Mitochondrial DNA sequence analysis from multiple gene fragments reveals genetic heterogeneity of Crassostrea ariakensis in East Asia

The native Asian oyster, Crassostrea ariakensis is one of the most common and important Crassostrea species that occur naturally along the coast of East Asia. Molecular species diagnosis is a prerequisite for population genetic analysis of wild oyster populations because oyster species cannot be discriminated reliably using external morphological characters alone due to character ambiguity. To date there have been few phylogeographic studies of natural edible oyster populations in East Asia, in particular this is true of the common species in Korea C. ariakensis. We therefore assessed the levels and patterns of molecular genetic variation in East Asian wild populations of C. ariakensis from Korea, Japan, and China using DNA sequence analysis of five concatenated mtDNA regions namely; 16S rRNA, cytochrome oxidase I, cytochrome oxidase II, cytochrome oxidase III, and cytochrome b. Two divergent C. ariakensis clades were identified between southern China and remaining sites from the northern region. In addition, hierarchical AMOVA and pairwise UST analyses showed that genetic diversity was discontinuous among wild populations of C. ariakensis in East Asia. Biogeographical and historical sea level changes are discussed as potential factors that may have influenced the genetic heterogeneity of wild C. ariakensis stocks across this region.

Using genetic algorithm in profile-based assignment of applications to virtual machines for greener data centers

The increase in data center dependent services has made energy optimization of data centers one of the most exigent challenges in today's Information Age. The necessity of green and energy-efficient measures is very high for reducing carbon footprint and exorbitant energy costs. However, inefficient application management of data centers results in high energy consumption and low resource utilization efficiency. Unfortunately, in most cases, deploying an energy-efficient application management solution inevitably degrades the resource utilization efficiency of the data centers. To address this problem, a Penalty-based Genetic Algorithm (GA) is presented in this paper to solve a defined profile-based application assignment problem whilst maintaining a trade-off between the power consumption performance and resource utilization performance. Case studies show that the penalty-based GA is highly scalable and provides 16% to 32% better solutions than a greedy algorithm.

A penalty-based genetic algorithm for the migration cost-aware virtual machine placement problem in cloud data centers

In the past few years, the virtual machine (VM) placement problem has been studied intensively and many algorithms for the VM placement problem have been proposed. However, those proposed VM placement algorithms have not been widely used in today's cloud data centers as they do not consider the migration cost from current VM placement to the new optimal VM placement. As a result, the gain from optimizing VM placement may be less than the loss of the migration cost from current VM placement to the new VM placement. To address this issue, this paper presents a penalty-based genetic algorithm (GA) for the VM placement problem that considers the migration cost in addition to the energy-consumption of the new VM placement and the total inter-VM traffic flow in the new VM placement. The GA has been implemented and evaluated by experiments, and the experimental results show that the GA outperforms two well known algorithms for the VM placement problem.

Phylogeographical relationships of Sicilian brown trout and the effects of genetic introgression on morphospace occupation

Genetic introgression of aquaculture stocks in local forms is well documented in many fish species but their evolutionary consequences for the local populations have not been thoroughly explored. Due to its wide geographical range, the existence of many locally adapted forms and the frequent occurrence of introgression of aquaculture stocks in local forms, brown trout represents the ideal system to study the effects of such introgressions. Here, we focus on a group of rivers and streams in Sicily (Italy), and, by using molecular tools, we show that autochthonous populations are probably derived from the Southern Atlantic clade, which is present in the Iberian peninsula and North Africa. Three out of the four studied rivers reveal signs of genetic introgression of domestic stocks. Finally, by using advanced geometric morphometric analyses, we show that genetic introgression produces a higher degree of morphological variability relative to that observed in non-introgressed populations.

Nature and extent of genetic diversity of dengue viruses determined by 454 pyrosequencing

Dengue virus (DENV) populations are characteristically highly diverse. Regular lineage extinction and replacement is an important dynamic DENV feature, and most DENV lineage turnover events are associated with increased incidence of disease. The role of genetic diversity in DENV lineage extinctions is not understood. We investigated the nature and extent of genetic diversity in the envelope (E) gene of DENV serotype 1 representing different lineages histories. A region of the DENV genome spanning the E gene was amplified and sequenced by Roche/454 pyrosequencing. The pyrosequencing results identified distinct sub-populations (haplotypes) for each DENV-1 E gene. A phylogenetic tree was constructed with the consensus DENV-1 E gene nucleotide sequences, and the sequences of each constructed haplotype showed that the haplotypes segregated with the Sanger consensus sequence of the population from which they were drawn. Haplotypes determined through pyrosequencing identified a recombinant DENV genome that could not be identified through Sanger sequencing. Nucleotide level sequence diversities of DENV-1 populations determined from SNP analysis were very low, estimated from 0.009-0.01. There were also no stop codon, frameshift or non-frameshift mutations observed in the E genes of any lineage. No significant correlations between the accumulation of deleterious mutations or increasing genetic diversity and lineage extinction were observed (p>0.5). Although our hypothesis that accumulation of deleterious mutations over time led to the extinction and replacement of DENV lineages was ultimately not supported by the data, our data does highlight the significant technical issues that must be resolved in the way in which population diversity is measured for DENV and other viruses. The results provide an insight into the within-population genetic structure and diversity of DENV-1 populations.

A linear programming approach for estimating the structure of a sparse linear genetic network from transcript profiling data

Background: A genetic network can be represented as a directed graph in which a node corresponds to a gene and a directed edge specifies the direction of influence of one gene on another. The reconstruction of such networks from transcript profiling data remains an important yet challenging endeavor. A transcript profile specifies the abundances of many genes in a biological sample of interest. Prevailing strategies for learning the structure of a genetic network from high-dimensional transcript profiling data assume sparsity and linearity. Many methods consider relatively small directed graphs, inferring graphs with up to a few hundred nodes. This work examines large undirected graphs representations of genetic networks, graphs with many thousands of nodes where an undirected edge between two nodes does not indicate the direction of influence, and the problem of estimating the structure of such a sparse linear genetic network (SLGN) from transcript profiling data. Results: The structure learning task is cast as a sparse linear regression problem which is then posed as a LASSO (l1-constrained fitting) problem and solved finally by formulating a Linear Program (LP). A bound on the Generalization Error of this approach is given in terms of the Leave-One-Out Error. The accuracy and utility of LP-SLGNs is assessed quantitatively and qualitatively using simulated and real data. The Dialogue for Reverse Engineering Assessments and Methods (DREAM) initiative provides gold standard data sets and evaluation metrics that enable and facilitate the comparison of algorithms for deducing the structure of networks. The structures of LP-SLGNs estimated from the INSILICO1, INSILICO2 and INSILICO3 simulated DREAM2 data sets are comparable to those proposed by the first and/or second ranked teams in the DREAM2 competition. The structures of LP-SLGNs estimated from two published Saccharomyces cerevisae cell cycle transcript profiling data sets capture known regulatory associations. In each S. cerevisiae LP-SLGN, the number of nodes with a particular degree follows an approximate power law suggesting that its degree distributions is similar to that observed in real-world networks. Inspection of these LP-SLGNs suggests biological hypotheses amenable to experimental verification. Conclusion: A statistically robust and computationally efficient LP-based method for estimating the topology of a large sparse undirected graph from high-dimensional data yields representations of genetic networks that are biologically plausible and useful abstractions of the structures of real genetic networks. Analysis of the statistical and topological properties of learned LP-SLGNs may have practical value; for example, genes with high random walk betweenness, a measure of the centrality of a node in a graph, are good candidates for intervention studies and hence integrated computational – experimental investigations designed to infer more realistic and sophisticated probabilistic directed graphical model representations of genetic networks. The LP-based solutions of the sparse linear regression problem described here may provide a method for learning the structure of transcription factor networks from transcript profiling and transcription factor binding motif data.

A robust approach to design a single facility layout plan in dynamic manufacturing environments using a permutation-based genetic algorithm

During the past few decades, developing efficient methods to solve dynamic facility layout problems has been focused on significantly by practitioners and researchers. More specifically meta-heuristic algorithms, especially genetic algorithm, have been proven to be increasingly helpful to generate sub-optimal solutions for large-scale dynamic facility layout problems. Nevertheless, the uncertainty of the manufacturing factors in addition to the scale of the layout problem calls for a mixed genetic algorithm–robust approach that could provide a single unlimited layout design. The present research aims to devise a customized permutation-based robust genetic algorithm in dynamic manufacturing environments that is expected to be generating a unique robust layout for all the manufacturing periods. The numerical outcomes of the proposed robust genetic algorithm indicate significant cost improvements compared to the conventional genetic algorithm methods and a selective number of other heuristic and meta-heuristic techniques.

Timing the Emergence of Resistance to Anti-HIV Drugs with Large Genetic Barriers

New antiretroviral drugs that offer large genetic barriers to resistance, such as the recently approved inhibitors of HIV-1 protease, tipranavir and darunavir, present promising weapons to avert the failure of current therapies for HIV infection. Optimal treatment strategies with the new drugs, however, are yet to be established. A key limitation is the poor understanding of the process by which HIV surmounts large genetic barriers to resistance. Extant models of HIV dynamics are predicated on the predominance of deterministic forces underlying the emergence of resistant genomes. In contrast, stochastic forces may dominate, especially when the genetic barrier is large, and delay the emergence of resistant genomes. We develop a mathematical model of HIV dynamics under the influence of an antiretroviral drug to predict the waiting time for the emergence of genomes that carry the requisite mutations to overcome the genetic barrier of the drug. We apply our model to describe the development of resistance to tipranavir in in vitro serial passage experiments. Model predictions of the times of emergence of different mutant genomes with increasing resistance to tipranavir are in quantitative agreement with experiments, indicating that our model captures the dynamics of the development of resistance to antiretroviral drugs accurately. Further, model predictions provide insights into the influence of underlying evolutionary processes such as recombination on the development of resistance, and suggest guidelines for drug design: drugs that offer large genetic barriers to resistance with resistance sites tightly localized on the viral genome and exhibiting positive epistatic interactions maximally inhibit the emergence of resistant genomes.

Understanding invasion history: genetic structure and diversity of two globally invasive plants and implications for their management

Aim: Resolving the origin of invasive plant species is important for understanding the introduction histories of successful invaders and aiding strategies aimed at their management. This study aimed to infer the number and origin(s) of introduction for the globally invasive species, Macfadyena unguis-cati and Jatropha gossypiifolia using molecular data. Location: Native range: Neotropics; Invaded range: North America, Africa, Europe, Asia, Pacific Islands and Australia. Methods: We used chloroplast microsatellites (cpSSRs) to elucidate the origin(s) of introduced populations and calculated the genetic diversity in native and introduced regions. Results: Strong genetic structure was found within the native range of M. unguis-cati, but no genetic structuring was evident in the native range of J. gossypiifolia. Overall, 27 haplotypes were found in the native range of M. unguis-cati. Only four haplotypes were found in the introduced range, with more than 96% of introduced specimens matching a haplotype from Paraguay. In contrast, 15 haplotypes were found in the introduced range of J. gossypiifolia, with all invasive populations, except New Caledonia, comprising multiple haplotypes. Main conclusions: These data show that two invasive plant species from the same native range have had vastly different introduction histories in their non-native ranges. Invasive populations of M. unguis-cati probably came from a single or few independent introductions, whereas most invasive J. gossypiifolia populations arose from multiple introductions or alternatively from a representative sample of genetic diversity from a panmictic native range. As introduced M. unguis-cati populations are dominated by a single haplotype, locally adapted natural enemies should make the best control agents. However, invasive populations of J. gossypiifolia are genetically diverse and the selection of bio-control agents will be considerably more complex.

Revisiting genetic structuring in spotted gums (genus Corymbia section Maculatae) focusing on C. maculata, an early diverged, insular lineage

Species delineation in the spotted gum complex was revisited focusing on Corymbia maculata. This study expands the range of C. maculata analysed with microsatellite markers to include populations from the north of the species range. It supported earlier findings that it is a cohesive genetic entity, well resolved from northern spotted gum taxa, Corymbia citriodora and Corymbia henryi; and inferences that its insularity is due to early lineage divergence and historical isolation. The northern extent of C. maculata sampled, as defined by chloroplast and nuclear genomes predominantly of C. maculata character, was the location of Kiwarrak, south of the Manning River near Taree in New South Wales. Trees from a recognised intergrade zone at the Yarratt locality, around 26 km north of Kiwarrak, also possessed a uniquely C. maculata chloroplast haplotype, but their nuclear genomes were predominantly of northern taxa ancestry. Range expansion of northern taxa leading to southerly gene movement into populations formerly C. maculata, would account for this apparent instance of chloroplast capture. Two subpopulations were identified in C. maculata, a northern population of which the Ourimbah locality was the most southerly studied, and a southern population of which Wingello was the most northerly locality studied. Diminished levels of northern taxa ancestry, i.e. C. citriodora or C. henryi, in individuals from the southern, relative to the northern subpopulation of C. maculata, suggested that secondary contact with northern taxa contributes to its substructure.

Development of type I genetic markers from expressed sequence tags in highly polymorphic species

Expressed sequence tag (EST) databases provide a primary source of nuclear DNA sequences for genetic marker development in non-model organisms. To date, the process has been relatively inefficient for several reasons: - 1) priming site polymorphism in the template leads to inferior or erratic amplification; - 2) introns in the target amplicon are too large and/or numerous to allow effective amplification under standard screening conditions, and; - 3) at least occasionally, a PCR primer straddles an exon–intron junction and is unable to bind to genomic DNA template. The first is only a minor issue for species or strains with low heterozygosity but becomes a significant problem for species with high genomic variation, such as marine organisms with extremely large effective population sizes. Problems arising from unanticipated introns are unavoidable but are most pronounced in intron-rich species, such as vertebrates and lophotrochozoans. We present an approach to marker development in the Pacific oyster Crassostrea gigas, a highly polymorphic and intron-rich species, which minimizes these problems, and should be applicable to other non-model species for which EST databases are available. Placement of PCR primers in the 3′ end of coding sequence and 3′ UTR improved PCR success rate from 51% to 97%. Almost all (37 of 39) markers developed for the Pacific oyster were polymorphic in a small test panel of wild and domesticated oysters.

The study of genetic diversity and population structure of the Korean fleshy shrimp, Fenneropenaeus chinensis, using newly developed microsatellite markers

The fleshy shrimp, Fenneropenaeus chinensis, is the family of Penaeidae and one of the most economically important marine culture species in Korea. However, its genetic characteristics have never been studied. In this study, a total of 240 wild F. chinensis individuals were collected from four locations as follows: Narodo (NRD, n = 60), Beopseongpo (BSP, n = 60), Chaesukpo (CSP, n = 60), and Cheonsuman (CSM, n = 60). Genetic variability and the relationships among four wild F. chinensis populations were analyzed using 13 newly developed microsatellite loci. Relatively high levels of genetic variability (mean allelic richness = 16.87; mean heterozygosity = 0.845) were found among localities. Among the 52 population loci, 13 showed significant deviation from the Hardy–Weinberg equilibrium. Neighbor-joining, principal coordinate, and molecular variance analyses revealed the presence of three subpopulations (NRD, CSM, BSP and CSP), which was consistent with clustering based on genetic distance. The mean observed heterozygosity values of the NRD, CSM, BSP, and CSP populations were 0.724, 0.821, 0.814, and 0.785 over all loci, respectively. These genetic variability and differentiation results of the four wild populations can be applied for future genetic improvement using selective breeding and to design suitable management guidelines for Korean F. chinensis culture.

Engineering the pentose phosphate pathway of Saccharomyces cerevisiae for production of ethanol and xylitol

The baker s yeast Saccharomyces cerevisiae has a long tradition in alcohol production from D-glucose of e.g. starch. However, without genetic modifications it is unable to utilise the 5-carbon sugars D-xylose and L arabinose present in plant biomass. In this study, one key metabolic step of the catabolic D-xylose pathway in recombinant D-xylose-utilising S. cerevisiae strains was studied. This step, carried out by xylulokinase (XK), was shown to be rate-limiting, because overexpression of the xylulokinase-encoding gene XKS1 increased both the specific ethanol production rate and the yield from D xylose. In addition, less of the unwanted side product xylitol was produced. Recombinant D-xylose-utilizing S. cerevisiae strains have been constructed by expressing the genes coding for the first two enzymes of the pathway, D-xylose reductase (XR) and xylitol dehydrogenase (XDH) from the D-xylose-utilising yeast Pichia stipitis. In this study, the ability of endogenous genes of S. cerevisiae to enable D-xylose utilisation was evaluated. Overexpression of the GRE3 gene coding for an unspecific aldose reductase and the ScXYL2 gene coding for a xylitol dehydrogenase homologue enabled growth on D-xylose in aerobic conditions. However, the strain with GRE3 and ScXYL2 had a lower growth rate and accumulated more xylitol compared to the strain with the corresponding enzymes from P. stipitis. Use of the strictly NADPH-dependent Gre3p instead of the P. stipitis XR able to utilise both NADH and NADPH leads to a more severe redox imbalance. In a S. cerevisiae strain not engineered for D-xylose utilisation the presence of D-xylose increased xylitol dehydrogenase activity and the expression of the genes SOR1 or SOR2 coding for sorbitol dehydrogenase. Thus, D-xylose utilisation by S. cerevisiae with activities encoded by ScXYL2 or possibly SOR1 or SOR2, and GRE3 is feasible, but requires efficient redox balance engineering. Compared to D-xylose, D-glucose is a cheap and readily available substrate and thus an attractive alternative for xylitol manufacture. In this study, the pentose phosphate pathway (PPP) of S. cerevisiae was engineered for production of xylitol from D-glucose. Xylitol was formed from D-xylulose 5-phosphate in strains lacking transketolase activity and expressing the gene coding for XDH from P. stipitis. In addition to xylitol, ribitol, D-ribose and D-ribulose were also formed. Deletion of the xylulokinase-encoding gene increased xylitol production, whereas the expression of DOG1 coding for sugar phosphate phosphatase increased ribitol, D-ribose and D-ribulose production. Strains lacking phosphoglucose isomerase (Pgi1p) activity were shown to produce 5 carbon compounds through PPP when DOG1 was overexpressed. Expression of genes encoding glyceraldehyde 3-phosphate dehydrogenase of Bacillus subtilis, GapB, or NAD-dependent glutamate dehydrogenase Gdh2p of S. cerevisiae, altered the cellular redox balance and enhanced growth of pgi1 strains on D glucose, but co-expression with DOG1 reduced growth on higher D-glucose concentrations. Strains lacking both transketolase and phosphoglucose isomerase activities tolerated only low D-glucose concentrations, but the yield of 5-carbon sugars and sugar alcohols on D-glucose was about 50% (w/w).

Mu in vitro transposition applications in protein engineering

Transposons, mobile genetic elements that are ubiquitous in all living organisms have been used as tools in molecular biology for decades. They have the ability to move into discrete DNA locations with no apparent homology to the target site. The utility of transposons as molecular tools is based on their ability to integrate into various DNA sequences efficiently, producing extensive mutant clone libraries that can be used in various molecular biology applications. Bacteriophage Mu is one of the most useful transposons due to its well-characterized and simple in vitro transposition reaction. This study establishes the properties of the Mu in vitro transposition system as a versatile multipurpose tool in molecular biology. In addition, this study describes Mu-based applications for engineering proteins by random insertional transposon mutagenesis in order to study structure-function relationships in proteins. We initially characterized the properties of the minimal Mu in vitro transposition system. We showed that the Mu transposition system works efficiently and accurately and produces insertions into a wide spectrum of target sites in different DNA molecules. Then, we developed a pentapeptide insertion mutagenesis strategy for inserting random five amino acid cassettes into proteins. These protein variants can be used especially for screening important sites for protein-protein interactions. Also, the system may produce temperature-sensitive variants of the protein of interest. Furthermore, we developed an efficient screening system for high-resolution mapping of protein-protein interfaces with the pentapeptide insertion mutagenesis. This was accomplished by combining the mutagenesis with subsequent yeast two-hybrid screening and PCR-based genetic footprinting. This combination allows the analysis of the whole mutant library en masse, without the need for producing or isolating separate mutant clones, and the protein-protein interfaces can be determined at amino acid accuracy. The system was validated by analysing the interacting region of JFC1 with Rab8A, and we show that the interaction is mediated via the JFC1 Slp homology domain. In addition, we developed a procedure for the production of nested sets of N- and C-terminal deletion variants of proteins with the Mu system. These variants are useful in many functional studies of proteins, especially in mapping regions involved in protein-protein interactions. This methodology was validated by analysing the region in yeast Mso1 involved in an interaction with Sec1. The results of this study show that the Mu in vitro transposition system is versatile for various applicational purposes and can efficiently be adapted to random protein engineering applications for functional studies of proteins.

Conservative Design Optimization of Laminated Composite Structures Using Genetic Algorithms and Multiple Failure Criteria

This article analyzes the effect of devising a new failure envelope by the combination of the most commonly used failure criteria for the composite laminates, on the design of composite structures. The failure criteria considered for the study are maximum stress and Tsai-Wu criteria. In addition to these popular phenomenological-based failure criteria, a micromechanics-based failure criterion called failure mechanism-based failure criterion is also considered. The failure envelopes obtained by these failure criteria are superimposed over one another and a new failure envelope is constructed based on the lowest absolute values of the strengths predicted by these failure criteria. Thus, the new failure envelope so obtained is named as most conservative failure envelope. A minimum weight design of composite laminates is performed using genetic algorithms. In addition to this, the effect of stacking sequence on the minimum weight of the laminate is also studied. Results are compared for the different failure envelopes and the conservative design is evaluated, with respect to the designs obtained by using only one failure criteria. The design approach is recommended for structures where composites are the key load-carrying members such as helicopter rotor blades.