or male competition. Those that have looked at the relationship between female choice and offspring fitness have focused on juvenile fitness components, rather than fitness at later stages in the life cycle. In addition, many of these studies have not controlled for possible maternal effects. To test for a relationship between sexual selection and adult fitness, we carried out an artificial selection experiment in the fruit fly, Drosophila melanogaster. We created two treatments that varied in the level of opportunity for sexual selection. Increased opportunity for female choice and male competition was genetically correlated with an increase in adult survivorship, as well as an increase in male and female body size. Contrary to previous, single-generation studies, we did not find an increase in larval competitive ability. This study demonstrates that mate choice and/or male–male competition are correlated with an increase in at least one adult fitness component of offspring.

Italian wild hop (Humulus lupulus L.): from biodiversity evaluation to varietal selection

Hop (Humulus lupulus L.) is a dioecius perennial plant. The cultivation is specific for female plants, used mainly for brewing and pharmacology. Female inflorescence, known as cone or strobili, contains bitter acids, essential oil and polyphenols. Commercial hop cultivation provides better results in regions between 45 and 55 degrees north or south in latitude, an area that also includes the northern part of Italy, where hop is endemic. Despite several studies have been conducted on the characterization of wild hops biodiversity in the U.S.A. and Europe, a lack in literature concerning the description of Italian wild hops genetic variability is still present. The increasing request of hop varieties improved in important traits, like diseases, resistance and valuable aroma profile, is bringing the hop industry. Moreover, Italian agricultural sector needs new impulse to be competitive in the market. In this view, Italian wild hop biodiversity is a resource, useful for the obtaining of Italian hop varieties, characterized by peculiar aromatic traits and more adaptable to Mediterranean climate, making their cultivation more sustainable. Based on this consideration, the present Ph.D. thesis deals with the evaluation of the Italian hop biodiversity, through the characterization of the wild samples under different point of view. The project started with the recovery of wild hop samples in different areas of north of Italy to consitue a collection field, where 11 commercial cultivars of US and European origin were grown, to have a complete vision of the hop panorama. Ph.D. project followed different research lines, the results of each one contributed to completly characterize the northern Italian hop wild biodiversity: • the morphological description showed a high phenological variability (Study 1); • the genetic characterization confirmed the rich biodiversity of the Italian population and showed a significant genetic distance between Italian genotypes and the commercial cultivars, taken in consideration (Study 2); • the need of an early sex discrimination method leads to an improvement of a genetic marker, developing a more efficient marker (Study 3); • a complete morphologic, genetic and chemical analysis of plants gave results to select the most promising genotypes (Study 4); • the comparison between the performance of wild hops and commercial cultivars in the same collection field indicated that some wild genotypes had a higher environment adaptability (Study 5); • the evaluation of the terroir, obtained comparing commercial cultivars in the collection field and the same genotypes purchased in the market, showed the influence of the northern Italian environment on the aromatic profile (Study 5); • a new analytical method for the revelation of bioactive metabolites and a simple extraction procedure were developed (Study 6). In conclusion, the Ph.D. thesis, contains the first characterization of Italian wild hop, made under field condition. The present study: i) permits to obtain a complete and significative description of the genotypes; ii) allows the identification of the most promising wild Italian genotypes; iii) allows the identification of commercial cultivars more adaptable the northern Italian climate.

The right time and place:strategic positioning for competitive manufacture

Increasingly in the UK, companies that have traditionally considered themselves as manufacturers are being advised to now see themselves as service providers and to reconsider whether to have any production capability. A key challenge is to translate this strategy into a selection of product and service-centred activities within the company's supply chain networks. Strategic positioning is concerned with the choice of business activities a company carries out itself, compared to those provided by suppliers, partners, distributors and even customers. In practice, strategic positioning is directly impacted by such decisions as outsourcing, off-shoring, partnering, technology innovation, acquisition and exploitation. If companies can better understand their strategic positioning, they can make more informed decisions about the adoption of alternative manufacturing and supply chain activities. Similarly, they are more likely to reject those that, like off-shoring, are currently en vogue but are highly likely to erode competitive edge and business success. Our research has developed a new concept we call 'competitive space' as a means of appreciating the strategic positioning of companies, along with a structured decision process for managing competitive space. Our ideas about competitive space, along with the decision process itself, have been developed and tested on a range of manufacturers. As more and more manufacturers are encouraged to move towards system integration and a serviceable business model, the challenge is to identify the appropriate strategic position for their organisations, or in other words, to identify their optimum competitive space for manufacture.

A decision support system for supplier selection and order allocation in stochastic, multi-stakeholder and multi-criteria environments

Integrated supplier selection and order allocation is an important decision for both designing and operating supply chains. This decision is often influenced by the concerned stakeholders, suppliers, plant operators and customers in different tiers. As firms continue to seek competitive advantage through supply chain design and operations they aim to create optimized supply chains. This calls for on one hand consideration of multiple conflicting criteria and on the other hand consideration of uncertainties of demand and supply. Although there are studies on supplier selection using advanced mathematical models to cover a stochastic approach, multiple criteria decision making techniques and multiple stakeholder requirements separately, according to authors' knowledge there is no work that integrates these three aspects in a common framework. This paper proposes an integrated method for dealing with such problems using a combined Analytic Hierarchy Process-Quality Function Deployment (AHP-QFD) and chance constrained optimization algorithm approach that selects appropriate suppliers and allocates orders optimally between them. The effectiveness of the proposed decision support system has been demonstrated through application and validation in the bioenergy industry.

Computer aided licence selection

A model of multiple criteria decision making is presented for selecting the “best” of a finite number of alternatives. Techniques of scoring the alternatives and weighting the criteria are combined with different evaluating procedures and amalgamated in an interactive algorithm. Application of this method for choosing the best tender in a competitive bidding is discussed and a case is presented in some detail.

Partner selection for reverse logistics centres in green supply chains: a fuzzy artificial immune optimization approach

The design of reverse logistics networks has now emerged as a major issue for manufacturers, not only in developed countries where legislation and societal pressures are strong, but also in developing countries where the adoption of reverse logistics practices may offer a competitive advantage. This paper presents a new model for partner selection for reverse logistic centres in green supply chains. The model offers three advantages. Firstly, it enables economic, environment, and social factors to be considered simultaneously. Secondly, by integrating fuzzy set theory and artificial immune optimization technology, it enables both quantitative and qualitative criteria to be considered simultaneously throughout the whole decision-making process. Thirdly, it extends the flat criteria structure for partner selection evaluation for reverse logistics centres to the more suitable hierarchy structure. The applicability of the model is demonstrated by means of an empirical application based on data from a Chinese electronic equipment and instruments manufacturing company.

Process Selection Using Variation and Cost Relations

Variations are inherent in all manufacturing processes and can significantly affect the quality of a final assembly, particularly in multistage assembly systems. Existing research in variation management has primarily focused on incorporating GD&T factors into variation propagation models in order to predict product quality and allocate tolerances. However, process induced variation, which has a key influence on process planning, has not been fully studied. Furthermore, the link between variation and cost has not been well established, in particular the effect that assembly process selection has on the final quality and cost of a product. To overcome these barriers, this paper proposes a novel method utilizing process capabilities to establish the relationship between variation and cost. The methodology is discussed using a real industrial case study. The benefits include determining the optimum configuration of an assembly system and facilitating rapid introduction of novel assembly techniques to achieve a competitive edge.

Directed Selection using Reinforcement Learning for the Examination Timetabling Problem

Traditional heuristic approaches to the Examination Timetabling Problem normally utilize a stochastic method during Optimization for the selection of the next examination to be considered for timetabling within the neighbourhood search process. This paper presents a technique whereby the stochastic method has been augmented with information from a weighted list gathered during the initial adaptive construction phase, with the purpose of intelligently directing examination selection. In addition, a Reinforcement Learning technique has been adapted to identify the most effective portions of the weighted list in terms of facilitating the greatest potential for overall solution improvement. The technique is tested against the 2007 International Timetabling Competition datasets with solutions generated within a time frame specified by the competition organizers. The results generated are better than those of the competition winner in seven of the twelve examinations, while being competitive for the remaining five examinations. This paper also shows experimentally how using reinforcement learning has improved upon our previous technique.

Phase transitions in gene networks evolved under different selection rules

Mathematical models of gene regulation are a powerful tool for understanding the complex features of genetic control. While various modeling efforts have been successful at explaining gene expression dynamics, much less is known about how evolution shapes the structure of these networks. An important feature of gene regulatory networks is their stability in response to environmental perturbations. Regulatory systems are thought to have evolved to exist near the transition between stability and instability, in order to have the required stability to environmental fluctuations while also being able to achieve a wide variety of functions (corresponding to different dynamical patterns). We study a simplified model of gene network evolution in which links are added via different selection rules. These growth models are inspired by recent work on `explosive' percolation which shows that when network links are added through competitive rather than random processes, the connectivity phase transition can be significantly delayed, and when it is reached, it appears to be first order (discontinuous, e.g., going from no failure at all to large expected failure) instead of second order (continuous, e.g., going from no failure at all to very small expected failure). We find that by modifying the traditional framework for networks grown via competitive link addition to capture how gene networks evolve to avoid damage propagation, we also see significant delays in the transition that depend on the selection rules, but the transitions always appear continuous rather than `explosive'.

Aligning supplier evaluation with manufacturing competitive priorities. Results of an international survey in manufacturing and assembly industries

The aim of our research is to investigate a company’s purchasing and manufacturing competitive priorities jointly in order to uncover any relationships between them and also their effect on the supply chain tools implemented by the company. We assume that the supplier selection criteria of the companies reflect the true goals of the purchasing function and we take the purchasing function’s point of view to examine the aforementioned relationships. We use a multinational database for our empirical analysis which contains almost 700 companies from 20 countries and data that were acquired in 2009. We identified four different clusters which reflect a different level of supply chain tool implementation.

A Mutational Hotspot and Strong Selection Contribute to the Order of Mutations Selected for during Escherichia coli Adaptation to the Gut

The relative role of drift versus selection underlying the evolution of bacterial species within the gut microbiota remains poorly understood. The large sizes of bacterial populations in this environment suggest that even adaptive mutations with weak effects, thought to be the most frequently occurring, could substantially contribute to a rapid pace of evolutionary change in the gut. We followed the emergence of intra-species diversity in a commensal Escherichia coli strain that previously acquired an adaptive mutation with strong effect during one week of colonization of the mouse gut. Following this first step, which consisted of inactivating a metabolic operon, one third of the subsequent adaptive mutations were found to have a selective effect as high as the first. Nevertheless, the order of the adaptive steps was strongly affected by a mutational hotspot with an exceptionally high mutation rate of 10-5. The pattern of polymorphism emerging in the populations evolving within different hosts was characterized by periodic selection, which reduced diversity, but also frequency-dependent selection, actively maintaining genetic diversity. Furthermore, the continuous emergence of similar phenotypes due to distinct mutations, known as clonal interference, was pervasive. Evolutionary change within the gut is therefore highly repeatable within and across hosts, with adaptive mutations of selection coefficients as strong as 12% accumulating without strong constraints on genetic background. In vivo competitive assays showed that one of the second steps (focA) exhibited positive epistasis with the first, while another (dcuB) exhibited negative epistasis. The data shows that strong effect adaptive mutations continuously recur in gut commensal bacterial species.

De Novo Assembly And Transcriptome Analysis Of The Rubber Tree (hevea Brasiliensis) And Snp Markers Development For Rubber Biosynthesis Pathways.

Hevea brasiliensis (Willd. Ex Adr. Juss.) Muell.-Arg. is the primary source of natural rubber that is native to the Amazon rainforest. The singular properties of natural rubber make it superior to and competitive with synthetic rubber for use in several applications. Here, we performed RNA sequencing (RNA-seq) of H. brasiliensis bark on the Illumina GAIIx platform, which generated 179,326,804 raw reads on the Illumina GAIIx platform. A total of 50,384 contigs that were over 400 bp in size were obtained and subjected to further analyses. A similarity search against the non-redundant (nr) protein database returned 32,018 (63%) positive BLASTx hits. The transcriptome analysis was annotated using the clusters of orthologous groups (COG), gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Pfam databases. A search for putative molecular marker was performed to identify simple sequence repeats (SSRs) and single nucleotide polymorphisms (SNPs). In total, 17,927 SSRs and 404,114 SNPs were detected. Finally, we selected sequences that were identified as belonging to the mevalonate (MVA) and 2-C-methyl-D-erythritol 4-phosphate (MEP) pathways, which are involved in rubber biosynthesis, to validate the SNP markers. A total of 78 SNPs were validated in 36 genotypes of H. brasiliensis. This new dataset represents a powerful information source for rubber tree bark genes and will be an important tool for the development of microsatellites and SNP markers for use in future genetic analyses such as genetic linkage mapping, quantitative trait loci identification, investigations of linkage disequilibrium and marker-assisted selection.

Petroleomics By Electrospray Ionization Ft-icr Mass Spectrometry Coupled To Partial Least Squares With Variable Selection Methods: Prediction Of The Total Acid Number Of Crude Oils.

Negative-ion mode electrospray ionization, ESI(-), with Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) was coupled to a Partial Least Squares (PLS) regression and variable selection methods to estimate the total acid number (TAN) of Brazilian crude oil samples. Generally, ESI(-)-FT-ICR mass spectra present a power of resolution of ca. 500,000 and a mass accuracy less than 1 ppm, producing a data matrix containing over 5700 variables per sample. These variables correspond to heteroatom-containing species detected as deprotonated molecules, [M - H](-) ions, which are identified primarily as naphthenic acids, phenols and carbazole analog species. The TAN values for all samples ranged from 0.06 to 3.61 mg of KOH g(-1). To facilitate the spectral interpretation, three methods of variable selection were studied: variable importance in the projection (VIP), interval partial least squares (iPLS) and elimination of uninformative variables (UVE). The UVE method seems to be more appropriate for selecting important variables, reducing the dimension of the variables to 183 and producing a root mean square error of prediction of 0.32 mg of KOH g(-1). By reducing the size of the data, it was possible to relate the selected variables with their corresponding molecular formulas, thus identifying the main chemical species responsible for the TAN values.

Selection And Validation Of Reference Genes For Functional Studies In The Calliphoridae Family.

The genera Cochliomyia and Chrysomya contain both obligate and saprophagous flies, which allows the comparison of different feeding habits between closely related species. Among the different strategies for comparing these habits is the use of qPCR to investigate the expression levels of candidate genes involved in feeding behavior. To ensure an accurate measure of the levels of gene expression, it is necessary to normalize the amount of the target gene with the amount of a reference gene having a stable expression across the compared species. Since there is no universal gene that can be used as a reference in functional studies, candidate genes for qPCR data normalization were selected and validated in three Calliphoridae (Diptera) species, Cochliomyia hominivorax Coquerel, Cochliomyia macellaria Fabricius, and Chrysomya albiceps Wiedemann . The expression stability of six genes ( Actin, Gapdh, Rp49, Rps17, α -tubulin, and GstD1) was evaluated among species within the same life stage and between life stages within each species. The expression levels of Actin, Gapdh, and Rp49 were the most stable among the selected genes. These genes can be used as reliable reference genes for functional studies in Calliphoridae using similar experimental settings.